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Researchers solve longstanding problem in measuring semiconductor defects

Researchers at Sandia National Laboratories and Auburn University have developed a new method to more accurately detect atomic-scale defects in electronic materials, an advance that could help improve technologies ranging from electric vehicles to high-power electronics. The study, appearing in the Journal of Applied Physics, addresses a longstanding challenge in understanding what happens at the critical boundary where a semiconductor meets an insulating layer.

At this interface, microscopic defects can trap electrical charge and quietly reduce device performance, even when the device otherwise appears to function normally. These defects can limit efficiency, increase electrical losses, and reduce the performance of advanced semiconductor devices.

Scientists commonly study these defects by comparing how a device responds to slow and fast electrical signals. However, the technique depends on knowing a key device property, the insulator capacitance, with very high accuracy. Even tiny errors can produce misleading results, sometimes making it appear that far more defects exist than are actually present.

Visualizing sound: Scientists reveal hidden behaviors of sound waves

An international team of scientists has developed a new analysis of how sound waves behave, revealing surprising effects that have largely been overlooked for decades. In the new paper in Scientific Reports, which was led by researchers from City St George’s, University of London, the team explored how sound waves move through air and how those movements might be perceived visually.

Sound travels as a longitudinal wave, meaning air molecules vibrate back and forth rather than moving up and down like waves in a violin string. These vibrations are usually assumed to be smooth and regular, and as a physical phenomenon they form the basis of acoustics and some forms of seismic transmission. However, the new theoretical analysis of physical longitudinal wave motion reveals that the behavior of sound waves changes dramatically when they become stronger (i.e. above 160 dB at 10 kHz, which is similar to the noise level inside a high-pitched jet engine), and the prior assumptions are only true for moderate sounds.

Using computer simulations, the researchers—namely Professor Christopher Tyler and Professor Joshua Solomon at City St George’s and Professor Stuart M. Anstis from the University of California, San Diego—created animations where each dot represents an air molecule. Each dot moves back and forth in place, slightly out of step with its neighbors. This tiny delay between dots creates the appearance of a wave traveling through space as the dots move back and forth in place, just as sound does in real life.

How everyday devices could train AI faster while keeping personal data on-device

A new method developed by MIT researchers can accelerate a privacy-preserving artificial intelligence training method by about 81%. This advance could enable a wider array of resource-constrained edge devices, like sensors and smartwatches, to deploy more accurate AI models while keeping user data secure.

The MIT researchers boosted the efficiency of a technique known as federated learning, which involves a network of connected devices that work together to train a shared AI model.

In federated learning, the model is broadcast from a central server to wireless devices. Each device trains the model using its local data and then transfers model updates back to the server. Data are kept secure because they remain on each device.

Scientists develop near-invisible solar cells that could turn windows into power generators

Imagine a car whose windows and sunroof can help top up its battery while parked under the sun, or a pair of smart glasses whose lenses can harvest light to power built-in electronics.

Such applications could become more feasible with a new type of ultrathin transparent solar cell developed by scientists from Nanyang Technological University, Singapore (NTU Singapore).

Led by Associate Professor Annalisa Bruno, the NTU researchers created perovskite solar cells that are about 10,000 times thinner than a strand of human hair and around 50 times thinner than conventional perovskite solar cells.

The DOJ Is Demanding Apple And Google Identify Over 100,000 Users Of This Car App

In the letter, EZ Lynk lawyers wrote that Apple and Google are planning to fight the subpoenas. Walmart declined to comment. None of the other companies subpoenaed responded to a comment request.

“These requests for potentially hundreds of thousands of people’s PII go well beyond the needs of this case and create serious privacy concerns,” wrote EZ Lynk’s lawyers in the letter. “Investigating this claim does not require identifying each person who has used the product.”

