The Advanced Educational Modeling Laboratory

A partnership with HOBOS

2012-01-21T12:13:00.010-05:00

Prof. Dr. Jürgen Tautz

We are honored to announce a partnership with the HOney Bee Online Studies (HOBOS) Program, directed by Prof. Dr. Jürgen Tautz at Universität Würzburg, Germany, to promote science education through the application of IR imaging technology. HOBOS uses bees to stimulate students' interest and promote their inquiry skills, including enhancement of the ability to "think critically, integrate and synthesize knowledge, draw conclusions from complex material, understand the natural and physical worlds, grasp the processes by which scientific concepts are developed and modified, develop the mathematical and quantitative skills necessary for calculation, and analytical thought and problem solving." These are exactly our goals on the other side of the pond. We hope this international collaboration will help us integrate our resources to promote these shared visions.

Prof. Tautz is a renown biologist whose work have been widely reported by New York Times, BBC, and so on. HOBOS has been supported by UNESCO and nominated for the 2011 Cleantech Media Award.

Thermal vision is a critical technique in bee research. HOBOS currently provides an online IR camera that allows anyone to observe bees in real time. We envision that this partnership will allow us to jointly explore broader applications of affordable IR imaging (and other applicable technologies) in biology education. We are looking forward to the return of bees, bugs, and other insects in the spring to start this journey!

Simulation fitting of experimental results: A damped pendulum

2012-01-20T10:36:00.006-05:00

The National Science Foundation recently awarded us a new grant to explore the concept of mixed-reality lab (MRL), which we proposed to combine the power of simulations and sensors to provide a new level of integrated learning experience that connects invisible science concepts with natural phenomena.

One of the proposed ways to integrate sensors and simulations is a strategy called "simulation fitting." When scientists observe something in the natural world, they typically build mathematical models to explain their observations. It is through this process that scientists make sense of their findings, understand the mechanisms more deeply, and derive new ideas for further investigations.

This is also an essential cycle of scientific inquiry we would like students to learn. The MRL project will explore how this "simulation fitting" strategy can improve science learning.

An example we have looked at is a simple pendulum. A swinging pendulum will eventually stop because of damping, which comes from two different sources: air resistance and bearing friction. Air resistance depends on the velocity of the pendulum whereas bearing friction doesn't.

My colleague Ed Hazzard has done a neat experiment that shows the difference of the two damping effects. His pendulum, under the normal circumstance, loses very little energy and can swing for a long time. To slow it down quickly, he attached a piece of paper to create a "sail," thus dramatically increasing the air drag. The result from a rotatory sensor shows the decaying of the rotational angle of the pendulum. In this case, the envelope of the curve looks like an exponential function (see the first image).

Launch the simulation.

Removing the "sail" and inserting some cotton into the bearing to increase the dry friction, he was able to amplify the effect of the dry friction. This time, the result of the rotational angle shows an envelope of a straight line, instead of an exponential curve (see the second image--it had two runs).

To understand these effects, we have created simulations that fit exactly the behaviors (see the third image). These simple simulations are based on solving Newton's equation of motion, with the only difference in the damping force: In one case it is proportional to the velocity; in the other case it is constant.

Our next step is to explore how to translate what we have done into a learning activity.

The world's first website for IR imaging experiments launched

2012-01-19T16:57:00.003-05:00

We have launched the world's first website dedicated to IR imaging experiments for science and engineering education: http://energy.concord.org/ir.

This website publishes the experiments I have designed to showcase IR visualizations of natural phenomena. Each experiment comes with an illustration of the setup and a short IR video recorded from the experiment. Dozens of IR videos will be produced and added to the website as we move along. Teachers and students may use these YouTube videos without purchasing IR cameras (the price for the basic versions of which have come under $900 in the United States).

Among other things, we are developing a unique approach that uses affordable handheld IR cameras to visualize unseen energy transfer processes occurring in easy-to-do science experiments. Using this approach, thermal energy can be readily visualized through an IR camera. Other types of energy that convert into thermal energy can be inferred from thermal energy visualizations. This allows many invisible physical, chemical, and biological processes that absorb or release heat to be discovered and investigated.

By lowering the technical barrier to authentic scientific inquiry and presenting compelling visualizations of energy flows and transformations in everyday life, the tool will enable more students in diverse schools to develop a deeper understanding of energy concepts and their broad applications.

Soft body dynamics in the Molecular Workbench

2011-11-18T21:08:00.011-05:00

For a long time, some of my colleagues joked about my work on the Molecular Workbench as some trick to randomize "bouncing balls in a box." Part of their impressions came from the overly demonstrated gas simulations that are conveniently linked to some widely taught physical science concepts.

To do justice to the Molecular Workbench, I intend to write a series of blog posts that show the unknown facts about what it is capable of doing. This series is not to defend the work I have done. It is more about digging the potential of computational science and see what favor it can do for science education.

My plain answer to my colleagues' comment is that: "It is something in a box, but not just bouncing balls." One of the things it does more than bouncing balls is its capacity in soft body dynamics.

Soft body dynamics is a subject that focuses on visually realistic physical simulations of the motion of soft bodies (or deformable objects). Why is "soft body" important? The answer is that most biological systems are soft--at the macroscopic level or at the microscopic level. Without the biomechanical flexibility of human body, we would be quite different.Without the biomolecular flexibility of cells, there probably would not be life (e.g., it would not be possible for molecules to move in and out cells).

In many cases when we model microscopic interactions, we don't really need to know how every atom in the system is doing, not only because tracking every single atom in a huge biomolecule is nearly impossible but also it is not necessary to know those details for a basic understanding. Scientists often need to simplify a complex system in order to be able to focus on important aspects. The need is even more so in teaching--the cognitive load for students should be minimized in order to effectively convey the conceptual picture in a short time.

So an interesting question is how flexible biological objects can be simulated in a meaningful way. One approach is to model a soft body as a network of particles connected by elastic constraints (linear, angular, or torsional). This is often known as the mass-spring model in the computer graphics community. In the case of a 2D model, these discrete particles are placed along the edge of a 2D object. In the case of a 3D model, these particles are placed on the surface mesh of a 3D object. Physical interactions among soft bodies are then made possible by giving these particles properties such as a stiff repulsive core, an attractive force, or an electric charge. This allows many interesting phenomena to be modeled, such as self-assembly, docking, and so on.

The above animation shows a box with bouncing balls and swimming "worms," produced by the Molecular Workbench. Does the dynamics of these long soft bodies show some kind of "wormy" behavior that is clearly not that of bouncy balls?

In fact, the mass-spring model implemented in the Molecular Workbench has a number of applications in artificial life ranging from digital fish to digital cells. See this page for a nice summary.

Rainbow, iron, and gray

2011-11-15T10:11:00.003-05:00

Energy2D is our signature software for simulating invisible energy flow in natural and man-made systems. One of its view shows the temperature distribution calculated by the physics engine. This view renders images similar to what an infrared camera shows. Most IR cameras have a few color palettes for the user to choose. So I think we should provide those options in Energy2D, too.

This blog post shows the three color palettes commonly used in IR imagery that were implemented in Energy2D: rainbow, iron, and gray. I guess the IR folks call the second one "iron" because it looks like the color of an iron bar heated to glow.

A criticism of using colorful heat maps to visualize distributions is the possibility of twisting data and therefore creating illusions--because our perception of color does not go linearly with the linear increase of the RGB values. You can compare these three images and see if that is a problem.

I have blogged a lot about how great an inquiry tool IR imaging represents. The resemblance of Energy2D's temperature patterns to IR images indicates a learning possibility of using simulations to deliver some of the nice features that an IR camera gives--before the prices of IR cameras come down to a couple of hundred dollars.

If you would like to show how they look in real simulations, go to Energy2D's home page and explore from there.

"Heart"-shape house? "Seastar"-shape house?

2011-11-10T20:23:00.007-05:00

In just a few hours, two students were capable of designing ten houses using our Energy3D software, about which they had no prior experience at all. Among them there is one with a floor plan of the shape of a heart and another the shape of a sea star.

We were excited about the ease of use of Energy3D for designing complex houses. However, there are a few concerns. First, these two houses have complicated shapes that take a long time to scale up on cardstock and assemble from the cutout pieces. With a powerful CAD tool like this, students' creativity can be unleashed--they are capable of coming up with sophisticated designs. But computer models are not the final destinations. They are thinking and visualization tools that help students conceptualize their designs. Our goal in engineering projects is to have them make real systems after computer models. If a computer model is too complex, students may not be able to make the real system within a given amount of time in the classroom. On the other hand, if a computer model is inflexible and few variations are feasible, students will quickly be bored. It may be a bad idea to limit the design capacity to simple models with only a handful of features and options. So where is the balance point?

Another thing we should watch out is that students who are too focused on designing the fancy shapes like these may pay less attention to the science and engineering principles we hope to teach in this engineering design challenge--we want them to think about designs that can achieve maximum livability and be energy-efficient. What kind of intelligence can we build into our CAD tool to provide just-in-time instructions that guide their designs?

Swedish newspaper reported IR research with pupils

2011-09-30T10:59:00.006-04:00

Swedish newspaper Norrköpings Tidningar reported today our international collaboration with Konrad Schönborn and Jesper Haglund at Linköping University on educational research that is aimed at uncovering the cognitive power of IR imaging for science education. If you don't understand Swedish, the title translates into “The heat camera can become important in school physics.” Jenny Sajjadi, a teacher in math and physics, was quoted as saying: “Physics is seen as an ‘old’ subject and this is a bit of new thinking that can increase the students’ interest. For me as a teacher, it is an entrance to deeper teaching.”

Modern handheld IR cameras deliver tremendous power equivalent to thousands of temperature sensors. This kind of Very Large Scale Integrated Sensing System (VLSISS, my coinage in parallel to VLSI circuits that have revolutionized computing) is about to change the landscape of scientific inquiry in the classroom. It opens up learning opportunities that have never been seen before. This US-Sweden collaboration will advance this agenda. As the first step, the collaborative project will provide some pivotal data for how augmented visualization (to the sense of touch) could be a good intervention to notoriously hardy misconceptions related to heat and temperature. See my earlier blog post about this.

An online gas lab simulation

2011-09-27T10:47:00.002-04:00

Go to simulation.

You probably know the Ideal Gas Law well. An ideal gas is a hypothetical gas made of randomly moving particles that do not have a volume and do not interact with one another. Have your students ever asked questions such as "What about non-ideal gases? How good is the Ideal Gas Law for real gases?" I don't know about other people's experience, but I myself was intrigued by those questions when I learned the gas laws. Unfortunately, I couldn't go too deeply in trying to answer them because just thinking about the complexity of the motion and interaction quickly intimidated me.

Before computer simulation was widely accessible, you probably would have to pull out the Van der Waals Equation and pray that doing the math would do the trick.

Now, there is a good way to teach this. Using an online molecular dynamics simulation--made using the Molecular Workbench software, investigating non-ideal gases is a piece of cake. This simulation uses a pair of gas containers side by side and allows the user to explore how six variables affect the volume of a gas: temperature, pressure, number of particles, particle mass, particle size, and particle attraction. It basically covers all the variables in the Van der Waals equation--without saying them explicitly. And there is a variable that is not included in the Van der Waals equation. The simulation reveals exactly why it is not there.

An online simulation for studying states of matter

2011-09-24T08:28:00.002-04:00

Go to the simulation

Have you wondered why some light elements form solids at room temperature whereas some heavy elements form liquids (e.g., mercury) or gases (e.g., radon) at room temperature? Many people tend to associate "heavy" with "solid." But that is not true.

Using an online 3D molecular dynamics simulation--made using the Molecular Workbench software, you can investigate if or how atomic mass, atomic size, interatomic attraction, and temperature affect the formation of a phase. This investigation allows for deeper exploration about what determines a phase.

Java is required to run this simulation in your browser.

Designing solar hot air collectors

2011-09-01T22:18:00.013-04:00

Engineering design is a lot of fun. The variety of engineering systems students can realistically design and build in classrooms is, however, limited by the constraints of time, resources, and student preparedness.

Currently, construction toys and computer programming are perhaps the most frequently adopted student projects for learning engineering design. These applications cover a number of domains such as robotics and software engineering.

In our Engineering Energy Efficiency project, we have been working on adding a new option of engineering project that students and teachers can choose to learn and teach engineering.

This Green Building Kit we are developing needs only paper, cardstock, foam board, among other typical office supplies and widely available sensors. Yet, it will allow students to design, build, and test energy-efficient model houses with considerable green features.

An example I am working on is a hot air collector (HAC, also known as the Trombe wall). This is actually very easy to construct (hence a popular DIY project for those who are "green"-minded and handy). It is not difficult for students to add an HAC unit to the sun-facing wall of a model house.

In order for students to have fun with this design challenge, we need to show them that there are a variety of things that they can learn, emulate, test, and invent.

