An automated photo-isomerisation and kinetics characterisation system for molecular photoswitches

Abstract

Physical chemistry parameters such as absorbance, photoconversion quantum yield, and thermal half-lives are crucial for the characterisation of new molecular photoswitch systems. In a traditional workflow, these parameters are challenging and time-consuming to measure. In this paper, a high-throughput flow-based photoswitch characterisation platform with a built-in broad-spectrum LED array and thermal back-conversion capabilities is developed with UV-Vis spectroscopic analysis tools to reduce materials consumption, limit laborous workflows, and improve experimental reproducibility. Following the experiments, an in-house developed Python program is used for easy and fast data analysis. The program is designed to be able to analyse different types of photoswitches depending on the molecular properties. The specific components and configurations are detailed, enabling reproducibility and adaptation to various experimental needs. This system demonstrates the potential for efficient, high-throughput analysis in spectroscopic studies. Wide applicability is underlined by showing the results and comparison of three different photoswitch types, norbornadienes, bicyclooctadienes, and azobenzenes. The results we obtain are in good agreement with reported values in the literature.

Graphical abstract: An automated photo-isomerisation and kinetics characterisation system for molecular photoswitches

Supplementary files

Transparent peer review

To support increased transparency, we offer authors the option to publish the peer review history alongside their article.

View this article’s peer review history

Article information

Article type
Paper
Submitted
22 Jan 2025
Accepted
20 Jun 2025
First published
30 Jun 2025
This article is Open Access
Creative Commons BY license

Digital Discovery, 2025, Advance Article

An automated photo-isomerisation and kinetics characterisation system for molecular photoswitches

J. L. Elholm, P. Baronas, P. A. Gueben, V. Gneiting, H. Hölzel and K. Moth-Poulsen, Digital Discovery, 2025, Advance Article , DOI: 10.1039/D5DD00031A

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given.

Read more about how to correctly acknowledge RSC content.

Social activity

Spotlight

Advertisements