Generative chemical language models pretrained on general chemical data and fine-tuned on energetic materials datasets enable accelerated discovery of synthetically accessible high-performance compounds.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
physics.chem-ph 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Generative Chemical Language Models for Energetic Materials Discovery
Generative chemical language models pretrained on general chemical data and fine-tuned on energetic materials datasets enable accelerated discovery of synthetically accessible high-performance compounds.