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Category: computing

New ultrathin ferroelectric capacitors show promise for compact memory devices

An ultrathin ferroelectric capacitor, designed by researchers from Japan, demonstrates strong electric polarization despite being just 30 nm thick including top and bottom electrodes—making it suitable for high-density electronics. Using a scandium-doped aluminum nitride film as the ferroelectric layer, the team achieved high remanent polarization even at reduced thicknesses. This breakthrough demonstrates good compatibility with semiconductor devices combining logic circuits and memory, paving the way for compact and efficient on-chip memory for future technologies.

Modern electronic technology is rapidly advancing towards miniaturization, creating devices that are increasingly compact yet high-performing. As the devices continue to shrink in size, there is an increasing demand for ultra-small memory materials that can efficiently store data, even in smaller dimensions. Ferroelectric memory devices are promising options for future mobile and compact electronics, as they store information using switchable electric polarization, allowing data retention even without power. However, very few initiatives have reported progress in downscaling of these ferroelectric devices.

Bridging this gap, a research team led by Professor Hiroshi Funakubo from the School of Materials and Chemical Technology, Institute of Science Tokyo (Science Tokyo), Japan, in collaboration with Canon ANELVA Corporation (Canon ANELVA), successfully downscaled a total ferroelectric memory capacitor stack using scandium-substituted aluminum nitride ((Al, Sc)N) thin films with platinum electrodes, reducing the total thickness to just 30 nm including top and bottom electrodes.

Physicists repair flaw of established quantum resource theorem

Quantum information theory is a field of study that examines how quantum technologies store and process information. Over the past decades, researchers have introduced several new quantum information frameworks and theories that are informing the development of quantum computers and other devices that operate leveraging quantum mechanical effects.

These include so-called resource theories, which outline the transformations that can take place in quantum systems when only a limited number of operations are allowed.

In 2008, two scientists at Imperial College London introduced what they termed the generalized quantum Stein’s lemma, a mathematical theorem that describes how well quantum states can be distinguished from one another. In this generalized setting, one typically considers multiple identical copies of a specific state (the null hypothesis) and tests them against a composite alternative hypothesis, i.e., a set of states (e.g., resource-free states).

Encoding adaptive intelligence in molecular matter by design

For more than 50 years, scientists have sought alternatives to silicon for building molecular electronics. The vision was elegant; the reality proved far more complex. Within a device, molecules behave not as orderly textbook entities but as densely interacting systems where electrons flow, ions redistribute, interfaces evolve, and even subtle structural variations can induce strongly nonlinear responses. The promise was compelling, yet predictive control remained elusive.

Meanwhile, neuromorphic computing—hardware inspired by the brain—has followed a parallel ambition: to discover a material that can store information, compute, and adapt within the same physical substrate and in real time. Yet today’s dominant platforms, largely based on oxide materials and filamentary switching mechanisms, continue to behave as engineered machines that emulate learning, rather than as matter that intrinsically embodies it.

A new study from the Indian Institute of Science (IISc) published in Advanced Materials suggests that these two long-standing challenges may finally converge.

TransBrain: a computational framework for translating brain-wide phenotypes between humans and mice

TransBrain translates brain phenotypes between mouse and human via homology mapping, thus making it possible to capitalize on the wealth of knowledge about the mouse brain and gain insights into the human brain.

Biology-inspired brain model matches animal learning and reveals overlooked neuron activity

A new computational model of the brain based closely on its biology and physiology has not only learned a simple visual category learning task exactly as well as lab animals, but even enabled the discovery of counterintuitive activity by a group of neurons that researchers working with animals to perform the same task had not noticed in their data before, reports a team of scientists at Dartmouth College, MIT, and the State University of New York at Stony Brook.

Josephson junction behavior observed with only one superconductor and iron barrier

Separate two superconductors with a thin layer of material and something strange happens.

Their superconductivity—a property driven by paired electrons that allows electricity to flow without energy loss—can leak into the barrier and link together, synchronizing their behavior despite the separation.

This device is known as a Josephson junction. It’s the foundational building block of quantum computers and advances of it won the 2025 Nobel Prize in Physics.

New model showcases microbubble behavior in viscoelastic fluid under ultrasound forcing

Encapsulated microbubbles (EMBs), tiny gas-filled bubbles coated in lipid or protein shells, play a central role in biomedical ultrasound. When exposed to ultrasound waves, EMBs contract, resulting in oscillations that enhance image contrast or deliver drugs directly by creating pores in cell membranes via sonoporation. However, while promising for biomedical applications, their behavior is far more complex.

Most existing theories on EMBs assume spherically symmetrical oscillations and only study them in simple Newtonian fluids. However, most biological fluids, such as blood, are viscoelastic (non-Newtonian) fluids. When inside the body, these fluid forces, pressure from vessel walls, and changing ultrasound pulses can influence the behavior of EMBs, affecting both imaging accuracy and treatment safety.

To better understand these effects, a multi-institutional research team has developed a comprehensive computational model that simulates the behavior of EMBs under real biological conditions. The team included Assistant Professor Haruki Furukawa and Professor Shuichi Iwata from Nagoya Institute of Technology (NITech), Japan, in collaboration with Emeritus Professor Tim N. Phillips, Dr. Michael J. Walters, and Reader Steven J. Lind from Cardiff University, Wales.

The Man Who Reimagined Math: David Deutsch And The Universal Quantum Computer

David Deutsch didn’t just contribute to the field of quantum computing—he redefined what computation *is*, bridging the gap between physics and information in a way no one had before. By theorizing the universal quantum computer, Deutsch opened the door to possibilities previously confined to science fiction, forever altering our understanding of reality and the limits of what machines can achieve.

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