Conveners
Parallel Session F: Computational and Experimental Approaches to Tunable Materials Properties
- Chenxu Yu (Iowa State University)
Prediction processing-microstructure-property (PMP) link is critical for material processing, characterization, and discovery. We demonstrate GAN-based machine learning models that can accurately predict PMP relationships, specifically in the prediction of (1) the microstructure of alumina under arbitrary laser power, (2) the expected microstructure from the desired hardness, (3) real-time,...
Tuning Soft Magnetic Properties in Fe-Based Nanocrystalline Alloys via Ge Substitution
Paul White, Department of Physics
Tula R. Paudel, Department of Physics
Soft magnetic materials play a crucial role in modern electrical and electronic devices, with ongoing research focused on enhancing their performance through compositional and structural modifications. In this study, we...
Two-dimensional (2D) perovskites are promising materials for nonlinear optics, photonics, and optoelectronics due to their strong excitonic behavior, quantum confinement, and structural tunability. We investigate second-order nonlinear optical properties of mono- and few-layered (Benzylammonium)2PbX4 (where X = Br, Cl, and I), with our current focus on (Benzylammonium)2PbBr4. Bulk crystals...