Tag: materials discovery

A new review details how graph neural networks are accelerating the discovery of electrocatalysts for green hydrogen production by learning ...

A dual-modality deep encoder called SIMPLEX achieved the highest R-squared of 0.6712 for predicting adhesion strength of hydrogel formulations collected ...

An international team of 69 researchers has proposed a physics-aware AI framework, published in ACS Energy Letters, designed to make ...

A new analysis argues that AI-generated scientific results require graded scientific maturity across domain anchoring, representational integration, failure articulation and ...

A new equivariant graph neural network predicts charge density and band structures across the periodic table more than ten times ...

A new conceptual analysis argues that property cliffs, abrupt physicochemical property changes triggered by small structural modifications, exist across acidity, ...

Researchers in China developed an improved crystal graph neural network that screened more than 46,000 piezoelectric crystals and identified several ...

A new review collection in Frontiers in Batteries and Electrochemistry shows battery research converging on safer interfaces, smarter manufacturing, computational ...

A machine learning-guided search has produced a tungsten bronze oxide ceramic that combines a high dielectric constant, ultralow loss and ...

Tohoku University researchers propose a framework called Physics-Grounded Materials AI that embeds thermodynamic, kinetic, and electronic-structure principles into machine learning ...