Authors: Debashree Ghosh
Source: Zenodo (CERN European Organization for Nuclear Research) (article, 2026-02-02)
Field: Materials Science — Materials Chemistry

Photophysics in Condensed Phases – Methods and Applications Photophysics and light-matter interaction is central to the functioning of several biological and materially relevant processes. Polyaromatic hydrocarbons (PAHs) such as acenes have long been studied due to its interesting optical properties and low singlet triplet gaps. Since complete active space based methods cannot be applied to such large active spaces, we have developed density matrix renormalization group (DMRG)1 based approaches. Small modification to the PAH topology shows interesting new phases of behaviour in its optical gaps. We have understood the effect of these effects based on spin frustration due to the presence of odd membered rings.2 Further developments based on artificial neural network based configuration interaction for strongly correlated systems will also be discussed.3 The similarities between the ANNs and the MPS wavefunctions will be leveraged for 2D systems.4 Using the methods developed in the group we study singlet fission phenomena and develop an integrated framework for multi-excitonic processes.5,6 Furthermore, the biological pigment melanin is the primary component in our skin that is responsible for photoprotection from sunlight. While this fact is well acknowledged, the exact molecular mechanism of the process is much more obscure. It is further complicated because of the lack of knowledge about the exact structure of melanin. We use computational tools to understand the mechanism of photoprotection in melanin and find the crucial role of heterogeneity is central to efficient nonradiative decay without any structural damage.7 Structure elucidation of melanin from inverse design approaches will also be discussed.8,9,10 1. In the quest for a stable triplet state in small polyaromatic hydrocarbons: an in silico tool for rational design and prediction, M. Rano, S.K. Ghosh, D. Ghosh, Chemical Science, 10, 9270 (2019).2. Configuration interaction trained by neural networks : Application to model polyaromatic hydrocarbons, S.K. Ghosh, M. Rano, D. Ghosh, J. Chem. Phys., 154, 094117 (2021).3. Active learning assisted MCCI to target spin states, K. Seth, D. Ghosh, J. Chem. Theory Comput., 19(2), 524 (2023).4. Machine learning matrix product state ansatz for strongly correlated systems, S.K. Ghosh, D. Ghosh, J. Chem. Phys., 158, 064108 (2023).5. Mechanism of singlet fission in carotenoids from a polyene model system, S. Santra, J. Ray, D. Ghosh, J. Phys. Chem. Lett., 13(29), 6800 (2022).6. Unravelling the geometrical effects on singlet fission in carotenoids: A Model Perspective, S. Santra, D. Ghosh, J. Phys Chem A, 129, 2738 (2025).7. Computational aspects towards understanding photoprocesses in eumelanin, D. Ghosh, WIREs Comput. Mol. Science., 11(3), e1505 (2021).8. Structure prediction from spectra amidst dynamical heterogeneity, A. Choudhury, R. Ramakrishnan, D. Ghosh, Chem Comm, 60, 2613 (2024).9. Machine learning modeling of electronic spectra and thermodynamic stability from a comprehensive chemical space of melanin, A. Choudhury, D. Ghosh, Chemical Science, 16, 9230 (2025).10. Elucidating the structure of melanin and its structure-property correlation, A. Choudhury, D. Ghosh, Acc. Chem. Res., 58, 1509 (2025). Singlet state ; Photoprotection ; Component (thermodynamics) ; Triplet state ; Density matrix renormalization group ; Melanin ; Mechanism (biology) ; Density functional theory ; Matrix (chemical analysis) Machine Learning in Materials Science ; Advanced Physical and Chemical Molecular Interactions ; Synthesis and Properties of Aromatic Compounds