'Invisibility': Key to Better Electronics?

'Invisibility': Key to Better Electronics?

  11:07:00 AM    Science Lover

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Visual 'Cloaking' Technology Enables More Efficient Transfer of Electrons

 A new approach that allows objects to become "invisible" has now been applied to an entirely different area: letting particles "hide" from passing electrons, which could lead to more efficient thermoelectric devices and new kinds of electronics.

Diagram shows the 'probability flux' of electrons, a 
representation of the paths of electrons as they pass through 
an 'invisible' nanoparticle. While the paths are bent as 
they enter the particle, they are subsequently bent back 
so that they re-emerge from the other side on the same 
trajectory they started with — just as if the particle 
wasn't there. (Credit: Image courtesy Bolin Liao et al.)

The concept -- developed by MIT graduate student Bolin Liao, former postdoc Mona Zebarjadi (now an assistant professor at Rutgers University), research scientist Keivan Esfarjani, and mechanical engineering professor Gang Chen -- is described in a paper in the journal Physical Review Letters.

Normally, electrons travel through a material in a way that is similar to the motion of electromagnetic waves, including light; their behavior can be described by wave equations. That led the MIT researchers to the idea of harnessing the cloaking mechanisms developed to shield objects from view -- but applying it to the movement of electrons, which is key to electronic and thermoelectric devices.

Previous work on cloaking objects from view has relied on so-called metamaterials made of artificial materials with unusual properties. The composite structures used for cloaking cause light beams to bend around an object and then meet on the other side, resuming their original path -- making the object appear invisible.

"We were inspired by this idea," says Chen, the Carl Richard Soderberg Professor of Power Engineering at MIT, who decided to study how it might apply to electrons instead of light. But in the new electron-cloaking material developed by Chen and his colleagues, the process is slightly different.

The MIT researchers modeled nanoparticles with a core of one material and a shell of another. But in this case, rather than bending around the object, the electrons do actually pass through the particles: Their paths are bent first one way, then back again, so they return to the same trajectory they began with.

In computer simulations, the concept appears to work, Liao says. Now, the team will try to build actual devices to see whether they perform as expected. "This was a first step, a theoretical proposal," Liao says. "We want to carry on further research on how to make some real devices out of this strategy."

While the initial concept was developed using particles embedded in a normal semiconductor substrate, the MIT researchers would like to see if the results can be replicated with other materials, such as two-dimensional sheets of graphene, which might offer interesting additional properties.

The MIT researchers' initial impetus was to optimize the materials used in thermoelectric devices, which produce an electrical current from a temperature gradient. Such devices require a combination of characteristics that are hard to obtain: high electrical conductivity (so the generated current can flow freely), but low thermal conductivity (to maintain a temperature gradient). But the two types of conductivity tend to coexist, so few materials offer these contradictory characteristics. The team's simulations show this electron-cloaking material could meet these requirements unusually well.

The simulations used particles a few nanometers in size, matching the wavelength of flowing electrons and improving the flow of electrons at particular energy levels by orders of magnitude compared to traditional doping strategies. This might lead to more efficient filters or sensors, the researchers say. As the components on computer chips get smaller, Chen says, "we have to come up with strategies to control electron transport," and this might be one useful approach.

The concept could also lead to a new kind of switches for electronic devices, Chen says. The switch could operate by toggling between transparent and opaque to electrons, thus turning a flow of them on and off. "We're really just at the beginning," he says. "We're not sure how far this is going to go yet, but there is some potential" for significant applications.

Xiang Zhang, a professor of mechanical engineering at the University of California at Berkeley who was not involved in this research, says "this is very exciting work" that expands the concept of cloaking to the domain of electrons. The authors, he says, "uncovered a very interesting approach that may be very useful to thermoelectric applications."

This research was funded by the U.S. Department of Energy (DOE) through MIT's Solid-State Solar-Thermal Energy Conversion center, a DOE Energy Frontier Research Center.

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Mimicking the Brain -- In Silicon: New Computer Chip Models How Neurons Communicate With Each Other at Synapses

Mimicking the Brain -- In Silicon: New Computer Chip Models How Neurons Communicate With Each Other at Synapses

  1:39:00 PM    Science Lover

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For decades, scientists have dreamed of building computer systems that could replicate the human BRAIN's talent for learning new tasks.

Researchers have taken a major step toward that goal by designing a computer chip that mimics how the brain's neurons adapt in response to new information. (Credit: MIT)

MIT researchers have now taken a major step toward that goal by designing a computer chip that mimics how the brain's neurons adapt in response to new information. This phenomenon, known as plasticity, is believed to underlie many brain functions, including learning and memory.

