1
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Litman Y, Kapil V, Feldman YMY, Tisi D, Begušić T, Fidanyan K, Fraux G, Higer J, Kellner M, Li TE, Pós ES, Stocco E, Trenins G, Hirshberg B, Rossi M, Ceriotti M. i-PI 3.0: A flexible and efficient framework for advanced atomistic simulations. J Chem Phys 2024; 161:062504. [PMID: 39140447 DOI: 10.1063/5.0215869] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2024] [Accepted: 07/11/2024] [Indexed: 08/15/2024] Open
Abstract
Atomic-scale simulations have progressed tremendously over the past decade, largely thanks to the availability of machine-learning interatomic potentials. These potentials combine the accuracy of electronic structure calculations with the ability to reach extensive length and time scales. The i-PI package facilitates integrating the latest developments in this field with advanced modeling techniques thanks to a modular software architecture based on inter-process communication through a socket interface. The choice of Python for implementation facilitates rapid prototyping but can add computational overhead. In this new release, we carefully benchmarked and optimized i-PI for several common simulation scenarios, making such overhead negligible when i-PI is used to model systems up to tens of thousands of atoms using widely adopted machine learning interatomic potentials, such as Behler-Parinello, DeePMD, and MACE neural networks. We also present the implementation of several new features, including an efficient algorithm to model bosonic and fermionic exchange, a framework for uncertainty quantification to be used in conjunction with machine-learning potentials, a communication infrastructure that allows for deeper integration with electronic-driven simulations, and an approach to simulate coupled photon-nuclear dynamics in optical or plasmonic cavities.
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Affiliation(s)
- Yair Litman
- Y. Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom
| | - Venkat Kapil
- Y. Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom
- Department of Physics and Astronomy, University College London, 17-19 Gordon St, London WC1H 0AH, United Kingdom
- Thomas Young Centre and London Centre for Nanotechnology, 19 Gordon St, London WC1H 0AH, United Kingdom
| | | | - Davide Tisi
- Laboratory of Computational Science and Modeling, Institut des Matériaux, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Tomislav Begušić
- Div. of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125, USA
| | - Karen Fidanyan
- MPI for the Structure and Dynamics of Matter, Hamburg, Germany
| | - Guillaume Fraux
- Laboratory of Computational Science and Modeling, Institut des Matériaux, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Jacob Higer
- School of Physics, Tel Aviv University, Tel Aviv 6997801, Israel
| | - Matthias Kellner
- Laboratory of Computational Science and Modeling, Institut des Matériaux, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Tao E Li
- Department of Physics and Astronomy, University of Delaware, Newark, Delaware 19716, USA
| | - Eszter S Pós
- MPI for the Structure and Dynamics of Matter, Hamburg, Germany
| | - Elia Stocco
- MPI for the Structure and Dynamics of Matter, Hamburg, Germany
| | - George Trenins
- MPI for the Structure and Dynamics of Matter, Hamburg, Germany
| | - Barak Hirshberg
- School of Chemistry, Tel Aviv University, Tel Aviv 6997801, Israel
| | - Mariana Rossi
- MPI for the Structure and Dynamics of Matter, Hamburg, Germany
| | - Michele Ceriotti
- Laboratory of Computational Science and Modeling, Institut des Matériaux, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
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2
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Berrens M, Kundu A, Calegari Andrade MF, Pham TA, Galli G, Donadio D. Nuclear Quantum Effects on the Electronic Structure of Water and Ice. J Phys Chem Lett 2024; 15:6818-6825. [PMID: 38916450 PMCID: PMC11229061 DOI: 10.1021/acs.jpclett.4c01315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2024] [Revised: 06/17/2024] [Accepted: 06/21/2024] [Indexed: 06/26/2024]
Abstract
The electronic properties and optical response of ice and water are intricately shaped by their molecular structure, including the quantum mechanical nature of the hydrogen atoms. Despite numerous previous studies, a comprehensive understanding of the nuclear quantum effects (NQEs) on the electronic structure of water and ice at finite temperatures remains elusive. Here, we utilize molecular simulations that harness efficient machine-learning potentials and many-body perturbation theory to assess how NQEs impact the electronic bands of water and hexagonal ice. By comparing path-integral and classical simulations, we find that NQEs lead to a larger renormalization of the fundamental gap of ice, compared to that of water, ultimately yielding similar bandgaps in the two systems, consistent with experimental estimates. Our calculations suggest that the increased quantum mechanical delocalization of protons in ice, relative to water, is a key factor leading to the enhancement of NQEs on the electronic structure of ice.
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Affiliation(s)
- Margaret
L. Berrens
- Department
of Chemistry, University of California Davis, One Shields Ave.. Davis, California 95616, United States
| | - Arpan Kundu
- Pritzker
School of Molecular Engineering, University
of Chicago, Chicago, Illinois 60637, United States
| | - Marcos F. Calegari Andrade
- Quantum
Simulations Group, Materials Science Division, Lawrence Livermore National Laboratory, Livermore, California 94550-5507, United States
| | - Tuan Anh Pham
- Quantum
Simulations Group, Materials Science Division, Lawrence Livermore National Laboratory, Livermore, California 94550-5507, United States
| | - Giulia Galli
- Pritzker
School of Molecular Engineering, University
of Chicago, Chicago, Illinois 60637, United States
- Department
of Chemistry, University of Chicago, Chicago, Illinois 60637, United States
- Materials
Science Division and Center for Molecular Engineering, Argonne National Laboratory, Lemont, Illinois 60439, United States
| | - Davide Donadio
- Department
of Chemistry, University of California Davis, One Shields Ave.. Davis, California 95616, United States
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3
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Jana A, Shepherd S, Litman Y, Wilkins DM. Learning Electronic Polarizations in Aqueous Systems. J Chem Inf Model 2024; 64:4426-4435. [PMID: 38804973 PMCID: PMC11167596 DOI: 10.1021/acs.jcim.4c00421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Revised: 05/10/2024] [Accepted: 05/14/2024] [Indexed: 05/29/2024]
Abstract
The polarization of periodically repeating systems is a discontinuous function of the atomic positions, a fact which seems at first to stymie attempts at their statistical learning. Two approaches to build models for bulk polarizations are compared: one in which a simple point charge model is used to preprocess the raw polarization to give a learning target that is a smooth function of atomic positions and the total polarization is learned as a sum of atom-centered dipoles and one in which instead the average position of Wannier centers around atoms is predicted. For a range of bulk aqueous systems, both of these methods perform perform comparatively well, with the former being slightly better but often requiring an extra effort to find a suitable point charge model. As a challenging test, we also analyze the performance of the models at the air-water interface. In this case, while the Wannier center approach delivers accurate predictions without further modifications, the preprocessing method requires augmentation with information from isolated water molecules to reach similar accuracy. Finally, we present a simple protocol to preprocess the polarizations in a data-driven way using a small number of derivatives calculated at a much lower level of theory, thus overcoming the need to find point charge models without appreciably increasing the computation cost. We believe that the training strategies presented here help the construction of accurate polarization models required for the study of the dielectric properties of realistic complex bulk systems and interfaces with ab initio accuracy.
