Index

People

Head of the Group

Carolin Müller, Jun.-Prof.
E-Mail:  carolin.cpc.mueller@fau.de
Office:  Computer-Chemie-Centrum (CCC), 2.201B

Isabelle Schraufstetter, secretary
E-Mail:  ccc@fau.de
Office:  Computer-Chemie-Centrum (CCC), 2.111
Phone:  09131-85-20400

Researcher

Debabrata Halder, Postdoctoral Researcher (EAM Starting Grant)
E-Mail:  debabrata.halder@fau.de
Office:  Computer-Chemie-Centrum (CCC), 2.306

Kevin Höllring, Postdoctoral Researcher (ChemPrint, CRC 1719)
E-Mail:  kevin.hoellring@fau.de
Office:  Computer-Chemie-Centrum (CCC), 2.306

Theodor Everley Röhrkasten, PhD student
E-Mail:  theodor.roehrkasten@fau.de
Office:  Computer-Chemie-Centrum (CCC), 2.306

Martina Hartinger, PhD student (FCI Kekulé Fellowship)
E-Mail:  martina.hartinger@fau.de
Office:  Computer-Chemie-Centrum (CCC), 2.306

Shi Hui Wong, PhD student (ChemPrint, CRC 1719)
E-Mail:  shi.wong@fau.de
Office:  Computer-Chemie-Centrum (CCC), 2.306

Cansun Saglam, research/conference assistant (CCSC 2026)
E-Mail:  cansun.saglam@fau.de
Office:  Computer-Chemie-Centrum (CCC), 2.306

Chemical Compound Space Conference 2026

Connor Forster, research assistant
E-Mail:  connor.forster@fau.de
Office:  Computer-Chemie-Centrum (CCC), 2.306

Tobias Werner, research assistant
E-Mail:  tobias.werner@fau.de
Office:  Computer-Chemie-Centrum (CCC), 2.306

Undergraduate and Graduate Students

Vipul Kumar Ambasta, master student
E-Mail:  vipul.kumar.ambasta@fau.de
Office:  Computer-Chemie-Centrum (CCC), 2.306

M. Sc. Advanced Materials and Processes

Fariba Mohammadipour, master student
E-Mail:  fariba.mohammadipour@fau.de
Office:  Computer-Chemie-Centrum (CCC), 2.306

M. Sc. Artificial Intelligence

Mohammad Saad Khan, master student
E-Mail:  mohammad.s.khan@fau.de
Office:  Computer-Chemie-Centrum (CCC), 2.306

M. Sc. Artificial Intelligence

Qingwen Pang, master student
E-Mail:  qingwen.pang@fau.de
Office:  Computer-Chemie-Centrum (CCC), 2.306

M. Sc. Artificial Intelligence

Mohammad Madahian, master student
E-Mail:  mohammad.madahian@fau.de
Office:  Computer-Chemie-Centrum (CCC), 2.306

M. Sc. Artificial Intelligence

Completed Theses

M. Sc. Chemie / Chemistry

  • Shi Hui Wong (‘Rational Design of Perylene-Rhodium Photocatalysts: A Computational Investigation‘)

Completed Theses

B. Sc. Chemie

  • Katharina Fuchs (Substituent Effects on the Photoisomerization of Aza-Diarylethenes: A Theoretical Study)
  • Connor Forster (Revisiting Woodward-Fieser-Kuhn Rules and Acridine Cyclo-Annulation for efficient Prediction of Absorption Maxima)
  • Dario Karlovic (Theoretical Insights into the light-driven intramolecular [3+2] cycloaddition towards Chromenopyrazoles)
  • Tobias Werner (Combining Active Learning and Excited State Machine Learning Force Fields for the Optimization of Data Acquisition to Describe Photoisomerization)

Alumni

Nathan Pierrat (master student @ ENS Paris-Saclay)

Julia Ngo (master student @ RWTH Aachen)

Teaching

Sprechstunde/Open Office:

  • jeden Dienstag von 16:00 bis 17:00 Uhr / every Tuesday, 4:00 to 5:00 pm

Vorlesungen und Kurse/Lectures and Courses

Aktuell

Sneak Peek at the Digital Chemistry Master Module Contents
Sneak Peek at the Digital Chemistry Master Module Contents

Generelle Informationen

  • eine Liste von Lehrveranstaltungen finde Sie auf Campo
  • Material zu den Vorlesungen finden Sie auf StudOn und GitHub

Research

CPC GroupIn the Computational PhotoChemistry (CPC) group, we explore the fascinating world of light-induced molecular phenomena. By integrating quantum chemistry, chemoinformatics, and spectroscopic data, we uncover the principles driving photochemical and photophysical processes at the molecular level.
CPC Group

Research Areas

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.

