RSC Mechanochemistry is excited to present October’s Paper of the month, titled A computational model for predicting triplet excitation energy distributions under ball-milling conditions. This study by Luis Manuel Frutos and colleagues presents a computational model to predict triplet excitation energy distributions under ball-milling conditions.
“Our research group has a long-standing background in investigating excited-state properties in molecular systems as well as the mechanical control of processes in excited states, including the study of non-vertical triplet energy transfer where we developed some theoretical models,” says Dr Frutos about the inspiration behind this study. “The convergence of this background with our recent contributions to the theoretical study of ball-milling processes led us to explore mechano-photochemistry under ball-milling conditions, where this work is framed and that constitute our first contribution.
“We are particularly interested in developing theoretical and computational tools useful for the scientific community in the mechanochemistry field. Combining mechanical input with electronic excited states introduce significant complexity but also versatility to reach new goals for instance in synthesis or photocatalysis applications. Understanding this interplay may encourage experimental community to further explore this area.”
Asked about the impact of their work for the mechanochemistry field, Dr Frutos added: “Our primary goal is to develop computational models/tools to advance in modelling mechanochemical processes to advance in overcoming the gap between experimental work and computational predictions. Ball-milling processes are exceptionally complex from the computational point of view. We hope this framework will provide not only an approach to understand the effect of ball-milling on triplet excitation energies, but a simple first approach to model, understand and rationalize these processes.”
Want to discover more? Read their article for free:
Alejandro Jodra, Manuel Temprado, Luis Manuel Frutos
RSC Mechanochem. 2026, Advance Article, DOI: 10.1039/D6MR00065G