Research Highlights
Research Highlights
Effective and durable catalysts using abundant materials for hydrogen production
In a study published in ACS Applied Nano Materials, researchers report a novel method to synthesize hybrid 2D FeS/FeS2 nanostructures, a promising low-cost catalyst for next-generation hydrogen production.
Ultrafast electron microscopy sheds light on plasmonic dynamics in metallic nanoframes
In an JACS Nano paper, researchers used ultrafast electron microscopy to study the dynamics of plasmon-enhanced localized fields in metallic nanoframes.
Enabling preparation of previously inaccessible semiconductor nanocrystals
In a Science paper, researchers report synthesizing III-V semiconductor nanocrystals with possible applications in displays, lasers, photodetectors, and more.
Additional Research Highlights
Leveraging AI for improved X-ray photon correlation spectroscopy
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.
New design for cathode particles yields ultra-stable cathodes
In a study published in Nature Energy, researchers develop a “dual-gradient” design for NMC cathodes that enables high-voltage operation, with minimal capacity loss during cycling, reduced cost, and improved thermal stability.
New AI-enabled microscopy images nanoscale magnetic spin textures
In a study published in npj Computational Materials, researchers enable quantitative imaging of nanoscale magnetic spin textures from any single defocused image using AI-based phase-retrieval, allowing near real-time quantitative magnetic imaging.
Atomistic mechanism in transforming graphite into diamond
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.
Data-driven approach to extract dynamics from coherent X-ray data
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.
Bottleneck in heterostructure yields red and green luminescence
In a Nano Letters paper, researchers that heterostructures of CdSe/CdTe/CdSe exhibit bicolor luminescence, which is attributed to a hole relaxation bottleneck.