Decoding, Mapping and Designing the Structural Complexity of Hydrogen-Bond Networks: from Water to Proteins to Polymers

Publications

Peer reviewed articles (30)

Machine learning unifies the modeling of materials and molecules

Author(s): Albert P. Bartók, Sandip De, Carl Poelking, Noam Bernstein, James R. Kermode, Gábor Csányi, Michele Ceriotti
Published in: Science Advances, Issue 3/12, 2017, Page(s) e1701816, ISSN 2375-2548
DOI: 10.1126/sciadv.1701816

Machine Learning for the Structure-Energy-Property Landscapes of Molecular Crystals

Author(s): Felix Musil, Sandip De, Jack Yang, Josh E. Campbell, Graeme Matthew Day, Michele Ceriotti
Published in: Chemical Science, Issue 9, 2017, Page(s) 1289, ISSN 2041-6520
DOI: 10.1039/C7SC04665K

Recognizing Local and Global Structural Motifs at the Atomic Scale

Author(s): Piero Gasparotto, Robert Horst Meißner, Michele Ceriotti
Published in: Journal of Chemical Theory and Computation, 2018, ISSN 1549-9618
DOI: 10.1021/acs.jctc.7b00993

Comparison of permutationally invariant polynomials, neural networks, and Gaussian approximation potentials in representing water interactions through many-body expansions

Author(s): Thuong T. Nguyen, Eszter Székely, Giulio Imbalzano, Jörg Behler, Gábor Csányi, Michele Ceriotti, Andreas W. Götz, Francesco Paesani
Published in: The Journal of Chemical Physics, Issue 148/24, 2018, Page(s) 241725, ISSN 0021-9606
DOI: 10.1063/1.5024577

Generalized convex hull construction for materials discovery

Author(s): Andrea Anelli, Edgar A. Engel, Chris J. Pickard, Michele Ceriotti
Published in: Physical Review Materials, Issue 2/10, 2018, ISSN 2475-9953
DOI: 10.1103/PhysRevMaterials.2.103804

Mapping uncharted territory in ice from zeolite networks to ice structures

Author(s): Edgar A. Engel, Andrea Anelli, Michele Ceriotti, Chris J. Pickard, Richard J. Needs
Published in: Nature Communications, Issue 9/1, 2018, ISSN 2041-1723
DOI: 10.1038/s41467-018-04618-6

Decisive role of nuclear quantum effects on surface mediated water dissociation at finite temperature

Author(s): Yair Litman, Davide Donadio, Michele Ceriotti, Mariana Rossi
Published in: The Journal of Chemical Physics, Issue 148/10, 2018, Page(s) 102320, ISSN 0021-9606
DOI: 10.1063/1.5002537

Fast-forward Langevin dynamics with momentum flips

Author(s): Mahdi Hijazi, David M. Wilkins, Michele Ceriotti
Published in: The Journal of Chemical Physics, Issue 148/18, 2018, Page(s) 184109, ISSN 0021-9606
DOI: 10.1063/1.5029833

Symmetry-Adapted Machine Learning for Tensorial Properties of Atomistic Systems

Author(s): Andrea Grisafi, David M. Wilkins, Gábor Csányi, Michele Ceriotti
Published in: Physical Review Letters, Issue 120/3, 2018, ISSN 0031-9007
DOI: 10.1103/PhysRevLett.120.036002

Automatic selection of atomic fingerprints and reference configurations for machine-learning potentials

Author(s): Giulio Imbalzano, Andrea Anelli, Daniele Giofré, Sinja Klees, Jörg Behler, Michele Ceriotti
Published in: The Journal of Chemical Physics, Issue 148/24, 2018, Page(s) 241730, ISSN 0021-9606
DOI: 10.1063/1.5024611

Nuclear quantum effects enter the mainstream

Author(s): Thomas E. Markland, Michele Ceriotti
Published in: Nature Reviews Chemistry, Issue 2/3, 2018, Page(s) 0109, ISSN 2397-3358
DOI: 10.1038/s41570-017-0109

