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Journal of Chemical Theory and Computation
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October 8, 2021
Fast Generation of Machine Learning-Based Force Fields for Adsorption Energies
Saientan Bag, Manuel Konrad, Tobias Schlöder, et al.
Journal of Chemical Theory and Computation
|
November 19, 2015
QM/QM approach to model energy disorder in amorphous organic semiconductors
Pascal Friederich, Velimir Meded, Franz Symalla, et al.
Nature Communications
|
September 12, 2020
Designing and understanding light-harvesting devices with machine learning
Florian Häse, Loïc M Roch, Pascal Friederich, et al.
Journal of Chemical Information and Modeling
|
February 16, 2022
Updated Calibrated Model for the Prediction of Molecular Frontier Orbital Energies and Its Application to Boron Subphthalocyanines
Devon P Holst, Pascal Friederich, Alán Aspuru-Guzik, et al.
Angewandte Chemie (International Ed. in English)
|
May 19, 2025
Mitigating Molecular Aggregation in Drug Discovery With Predictive Insights From Explainable AI
Hunter Sturm, Jonas Teufel, Kaitlin A Isfeld, et al.
Digital Discovery
|
January 24, 2025
Predicting hydrogen atom transfer energy barriers using Gaussian process regression
Evgeni Ulanov, Ghulam A Qadir, Kai Riedmiller, et al.
Scientific Data
|
September 5, 2023
Accurate GW frontier orbital energies of 134 kilo molecules
Artem Fediai, Patrick Reiser, Jorge Enrique Olivares Peña, et al.
Advanced Materials (Deerfield Beach, Fla.)
|
April 24, 2019
Toward Design of Novel Materials for Organic Electronics
Pascal Friederich, Artem Fediai, Simon Kaiser, et al.
Chemphyschem : a European Journal of Chemical Physics and Physical Chemistry
|
August 21, 2018
Meltdown! Local Heating by Decaying Excited Host Positive Polarons Triggers Aggregation Quenching in Blue PhOLEDs
Tobias Setzer, Pascal Friederich, Velimir Meded, et al.
Journal of Chemical Theory and Computation
|
May 4, 2021
Analyzing Dynamical Disorder for Charge Transport in Organic Semiconductors via Machine Learning
Patrick Reiser, Manuel Konrad, Artem Fediai, et al.
Page
of 6
Search research articles
Search
Showing results (11-20 of 52) with videos related to
Sort By:
Page
of 6
Journal of Chemical Theory and Computation
|
October 8, 2021
Fast Generation of Machine Learning-Based Force Fields for Adsorption Energies
Saientan Bag, Manuel Konrad, Tobias Schlöder, et al.
Journal of Chemical Theory and Computation
|
November 19, 2015
QM/QM approach to model energy disorder in amorphous organic semiconductors
Pascal Friederich, Velimir Meded, Franz Symalla, et al.
Nature Communications
|
September 12, 2020
Designing and understanding light-harvesting devices with machine learning
Florian Häse, Loïc M Roch, Pascal Friederich, et al.
Journal of Chemical Information and Modeling
|
February 16, 2022
Updated Calibrated Model for the Prediction of Molecular Frontier Orbital Energies and Its Application to Boron Subphthalocyanines
Devon P Holst, Pascal Friederich, Alán Aspuru-Guzik, et al.
Angewandte Chemie (International Ed. in English)
|
May 19, 2025
Mitigating Molecular Aggregation in Drug Discovery With Predictive Insights From Explainable AI
Hunter Sturm, Jonas Teufel, Kaitlin A Isfeld, et al.
Digital Discovery
|
January 24, 2025
Predicting hydrogen atom transfer energy barriers using Gaussian process regression
Evgeni Ulanov, Ghulam A Qadir, Kai Riedmiller, et al.
Scientific Data
|
September 5, 2023
Accurate GW frontier orbital energies of 134 kilo molecules
Artem Fediai, Patrick Reiser, Jorge Enrique Olivares Peña, et al.
Advanced Materials (Deerfield Beach, Fla.)
|
April 24, 2019
Toward Design of Novel Materials for Organic Electronics
Pascal Friederich, Artem Fediai, Simon Kaiser, et al.
Chemphyschem : a European Journal of Chemical Physics and Physical Chemistry
|
August 21, 2018
Meltdown! Local Heating by Decaying Excited Host Positive Polarons Triggers Aggregation Quenching in Blue PhOLEDs
Tobias Setzer, Pascal Friederich, Velimir Meded, et al.
Journal of Chemical Theory and Computation
|
May 4, 2021
Analyzing Dynamical Disorder for Charge Transport in Organic Semiconductors via Machine Learning
Patrick Reiser, Manuel Konrad, Artem Fediai, et al.
Page
of 6