Perovskite solar cells have gained considerable momentum in the search for cheaper, more efficient solar energy. However, the ...

This Collection supports and amplifies research related to SDG 9 - Industry, Innovation & Infrastructure. Discovering new materials with customizable and optimized properties, driven either by ...

A method to interpret artificial intelligence (AI) models used in materials discovery by analyzing their learned features has been developed by researchers from Japan. The method extracts key features ...

Cornell researchers are demonstrating how artificial intelligence—particularly deep learning and generative modeling—can accelerate the design of new molecules and materials, and even function as an ...

For grid-scale energy storage and national energy resilience, the U.S. needs better batteries. Lawrence Livermore National ...

(a) A feasible route for developing large materials models capable of describing the structure-property relationship of materials. The universal materials model of DeepH accepts an arbitrary material ...

A general-purpose LLM is fine-tuned with inorganic material knowledge datasets and used to predict the synthesizability and precursor compounds of hypothetical inorganic materials. Seoul National ...

Physics-informed machine learning connects atomic structure with ion transport and electrolyte stability, accelerating better sodium- and lithium-ion batteries.