HAC units are usually installed to the part of the sun-facing wall that is not occupied by windows. Windows are necessary to a house because they let light in, but they generally lose more heat than an insulated wall. An insulated wall keeps the heat inside the house, but it does not do anything to collect the heat from the sun and give it to the house. The idea of hot air collector is to use the surface area of the wall that is exposed to the sun to collect some solar energy for warming up the house.

If you think about this engineering design task, it is really a problem about the optimal use of the sun-facing wall surface. So where should we put windows and HAC units and what is the best way of using them? The above images show a variety of designs. Click each image to enlarge it and see the details of each design.

The fourth design combines the benefits of windows and HAC units. It is basically a large HAC unit with the middle part replaced by a window. On the one hand, sunlight still can shine into the house through the two layers of glazing (we automatically have a double-pane window). On the other hand, as the HAC unit is tall, the convective heat exchange between the HAC unit and the room will be more significant. I haven't seen an HAC design like this, so this is my little "invention." Well, I am pretty sure some guy has thought of this before and there is probably a pending patent for this, but never mind about this, I am just demonstrating how an engineering design process in the classroom could be made more inventive.

Our next step is to make it possible for students to add these green architectural elements (HAC is just one of them) in one of our flagship products: Energy3D. Energy3D already has a powerful heliodon for solar design.

The Physics Teacher Magazine features IR article

2011-08-25T07:54:00.002-04:00

The Physics Teacher Magazine published by the American Association of Physics Teachers (AAPT) selected our article "Infrared Imaging for Inquiry-Based Learning" as a featured article on the September 2011 issue. A featured article is made free to the public. Each issue chooses three featured articles.

In this paper, we described a series of IR experiments that can be readily used to teach the basic concepts of heat transfer and their applications to engineering.

Students enjoyed Energy3D in Engineering Energy Efficiency Summer School 2011

2011-08-23T16:26:00.010-04:00

Click to enlarge

This week 11 students of different ages (10-17) participated in our three-day summer school for the Engineering Energy Efficiency project. They were charged with using Energy3D to design their own model houses on a computer first and then construct them using inexpensive materials.

Although Energy3D is still in its alpha phase, it seemed to work remarkably well for these students who used the Mac computers we provided (thanks to Dr. Saeid Nourian, the lead developer of the software). Despite of some glitches, the students easily designed their own computer models. Creating the roof, the hardest part using other programs such as SketchUp, has been greatly simplified in Energy3D.

Interestingly, of the five groups, none used the template houses we provided to help them get started, indicating the fact that the students actually preferred designing their very own houses from scratch.

Strange thermal conductivity of leaves?

2011-08-03T15:02:00.034-04:00

One way to tell if a plant is a plastic fake or not is to touch a leaf. If it feels cool, the plant is a real one. Have you ever wondered why a leaf feels cool? (A leaf of an indoor plant always rests at about the room temperature, plastic or real. It is not really cooler before you touch it. You can confirm this by measuring its temperature using a sensitive temperature sensor.)

We know metals feel cold because they conduct heat fast. Within a given amount of time, our fingers lose more thermal energy to a piece of metal than to a piece of wood.

Do leaves also conduct heat fast? On the contrary.

Let's put a fresh leaf on top of a piece of dry paper. The first set of IR images in this post shows what happened after I used two fingers to touch the leaf (on the left) and the paper to warm them up. The result tells that the leaf actually conducted heat more slowly than the paper, which has much lower thermal conductivity than metals.

Source: Wikipedia.

Now, we have a problem. We know leaves feel cooler than paper. But leaves conduct heat more slowly than paper! Our sense of touch honestly tells us that our fingers lose more thermal energy to leaves than to paper. So where does the thermal energy go on a leaf, if it doesn't diffuse to other parts?

My theory is that the thermal energy goes to heat up the water in the spongy layer of the leaf. The spongy layer lies beneath the palisade layer--the waxy surface layer of the leaf. Its cells are irregular in shape and loosely packed--hence the name "the spongy layer." During transpiration, the spongy layer is full of water in the spaces before they exit stoma. The specific heat of water is considerably high--4.18 J/(g*K) and the spongy layer is filled with water.

My theory is backed by the fact that a dry leaf conducts heat as fast as paper (IR images not shown here). This should not surprise you as paper is made of dehydrated wood fibers.

Now, the question is why the water in the spongy layer doesn't dissipate thermal energy quickly as water in a cup does (I confirmed the energy dissipation in water by IR imaging, which is not shown here). The thermal conductivity of liquid water is about 0.58 W/(m*K), compared with 0.024 W/(m*K) for air, 0.016 W/(m*K) for water vapor, and 0.05 W/(m*K) for paper. Somehow, the water trapped in the spongy layer cannot conduct heat like free water does.

Let's get get a wet (20% of full water absorption capacity) sponge (left) and a dry one (right) and look at their thermal conductivities under an IR camera. Again, I used my fingers to leave a heat mark on each. The second set of IR images shows a surprising result: the wet sponge appeared to conduct heat more slowly than the dry one!

Does this thermal conductivity protect plants' leaves? Have you wondered why some plants are anti-freezing and some are not? Leaves may have very complicated thermal regulation that we don't quite understand.

The thermogenesis of a moth

2011-07-28T10:33:00.034-04:00

Is a moth warm-blooded or cold-blooded? If you google this, some would tell you it is cold-blooded. They are not completely right. This infrared study shows how a moth warms up before it flies. So at least a moth is warm-blooded when it moves.

Click to view a larger image

The moth (see the close-up photo above--what species is it?) was kept in a jar. The first IR image shows that when it was idle (sleeping?), its body temperature agreed with the ambient temperature. This means that it does not lose heat to the environment--a clever way for saving energy.

However, before making a move, it needs to heat up its flight muscles (near its head where the wings are attached) to above 30 degrees Celsius. In this observation, the warming process took 1-2 minutes for the moth in our experiment, as is shown by the sequence of the IR images. (Note: You may only observe this effect when the moth is energetic. A moth on the verge of death does not have enough energy to warm up.)

Note that we used the automatic color remapping, i.e., the heat map is rescaled based on the lowest and highest temperatures detected in the view. As a result, while the moth warmed up and appeared redder in the IR view, the background--in contrast--became bluer in the IR view. This, however, does not mean that the temperature of the background has decreased. The automatic remapping could create some confusion, but it is necessary in many cases, especially when you don't know what to expect. It maximizes the difference by increasing the contrast and, therefore, allows the observer to pick up small changes.

The last image shows that the temperature was ready and the moth started to move. In this particular experiment, the moth responded slowly because it could have been exhausted as it had struggled quite a bit before it was imaged.

What interests me in this experiment is thermogenesis: the process of heat production in organisms. What biochemical reactions are responsible for the thermogenesis in moths and bees? Can we learn from them to find a green way to heat our homes?

Design your own house with Energy3D

2011-07-26T16:43:00.015-04:00

Energy3D is a free, open-source tool we are developing from scratch to empower students to design, make, and test energy-efficient model houses.

Today we had some students design and make their own houses. One student succeeded in designing a model house after her own real house. The first two screenshots show her model under the sun in different months.

Like many architecture design tools, students can "walk" into their own design and imagine "living in the house" virtually. The other two screenshots show two close-ups: one from the outside and the other from the inside. The fifth image is a physical house made of foam board and assembled, based on this design.

If they are satisfied with their designs, students can "print" out their houses, cut out all the pieces, and assemble them.

We feel that computer-aided design tools such as Energy3D would be a big help to students when they are undertaking complicated engineering design challenges such as making a house. 3D reasoning is usually difficult for most students. A What-You-See-Is-What-You-Get (WYSIWYG) CAD tool can help them think through.

You may be wondering why we want to develop this tool. Many students complain that their science and engineering projects in schools are not challenging enough to be interesting. Many teachers do strive to make their student projects more attractive. However, they lack appropriate educational tools to do so. Energy3D is an attempt to provide teachers and students with cutting-edge tools that can teach and learn modern full-cycle engineering processes--from design to manufacturing to test-- through an interesting project about energy-efficient houses. We hope this tool would intrigue, inspire, and prepare students for STEM careers.

PS on 7/28: This is another building designed by the same student, which shows an intersecting roof. These examples show that Energy3D could be used to design quite a variety of architecture. It turns out that roof is the most difficult part to design using tools such as Google's SketchUp. We are trying to simplify that part by figuring out algorithms that would enable easy editing of roofs. Our work focuses on two directions. First, an algorithm is needed to automatically generate a roof of a given type based on the boundary walls the user has laid. Second, the topological transformations between different types of roofs need to be identified so that we can build the user interface for adjusting the roof easily.

An infrared view of bees

2011-07-25T08:08:00.014-04:00

A bumble bee.

I have been wanting to see what I can do with IR imaging in my backyard. Folks at the Discovery and Animal Planet channels use IR imaging regularly to show thermal patterns of animals and plants. So I guess I could do something with it. I cannot afford a high-definition IR camera. But I think my low-grade IR camera should be able to catch something. Here is an interesting story about bees.

Bees are warm-blooded insects. In order to fly, bees must heat up their flight muscles to above 30^oC. So let's check this using an IR camera.

Indeed, a bee looks warm through the IR camera. To be more specific, the thorax of a bee appears to be warmer than the rest of its body (see the IR image to the right). I observed both a honey bee and a bumble bee. Both types have a warmer thorax, where the flight muscles are located. Exactly why the muscles can operate only at a warm temperature is an interesting question.

Bees are known to form societies that depend on successful division of work. Researchers have been using high-definition IR imaging to study bee behavior. With the assistance of IR imaging, German researchers led by Prof. Dr. Jürgen Tautz at Würzburg University found a new type of role known as the heater bees. The heater bees are responsible for maintaining the temperature in the hive where young bees (pupae) grow in sealed wax cells. The bees purposely leave some empty cells among those pupa cells so that the heater bees can crawl into them to warm up the pupae. By varying the temperature of each pupa they can determine what kind of bee it will become. As a result, the heater bees are vital in determining what job a young bee will perform once it matures. In the IR video, heater bees' thoraxes also appeared to be warmer, agreeing with what I observed using my IR camera for a worker bee.

Another article published in Optics Express discussed using IR imaging to evaluate beehive population. The idea is based on the assumption that the more bees in a hive, the warmer it would be. An unhealthy colony that has lost population would appear colder in the IR view, as the number of heater bees might have died down because of the lack of worker bees and hence the food they bring back. And if there are not enough heater bees, the pupae would not grow up normally, worsening the situation.

If you don't want to disturb bees and get stung by them, the non-touch, non-invasive IR imaging is probably the best way to go. :-)

PS on 8/3/2011:

Other flying insects like flies, dragonflies, cicadas, and wasps have a similar thermogram (i.e., warm thorax while active). See these two additional images. Or see this blog post about a moth.

I didn't observe warming in ants. They probably don't produce heat. Or they could be just too small to emit any appreciable IR radiation.

Use a garden nozzle to create a rainbow

2011-07-24T17:31:00.009-04:00

You don't have to wait until it rains to catch a sight of rainbow. You can create one any time as long as there is sunshine. Just use a garden nozzle to create a mist and you will see a rainbow.

Theo Jansen's mechanism

2011-07-24T11:10:00.001-04:00

Go to the simulation

Theo Jansen is a Dutch artist and kinetic sculptor who builds large works that resemble skeletons of animals that are able to walk using the wind on the beach. His works are a fusion of art and engineering.

Theo Jansen's famous mechanism can be simulated by using the Molecular Workbench software. Shown in this blog post is a screenshot of the simulation. You can click the link below the screenshot to watch the simulation.

Water permeation across paper and colors under the sun

2011-07-22T07:54:00.008-04:00

Yesterday I reported evidence of tiny water permeation across a piece of paper on top of a cup of water. In order to double-check my theory, I placed a piece of transparency film on top of another cup of water and left the two cups overnight. When I came back this morning, I removed the paper and the film from the two cups and viewed the IR image of the two cups of water. To the right is the image I saw.

The cup of water that had paper atop was cooler (the dark circle on the right) than the cup of water that had transparency film atop (the light gray circle on the left). This means evaporation was stopped by the film but not the paper. The only explanation of this effect is that water can permeate through the paper but not the film.

Last October, I blogged about visualizing different colors' ability to absorb light. In that experiment, I used a table lamp as the light source. Later, I realized a flaw in that experiment because a table lamp is, after all, a point source. For the color bars to have equal illumination, we need a light source that is far far way. The sun is such a light source. So I brought the color plate outside and put it under the sun. You can now have a better idea of which color is more capable of absorbing heat. No doubt black won. To my surprise, purple and yellow have approximately the same light absorptivity. So do blue and green. Red, on the other hand, absorbed about the same amount of light as light gray. The background is white. It absorbed the least amount of light energy and appeared to be bluest in the IR image. Amazingly, paper doesn't conduct heat well, otherwise the color bars in the IR image would not have been so well separated.

