Research Highlight

In a study published in Nature Communications, researchers develop an AI-based approach, AI-NERD, to classify a colloidal glass’s relaxation dynamics without prior knowledge of the material, highlighting potential for autonomous materials discovery.

In a study published in Carbon, researchers uncover the nucleation-growth mechanism behind direct graphite-to-diamond transformation, revealing new ways to synthesize hexagonal diamond that could be used for quantum information applications.

In a study published in npj Computational Materials, researchers used machine learning to develop a data-driven platform that models previously inaccessible complex, real-space dynamics from time-resolved coherent X-ray scattering.

A new high-resolution dataset is created to better understand impacts of tree and building height on urban climate and morphology.

Argonne researchers give future-focused flash talks on energy-efficient computing at critical Department of Energy workshop.

Long-term observations of deep convective cloud vertical velocity and mass flux for different convection lifecycle stages.

In a Nano Letters paper, researchers that heterostructures of CdSe/CdTe/CdSe exhibit bicolor luminescence, which is attributed to a hole relaxation bottleneck.

As shown in a Nature Sustainability paper, researchers have created a luminescent polymer that is both depolymerizable and recyclable.

Scientists can now expand their reach to help manufacturers produce the world’s most efficient batteries on a sustainable commercial scale.

The Argonne-managed Battery Workforce Challenge Program aims to promote workforce development and ensure economic growth and sustainability in the clean energy sector.