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Digital Discovery
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April 9, 2026
Learning potential energy surfaces of hydrogen atom transfer reactions in peptides
Marlen Neubert, Patrick Reiser, Frauke Gräter, et al.
Scientific Reports
|
February 9, 2018
Machine learning of correlated dihedral potentials for atomistic molecular force fields
Pascal Friederich, Manuel Konrad, Timo Strunk, et al.
Scientific Reports
|
August 29, 2019
Concentration dependent energy levels shifts in donor-acceptor mixtures due to intermolecular electrostatic interaction
Saientan Bag, Pascal Friederich, Ivan Kondov, et al.
Scientific Data
|
November 22, 2023
3DSC - a dataset of superconductors including crystal structures
Timo Sommer, Roland Willa, Jörg Schmalian, et al.
Nature Communications
|
October 9, 2019
Disorder compensation controls doping efficiency in organic semiconductors
Artem Fediai, Franz Symalla, Pascal Friederich, et al.
Nature Materials
|
May 28, 2021
Machine-learned potentials for next-generation matter simulations
Pascal Friederich, Florian Häse, Jonny Proppe, et al.
ACS Applied Materials & Interfaces
|
December 26, 2017
Built-In Potentials Induced by Molecular Order in Amorphous Organic Thin Films
Pascal Friederich, Vadim Rodin, Florian von Wrochem, et al.
Chemical Science
|
February 16, 2024
Artificial design of organic emitters <i>via</i> a genetic algorithm enhanced by a deep neural network
AkshatKumar Nigam, Robert Pollice, Pascal Friederich, et al.
Journal of Chemical Theory and Computation
|
November 21, 2015
Ab Initio Treatment of Disorder Effects in Amorphous Organic Materials: Toward Parameter Free Materials Simulation
Pascal Friederich, Franz Symalla, Velimir Meded, et al.
Journal of Chemical Information and Modeling
|
October 1, 2025
The Black Hole Strategy: Gravity-Based Representative Sampling for Frugal Graph Learning on Metal-Organic Framework Networks
Mehrdad Jalali, A D Dinga Wonanke, Pascal Friederich, et al.
Page
of 6
Search research articles
Search
Showing results (1-10 of 52) with videos related to
Sort By:
Page
of 6
Digital Discovery
|
April 9, 2026
Learning potential energy surfaces of hydrogen atom transfer reactions in peptides
Marlen Neubert, Patrick Reiser, Frauke Gräter, et al.
Scientific Reports
|
February 9, 2018
Machine learning of correlated dihedral potentials for atomistic molecular force fields
Pascal Friederich, Manuel Konrad, Timo Strunk, et al.
Scientific Reports
|
August 29, 2019
Concentration dependent energy levels shifts in donor-acceptor mixtures due to intermolecular electrostatic interaction
Saientan Bag, Pascal Friederich, Ivan Kondov, et al.
Scientific Data
|
November 22, 2023
3DSC - a dataset of superconductors including crystal structures
Timo Sommer, Roland Willa, Jörg Schmalian, et al.
Nature Communications
|
October 9, 2019
Disorder compensation controls doping efficiency in organic semiconductors
Artem Fediai, Franz Symalla, Pascal Friederich, et al.
Nature Materials
|
May 28, 2021
Machine-learned potentials for next-generation matter simulations
Pascal Friederich, Florian Häse, Jonny Proppe, et al.
ACS Applied Materials & Interfaces
|
December 26, 2017
Built-In Potentials Induced by Molecular Order in Amorphous Organic Thin Films
Pascal Friederich, Vadim Rodin, Florian von Wrochem, et al.
Chemical Science
|
February 16, 2024
Artificial design of organic emitters <i>via</i> a genetic algorithm enhanced by a deep neural network
AkshatKumar Nigam, Robert Pollice, Pascal Friederich, et al.
Journal of Chemical Theory and Computation
|
November 21, 2015
Ab Initio Treatment of Disorder Effects in Amorphous Organic Materials: Toward Parameter Free Materials Simulation
Pascal Friederich, Franz Symalla, Velimir Meded, et al.
Journal of Chemical Information and Modeling
|
October 1, 2025
The Black Hole Strategy: Gravity-Based Representative Sampling for Frugal Graph Learning on Metal-Organic Framework Networks
Mehrdad Jalali, A D Dinga Wonanke, Pascal Friederich, et al.
Page
of 6