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cond-mat.mtrl-sci2026
On-the-Fly Machine-Learned Force Fields for High-Fidelity Polymer Glass Transition Simulations
Ashutosh Srivastava, Sakshi Agarwal, Shivank Shukla +2
Predicting polymer glass transition temperatures (Tg) with first-principles fidelity has long remained out of reach, as cooling multi-thousand-atom systems over a broad temperature…
cond-mat.mtrl-sci2026
Load-dependent Hardness Prediction for Materials using Machine Learning
Madhubanti Mukherjee, Rampi Ramprasad, Harikrishna Sahu
Superhard materials are critical for wear-resistant and high-stress applications. Conventional approaches correlating hardness with elastic moduli derived from DFT calculations ena…
cond-mat.mtrl-sci2025
An Encoder-Decoder Foundation Chemical Language Model for Generative Polymer Design
Harikrishna Sahu, Wei Xiong, Anagha Savit +2
Traditional machine learning has advanced polymer discovery, yet direct generation of chemically valid and synthesizable polymers without exhaustive enumeration remains a challenge…