Dresden 2026 – scientific programme

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CPP: Fachverband Chemische Physik und Polymerphysik

CPP 46: Poster II

CPP 46.66: Poster

Thursday, March 12, 2026, 09:30–11:30, P5

Learn how to switch off: In-silico Modelling of Thermal Ring-closing Process in Spiropyran Derivatives — •Bowen Cheng, Robert Strothmann, Hendrik Heenen, and Karsten Reuter — Fritz-Haber-Institut der MPG, Berlin, Germany

Spiropyran (SP) and its derivatives undergo a ring-opening reaction via UV radiation and a ring-closing reaction in thermal conditions, making them excellent candidates for photoswitches. One key aspect that governs the sensitivity of such photoswitches is the rate of the thermal ring-closing process. A main challenge in modelling this process is the existence of various thermally accessible conformers, leading to a complex reaction network.

In this study, we highlight a combined workflow using machine-learned interatomic potential (MLIP) and a microkinetics model (MKM) to address this. With a fine-tuned MACE-OFF24 foundation model, we predict different transition state energies within the reaction network using the nudge elastic band method, and correlate these energies to experimental observations using the MKM.

Our workflow can be migrated between different SP derivatives to reveal the effect of functional group decorations. Our findings demonstrate the potential of using MLIPs to predict transition states and enable larger-scale studies of complex reaction networks. We also aim to condense our workflow as a new descriptor for in-silico screening in future spiropyran photoswitch design.

Keywords: Machine-learned Interatomic Potential; Micro-kinetics Modelling