Domain-Gated Latent Diffusion: Generative Inverse Design of HMX-Class Energetic Materials with First-Principles Validation
Energetic materials power mining, demolition, propulsion and airbags, yet today's compounds were designed decades ago. A successor must combine high energy release, low sensitivity to accidental initiation and a practical synthesis route, found within an astronomically large molecular space. Generative models are the natural search tool, but their training data are mostly untrustworthy: of approximately 66,000 molecules with recorded properties, only approximately 3,000 were measured or computed from first principles. Models trained on all of them imitate the rough estimates and propose molecules that collapse under real physics. We introduce Domain-Gated Latent Diffusion (DGLD), a diffus...
| Authors | Yehudit Aperstein, Alexander Apartsin |
|---|---|
| Primary category | physics.chem-ph |
| Published | 26 May 2026 |
| Last updated at source | 6 August 2026 |
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