Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...

(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 Johns Hopkins University engineer has developed a specialized AI tool that could do for materials scientists what ChatGPT has done for coders and writers. The new system, called ChatGPT Materials ...

British biochemist Professor Frederick Sanger was awarded his second Nobel Prize for Chemistry in 1980. He is only the third person to win Nobel Prizes for science in the history of he awards and ...

(Nanowerk News) The arrangement of electrons in matter, known as the electronic structure, plays a crucial role in fundamental but also applied research such as drug design and energy storage. However ...

You’ll tackle projects in computational materials design (from high-throughput modeling and phase-diagram simulations to training machine-learning models on experimental signals such as UV–Vis/IR) ...

Creeps are characterized as time-dependent permanent deformations that occur under constant stress at elevated temperatures. The material composition determines the onset of creep. For example, steel ...

The performance of rechargeable batteries is governed by processes deep within their components. A fundamental understanding of electrochemistry, structure–property–performance relationships and the ...