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Computation and theory news, March 2022

Using a novel method, researchers can conduct real-time atomic-level observations of grain boundary deformation in poly-grained metallic materials.

Researchers have developed a machine-learning model that can assess the stability of rare-earth compounds.

All electrochemical energy storage mechanisms exist somewhere on a continuum between those that work in batteries and those that work in capacitors.

A novel ‘self-driving lab’ uses artificial intelligence and fluidic systems to advance understanding of semiconductor and metallic nanomaterials.

A new theory of entropy called Zentropy can predict the change in volume of a material as a function of temperature at a multiscale level.

Researchers have used data-driven methods to predict 28 likely representatives of a new class of 2D metal oxides.

carbon fiber-based composite battery electrodes could pave the way for high-performance structural components with energy storage capabilities

Researchers have discovered that magnetism is key to understanding the behavior of electrons in so-called ‘high-temperature’ superconductors.

Adding a bit of liquid electrolyte to a solid-state battery can greatly increase its performance while only having a small impact on safety.

Researchers have developed a novel process for predicting and guiding the ordered creation of strong yet flexible diamond nanothreads.

Using computer modeling and experimental data, researchers can now predict, with unprecedented precision, when a soft material will crack and fail.

Researchers have shown that, under the right conditions, proteins can form tiny, current-carrying wires, for use in nanoelectronics.

Researchers have discovered a long-predicted magnetic state of matter called an ‘antiferromagnetic excitonic insulator’.

Researchers have found a way to reduce the 'hairs' that can form on nanocrystals, greatly improving their ability to function together electronically.

Using artificial intelligence, researchers analyzed new kinds of atomic-scale microscopic images to understand exactly why batteries wear out.

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