3 papers
cond-mat.mtrl-sci2026
Compositionally tuned phase transformations enhance pyroelectric energy harvesting from low-grade heat
Ruiheng Geng, Ka Hung Chan, Xinyue Huang +6
Phase-transforming pyroelectric materials have emerged as promising candidates for low-grade thermal energy harvesting. However, whether first-order transformations with large pyro…
cond-mat.mtrl-sci2025
FerroAI: A Deep Learning Model for Predicting Phase Diagrams of Ferroelectric Materials
Chenbo Zhang, Xian Chen
Composition-temperature phase diagrams are crucial for designing ferroelectric materials, however predicting them accurately remains challenging due to limited phase transformation…
cond-mat.mtrl-sci2025
Physics-informed Machine Learning Analysis for Nanoscale Grain Mapping by Synchrotron Laue Microdiffraction
Ka Hung Chan, Xinyue Huang, Nobumichi Tamura +1
Understanding the grain morphology, orientation distribution, and crystal structure of nanocrystals is essential for optimizing the mechanical and physical properties of functional…