Experiment and machine learning are combined to extract key material parameters and insight into charge carrier transport in metal halide perovskites for solar cell applications.

Muon tomography, a non-invasive technique that can be used to image large, inaccessible structures, is combined with machine learning to create a 3D reconstruction of a historical nuclear reactor that reveals material density variations, including potential anomalies in the graphite core.

Using data-driven machine learning models, this work demonstrates a method to map the dynamical state of a full power grid from limited observations, enabling the user to locate disruptions with information only from other areas of the grid.

A partial form of exciton condensation occurs in the light-harvesting complex of purple bacteria under ambient conditions, facilitating energy transfer by bridging quantum coherence and classical transport mechanisms.

A new “constant-current” nonequilibrium molecular dynamics simulation method accelerates ionic conductivity calculations by up to two orders of magnitude while accurately capturing ion-ion correlations, enabling more efficient screening of solid electrolytes and revealing important low-temperature conduction behaviors.

To understand the radiation hardness of halide perovskites and their suitability for space-based photovoltaics, $abinitio$ molecular dynamics simulations model the creation and diffusion of atomic defects in these materials, finding a lower threshold for defect generation than was previously assumed.

A method for direct energy conversion from high temperature plasmas is presented, with implications for efficient electricity generation in nuclear fusion reactors.

This study reveals how anharmonic, entropy-driven stabilization of di-vacancies at elevated temperatures reconcile theoretical predictions with experimental observations of vacancy clustering in tungsten, a prime candidate material for fusion reactors.

Using in-house operando X-ray diffraction, this study shows that a surface coating applied via particle atomic layer deposition improves the high-voltage cycling stability of nickel-rich lithium-ion battery cathodes by reducing cycling-induced structural fatigue.

An enhanced band gap and strong electron-hole band asymmetry in Ru${}_2$TiSi full-Heusler semiconductors could lead to thermoelectric performance on par with the best half-Heusler thermoelectrics, extending the phase space of Heusler thermoelectric materials for energy conversion applications.

This study employs electrochemical and optical techniques to compare hydrogen and oxygen bubble dynamics at microelectrode surfaces during water electrolysis, revealing distinct differences in the bubble dynamics that could inform the design of efficient electrolyzers.

This theoretical study shows that a crystalline silver-based argyrodite exhibits glass-like thermal transport with nearly temperature-independent thermal conductivity due to weakly bonded, highly mobile silver atoms that disrupt heat flow.

Using advanced first principles calculations, this work explores significant changes to the electronic structure and charge carrier concentration of the solid oxide electrolyte BaZrO${}_3$ at elevated temperatures, which represent the operating conditions in an electrolyzer or fuel cell.

A report on atmospheric carbon dioxide removal (CDR) underscores the importance of CDR technologies in meeting carbon dioxide management targets, while emphasizing that reducing carbon dioxide emissions must remain a top priority.

This Review describes the promise of atmospheric pressure spatial atomic layer deposition (SALD) for the precise manufacture of thin films at scale. Case studies of SALD for energy conversion and storage and electronic devices are presented, and the potential of SALD for emerging technologies is discussed.