With about 400 transistors, the silicon chip can simulate the activity of a single brain synapse -- a connection between two neurons that allows information to flow from one to the other. The researchers anticipate this chip will help neuroscientists learn much more about how the brain works, and could also be used in neural prosthetic devices such as artificial retinas, says Chi-Sang Poon, a principal research scientist in the Harvard-MIT Division of Health Sciences and Technology.

Poon is the senior author of a paper describing the chip in the Proceedings of the National Academy of Sciences the week of Nov. 14. Guy Rachmuth, a former postdoc in Poon's lab, is lead author of the paper. Other authors are Mark Bear, the Picower Professor of Neuroscience at MIT, and Harel Shouval of the University of Texas Medical School.

Modeling synapses

There are about 100 billion neurons in the brain, each of which forms synapses with many other neurons. A synapse is the gap between two neurons (known as the presynaptic and postsynaptic neurons). The presynaptic neuron releases neurotransmitters, such as glutamate and GABA, which bind to receptors on the postsynaptic cell membrane, activating ion channels. Opening and closing those channels changes the cell's electrical potential. If the potential changes dramatically enough, the cell fires an electrical impulse called an action potential.

All of this synaptic activity depends on the ion channels, which control the flow of charged atoms such as sodium, potassium and calcium. Those channels are also key to two processes known as long-term potentiation (LTP) and long-term depression (LTD), which strengthen and weaken synapses, respectively.

The MIT researchers designed their computer chip so that the transistors could mimic the activity of different ion channels. While most chips operate in a binary, on/off mode, current flows through the transistors on the new brain chip in analog, not digital, fashion. A gradient of electrical potential drives current to flow through the transistors just as ions flow through ion channels in a cell.

"We can tweak the parameters of the circuit to match specific ion channels," Poon says. "We now have a way to capture each and every ionic process that's going on in a neuron."

Previously, researchers had built circuits that could simulate the firing of an action potential, but not all of the circumstances that produce the potentials. "If you really want to mimic brain function realistically, you have to do more than just spiking. You have to capture the intracellular processes that are ion channel-based," Poon says.

The new chip represents a "significant advance in the efforts to incorporate what we know about the biology of neurons and synaptic plasticity onto CMOS [complementary metal-oxide-semiconductor] chips," says Dean Buonomano, a professor of neurobiology at the University of California at Los Angeles, adding that "the level of biological realism is impressive.

The MIT researchers plan to use their chip to build systems to model specific neural functions, such as the visual processing system. Such systems could be much faster than digital computers. Even on high-capacity computer systems, it takes hours or days to simulate a simple brain circuit. With the analog chip system, the simulation is even faster than the biological system itself.

Another potential application is building chips that can interface with biological systems. This could be useful in enabling communication between neural prosthetic devices such as artificial retinas and the brain. Further down the road, these chips could also become building blocks for artificial intelligence devices, Poon says.

Debate resolved

The MIT researchers have already used their chip to propose a resolution to a longstanding debate over how LTD occurs.

One theory holds that LTD and LTP depend on the frequency of action potentials stimulated in the postsynaptic cell, while a more recent theory suggests that they depend on the timing of the action potentials' arrival at the synapse.

Both require the involvement of ion channels known as NMDA receptors, which detect postsynaptic activation. Recently, it has been theorized that both models could be unified if there were a second type of receptor involved in detecting that activity. One candidate for that second receptor is the endo-cannabinoid receptor.

Endo-cannabinoids, similar in structure to marijuana, are produced in the brain and are involved in many functions, including appetite, pain sensation and memory. Some neuroscientists had theorized that endo-cannabinoids produced in the postsynaptic cell are released into the synapse, where they activate presynaptic endo-cannabinoid receptors. If NMDA receptors are active at the same time, LTD occurs.

When the researchers included on their chip transistors that model endo-cannabinoid receptors, they were able to accurately simulate both LTD and LTP. Although previous experiments supported this theory, until now, "nobody had put all this together and demonstrated computationally that indeed this works, and this is how it works," Poon says.

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Parts of Brain Can Switch Functions: In People Born Blind, Brain Regions That Usually Process Vision Can Tackle Language

Parts of Brain Can Switch Functions: In People Born Blind, Brain Regions That Usually Process Vision Can Tackle Language

  9:52:00 AM    Science Lover

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When your brain encounters sensory stimuli, such as the scent of your morning coffee or the sound of a honking car, that input gets shuttled to the appropriate brain region for analysis. The coffee aroma goes to the olfactory cortex, while sounds are processed in the auditory cortex.

