Mielke, Alexander Javier and Scrimgeour, Alexander and Tapavicza, Enrico (2025) Chemical Space of Molecular Nanomotors: Optimizing Photochemical Properties for One- and Two-Photon Applications. JOURNAL OF CHEMICAL INFORMATION AND MODELING, 65 (20). pp. 11029-11046. ISSN 1549-9596, 1549-960X
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Light-driven molecular nanomotors hold promise for applications in materials science and biomedicine. Significant efforts have focused on improving their efficiency, often targeting single candidate molecules. Here, we present a systematic, data-driven approach to design nanomotors with high isomerization quantum yields for one- and two-photon applications, the latter being critical for biomedical applications requiring near-infrared light. We analyze the excited state properties of a data set of 2016 nanomotors substituted with electron-donating and electron-withdrawing (push-pull) groups. Among the top candidates, we achieved an increase in two-photon absorption strengths of up to 2 orders of magnitude compared to existing nanomotors. To ensure that the pi-pi* character of the excited state is preserved, which is necessary to achieve the required photoisomerization, we introduce a transition density similarity score that gauges the excited state character based on the transition. Furthermore, we benchmark three machine learning (ML) models-Kernel Ridge Regression, XGBoost, and a Neural Network-using physical and connectivity-based molecular descriptors. The excellent accuracy of our ML predictions holds promise to replace computationally costly quantum chemistry calculations in chemical space explorations.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | DENSITY-FUNCTIONAL METHODS; COMPUTATIONAL DESIGN; BASIS-SETS; MOTORS; ROTATION; ACCELERATION; ABSORPTION; SPEED |
| Subjects: | 500 Science > 540 Chemistry & allied sciences |
| Divisions: | Chemistry and Pharmacy > Institut für Physikalische und Theoretische Chemie |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 18 Jun 2026 05:06 |
| Last Modified: | 18 Jun 2026 05:06 |
| URI: | https://pred.uni-regensburg.de/id/eprint/66529 |
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