The government said in the letter its request for data was fair and appropriate, and it had “consistently sought customer information” because its lawyers want to interview witnesses about their use of EZ Lynk’s technology. It has already presented evidence to the court of people using the company’s tools to remove emissions controls on their cars, including Facebook and EZ Lynk forum posts outlining that use of the product.

Brighter red micro-LEDs could help solve full-color display stability challenge

Researchers at The University of Osaka, in collaboration with Ritsumeikan University, have demonstrated that growing europium-doped gallium nitride (Eu-doped GaN) on a semipolar crystal plane dramatically improves red light emission. The team found that this approach selectively promotes the formation of highly efficient Eu luminescent centers, resulting in red emission intensity more than 3.6 times higher than that of conventionally grown polar-plane material.

The study is published in the journal Applied Physics Letters.

Red emitters based on Eu-doped GaN are attracting attention as promising light sources for next-generation micro-LED displays because they can provide narrow-linewidth, wavelength-stable red emission based on intra-4f-shell transitions of Eu ions. This is particularly important for full-color monolithic integration with blue and green InGaN LEDs, where wavelength stability under device operation is essential.

Godfather of AI: How To Make Safe Superintelligent AI

The co-inventor of modern AI and the most cited living scientist believes he’s figured out how to ensure AI is honest, incapable of deception, and never goes rogue. Yoshua Bengio – Turing Award Winner and founder of LawZero – is disturbed by the many unintended drives and goals present in today’s AIs, their ability to tell when they’re being tested, and demonstrated willingness to lie. AI companies are trying to stamp these out in a ‘cat-and-mouse game’ that Yoshua fears they’re losing.

But Yoshua is optimistic: he believes the companies can win this battle decisively with a single rearrangement to how AI models are trained, and has been developing mathematical proofs to back up the claim. The core idea is that instead of training AI to predict what a human would say, or to produce responses we’d rate highly, we should train it to model what’s actually true.

Learn more & full transcript: https://80k.info/bengio.

Yoshua argues this new architecture, which he calls “Scientist AI,” is a small enough change that we could keep almost all the techniques and data we use to train frontier AIs like Claude and ChatGPT. And that the new architecture need not cost more, could be built iteratively, and might be more capable as well as more honest.

Until recently, the biggest practical objection to Scientist AI was simple: the world wants agents, and Scientist AI isn’t one. But in new research, Yoshua has extended the design and believes the same honest predictor can be turned into a capable agent without losing its \.

Photonics advance could enable compact, high-performance lidar sensors

Lidar systems use pulses of infrared light to measure distance and map a 3D scene with high resolution, allowing autonomous vehicles to rapidly react to obstacles that appear in their path. But traditional lidar sensors are expensive, bulky systems with many moving parts that degrade over time, limiting how the sensors can be deployed.

A new study from MIT researchers could help to enable next-generation lidar sensors that are compact, durable, and have no moving parts. The key advance is a novel design for a silicon-photonics chip, which is a semiconductor device that manipulates light rather than electricity.

Typically, such silicon-photonics chip-based systems have a restricted field of view, so a silicon-photonics-based lidar would not be able to scan angles in the periphery. Existing workarounds to this problem increase noise and hamper precision.

Magnetic checkerboard separates microparticles by size and sends them along different paths

A team of researchers from the Universities of Tübingen, Bayreuth, and Kassel, and the Polish Academy of Sciences has developed a method for precisely controlling the movement of magnetic microparticles based on their size. These suspended particles, known as colloidal particles, range in size from a few tens of nanometers to several micrometers. Controlling them is important for applications such as drug delivery, medical laboratory tests, and the synthesis of new materials. The team’s study has now been published in Physical Review Letters.

The new method involves positioning microparticles above a magnetic layer that is patterned like a chessboard. In previous studies, magnetic transportation of the colloidal particles was limited to a specific height. At this distance, although the magnetic forces appear to balance each other out, the particles move regardless of their size. Therefore, it was not possible to control the particles specifically based on their size.

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