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Affiliation(s)
- Arnab Jana
- Centre
for Quantum Materials and Technologies, School of Mathematics and
Physics, Queen’s University Belfast, Belfast BT7 1NN, U.K.
| | - Sam Shepherd
- Centre
for Quantum Materials and Technologies, School of Mathematics and
Physics, Queen’s University Belfast, Belfast BT7 1NN, U.K.
| | - Yair Litman
- Yusuf
Hamied Department of Chemistry, University
of Cambridge, Lensfield Road, Cambridge CB2 1EW, U.K.
| | - David M. Wilkins
- Centre
for Quantum Materials and Technologies, School of Mathematics and
Physics, Queen’s University Belfast, Belfast BT7 1NN, U.K.
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4
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Montero de Hijes P, Dellago C, Jinnouchi R, Schmiedmayer B, Kresse G. Comparing machine learning potentials for water: Kernel-based regression and Behler-Parrinello neural networks. J Chem Phys 2024; 160:114107. [PMID: 38506284 DOI: 10.1063/5.0197105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Accepted: 03/03/2024] [Indexed: 03/21/2024] Open
Abstract
In this paper, we investigate the performance of different machine learning potentials (MLPs) in predicting key thermodynamic properties of water using RPBE + D3. Specifically, we scrutinize kernel-based regression and high-dimensional neural networks trained on a highly accurate dataset consisting of about 1500 structures, as well as a smaller dataset, about half the size, obtained using only on-the-fly learning. This study reveals that despite minor differences between the MLPs, their agreement on observables such as the diffusion constant and pair-correlation functions is excellent, especially for the large training dataset. Variations in the predicted density isobars, albeit somewhat larger, are also acceptable, particularly given the errors inherent to approximate density functional theory. Overall, this study emphasizes the relevance of the database over the fitting method. Finally, this study underscores the limitations of root mean square errors and the need for comprehensive testing, advocating the use of multiple MLPs for enhanced certainty, particularly when simulating complex thermodynamic properties that may not be fully captured by simpler tests.
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Affiliation(s)
- Pablo Montero de Hijes
- University of Vienna, Faculty of Physics, Kolingasse 14, A-1090 Vienna, Austria
- University of Vienna, Faculty of Earth Sciences, Geography and Astronomy, Josef-Holaubuek-Platz 2, 1090 Vienna, Austria
| | - Christoph Dellago
- University of Vienna, Faculty of Physics, Kolingasse 14, A-1090 Vienna, Austria
| | - Ryosuke Jinnouchi
- Toyota Central R&D Labs., Inc., 41-1 Yokomichi, Nagakute, Aichi 480-1192, Japan
| | | | - Georg Kresse
- University of Vienna, Faculty of Physics, Kolingasse 14, A-1090 Vienna, Austria
- VASP Software GmbH, Berggasse 21, A-1090 Vienna, Austria
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5
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Tokita AM, Behler J. How to train a neural network potential. J Chem Phys 2023; 159:121501. [PMID: 38127396 DOI: 10.1063/5.0160326] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 07/24/2023] [Indexed: 12/23/2023] Open
Abstract
The introduction of modern Machine Learning Potentials (MLPs) has led to a paradigm change in the development of potential energy surfaces for atomistic simulations. By providing efficient access to energies and forces, they allow us to perform large-scale simulations of extended systems, which are not directly accessible by demanding first-principles methods. In these simulations, MLPs can reach the accuracy of electronic structure calculations, provided that they have been properly trained and validated using a suitable set of reference data. Due to their highly flexible functional form, the construction of MLPs has to be done with great care. In this Tutorial, we describe the necessary key steps for training reliable MLPs, from data generation via training to final validation. The procedure, which is illustrated for the example of a high-dimensional neural network potential, is general and applicable to many types of MLPs.
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Affiliation(s)
- Alea Miako Tokita
- Lehrstuhl für Theoretische Chemie II, Ruhr-Universität Bochum, 44780 Bochum, Germany and Research Center Chemical Sciences and Sustainability, Research Alliance Ruhr, 44780 Bochum, Germany
| | - Jörg Behler
- Lehrstuhl für Theoretische Chemie II, Ruhr-Universität Bochum, 44780 Bochum, Germany and Research Center Chemical Sciences and Sustainability, Research Alliance Ruhr, 44780 Bochum, Germany
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6
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Trenins G, Meuser L, Bertschi H, Vavourakis O, Flütsch R, Richardson JO. Exact tunneling splittings from symmetrized path integrals. J Chem Phys 2023; 159:034108. [PMID: 37466233 DOI: 10.1063/5.0158879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 06/13/2023] [Indexed: 07/20/2023] Open
Abstract
We develop a new simulation technique based on path-integral molecular dynamics for calculating ground-state tunneling splitting patterns from ratios of symmetrized partition functions. In particular, molecular systems are rigorously projected onto their J = 0 rotational state by an "Eckart spring" that connects two adjacent beads in a ring polymer. Using this procedure, the tunneling splitting can be obtained from thermodynamic integration at just one (sufficiently low) temperature. Converged results are formally identical to the values that would have been obtained by solving the full rovibrational Schrödinger equation on a given Born-Oppenheimer potential energy surface. The new approach is showcased with simulations of hydronium and methanol, which are in good agreement with wavefunction-based calculations and experimental measurements. The method will be of particular use for the study of low-barrier methyl rotations and other floppy modes, where instanton theory is not valid.
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Affiliation(s)
- George Trenins
- Department of Chemistry and Applied Biosciences, ETH Zürich, 8093 Zürich, Switzerland
| | - Lars Meuser
- Department of Chemistry and Applied Biosciences, ETH Zürich, 8093 Zürich, Switzerland
| | - Hannah Bertschi
- Department of Chemistry and Applied Biosciences, ETH Zürich, 8093 Zürich, Switzerland
| | - Odysseas Vavourakis
- Department of Chemistry and Applied Biosciences, ETH Zürich, 8093 Zürich, Switzerland
| | - Reto Flütsch
- Department of Chemistry and Applied Biosciences, ETH Zürich, 8093 Zürich, Switzerland
| | - Jeremy O Richardson
- Department of Chemistry and Applied Biosciences, ETH Zürich, 8093 Zürich, Switzerland
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7
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Alvertis AM, Haber JB, Engel EA, Sharifzadeh S, Neaton JB. Phonon-Induced Localization of Excitons in Molecular Crystals from First Principles. PHYSICAL REVIEW LETTERS 2023; 130:086401. [PMID: 36898125 DOI: 10.1103/physrevlett.130.086401] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 01/20/2023] [Accepted: 01/23/2023] [Indexed: 06/18/2023]
Abstract
The spatial extent of excitons in molecular systems underpins their photophysics and utility for optoelectronic applications. Phonons are reported to lead to both exciton localization and delocalization. However, a microscopic understanding of phonon-induced (de)localization is lacking, in particular, how localized states form, the role of specific vibrations, and the relative importance of quantum and thermal nuclear fluctuations. Here, we present a first-principles study of these phenomena in solid pentacene, a prototypical molecular crystal, capturing the formation of bound excitons, exciton-phonon coupling to all orders, and phonon anharmonicity, using density functional theory, the ab initio GW-Bethe-Salpeter equation approach, finite-difference, and path integral techniques. We find that for pentacene zero-point nuclear motion causes uniformly strong localization, with thermal motion providing additional localization only for Wannier-Mott-like excitons. Anharmonic effects drive temperature-dependent localization, and, while such effects prevent the emergence of highly delocalized excitons, we explore the conditions under which these might be realized.
