3 papers
cond-mat.str-el2026
Beyond Stoner-Wohlfarth: Machine-Learning Models and Symbolic Regression of Hard-Magnet Properties
Samuel J. R. Holt, Christina Winkler, Timoteo Colnaghi +7
Predicting the extrinsic properties from hysteresis loops of a magnetic grain, namely the coercive field, remanent magnetisation, and maximum energy product, from its intrinsic mic…
astro-ph.GA2024
All-sky three-dimensional dust density and extinction Maps of the Milky Way out to 2.8 kpc
T. E. Dharmawardena, C. A. L. Bailer-Jones, M. Fouesneau +5
Three-dimensional dust density maps are crucial for understanding the structure of the interstellar medium of the Milky Way and the processes that shape it. However, constructing t…
cond-mat.mtrl-sci2024
3D deep learning for enhanced atom probe tomography analysis of nanoscale microstructures
Jiwei Yu, Zhangwei Wang, Aparna Saksena +8
Quantitative analysis of microstructural features on the nanoscale, including precipitates, local chemical orderings (LCOs) or structural defects (e.g. stacking faults) plays a piv…