Seeing permeation of water molecules

2011-07-21T10:52:00.010-04:00

I have blogged about some intriguing IR images when a piece of paper is placed on top of a cup of water. The part of paper above the water warms up (Figure 1) because of the release of latent heat of condensation of water vapor to its underside. If you want to reproduce this effect, note that the shallow the cup, the more pronounced the effect (I used a lid and turned it over to use as a shallow cup). In these IR images, I chose the gray coloring mode. So white represents the hottest and black the coldest.

The warming stops after a minute because the condensate layer reaches the maximal thickness due to the dynamic equilibrium of condensation and evaporation. So we see there is no difference of temperature across the paper any more (see Figure 2). (Well, except for the ring area that touches the edge of the cup, in which it gets the temperature of the cup.)

If we leave the paper for a couple more minutes, the part of paper actually becomes cooler (Figure 3). So what is going on?

My theory is that water molecules have percolated through the paper, which is porous (having a lot of small holes), to the other side and evaporate from there. So we are seeing the evaporative cooling effect from the above side of the paper. Figure 4 presents evidence that supports this theory. If we shift the paper a little bit, we will see three zones with three different temperatures. The coolest zone shows the effect of evaporative cooling from both sides. The overlap zone shows the effect of evaporative cooling from only the above side. And the warmest zone shows the effect of condensation heating from the underside. (Is this pattern beautiful?!)

Figure 5 shows the comparison between direct evaporation (the dark area on the left) and permeation-then-evaporation (the less dark area on the right). The result indicates that the paper did impede evaporation, even though its micro pores allow water to percolate through.

This follow-up study shows that even a humble experiment like placing a piece of paper atop water has many surprises that reveal the richness of science, which all become transparent under an IR camera. I will blog more surprises derived from this experiment later.

A theory of multisensory learning for IR visualization of hands-on experiments

2011-07-01T03:17:00.008-04:00

I have been "shopping" for a learning theory that can frame the value added by IR visualization to hands-on experiments. Here is a candidate theory.

There are four learning pathways to the brain: visual, auditory, kinesthetic, and tactile. Theory has it that memory and learning could be enhanced if multiple learning pathways are utilized simultaneously.

Let's look at a notorious misconception in heat and temperature. Many people believe that metals are colder than wood or paper. This misconception cannot be easily dispelled because that is how they feel through the sense of touch. As heat transfer is invisible, the tactile experience is all they have.

Now, what if the heat transfer process can be visualized? In other words, what if students have multisensory learning experience: they feel and see it at the same time? IR imaging has enabled us to design such an experiment. The image above shows an IR view that compares heat flow through paper and metal from hands.

Recent studies from Swedish scholars including Konrad J. Schönborn, whom I ran into at a conference and who was enticed by my IR magic, showed that adding haptics to visualization could improve student learning of biomolecular interactions such as docking. Visual and tactile sensorimotor interactions could enhance the cognitive process. Or, in this case, the visualization could "correct" the erroneous idea tangibly gained. The IR visualization shows that the metal is actually warmer than the paper, creating a contradiction with the tactile input that students must reconcile.

Konrad said he would investigate this through a cognitive experiment with students from his University in Sweden. I was psyched. This is complementary to what he has done. In this case, visualization augments touch--exactly opposite to his prior research on molecular binding in which case haptics augments visualization.

The Molecular Workbench wins a SPORE Award from the Science Magazine

2011-06-23T14:18:00.004-04:00

The Science Magazine announced that the Molecular Workbench software has won a SPORE Award. The Science Prize for Online Resources in Education (SPORE) has been established by the American Association for the Advancement of Science to "encourage innovation and excellence in education, as well as to encourage the use of high-quality on-line resources by students, teachers, and the public."

Read our essay published in the Science Magazine.

Here is the AAAS announcement.

Journal of Chemical Education features IR work

2011-06-14T08:18:00.002-04:00

The Journal of Chemical Education, published by the American Chemical Society, selects my paper "Visualizing Chemistry with Infrared Imaging" as the cover article on the July 2011 issue. The IR experiments presented in the paper were described as "captivating, intriguing, and thought-provoking."

Scientists have long relied on powerful imaging techniques to
see things invisible to the naked eye and thus advance
science. IR imaging is one of the few scientific imaging tools that can be easily used by anyone without complicated setup and calibration. And the price for an affordable IR camera has recently fallen below $900. This is a truly transformative tool that will empower students to learn and discover deep science from everyday life. I have shown many examples in this blog.

Every time I did some experiments with this wonderful tool, there was always something that surprised me. Even a humble leaf from a plant in my office shows a lot of things I don't really have a clue (I will blog more about biological applications later). Being a scientist, I intuitively feel that some of the surprises are not simple at all. Behind them there is very deep science that might have never been discovered before. It is a lot of fun to "crack" the scientific secrets in these surprises.

I hope every student would have the same opportunity to have fun with science as I have. Discovery should be an important part of science in schools.

Infrared illusions

2011-06-10T22:36:00.014-04:00

Infrared (IR) thermography is increasingly used to carry out home energy inspection. In theory, it can be used to identify energy leaks by looking at the temperature distribution on the building envelope.

In practice, however, it can be tricky. One of the problems that IR users commonly encounter is optical illusion. After all, what an IR camera detects is IR radiations, which is light. So we are subject to the rules of optics.

To illustrate my point, I took a few IR images of my house at around 9pm at this windless summer night. I looked at a closed window from two different angles and my IR images show that at one angle, the upper pane of the window appeared to be cooler than the lower pane (Figure 1). When I saw this, I knew this was hardly possible, because it was against natural convection--there is no way that the upper pane of the window would be cooler than the lower pane in a house that wasn't being heated or cooled.

Looking at the window from another angle, there was almost no temperature difference (Figure 2). Notice that from both angles, the ridge vent looked pretty hot, of course, after heating by the sun the whole summer day.

So what is it?

This IR illusion is caused by the glass of the window. Glass not only emits IR radiations but also reflects them. Figure 3 shows the reflection of my body radiation superposed to the IR emission of a glass door.

So what did the upper pane of the window appear cooler from the first angle? This is because at that angle, it happened to reflect the night sky. And the night sky is seen by an IR camera to be very cold (below 0°C; explaining this needs another blog article). This reflection was added to the IR emission of the upper pane and caused it to look cooler than it should be.

The lesson learned from this example is that you have to know a lot of science in order not to be deceived by what you see through an IR camera. An IR camera is a powerful tool only in the hand of a person with the knowledge to interpret the image correctly. Having an IR camera sounds snazzy, but it does not necessarily mean you are spared from learning what it can do and cannot do or when and where it can fool you. To some extent, the business of IR thermography is not unlike the business of a detective.

Molecular simulation of self-assembly

2011-06-04T22:47:00.006-04:00

Molecular self-assembly is the process by which molecules adopt a defined arrangement without guidance or management from an outside source. This is one of the ways Mother Nature makes biomolecules that support life. For example, the amino acids of a protein self-assembles themselves and fold into a conformation determined primarily by its primary structure (the sequence of amino acids). It has inspired scientists to invent nanotechnology that is based on self-assembly.

Ab initio simulations of self-assembly involve many atoms and take a long time to run. For intermolecular self-assembly, most of the time the molecules' internal chemical structures do not change much. The Molecular Workbench has a coarse-grained model that simulates the soft, sticky character of the molecular surfaces, which is the most important factor during self-assembly. With this model, we have created a sequence of simulations for teaching the concept of self-assembly (see the images for an example). These simulations have been well-received and used in many classrooms as an introduction to nanotechnology.

You can explore these simulations with this applet.

Several of these simulations were used by a research scientist, Dr. Frank Balzer at NanoSYD of the University of Southern Denmark, in his presentation to illustrate the principles for nanofabrication laboratory experiments.

FLIR infrared cameras now priced below $900 for educational use!

2011-05-31T21:45:00.008-04:00

I just got a quote from a FLIR sale representative that they now offer 25% educational discount for their products. This means for an I3 camera that is listed as $1,195, the educational price is now $896.25. For an I5 camera, the educational price is now $1196.25.

These prices may be even lower if a school purchases ten cameras, or perhaps through a Groupon deal? :-) Given the power of IR imaging, it seems to me that IR cameras now have higher cost effectiveness compared with sensors, which cost $50-100 each (already discounted prices from major vendors such as Vernier and Pasco). Note that an I3 camera can be considered as 3,600 temperature sensors bundled in just one camera. And the measurement is reduced to a camera shot, saving all the work needed to connect the dots and color-map them.

The educational potential of IR imaging stems from two aspects: First, its usefulness has been demonstrated by many commercial applications. Second, it is a tool that greatly literates students from laborious, tedious data acquisition work and allows them to focus on science concepts.

A virtual heliodon from Energy3D

2011-05-24T21:46:00.007-04:00

The virtual heliodon of Energy3D
in action.

According to Wikipedia, "a heliodon is a device for adjusting the angle between a flat surface and a beam of light to match the angle between a horizontal plane at a specific latitude and the solar beam. Heliodons are used primarily by architects and students of architecture. By placing a model building on the heliodon’s flat surface and making adjustments to the light/surface angle, the investigator can see how the building would look in the three dimensional solar beam at various dates and times of day."

Nowadays, few architects would construct a model building and put it under a heliodon. Computer software can do a far better job in simulating the physical situations than electric light of a mechanical heliodon. A number of companies have developed virtual heliodons for daylighting design. Some of these are part of integrated CAD systems such as Autodesk's Ecotect, which are quite pricy. Now, there is a free version we just developed, which is equally good. Even better, it runs on the Web as a Java applet. And it comes with a design studio for you to create your own buildings. Imagine designing your houses online and use the virtual heliodon to check how the sun shines on them at different days and times at different locations.

You can try our heliodon applet out at this URL. Unfortunately, this applet only works on Windows at this point.

ACS-Hach High School Chemistry Grants for infrared cameras?

2011-05-23T08:57:00.012-04:00

As the 18th century British chemist Sir Humphry Davy put it, “nothing tends so much to the advancement of knowledge as the application of a new instrument.” True for infrared imaging, especially when it is used as an educational tool to advance students' science knowledge with first-hand experiences.

Erica K. Jacobsen, an Associate Editor of the Journal of Chemical Education (JCE), had an interesting idea about where to get funds to buy an infrared camera.

Interested in my work recently published on JCE online, she wrote in the editorial of the July 2011 issue of Journal of Chemical Education: "Xie's article Visualizing Chemistry with Infrared Imaging describes the use of infrared (IR) cameras for inquiry-based experiments. The cost is still somewhat prohibitive ($1,500-2,500), but Xie states that the price continues to drop. He provides several experiments that allow students to 'see' phenomena such as evaporation, condensation, and latent heat, heat of solution, and vapor pressure lowering. The IR images of the experiments are captivating, intriguing, and thought provoking. What if a summer science course were to offer an experience with IR cameras and such real-world processes as illustrated in this article? Or, perhaps a high school educator might find this a useful focus for an application for one of next year's ACS-Hach High School Chemistry Grants."

True to form, infrared cameras are becoming more affordable. For $1,195, you can now buy a brand new FLIR I3 (60x60 pixels) from Amazon. If you want to try one and happen to be in Massachusetts, rent one from Home Depot! The price of an I3 may fall below $1,000 next year, or an educational discount will make it do so.

The ACS-Hach High School Chemistry Grants provide up to $1,500 for teachers "seeking funds to support ideas that transform classroom learning, foster student development, and reveal the wonders of chemistry." Each year, ACS awards a few dozens grants. If you are interested in applying for one based on the infrared imaging idea and need some help, please do not hesitate to contact me.

I will showcase this technology at the 2011 Gordon Conference for Chemistry Education and the 2011 Gordon Conference for Visualization in Science and Education. Hope to see you there!

Disclaimer: Although I was probably responsible for the purchase of 10+ IR cameras through my active presentations, publications, and blog articles, I am an independent researcher who has no link to FLIR, FLUKE, or any other IR camera manufacturers.

"Mega" Molecular Workbench applets

2011-04-21T08:54:00.010-04:00

The Molecular Workbench software allows developers to create interlinked simulations. This allows many simulations in just one applet, which I call a "mega" applet. The following example, which provides simulations of physical phenomena at different scales, shows how this works.

[ Click to go to the applet ]

Here is another example of molecular dynamics simulations of pressure conveyance in different settings through fluids:

[ Click to go to the applet ]

A Molecular Workbench "mega" applet provides rich user experiences similar to Web 2.0, which can be designed using the software's authoring system. This is similar to Macromedia's Flash software.

Comparing convection and conduction using Energy2D

2011-02-06T16:32:00.043-05:00

The following are two Energy2D simulations that compare convection and conduction, which should run within this page if you have installed Java and Java applets are enabled with your browser. The first one shows the case of natural convection. The second one shows the case of forced convection.

Instruction: Click inside a simulation window. Press 'R' to start or stop, 'T' to reset, 'L' to reload the initial configurations, and 'G' to open or close a graph. The virtual temperature sensors can be moved around, though most other pieces are locked to their positions. Right-click on the windows for more actions.

Natural convection (driven by thermal buoyancy):

Forced convection (driven by airflow):

A Von Kármán vortex street.