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Affiliation(s)
- Antonios M Alvertis
- Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
- Department of Physics, University of California Berkeley, Berkeley, 94720 California, USA
| | - Jonah B Haber
- Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
- Department of Physics, University of California Berkeley, Berkeley, 94720 California, USA
| | - Edgar A Engel
- Cavendish Laboratory, University of Cambridge, J.J. Thomson Avenue, Cambridge CB3 0HE, United Kingdom
| | - Sahar Sharifzadeh
- Division of Materials Science and Engineering, Boston University, Boston, 02215 Massachusetts, USA
- Department of Electrical and Computer Engineering, Boston University, Boston, 02215 Massachusetts, USA
| | - Jeffrey B Neaton
- Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
- Department of Physics, University of California Berkeley, Berkeley, 94720 California, USA
- Kavli Energy NanoScience Institute at Berkeley, Berkeley, 94720 California, USA
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8
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Mauger N, Plé T, Lagardère L, Huppert S, Piquemal JP. Improving Condensed-Phase Water Dynamics with Explicit Nuclear Quantum Effects: The Polarizable Q-AMOEBA Force Field. J Phys Chem B 2022; 126:8813-8826. [PMID: 36270033 DOI: 10.1021/acs.jpcb.2c04454] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
We introduce a new parametrization of the AMOEBA polarizable force field for water denoted Q-AMOEBA, for use in simulations that explicitly account for nuclear quantum effects (NQEs). This study is made possible thanks to the recently introduced adaptive Quantum Thermal Bath (adQTB) simulation technique which computational cost is comparable to classical molecular dynamics. The flexible Q-AMOEBA model conserves the initial AMOEBA functional form, with an intermolecular potential including an atomic multipole description of electrostatic interactions (up to quadrupole), a polarization contribution based on the Thole interaction model and a buffered 14-7 potential to model van der Waals interactions. It has been obtained by using a ForceBalance fitting strategy including high-level quantum chemistry reference energies and selected condensed-phase properties targets. The final Q-AMOEBA model is shown to accurately reproduce both gas-phase and condensed-phase properties, notably improving the original AMOEBA water model. This development allows the fine study of NQEs on water liquid phase properties such as the average H-O-H angle compared to its gas-phase equilibrium value, isotope effects, and so on. Q-AMOEBA also provides improved infrared spectroscopy prediction capabilities compared to AMOEBA03. Overall, we show that the impact of NQEs depends on the underlying model functional form and on the associated strength of hydrogen bonds. Since adQTB simulations can be performed at near classical computational cost using the Tinker-HP package, Q-AMOEBA can be extended to organic molecules, proteins, and nucleic acids opening the possibility for the large-scale study of the importance of NQEs in biophysics.
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Affiliation(s)
- Nastasia Mauger
- Sorbonne Université, Laboratoire de Chimie Théorique, UMR 7616 CNRS, 75005 Paris, France
| | - Thomas Plé
- Sorbonne Université, Laboratoire de Chimie Théorique, UMR 7616 CNRS, 75005 Paris, France
| | - Louis Lagardère
- Sorbonne Université, Laboratoire de Chimie Théorique, UMR 7616 CNRS, 75005 Paris, France
| | - Simon Huppert
- Sorbonne Université, Institut des NanoSciences de Paris, UMR 7588 CNRS, 75005 Paris, France
| | - Jean-Philip Piquemal
- Sorbonne Université, Laboratoire de Chimie Théorique, UMR 7616 CNRS, 75005 Paris, France
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9
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Liu Z, Xu W, Tuckerman ME, Sun X. Imaginary-Time Open-Chain Path-Integral Approach for Two-State Time Correlation Functions and Applications in Charge Transfer. J Chem Phys 2022; 157:114111. [DOI: 10.1063/5.0098162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Quantum time correlation functions (TCFs) involving two states are important for describing nonadiabatic dynamical processes such as charge transfer. Based on a previous single-state method, we propose an imaginary-time open-chain path-integral (OCPI) approach for evaluating the two-state symmetrized TCFs. Expressing the forward and backward propagation on different electronic potential energy surfaces as a complex-time path integral, we then transform the path variables to average and difference variables such that the integration over the difference variables up to the second order can be performed analytically. The resulting expression for the symmetrized TCF is equivalent to sampling the open-chain configurations in an effective potential that corresponds to the average surface. Using importance sampling over the extended OCPI space via open path integral molecular dynamics, we tested the resulting path-integral approximation by calculating the Fermi's golden rule charge transfer rate constant within a widely-used spin-boson model. Comparing with the real-time linearized semiclassical method and analytical result, we show that the imaginary-time OCPI provides an accurate two-state symmetrized TCF and rate constant in the typical turnover region. It is shown that the first bead of the open chain corresponds to physical zero-time, and the endpoint bead corresponds to final time t; oscillations of the end-to-end distance perfectly match the nuclear mode frequency. The two-state OCPI scheme is seen to capture the tested model's electronic quantum coherence and nuclear quantum effects accurately.
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Affiliation(s)
- Zengkui Liu
- Division of Arts and Sciences, New York University Shanghai, China
| | - Wen Xu
- New York University Shanghai, China
| | - Mark E. Tuckerman
- Department of Chemistry and Courant Institute of Mathematical Sciences, New York University, United States of America
| | - Xiang Sun
- Division of Arts and Sciences, New York University Shanghai, China
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10
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Wang C, Zhang L, Liu J, Shao J. Generalized fourth-order decompositions of imaginary time path integral: Implications of the harmonic oscillator. CHINESE J CHEM PHYS 2022. [DOI: 10.1063/1674-0068/cjcp2205089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
The imaginary time path integral formalism offers a powerful numerical tool for simulating thermodynamic properties of realistic systems. We show that, when second-order and fourth-order decompositions are employed, they share a remarkable unified analytic form for the partition function of the harmonic oscillator. We are then able to obtain the expression of the thermodynamic property and the leading error terms as well. In order to obtain reasonably optimal values of the free parameters in the generalized symmetric fourth-order decomposition scheme, we eliminate the leading error terms to achieve the accuracy of desired order for the thermodynamic property of the harmonic system. Such a strategy leads to an efficient fourth-order decomposition that produces third-order accurate thermodynamic properties for general systems.
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Affiliation(s)
- Cong Wang
- College of Chemistry and Center for Advanced Quantum Studies, Key Laboratory of Theoretical and Computational Photochemistry, Ministry of Education, Beijing Normal University, Beijing 100875, China
| | - Lihan Zhang
- Institute of Condensed Matter and Material Physics, School of Physics, Peking University, Beijing 100871, China
| | - Jian Liu
- Beijing National Laboratory for Molecular Sciences, Institute of Theoretical and Computational Chemistry, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China
| | - Jiushu Shao
- College of Chemistry and Center for Advanced Quantum Studies, Key Laboratory of Theoretical and Computational Photochemistry, Ministry of Education, Beijing Normal University, Beijing 100875, China
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11
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Wu C, Li R, Yu K. Learning the Quantum Centroid Force Correction in Molecular Systems: A Localized Approach. Front Mol Biosci 2022; 9:851311. [PMID: 35664679 PMCID: PMC9161153 DOI: 10.3389/fmolb.2022.851311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2022] [Accepted: 04/27/2022] [Indexed: 11/13/2022] Open
Abstract
Molecular mechanics (MM) is a powerful tool to study the properties of molecular systems in the fields of biology and materials science. With the development of ab initio force field and the application of ab initio potential energy surface, the nuclear quantum effect (NQE) is becoming increasingly important for the robustness of the simulation. However, the state-of-the-art path-integral molecular dynamics simulation, which incorporates NQE in MM, is still too expensive to conduct for most biological and material systems. In this work, we analyze the locality of NQE, using both analytical and numerical approaches, and conclude that NQE is an extremely localized phenomenon in nonreactive molecular systems. Therefore, we can use localized machine learning (ML) models to predict quantum force corrections both accurately and efficiently. Using liquid water as example, we show that the ML facilitated centroid MD can reproduce the NQEs in both the thermodynamical and the dynamical properties, with a minimal increase in computational time compared to classical molecular dynamics. This simple approach thus largely decreases the computational cost of quantum simulations, making it really accessible to the studies of large-scale molecular systems.
