4 papers · 1 filter
Microstructure-Aware Deep Learning Bridges Atomistics to Macroscale for Shock-to-Detonation Prediction
Simon Gonzalez-Zapata, Aidan Pantoya, Chunyu Li +2
The shock-to-detonation transition in energetic materials is governed by coupled processes spanning Angstroms to millimeters and femtoseconds to microseconds, where traditional mul…
Predictive models for strain energy in condensed phase reactions
Baptiste Martin, Shukai Yao, Chunyu Li +3
Molecular modeling of thermally activated chemistry in condensed phases is essential to understand polymerization, depolymerization, and other processing steps of molecular materia…
Multi-Fidelity Predictive Model for Shock Response of Energetic Materials Using Conditional U-Net
Brian H. Lee, Chunyu Li, Aidan Pantoya +3
Mapping microstructure to properties is central to materials science. Perhaps most famously, the Hall-Petch relationship relates average grain size to strength. More challenging ha…
Spall strength of symmetric tilt grain boundaries in 6H silicon carbide
Chunyu Li, Alejandro Strachan
Characterizing microstructural effects on the dynamical response of materials is challenging due to the extreme conditions and the short timescales involved. For example, little is…