The following screenshot shows a typical Von Kármán vortex street produced from the second simulation. Energy2D is also capable of producing other interesting fluid patterns such as mushroom clouds, Bernard's Cell, and the Kelvin–Helmholtz instability.

More generally, Energy2D is a Java application that allows users to create interactive, real-time simulations of heat and mass flow. A simulation you create can be easily placed on the Internet just like what you saw above.

On a separate note, below are two results for conduction simulations using Energy2D that illustrate the circuit analogy: Ohm's Law is the electrical analogy of Fourier's Law of Heat Conduction. It is interesting to note that Ohm actually drew considerable inspiration from Fourier's work on heat conduction in the theoretical explanation of his work (see Ohm's Law in Wikipedia). Ironically, today's students seem to be more familiar with Ohm's Law than Fourier's Law. So the circuit analogy is used in textbooks to help students understand heat conduction.

The analogy to a parallel circuit.

The analogy to a series circuit.

Why do metals feel colder? An infrared view

2011-01-19T20:06:00.005-05:00

Metals feel colder because they conduct heat faster, not because they are really "colder." This is often a misconception from students. A very simple IR experiment may dispel this misconception by visualizing what is going on when you touch a piece of metal and a piece of paper.

Lay a piece of aluminum on a foamcore board. Then cover it up with a piece of paper. Put one hand on top of the part of paper above the metal and the other on top of a part of paper that is not above the metal. Have your partner look at the hands on the plate through an IR camera. The reason that we want to cover the metal up with a piece of paper is because we want to make sure that the difference of temperature we observe has nothing to do with the difference of emissivity--the ability of a substance to emit infrared light--between metal and the base material.

The first IR image shows the initial temperature distribution when the hands were on. The second one shows the temperature distribution after two minutes. It clearly shows that the hand above the metal strip is losing more thermal energy than the hand above paper.

This simple experiment, once again, demonstrates the transformative power of IR imaging. IR imaging experiments such as this are much easier to do than conventional experiments. They provide more intuitive, richer results in a snap. Imagine how many other experiments out there that can be transformed by this new instrument!

Energy3D: Design, print, cut, assemble, and test

2010-11-25T09:32:00.001-05:00


Figure 1: Designing a building with Energy3D.

We have come close to release an alpha version of Energy3D, a computational building science laboratory for simulating energy flow and designing energy efficiency. This program will allow you to design a building in a What-You-See-Is-What-You-Get style in 3D, just like Google SketchUp, and then evaluate its energy performance.

The alpha version will feature the Blueprint Wizard, which automatically deconstructs a 3D structure into 2D pieces, figures out which pieces are on the same 2D plane, generates a layout of all the planes, calculates the necessary lengths and angles, and prints them on a sequence of pages. Every piece is numbered and annotated with calculated geometric information adequate to guide students to cut it from provided constructional materials such as paper or foam board. The entire deconstruction process is animated so that the user has an intuitive understanding of the relationship between a house and the pieces in the blueprint.

Figure 2: Cutting and assembling the
building shown in Figure 1.

Students also have an option of fitting designs to the dimensions of constructional materials. For example, one option is to assemble a house using printer paper. If students select this option, Energy3D will automatically rescale every piece to guarantee that the largest piece can fit an A4 page and all the others will be proportionally rescaled accordingly. In this case, the texture and all the marks on a piece will be printed out, making it possible for students to construct a physical scale model that looks just like its computer counterpart.

Figure 3: Testing the scale model under
a table light and observing its thermal
signature with an IR camera.

If students are not sure where a piece is located during assembly, they can go back to Energy3D and click on the corresponding virtual piece in the 3D computer model, which will then be highlighted to indicate its position. Thus, the software tool remains useful during the hands-on construction. If any revision is needed after a physical scale model has been constructed, Energy3D’s blueprint feature can help students evaluate whether a modification is feasible by calculating how many pieces will need to be changed and whether there will be enough materials to make the changes.

Energy3D is developed by Drs. Saeid Nourian and Charles Xie and made possible by a grant awarded to the Concord Consortium by the National Science Foundation.

An infrared view of a popular chemistry experiment

2010-10-26T08:03:00.042-04:00

Figure 1. An IR image of a freshwater
cup and a saltwater cup after an ice
cube was added to each.

Will an ice cube melt faster in freshwater or saltwater? Why do we salt the road in water? How does an iceberg melt and how might it affect the ocean currents? All these curious questions are wonderful for students to explore. And they are very easy to do.

However, the science behind these questions are not that easy. To explain the results, we will probably need some reasoning at the molecular level, which is not at all easy for lower-grade students. But that is what we hope them to learn. These explorations require not only hands-on but also minds-on, which is why they are so great.

Figure 2. An IR image take after four
minutes showing the convection in
the freshwater cup.

They are not obvious at first glance and often can be counterintuitive. If you google "ice melts slowly in saltwater," you can find a lot of discussions--and debates as well. Many students and teachers were confused by what they observed in such a simple system as an ice cube floating in a cup of saltwater. Most of the discussions were, however, merely based on theoretical deductions.

Had they had an IR camera, the thermodynamic processes would have been much more obvious. Figures 1-4 show a series of IR images taken to reveal what happened in the two cups after an ice cube was added.

The IR images show that ice molt faster in freshwater because cold molten water can sink to the bottom and warmer water at the bottom is pushed to rise. This process, called convection, runs continuously to carry heat from the whole cup to melt the ice cube.

Figure 3. An IR image taken after
nine minutes showing the cooling
effect at the bottom as indicated by
the greenish halo.

In the case of saltwater, the cold water just sat at the top. The only explanation of this is that saltwater is denser so molten freshwater from the ice cube cannot sink, even if it is colder. Somehow, saltwater provides greater buoyancy that counters the thermal buoyancy.

Figure 4 shows that sixteen minutes later, the cold front still had not reached the bottom. This means that not only convection slowed down but also conduction was very slow.

Figure 4. 16 minutes later...

Recall our finding that a cup of saturated saltwater can spontaneously develop a temperature gradient from bottom up. This experiment provides a direct evidence that supports the theory that the temperature gradient can be created by the salinity. However, this evidence is not decisive, as the phenomenon reported here happens in an unsaturated solution whereas the small temperature gradient only exists in a saturated solution.

The puzzle still remains unsolved.

PS: Sprinkling some salt to an ice cube seems to accelerate the melting process. This seems to be in contradiction with the observation that ice melts more slowly in saltwater. This is where a lot of people are confused. The physics behind the two processes is different, even though they involve exactly the same chemical ingredients--just water in two different phases and salt.

Which colors absorb more light energy?

2010-10-25T08:48:00.006-04:00

Figure 1. A page with some color
strips under a table lamp. Click the
image to enlarge it to see the details.

We all know black objects absorb more light energy than white ones. What about red, green, blue, and any other colors? With an infrared (IR) camera, this is very easy to figure out.

Print some strips in any color you want on a page, as shown in Figure 1. Put the page under a table lamp and let the light shine on it for 10 seconds. Then aim an IR camera at the paper. Figure 2 shows the results.

Figure 2. An IR image showing the
amount of light energy absorbed by
the color strips.

Obviously the black strip absorbed the most. But the red, blue, and green ones did not absorb much. Interestingly, the dark gray and purple ones absorbed absorbed more than I would imagine.

I have to admit that I didn't know how other colors absorb light energy before doing this experiment. With an IR camera, you can easily check it out just on your own like what I did--for any color and any comparison.

If you have heard that Steve Chu, our Energy Secretary, has been serious about painting our roofs with light colors and Mayor Michael Bloomberg has agreed to answer the call in New York City, you may find this little experiment worth your while--you may pick a color that does not absorb a lot of energy yet it will be more colorful than white.

Visualizing convection without using ink

2010-10-24T20:59:00.010-04:00

Figure 1. A top view of a floating

ice cube.

If you have done a convection demo using a container of water and some ink, you may have had to change the water after each demo since the ink had diffused everywhere, which may make the convection pattern less easy to observe. Depending on the size of your container, that is some work to do and some water and ink to waste.

Here is a greener and better way to do it--using an infrared (IR) camera. An IR camera shows hot and cold (typically) in red and blue colors, which can be considered as "IR ink" that can be seen only through an IR camera. With the tool, all you can do is to add some ice cubes or hot water to a container of water every time you need to do a demo. There is no need to change the water.

Figure 2. A side view of a floating ice
cube showing "cold fingers."

One thing to notice is that you should not use a glass container--because it reflects off IR rays that will get into the image. A clear plastic one is the best as it does not reflect much and it allows you to observe what happens inside (if anything visible) with naked eyes.

Figure 3. A view from another side
showing the the cooling at the
bottom.

Figure 4. An IR image after hot water
was added to room temperature water
in a container showing hot water
tended to float atop.

Figure 5. An IR image of a fish tank
showing a clear pattern of
temperature stratification.

Salinity gradient vs. temperature gradient

2010-10-22T08:56:00.025-04:00

Figure 1. The salinity gradient and
temperature gradient observed in an
open cup of saturated saltwater.

This is the fifth follow-up of the blog article: "A perfect storm in a cup of salt water?" This investigation focused on the relationship between the salinity gradient and the temperature gradient. Is the temperature gradient caused by the salinity gradient, or the other way around? Both arguments seem to make some sense. On the one hand, one can argue that the salinity gradient stops the convection. On the other hand, warmer water tends to dissolve more salt. So we are in a chicken-egg situation.

Let's do an experiment to explore a bit further. I prepared two cups of saturated saltwater. One open and the other sealed. I let them sit overnight and then checked the salinity and temperature distribution the next day using Vernier's salinity sensor and temperature sensor. I did this by moving the salinity sensor and the temperature sensor together up and down in the saltwater. Figure 1 shows the results for the open cup.

Figure 2. The salinity gradient and
temperature gradient observed in
a closed cup of saturated saltwater.
Note: The measurement was done
shortly after removing the seal.
Hence the results can be regarded
as approximately those of the
sealed cup as the gradients will
take a longer while to establ

To measure the data for the closed cup, I first removed the seal and then quickly did the measurement. Since the salinity and temperature gradient would take some time to readjust after the seal was removed, we can pretty much assume that the results I got approximately reflect what would have been measured if the seal had not been removed. Figure 2 shows the results.

The comparison of the results shows that the salinity gradient is about the same for the open and closed cup--the bottom is about 1.3 ppt saltier than the top, but the temperature gradients are quite different--the open cup measured about three times as large as the closed cup (0.3°C vs. 0.1°C).

Due to the evaporative cooling effect, the overall temperature of the open cup is at least 0.5°C lower than the closed one.

What do these results suggest? A weak temperature gradient may exist in a closed system that does not have the driving force of evaporative updraft.

Visualizing vapor pressure lowering

2010-10-12T11:30:00.019-04:00

Figure 1. Two shallow plastic containers.

The left one holds a lot of salt and the

right one is plain water. A small amount

of water was added to the left one.

This is the fourth followup of the blog article: "A perfect storm in a cup of salt water?" that started this journey of discovery.

The vapor pressure lowering is an effect that says the water vapor pressure above saltwater is lower than that above freshwater. This is more generally described by Raoult's Law, which states that the vapor pressure of an ideal solution depends on the vapor pressure of each chemical component and the mole fraction of the component present in the solution. Since the sodium and chlorine ions hardly evaporate, the vapor pressure above saltwater comes from the evaporation of water molecules.

The molecular mechanism behind the vapor pressure lowering is easy to understand--the ions stay in the way of water molecules and slow down the rate of their evaporation and, in the case of salt, they even act to attract the water molecules and prevent them from leaving the solution.

Figure 2. An IR image of the two shallow

containers right after water was added to

the salt one on the left.

Let's try to use infrared (IR) imaging to visualize this process. Prepare two plastic containers like the ones shown in Figure 1. Add plenty of salt to one of them and some water to the other. Then add some water to the salt one. Figure 2 shows an IR image just after water was added. The image shows that the system absorbed heat while salt was being dissolved.

Figure 3. An IR image after half an hour
showing that the evaporative cooling
effect of the saltwater container is weaker
than the pure water one.

Let the containers sit for about half an hour and then take another IR image. Figure 3 shows the result. Interestingly, the colors reversed. Now, the saltwater container appears to be warmer than the pure water one.

Figure 4. An IR image after a few hours
showing that the contrast of colors
became greater.

Wait for a few hours and then come back to take an IR shot. Figure 4 shows that the temperature difference became greater.

How to interpret these results? There are two mechanisms that cause the temperature difference.

One is the vapor pressure lowering mentioned above. Using a Vernier relative humidity sensor, one can confirm that the humidity above the saltwater is lower than that above the freshwater. This means that the evaporation weakens above saltwater, which reduces the cooling effect.