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Affiliation(s)
| | | | - Kuang Yu
- Tsinghua-Berkeley Shenzhen Institute, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China
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12
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A complete description of thermodynamic stabilities of molecular crystals. Proc Natl Acad Sci U S A 2022; 119:2111769119. [PMID: 35131847 PMCID: PMC8832981 DOI: 10.1073/pnas.2111769119] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/23/2021] [Indexed: 12/27/2022] Open
Abstract
Predicting stable polymorphs of molecular crystals remains one of the grand challenges of computational science. Current methods invoke approximations to electronic structure and statistical mechanics and thus fail to consistently reproduce the delicate balance of physical effects determining thermodynamic stability. We compute the rigorous ab initio Gibbs free energies for competing polymorphs of paradigmatic compounds, using machine learning to mitigate costs. The accurate description of electronic structure and full treatment of quantum statistical mechanics allow us to predict the experimentally observed phase behavior. This constitutes a key step toward the first-principles design of functional materials for applications from photovoltaics to pharmaceuticals. Predictions of relative stabilities of (competing) molecular crystals are of great technological relevance, most notably for the pharmaceutical industry. However, they present a long-standing challenge for modeling, as often minuscule free energy differences are sensitively affected by the description of electronic structure, the statistical mechanics of the nuclei and the cell, and thermal expansion. The importance of these effects has been individually established, but rigorous free energy calculations for general molecular compounds, which simultaneously account for all effects, have hitherto not been computationally viable. Here we present an efficient “end to end” framework that seamlessly combines state-of-the art electronic structure calculations, machine-learning potentials, and advanced free energy methods to calculate ab initio Gibbs free energies for general organic molecular materials. The facile generation of machine-learning potentials for a diverse set of polymorphic compounds—benzene, glycine, and succinic acid—and predictions of thermodynamic stabilities in qualitative and quantitative agreement with experiments highlight that predictive thermodynamic studies of industrially relevant molecular materials are no longer a daunting task.
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13
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Campos-Villalobos G, Boattini E, Filion L, Dijkstra M. Machine learning many-body potentials for colloidal systems. J Chem Phys 2021; 155:174902. [PMID: 34742191 DOI: 10.1063/5.0063377] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Simulations of colloidal suspensions consisting of mesoscopic particles and smaller species such as ions or depletants are computationally challenging as different length and time scales are involved. Here, we introduce a machine learning (ML) approach in which the degrees of freedom of the microscopic species are integrated out and the mesoscopic particles interact with effective many-body potentials, which we fit as a function of all colloid coordinates with a set of symmetry functions. We apply this approach to a colloid-polymer mixture. Remarkably, the ML potentials can be assumed to be effectively state-independent and can be used in direct-coexistence simulations. We show that our ML method reduces the computational cost by several orders of magnitude compared to a numerical evaluation and accurately describes the phase behavior and structure, even for state points where the effective potential is largely determined by many-body contributions.
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Affiliation(s)
- Gerardo Campos-Villalobos
- Soft Condensed Matter, Debye Institute for Nanomaterials Science, Utrecht University, Princetonplein 1, 3584 CC Utrecht, The Netherlands
| | - Emanuele Boattini
- Soft Condensed Matter, Debye Institute for Nanomaterials Science, Utrecht University, Princetonplein 1, 3584 CC Utrecht, The Netherlands
| | - Laura Filion
- Soft Condensed Matter, Debye Institute for Nanomaterials Science, Utrecht University, Princetonplein 1, 3584 CC Utrecht, The Netherlands
| | - Marjolein Dijkstra
- Soft Condensed Matter, Debye Institute for Nanomaterials Science, Utrecht University, Princetonplein 1, 3584 CC Utrecht, The Netherlands
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14
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Shepherd S, Lan J, Wilkins DM, Kapil V. Efficient Quantum Vibrational Spectroscopy of Water with High-Order Path Integrals: From Bulk to Interfaces. J Phys Chem Lett 2021; 12:9108-9114. [PMID: 34523941 DOI: 10.1021/acs.jpclett.1c02574] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Vibrational spectroscopy is key in probing the interplay between the structure and dynamics of aqueous systems. To map different regions of experimental spectra to the microscopic structure of a system, it is important to combine them with first-principles atomistic simulations that incorporate the quantum nature of nuclei. Here we show that the large cost of calculating the quantum vibrational spectra of aqueous systems can be dramatically reduced compared with standard path integral methods by using approximate quantum dynamics based on high-order path integrals. Together with state-of-the-art machine-learned electronic properties, our approach gives an excellent description not only of the infrared and Raman spectra of bulk water but also of the 2D correlation and the more challenging sum-frequency generation spectra of the water-air interface. This paves the way for understanding complex interfaces such as water encapsulated between or in contact with hydrophobic and hydrophilic materials through robust and inexpensive surface-sensitive and multidimensional spectra with first-principles accuracy.
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Affiliation(s)
- Sam Shepherd
- Atomistic Simulation Centre, School of Mathematics and Physics, Queen's University Belfast, Belfast BT7 1NN, Northern Ireland, United Kingdom
| | - Jinggang Lan
- Department of Chemistry, University of Zürich, Zürich 8057, Switzerland
| | - David M Wilkins
- Atomistic Simulation Centre, School of Mathematics and Physics, Queen's University Belfast, Belfast BT7 1NN, Northern Ireland, United Kingdom
| | - Venkat Kapil
- Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW,United Kingdom
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15
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Mauger N, Plé T, Lagardère L, Bonella S, Mangaud É, Piquemal JP, Huppert S. Nuclear Quantum Effects in Liquid Water at Near Classical Computational Cost Using the Adaptive Quantum Thermal Bath. J Phys Chem Lett 2021; 12:8285-8291. [PMID: 34427440 DOI: 10.1021/acs.jpclett.1c01722] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
We demonstrate the accuracy and efficiency of a recently introduced approach to account for nuclear quantum effects (NQEs) in molecular simulations: the adaptive quantum thermal bath (adQTB). In this method, zero-point energy is introduced through a generalized Langevin thermostat designed to precisely enforce the quantum fluctuation-dissipation theorem. We propose a refined adQTB algorithm with improved accuracy and report adQTB simulations of liquid water. Through extensive comparison with reference path integral calculations, we demonstrate that it provides excellent accuracy for a broad range of structural and thermodynamic observables as well as infrared vibrational spectra. The adQTB has a computational cost comparable to that of classical molecular dynamics, enabling simulations of up to millions of degrees of freedom.
