A method to interpret artificial intelligence (AI) models used in materials discovery by analyzing their learned features has ...
This Collection supports and amplifies research related to SDG 9 - Industry, Innovation & Infrastructure. Discovering new materials with customizable and optimized properties, driven either by ...
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 ...
(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 ...
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 ...
Researchers have developed a deep learning-based approach that significantly streamlines the accurate identification and classification of two-dimensional (2D) materials through Raman spectroscopy. In ...
Materials informatics applies data-driven strategies to materials R&D. Long before generative AI technology reached peak hype, it had a long history of success in this field. A common approach is to ...
Engineers now use simulations of adhesively bonded joints as a common design tool. Robust numerical simulation of adhesively bonded structures requires detailed Material Models based on solid ...
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