What question did this study set out to answer?

The aim is to use machine learning to optimize the HOMO-LUMO gap in diarylethene compounds for better photoresponsive materials.

April 19, 2026Physical Chemistry Chemical Physics0 citations

Machine learning-based closed-loop for optimizing HOMO–LUMO gap in diarylethene

LNLinh Thi Hoai Nguyen EFEdoardo Fabbrini AOAndriy Olenko

Key Points

The aim is to use machine learning to optimize the HOMO-LUMO gap in diarylethene compounds for better photoresponsive materials.
Utilized a machine learning-driven strategy
Focused on diarylethene switches
Optimized electronic gaps
Achieved precise tuning of electronic gaps
Accelerated the design process for high-performance materials

Abstract

Machine learning-driven strategy enables rapid discovery of diarylethene switches with precisely tuned electronic gaps, significantly accelerating the design of high-performance photoresponsive materials.

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