New Research Shows Successful Ab Initio Crystal Structure Prediction of Energetic Materials

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The figure shows the energy ranking, where lower energy means higher stability, as a function of density for the most stable crystal structures generated by the algorithm.
The figure shows the energy ranking, where lower energy means higher stability, as a function of density for the most stable crystal structures generated by the algorithm.

September 5, 2023 | Originally published by Lawrence Livermore National Laboratory on August 31, 2023

New research by Lawrence Livermore National Laboratory researchers and collaborators from Carnegie Mellon University (CMU) demonstrates that crystal structure prediction is a useful tool for studying the various ways the molecules can pack together, also known as ubiquitous polymorphism, in energetic materials. The research also shows promise of becoming an integral part of the energetic materials development pipeline.

Experimental synthesis of novel energetic materials can be a costly, time-consuming and hazardous process, sometimes requiring a significant amount of trial and error. If material properties could be predicted ahead of time, compound selection and solid form development process could be streamlined.

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