MRI scan of brain. (Credit: iStockphoto)

 

That division of labor suggests that the brain's structure follows a predetermined, genetic blueprint. However, evidence is mounting that brain regions can take over functions they were not genetically destined to perform. In a landmark 1996 study of people blinded early in life, neuroscientists showed that the visual cortex could participate in a nonvisual function -- reading Braille.

Now, a study from MIT neuroscientists shows that in individuals born blind, parts of the visual cortex are recruited for language processing. The finding suggests that the visual cortex can dramatically change its function -- from visual processing to language -- and it also appears to overturn the idea that language processing can only occur in highly specialized brain regions that are genetically programmed for language tasks.

"Your brain is not a prepackaged kind of thing. It doesn't develop along a fixed trajectory, rather, it's a self-building toolkit. The building process is profoundly influenced by the experiences you have during your development," says Marina Bedny, an MIT postdoctoral associate in the Department of Brain and Cognitive Sciences and lead author of the study, which appears in the Proceedings of the National Academy of Sciences the week of Feb. 28.

Flexible connections

For more than a century, neuroscientists have known that two specialized brain regions -- called Broca's area and Wernicke's area -- are necessary to produce and understand language, respectively. Those areas are thought to have intrinsic properties, such as specific internal arrangement of cells and connectivity with other brain regions, which make them uniquely suited to process language.

Other functions -- including vision and hearing -- also have distinct processing centers in the sensory cortices. However, there appears to be some flexibility in assigning brain functions. Previous studies in animals (in the laboratory of Mriganka Sur, MIT professor of brain and cognitive sciences) have shown that sensory brain regions can process information from a different sense if input is rewired to them surgically early in life. For example, connecting the eyes to the auditory cortex can provoke that brain region to process images instead of sounds.

Until now, no such evidence existed for flexibility in language processing. Previous studies of congenitally blind people had shown some activity in the left visual cortex of blind subjects during some verbal tasks, such as reading Braille, but no one had shown that this might indicate full-fledged language processing.

Bedny and her colleagues, including senior author Rebecca Saxe, assistant professor of brain and cognitive sciences, and Alvaro Pascual-Leone, professor of neurology at Harvard Medical School, set out to investigate whether visual brain regions in blind people might be involved in more complex language tasks, such as processing sentence structure and analyzing word meanings.

To do that, the researchers scanned blind subjects (using functional magnetic resonance imaging) as they performed a sentence comprehension task. The researchers hypothesized that if the visual cortex was involved in language processing, those brain areas should show the same sensitivity to linguistic information as classic language areas such as Broca's and Wernicke's areas.

They found that was indeed the case -- visual brain regions were sensitive to sentence structure and word meanings in the same way as classic language regions, Bedny says. "The idea that these brain regions could go from vision to language is just crazy," she says. "It suggests that the intrinsic function of a brain area is constrained only loosely, and that experience can have really a big impact on the function of a piece of brain tissue."

Bedny notes that the research does not refute the idea that the human brain needs Broca's and Wernicke's areas for language. "We haven't shown that every possible part of language can be supported by this part of the brain [the visual cortex]. It just suggests that a part of the brain can participate in language processing without having evolved to do so," she says.

Redistribution

One unanswered question is why the visual cortex would be recruited for language processing, when the language processing areas of blind people already function normally. According to Bedny, it may be the result of a natural redistribution of tasks during brain development.

"As these brain functions are getting parceled out, the visual cortex isn't getting its typical function, which is to do vision. And so it enters this competitive game of who's going to do what. The whole developmental dynamic has changed," she says.

This study, combined with other studies of blind people, suggest that different parts of the visual cortex get divvied up for different functions during development, Bedny says. A subset of (left-brain) visual areas appears to be involved in language, including the left primary visual cortex.

It's possible that this redistribution gives blind people an advantage in language processing. The researchers are planning follow-up work in which they will study whether blind people perform better than sighted people in complex language tasks such as parsing complicated sentences or performing language tests while being distracted.

The researchers are also working to pinpoint more precisely the visual cortex's role in language processing, and they are studying blind children to figure out when during development the visual cortex starts processing language.
 

