Diffusion driven by temperature or concentration gradients is a fundamental mechanism of
energy and mass transport that inherently differs from wave propagation in both physical …

Diffusion and wave propagation are both fundamental transport mechanisms, but they have
intrinsically different dynamics, governing equations, and applications. Over the past …

One of the most exciting tools that have entered the material science toolbox in recent years
is machine learning. This collection of statistical methods has already proved to be capable …

Over the past decade, topology has emerged as a major branch in broad areas of physics,
from atomic lattices to condensed matter. In particular, topology has received significant …

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 …

Recent advances in experimental and computational methods are increasing the quantity
and complexity of generated data. This massive amount of raw data needs to be stored and …

Abstract Machine Learning (ML) is one of the most exciting and dynamic areas of modern
research and application. The purpose of this review is to provide an introduction to the core …

Batteries are of paramount importance for the energy storage, consumption, and
transportation in the current and future society. Recently machine learning (ML) has …

Single‐atom catalysts (SACs) have become the forefront of energy conversion studies, but
unfortunately, the origin of their activity and the interpretation of the synchrotron …

The Landau description of phase transitions relies on the identification of a local order
parameter that indicates the onset of a symmetry-breaking phase. In contrast, topological …