Machine learning is transforming many scientific fields, including computational materials science. For about two decades, ...
This Collection supports and amplifies research related to SDG 9 - Industry, Innovation & Infrastructure. Discovering new materials with customizable and optimized properties, driven either by ...
Materials informatics combines data analytics and engineering design, streamlining material development and enhancing performance through AI integration.
A research team led by Chang Keke from the Ningbo Institute of Materials Technology and Engineering (NIMTE), Chinese Academy ...
Open Materials 2024 will be one of the biggest data sets available for materials science. Meta is releasing a massive data set and models, called Open Materials 2024, that could help scientists use AI ...
Machine learning tools can accelerate all stages of materials discovery, from initial screening to process development.
Overview of class Key models of electron and ion vacancy transport in hard and soft, crystalline and non-crystalline materials, including hopping, tunneling, polaronic transport and mixed conduction.
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