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A Plane That Lands Like a Bird

A Plane That Lands Like a Bird

  6:22:00 AM    Science Lover

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Everyone knows what it's like for an airplane to land: the slow maneuvering into an approach pattern, the long descent, and the brakes slamming on as soon as the plane touches down, which seems to just barely bring it to a rest a mile later. Birds, however, can switch from barreling forward at full speed to lightly touching down on a target as narrow as a telephone wire. Why can't an airplane be more like a bird?

A smoke visualization still of the actual vortex wake behind our glider during a free-flight high angle of attack landing. (Credit: Jason Dorfman/CSAIL)

MIT researchers have demonstrated a new control system that allows a foam glider with only a single motor on its tail to land on a perch, just like a pet parakeet. The work could have important implications for the design of robotic planes, greatly improving their maneuverability and potentially allowing them to recharge their batteries simply by alighting on power lines.

Birds can land so precisely because they take advantage of a complicated physical phenomenon called "stall." Even when a commercial airplane is changing altitude or banking, its wings are never more than a few degrees away from level. Within that narrow range of angles, the airflow over the plane's wings is smooth and regular, like the flow of water around a small, smooth stone in a creek bed.

A bird approaching its perch, however, will tilt its wings back at a much sharper angle. The airflow over the wings becomes turbulent, and large vortices -- whirlwinds -- form behind the wings. The effects of the vortices are hard to predict: If a plane tilts its wings back too far, it can fall out of the sky. Hence the name "stall."

The smooth airflow over the wings of a normally operating plane is well-understood mathematically; as a consequence, engineers are highly confident that a commercial airliner will respond to the pilot's commands as intended. But stall is a much more complicated phenomenon: Even the best descriptions of it are time-consuming to compute.

Reap the whirlwind

To design their control system, MIT Associate Professor Russ Tedrake, a member of the Computer Science and Artificial Intelligence Laboratory, and Rick Cory, a PhD student in Tedrake's lab who defended his dissertation this spring, first developed their own mathematical model of a glider in stall. For a range of launch conditions, they used the model to calculate sequences of instructions intended to guide the glider to its perch. "It gets this nominal trajectory," Cory explains. "It says, 'If this is a perfect model, this is how it should fly.'" But, he adds, "because the model is not perfect, if you play out that same solution, it completely misses."

So Cory and Tedrake also developed a set of error-correction controls that could nudge the glider back onto its trajectory when location sensors determined that it had deviated from it. By using innovative techniques developed at MIT's Laboratory for Information and Decision Systems, they were able to precisely calculate the degree of deviation that the controls could compensate for. The addition of the error-correction controls makes a trajectory look like a tube snaking through space: The center of the tube is the trajectory calculated using Cory and Tedrake's model; the radius of the tube describes the tolerance of the error-correction controls.

The control system ends up being, effectively, a bunch of tubes pressed together like a fistful of straws. If the glider goes so far off course that it leaves one tube, it will still find itself in another. Once the glider is launched, it just keeps checking its position and executing the command that corresponds to the tube in which it finds itself. The design of the system earned Cory Boeing's 2010 Engineering Student of the Year Award.

The measure of air resistance against a body in flight is known as the "drag coefficient." A cruising plane tries to minimize its drag coefficient, but when it's trying to slow down, it tilts its wings back in order to increase drag. Ordinarily, it can't tilt back too far, for fear of stall. But because Cory and Tedrake's control system takes advantage of stall, the glider, when it's landing, has a drag coefficient that's four to five times that of other aerial vehicles.

From spy planes to fairies

For some time, the U.S. Air Force has been interested in the possibility of unmanned aerial vehicles that could land in confined spaces and has been funding and monitoring research in the area. "What Russ and Rick and their team is doing is unique," says Gregory Reich of the Air Force Research Laboratory. "I don't think anyone else is addressing the flight control problem in nearly as much detail." Reich points out, however, that in their experiments, Cory and Tedrake used data from wall-mounted cameras to gauge the glider's position, and the control algorithms ran on a computer on the ground, which transmitted instructions to the glider. "The computational power that you may have on board a vehicle of this size is really, really limited," Reich says. Even though the MIT researchers' course correction algorithms are simple, they may not be simple enough.

Tedrake believes, however, that computer processors powerful enough to handle his and Cory's control algorithms are only a few years off. In the meantime, his lab has already begun to address the problem of moving the glider's location sensors onboard, and although Cory will be moving to California to take a job researching advanced robotics techniques for Disney, he hopes to continue collaborating with Tedrake. "I visited the air force, and I visited Disney, and they actually have a lot in common," Cory says. "The air force wants an airplane that can land on a power line, and Disney wants a flying Tinker Bell that can land on a lantern. But the technology's similar."

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