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Johannes Margraf
PeerJ Editor & Reviewer
630 Points

Contributions by role

Reviewer 30
Editor 600

Contributions by subject area

Theoretical and Computational Chemistry
Biophysical Chemistry
Nanomaterials and Nanochemistry
Physical Chemistry (other)
Catalysis
Kinetics and Reactions

Johannes T Margraf

PeerJ Editor & Reviewer

Summary

Johannes Margraf is a professor of theory and machine learning in physical chemistry at the University of Bayreuth. His group focuses on using and developing machine-learning and electronic structure methods to study chemical reactions and discover new functional materials. He obtained his PhD at the University of Erlangen, working with Timothy Clark and Dirk Guldi on the theoretical and experimental characterization of quantum dot solar cells. Subsequently he joined the group of Rodney Bartlett at the University of Florida working on method development in coupled cluster theory and single particle methods, and worked as a group leader at TU Munich and the Fritz Haber Institute in Berlin, in the theory department lead by Karsten Reuter.

Catalysis Data Mining & Machine Learning Theoretical & Computational Chemistry

Editorial Board Member

PeerJ Physical Chemistry

Past or current institution affiliations

Technische Universität München

Work details

Group Leader

Technische Universität München
February 2021
Theory

Websites

  • Google Scholar

PeerJ Contributions

  • Edited 6

Academic Editor on

January 6, 2025
Beyond predefined ligand libraries: a genetic algorithm approach for de novo discovery of catalysts for the Suzuki coupling reactions
Julius Seumer, Jan H. Jensen
https://doi.org/10.7717/peerj-pchem.34
April 5, 2023
In-silico assay of a dosing vehicle based on chitosan-TiO2 and modified benzofuran-isatin molecules against Pseudomonas aeruginosa
Verónica Castro-Velázquez, Erik Díaz-Cervantes, Vicente Rodríguez-González, Carlos J. Cortés-García
https://doi.org/10.7717/peerj-pchem.27
May 17, 2021
Using a genetic algorithm to find molecules with good docking scores
Casper Steinmann, Jan H. Jensen
https://doi.org/10.7717/peerj-pchem.18
September 18, 2020
The SIR dynamic model of infectious disease transmission and its analogy with chemical kinetics
Cory M. Simon
https://doi.org/10.7717/peerj-pchem.14
July 31, 2020
Chemical space exploration: how genetic algorithms find the needle in the haystack
Emilie S. Henault, Maria H. Rasmussen, Jan H. Jensen
https://doi.org/10.7717/peerj-pchem.11
October 15, 2019
Effects of number of parallel runs and frequency of bias-strength replacement in generalized ensemble molecular dynamics simulations
Takuya Shimato, Kota Kasahara, Junichi Higo, Takuya Takahashi
https://doi.org/10.7717/peerj-pchem.4