Machine learning enabled design of sustainable alloys considering real world constraints
cond-mat.mtrl-sci
Submitted: 2026-10-23
Updated: 2026-10-23
Related papers
- Mode-selective electron-phonon coupling drives charge density waves in the kagome metals YRu 3 Si 2 and LaRu 3 Si 2
- Direct Raman observation of the quantum metric in a quantum magnet
- Restoring the Surface Magnetic Gap in MnBi 2 Te 4
- ATLAS: A Foundation Neural Sampler for Amorphous Materials
- A Generalizable Machine Learning Framework for Half-Heusler Thermoelectrics
- Nonlinear dynamics in magnonic Fabry-P' e rot resonators: Low-power neuron-like activation and transmission suppression