Presently, conventional technologies in water treatment are not efficient enough to
completely mineralize refractory water contaminants. In this context, the implementation of …

This is a critical review of artificial intelligence/machine learning (AI/ML) methods applied to
battery research. It aims at providing a comprehensive, authoritative, and critical, yet easily …

During the last decades, X-ray absorption spectroscopy (XAS) has become an
indispensable method for probing the structure and composition of heterogeneous catalysts …

The discovery and development of catalysts and catalytic processes are essential
components to maintaining an ecological balance in the future. Recent revolutions made in …

Transition metal-nitrogen-doped carbons (TMNCs) are a promising class of catalysts for the
CO2 electrochemical reduction reaction. In particular, high CO2-to-CO conversion activities …

Abstract Machine learning (ML) is emerging as a powerful tool for identifying quantitative
structure–activity relationships to accelerate electrocatalyst design by learning from historic …

The potential of operando X-ray techniques for following the structure, fate, and active site of
single-atom catalysts (SACs) is highlighted with emphasis on a synergetic approach of both …

Single‐atom catalysts (SACs) have recently emerged as an exciting system in
heterogeneous catalysis showing outstanding performance in many catalytic reactions …

Neutron and x-ray scattering represent two classes of state-of-the-art materials
characterization techniques that measure materials structural and dynamical properties with …

X-ray absorption spectroscopy (XAS) produces a wealth of information about the local
structure of materials, but interpretation of spectra often relies on easily accessible trends …