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Affiliation(s)
- Nastasia Mauger
- Sorbonne Université, LCT, UMR 7616 CNRS, F-75005 Paris, France
| | - Thomas Plé
- CNRS, Sorbonne Université, Institut des NanoSciences de Paris, UMR 7588, 4 Place Jussieu, F-75005 Paris, France
| | - Louis Lagardère
- Sorbonne Université, LCT, UMR 7616 CNRS, F-75005 Paris, France
| | - Sara Bonella
- CECAM Centre Européen de Calcul Atomique et Moléculaire, École Polytechnique Fédérale de Lausanne, Batochimie, Avenue Forel 2, 1015 Lausanne, Switzerland
| | - Étienne Mangaud
- CNRS, Sorbonne Université, Institut des NanoSciences de Paris, UMR 7588, 4 Place Jussieu, F-75005 Paris, France
| | - Jean-Philip Piquemal
- Sorbonne Université, LCT, UMR 7616 CNRS, F-75005 Paris, France
- Institut Universitaire de France, 75005 Paris, France
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Simon Huppert
- CNRS, Sorbonne Université, Institut des NanoSciences de Paris, UMR 7588, 4 Place Jussieu, F-75005 Paris, France
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16
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Remsing RC, Bates JE. Effective mass path integral simulations of quasiparticles in condensed phases. J Chem Phys 2020; 153:121104. [PMID: 33003737 DOI: 10.1063/5.0020555] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
The quantum many-body problem in condensed phases is often simplified using a quasiparticle description, such as effective mass theory for electron motion in a periodic solid. These approaches are often the basis for understanding many fundamental condensed phase processes, including the molecular mechanisms underlying solar energy harvesting and photocatalysis. Despite the importance of these effective particles, there is still a need for computational methods that can explore their behavior on chemically relevant length and time scales. This is especially true when the interactions between the particles and their environment are important. We introduce an approach for studying quasiparticles in condensed phases by combining effective mass theory with the path integral treatment of quantum particles. This framework incorporates the generally anisotropic electronic band structure of materials into path integral simulation schemes to enable modeling of quasiparticles in quantum confinement, for example. We demonstrate the utility of effective mass path integral simulations by modeling an exciton in solid potassium chloride and electron trapping by a sulfur vacancy in monolayer molybdenum disulfide.
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Affiliation(s)
- Richard C Remsing
- Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, New Jersey 08854, USA
| | - Jefferson E Bates
- A. R. Smith Department of Chemistry and Fermentation Sciences, Appalachian State University, Boone, North Carolina 28608, USA
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17
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Schran C, Brezina K, Marsalek O. Committee neural network potentials control generalization errors and enable active learning. J Chem Phys 2020; 153:104105. [DOI: 10.1063/5.0016004] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Christoph Schran
- Charles University, Faculty of Mathematics and Physics, Ke Karlovu 3, 121 16 Prague 2, Czech Republic
| | - Krystof Brezina
- Charles University, Faculty of Mathematics and Physics, Ke Karlovu 3, 121 16 Prague 2, Czech Republic
| | - Ondrej Marsalek
- Charles University, Faculty of Mathematics and Physics, Ke Karlovu 3, 121 16 Prague 2, Czech Republic
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18
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Boattini E, Bezem N, Punnathanam SN, Smallenburg F, Filion L. Modeling of many-body interactions between elastic spheres through symmetry functions. J Chem Phys 2020; 153:064902. [DOI: 10.1063/5.0015606] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Affiliation(s)
- Emanuele Boattini
- Soft Condensed Matter, Debye Institute for Nanomaterials Science, Utrecht University, Utrecht, The Netherlands
| | - Nina Bezem
- Soft Condensed Matter, Debye Institute for Nanomaterials Science, Utrecht University, Utrecht, The Netherlands
| | - Sudeep N. Punnathanam
- Department of Chemical Engineering, Indian Institute of Science, Bangalore 560012, Karnataka, India
| | - Frank Smallenburg
- Université Paris-Saclay, CNRS, Laboratoire de Physique des Solides, 91405 Orsay, France
| | - Laura Filion
- Soft Condensed Matter, Debye Institute for Nanomaterials Science, Utrecht University, Utrecht, The Netherlands
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19
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Pattnaik P, Raghunathan S, Kalluri T, Bhimalapuram P, Jawahar CV, Priyakumar UD. Machine Learning for Accurate Force Calculations in Molecular Dynamics Simulations. J Phys Chem A 2020; 124:6954-6967. [DOI: 10.1021/acs.jpca.0c03926] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Punyaslok Pattnaik
- Center for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology, Hyderabad 500 032, India
| | - Shampa Raghunathan
- Center for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology, Hyderabad 500 032, India
| | - Tarun Kalluri
- Center for Visual Information Technology, KCIS, International Institute of Information Technology, Hyderabad 500 032, India
| | - Prabhakar Bhimalapuram
- Center for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology, Hyderabad 500 032, India
| | - C. V. Jawahar
- Center for Visual Information Technology, KCIS, International Institute of Information Technology, Hyderabad 500 032, India
| | - U. Deva Priyakumar
- Center for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology, Hyderabad 500 032, India
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20
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Yao Y, Kanai Y. Temperature dependence of nuclear quantum effects on liquid water via artificial neural network model based on SCAN meta-GGA functional. J Chem Phys 2020; 153:044114. [DOI: 10.1063/5.0012815] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Yi Yao
- Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
- Department of Mechanical Engineering and Materials Science, Duke University, Durham, North Carolina 27708, USA
| | - Yosuke Kanai
- Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
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21
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Mandelli D, Hirshberg B, Parrinello M. Metadynamics of Paths. PHYSICAL REVIEW LETTERS 2020; 125:026001. [PMID: 32701329 DOI: 10.1103/physrevlett.125.026001] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/17/2020] [Revised: 05/09/2020] [Accepted: 06/12/2020] [Indexed: 05/27/2023]
Abstract
We present a method to sample reactive pathways via biased molecular dynamics simulations in trajectory space. We show that the use of enhanced sampling techniques enables unconstrained exploration of multiple reaction routes. Time correlation functions are conveniently computed via reweighted averages along a single trajectory and kinetic rates are accessed at no additional cost. These abilities are illustrated analyzing a model potential and the umbrella inversion of NH_{3} in water. The algorithm allows a parallel implementation and promises to be a powerful tool for the study of rare events.