The other is the crystallization of salt that releases heat. The evaporation of every water molecule weakens the ability of the solution to hold ions. As water constantly evaporates, a corresponding amount of ions must return to the crystalline form--mostly at the bottom because the contact area with the wall is much smaller compared with the contact area with the bottom. This process releases heat at the bottom. Since the saltwater is very shallow, the heat conduction may happen fast enough so that the crystallization heat will pass to the surface of the saltwater--even if convection may be insignificant with such a shallowness--and make it even warmer on top of the weaker evaporative cooling effect. This effect, which is totally based on molecular reasoning, is yet to be confirmed by an experimental method.

The vapor pressure lowering process and the crystallization process in this system are intertwined. If evaporation slows down (absorb less heat) due to salt, crystallization slows down (release less heat) too. The small amount of crystallization heat transfers to the surface and slightly increases the evaporation rate, which in turn causes slightly more ions to crystallize. The two processes manage to keep the saltwater container warmer than the freshwater container. But we still don't know which process contributes more. The question is, without the crystallization heat, can the IR image of the saltwater be as warm as it appears to be? How can we separate the two effects? Sealing the containers to stop evaporation doesn't work because that will stop crystallization as well.

Why do I insist on the theory of crystallization heat? Not only because it is logical. If we look at Figure 2, we will see that the effect of heat of solution is pretty significant. In order for salt to dissolve in water, some heat needs to be absorbed. Now, when the reverse process has to happen, i.e., when the salt ions have to return to the solid form, the same amount of heat must be released--in a much slower pace because of the low rate of evaporation (compared with the rate of dissolving). This is just simply the rule of energy conservation at work. The chemical potential must act like a spring. Energy is stored when it is "compressed" and released when it "bounces back."

Most likely, I now think this mysterious effect in a cup of saltwater is an orchestration of many physical and chemical effects. The salt gradient in a saturated solution is yet another mystery to be uncovered: the salinity gradient exists only in a saturated solution but not in any unsaturated solution.

A small cup of saltwater may contain a lot of physical chemistry! Stay tuned for more follow-up experiments.

Mystery solved?

2010-09-23T05:19:00.025-04:00

This is the third followup of the blog article: "A perfect storm in a cup of salt water?"

I woke up last night with a perfect explanation for the mysterious temperature gradient observed in a saturated salt solution. It is the recrystallization of salt at the bottom of the cup that releases the heat.

Since water molecules are constantly evaporating from the surface of the solution, a corresponding amount of ions must return to the crystal form at the same time--because a reduced amount of water in a saturated solution in the cup cannot take them any more. This most likely occurs at the bottom since the surface of the precipitate already provides a perfect ground of crystal growth. When ions adhere to the surface of a crystal, heat is released. The amount of released heat is approximately equal to half of the cohesive energy of the salt crystal (because it is a surface adhesion), which may be quite high because of the strong electrostatic attractions in the ionic crystal. The released heat transfers to the solution near the bottom and, together with the evaporative cooling effect on the surface, creates the temperature gradient we observed. The entire process runs continually across the solution because of the diffusion of water molecules and ions driven by their concentration gradients: the concentration of water/salt becomes lower/higher at the surface when water evaporates.

There are four evidences that support this theory:

The temperature gradient disappears when we sealed the cup, because that stopped the evaporation at the surface as well as the recrystallization at the bottom.
We observed no temperature gradient in an unsaturated solution because there is no recrystallization process.
The temperature hiked when the sensor touched the salt deposit at the bottom.
This temperature gradient lasts for a long time because this process will continue until all the water molecules evaporate.

Now, how can we make use of this effect to produce clean energy? As we produce sea salt by using solar energy to evaporate the water in brine anyway, might it be possible to harvest the energy released from the crystallization process? This seems like a stone that kills two birds: generating electricity while producing salt.

The diagram above illustrates the energy cycle of a saltpan/ionic power plant combo. This design is based on a chain reaction that involves two phase changes in a salt solution to convert solar energy into electricity through the ionic potential.

PS: I found in Wikipedia the concept of solar pond that uses a large pool of saltwater to collect solar energy. I think its mechanism is different from what I discussed above. I have had no luck reproducing the effect of a solar pond in a cup yet.

The temperature gradient exists only in a saturated solution

2010-09-20T08:24:00.030-04:00

This is the second followup of an earlier blog article "A perfect storm in a cup of salt water?"

I did an experiment to investigate the relationship of the salt concentration with the mysterious temperature gradient in a cup of salt water. The experiment was to measure the top-bottom temperature differences in three cups of salt water: low-concentration, medium-concentration, and saturated solution. In the saturated solution, there is a salt precipitate at the bottom of the cup. In all measurements, a fast-response temperature sensor was moved up and down in a cup. And the solutions had existed for over 100 hours to ensure that the salt was completely dissolved and the systems had reached thermal equilibrium with the environment.

The results shown in the graph above clearly indicate that the temperature gradient exists only in the saturated solution. The two unsaturated solutions exhibit no appreciable temperature gradients and measure approximately the same temperature with plain water.

The results were confirmed by an IR image shown above (from left to right: low-concentration, medium-concentration, and saturated).

This experiment suggests that there is probably no ion gradient in an unsaturated solution. An unsaturated salt solution has the same temperature everywhere and that temperature is the same as that of the plain water, whatever its concentration is. I originally expected that an unsaturated solution would have a temperature gradient more or less proportional to the salt concentration, as would a colligative property. This surprising result made me think that the prime suspect is the salt precipitate at the bottom of the cup. We know there is a lot going on on the surface of the precipitate layer. The dissolving and crystallization never cease. It is just that the two processes reach a dynamic equilibrium--the rate of dissolving becomes the same as the rate of crystallization.

Let's think a bit more about the meaning of this experiment. Notice that the temperature curve of the saturated solution lies entirely between that of the ambient temperature and that of the pure water temperature in the graph. This means that the existence of the precipitate somehow weakens the evaporative cooling effect, and probably the evaporation process itself. Why would the evaporation of water at the top of the solution slow down in the presence of some precipitate at the bottom? Exactly how does this process contribute to the temperature gradient existing in the solution?

We can plausibly reason that the rate of evaporation decreases because the ions somewhat act as binding agents that hold the water molecules more tightly through the strong electrostatic attractions. This is known as the water shell effect—water molecules are attracted to an ion and form a dynamic shell around it. As a result, it is more difficult for water molecules to leave the solution to evaporate. But this picture cannot explain why there is virtually no difference between the temperature of a cup of pure water and the temperature of a cup of unsaturated salt water.

It seems the mystery is far from being uncovered. While clarifying a few things, this experiment makes the phenomenon more baffling. Stay tuned for our next investigation.

In terms of its other implications, there is one thing that we can rule out now. There is no such effect in the ocean, as sea water is not saturated.

Evaporation is a driving force

2010-09-14T09:05:00.020-04:00

This is the first followup of the blog article last week "A perfect storm in a cup of salt water?".

Several people including Bob Tinker, John Loosmann, and Einar Berg suggested that it was the evaporation of water that drives the observed persisting temperature gradient. It turned out that they were right. After sealing the salt cup with plastic wrap and leaving the three cups for 24 hours, their thermogram shows the sealed cup vanishes from the infrared image (see the image to the right--the sealed salt water cup is in the middle, which is invisible). This means that the temperature everywhere in the cup is the same as the ambient temperature. The infrared image also shows the baking soda cup, which has not been sealed, continues to show a temperature gradient.

Now, we have to explain why the pure water cup shows a cool infrared signature. So I added a sealed pure water cup. The thermogram to the right shows that the sealed pure water cup vanishes in the infrared image (the sealed water cup is on the right of the thermogram), whereas the open pure water cup shows a cooler image for the part filled with water. Interestingly enough, the upper part of the cup that does not have water contact is constantly almost 1°C warmer than the filled part. This temperature gradient is clearly shown in the infrared image below. Why is the temperature gradient across the water line on the surface of the plastic cup so sharp?

Now go back to the evaporative updraft force. At this point, we only know that cutting off evaporation shuts down the energy loop. We still do not know how what happens under the water line in the salt water cup. The following graph clearly shows that this effect exists in not only a salt solution, but also a baking soda solution and a sugar solution.

We can suspect that the ion concentration gradient is another driving force for this energy circuit. This will be our next step of investigation. Stay tuned.

A perfect storm in a cup of salt water?

2010-09-10T18:37:00.035-04:00

I was bothered by an experiment I did recently about the temperature distribution in a cup of salt solution. I added a few spoons of table salt and baking soda in two cups of water to create two saturated solutions. Then I left them sit there for a few days, along with a cup of plain water. When I came back and aimed my infrared camera at them, I saw something quite puzzling: in the two cups of solution, the bottoms were always about 0.5°C warmer than the tops (see the IR image above)! In contrast, a cup of plain water did not show this temperature difference--the temperature was the same everywhere just as expected.

Exactly what kind of chemical force sets up this temperature gradient? We all know that warmer water should rise and colder water should sink, and eventually the convection stops and the temperature becomes the same everywhere. But this is apparently not true in the presence of salt solute. I feel this has to do with gravity. It must be gravity that causes a concentration gradient of the solute, which in turn results in the temperature gradient. But I am not sure how exactly this happens. I have no idea what energy source feeds this temperature gradient. Don't forget that the cup material tends to eliminate it through heat conduction and the air through convection. There must be an invisible hand that counters all these thermodynamic forces. This seems pretty amazing to me.

To make sure that this is not an effect of infrared radiation, I confirmed the result by sticking a sensitive temperature probe into the solution and moved it up an down for a few times. The image below is the 60-second result recorded by the temperature probe, which clearly agrees with the IR image.

This is an example that, once again, shows the power of infrared imaging. I would not have noticed there was such a temperature gradient in a solution without my infrared camera. The infrared camera, in just one simple shot, captured the salient and subtle details that reveal very complex physics, which I still do not understand.

What is the significance of this result rather than a tempest in a teacup? Might the temperature gradient be used to generate a voltage gradient, which in turn generates electricity? In other words, might this be some kind of battery that is a 100% clean energy source?

The ocean is a gigantic solution of salt. Half Celsius of temperature difference in the ocean translates into an enormous amount of energy. Might there be such an effect in the ocean?

Followups:
1) Evaporation is a driving force
2) The temperature gradient exists only in a saturated solution
3) Mystery solved?
4) Visualizing vapor pressure depression
5) Salinity gradient vs. temperature gradient
6) An evidence from an ice cube

Infrared imaging for chemistry education

2010-09-05T23:06:00.014-04:00

Infrared (IR) imaging is a technique for seeing heat based on detecting thermal radiation (mostly IR) an object emits. It used to be a very expensive tool only affordable to guys in military and secret services where money is not a problem.

You can now buy "lower"-grade IR cameras with $1,500-$2,500, which are pretty cool (thank you for lowering down the prices, Flir and Fluke!). There is a vast market for this technology. Engineers and technicians buy them primarily for checking heat flow in building, electrical systems, and mechanical systems. Companies also use them to do quality assurance and safety monitoring.

I have been digging the educational potential of IR imaging lately. I feel that the tool can be very useful in education. Compare it with a microscope. Both can be used to see something invisible. In the case of a microscope, it is things that are too small to be seen. In the case of an IR camera, it is things that our eyes cannot detect. It is obvious that students need a microscope to see small things. But perhaps we can also rationalize the need for an IR camera in the classroom? What are the most important things that IR imaging can teach?

Obviously there is heat transfer. I have recently written a paper about this. But I don't want to just do the evident ones. So I have been thinking about how to broaden its applications. A direction I am taking now is its applications in chemistry, where heat is a central concept. You probably still remember that your high school chemistry teacher always wanted you to remember how much heat is released or absorbed in a chemical reaction. If a reaction produces a dramatic effect, such as a bang or a flash or a flame, then you probably were impressed. What about those reactions that mostly go unnoticed unless some sensitive methods are used to show them? For instance, most biochemical processes are pretty "calm." How does one "see" or "hear" them?

I have done an experiment that uses an IR camera to show evaporation and condensation, as mentioned in the paper. The above IR thermogram shows what happened when a piece of paper was placed on top of a cup of water. The paper did not fully cover the cup. What we see from this IR image is a cooler area that shows the evaporation process of the water in the cup and a warmer area that shows the condensation process of the water on the other side of the paper.

Last week, I did another experiment to prove that it can also be used to visualize dissolving. This experiment is introduced in a short article. The image to the right shows the thermograms of three cups: pure water, table salt solution, and baking soda solution, shortly after table salt and baking soda were added to two of the cups originally filled with pure water.

I am hoping to devise more chemistry experiments to prove the versatility of this powerful tool in making mysterious things in chemistry visible. I intuitively feel that this tool, which is essentially a bundle of thousands of IR thermometers, may be able to release students from tedious lab procedures and make chemistry experiments easier to conduct and fun to look at.

Who says kids cannot invent?

2010-08-16T20:43:00.038-04:00

I was recently involved in a few pilot field tests in which high school students were challenged to build an energy efficient scale model house. We observed something amazing. Initially, I was worried that students may end up building houses that are so similar to each other that the entire research will be invalidated. But that did not happen.

