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Nanophotonic structures that enhance light-matter interaction can increase the sensitivity of spectroscopic optical measurements, such as detection and enantiomer discrimination of chiral molecules. However, this improved sensitivity comes at the cost of complicated modification of the spectra, and it is necessary to account for this during the experiment and in data analysis. This calls for the construction of a digital twin: a comprehensive computer model of the experiment.
In this work [1], we develop a digital twin for a chiral sensing platform based on helicity-preserving optical cavities that enhance the circular dichroism (CD) signal of molecules [2]. The digital twin comprises a series of simulations, each related to a certain part of the sensing device. The chiral molecules are modelled using density functional theory-based simulations, and the light-matter interaction and the formation of the detectable signal are modelled using optical simulations [3,4]. A machine learning-based approach bridges the calculation results with experimentally measurable data. The digital twin is needed to interpret the experimental results and reconstruct the molecule’s CD spectrum from measurement data. It is also used to design the optical cavities while accounting for the limitations of the experimental equipment.
The idea of using a digital twin to support nanophotonically enhanced optical experiments broadly applies to measurements other than CD spectroscopy. As increasing effort is put into utilizing nanophotonic concepts in measurement devices, we expect digital twins to be an important part of such experimental workflows.
[1] M. Nyman et al., Laser Photonics Rev. 2024, 2300967 (2024).
[2] J. Feis et al., Phys. Rev. Lett. 124, 033201 (2020).
[3] I. Fernandez-Corbaton et al., ChemPhysChem 21, 878 (2020).
[4] D. Beutel et al., Comp. Phys. Comm. 297, 109076 (2024).