Following the success of large language models, the concept of large materials models as deep-learning computational models for materials design has attracted great interest. Nevertheless, the task of ...
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 ...
This Collection supports and amplifies research related to SDG 9 - Industry, Innovation & Infrastructure. Discovering new materials with customizable and optimized properties, driven either by ...
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Physics-aware benchmark reveals why similar materials AI models can predict thermal conductivity differently
Material properties such as sound insulation, resistance to extreme heat and thermal expansion originate from how the zillions of microscopic building blocks (nuclei and electrons) interact at ...
Tohoku University researchers propose a framework called Physics-Grounded Materials AI that embeds thermodynamic, kinetic, ...
Experiments and machine learning reveal that grain boundary sliding governs the exceptional room-temperature ductility of an ...
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 ...
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