In one field test, a group of students created a pyramid and discovered an effect that I would call "a heat funnel." The images to the right show the pyramid heated by a 40W light bulb on the floor inside and an infrared signature showing the equilibrium temperature distribution. The students observed that the temperature at the tip of the pyramid reached nearly 150°C--enough to boil water! This amazing heating effect is due to the fact that hot air rises to the top in a way similar to how water flows down in a funnel. Just like the bottleneck of the funnel records the highest speed of water flow, the top of the heat funnel records the highest temperature of heat flow. The water funnel is usually explained using the conservation of mass, whereas the heat funnel can be explained using the conservation of energy. The density of thermal energy must increase when the heat conduit narrows in order for energy to conserve. Therefore, the temperature at the tip can be very high because its cross section is very small.

Although they did not expect the temperature at the tip to be so high, the students were fully aware of the convection effect, because they cut some slits at the bottom of the pyramid to let fresh air in in order to keep the air flow through it (you can see a slit from the photo on the left). This is the stack effect that drives a chimney. At the top of the pyramid, the hot air just exits through the tip, which naturally has small passages for the air because it was not perfectly sealed. Had students had a sensitive air speed meter, they would have observed a small but appreciable jet stream coming out from the tip (would they?), just like steam from the vent of a cooking pot.

In another field test, a group of students created a sliding roof that can provide overhang shading in summer and increase roof insulation in winter (see the images to the right).

I must confess that, as a physicist, I have never heard of or thought of the heat funnel effect until I saw it in the classroom. Pondering about this effect, I realized that it might be non-trivial and could have some engineering implications. For example, might this effect be used to build some kind of solar updraft pyramid for generating electricity? I have heard that in the US there are huge solar power plants that utilize the optical focus effect to create high temperature to boil water, which in turn creates steam to push an electrical generator. How about a heat funnel generator that will work sunny or cloudy?

The sliding roof invention is impressive in that the students figured out an engineering solution that solves two problems: winter insulation and summer shading. The students also had an idea of putting solar panels on the sliding roof and the base roof. This smart design, which increases the solar reception area, will turn the unwanted solar heat into electricity instead of reflecting it off. This is not just a single solution that solves one problem. This is a stone that kills three birds. Isn't this exactly what we strive to teach in our engineering classes?

These inventions of students should convince you that students are not just learners. If we give them creative tools and interesting projects, they can be inventors as well. Sometimes, their inventions will surprise even seasoned scientists and engineers. Science and engineering education should make more opportunities for these young inventors to rise to the top.

MW applets and MWScript-JavaScript interactions

2010-02-14T14:04:00.035-05:00

Now that you can publish a Molecular Workbench simulation as an applet and embed it on your web page, you may be wondering how you can control it and get data in and out. It may be interesting for web developers who would like to link an existing Flash animation with a molecular dynamics simulation in MW. For example, when the visitor clicks something in the Flash animation, a molecular dynamics simulation will pop out to show the molecular mechanism of what is going on underneath.

With MW, this can now be done using MWScript and JavaScript. MWScript is a scripting language used in MW to support modelers and animators to design simulations. The model builders in MW do have some simple GUI for building models and designing simulations, but their functionality is limited (as with any GUI). Syntactically, MWScript is a cousin of JmolScript, which supports scripting with the popular Jmol molecular viewer. So anyone who is already familiar with JmolScript may find it easy.

Before we talk about scripting, let me show you how to set up an MW applet on your web page. If you just want to show an existing MW simulation from mw2.concord.org (which hosts MW) on your web page, just embed the following applet code within the body of your HTML file:

<applet id="applet_id"
archive="http://mw2.concord.org/public/lib/mwapplet.jar" 
code="org.concord.modeler.MwApplet" 
width="100%" height="500">
<param name="script" value=
"page:0:import http://mw2.concord.org/public/student/classic/motion/undershotwaterwheel.cml"/>
</applet>

In the above example, I have randomly chosen an existing simulation from MW to show how this works. If you want to show other simulations, just replace "http://mw2.concord.org/public/student/classic/motion/undershotwaterwheel.cml" with whatever else.

This following shows the embedded MW applet specified by the above code:

This is very easy to do. But it has a limitation. Suppose you have created an MW simulation of your own and the name of the main file is "simulation.cml" (an MW simulation has other files associated with it as well). Now you have to upload the files to the Web. If you use its URL in the embedding code, the MW applet will not load it. Because of a good security reason, an applet is allowed to read files from only the same code base where the Java executable is located (in this case, http://mw2.concord.org/public/lib/mwapplet.jar).

To avoid this problem, you would want to have your own code base instead of using mw2.concord.org. First, you download the jar file: mwapplet.jar to the same folder where "simulation.cml" and the HTML file sit. Second, change the embedding code to:

<applet id="applet_id" archive="mwapplet.jar" 
code="org.concord.modeler.MwApplet" 
width="100%" height="450">
<param name="script"
value="page:0:import simulation.cml"/>
</applet>

Having done these, you just need to make sure to also upload "mwapplet.jar" to the same web folder where "simulation.cml" has been uploaded to.

If you have done these and succeeded in getting an MW applet to work properly, let's see how to get it to work with JavaScript as well. First, download this file: mw.js to the same folder. Second, put the following script declaration in the header of your HTML file:

<script type="text/javascript" src="mw.js"></script>

The MW applet is now ready to interact with JavaScript. The applet works offline as well, so you can conveniently test your JavaScript before deploying the whole thing to the Internet, by just double-clicking on the HTML file and see how it works.

There are currently three types of interactions between MWScript and JavaScript.

Use JavaScript to send MWScript to control an MW applet
Use JavaScript to feed data to an MW applet
Use JavaScript to get data out of an MW applet

The runScript(id, script) method in mw.js can be used to send MWScript to an MW applet with the specified ID. An MW applet is an MW page that can have multiple models, though in practice you would only use one model per applet. To specify which model you would like to send the MWScript, you have to following the following protocol:

[model type]:[index or UID of model]:[script body]

For instance, mw2d:1:run instructs the first model within the MW applet to run. You can pass a variable from JavaScript to MWScript by concatenating the variable with a script command. For example, var temp = 300; runScript("applet_id", "mw2d:1:set temperature " + temp) sets the temperature of the system to be 300 K.

The get command in MWScript was specifically designed to fetch data out of an MW applet. For instance, you can get the temperature by using the following code: var temp = runScript("applet_id", "mw2d:1:get %temperature");.

This page demonstrates all these three types of interactions with one applet. It is inconvenient for me to mix code in this blog as it interferes with the blog's setup. When you go to that page, you can view the page source to see the JavaScript code. If you have Firebug, it can also be used to view the code easily.

For more information about MWScript, go to http://mw.concord.org to launch the standalone application and check out the "Script" section in the User's Manual.

Publishing Molecular Workbench simulations as applets

2010-01-30T19:20:00.017-05:00

For a while I have been asked whether or not an MW simulation can be made to run directly within a browser page instead of a pop-up window. Several collaborators would like to deploy MW simulations within their web portals or delivery systems. For them, embedding a simulation within a web page is desirable. The current way of using the Java Web Start to launch an MW simulation sometimes irritates users as it can appear to be yet another kind of annoying pop-ups.

So I did some work in the past week to make it possible for users to save an MW page as an applet, which can then be deployed anywhere without having to rely on my company's server. This is always good for the integrity of a web site, as no serious web developer wants to depend on other people's servers to be up and running forever.

Here are some demos:

This new mechanism of publishing MW simulations provides an option for people who want to integrate MW simulations with their web applications, if they don't mind the relatively slow loading speed.

Energy2D: Interactive computational fluid dynamics

2010-01-11T19:40:00.036-05:00

Computational fluid dynamics (CFD) uses numeric methods to study any natural phenomenon and solve any engineering problem related to fluid flow. It has been an indispensable tool for many engineers. Mature, powerful CFD products are available nowadays. While these products are very useful tools for engineers, they were not designed for kids to play with. Understandably, the business community lacks the financial incentive to push the agenda of making a product friendly to students for learning science and engineering. With all these years passed while CFD products got better and better, all the wisdom developed for modeling and understanding the natural and man-made systems never got spread to schools in a satisfactory scale.

This tragedy was, in part, caused by the unfortunate fact that few people in the education community had realized the enormous power of CFD for teaching science and engineering. Educators had a very good reason for not seeing it, because the power has never been brought close enough to matter in their professional careers. Most CFD tools are either too complicated to use or do not deliver the needed visual effects and user interfaces to matter. This is an issue that cannot be simply said solved by sending a demonstrator from the CFD community to the education community. Talking and showing are cheap. To bridge the gap, we need actions that will truly make a difference.

Supported by the National Science Foundation with an urgent need for educating young students with energy science and technology, we are developing a versatile CFD package suitable for teaching the scientific and engineering principles related to energy flow, particularly about energy-efficient passive solar buildings. The package consists of two programs called Energy2D and Energy3D, respectively, for the 2D and 3D versions of the CFD simulator.

Energy2D and Energy3D are based on solving the heat equation for modeling thermal conduction, coupled with the Navier-Stokes equation for modeling convection. A ray-tracing method is used to model radiation. The minimum requirement is that the simulation must run fast enough to be interactive so that students can play with it.

After a few weeks of work, I came up with a primitive version of Energy2D. The following two screenshots show that if the obstacle has a small cross section against the flow, turbulence will not occur.

It turned out that writing an unconditionally stable heat solver was not a big deal. After all, it is just a simple diffusion equation that can be easily solved using an implicit method.

Writing a fluid solver is more challenging as it is non-linear (which is where all the fun comes from). I played and tested Jos Stam's fluid solver, which is based on an unconditionally stable Semi-Lagrangian method that is also used in weather prediction. Unfortunately, the solver is covered by a pending patent that we didn't succeed in convincing the current patent owner to license to us in any way--open-source or not. So I had to give up Stam's method and sought to reinvent the wheel.

I implemented the MacCormack method, which turned out to work fine for now. Compared with the Semi-Lagrangian method that achieves its stability by overdamping the fluid, the MacCormack method has no overdamping problem so it has to suffer from the stability problem. As a side note, I also found that after using the vorticity confinement method to re-inject vorticity to the solution of the Semi-Lagrangian method to make it more turbulent, it would also suffer from the stability problem. There seems to be no free lunch in seeking a fast, yet accurate, fluid solver.

Beyond Google SketchUp

2009-10-25T18:03:00.036-04:00

Google SketchUp is a wonderful program that you can use to design 3D structures such as a building WYSIWYG-ly. It offers by far the most advanced user interface for creating 3D objects. Within ten minutes, you can sketch up a simple house with a roof, a few windows, and a door, as shown by the image below (if you have learned the basics). While the learning curve may take a little while to overcome--not because the program does a poor job but because the task of creating 3D objects is inherently difficult, the program still provides tremendous opportunities for education.

If you are a teacher, you may have used it in your classroom, or seen someone using it to engage students to design things like a house. These activities are just wonderful as students really love designing their own homes or schools. SketchUp provides them a simple platform to do exactly that.

Now, the question is that what students learn from designing their dream houses. The obvious answer is that they learn solid geometry, without which one cannot really design any 3D structures.

Solid geometry isn't an easy subject and being able to reason in three dimensions is an important skill to have. All these things are very good, but what about teaching other topics in science and engineering?

As many students use SketchUp to design buildings, those who have a mindset of energy efficiency may come up with some green designs, for instance, some neat passive heating or cooling architecture. After they draw their structures, they would like to evaluate if their designs are really green. This goes beyond what SketchUp can do, because it doesn't deal with heat and mass transfer for the created structures.

There has been a plug-in to SketchUp called OpenStudio, which was developed by the Department of Energy to integrate SketchUp with their EnergyPlus software. EnergyPlus is a program written in Fortran that was created for architects to evaluate thermal performance of buildings they design.

OpenStudio, however, doesn't quite do the job one would like to get done (judged from a demo video). The image below, taken from Wikipedia, is what we have in our mind that we would like to see. The image is a thermogram of a passive house in the background of traditional houses, taken by an infrared camera.

Wouldn't it be great if students can design a building and then do some thermal physical analysis using some kind of virtual thermography? This ability will truly extend what students can do with a geometric design tool such as SketchUp. By giving the power of physics-based simulation to the design tool, it will be transformed into a useful experimental tool that allows students to learn the scientific and engineering principles behind energy efficiency.

This is exactly what we set out to do since October 1, 2009, thanks to the generous funding by the US National Science Foundation.

Heat transfer calculations aren't new things to engineers. There have been plenty of commercial software that have been developed to simulate heat transfer. But many of them do not meet our criteria for creating an interactive learning environment. Unlike an industrial application with which engineers can take their time and make all kinds of valid assumptions, there isn't much flexibility for an educational program.

First, students cannot wait. The calculations must be done relatively quickly. Anything that takes a long time to compute kills interactivity.

Second, again required by interactivity, transient heat transfer is a must-do, leaving us no steady state to retreat to. An interactive learning environment requires that the user can intervene at any time when he or she would like to see the causality. There is simply no such thing as a steady state when the user is interacting with a simulation as user's action is totally unpredictable.

