This Tutorial demonstrates how Bayesian methods can be applied to analyze temperature-dependent transport data, offering practical workflows to model ionic conductivity in energy materials.

This work introduces corrections that significantly improve the accuracy of models for halocarbon chemistry, making computational approaches to understand catalytic reactions and environmental chemistry more reliable.

An advanced neutron scattering technique reveals the complex ionic conduction mechanism of the superionic phase of SrCl${}_2$. This approach will enable insight into solid ionic conductors for energy generation and storage.

Thermal-reservoir-driven nonreciprocal quantum batteries provide thermally shielded extractable work, offering a pathway to practical, high-performance energy storage.

This work formalizes operations that preserve ergotropy, or extractable work, while redistributing its internal structure during quantum state transformations, with implications for quantum battery charging and storage.

Detailed mass spectrometry reveals the chemical transformation pathways during pyrolysis of the model lignin compounds anisole and 4-vinylanisole, offering key insights for sustainable biomass conversion and the formation of particulates in wildfires.

A universal model for multiresonant absorption identifies the upper bounds on broadband absorption and provides a tool to to determine the optimal light trapping strategy for solar cells.

Analysis of five years of wind farm data uncovers correlated fluctuations in wind speed across scales and provides the foundation needed to optimize wind power forecasting and control strategies.

A combined spectroscopic and structural analysis identifies structural impacts on carrier transport in polymeric nonfullerene acceptors. The findings establish a framework for the rational design of high-efficiency organic solar cells.

This study shows how locally coherent Cu${}_2$S/MoS${}_2$ interfaces alter interfacial charge transfer and electronic structure, providing a design principle for tuning catatlytic reactivity in heterostructured materials.

Advanced computational modeling reveals that optimal carbon anodes for lithium-ion and sodium-ion batteries require distinct interlayer spacings, driven by unique ion intercalation behaviors in layered carbon materials.

This work models the thermodynamic costs of memory storage in realistic circuits, offering an optimization scheme to enable energy-efficient computation.

This work introduces a model that quantifies how wind speed variations across different scales dictate the power output of wind farms. Validated against numerical simulations and field measurements, this predictive framework provides a robust tool for optimizing next-generation wind farm designs.

Advanced computational insights reveal how disorder dictates the low thermal conductivity of (Al,Ga)N, a key factor for thermal management in high-power electronics

This work presents a method for modeling multijunction solar cell performance under realistic conditions, validated by a year of field data from a GaAs/Si tandem module.

This Review summarizes recent progress in the search for high-performance solid-state electrolytes for magnesium-based batteries.