Chemical shifts in molecular solids by machine learning

Author(s): Federico M. Paruzzo, Albert Hofstetter, Félix Musil, Sandip De, Michele Ceriotti, Lyndon Emsley
Published in: Nature Communications, Issue 9/1, 2018, ISSN 2041-1723
DOI: 10.1038/s41467-018-06972-x

Theoretical prediction of the homogeneous ice nucleation rate: disentangling thermodynamics and kinetics

Author(s): Bingqing Cheng, Christoph Dellago, Michele Ceriotti
Published in: Physical Chemistry Chemical Physics, Issue 20/45, 2018, Page(s) 28732-28740, ISSN 1463-9076
DOI: 10.1039/C8CP04561E

Feature optimization for atomistic machine learning yields a data-driven construction of the periodic table of the elements

Author(s): Michael J. Willatt, Félix Musil, Michele Ceriotti
Published in: Physical Chemistry Chemical Physics, Issue 20/47, 2018, Page(s) 29661-29668, ISSN 1463-9076
DOI: 10.1039/C8CP05921G

Transferable Machine-Learning Model of the Electron Density

Author(s): Andrea Grisafi, Alberto Fabrizio, Benjamin Meyer, David M. Wilkins, Clemence Corminboeuf, Michele Ceriotti
Published in: ACS Central Science, Issue 5/1, 2019, Page(s) 57-64, ISSN 2374-7943
DOI: 10.1021/acscentsci.8b00551

Accurate molecular polarizabilities with coupled cluster theory and machine learning

Author(s): David M. Wilkins, Andrea Grisafi, Yang Yang, Ka Un Lao, Robert A. DiStasio, Michele Ceriotti
Published in: Proceedings of the National Academy of Sciences, Issue 116/9, 2019, Page(s) 3401-3406, ISSN 0027-8424
DOI: 10.1073/pnas.1816132116

Unsupervised machine learning in atomistic simulations, between predictions and understanding

Author(s): Michele Ceriotti
Published in: The Journal of Chemical Physics, Issue 150/15, 2019, Page(s) 150901, ISSN 0021-9606
DOI: 10.1063/1.5091842

i-PI 2.0: A universal force engine for advanced molecular simulations

Author(s): Venkat Kapil, Mariana Rossi, Ondrej Marsalek, Riccardo Petraglia, Yair Litman, Thomas Spura, Bingqing Cheng, Alice Cuzzocrea, Robert H. Meißner, David M. Wilkins, Benjamin A. Helfrecht, Przemysław Juda, Sébastien P. Bienvenue, Wei Fang, Jan Kessler, Igor Poltavsky, Steven Vandenbrande, Jelle Wieme, Clemence Corminboeuf, Thomas D. Kühne, David E. Manolopoulos, Thomas E. Markland, Jeremy O. Rich
Published in: Computer Physics Communications, Issue 236, 2019, Page(s) 214-223, ISSN 0010-4655
DOI: 10.1016/j.cpc.2018.09.020

Fast and Accurate Uncertainty Estimation in Chemical Machine Learning

Author(s): Félix Musil, Michael J. Willatt, Mikhail A. Langovoy, Michele Ceriotti
Published in: Journal of Chemical Theory and Computation, Issue 15/2, 2018, Page(s) 906-915, ISSN 1549-9618
DOI: 10.1021/acs.jctc.8b00959

Ab initio thermodynamics of liquid and solid water

Author(s): Bingqing Cheng, Edgar A. Engel, Jörg Behler, Christoph Dellago, Michele Ceriotti
Published in: Proceedings of the National Academy of Sciences, Issue 116/4, 2019, Page(s) 1110-1115, ISSN 0027-8424
DOI: 10.1073/pnas.1815117116

Atom-density representations for machine learning

Author(s): Michael J. Willatt, Félix Musil, Michele Ceriotti
Published in: The Journal of Chemical Physics, Issue 150/15, 2019, Page(s) 154110, ISSN 0021-9606
DOI: 10.1063/1.5090481