Third, the simulation must render a convincing visualization that shows what happen to the heat inside and outside a house. All things must be considered so as to support as many explorations as possible. This requirement is at odd with the first one, as it will load the engine with all kinds of calculations that may slow each other down.

So how do we model the heat transfer of a house? In a model of building, there are two different kinds of things: solid structures and air. The major difference between the heat transfer in them is that there is only conduction in a solid structure but there are both conduction and convection in the air because air is a fluid.

Mathematically, what we have boils down to two fundamental equations: the heat equation and the Navier-Stokes equation. The heat equation models conduction and the Navier-Stokes equation models convection. These two equations are coupled to simulate the heat transfer in the air. For the heat transfer in a solid structure, only the heat equation is needed. A convective boundary condition is applied to the edge of the border to model the effect of heating or cooling through the flow of air over the surface of the structure.

That is pretty much all the computational physics involved in modeling the thermal performance of a house. We leave out radiation, but it should not be hard to add it to the boundary conditions.

What is in a Molecular Workbench simulation?

2009-06-26T21:13:00.059-04:00

The Molecular Workbench (MW) software offers salient interactive simulations of electrons, atoms, and molecules that explain many phenomena from the microscopic level. What exactly is in a simulation that makes it a better teaching tool than a text book illustration?

Let's start with a real world example. Imagine a closed glass bottle with some liquid at the bottom. There are a number of things about such a system that most of us have noticed since we were a kid. When we rotate the bottle, the liquid will always flow to fill the lowest part. When the liquid comes to rest, its surface levels off.

Now let's heat it up. As the temperature increases, evaporation accelerates. Eventually, all liquid molecules are evaporated and the liquid vanishes--we end up with a gas that fills the entire bottle. The gas molecules are evenly distributed inside the bottle, no matter how we rotate it. Suppose the bottle is expandable. The gas molecules will fill the entire volume of it, no matter how large it becomes (the gas just gets more diluted).

These are the things we know about the difference between a gas and a liquid from everyday life. Now, let's see how a simple MW simulation can model all these facts. On the right is an animation of a liquid in a box made from an MW simulation (click this link to run it; you will need Java 5.0+). In order for the simulation to run fast enough on an ordinary computer, the liquid includes just 256 molecules. This is not a lot to be called a liquid, but it is enough to demonstrate the phenomena. In addition, a super-strong gravitational field is applied to accelerate the gravitational effect (you might have heard from someone that the gravitational effect is not important at the atomic level, but that is because the gravity on the surface of the Earth is too weak).

A theoretical physicist would celebrate the simulation as the triumph of theoretical physics. The fact that a computational model can describe such a variety of natural phenomena means that they have been deciphered by science.

As an ordinary user, you may not know much about what is under the hood--in fact, most of the time, you should not have to care. You may be wondering what advantages a computer simulation has, compared with just giving students a bottle of water and asking them to flip and boil it. If you are a hands-on person, you may, on the contrary, prefer giving students a bottle of water. So what is the big deal of a simulation for you?

There are a few things that the computer simulation can do for you but a bottle of water cannot. First, the simulation is literally an atomic explanation of what happens when you play with a bottle of water. The very fact that a macroscopic phenomenon can be explained with a picture of a few hundred atoms is a very important insight in science. People have probably known how water in a bottle behaves thousands of years before, but an atomic perspective was not firmly established until 100 years ago.

Second, the simulation provides an "atomic microscope" that allows users to "zoom" into the atomic world easily because we can control it in many ways that are not realizable with a bottle of water. For example, we can navigate an "atomic camera" inside the system, or attach it to an atom. What would it look like if we could be shrunk to an atomic size and take a "space walk" or just "ride on an atom" inside a gas (the image on the right shows a screenshot in which atoms appear to run down to your face)? Kids are motivated by this kind of adventure experience, which can be supported very well by a computer simulation.

Another advantage of a computer simulation is that it can be easily embedded into an electronic textbook (which recently becomes the trend due to budget crises in many states in the US). Obviously, embedding a bottle of water into an electronic textbook is much harder, if not impossible at all (I would never say that is impossible). With the support of this kind of interactive simulation, future textbooks will not be just some readable things. They will be playable delights.

Why do educational software need rocket science?

2009-06-02T16:07:00.118-04:00

The educational software market is largely dominated by cartoon movies, animations, and games. Developing these media usually requires no rocket science (i.e., sophisticated mathematics and computation in the context of this blog). But this may change soon in the field of science education, enlightened by the success of some applications that will be discussed below.

A strand of mechanical simulation programs started with Interactive Physics back in the 90s and significantly advanced by the recently released Phun and Crayon Physics have demonstrated great educational potential. These impressive programs allow users to draw a variety of shapes, which then move realistically on the screen: they fall, slide, roll, and bump into each other--just like objects in the real world they model do. These programs have a user interface that is very friendly to novices, especially with a freehand drawing tool connected to a digital pen. With only a handful of tools, users can create many interesting simulations. Experienced users can build simulations as sophisticated as a vehicle impact test and a hovercraft takeoff. As a matter of fact, what users can create is limited only by their imagination.

There is no doubt that these tools truly motivate students, unleash their creativity, and make learning physics unprecedentedly enjoyable. But the important thing is that all these would not have been possible without using computational physics. The reason that these tools model the real world so well is because the motions of objects are calculated using Newtonian dynamics--to be more precise, using a computational method commonly known as the multibody dynamics. In fact, Phun uses a computational engine called SPOOK developed by Dr. Claude Lacoursière, and Crayon Physics uses a similar one called Box2D developed by Dr. Erin Catto. These multibody dynamics engines simulate interconnected bodies with contacts, joints, constraints, dry friction, and power input/output. SPOOK even supports multiphysics simulations by integrating the multibody dynamics for modeling rigid bodies with the smoothed particle hydrodynamics for modeling fluids.

The multibody dynamics method comes from rocket science--it is used in industry to model robots, vehicles, and aircraft. It was, however, not intentionally developed for use in education. The generations of computational scientists who developed the method presumably did not anticipate that one day the method would find its use in hundreds of thousands of middle schools and high schools. By the time I was blogging about this, the simulations run in classrooms may have far exceeded those run for research--by any standard.

What does this teach us?

The first lesson we learned is that computational science is not a privilege of some scientists in ivory towers any more. In fact, science education and scientific research share a common goal: to understand how things work. It is, therefore, not surprising that a research tool like the multibody dynamics can be so successfully converted into an effective learning tool. I would further contend that the only correct way to develop an educational tool would be to use the first principles in the corresponding domain of science as much as possible. The initial investment on such a tool may be high (e.g., it needs dedicated computational scientists such as Drs. Lacoursière and Catto, as well as brilliant programmers such as the authors of Phun and Crayon Physics), but the payback will be more powerful, generic software that can last for a long time.

In my opinion, the single most important advantage of using first principles to build an educational tool is that the power of creation and prediction embodied in these scientific principles will be given to students. What else is more important in education than giving students the power developed by the most intelligent individuals of the entire human race in decades or hundreds of years, now that we have a wonderful way of delivering it through computing?

Unfortunately, this advantage is often underappreciated by many educators who do not fully realize the potential of this approach. The vision that the well-advocated cyberinfrastructure should include smart media powered by first principles is not widely shared. Using science to build interactive science media is not part of the design guidelines of mainstream educational media. Applications such as Phun and Crayon Physics are still scarce. There are many more domains of science and engineering that need to be covered.

But there is hope. Outside education, game developers have adopted first principles far earlier. Games need to have realistic look-and-feels in order to be competitive in the market. Major graphics libraries already provide excellent lighting functions. Realistic motion of objects powered by physics engines and projected grid engine for rendering water are now not uncommon in games. Phun and Crayon Physics, despite their great educational power, are billed as games but not educational tools. Perhaps, the breeze from the gaming world into the educational world will slowly transform the way people think of educational media and changes will then occur naturally. What would schools be when they are equipped with tools powered by rocket science?

Smart molecules: next generation molecular visualization

2009-03-28T10:16:00.032-04:00

A significant part of chemistry education is about teaching molecular structures. Before computers were widely available, many teachers used physical ball-and-stick models in the classroom. Using physical models has limitations--the variety of the molecules we can make is limited and the molecules cannot have too many atoms. When computers were powerful enough to support 3D video gaming, chemistry educators realized that they could be used to show any kind of molecules on the computer screen and there was essentially no limitation to the molecular structures that one wished to show. This method of computer-aided teaching is now commonly known as molecular visualization and is widely adopted by chemistry teachers in teaching about molecules.

There are now many molecular visualization tools freely available for education, such as Jmol, PyMOL, QuteMol, and Visual Molecular Dynamics, to name a few. All of these tools present wonderful graphics for showing molecules in 3D. When a student uses such a tool to learn a molecule's structure, he or she usually rotates the molecule to see it from different angles, zooms in and out to view different levels of details, and sometimes turns on different representations of the molecule to identify some recognizable patterns (such as a structural motif of a biomolecule like the famous DNA double helix and an electrostatic surface of a polar molecule like a water molecule).

It is our hope that through manipulating and observing these virtual molecules students will gain a lot of information about them and be able to apply the knowledge and learn to think like a chemist. There are, however, some reasonable doubts that this expected learning would spontaneously occur once students are given these tools. We observed in the classroom that there were a number of students who did not accomplish the learning goal even though they were fascinated by beautiful visualizations of molecules and played with them tirelessly. Most materials do provide instructions and background readings, but they seem to be not very effective. In the absence of an instructor nearby to explain to them what they are seeing on the screen, many students may leave the activity with no science learning accomplished.

The problem, in my opinion, partly lies in that most of these tools only present a passive learning experience. By passive I mean the molecule does not actually give any feedback to the student while he or she is interacting with it.

In the game world, a well-designed game presents an active experience to the user. While the user is playing a game, he constantly receives feedback from the system that attracts his attention and he is always facing a challenge that he must meet to accomplish his goals.

What can we learn from games? A lot. The first thing is: imagine the molecule can respond to the student's actions. For example, the student pilots a microscopic spaceship into the molecule with a mission to fight some toxic molecules (such as carbon monoxide) and he has to carefully avoid running into vicious traps from strongly polar sites that want to catch his ship. His ship is equipped with a laser gun that can break a chemical bond and destroy an evil molecule. During his journey, he will encounter a number of puzzles and challenges that he must solve to win the game. For instance, he must maneuver his ship through a narrow passage inside a molecule in order to get to an active reaction site.

By adding these additional functionalities to a molecular visualization tool to make the molecule actively interact with the user (in addition to just passively rendering a view), we may be able to increase the learning opportunities for students. We call this idea the Smart Molecules, which is based on our NSF-funded Molecular Rover Project.

A smart molecule can also be thought of as an interactive tutor built into a visualization tool. For example, depending on where the ship is, the molecule can act like a flight controller to instruct the student where to pilot the ship. It can give hints to the user while navigating. It can provide more munition or fuel once the supplies on the ship are running low. Science lessons can be embedded into the environment to be called up for help if needed.

The Smart Molecules represents a revolutionary step forward for the use of molecular visualization tools in education. It would be interesting to see if this technology will help students learn molecular structures better in the classroom. Stay tuned.

Constructive science in the classroom

2009-03-19T07:59:00.001-04:00

"Imagination is more important than knowledge." --- Albert Einstein

Science should be taught as a verb, not only as a noun. Doing science is a compelling and effective way to learn. It is through the process of exploration, creation, and invention that theories are applied, ideas are tested, and knowledge is synthesized and upgraded. This post showcases some interesting simulations recently created by students using the Molecular Workbench software and proves the feasibility of using the constructionist approach to teach science more effectively.

The image on the left is a screenshot of a student's simulation about how a ball that has a density lower than that of water keeps afloat in a bucket being filled up by rain. The dynamic simulation shows how buoyancy works with an amicable setup of clouds, rain, a ball, and a bucket. The simulation and the note made by the student (not presented here due to privacy issues) clearly show that the student had learned not only the modeling tool but also the science during the construction process, because the simulation produces the emergent behavior exactly intended and explained by the student.

The second image is a screenshot of a student's simulation about the gas laws. Designing something that violates a physics law is often very motivational to students. Students are inspired to use their creativity to come up with every imaginable possibility of violation. This student designed a subtle situation in which all atoms in one container move only in the direction perpendicular to the piston and atoms in another container move in both the perpendicular and the parallel direction with an initial setup that guarantees the equipartition of the kinetic energy in each direction. The simulation shows that the volume of the gas in the right container is approximately half of that of the gas in the left container. Is the Ideal Gas Law broken? We leave this question to you.

The third image is a screenshot of a simulation of a salt crystal and water a student created using the 3D Molecular Simulator. It shows that the student knew what a crystal structure is and how dissolving occurs. Considering the complexity of constructing a 3D model (over a 2D one), this student's work is quite impressive. The fourth image is a screenshot of a simulation of photosynthesis created by another student, which shows the student's understanding of this complex biological process and her efforts in modeling it.

