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Advanced system-on-chip designs are extremely complex in terms of transistor count and are hard to build using the latest fabrication processes. In a bid to make production of next-generation chips economically feasible, chip fabs need to ensure high yields early in their lifecycle by quickly finding and correcting defects.

But finding and fixing defects is not easy today, as traditional optical inspection tools don’t offer sufficiently detailed image resolution, while high-resolution e-beam and multibeam inspection tools are relatively slow. Looking to bridge the gap on inspection costs and time, Applied Materials has been developing a technology called ExtractAI technology, which uses a combination of the company’s latest Enlight optical inspection tool, SEMVision G7 e-beam review system, and deep learning (AI) to quickly find flaws. And surprisingly, this solution has been in use for about a year now.

“Applied’s new playbook for process control combines Big Data and AI to deliver an intelligent and adaptive solution that accelerates our customers’ time to maximum yield,” said Keith Wells, group vice president and general manager, Imaging and Process Control at Applied Materials. “By combining our best-in-class optical inspection and eBeam review technologies, we have created the industry’s only solution with the intelligence to not only detect and classify yield-critical defects but also learn and adapt to process changes in real-time. This unique capability enables chipmakers to ramp new process nodes faster and maintain high capture rates of yield-critical defects over the lifetime of the process.”

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Summary: A new genetic engineering strategy significantly reduces levels of tau in animal models of Alzheimer’s disease. The treatment, which involves a single injection, appears to have long-last effects.

Source: Mass General.

Researchers have used a genetic engineering strategy to dramatically reduce levels of tau–a key protein that accumulates and becomes tangled in the brain during the development of Alzheimer’s disease–in an animal model of the condition.

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Layers of ice and rock obviate the need for “habitable zone” and shield life against threats.

SwRI researcher theorizes worlds with underground oceans may be more conducive to life than worlds with surface oceans like Earth.

One of the most profound discoveries in planetary science over the past 25 years is that worlds with oceans beneath layers of rock and ice are common in our solar system. Such worlds include the icy satellites of the giant planets, like Europa, Titan, and Enceladus, and distant planets like Pluto.

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The Research Group on Synthetic Biology for Biomedical Applications at Pompeu Fabra University in Barcelona, Spain, has designed a cellular device capable of computing by printing cells on paper. For the first time, they have developed a living device that could be used outside the laboratory without a specialist, and it could be produced on an industrial scale at low cost. The study is published in Nature Communications and was carried out by Sira Mogas-Díez, Eva Gonzalez-Flo and Javier Macía.

We currently have many available to us such as computers and tablets whose computing power is highly efficient. But, despite their power, they are very limited devices for detecting biological markers, such as those that indicate the presence of a disease. For this reason, a few years ago ‘biological computers’ began to be developed—in other words, living cellular devices that can detect multiple markers and generate complex responses. In them, the researchers leverage biological receptors that allow detecting exogenous signals and, by means of , modify them to emit a response in accordance with the information they detect.

So far, cellular devices have been developed that must operate in the laboratory, for a limited time, under specific conditions, and must be handled by a specialist in molecular biology. Now, a team of researchers from Pompeu Fabra University has developed new technology to ‘print’ cellular devices on paper that can be used outside the laboratory.

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Research papers come out far too rapidly for anyone to read them all, especially in the field of machine learning, which now affects (and produces papers in) practically every industry and company. This column aims to collect some of the most relevant recent discoveries and papers — particularly in but not limited to artificial intelligence — and explain why they matter.

This week brings a few unusual applications of or developments in machine learning, as well as a particularly unusual rejection of the method for pandemic-related analysis.

One hardly expects to find machine learning in the domain of government regulation, if only because one assumes federal regulators are hopelessly behind the times when it comes to this sort of thing. So it may surprise you that the U.S. Environmental Protection Agency has partnered with researchers at Stanford to algorithmically root out violators of environmental rules.

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Researchers at the University of Ottawa have debunked the decade-old myth of metals being useless in photonics – the science and technology of light – with their findings, recently published in Nature Communications, expected to lead to many applications in the field of nanophotonics.

“We broke the record for the resonance quality factor (Q-factor) of a periodic array of metal nanoparticles by one order of magnitude compared to previous reports,” said senior author Dr. Ksenia Dolgaleva, Canada Research Chair in Integrated Photonics (Tier 2) and Associate Professor in the School of Electrical Engineering and Computer Science (EECS) at the University of Ottawa.

“It is a well-known fact that metals are very lossy when they interact with light, which means they cause the dissipation of electrical energy. The high losses compromise their use in optics and photonics. We demonstrated ultra-high-Q resonances in a metasurface (an artificially structured surface) comprised of an array of metal nanoparticles embedded inside a flat glass substrate. These resonances can be used for efficient light manipulating and enhanced light-matter interaction, showing metals are useful in photonics.”

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