One of the grand challenges in the physical sciences is to 'design'a material before it is ever
synthesized. There has been fast progress in predicting new solid-state compounds with the …

Computer simulations can play a central role in the understanding of phase-change
materials and the development of advanced memory technologies. However, direct quantum …

Being rich in hydrogen and easy to transport, ammonia is a promising hydrogen carrier.
However, a microscopic characterization of the ammonia cracking reaction is still lacking …

Chalcogenide phase-change materials (PCMs) are showing versatile possibilities in cutting-
edge applications, including non-volatile memory, neuromorphic computing, and nano …

Simulating catalytic reactivity under operative conditions poses a significant challenge due
to the dynamic nature of the catalysts and the high computational cost of electronic structure …

Advances in machine learning have led to the development of foundation models for
atomistic materials chemistry, enabling quantum-accurate descriptions of interatomic forces …

Phase change materials such as Ge 2 Sb 2 Te 5 (GST) are ideal candidates for next-
generation, non-volatile, solid-state memory due to the ability to retain binary data in the …

The importance of the structure-function relationship in molecular biology was confirmed
dramatically by the recent award of the 2024 Nobel Prize in Chemistry'for computational …

A machine-learned interatomic potential for Ge-rich Ge x Te alloys has been developed
aiming at uncovering the kinetics of phase separation and crystallization in these materials …

In their letter, Lee and Elliott question the existence of a distinct class of glass-forming
materials (1) which are at variance with Zachariasen's conjecture, ie, form non-Zachariasen …