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Affiliation(s)
- Davide Mandelli
- Atomistic Simulations, Italian Institute of Technology, via Morego 30, 16163 Genova, Italy
| | - Barak Hirshberg
- Department of Chemistry and Applied Biosciences, ETH Zurich, 8092 Zurich, Switzerland
- Institute of Computational Sciences, Università della Svizzera Italiana, 6900 Lugano, Switzerland
| | - Michele Parrinello
- Atomistic Simulations, Italian Institute of Technology, via Morego 30, 16163 Genova, Italy
- Department of Chemistry and Applied Biosciences, ETH Zurich, 8092 Zurich, Switzerland
- Institute of Computational Sciences, Università della Svizzera Italiana, 6900 Lugano, Switzerland
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22
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Brieuc F, Schran C, Uhl F, Forbert H, Marx D. Converged quantum simulations of reactive solutes in superfluid helium: The Bochum perspective. J Chem Phys 2020; 152:210901. [DOI: 10.1063/5.0008309] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Affiliation(s)
- Fabien Brieuc
- Lehrstuhl für Theoretische Chemie, Ruhr-Universität Bochum, 44780 Bochum, Germany
| | - Christoph Schran
- Lehrstuhl für Theoretische Chemie, Ruhr-Universität Bochum, 44780 Bochum, Germany
| | - Felix Uhl
- Lehrstuhl für Theoretische Chemie, Ruhr-Universität Bochum, 44780 Bochum, Germany
| | - Harald Forbert
- Center for Solvation Science ZEMOS, Ruhr-Universität Bochum, 44780 Bochum, Germany
| | - Dominik Marx
- Lehrstuhl für Theoretische Chemie, Ruhr-Universität Bochum, 44780 Bochum, Germany
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23
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Kapil V, Wilkins DM, Lan J, Ceriotti M. Inexpensive modeling of quantum dynamics using path integral generalized Langevin equation thermostats. J Chem Phys 2020; 152:124104. [PMID: 32241150 DOI: 10.1063/1.5141950] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
The properties of molecules and materials containing light nuclei are affected by their quantum mechanical nature. Accurate modeling of these quantum nuclear effects requires computationally demanding path integral techniques. Considerable success has been achieved in reducing the cost of such simulations by using generalized Langevin dynamics to induce frequency-dependent fluctuations. Path integral generalized Langevin equation methods, however, have this far been limited to the study of static, thermodynamic properties due to the large perturbation to the system's dynamics induced by the aggressive thermostatting. Here, we introduce a post-processing scheme, based on analytical estimates of the dynamical perturbation induced by the generalized Langevin dynamics, which makes it possible to recover meaningful time correlation properties from a thermostatted trajectory. We show that this approach yields spectroscopic observables for model and realistic systems that have an accuracy comparable to much more demanding approximate quantum dynamics techniques based on full path integral simulations.
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Affiliation(s)
- Venkat Kapil
- Laboratory of Computational Science and Modelling, Institute of Materials, Ecole Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - David M Wilkins
- Laboratory of Computational Science and Modelling, Institute of Materials, Ecole Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Jinggang Lan
- Department of Chemistry, University of Zürich, Zürich, Switzerland
| | - Michele Ceriotti
- Laboratory of Computational Science and Modelling, Institute of Materials, Ecole Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
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24
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Poltavsky I, Kapil V, Ceriotti M, Kim KS, Tkatchenko A. Accurate Description of Nuclear Quantum Effects with High-Order Perturbed Path Integrals (HOPPI). J Chem Theory Comput 2020; 16:1128-1135. [PMID: 31913625 DOI: 10.1021/acs.jctc.9b00881] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Imaginary time path-integral (PI) simulations that account for nuclear quantum effects (NQE) beyond the harmonic approximation are increasingly employed together with modern electronic-structure calculations. Existing PI methods are applicable to molecules, liquids, and solids; however, the computational cost of such simulations increases dramatically with decreasing temperature. To address this challenge, here, we propose to combine high-order PI factorization with perturbation theory (PT). Already for conventional second-order PI simulations, the PT ansatz increases the accuracy 2-fold compared to fourth-order schemes with the same settings. In turn, applying PT to high-order path integrals (HOPI) further improves the efficiency of simulations for molecular and condensed matter systems especially at low temperatures. We present results for bulk liquid water, the aspirin molecule, and the CH5+ molecule. Perturbed HOPI simulations remain both efficient and accurate down to 20 K and provide a convenient method to estimate the convergence of quantum-mechanical observables.
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Affiliation(s)
- Igor Poltavsky
- Physics and Materials Science Research Unit , University of Luxembourg , L-1511 Luxembourg City , Luxembourg
| | - Venkat Kapil
- Laboratory of Computational Science and Modelling, Institute of Materials , Ecole Polytechnique Fédérale de Lausanne , Lausanne , Switzerland
| | - Michele Ceriotti
- Laboratory of Computational Science and Modelling, Institute of Materials , Ecole Polytechnique Fédérale de Lausanne , Lausanne , Switzerland
| | - Kwang S Kim
- Department of Chemistry, School of Natural Science , Ulsan National Institute of Science and Technology , Ulsan 44919 , Korea
| | - Alexandre Tkatchenko
- Physics and Materials Science Research Unit , University of Luxembourg , L-1511 Luxembourg City , Luxembourg
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25
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Fang W, Thapa MJ, Richardson JO. Nonadiabatic quantum transition-state theory in the golden-rule limit. II. Overcoming the pitfalls of the saddle-point and semiclassical approximations. J Chem Phys 2019; 151:214101. [DOI: 10.1063/1.5131092] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Wei Fang
- Laboratory of Physical Chemistry, ETH Zurich, 8093 Zurich, Switzerland
| | - Manish J. Thapa
- Laboratory of Physical Chemistry, ETH Zurich, 8093 Zurich, Switzerland
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26
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Wieme J, Vandenbrande S, Lamaire A, Kapil V, Vanduyfhuys L, Van Speybroeck V. Thermal Engineering of Metal-Organic Frameworks for Adsorption Applications: A Molecular Simulation Perspective. ACS APPLIED MATERIALS & INTERFACES 2019; 11:38697-38707. [PMID: 31556593 PMCID: PMC6818952 DOI: 10.1021/acsami.9b12533] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/17/2019] [Accepted: 09/26/2019] [Indexed: 05/29/2023]
Abstract
Thermal engineering of metal-organic frameworks for adsorption-based applications is very topical in view of their industrial potential, in particular, since heat management and thermal stability have been identified as important obstacles. Hence, a fundamental understanding of the structural and chemical features underpinning their intrinsic thermal properties is highly sought-after. Herein, we investigate the nanoscale behavior of a diverse set of frameworks using molecular simulation techniques and critically compare properties such as thermal conductivity, heat capacity, and thermal expansion with other classes of materials. Furthermore, we propose a hypothetical thermodynamic cycle to estimate the temperature rise associated with adsorption for the most important greenhouse and energy-related gases (CO2 and CH4). This macroscopic response on the heat of adsorption connects the intrinsic thermal properties with the adsorption properties and allows us to evaluate their importance.
