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Machine Learning of Two-Dimensional Spectroscopic Data
摘要： Two-dimensional electronic spectroscopy has become one of the main experimental tools for analyzing the dynamics of excitonic energy transfer in large molecular complexes. Simplified theoretical models are usually employed to extract model parameters from the experimental spectral data. Here we show that computationally expensive but exact theoretical methods encoded into a neural network can be used to extract model parameters and infer structural information such as dipole orientation from two dimensional electronic spectra (2DES) or reversely, to produce 2DES from model parameters. We propose to use machine learning as a tool to predict unknown parameters in the models underlying recorded spectra and as a way to encode computationally expensive numerical methods into efficient prediction tools. We showcase the use of a trained neural network to efficiently compute disordered averaged spectra and demonstrate that disorder averaging has non-trivial effects for polarization controlled 2DES.
关键词： Neural Networks,excitonic energy transfer,light-harvesting complexes,ML numerical methods
更新于2025-09-23 15:23:52
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The molecular mechanisms of light adaption in light-harvesting complexes of purple bacteria revealed by a multiscale modeling
摘要： The light-harvesting in photosynthetic purple bacteria can be tuned in response to the light conditions during cell growth. One of the used strategies is to change the energy of the excitons in the major light-harvesting complex, commonly known as LH2. In the present study we report the first systematic investigation of the microscopic origin of the exciton tuning using three complexes, namely the common (high-light) and the low-light forms of LH2 from Rps. acidophila plus a third complex analogous to the PucD complex from Rps. palustris. The study is based on the combination of classical molecular dynamics of each complex in a lipid membrane and excitonic calculations based on a multiscale quantum mechanics/molecular mechanics approach including a polarizable embedding. From the comparative analysis, it comes out that the mechanisms that govern the adaptation of the light conditions use the different H-bonding environment around the bacteriochlorophyll pigments to dynamically control both internal and inter-pigment degrees of freedom. While the former have a large effect on the site energies, the latter significantly change the electronic couplings, but only the combination of the two effects can fully reproduce the tuning of the final excitons and explain the observed spectroscopic differences.
关键词： purple bacteria,H-bonding environment,multiscale modeling,light-harvesting complexes,excitonic tuning
更新于2025-09-16 10:30:52