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Concentrated Solar Startup Sets a New Efficiency Record
Semprius, a startup that makes miniscule solar cells capable of capturing concentrated sunlight without costly cooling systems, announced this week that it had made the world's most efficient solar panel.
The company's solar panels use tiny solar cells made of gallium arsenide—the record-breaking solar module contains hundreds of such solar cells, each about the width of a line drawn by a ball-point pen, arranged under lenses that concentrate sunlight 1,100 times.
Gallium arsenide is far better at absorbing sunlight than silicon, the material used in most solar cells, but it's also more expensive. Furthermore, although concentrated solar modules use less semiconducting material, they usually require expensive optics, cooling systems, and tracking systems to keep them aimed at the sun. Semprius's microscaled solar cells are inherently much better at dissipating heat, making them cheaper.
Semprius's modules have another advantage: whereas a silicon solar cell only efficiently absorbs a narrow band of sunlight, the solar cells in this module are made of three layers of gallium arsenide, each modified to convert a different part of the solar spectrum into electricity.
Tests by a third-party certified the efficiency of Semprius's solar panel at 33.9 percent, marking the first time any solar
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Smart paint could revolutionize structural safety
An innovative low-cost smart paint that can detect microscopic faults in wind turbines, mines and bridges before structural damage occurs is being developed by researchers at the University of Strathclyde in Glasgow, Scotland.
The environmentally-friendly paint uses nanotechnology to detect movement in large structures, and could shape the future of safety monitoring.
Traditional methods of assessing large structures are complex, time consuming and use expensive instrumentation, with costs spiraling into millions of pounds each year.
However, the smart paint costs just a fraction of the cost and can be simply sprayed onto any surface, with electrodes attached to detect structural damage long before failure occurs.
Dr Mohamed Saafi, of the University's Department of Civil Engineering, said: "The development of this smart paint technology could have far-reaching implications for the way we monitor the safety of large structures all over the world.
"There are no limitations as to where it could be used and the low-cost nature gives it a significant advantage over the current options available in the industry. The process of producing and applying the paint also gives it an advantage as no expertise is required and monitoring itself is straightforward."
The paint is formed using a recycled waste product
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Stanford pioneering a wireless electric highway
A Stanford University research team has designed a high-efficiency charging system that uses magnetic fields to wirelessly transmit large electric currents between metal coils placed several feet apart. The long-term goal of the research is to develop an all-electric highway that wirelessly charges cars and trucks as they cruise down the road.The new technology has the potential to dramatically increase the driving range of electric vehicles and eventually transform highway travel, according to the researchers. Their results are published in the journal Applied Physics Letters (APL). "Our vision is that you'll be able to drive onto any highway and charge your car," said Shanhui Fan, an associate professor of electrical engineering. "Large-scale deployment would involve revamping the entire highway system and could even have applications beyond transportation."Driving rangeA wireless charging system would address a major drawback of plug-in electric cars – their limited driving range. The all-electric Nissan Leaf, for example, gets less than 100 miles on a single charge, and the battery takes several hours to fully recharge.A charge-as-you-drive system would overcome these limitations. "What makes this concept exciting is that you
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A New Study Shows How to Boost the Power of Pain Relief, Without Drugs
Placebos reduce pain by creating an expectation of relief. Distraction—say, doing a puzzle—relieves it by keeping the brain busy. But do they use the same brain processes? Neuromaging suggests they do. When applying a placebo, scientists see activity in the dorsolateral prefrontal cortex. That’s the part of the brain that controls high-level cognitive functions like working memory and attention—which is what you use to do that distracting puzzle.
Now a new study challenges the theory that the placebo effect is a high-level cognitive function. The authors—Jason T. Buhle, Bradford L. Stevens, and Jonathan J. Friedman of Columbia University and Tor D. Wager of the University of Colorado Boulder—reduced pain in two ways – either by giving them a placebo, or a difficult memory task. lacebo. But when they put the two together, “the level of pain reduction that people experienced added up. There was no interference between them,” says Buhle. “That suggests they rely on separate mechanisms.” The findings, published in Psychological Science, a journal of the Association for Psychological Science, could help clinicians maximize pain relief without drugs.
