Alexandre Tkatchenko

Cited by

	All	Since 2018
Citations	34773	25248
h-index	79	69
i10-index	175	164

6000

3000

1500

4500

20102011201220132014201520162017201820192020202120222023143 218 550 848 1376 1571 2109 2382 3198 3653 4748 5076 5859 2703

Public access

View all

151 articles

0 articles

available

not available

Based on funding mandates

Co-authors

Klaus-Robert MüllerTU Berlin & Korea University & Google Brain & Max Planck Institute for Informatics, GermanyVerified email at tu-berlin.de
Matthias SchefflerDirector of NOMAD Laboratory at FHI of Max-Planck-Gesellschaft and IRIS-Adlershof of HU BerlinVerified email at fhi-berlin.mpg.de
O. Anatole von LilienfeldClark & CIFAR AI chair at University of Toronto/Vector Institute/Technical University BerlinVerified email at utoronto.ca
Robert A. DiStasio Jr.Associate Professor, Chemistry and Chemical Biology, Cornell UniversityVerified email at cornell.edu
Wei LiuChangchun Institute of Applied Chemistry, Chinese Academy of SciencesVerified email at ciac.ac.cn
Stefan ChmielaTechnische Universität BerlinVerified email at chmiela.com
Kristof T. SchüttPfizerVerified email at pfizer.com
Huziel E. SaucedaAssistant Professor, Instituto de Física, Universidad Nacional Autonoma de MexicoVerified email at fisica.unam.mx
Igor PoltavskyPostDocVerified email at uni.lu
alberto ambrosettiUniversità degli Studi di PadovaVerified email at pd.infn.it
Matthias RuppLuxembourg Institute of Science and Technology (LIST)Verified email at list.lu
Jan HermannMicrosoft Research AI4ScienceVerified email at microsoft.com
Leeor KronikWeizmann Institute of ScienceVerified email at weizmann.ac.il
Angelos MichaelidesUniversity of CambridgeVerified email at cam.ac.uk
Noa MaromAssociate Professor, Materials Science and Engineering, Carnegie Mellon UniversityVerified email at andrew.cmu.edu
Dario AlfeProfessor of Physics at University College London and Universita' di Napoli Federico IIVerified email at ucl.ac.uk
Reinhard J. MaurerProfessor, Department of Chemistry & Department of Physics, University of WarwickVerified email at warwick.ac.uk
Johannes HojaUniversity of GrazVerified email at uni-graz.at
Xinguo RenInstitute of Physics, Chinese Academy of SciencesVerified email at ustc.edu.cn
Karsten ReuterDirector at Fritz-Haber-Institut der MPGVerified email at fhi-berlin.mpg.de

Alexandre Tkatchenko

Professor of Physics, University of Luxembourg; Visiting Professor, TU Berlin

Verified email at uni.lu - Homepage

Intermolecular Interactions AI for Science Chemical Physics Materials Physics


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Accurate molecular van der Waals interactions from ground-state electron density and free-atom reference data A Tkatchenko, M Scheffler Physical Review Letters 102 (7), 073005, 2009	5434	2009
Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning M Rupp, A Tkatchenko, KR Müller, OA von Lilienfeld Physical Review Letters 108, 058301, 2012	1911	2012
Accurate and efficient method for many-body van der Waals interactions A Tkatchenko, RA DiStasio Jr, R Car, M Scheffler Physical Review Letters 108 (23), 236402, 2012	1344	2012
Quantum-chemical insights from deep tensor neural networks KT Schütt, F Arbabzadah, S Chmiela, KR Müller, A Tkatchenko Nature communications 8 (1), 13890, 2017	1209	2017
Schnet–a deep learning architecture for molecules and materials KT Schütt, HE Sauceda, PJ Kindermans, A Tkatchenko, KR Müller The Journal of Chemical Physics 148 (24), 241722, 2018	1202	2018
Reproducibility in density functional theory calculations of solids K Lejaeghere, G Bihlmayer, T Björkman, P Blaha, S Blügel, V Blum, ... Science 351 (6280), aad3000, 2016	1178*	2016
Machine learning of accurate energy-conserving molecular force fields S Chmiela, A Tkatchenko, HE Sauceda, I Poltavsky, KT Schütt, KR Müller Science advances 3 (5), e1603015, 2017	885	2017
Schnet: A continuous-filter convolutional neural network for modeling quantum interactions K Schütt, PJ Kindermans, HE Sauceda Felix, S Chmiela, A Tkatchenko, ... Advances in neural information processing systems 30, 2017	767	2017
Machine learning predictions of molecular properties: Accurate many-body potentials and nonlocality in chemical space K Hansen, F Biegler, R Ramakrishnan, W Pronobis, OA Von Lilienfeld, ... The journal of physical chemistry letters 6 (12), 2326-2331, 2015	688	2015
Machine learning of molecular electronic properties in chemical compound space G Montavon, M Rupp, V Gobre, A Vazquez-Mayagoitia, K Hansen, ... New Journal of Physics 15 (9), 095003, 2013	643	2013
Resolution-of-identity approach to Hartree–Fock, hybrid density functionals, RPA, MP2 and GW with numeric atom-centered orbital basis functions X Ren, P Rinke, V Blum, J Wieferink, A Tkatchenko, A Sanfilippo, K Reuter, ... New Journal of Physics 14 (5), 053020, 2012	634	2012
Assessment and validation of machine learning methods for predicting molecular atomization energies K Hansen, G Montavon, F Biegler, S Fazli, M Rupp, M Scheffler, ... Journal of Chemical Theory and Computation 9 (8), 3404-3419, 2013	619	2013
Density-functional theory with screened van der Waals interactions for the modeling of hybrid inorganic-organic systems VG Ruiz, W Liu, E Zojer, M Scheffler, A Tkatchenko Physical Review Letters 108 (14), 146103, 2012	603	2012
Long-range correlation energy calculated from coupled atomic response functions A Ambrosetti, AM Reilly, RA DiStasio, A Tkatchenko The Journal of chemical physics 140 (18), 2014	547	2014
Report on the sixth blind test of organic crystal structure prediction methods AM Reilly, RI Cooper, CS Adjiman, S Bhattacharya, AD Boese, ... Acta Crystallographica Section B: Structural Science, Crystal Engineering …, 2016	510	2016
DFTB+, a software package for efficient approximate density functional theory based atomistic simulations B Hourahine, B Aradi, V Blum, F Bonafé, A Buccheri, C Camacho, ... The Journal of chemical physics 152 (12), 124101, 2020	508	2020
Towards exact molecular dynamics simulations with machine-learned force fields S Chmiela, HE Sauceda, KR Müller, A Tkatchenko Nature communications 9 (1), 3887, 2018	508	2018
First-principles models for van der Waals interactions in molecules and materials: Concepts, theory, and applications J Hermann, RA DiStasio Jr, A Tkatchenko Chemical Reviews 117 (6), 4714-4758, 2017	457	2017
Machine learning for molecular simulation F Noé, A Tkatchenko, KR Müller, C Clementi Annual review of physical chemistry 71, 361-390, 2020	447	2020
Machine learning force fields OT Unke, S Chmiela, HE Sauceda, M Gastegger, I Poltavsky, KT Schütt, ... Chemical Reviews 121 (16), 10142-10186, 2021	433	2021

The system can't perform the operation now. Try again later.

Articles 1–20

Citations per year

Duplicate citations

Merged citations

Add co-authorsCo-authors

Follow

Cited by

Co-authors