Artificial intelligence (AI) is rapidly emerging as a enabling tool for solving complex materials
design problems. This paper aims to review recent advances in AI‐driven materials‐by …

Predictive simulations of the shock‐to‐detonation transition (SDT) in heterogeneous
energetic materials (EM) are vital to the design and control of their energy release and …

The thermo-mechanical response of shock-initiated energetic materials (EMs) is highly
influenced by their microstructures, presenting an opportunity to engineer EM …

Modeling unsteady, fast transient, and advection-dominated physics problems is a pressing
challenge for physics-aware deep learning (PADL). The physics of complex systems is …

Understanding the impact-induced deformation and ignition properties of high-ductility
composite energetic material (CEM), including high-energy propellants and casted high …

Multi-scale predictive models for the shock sensitivity of energetic materials connect energy
localization (“hotspots”) in the microstructure to macro-scale detonation phenomena …

Electromagnetohydrodynamic (EMHD) flow in porous media is recently gaining substantial
attention from researchers. EMHD involves analyzing the combined effects of electric and …

Reactive burn models for heterogeneous energetic materials (EMs) must account for
chemistry as well as microstructure to predict shock-to-detonation transition (SDT). Upon …

Cavities and other fracture structures within energetic materials may have significant impact
on their performance. The mechanism on how hot spots induced by cavity collapse affect the …

When high-energy-density materials are subjected to thermal or mechanical insults at
extreme conditions (shock loading), a coupled response between the thermo-mechanical …