Energy from renewable resources is central to environmental sustainability. Among the
renewables, sunlight-driven fuel synthesis is a sustainable and economical approach to …

Deep learning (DL) is one of the fastest-growing topics in materials data science, with
rapidly emerging applications spanning atomistic, image-based, spectral, and textual data …

With the development of advanced electronic devices and electric power systems, polymer-
based dielectric film capacitors with high energy storage capability have become particularly …

BACKGROUND Metallic components are the cornerstone of modern industries such as
aviation, aerospace, automobile manufacturing, and energy production. The stringent …

On top of machine learning (ML) models, uncertainty quantification (UQ) functions as an
essential layer of safety assurance that could lead to more principled decision making by …

Hypersonic vehicles must withstand extreme conditions during flights that exceed five times
the speed of sound. These systems have the potential to facilitate rapid access to space …

The Martini model, a coarse‐grained force field for molecular dynamics simulations, has
been around for nearly two decades. Originally developed for lipid‐based systems by the …

Polymer materials provide solutions to some of the most pressing environmental,
manufacturing and health-care challenges. Traditional thermoplastic and thermoset …

Machine learning models are poised to make a transformative impact on chemical sciences
by dramatically accelerating computational algorithms and amplifying insights available from …

Nanocarriers (NCs) that can precisely deliver active agents, nutrients and genetic materials
into plants will make crop agriculture more resilient to climate change and sustainable. As a …