Juniorprofessorship Westermayr

News

  • Our latest preprints

    High-throughput property-driven generative design of functional organic molecules in arXiv:2207.01476 (2022)

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  • Rhyan Barrett new PhD student.

    He will work on the development of deep learning methods. He will use reinforcement learning to discover reaction pathways in organic molecules, peptides, and proteins and to better understand their…

Theoretische Chemie des Materialdesign, Grafik: Julia Westermayr

Overview

The overall goal of the research is to use machine learning methods to address current problems in theoretical chemistry.

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Research

The group develops and uses unsupervised, supervised and reinforcement learning to advance the modeling and design of new molecules and materials.

Projects

The design of new materials can be driven with unsupervised machine learning (ML), such as generative learning. Here, a model can learn from a set of structures and can predict new ones that have never been seen before but have similar properties. Combined with predictive models, molecules can be created that have optimized properties. These techniques should be applied to design novel organic, inorganic, and hybrid systems that could serve as, e.g., building blocks for organic electronics, catalysts or inhibitors for certain reactions.

Light is ubiquitous. Thus, it is probably not surprising that nature and life as we know it inherently depends on light-induced reactions. Yet, it is extremely difficult to study light-matter interactions and to unravel mechanisms of light-induced reactions. With the help of ML, new methods will be developed that can accelerate the simulation of photochemical reactions and can provide access to properties that cannot be computed with traditional quantum chemical methods.

With the help of predictive, supervised ML models, we want to understand mechanistic details of reactions of molecules. One particular focus is the self-assembly of molecules. Self-assembly is the organized formation of highly-ordered structures or patterns from molecular building blocks. While this reaction can be useful to form functional nanomaterials, it also takes place in the human body and can lead to the aggregation of peptides and proteins, which plays a role, for instance, in Alzheimer’s or Parkinson’s disease.

Due to the increasing amount of data that becomes available, new techniques are needed to extract information. We will use unsupervised learning to extract information hidden behind the complexity of data. In addition, we will use tools from explainable artificial intelligence to better understand how a ML model learns – paving the way towards the discovery of new chemical rules still hidden from us.

Publications

Our latest publications

  • High-throughput property-driven generative design of functional organic molecules

    J. Westermayr,* J. Gilkes, R. Barrett, R. J. Maurer*, arXiv:2207.01476 (2022)

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  • Deep learning study of tyrosine reveals that roaming can lead to photodamage

    J. Westermayr, M. Gastegger, D. Vörös, L. Panzenboeck, F. Joerg, L. González, P. Marquetand, Nat. Chem. 14, 914-919 (2022)

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  • BuRNN: Buffer Region Neural Network Approach for Polarizable-Embedding Neural Network/Molecular Mechanics…

    B. Lier, P. Poliak, P. Marquetand, J. Westermayr,* C. Oostenbrink*, J. Phys. Chem. Lett. 13 (17), 3812-3818 (2022)

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  • Machine learning for electronically excited states of molecules

    J. Westermayr, P. Marquetand, Chem. Rev. 121, 16, 9873-9926 (2021)

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Teaching

Module Bachelor in Chemistry

in preparation

 

Module Master Chemistry

Practical Course “Artificial Intelligence in Theoretical Chemistry”

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Team

Introducing the junior professorship group.

Group Leader

Juniorprof. Dr. Julia Westermayr

Juniorprof. Dr. Julia Westermayr

Theoretical Chemistry of Materials Design
Philipp-Rosenthal-Straße 31, Room E-047
Linnestr. 2
04103 Leipzig

PhD Students

 Ryan Barrett

Ryan Barrett

Theoretische Chemie des Materialdesign
Philipp-Rosenthal-Straße 31, Room E-044
Linnestr. 2

Leipzig 04103

Open Positions

enlarge the image: Career, Foto: Colourbox
Career, Foto: Colourbox

The group welcomes research interns, bachelor's or master's students to conduct their thesis. To discuss possible topics, please reach me via my office hours. Currently, no open positions are available for PhD or PostDocs. If you cannot find what you are looking for, please do not hesitate to contact me - there may be other ways like scholarships to work with us.

Contact & Arrival

Juniorprof. Dr. Julia Westermayr

Juniorprof. Dr. Julia Westermayr

Theoretical Chemistry of Materials Design
Philipp-Rosenthal-Straße 31, Room E-047
Linnestr. 2
04103 Leipzig