Vibrational energy transfer in RDX from selective IR excitation
A non-equilibrium kinetic model resolves how IR photons drive mode-specific vibrational populations in RDX. Direct insight into how energy localizes before bond breaking.
Research Area
How does a molecular crystal respond when struck, shocked, heated, or sparked? CECD's energetic-materials science program answers that question across length and time scales, combining first-principles chemistry, mesoscale defect dynamics, and large-scale validation against experimental data from federal laboratories.
Material systems
Length scales
Time scales
Methods
Initiation, growth, and detonation in heterogeneous explosives remain among the hardest problems in materials science. CECD attacks the problem with the only honest approach: rigorous multi-scale theory tied tightly to experiment.
Selective IR excitation, mode-resolved phonon kinetics, and non-equilibrium dynamics in RDX and analogous secondary explosives.
A new class of chemically driven, spatially programmed energetic molecular ferroelectrics. Controlled energy release through ferroelectric switching.
Peierls stress, dislocation nucleation, generalized stacking faults, and high-pressure phase transitions in α-RDX.
Critical evaluation, parameterization, and refinement of reactive potentials for accurate vibrational spectra and reaction kinetics.
Joint-embedding generative frameworks that propose nitrogen-rich molecules. Similar but improved relative to known candidates.
Domain-specific NLP pipelines that compress the energetic-materials literature into queryable structure-property graphs.
Selected studies that capture the program's breadth. Vibrational energy transfer, ML-driven property prediction, and chemically driven ferroelectricity in energetic crystals.
A non-equilibrium kinetic model resolves how IR photons drive mode-specific vibrational populations in RDX. Direct insight into how energy localizes before bond breaking.
A new chemistry of energetic molecular ferroelectrics in which ferroelectric switching controls how, and where. Chemical energy is released.
A foundational study showing that supervised ML models trained on curated experimental data can predict density, detonation velocity, and impact sensitivity from molecular structure alone.
The program brings together specialized capabilities developed over two decades, and is integrated with the wider CECD portfolio in mechanics, manufacturing, and diagnostics.
DFT, AIMD, and hybrid functionals for accurate reaction energetics in molecular crystals.
Large-scale molecular dynamics with refined reactive force fields for shock-to-detonation studies.
Models trained on curated property databases for inverse design and rapid screening.
Tight loops with ARL, NSWC IHEODTD, LANL, and Sandia diagnostic facilities for validation.
Inquiries about sponsored research, graduate training, or technology transitions in this area can be directed to the center.