Prof. Dr. Carolin Müller

Computational PhotoChemistry Group

CM

Professorship for the Theory of Excited Electronic States

Assistant professors

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Nägelsbachstraße 25 91052 Erlangen

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Research Focus
The research in Prof. Carolin Müller’s Computational PhotoChemistry (CPC) Group focuses on the fascinating field of light-induced physical processes and chemical reactions, ranging from electron transfer processes to isomerization. By using advanced computational methods, the mechanisms behind photoinduced phenomena are revealed. A central focus is on the control and optimization of light-driven processes to achieve increased reactivity and efficiency. This research direction is interdisciplinary in nature and not only combines approaches from quantum chemistry and chemoinformatics, but also works closely with experimental, spectroscopic research groups.
Mechanistic Studies of Photoactive Molecules

Our group investigates the fundamental mechanisms that govern how photoactive molecules convert light into motion, charge, or chemical reactivity. Using excited-state quantum chemical simulations and photodynamics simulations, we uncover how structural features, key geometries (e.g. minima, transition states and conical intersections), and spin states shape photophysical properties and photochemical reactions. These insights guide the rational design of molecular photoswitches and photocatalysts with tailored performance.

Data Infrastructure & Machine Learning for Excited-State Dynamics

We are developing tools to support the lifecycle of excited-state dynamics data, beginning once trajectories are available. We aim to enable exploratory analysis, visualization, and the extraction of mechanistic insights, while standardizing how simulation data are stored and applied in machine learning workflows. By bridging raw trajectory data with AI models and community data standards, we aim to facilitate reproducible, large-scale, and accelerated simulations of photoactive systems, providing researchers with streamlined tools to efficiently turn data into understanding.
Molecular Design and Functional Photoactive Materials

Building on mechanistic and computational insights, we design and predict new classes of functional photoactive molecules. Our work combines quantum chemistry and digital chemistry approaches to discover fluorophores and chromophores with optimized photophysical properties — from always-on fluorescence to digitally predicted absorption properties.





We are always interested in hearing from motivated students and researchers with an interest in quantum chemistry, excited-state theory, and digital chemistry. Even if no official positions are currently advertised, feel free to get in touch if you are interested in our research.

Prospective Bachelor’s and Master’s students are particularly encouraged to contact us by email with a short statement of interest. A selection of previous thesis topics listed below may serve as inspiration for possible projects:

  • Substituent Effects on the Photoisomerization of Aza-Diarylethenes: A Theoretical Study
  • Theoretical Insights into the light-driven intramolecular [3+2] cycloaddition towards Chromenopyrazoles
  • Combining Active Learning and Excited State Machine Learning Force Fields for the Optimization of Data Acquisition to Describe Photoisomerization
  • Time-Series Learning for Efficient Simulation Steering: A Case Study on Photoinduced E/Z-Isomerization

  • Beyond Retinal: Machine Learning Models for Photochemical Control in Rhodopsins


    (Third Party Funds Single)
    Project leader:
    Term: 1. June 2026 - 31. May 2030
    Funding source: Stiftungen
    Abstract

    Rhodopsins are light sensitive proteins that play key roles in vision and other biological processes. Although they share the same light absorbing molecule, their responses vary due to the surrounding protein environment. This project uses machine learning together with simulations and experiments to understand and predict these light driven reactions, with the aim of enabling the design of new light sensitive proteins for applications in biology and medicine.

  • Excited-state phenomena: Unraveling structure-property relationships across dimensions


    (Third Party Funds Group – Sub project)
    Overall project: SFB 1719: Next-generation printed semiconductors: Atomic-level engineering via molecular surface chemistry
    Project leader:
    Term: 1. October 2025 - 30. June 2029
    Acronym: SFB 1719 M02
    Funding source: DFG / Sonderforschungsbereich (SFB)
    Abstract

    Project M2 is devoted to the development and application of approaches to elucidate and predict excited  state phenomena in aggregates of varying numbers of atoms and molecules. This includes studying model systems throughout the molecular precursor-to-material pathway, from individual atoms and molecules to aggregates and extended systems such as two-dimensional (2D) materials on different length-scales (e.g., monolayers or multilayers), assembled molecules (e.g., dimers or monolayers), and molecules adsorbed or covalently bonded on surfaces. The primary focus will be on transition metal dichalcogenides, V-VI chalcogenides, and perovskites for materials, and photoswitches for molecular systems. To address this challenge, we will use a combination of ab initio quantum chemical methods, such as time-dependent density functional theory and many-body perturbation theory, along with data science techniques. This approach will help us to explore structure- and size-dependent properties of excited state phenomena, including electronic absorption and emission spectra and the yield and rate of certain photoinduced processes. The developed procedures will be critically validated through close collaboration with experimental spectroscopic projects, reinforcing our understanding of how certain structures determine the excited state properties of materials.

  • Navigating the Odyssey of Photochemistry: Charting Efficient Strategies for the Prediction and Optimization of Light-Induced Triplet Energy Transfer Reactions


    (Third Party Funds Single)
    Project leader:
    Term: 1. February 2025 - 31. January 2031
    Acronym: HRCD 2024
    Funding source: Stiftungen
    URL: https://hector-fellow-academy.de/spitzenforschung/hector-rcd-awardees/carolin-mueller/

  • PRISM: Photochemical Rules and Insights for Systematic Modeling


    (FAU Funds)
    Project leader:
    Term: 1. December 2024 - 31. December 2025
    Acronym: EAM-SG24-01

  • Eco-PhotoCompute - Crafting Sustainable Strategies for Computational Photochemistry


    (FAU Funds)
    Project leader:
    Term: 15. July 2024 - 15. July 2025
    Acronym: ETI-Förderung 2024-2_Nat_09_Mueller
Group Members
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Research
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CV