Michele Ceriotti

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Citations	18324	15050
h-index	67	58
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michele parrinelloDepartment of ChemistryVerified email at phys.chem.ethz.ch
Gabor CsanyiProfessor of Molecular Modelling, Engineering Laboratory, University of CambridgeVerified email at cam.ac.uk
David M WilkinsQueen's University BelfastVerified email at qub.ac.uk
David ManolopoulosUniversity of OxfordVerified email at chem.ox.ac.uk
Andrea GrisafiCNRS researcher, Sorbonne Université, ParisVerified email at sorbonne-universite.fr
Félix MusilCuspAIVerified email at cusp.ai
Venkat KapilLecturer (Assistant Professor), Department of Physics & Astronomy, University College LondonVerified email at ucl.ac.uk
Bingqing ChengAssistant Professor at University of California, BerkeleyVerified email at berkeley.edu
Sandip DeBASFVerified email at basf.com
Gareth TribelloSchool of Maths and Physics, Queen's University BelfastVerified email at qub.ac.uk
Mariana RossiHead of Independent Lise Meitner Group, MPI for Structure and Dynamics of Matter, HamburgVerified email at mpsd.mpg.de
E A EngelEcole Polytechnique Fédérale de LausanneVerified email at epfl.ch
Albert P. BartokUniversity of WarwickVerified email at warwick.ac.uk
Thomas MarklandAssociate Professor of Chemistry, Stanford UniversityVerified email at stanford.edu
Sergey N. PozdnyakovÉcole polytechnique fédérale de LausanneVerified email at epfl.ch
Jörg BehlerRuhr-Universität BochumVerified email at ruhr-uni-bochum.de
Marco BernasconiUniversity of Milano-BicoccaVerified email at unimib.it
Giulio ImbalzanoEPFLVerified email at epfl.ch
Piero GasparottoMicrosoftVerified email at microsoft.com
Guillaume FrauxPost-doctoral researcher at EPFL, Institute of MaterialsVerified email at epfl.ch

Michele Ceriotti

Associate Professor at EPFL, Institute of Materials

Verified email at epfl.ch - Homepage

Atomic-scale modeling Machine learning Materials science Statistical mechanics Physical chemistry


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Gaussian process regression for materials and molecules VL Deringer, AP Bartók, N Bernstein, DM Wilkins, M Ceriotti, G Csányi Chemical Reviews 121 (16), 10073-10141, 2021	781	2021
Promoting transparency and reproducibility in enhanced molecular simulations Nature methods 16 (8), 670-673, 2019	772	2019
Comparing molecules and solids across structural and alchemical space S De, AP Bartók, G Csányi, M Ceriotti Phys. Chem. Chem. Phys. 18, 13754, 2016	753	2016
Machine Learning Unifies the Modelling of Materials and Molecules AP Bartok, S De, C Poelking, N Bernstein, J Kermode, G Csanyi, ... Science Advances 3 (12), e1701816, 2017	717	2017
Nuclear Quantum Effects in Water and Aqueous Systems: Experiment, Theory, and Current Challenges M Ceriotti, W Fang, PG Kusalik, RH McKenzie, A Michaelides, ... Chemical Reviews 116, 7529, 2016	630	2016
Physics-inspired structural representations for molecules and materials F Musil, A Grisafi, AP Bartók, C Ortner, G Csányi, M Ceriotti Chemical Reviews 121 (16), 9759-9815, 2021	447	2021
Nuclear quantum effects enter the mainstream TE Markland, M Ceriotti Nature Reviews Chemistry 2 (3), 0109, 2018	409	2018
Efficient stochastic thermostatting of path integral molecular dynamics M Ceriotti, M Parrinello, TE Markland, DE Manolopoulos The Journal of chemical physics 133, 124104, 2010	402	2010
Automatic Selection of Atomic Fingerprints and Reference Configurations for Machine-Learning Potentials G Imbalzano, A Anelli, S Klees, M Ceriotti The Journal of Chemical Physics 148, 241730, 2018	339	2018
Simplifying the representation of complex free-energy landscapes using sketch-map M Ceriotti, GA Tribello, M Parrinello Proceedings of the National Academy of Sciences 108 (32), 13023-13028, 2011	338	2011
i-PI 2.0: A universal force engine for advanced molecular simulations V Kapil, M Rossi, O Marsalek, R Petraglia, Y Litman, T Spura, B Cheng, ... Computer Physics Communications 236, 214-223, 2019	336	2019
Colored-noise thermostats à la carte M Ceriotti, G Bussi, M Parrinello Journal of Chemical Theory and Computation 6 (4), 1170-1180, 2010	325	2010
Ab initio thermodynamics of liquid and solid water B Cheng, EA Engel, J Behler, C Dellago, M Ceriotti Proceedings of the National Academy of Sciences 116 (4), 1110-1115, 2019	310	2019
i-PI: A Python interface for ab initio path integral molecular dynamics simulations M Ceriotti, J More, DE Manolopoulos Computer Physics Communications 185 (3), 1019-1026, 2014	310	2014
Symmetry-Adapted Machine-Learning for Tensorial Properties of Atomistic Systems A Grisafi, DM Wilkins, G Csányi, M Ceriotti Physical Review Letters 120, 036002, 2018	296	2018
Nuclear quantum effects in solids using a colored-noise thermostat M Ceriotti, G Bussi, M Parrinello Physical review letters 103 (3), 030603, 2009	289	2009
Origins of structural and electronic transitions in disordered silicon VL Deringer, N Bernstein, G Csányi, C Ben Mahmoud, M Ceriotti, ... Nature 589 (7840), 59-64, 2021	286	2021
Nuclear quantum effects and hydrogen bond fluctuations in water M Ceriotti, J Cuny, M Parrinello, DE Manolopoulos Proceedings of the National Academy of Sciences 110 (39), 15591-15596, 2013	276	2013
Barely porous organic cages for hydrogen isotope separation M Liu, L Zhang, MA Little, V Kapil, M Ceriotti, S Yang, L Ding, DL Holden, ... Science 366 (6465), 613-620, 2019	273	2019
How to remove the spurious resonances from ring polymer molecular dynamics M Rossi, M Ceriotti, DE Manolopoulos The Journal of Chemical Physics 140, 234116, 2014	269	2014

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