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Manuel Konrad

Showing results (1-10 of 6) with videos related to

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Journal of Chemical Theory and Computation|July 12, 2021
CONI-Net: Machine Learning of Separable Intermolecular Force FieldsManuel Konrad, Wolfgang Wenzel
Scientific Reports|February 9, 2018
Machine learning of correlated dihedral potentials for atomistic molecular force fieldsPascal Friederich, Manuel Konrad, Timo Strunk, et al.
Journal of Chemical Theory and Computation|October 8, 2021
Fast Generation of Machine Learning-Based Force Fields for Adsorption EnergiesSaientan Bag, Manuel Konrad, Tobias Schlöder, et al.
Advanced Materials (Deerfield Beach, Fla.)|April 24, 2019
Toward Design of Novel Materials for Organic ElectronicsPascal Friederich, Artem Fediai, Simon Kaiser, et al.
Journal of Chemical Theory and Computation|May 4, 2021
Analyzing Dynamical Disorder for Charge Transport in Organic Semiconductors via Machine LearningPatrick Reiser, Manuel Konrad, Artem Fediai, et al.
Nanoscale Advances|September 22, 2022
Nanocrystalline graphene at high temperatures: insight into nanoscale processesC N Shyam Kumar, Manuel Konrad, Venkata Sai Kiran Chakravadhanula, et al.
Pageof 1

Showing results (1-10 of 6) with videos related to

Sort By:
Pageof 1
Journal of Chemical Theory and Computation|July 12, 2021
CONI-Net: Machine Learning of Separable Intermolecular Force FieldsManuel Konrad, Wolfgang Wenzel
Scientific Reports|February 9, 2018
Machine learning of correlated dihedral potentials for atomistic molecular force fieldsPascal Friederich, Manuel Konrad, Timo Strunk, et al.
Journal of Chemical Theory and Computation|October 8, 2021
Fast Generation of Machine Learning-Based Force Fields for Adsorption EnergiesSaientan Bag, Manuel Konrad, Tobias Schlöder, et al.
Advanced Materials (Deerfield Beach, Fla.)|April 24, 2019
Toward Design of Novel Materials for Organic ElectronicsPascal Friederich, Artem Fediai, Simon Kaiser, et al.
Journal of Chemical Theory and Computation|May 4, 2021
Analyzing Dynamical Disorder for Charge Transport in Organic Semiconductors via Machine LearningPatrick Reiser, Manuel Konrad, Artem Fediai, et al.
Nanoscale Advances|September 22, 2022
Nanocrystalline graphene at high temperatures: insight into nanoscale processesC N Shyam Kumar, Manuel Konrad, Venkata Sai Kiran Chakravadhanula, et al.
Pageof 1