4 papers
Machine learning-enabled inverse design of bimaterial thermoelastic lattice metamaterials
Xiang-Long Peng, Bai-Xiang Xu
The thermoelastic metamaterial based on a bimaterial hybrid-honeycomb structure, exhibiting simultaneously negative Poisson's ratios and negative thermal expansion coefficients is…
A defect-chemistry-informed phase-field model of grain growth in oxide ceramics: application to Fe-doped SrTiO3
Kai Wang, Roger A. De Souza, Xiang-Long Peng +4
Dopants can significantly affect the properties of oxide ceramics through their impact on the property-determined microstructure characteristics such as grain boundary (GB) segrega…
Deep learning-enabled large-scale analysis of particle geometry-lithiation correlations in battery cathode materials
Binbin Lin, Luis J. Carrillo, Xiang-Long Peng +4
A deep learning model is employed to address the challenging problem of V2O5 nanoparticle segmentation and the correlation between the chemical composition and the geometrical feat…
Deciphering the interplay between wetting and chemo-mechanical fracture in lithium-ion battery cathode materials
Wan-Xin Chen, Luis J. Carrillo, Arnab Maji +4
Crack growth in lithium-ion battery electrodes is typically detrimental and undesirable. However, recent experiments suggest that stabilized fracture of cathode active materials in…