In the study, 33 participants came in for three separate sessions. In the
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Decoding brain waves to eavesdrop on what we hear
BERKELEY — Neuroscientists may one day be able to hear the imagined speech of a patient unable to speak due to stroke or paralysis, according to University of California, Berkeley, researchers.
These scientists have succeeded in decoding electrical activity in the brain’s temporal lobe – the seat of the auditory system – as a person listens to normal conversation. Based on this correlation between sound and brain activity, they then were able to predict the words the person had heard solely from the temporal lobe activity.
“This research is based on sounds a person actually hears, but to use it for reconstructing imagined conversations, these principles would have to apply to someone’s internal verbalizations,” cautioned first author Brian N. Pasley, a post-doctoral researcher in the center. “There is some evidence that hearing the sound and imagining the sound activate similar areas of the brain. If you can understand the relationship well enough between the brain recordings and sound, you could either synthesize the actual sound a
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MIT Researchers Find a Way To Make Solar Panels from Grass Clippings
What if generating solar energy at home required little more than mixing some grass clippings with inexpensive chemicals? That’s exactly what MIT researcher Andreas Mershin has found to be the case. The scientist says creating a solar cell could be as easy as mixing any green organic material (grass clippings, agricultural waste) with a bag of custom chemicals and painting the mixture on a roof. Once the efficiency of Mershin’s system is improved, this type of solar technology could make cheap energy available in rural places and developing countries where people don’t have access to affordable energy. Read on to see a video of Mershin’s findings.
Here at Inhabitat, we’ve been following biophotovoltaics — devices that generate energy from photosynthesis — and although the possibilities are limitless, most of the existing technology is very expensive and a long way from reaching the market. In a study published in Scientific Reports (http://www.nature.com/srep/2012/120202/srep00234/full/srep00234.html), Mershin and his fellow researchers have come up with a process to “hijack” the PS-I molecules that are responsible for photosynthesis. As Mershin explains in this video, in order to get these molecules to work for us, we must extract the protein that’s at the center
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Pacemakers of tomorrow could be powered by the beating of the heart
A heart-powered pacemaker may sound counter-intuitive, but in essence this is precisely what aerospace engineers from the University of Michigan are proposing. The engineers have come up with a prototype powered by vibrations in the chest cavity vibrations which are caused mainly by the beating of the heart.
Unfortunately the explanation being circulated is somewhat hazy, but it seems that this prototype employs piezoelectric material which can generate electricity when undergoing mechanical stresses, such as those caused by these naturally occurring vibrations in the chest.
Better news still is that the energy harvested from the chest is always more than is required to power a pacemaker, and typically by a factor of eight. Since pacemakers apparently only require 1 millionth of a watt to run, perhaps this shouldn't be all that surprising. Further, the device operates at heart rates ranging from seven to 700 beats per minute, comfortably encompassing the required range.
If viable, one day the technology could conceivably negate the need for surgery to replace pacemakers with dead batteries. The prototypes to date are not biocompatible, so don't expect to see effectively self-powered pacemakers any time soon. The team's findings were published in the American
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Artificial intelligence: Getting better at the age guessing game
Scientists are developing artificial intelligence solutions for image processing, which have applications in many areas including advertising, entertainment, education and healthcare. They have, for example, developed computer algorithms for facial age classification — the automated assignment of individuals to predefined age groups based on their facial features as seen on video captures or still images.
Improving the accuracy of facial age classification, however, is not easy. A person can teach a computer to make better guesses by running its algorithm through a large database of facial images of which the age is known using sets of labeled images, but acquiring such a database can be both time-consuming and expensive. The process might even breach privacy in certain countries. Jian-Gang Wang at the A*STAR Institution for Infocomm Research and co-workers have now developed an algorithm called incremental bilateral two-dimensional linear discriminant analysis (IB2DLDA) that could overcome such problems.
The researchers designed IB2DLDA so that it actively ‘learns’. The algorithm first processes a small pool of labeled images, and then iteratively selects the most informative samples from a large pool of unlabeled images to query the
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