A common challenge in using a general-purpose modeling tool in the classroom is that it may take students longer time than teachers are willing to spend in the classroom to make something pertinent to the learning goals. Tempted by the versatility of the tool, some students even tend to "drift" away from the learning goals. To help students focus on learning science, the Molecular Workbench software permits instructors to design scaffolded construction activities while engaging students to build simulations. This is a unique and important feature of the software that will facilitate the wide adoption of this pedagogy.

From the point of view of assessment, the richness of information expressed in these simulations has much to offer to research and evaluation about using computer simulations in the classroom. As a Chinese proverb says: "A picture is worth a thousand words," a simulation may be worth much more than a thousand words for the assessment of student learning. Ultimately, the most reliable and relevant assessment of educational simulations should use simulations themselves as the data sources. The only way to make this assessment work is to engage students to make their own simulations.

Making sense of quantum phenomena through simulations

2009-02-18T07:53:00.001-05:00

"We have become quantum mechanics -- engineering and exploring the properties of quantum states. We're paving the way for the future nanotechnicians." --- Donald M. Eigler, IBM Fellow

Understanding how things work in the microscopic world is fundamentally important to science and engineering education in this century. The micro world is essentially operated by quantum mechanics, which is traditionally very difficult to learn--even for a physics student--because it is so unintuitive. Nevertheless, a large number of phenomena can only be understood with the quantum picture. Understanding these phenomena is becoming imperative. Many important technologies such as microelectronics and nanophotonics are built upon the science of electrons. These technologies are now spearheading new innovations that will lead to revolutionary changes in manufacturing, computing, communication, health care, and medicine.

This poses an interesting challenge to educators: how do we teach quantum reasoning to students without getting them bogged down in the complex field of quantum mechanics (and possibly the philosophical issues associated with its weird interpretations that are still at issues among some scientists and philosophers)? Is there a pathway for students to develop a quantum sense without resorting to the formalism of quantum mechanics?

Funded by the National Science Foundation, we are currently exploring effective ways through simulations to teach the science of electrons and the related technologies. Unlike many existing interactives on the web, our simulation program will provide students a tool with which they can familiarize themselves with the strange quantum world, without having to learn any equation at all. They will learn through playing with existing systems set up by curriculum developers or customized by their instructors (learning by interacting), or through designing new virtual devices of their own (learning by designing), such as a multigate field effect transistor, a quantum dot, a nanowire, or a molecular switch.

Unlike the common approach in which knowledge is told, these quantum simulations allow students to discover how tiny things behave through exploring the emergent behaviors of the microelectronic systems. For example, photon absorption and stimulate emission emerge from a quantum dynamics simulation of a bound electron and a laser. It also allows students to discover that it is the frequency of the laser, not the intensity, that determines these important processes. Another example is related to the core of chemistry. Our quantum dynamics simulator can be used to model how electron cloud changes when an atom is polarized (see the left part of the image on the left). When the user moves the nucleus closer, there is a dramatic change of the electron cloud--it now covers both nuclei. This causes a strong binding of two nuclei through the electron cloud, which is called the covalent bonding. When the user applies an external electric field (other than that of a point charge), it will also cause polarization. When the intensity of the field increases to a certain extent, the electron cloud will be stripped away from the nucleus--a phenomenon that we call ionization. It is fascinating to see that these fundamental concepts in chemistry just emerge from our quantum dynamics simulations! (see this page for more information.) These seemingly disparate concepts can be learned with a single, coherent picture of moving electron cloud in our simulations. The technology provides us a fresh opportunity to look at the reductionist approach, which advocates teaching fewer but more fundamental scientific principles and deriving other knowledge based on them (also see a recent article "How less can be more" by Bob Tinker).

In addition to the quantum dynamics simulator, we are also building a user interface that students can use to design systems such as a chemical reaction or a nanoscale circuit board.

These virtual experiments and virtual designs provide an accessible way to learning quantum phenomena. After all, a large part of the difficulty in understanding quantum phenomena stems from trying to explain microscopic things using our everyday experience, among some other philosophical issues that technical and engineering students may not care. If this obstacle is removed, understanding quantum phenomena should not be much more difficult than understanding water waves and optics. Computer models just streamline this learning process, as if students had a powerful, ultrafast microscope that can be used to look into the micro world. The visualization of how a nanoelectronic device works will help students understand the mechanism, just like a video that shows how air flows in a wind tunnel. Creating virtual devices and observing their properties will allow students to apply their knowledge and further enhance their learning, just like designing a stream table and then running water through it. Through this intimate interaction with a salient simulated micro world, students will learn more deeply than the traditional treatment through the standard teaching approach used in a textbook of solid state physics or chemistry, which either attempts to teach quantum concepts through daunting formalism or static illustrations, or completely avoids them.

It is important to point out that, although we do not try to teach the formalism of quantum mechanics, we use the theory to create the simulation tool. Our quantum dynamics simulation engine behind the user interface is based on numerically solving the time-dependent Schrodinger equation, and our computational method is based on cutting-edge research in computational physics (e.g., a speedy finite-difference time-domain method and novel boundary conditions). Because of this, our tool delivers accurate simulations that correctly depict the spatial distribution and the time evolution of electrons. This is very important, because it ensures the quality and scientific integrity of our simulations.

Image captions: 1) A quantum corral (click here to launch the model). 2) The probability wave just in the middle of a quantum tunneling event (click here to launch the model). 3) The electron clouds in the polarization of an atom and the formation of a covalent bond (click here to launch the model). 4) A nano star coupler that splits an input signal into three output signals (click here to launch the model).

Multicore computing: now and future

2008-11-11T18:09:00.000-05:00

Moore's Law has been the golden rule in predicting the increasing of personal computing power for more than a decade, but change has arrived. A couple of years ago, Amdahl's Law became the governing law (without an inauguration). Multicore computing is now the critical driven force of computer performance. As of October 2008, the 7400-series "Dunnington" of Intel's Xeon offers hexa-core capacity.

The trend is, knowing it or not, computers will have more cores and your personal computer will rival the computing power of a supercomputer defined by the government only a decade ago. There are, of course, some debates going on among CPU designers whether to make a personal computer something like a shiny iPhone box, or to make it a little machine that can easily crack the current military code (http://www.eetimes.com/showArticle.jhtml?articleID=206105179). This is a critical decision that will affect the architecture of future computers: will the future generation of CPUs be a bundle of different special-purpose cores, or will they will be made of homogeneous, generic cores that can be assigned any task? (Or, maybe they should be the combination of the special-purpose cores such as GPUs and generic cores, as that seems to be the way our brains work.)

As a software developer, I clearly want to have more generic cores, as they are apparently my power base. One could suggest that a developer can try to access the power of things like a GPU (as folding@home seems to be doing well with), but the real questions are: (1) Do we really want to learn those lower-level libraries for each type of the special-purpose cores, in order to use them? (2) Do we really want our applications to be bound to special-purpose cores, which raises the cross-platform issues?

On the one hand, if a CPU comes with a lot of power that cannot be easily harnessed by an average programmer, then it will become only a few elite developers' privilege. On the other hand, if average programmers like me cannot come up with a convincing argument that we can develop killer applications if we are given more generic power, then the industry has the right reason to doubt that generic power will be useful to the vast majority of people out there.

So, can we come up with some cool ideas how multicore computing may be good to average people like Joe and Jane (not just offering dream machines to evil hackers --- for them to break into our bank accounts)?

I feel it is not easy to present a clear example of how I would use a 128-core CPU predicted to be available on a single notebook machine in less than 10 years (note that each core will surely run faster than the ones currently in your dual-core CPU --- just imagine the power we will have at our fingers). It is hard for me to imagine an application that will invoke 128 processes simultaneously at any time. But I recognize that I am probably in a mind block. The fact that I cannot see the big picture now simply does not mean it does not exist.

My background as a computational physicist gave me some hints of how things might develop. Parallel computing is essential in solving many scientific problems that involve huge calculations. Computational scientists are used to think in the language of parallelism. So a 128-core computer is nothing new for them. It is just a shared-memory supercomputer condensed to a laptop box.

Molecular dynamics is a "lab rat" for parallel computing research, because it is relatively simple to implement and study. Given the fact that the Molecular Workbench does molecular dynamics on a personal computer, it may be a wonderful candidate for us to make a highly relevant case.

The Molecular Workbench currently benefits from multicore computing in two ways. First, there exists embarrassingly parallel problems that automatically utilize this power. For example, one can do multiple simulations at the same time. If there are enough cores available, each will run on a core independently. This needs no extra work from the programmer, because a simulation runs on a thread that is assigned by the JVM and OS to a core. It is interesting to note that the model containers in the Molecular Workbench could provide a way to decompose a larger system, if the simulations are synchronized by communication among them through scripts.

Second, the graphics part of a simulation is handled in a different thread than the calculation thread. Therefore, a single simulation can have its molecular dynamics calculations running on one core, and the graphics running asynchronously on another. This is most helpful when the refreshing rate needs to be high to render the motion smoothly.

The Java molecular dynamics code of the Molecular Workbench, however, has not been parallelized. I have been playing with java.util.concurrent to parallelize it, but at this point, it seems the gain won't be measurable (if positive at all!) if we only have two cores, as is the case of most personal computers as of today. The overhead cost of task coordination may be higher than what it worths.

But suppose I had a 128-core CPU to back my pool of simulation threads, the story I am writing could be quite different.

Besides scientific simulations, 3D navigation environments such as SecondLife would also benefit enormously from multicore computing. The process of landscape download and construction can be easily decomposed into chunks and assigned to different cores.

Can photonics simulations be useful to advanced technical education?

2008-11-09T08:15:00.000-05:00

Photonics is a difficult subject because it involves electromagnetism that is basically an invisible and unintuitive world to many students. Yet this is a promising and thriving technical field where many jobs are being created.

Computer simulation of light propagation in medium has become an important part in the design of optical waveguides, photonic circuits and optical fiber communication units. Commercial tools such as those developed by Optiwave have been widely used in industry. These tools and methods may also be very useful in helping students develop intuition ans sense about photonics.

Theoretical photonics is largely based on the numerical solution of the Maxwell equation, which governs light propagation. Solving the Maxwell equation for different system configurations is by no mean a trivial task. Many approximations have been developed. Each is good at solving a particular type of problem. Most of them are based on either the finite element method (FEM) or the finite difference method (FDM). Among them, the beam propagation method (BPM) is one that was specifically developed to simulate light propagation in waveguides. It gives reasonably accurate results that can provide useful guidance to designing optimal photonic circuits.

BPM seems to be an attractive candidate of teaching tool in that it can be used to build salient (that is, interactive and dynamic) simulations that show h0w things work in photonic devices. A playful environment that allows students to build circuits and run simulations to see how light travels through them may be very instructive and attractive to students.

The following pictures show a BPM 2D simulation of a photonic parallel circuit (many real engineering problems can be reduced to 2D based on the effective index method). Note that there are some loss due to the twist of the two branches where they split and join.

Integrating simulations in SecondLife/Wonderland?

2008-11-02T17:35:00.000-05:00

SecondLife has drawn extensive interest among educators. It is an attractive immersive environment for multiple users to interact with each other through navigating in an interesting 3D landscape. SecondLife represents the latest effort of developing 3D Internet, which, as opposed to the conventional page-by-page Internet, provides a novel mechanism to display information in a more interesting way beyond text, images, animations and applets interspersed in a 2D layout.

Although SecondLife is very interesting, it currently does not allow an author to embed an existing simulation in its environment. The media support is currently limited to text (animated or not), images and movies. Considering the fact that there exists a vast number of simulations on the Internet written in Java and C++, including those offered by the Molecular Workbench (http://mw.concord.org), it would be nice if one day we can see the user interacts with a simulation hung on a whiteboard inside SecondLife. We can imagine that there will be a virtual math and science musuem. Students will "walk" into rooms that have different exhibits, explore the wonderful models by pushing various buttons and observing what happens, and discuss with people in the same room about it --- pretty much like their real experience when they go to a real museum.

I think it is unlikely that SecondLife itself would offer simulations that are content-specific, such as those offfered by the Molecular Workbench. The SecondLife community will have to rely on the domain experts to fill in the real stuff. So it seems to me that the best strategy is to make Java work in SecondLife and provide a plugin service for C++ applications.

Wonderland (https://lg3d-wonderland.dev.java.net/) is a toolkit developed by Sun Microsystem that rivals SecondLife. Wonderland is particularly interesting because Open Office works within it. As a result, multiple users can work on the same Open Office document projected onto a whiteboard in Wonderland. If an application as complex as Open Office can work within Wonderland, there is every reason that we should believe Java should just work without a problem in Wonderland. Wonderland, therefore, may seem a very attractive option for developing a virtual museum as described above.

There are many technical issues about integrating a compute-intensive simulation with a compute-intensive immersive environment. Some of the problems will automatically go away as multicore computers become more powerful and more available. Some won't without substantial work in figuring out better ways of synchronizing a simulation for multiple users and synthesizing their inputs.