Photoswicthing of peri‐Anthracenethioindigo
Topic2

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.

SPaiNN
SHNITSEL-data
ML & Photodynamics

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.

ChromoPredict
single-benzene fluorophores

Research Spotlights

  • We've developed shnitsel-tools: a powerful, user-friendly package for analyzing trajectory surface hopping simulations. No more tedious scripting or fragmented analysis! With shnitsel-tools, you can automate filtering, visualize dynamics, and uncover excited-state mechanisms across multiple molecules.

  • What happens when the wisdom of mid-20th-century chemists meets today’s digital tools?

  • We present a multistate molecular mechanics model that captures both the ground (S0) and triplet excited (T1) states of hemithioindigo-based photoswitches — enabling nanosecond-scale molecular dynamics with near quantum mechanical accuracy.

  • Curious about how machine learning is transforming excited-state molecular dynamics? Our latest overview dives into best practices for applying machine learning in non-adiabatic dynamics simulations, from data pre-processing and surface fitting to post-simulation analysis. Learn how machine learning approaches can help overcome computational bottlenecks and uncover patterns in complex photochemical systems — paving the way for data-driven design of photochemistry and -physics.

  • SHNITSEL-data (Surface Hopping Nested Instances Training Set for Excited-state Learning) is an open-access dataset containing 418,870 high-accuracy ab initio data points for nine organic molecules. It includes quantum chemical properties in ground and electronically excited singlet and triplet states, such as energies, forces, dipole moments, nonadiabatic couplings, transition dipoles, and spin-orbit couplings. Generated with state-of-the-art methods, SHNITSEL-data supports the development of machine learning models for excited-state processes in photochemistry and photophysics.

  • How does Near-Infrared-Photoswitching work? Our newest research delivers an ultrafast molecular movie of the all-red-light photoswitch peri-Anthracenethioindigo (PAT) in action! Guided by excited-state simulations, its mechanism of motion is fully revealed. We show that PAT double bond rotation occurs exclusively from the triplet state – but it is stable in air due to very favorable energy levels.

  • 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

CV Carolin Müller

Jun.-Prof. Carolin Müller
Carolins academic journey began at Friedrich Schiller University Jena, where she earned her Master of Science degree in chemistry in 2018. From 2018 to 2021, she delved into her doctoral studies at the same university, guided by Benjamin Dietzek-Ivanšić. After completing her doctorate, she spent a year as a postdoctoral researcher with Benjamin Dietzek-Ivanšić. Afterwards she moved to the University of Luxembourg, where she joined the Theoretical Chemical Physics group, led by Alexandre Tkatchenko, as a Feodor Lynen Postdoctoral researcher of the Alexander von Humboldt Foundation in June 2022. In November 2023, she joined the FAU Erlangen-Nürnberg as Assistant Professor for the Theory of Electronically Excited States.

Her research is about exploring the fascinating world of light-induced processes in chemistry, from the lively dance of electrons to the magical transformation of molecules. Her main focus is on generating, analysing, and archiving data related to excited states. To accomplish this, she blends the tools of quantum chemistry, chemoinformatics, and spectroscopy into a dynamic team to unlock the secrets behind these impressive light-driven phenomena.

since 11/2023 Juniorprofessor for the Theory of Electronically Excited States, Friedrich-Alexander-University Erlangen-Nuremberg, Germany
06/2022-10/2023 Feodor Lynen Postdoctoral Researcher, University of Luxembourg, Luxembourg
03/2021-05/2022 Postdoctoral Researcher, Friedrich Schiller University Jena, Germany
09/2018-02/2021 Dissertation (Dr. rer. nat), Friedrich Schiller University Jena, Germany
Thesis: Towards Operando Spectroscopy of Supramolecular Photocatalysts – A Case Study on Ru-dppz-derived Systems
08/2020 Research Stay, Lund University, Sweden
10/2016-09/2018 M. Sc. in Chemistry, Friedrich Schiller University Jena, Germany
02/2018-08/2018 Research Stay, Dublin City University, Ireland
10/2013-09/2016 B. Sc. in Chemistry, Friedrich Schiller University Jena, Germany