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Affiliation(s)
- Jelle Wieme
- Center for Molecular
Modeling, Ghent University, Tech Lane Ghent Science Park Campus
A, Technologiepark 46, 9052 Zwijnaarde, Belgium
| | - Steven Vandenbrande
- Center for Molecular
Modeling, Ghent University, Tech Lane Ghent Science Park Campus
A, Technologiepark 46, 9052 Zwijnaarde, Belgium
| | - Aran Lamaire
- Center for Molecular
Modeling, Ghent University, Tech Lane Ghent Science Park Campus
A, Technologiepark 46, 9052 Zwijnaarde, Belgium
| | - Venkat Kapil
- Laboratory
of Computational Science and Modelling, Institute of Materials, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Louis Vanduyfhuys
- Center for Molecular
Modeling, Ghent University, Tech Lane Ghent Science Park Campus
A, Technologiepark 46, 9052 Zwijnaarde, Belgium
| | - Veronique Van Speybroeck
- Center for Molecular
Modeling, Ghent University, Tech Lane Ghent Science Park Campus
A, Technologiepark 46, 9052 Zwijnaarde, Belgium
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27
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Kapil V, Engel E, Rossi M, Ceriotti M. Assessment of Approximate Methods for Anharmonic Free Energies. J Chem Theory Comput 2019; 15:5845-5857. [DOI: 10.1021/acs.jctc.9b00596] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Affiliation(s)
- Venkat Kapil
- Laboratory of Computational Science and Modeling, Institut des Matériaux, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Edgar Engel
- Laboratory of Computational Science and Modeling, Institut des Matériaux, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Mariana Rossi
- Fritz Haber Institute of the Max Planck Society, Faradayweg 4-6, 14195 Berlin, Germany
| | - Michele Ceriotti
- Laboratory of Computational Science and Modeling, Institut des Matériaux, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
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28
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Kapil V, Wieme J, Vandenbrande S, Lamaire A, Van Speybroeck V, Ceriotti M. Modeling the Structural and Thermal Properties of Loaded Metal–Organic Frameworks. An Interplay of Quantum and Anharmonic Fluctuations. J Chem Theory Comput 2019; 15:3237-3249. [DOI: 10.1021/acs.jctc.8b01297] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Venkat Kapil
- Laboratory of Computational Science and Modelling, Institute of Materials, Ecole Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
| | - Jelle Wieme
- Center for Molecular Modeling, Ghent University, Tech Lane Ghent Science Park Campus A, Technologiepark 46, 9052 Zwijnaarde, Belgium
| | - Steven Vandenbrande
- Center for Molecular Modeling, Ghent University, Tech Lane Ghent Science Park Campus A, Technologiepark 46, 9052 Zwijnaarde, Belgium
| | - Aran Lamaire
- Center for Molecular Modeling, Ghent University, Tech Lane Ghent Science Park Campus A, Technologiepark 46, 9052 Zwijnaarde, Belgium
| | - Veronique Van Speybroeck
- Center for Molecular Modeling, Ghent University, Tech Lane Ghent Science Park Campus A, Technologiepark 46, 9052 Zwijnaarde, Belgium
| | - Michele Ceriotti
- Laboratory of Computational Science and Modelling, Institute of Materials, Ecole Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
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29
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Lamaire A, Wieme J, Rogge SMJ, Waroquier M, Van Speybroeck V. On the importance of anharmonicities and nuclear quantum effects in modelling the structural properties and thermal expansion of MOF-5. J Chem Phys 2019; 150:094503. [DOI: 10.1063/1.5085649] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023] Open
Affiliation(s)
- Aran Lamaire
- Center for Molecular Modeling (CMM), Ghent University, Technologiepark 46, 9052 Zwijnaarde, Belgium
| | - Jelle Wieme
- Center for Molecular Modeling (CMM), Ghent University, Technologiepark 46, 9052 Zwijnaarde, Belgium
| | - Sven M. J. Rogge
- Center for Molecular Modeling (CMM), Ghent University, Technologiepark 46, 9052 Zwijnaarde, Belgium
| | - Michel Waroquier
- Center for Molecular Modeling (CMM), Ghent University, Technologiepark 46, 9052 Zwijnaarde, Belgium
| | - Veronique Van Speybroeck
- Center for Molecular Modeling (CMM), Ghent University, Technologiepark 46, 9052 Zwijnaarde, Belgium
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30
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Veit M, Jain SK, Bonakala S, Rudra I, Hohl D, Csányi G. Equation of State of Fluid Methane from First Principles with Machine Learning Potentials. J Chem Theory Comput 2019; 15:2574-2586. [DOI: 10.1021/acs.jctc.8b01242] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Affiliation(s)
- Max Veit
- Engineering Laboratory, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, United Kingdom
| | | | | | - Indranil Rudra
- Shell India Markets
Pvt. Ltd., Bengaluru 562149, Karnataka, India
| | - Detlef Hohl
- Shell Global Solutions
International BV, Grasweg 31, 1031 HW Amsterdam, The Netherlands
| | - Gábor Csányi
- Engineering Laboratory, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, United Kingdom
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31
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Hellström M, Ceriotti M, Behler J. Nuclear Quantum Effects in Sodium Hydroxide Solutions from Neural Network Molecular Dynamics Simulations. J Phys Chem B 2018; 122:10158-10171. [DOI: 10.1021/acs.jpcb.8b06433] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Affiliation(s)
- Matti Hellström
- Lehrstuhl für Theoretische Chemie, Ruhr-Universität Bochum, 44780 Bochum, Germany
- Universität Göttingen, Institut für Physikalische Chemie, Theoretische Chemie, Tammannstr. 6, 37077 Göttingen, Germany
| | - Michele Ceriotti
- Laboratory of Computational Science and Modeling, Institute of Materials, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Jörg Behler
- Lehrstuhl für Theoretische Chemie, Ruhr-Universität Bochum, 44780 Bochum, Germany
- Universität Göttingen, Institut für Physikalische Chemie, Theoretische Chemie, Tammannstr. 6, 37077 Göttingen, Germany
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32
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Schran C, Brieuc F, Marx D. Converged Colored Noise Path Integral Molecular Dynamics Study of the Zundel Cation Down to Ultralow Temperatures at Coupled Cluster Accuracy. J Chem Theory Comput 2018; 14:5068-5078. [PMID: 30217111 DOI: 10.1021/acs.jctc.8b00705] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
For a long time, performing converged path integral simulations at ultralow but finite temperatures of a few Kelvin has been a nearly impossible task. However, recent developments in advanced colored noise thermostatting schemes for path integral simulations, namely, the Path Integral Generalized Langevin Equation Thermostat (PIGLET) and the Path Integral Quantum Thermal Bath (PIQTB), have been able to greatly reduce the computational cost of these simulations, thus making the ultralow temperature regime accessible in practice. In this work, we investigate the influence of these two thermostatting schemes on the description of hydrogen-bonded systems at temperatures down to a few Kelvin as encountered, for example, in helium nanodroplet isolation or tagging photodissociation spectroscopy experiments. For this purpose, we analyze the prototypical hydrogen bond in the Zundel cation (H5O2+) as a function of both oxygen-oxygen distance and temperature in order to elucidate how the anisotropic quantum delocalization and, thus, the shape of the shared proton adapts depending on the donor-acceptor distance. The underlying electronic structure of the Zundel cation is described in terms of Behler's Neural Network Potentials of essentially converged Coupled Cluster accuracy, CCSD(T*)-F12a/AVTZ. In addition, the performances of the PIQTB and PIGLET methods for energetic, structural, and quantum delocalization properties are assessed and directly compared. Overall, our results emphasize the validity and practical usefulness of these two modern thermostatting approaches for path integral simulations of hydrogen-bonded systems even at ultralow temperatures.
