A machine learning pipeline identifies low-frequency Raman signatures as reliable indicators of liquid-like ionic conduction ...

Scientists at the Department of Energy's Lawrence Berkeley National Laboratory (Berkeley Lab) have developed a new way to determine atomic structures from nanocrystals previously considered unusable, ...

A new AI-driven technique spots the telltale Raman signal of liquid-like ion motion—helping scientists rapidly identify ...

Michael Martynowycz, PhD, assistant professor of structural biology at the Jacobs School of Medicine and Biomedical Sciences, recently described a new technique for solving protein structures in a rec ...

The search for materials that can conduct electricity at room temperature without losing energy is one of the greatest and most consequential challenges of modern physics: loss-free power transmission ...

Solid-state batteries could be safer and more energy-dense than today’s lithium-ion technology, but finding materials that allow ions to move quickly through solid electrolytes has been difficult.

Researchers at Lawrence Berkeley National Laboratory have developed a 4D-STEM workflow that can isolate and solve atomic structures from individual nanocrystals buried inside dense, tangled clusters, ...

A team of researchers at the Technical University of Munich and ́Ecole Polytechnique Fédérale de Lausanne has developed an innovative computational approach combining machine learning and Raman ...

Virtual apertures let researchers isolate and solve atomic structures from individual nanocrystals embedded in dense clusters, providing valuable new data for energy and pharmaceutical applications.

All-solid-state batteries (ASSB) are widely recognized as a safer and potentially more energy-dense alternative to conventional lithium-ion ...