06/2022 – 10/2023 Feodor Lynen Research Fellowship, Alexander von Humboldt Foundation
04/2023 Thuringian Research Award 2023 (Applied Research), Federal State of Thuringia (Thüringer Ministerium für Wirtschaft, Wissenschaft und Digitale Gesellschaft)
09/2022 Albert-Weller Award, German Chemical Society (GDCh, Division of Photochemistry) and the German Bunsen Society for Physical Chemistry (DBG)
06/2022 Dissertation Award, Faculty of Chemistry and Earth Sciences, Friedrich Schiller University Jena
05/2019 – 02/2021 FCI Kekulé PhD fellowship, Fonds der Chemischen Industrie

  • 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

since 2023 TeX User Group (TUG)
since 2022 German Bunsen Society for Physical Chemistry e.V. (DBG) and Young Physical Chemists (yPC) of the DBG
since 2013 Gesellschaft Deutscher Chemiker (GDCh)

Publications

Research Spotlights

  • We've developed shnitsel-tools: a powerful, user-friendly package for analyzing trajectory surface hopping simulations. No more tedious scripting or fragmented analysis! With shnitsel-tools, you can automate filtering, visualize dynamics, and uncover excited-state mechanisms across multiple molecules.

  • What happens when the wisdom of mid-20th-century chemists meets today’s digital tools?

  • We present a multistate molecular mechanics model that captures both the ground (S0) and triplet excited (T1) states of hemithioindigo-based photoswitches — enabling nanosecond-scale molecular dynamics with near quantum mechanical accuracy.

  • Curious about how machine learning is transforming excited-state molecular dynamics? Our latest overview dives into best practices for applying machine learning in non-adiabatic dynamics simulations, from data pre-processing and surface fitting to post-simulation analysis. Learn how machine learning approaches can help overcome computational bottlenecks and uncover patterns in complex photochemical systems — paving the way for data-driven design of photochemistry and -physics.

  • SHNITSEL-data (Surface Hopping Nested Instances Training Set for Excited-state Learning) is an open-access dataset containing 418,870 high-accuracy ab initio data points for nine organic molecules. It includes quantum chemical properties in ground and electronically excited singlet and triplet states, such as energies, forces, dipole moments, nonadiabatic couplings, transition dipoles, and spin-orbit couplings. Generated with state-of-the-art methods, SHNITSEL-data supports the development of machine learning models for excited-state processes in photochemistry and photophysics.

  • How does Near-Infrared-Photoswitching work? Our newest research delivers an ultrafast molecular movie of the all-red-light photoswitch peri-Anthracenethioindigo (PAT) in action! Guided by excited-state simulations, its mechanism of motion is fully revealed. We show that PAT double bond rotation occurs exclusively from the triplet state – but it is stable in air due to very favorable energy levels.

List of Publications

2026

2025

2024

2023

2022

2021

2020

2019

2017

Recent Highlights

More news

We’ve developed shnitsel-tools: a powerful, user-friendly package for analyzing trajectory surface hopping simulations. No more tedious scripting or fragmented analysis! With shnitsel-tools, you can automate filtering, visualize dynamics, and uncover excited-state mechanisms across multiple molecules.

What happens when the wisdom of mid-20th-century chemists meets today’s digital tools?

We present a multistate molecular mechanics model that captures both the ground (S0) and triplet excited (T1) states of hemithioindigo-based photoswitches — enabling nanosecond-scale molecular dynamics with near quantum mechanical accuracy.

Curious about how machine learning is transforming excited-state molecular dynamics? Our latest overview dives into best practices for applying machine learning in non-adiabatic dynamics simulations, from data pre-processing and surface fitting to post-simulation analysis. Learn how machine learning approaches can help overcome computational bottlenecks and uncover patterns in complex photochemical systems — paving the way for data-driven design of photochemistry and -physics.

SHNITSEL-data (Surface Hopping Nested Instances Training Set for Excited-state Learning) is an open-access dataset containing 418,870 high-accuracy ab initio data points for nine organic molecules. It includes quantum chemical properties in ground and electronically excited singlet and triplet states, such as energies, forces, dipole moments, nonadiabatic couplings, transition dipoles, and spin-orbit couplings. Generated with state-of-the-art methods, SHNITSEL-data supports the development of machine learning models for excited-state processes in photochemistry and photophysics.

How does Near-Infrared-Photoswitching work? Our newest research delivers an ultrafast molecular movie of the all-red-light photoswitch peri-Anthracenethioindigo (PAT) in action! Guided by excited-state simulations, its mechanism of motion is fully revealed. We show that PAT double bond rotation occurs exclusively from the triplet state – but it is stable in air due to very favorable energy levels.

