Lifeboat Foundation

Transistors are the building blocks of modern electronics, used in everything from televisions to laptops. As transistors have gotten smaller and more compact, so have electronics, which is why your cell phone is a super powerful computer that fits in the palm of your hand.

But there’s a scaling problem: Transistors are now so small that they are difficult to turn off. A key device element is the channel that charge carriers (such as electrons) travel across between electrodes. If that channel gets too short, quantum effects allow electrons to effectively jump from one side to another even when they shouldn’t.

One way to get past this sizing roadblock is to use layers of 2D materials—which are only a single atom thick—as the channel. Atomically thin channels can help enable even smaller transistors by making it harder for the electrons to jump between electrodes. One well-known example of a 2D material is graphene, whose discoverers won the Nobel Prize in Physics in 2010. But there are other 2D materials, and many believe they are the future of transistors, with the promise of scaling channel thickness down from its current 3D limit of a few nanometers (nm, billionths of a meter) to less than a single nanometer thickness.

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We’ve been hearing about the potential of graphene for decades, and yet very few of the big promises have come to pass. But a new aluminum graphene battery design is coming out this year that could charge a phone in less than a minute, and it may be the future of energy storage.

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Artificial Intelligence trained with first-person videos could better understand our world. At Meta, AR and AI development intersect in this space.

In the run-up to the CVPR 2022 computer vision conference, Meta is releasing the “Project Aria Pilot Dataset,” with more than seven hours of first-person videos spread across 159 sequences in five different locations in the United States. They show scenes from everyday life – doing the dishes, opening a door, cooking, or using a smartphone in the living room.

AI training for everyday life.

The spyware has been used to target people in Italy, Kazakhstan, and Syria, researchers at Google and Lookout have found.

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Unfortunately my internet link went down in the second Q&A session at the end and the recording cut off. Shame, loads of great information came out about FPGA/ASIC implementations, AI for the VR/AR, C/C++ and a whole load of other riveting and most interesting techie stuff. But thankfully the main part of the talk was recorded.

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From there, they ran flight tests using a specially designed motion-tracking system. Each electroluminescent actuator served as an active marker that could be tracked using iPhone cameras. The cameras detect each light color, and a computer program they developed tracks the position and attitude of the robots to within 2 millimeters of state-of-the-art infrared motion capture systems.

“We are very proud of how good the tracking result is, compared to the state-of-the-art. We were using cheap hardware, compared to the tens of thousands of dollars these large motion-tracking systems cost, and the tracking results were very close,” Kevin Chen says.

In the future, they plan to enhance that motion tracking system so it can track robots in real-time. The team is working to incorporate control signals so the robots could turn their light on and off during flight and communicate more like real fireflies. They are also studying how electroluminescence could even improve some properties of these soft artificial muscles, Kevin Chen says.

Scientists at the Institute of Applied Physics at TU Dresden have come a step closer to the vision of a broad application of flexible, printable electronics. The team around Dr. Hans Kleemann has succeeded for the first time in developing powerful vertical organic transistors with two independent control electrodes. The results have recently been published in the renowned online journal Nature Communications.

High-definition roll-up televisions or foldable smartphones may soon no longer be unaffordable luxury goods that can be admired at international electronics trade fairs. High-performance organic transistors are a key necessity for the mechanically flexible electronic circuits required for these applications. However, conventional horizontal organic thin-film transistors are very slow due to the hopping-transport in organic semiconductors, so they cannot be used for applications requiring high frequencies. Especially for logic circuits with low power consumption, such as those used for Radio Frequency Identification (RFID), it is mandatory to develop transistors enabling high operation frequency as well as adjustable device characteristics (i.e., threshold-voltage). The research group Organic Devices and Systems (ODS) at the Dresden Integrated Center for Applied Photophysics (IAPP) of the Institute of Applied Physics headed by Dr.

Biometric authentication like fingerprint and iris scans are a staple of any spy movie, and trying to circumvent those security measures is often a core plot point. But these days the technology is not limited to spies, as fingerprint verification and facial recognition are now common features on many of our phones.

Now, researchers have developed a new potential odorous option for the biometric security toolkit: your breath. In a report published in Chemical Communications, researchers from Kyushu University’s Institute for Materials Chemistry and Engineering, in collaboration with the University of Tokyo, have developed an olfactory sensor capable of identifying individuals by analyzing the compounds in their breath.

Combined with machine learning, this “artificial nose,” built with a 16-channel sensor array, was able to authenticate up to 20 individuals with an average accuracy of more than 97%.

When our phones and computers run out of power, their glowing screens go dark and they die a sort of digital death. But switch them to low-power mode to conserve energy, and they cut expendable operations to keep basic processes humming along until their batteries can be recharged.

Our energy-intensive brain needs to keep its lights on too. Brain cells depend primarily on steady deliveries of the sugar glucose, which they convert to adenosine triphosphate (ATP) to fuel their information processing. When we’re a little hungry, our brain usually doesn’t change its energy consumption much. But given that humans and other animals have historically faced the threat of long periods of starvation, sometimes seasonally, scientists have wondered whether brains might have their own kind of low-power mode for emergencies.

Now, in a paper published in Neuron in January, neuroscientists in Nathalie Rochefort’s lab at the University of Edinburgh have revealed an energy-saving strategy in the visual systems of mice. They found that when mice were deprived of sufficient food for weeks at a time — long enough for them to lose 15%-20% of their typical healthy weight — neurons in the visual cortex reduced the amount of ATP used at their synapses by a sizable 29%.