Machine learning (ML) encompasses a broad range of algorithms and modeling tools used
for a vast array of data processing tasks, which has entered most scientific disciplines in …

Modern simulation techniques have reached a level of maturity which allows a wide range of
problems in chemistry and materials science to be addressed. Unfortunately, the application …

We formulate a materials design strategy combining a machine learning (ML) surrogate
model with experimental design algorithms to search for high entropy alloys (HEAs) with …

Despite decades of theoretical studies, the nature of the glass transition remains elusive and
debated, while the existence of structural predictors of its dynamics is a major open …

Disorder, which qualitatively describes some measure of irregularities in spatial patterns, is
ubiquitous in many-body systems, equilibrium and non-equilibrium states of matter, network …

Abstract The Materials Genome Initiative (MGI) advanced a new paradigm for materials
discovery and design, namely that the pace of new materials deployment could be …

Dynamic relaxation is an intrinsic and universal feature of glasses and enables fluctuation
and dissipation to occur, which induces plentiful behaviour, maintains equilibrium, and …

The deformation and flow of disordered solids, such as metallic glasses and concentrated
emulsions, involves swift localized rearrangements of particles that induce a long-range …

The physics of the glass transition and amorphous materials continues to attract the attention
of a wide research community after decades of effort. Supercooled liquids and glasses have …

In contrast with crystallization, there is no noticeable structural change at the glass transition.
Characteristic features of glassy dynamics that appear below an onset temperature, T 0 …