List of publications can also be found here:

Personal Website
Google Scholar
ResearchGate
ORCID
Web Of Science

Teaching

Sprechstunde/Open Office:

  • jeden Dienstag von 16:00 bis 17:00 Uhr / every Tuesday, 4:00 to 5:00 pm

Vorlesungen und Kurse/Lectures and Courses

Aktuell

Sneak Peek at the Digital Chemistry Master Module Contents
Sneak Peek at the Digital Chemistry Master Module Contents

Generelle Informationen

  • eine Liste von Lehrveranstaltungen finde Sie auf Campo
  • Material zu den Vorlesungen finden Sie auf StudOn und GitHub

About Carolin Müller

Jun.-Prof. Carolin Müller
Carolins academic journey began at Friedrich Schiller University Jena, where she earned her Master of Science degree in chemistry in 2018. From 2018 to 2021, she delved into her doctoral studies at the same university, guided by Benjamin Dietzek-Ivanšić. After completing her doctorate, she spent a year as a postdoctoral researcher with Benjamin Dietzek-Ivanšić. Afterwards she moved to the University of Luxembourg, where she joined the Theoretical Chemical Physics group, led by Alexandre Tkatchenko, as a Feodor Lynen Postdoctoral researcher of the Alexander von Humboldt Foundation in June 2022. In November 2023, she joined the FAU Erlangen-Nürnberg as Assistant Professor for the Theory of Electronically Excited States.

Her research is about exploring the fascinating world of light-induced processes in chemistry, from the lively dance of electrons to the magical transformation of molecules. Her main focus is on generating, analysing, and archiving data related to excited states. To accomplish this, she blends the tools of quantum chemistry, chemoinformatics, and spectroscopy into a dynamic team to unlock the secrets behind these impressive light-driven phenomena.

since 11/2023 Juniorprofessor for the Theory of Electronically Excited States, Friedrich-Alexander-University Erlangen-Nuremberg, Germany
06/2022-10/2023 Feodor Lynen Postdoctoral Researcher, University of Luxembourg, Luxembourg
03/2021-05/2022 Postdoctoral Researcher, Friedrich Schiller University Jena, Germany
09/2018-02/2021 Dissertation (Dr. rer. nat), Friedrich Schiller University Jena, Germany
Thesis: Towards Operando Spectroscopy of Supramolecular Photocatalysts – A Case Study on Ru-dppz-derived Systems
08/2020 Research Stay, Lund University, Sweden
10/2016-09/2018 M. Sc. in Chemistry, Friedrich Schiller University Jena, Germany
02/2018-08/2018 Research Stay, Dublin City University, Ireland
10/2013-09/2016 B. Sc. in Chemistry, Friedrich Schiller University Jena, Germany

06/2022 – 10/2023 Feodor Lynen Research Fellowship, Alexander von Humboldt Foundation
04/2023 Thuringian Research Award 2023 (Applied Research), Federal State of Thuringia (Thüringer Ministerium für Wirtschaft, Wissenschaft und Digitale Gesellschaft)
09/2022 Albert-Weller Award, German Chemical Society (GDCh, Division of Photochemistry) and the German Bunsen Society for Physical Chemistry (DBG)
06/2022 Dissertation Award, Faculty of Chemistry and Earth Sciences, Friedrich Schiller University Jena
05/2019 – 02/2021 FCI Kekulé PhD fellowship, Fonds der Chemischen Industrie

  • 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

since 2023 TeX User Group (TUG)
since 2022 German Bunsen Society for Physical Chemistry e.V. (DBG) and Young Physical Chemists (yPC) of the DBG
since 2013 Gesellschaft Deutscher Chemiker (GDCh)

Prof. Dr. Carolin Müller

Prof. Dr. Carolin Müller

Department of Chemistry and Pharmacy
Juniorprofessur für die Theorie elektronisch angeregter Zustände

Room: Room CCC 2.201b
Nägelsbachstr. 25
91052 Erlangen

Section

Theoretical and Computer Chemistry

Research areas

Molecular materials:
Energy

Molecular and material modeling for solar energy conversion

Modeling excited-state processes and reactions triggered by light absorption or energy transfer

Molecular materials:
Sustainability

Efficient workflows for predicting photoinduced processes and reactions

Bioactive Compounds:
Compound discovery

Creation of computational chemistry databases

Machine learning for molecular and material design

Member of:

FAU Profile Center New Materials and Processes (FAU NMP)

FAU Profile Center Solar (FAU Solar)

FAU Competence Center Engineering of Advanced Materials (FAU EAM)

Computer Chemistry Center (CCC)

Research Focus

The research in Prof. Carolin Müller’s Computational PhotoChemistry 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.

