2025 could be the year that puts mainstream computing on the track toward developing ‘augmented mentality.’
Category: computing – Page 92
Decoding 2D material growth: White graphene insights open doors to cleaner energy and more efficient electronics
A breakthrough in decoding the growth process of hexagonal boron nitride (hBN), a 2D material, and its nanostructures on metal substrates could pave the way for more efficient electronics, cleaner energy solutions and greener chemical manufacturing, according to new research from the University of Surrey published in the journal Small.
Only one atom thick, hBN—often nicknamed “white graphene”—is an ultra-thin, super-resilient material that blocks electrical currents, withstands extreme temperatures and resists chemical damage. Its unique versatility makes it an invaluable component in advanced electronics, where it can protect delicate microchips and enable the development of faster, more efficient transistors.
Going a step further, researchers have also demonstrated the formation of nanoporous hBN, a novel material with structured voids that allows for selective absorption, advanced catalysis and enhanced functionality, vastly expanding its potential environmental applications. This includes sensing and filtering pollutants—as well as enhancing advanced energy systems, including hydrogen storage and electrochemical catalysts for fuel cells.
Specialized hardware solves high-order optimization problems with in-memory computing
In an unprecedented new study, researchers have shown neurotransmitters in the human brain are released during the processing of the emotional content of language, providing new insights into how people interpret the significance of words.
The work, conducted by an international team led by Virginia Tech scientists, offers deeper understanding into how language influences human choices and mental health.
Spearheaded by computational neuroscientist Read Montague, a professor of the Fralin Biomedical Research Institute at VTC and director of the institute’s Center for Human Neuroscience Research, the study represents a first-of-its-kind exploration of how neurotransmitters process the emotional content of language—a uniquely human function.
Proximity effect enables non-ferroelectric materials to gain new properties
Ferroelectrics are special materials with polarized positive and negative charges—like a magnet has north and south poles—that can be reversed when external electricity is applied. The materials will remain in these reversed states until more power is applied, making them useful for data storage and wireless communication applications.
Now, turning a non-ferroelectric material into one may be possible simply by stacking it with another ferroelectric material, according to a team led by scientists from Penn State who demonstrated the phenomenon, called proximity ferroelectricity.
The discovery offers a new way to make ferroelectric materials without modifying their chemical formulation, which commonly degrades several useful properties. This has implications for next-generation processors, optoelectronics and quantum computing, the scientists said. The researchers published their findings in the journal Nature.
Simulations of supercooled liquid molecular dynamics may lead to higher-quality glass production at lower cost
Glass might seem to be an ordinary material we encounter every day, but the physics at play inside are actually quite complex and still not completely understood by scientists. Some panes of glass, such as the stained-glass windows in many medieval buildings, have remained rigid for centuries, as their constituent molecules are perpetually frozen in a state of disorder.
Similarly, supercooled liquids are not quite solid, in the sense that their fundamental particles do not stick to a lattice pattern with long-range order, but they are also not ordinary liquids, because the particles also lack the energy to move freely. More research is required to reveal the physics of these complex systems.
In a study published in Nature Materials, researchers from the Institute of Industrial Science, the University of Tokyo have used advanced computer simulations to model the behavior of fundamental particles in a glassy supercooled liquid. Their approach was based on the concept of the Arrhenius activation energy, which is the energy barrier a process must overcome to proceed.
New Quantum Particle Discovery Set to Revolutionize Physics
Scientists at Brown University have discovered a new class of quantum particles known as fractional excitons, which exhibit both fermion and boson characteristics.
This groundbreaking finding could pave the way for new phases of matter and enhance quantum computing by providing unique ways to manipulate quantum states.
Novel Quantum Particles Discovered
Tiny Chips promise Swift Disease Diagnosis from a Single Breath
In a world grappling with a multitude of health threats—ranging from fast-spreading viruses to chronic diseases and drug-resistant bacteria—the need for quick, reliable, and easy-to-use home diagnostic tests has never been greater. Imagine a future where these tests can be done anywhere, by anyone, using a device as small and portable as your smartwatch. To do that, you need microchips capable of detecting miniscule concentrations of viruses or bacteria in the air.
A new computational model can predict antibody structures more accurately
Using this model, researchers may be able to identify antibody drugs that can target a variety of infectious diseases.
MIT researchers have developed a computational technique that allows large language models to predict antibody structures more accurately. Their work could enable researchers to sift through millions of possible antibodies to identify those that could be used to treat SARS-CoV-2 and other infectious diseases.
Check out the full article here: https://www.wevolver.com/article/a-new-computational-model-c…accurately.
Schemas, reinforcement learning and the medial prefrontal cortex
A computational account of how schemas are learned through experience is lacking. In this Perspective, Bein and Niv synthesize schema theory and reinforcement learning research to derive computational principles that might govern schema learning and then propose their mediation via dimensionality reduction in the medial prefrontal cortex.