Julia Westermayr

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Assistant Professor

Leipzig University

Germany

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Recent Grants

Grant: Close

Deep-learning enhanced photoplasmonic catalysis of CO2

Open Date: 2021-01-01

Close Date: 2022-09-01

Grant: Close

Machine learning predictions of excited state properties of tyrosine using SchNet

Open Date: 2019-05-01

Close Date: 2019-05-01

Grant: Close

Photodamage of Proteins by Dityrosine Crosslinking: A Quantum Study of Tyrosine and its Dipeptide

Open Date: 2017-10-01

Close Date: 2020-09-01

Articles (10)

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2023

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2023

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2022

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2022

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2022

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2022

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2022

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2021

Year:

2021

Year:

2021

Collaborators (12)

Michael Jakupec

Universität Wien

AUSTRIA

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Reinhard Maurer

Professor of Computational Chemistry

University of Warwick

UNITED KINGDOM

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Oliver T. Hofmann

Graz University of Technology

AUSTRIA

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Philipp Marquetand

Universität Wien

AUSTRIA

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Wolfgang Kandioller

Universität Wien

AUSTRIA

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Chris Oostenbrink

AUSTRIA

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Scott Habershon

Professor

University of Warwick

UNITED KINGDOM

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Gunda Koellensperger

Professor

AUSTRIA

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Dominik Wenisch

Universität Wien

AUSTRIA

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Florian Jörg

Universität Wien

AUSTRIA

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Ralf Tonner-Zech

Professor for Theoretical Chemistry of complex systems

Leipzig University

GERMANY

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Michael Gastegger

GERMANY

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Julia Westermayr

Research Interests

Explore related searches

Contact this professor

Recent Grants

Articles (10)

Machine learning for accelerated bandgap prediction in strain-engineered quaternary III–V semiconductors

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

Arene Variation of Highly Cytotoxic Tridentate Naphthoquinone-Based Ruthenium(II) Complexes and In-Depth In Vitro Studies

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

NQCDynamics.jl: A Julia package for nonadiabatic quantum classical molecular dynamics in the condensed phase

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

Long-range dispersion-inclusive machine learning potentials for structure search and optimization of hybrid organic–inorganic interfaces

Machine Learning for Electronically Excited States of Molecules

Tridentate 3-Substituted Naphthoquinone Ruthenium Arene Complexes: Synthesis, Characterization, Aqueous Behavior, and Theoretical and Biological Studies

Perspective on integrating machine learning into computational chemistry and materials science

Collaborators (12)

Michael Jakupec

Reinhard Maurer

Oliver T. Hofmann

Philipp Marquetand

Wolfgang Kandioller

Chris Oostenbrink

Scott Habershon

Gunda Koellensperger

Dominik Wenisch

Florian Jörg

Ralf Tonner-Zech

Michael Gastegger

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