Electrocatalysts and photocatalysts are key to a sustainable future, generating clean fuels,
reducing the impact of global warming, and providing solutions to environmental pollution …

Mechanical metamaterials are engineered materials with unconventional mechanical
behavior that originates from artificially programmed microstructures along with intrinsic …

Deep learning (DL) is one of the fastest-growing topics in materials data science, with
rapidly emerging applications spanning atomistic, image-based, spectral, and textual data …

Lithium-ion batteries play a pivotal role in a wide range of applications, from electronic
devices to large-scale electrified transportation systems and grid-scale energy storage …

Alloy modelling has a history of machine-learning-like approaches, preceding the tide of
data-science-inspired work. The dawn of computational databases has made the integration …

Artificial Intelligence (AI) has advanced material research that were previously intractable,
for example, the machine learning (ML) has been able to predict some unprecedented …

The prosperity and lifestyle of our society are very much governed by achievements in
condensed matter physics, chemistry and materials science, because new products for …

Graph neural networks (GNN) have been shown to provide substantial performance
improvements for atomistic material representation and modeling compared with descriptor …

ChatMOF is an artificial intelligence (AI) system that is built to predict and generate metal-
organic frameworks (MOFs). By leveraging a large-scale language model (GPT-4, GPT-3.5 …

Advanced oxidation processes (AOPs) based on persulfates such as peroxymonosulfate
and peroxydisulfate via heterogeneous catalysts have been a research hotspot due to their …