A new kind of atlas of zeolite building blocks

Author(s): Benjamin A. Helfrecht, Rocio Semino, Giovanni Pireddu, Scott M. Auerbach, Michele Ceriotti
Published in: The Journal of Chemical Physics, Issue 151/15, 2019, Page(s) 154112, ISSN 0021-9606
DOI: 10.1063/1.5119751

Assessment of Approximate Methods for Anharmonic Free Energies

Author(s): Venkat Kapil, Edgar Engel, Mariana Rossi, Michele Ceriotti
Published in: Journal of Chemical Theory and Computation, Issue 15/11, 2019, Page(s) 5845-5857, ISSN 1549-9618
DOI: 10.1021/acs.jctc.9b00596

A Bayesian approach to NMR crystal structure determination

Author(s): Edgar A. Engel, Andrea Anelli, Albert Hofstetter, Federico Paruzzo, Lyndon Emsley, Michele Ceriotti
Published in: Physical Chemistry Chemical Physics, Issue 21/42, 2019, Page(s) 23385-23400, ISSN 1463-9076
DOI: 10.1039/c9cp04489b

Quantum mechanical static dipole polarizabilities in the QM7b and AlphaML showcase databases

Author(s): Yang Yang, Ka Un Lao, David M. Wilkins, Andrea Grisafi, Michele Ceriotti, Robert A. DiStasio
Published in: Scientific Data, Issue 6/1, 2019, ISSN 2052-4463
DOI: 10.1038/s41597-019-0157-8

Using Gaussian process regression to simulate the vibrational Raman spectra of molecular crystals

Author(s): Nathaniel Raimbault, Andrea Grisafi, Michele Ceriotti, Mariana Rossi
Published in: New Journal of Physics, Issue 21/10, 2019, Page(s) 105001, ISSN 1367-2630
DOI: 10.1088/1367-2630/ab4509

Barely porous organic cages for hydrogen isotope separation

Author(s): Ming Liu, Linda Zhang, Marc A. Little, Venkat Kapil, Michele Ceriotti, Siyuan Yang, Lifeng Ding, Daniel L. Holden, Rafael Balderas-Xicohténcatl, Donglin He, Rob Clowes, Samantha Y. Chong, Gisela Schütz, Linjiang Chen, Michael Hirscher, Andrew I. Cooper
Published in: Science, Issue 366/6465, 2019, Page(s) 613-620, ISSN 0036-8075
DOI: 10.1126/science.aax7427

Atomic Motif Recognition in (Bio)Polymers: Benchmarks From the Protein Data Bank

Author(s): Benjamin A. Helfrecht, Piero Gasparotto, Federico Giberti, Michele Ceriotti
Published in: Frontiers in Molecular Biosciences, Issue 6, 2019, ISSN 2296-889X
DOI: 10.3389/fmolb.2019.00024

Incorporating long-range physics in atomic-scale machine learning

Author(s): Andrea Grisafi, Michele Ceriotti
Published in: The Journal of Chemical Physics, Issue 151/20, 2019, Page(s) 204105, ISSN 0021-9606
DOI: 10.1063/1.5128375

Thermally-nucleated self-assembly of water and alcohol into stable structures at hydrophobic interfaces

Author(s): Kislon Voïtchovsky, Daniele Giofrè, Juan José Segura, Francesco Stellacci, Michele Ceriotti
Published in: Nature Communications, Issue 7, 2016, Page(s) 13064, ISSN 2041-1723
DOI: 10.1038/ncomms13064

Non-peer reviewed articles (1)

Determination and evaluation of the nonadditivity in wetting of molecularly heterogeneous surfaces

Author(s): Zhi Luo, Anna Murello, David M. Wilkins, Filip Kovacik, Joachim Kohlbrecher, Aurel Radulescu, Halil I. Okur, Quy K. Ong, Sylvie Roke, Michele Ceriotti, Francesco Stellacci
Published in: Proceedings of the National Academy of Sciences, Issue 116/51, 2019, Page(s) 25516-25523, ISSN 0027-8424
DOI: 10.1073/pnas.1916180116