Follow
Pavlo O. Dral
Title
Cited by
Cited by
Year
Quantum chemistry structures and properties of 134 kilo molecules
R Ramakrishnan, PO Dral, M Rupp, OA Von Lilienfeld
Scientific data 1, 140022, 2014
18102014
Big Data Meets Quantum Chemistry Approximations: The Δ-Machine Learning Approach
R Ramakrishnan, PO Dral, M Rupp, OA von Lilienfeld
Journal of Chemical Theory and Computation 11 (5), 2087-2096, 2015
7882015
Quantum Chemistry in the Age of Machine Learning
PO Dral
The Journal of Physical Chemistry Letters 11 (6), 2336-2347, 2020
3592020
Semiempirical quantum-chemical orthogonalization-corrected methods: theory, implementation, and parameters
PO Dral, X Wu, L Spörkel, A Koslowski, W Weber, R Steiger, M Scholten, ...
Journal of chemical theory and computation 12 (3), 1082-1096, 2016
1512016
Deep Learning for Nonadiabatic Excited-State Dynamics
WK Chen, XY Liu, WH Fang, PO Dral, G Cui
The journal of physical chemistry letters 9 (23), 6702-6708, 2018
1462018
Molecular excited states through a machine learning lens
PO Dral, M Barbatti
Nature Reviews Chemistry 5 (6), 388-405, 2021
1432021
Nonadiabatic Excited-State Dynamics with Machine Learning
PO Dral, M Barbatti, W Thiel
The journal of physical chemistry letters 9 (19), 5660-5663, 2018
1412018
Structure-based sampling and self-correcting machine learning for accurate calculations of potential energy surfaces and vibrational levels
PO Dral, A Owens, SN Yurchenko, W Thiel
The Journal of Chemical Physics 146 (24), 244108, 2017
1382017
The relationship between threshold voltage and dipolar character of self-assembled monolayers in organic thin-film transistors
M Salinas, CM Jäger, AY Amin, PO Dral, T Meyer-Friedrichsen, A Hirsch, ...
Journal of the American Chemical Society 134 (30), 12648-12652, 2012
1172012
Machine Learning of Parameters for Accurate Semiempirical Quantum Chemical Calculations
PO Dral, OA von Lilienfeld, W Thiel
Journal of Chemical Theory and Computation 11 (5), 2120-2125, 2015
1162015
Choosing the right molecular machine learning potential
M Pinheiro Jr, F Ge, N Ferré, PO Dral, M Barbatti
Chemical Science, 2021
1112021
Semiempirical quantum-chemical orthogonalization-corrected methods: benchmarks for ground-state properties
PO Dral, X Wu, L Spörkel, A Koslowski, W Thiel
Journal of chemical theory and computation 12 (3), 1097-1120, 2016
1022016
Hierarchical machine learning of potential energy surfaces
PO Dral, A Owens, A Dral, G Csányi
The Journal of Chemical Physics 152 (20), 204110, 2020
762020
Artificial intelligence-enhanced quantum chemical method with broad applicability
P Zheng, R Zubatyuk, W Wu, O Isayev, PO Dral
Nature communications 12 (1), 7022, 2021
672021
MLatom: A program package for quantum chemical research assisted by machine learning
PO Dral
Journal of Computational Chemistry 40 (26), 2339-2347, 2019
642019
Semiempirical quantum-chemical methods with Orthogonalization and dispersion corrections
PO Dral, X Wu, W Thiel
Journal of chemical theory and computation 15 (3), 1743-1760, 2019
622019
Oxygen-Doped Nanodiamonds: Synthesis and Functionalizations†
AA Fokin, TS Zhuk, AE Pashenko, PO Dral, PA Gunchenko, JEP Dahl, ...
Organic letters 11 (14), 3068-3071, 2009
612009
Machine Learning for Absorption Cross Sections
BX Xue, M Barbatti, PO Dral
The Journal of Physical Chemistry A 124 (35), 7199-7210, 2020
562020
MLatom 2: An Integrative Platform for Atomistic Machine Learning
PO Dral, F Ge, BX Xue, YF Hou, M Pinheiro, J Huang, M Barbatti
Topics in Current Chemistry 379 (4), 1-41, 2021
552021
Doped Polycyclic Aromatic Hydrocarbons as Building Blocks for Nanoelectronics: A Theoretical Study
PO Dral, M Kivala, T Clark
The Journal of organic chemistry, 2012
472012
The system can't perform the operation now. Try again later.
Articles 1–20