  • 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

Publications

Recent Highlights

  • We've developed shnitsel-tools: a powerful, user-friendly package for analyzing trajectory surface hopping simulations. No more tedious scripting or fragmented analysis! With shnitsel-tools, you can automate filtering, visualize dynamics, and uncover excited-state mechanisms across multiple molecules.

  • What happens when the wisdom of mid-20th-century chemists meets today’s digital tools?

  • We present a multistate molecular mechanics model that captures both the ground (S0) and triplet excited (T1) states of hemithioindigo-based photoswitches — enabling nanosecond-scale molecular dynamics with near quantum mechanical accuracy.

  • Curious about how machine learning is transforming excited-state molecular dynamics? Our latest overview dives into best practices for applying machine learning in non-adiabatic dynamics simulations, from data pre-processing and surface fitting to post-simulation analysis. Learn how machine learning approaches can help overcome computational bottlenecks and uncover patterns in complex photochemical systems — paving the way for data-driven design of photochemistry and -physics.

  • SHNITSEL-data (Surface Hopping Nested Instances Training Set for Excited-state Learning) is an open-access dataset containing 418,870 high-accuracy ab initio data points for nine organic molecules. It includes quantum chemical properties in ground and electronically excited singlet and triplet states, such as energies, forces, dipole moments, nonadiabatic couplings, transition dipoles, and spin-orbit couplings. Generated with state-of-the-art methods, SHNITSEL-data supports the development of machine learning models for excited-state processes in photochemistry and photophysics.

  • How does Near-Infrared-Photoswitching work? Our newest research delivers an ultrafast molecular movie of the all-red-light photoswitch peri-Anthracenethioindigo (PAT) in action! Guided by excited-state simulations, its mechanism of motion is fully revealed. We show that PAT double bond rotation occurs exclusively from the triplet state – but it is stable in air due to very favorable energy levels.

List of Publications

2026

2025

2024

2023

2022

2021

2020

2019

2017

List of publications can also be found here:

Recent Highlights

More news

Team

Head of the Group

Carolin Müller, Jun.-Prof.
E-Mail:  carolin.cpc.mueller@fau.de
Office:  Computer-Chemie-Centrum (CCC), 2.201B

Isabelle Schraufstetter, secretary
E-Mail:  ccc@fau.de
Office:  Computer-Chemie-Centrum (CCC), 2.111
Phone:  09131-85-20400

Researcher

Debabrata Halder, Postdoctoral Researcher (EAM Starting Grant)
E-Mail:  debabrata.halder@fau.de
Office:  Computer-Chemie-Centrum (CCC), 2.306

Kevin Höllring, Postdoctoral Researcher (ChemPrint, CRC 1719)
E-Mail:  kevin.hoellring@fau.de
Office:  Computer-Chemie-Centrum (CCC), 2.306

Theodor Everley Röhrkasten, PhD student
E-Mail:  theodor.roehrkasten@fau.de
Office:  Computer-Chemie-Centrum (CCC), 2.306

Martina Hartinger, PhD student (FCI Kekulé Fellowship)
E-Mail:  martina.hartinger@fau.de
Office:  Computer-Chemie-Centrum (CCC), 2.306

Shi Hui Wong, PhD student (ChemPrint, CRC 1719)
E-Mail:  shi.wong@fau.de
Office:  Computer-Chemie-Centrum (CCC), 2.306

Vipul Kumar Ambasta, research assistant (eti)
E-Mail:  vipul.kumar.ambasta@fau.de
Office:  Computer-Chemie-Centrum (CCC), 2.306

Cansun Saglam, research/conference assistant (CCSC 2026)
E-Mail:  cansun.saglam@fau.de
Office:  Computer-Chemie-Centrum (CCC), 2.306

Chemical Compound Space Conference 2026

Connor Forster, research assistant
E-Mail:  connor.forster@fau.de
Office:  Computer-Chemie-Centrum (CCC), 2.306

Undergraduate and Graduate Students

M. Sc. Chemie / Chemistry

  • Shi Hui Wong

M. Sc. Artificial Intelligence

  • Fariba Mohammadipour
  • Qingwen Pang
  • Mohammad Madahian

B. Sc. Chemie

  • Katharina Fuchs
  • Connor Forster
  • Dario Karlovic
  • Tobias Werner

Alumni

Nathan Pierrat, research student
E-Mail:  nathan.pierrat@ens-paris-saclay.fr
Office:  Computer-Chemie-Centrum (CCC), 2.306