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Category: computing – Page 12

RRAM-based analog computing system rapidly solves matrix equations with high precision

Analog computers are systems that perform computations by manipulating physical quantities such as electrical current, that map math variables, instead of representing information using abstraction with discrete binary values (i.e., 0 or 1), like digital computers.

While computing systems can perform well on general-purpose tasks, they are known to be susceptible to noise (i.e., background or external interferences) and less precise than .

Researchers at Peking University and the Beijing Advanced Innovation Center for Integrated Circuits have developed a scalable analog computing device that can solve so-called matrix equations with remarkable precision. This new system, introduced in a paper published in Nature Electronics, was built using tiny non-volatile memory devices known as resistive random-access memory (RRAM) chips.

Computationally accelerated organic synthesis: Optimal ligand prediction for generating reactive alkyl ketone radicals

Because ketones are widespread in organic molecules, chemists are eager to develop new reactions that use them to form chemical bonds. One challenging reaction is the one-electron reduction of ketones to generate ketyl radicals.

Ketyl radicals are reactive intermediates used in natural product synthesis and pharmaceutical chemistry; however, most methodologies are optimized for aryl while simple alkyl ketones remain challenging for chemists. Alkyl ketones are considerably more abundant but intrinsically more difficult to reduce than aryl ketones.

To this end, a team of specialized organic chemists and computational chemists from WPI-ICReDD at Hokkaido University has developed a new catalytic method for generating alkyl ketyl radicals.

Scientists create new type of semiconductor that holds superconducting promise

Scientists have long sought to make semiconductors—vital components in computer chips and solar cells—that are also superconducting, thereby enhancing their speed and energy efficiency and enabling new quantum technologies. However, achieving superconductivity in semiconductor materials such as silicon and germanium has proved challenging due to difficulty in maintaining an optimal atomic structure with the desired conduction behavior.

In a paper published in the journal Nature Nanotechnology, an international team of scientists reports producing a form of that is superconducting—able to conduct electricity with , which allows currents to flow indefinitely without , resulting in greater operational speed that requires less energy.

“Establishing superconductivity in germanium, which is already widely used in computer chips and , can potentially revolutionize scores of consumer products and industrial technologies,” says New York University physicist Javad Shabani, director of NYU’s Center of Quantum Information Physics and the university’s newly established Quantum Institute, one of the paper’s authors.

Sensory expectations configure neural responses before disturbances occur, study reveals

A study led by Jonathan Michaels, a Faculty of Health professor at York’s School of Kinesiology and Health Science, reveals how the brains of humans and monkeys use sensory expectations to prepare for unexpected disturbances, enabling faster and more accurate motor responses.

Published today in Nature, the study demonstrates that motor circuits across the brain do not passively wait for sensory signals. Instead, they proactively anticipate potential challenges, configuring themselves to respond effectively to disturbances. The research represents a significant leap forward in uncovering the brain’s predictive capabilities and its role in .

This advancement provides a clearer picture of the neural mechanisms underlying movement preparation and response, illustrating how expectation itself enhances precision and stability. The discovery opens new pathways for improving rehabilitation techniques and advancing brain-computer interface technology.

Electrons can now be controlled to build smarter quantum devices

Auburn University scientists have developed a new class of materials that lets researchers precisely control free electrons, a breakthrough that could reshape the future of computing and chemical manufacturing.

Their study introduces a material system that allows fine-tuned control over how electrons behave within matter, potentially paving the way for faster computers, smarter machines, and more efficient industrial processes.

Iontronic Circuits: Building Intelligence in Brine

Experiments with membranes offer a path toward scalable neuromorphic computing.

Imagine a future in which computers process information not with streams of electrons but with hydrated ions flowing through salt water, a system that mimics how the brain itself computes. This emerging field—known as iontronics, a portmanteau of ions and electronics—is rapidly growing as researchers design neuromorphic computing devices, inspired by animal nervous systems and powered by electrolyte solutions at the nanoscale [1–3]. Since Leon Chua introduced the memory resistor or “memristor” in the 1970s [4], these components have been considered revolutionary building blocks for neuromorphic computing. A memristor’s electrical resistance depends on the current that flowed through it before it was powered off, offering a way to store information. Unlike solid-state memristors, fluidic ones still face challenges in terms of scalability and integration with a circuit.

Electric signals reveal magnetic spin waves, hinting at faster computing

Today’s computers store information in magnetic hard drives, keeping files safe even when the device is powered off. But to run programs and process information, computers rely on electricity. Each calculation requires a transfer of information between the electric and magnetic systems. This back-and-forth is a major bottleneck in the speed of modern computing.

Devices that integrate magnetic components directly into computing logic would remove this limitation and allow computers to perform faster and more efficiently.

A new theoretical study led by University of Delaware engineers reveals that magnons, a type of magnetic spin wave, can produce detectable electric signals. The findings, published in the Proceedings of the National Academy of Sciences, highlight potential ways to control and manipulate magnons with electric fields and suggest a path toward integrating electric and magnetic components to enable next-generation computing technologies.

This Quantum Electron Breakthrough Could Make Computers Faster Than Ever Before

Auburn University scientists have developed a new class of materials that allow precise control over free electrons, potentially transforming computing and chemical manufacturing. Imagine a future where factories produce new materials and chemical compounds more quickly, more efficiently, and at

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