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Affiliation(s)
- Christoph Schran
- Lehrstuhl für Theoretische Chemie , Ruhr-Universität Bochum , 44780 Bochum , Germany
| | - Fabien Brieuc
- Lehrstuhl für Theoretische Chemie , Ruhr-Universität Bochum , 44780 Bochum , Germany
| | - Dominik Marx
- Lehrstuhl für Theoretische Chemie , Ruhr-Universität Bochum , 44780 Bochum , Germany
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33
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Imbalzano G, Anelli A, Giofré D, Klees S, Behler J, Ceriotti M. Automatic selection of atomic fingerprints and reference configurations for machine-learning potentials. J Chem Phys 2018; 148:241730. [DOI: 10.1063/1.5024611] [Citation(s) in RCA: 163] [Impact Index Per Article: 27.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Affiliation(s)
- Giulio Imbalzano
- Laboratory of Computational Science and Modeling, IMX, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Andrea Anelli
- Laboratory of Computational Science and Modeling, IMX, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Daniele Giofré
- Laboratory of Computational Science and Modeling, IMX, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Sinja Klees
- Lehrstuhl für Theoretische Chemie, Ruhr-Universität Bochum, 44801 Bochum, Germany
| | - Jörg Behler
- Lehrstuhl für Theoretische Chemie, Ruhr-Universität Bochum, 44801 Bochum, Germany
- Universität Göttingen, Institut für Physikalische Chemie, Theoretische Chemie, Tammannstr. 6, 37077 Göttingen, Germany
| | - Michele Ceriotti
- Laboratory of Computational Science and Modeling, IMX, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
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Kapil V, Cuzzocrea A, Ceriotti M. Anisotropy of the Proton Momentum Distribution in Water. J Phys Chem B 2018; 122:6048-6054. [DOI: 10.1021/acs.jpcb.8b03896] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Affiliation(s)
- Venkat Kapil
- Laboratory of Computational Science and Modelling, Institute of Materials, Ecole Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Alice Cuzzocrea
- Laboratory of Computational Science and Modelling, Institute of Materials, Ecole Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Michele Ceriotti
- Laboratory of Computational Science and Modelling, Institute of Materials, Ecole Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
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Poltavsky I, DiStasio RA, Tkatchenko A. Perturbed path integrals in imaginary time: Efficiently modeling nuclear quantum effects in molecules and materials. J Chem Phys 2018; 148:102325. [DOI: 10.1063/1.5006596] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023] Open
Affiliation(s)
- Igor Poltavsky
- Physics and Materials Science Research Unit, University of Luxembourg, Luxembourg L-1511, Luxembourg
| | - Robert A. DiStasio
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, USA
| | - Alexandre Tkatchenko
- Physics and Materials Science Research Unit, University of Luxembourg, Luxembourg L-1511, Luxembourg
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Rossi M, Kapil V, Ceriotti M. Fine tuning classical and quantum molecular dynamics using a generalized Langevin equation. J Chem Phys 2018; 148:102301. [DOI: 10.1063/1.4990536] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Mariana Rossi
- Laboratory of Computational Science and Modelling, Institute of Materials, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Venkat Kapil
- Laboratory of Computational Science and Modelling, Institute of Materials, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Michele Ceriotti
- Laboratory of Computational Science and Modelling, Institute of Materials, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
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Schran C, Uhl F, Behler J, Marx D. High-dimensional neural network potentials for solvation: The case of protonated water clusters in helium. J Chem Phys 2018; 148:102310. [DOI: 10.1063/1.4996819] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Affiliation(s)
- Christoph Schran
- Lehrstuhl für Theoretische Chemie, Ruhr-Universität Bochum, 44780 Bochum, Germany
| | - Felix Uhl
- Lehrstuhl für Theoretische Chemie, Ruhr-Universität Bochum, 44780 Bochum, Germany
| | - Jörg Behler
- Lehrstuhl für Theoretische Chemie, Ruhr-Universität Bochum, 44780 Bochum, Germany
- Theoretische Chemie, Institut für Physikalische Chemie, Universität Göttingen, Tammannstr. 6, 37077 Göttingen, Germany
| | - Dominik Marx
- Lehrstuhl für Theoretische Chemie, Ruhr-Universität Bochum, 44780 Bochum, Germany
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Lindoy LP, Huang GS, Jordan MJT. Path integrals with higher order actions: Application to realistic chemical systems. J Chem Phys 2018; 148:074106. [PMID: 29471661 DOI: 10.1063/1.5000392] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Quantum thermodynamic parameters can be determined using path integral Monte Carlo (PIMC) simulations. These simulations, however, become computationally demanding as the quantum nature of the system increases, although their efficiency can be improved by using higher order approximations to the thermal density matrix, specifically the action. Here we compare the standard, primitive approximation to the action (PA) and three higher order approximations, the Takahashi-Imada action (TIA), the Suzuki-Chin action (SCA) and the Chin action (CA). The resulting PIMC methods are applied to two realistic potential energy surfaces, for H2O and HCN-HNC, both of which are spectroscopically accurate and contain three-body interactions. We further numerically optimise, for each potential, the SCA parameter and the two free parameters in the CA, obtaining more significant improvements in efficiency than seen previously in the literature. For both H2O and HCN-HNC, accounting for all required potential and force evaluations, the optimised CA formalism is approximately twice as efficient as the TIA formalism and approximately an order of magnitude more efficient than the PA. The optimised SCA formalism shows similar efficiency gains to the CA for HCN-HNC but has similar efficiency to the TIA for H2O at low temperature. In H2O and HCN-HNC systems, the optimal value of the a1 CA parameter is approximately 13, corresponding to an equal weighting of all force terms in the thermal density matrix, and similar to previous studies, the optimal α parameter in the SCA was ∼0.31. Importantly, poor choice of parameter significantly degrades the performance of the SCA and CA methods. In particular, for the CA, setting a1 = 0 is not efficient: the reduction in convergence efficiency is not offset by the lower number of force evaluations. We also find that the harmonic approximation to the CA parameters, whilst providing a fourth order approximation to the action, is not optimal for these realistic potentials: numerical optimisation leads to better approximate cancellation of the fifth order terms, with deviation between the harmonic and numerically optimised parameters more marked in the more quantum H2O system. This suggests that numerically optimising the CA or SCA parameters, which can be done at high temperature, will be important in fully realising the efficiency gains of these formalisms for realistic potentials.
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Affiliation(s)
- Lachlan P Lindoy
- School of Chemistry, The University of Sydney, Sydney, NSW 2006, Australia
| | - Gavin S Huang
- School of Chemistry, The University of Sydney, Sydney, NSW 2006, Australia
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Behler J. First Principles Neural Network Potentials for Reactive Simulations of Large Molecular and Condensed Systems. Angew Chem Int Ed Engl 2017; 56:12828-12840. [PMID: 28520235 DOI: 10.1002/anie.201703114] [Citation(s) in RCA: 329] [Impact Index Per Article: 47.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2017] [Indexed: 11/06/2022]
Abstract
Modern simulation techniques have reached a level of maturity which allows a wide range of problems in chemistry and materials science to be addressed. Unfortunately, the application of first principles methods with predictive power is still limited to rather small systems, and despite the rapid evolution of computer hardware no fundamental change in this situation can be expected. Consequently, the development of more efficient but equally reliable atomistic potentials to reach an atomic level understanding of complex systems has received considerable attention in recent years. A promising new development has been the introduction of machine learning (ML) methods to describe the atomic interactions. Once trained with electronic structure data, ML potentials can accelerate computer simulations by several orders of magnitude, while preserving quantum mechanical accuracy. This Review considers the methodology of an important class of ML potentials that employs artificial neural networks.
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Affiliation(s)
- Jörg Behler
- Universität Göttingen, Institut für Physikalische Chemie, Theoretische Chemie, Tammannstrasse 6, 37077, Göttingen, Germany
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Behler J. Hochdimensionale neuronale Netze für Potentialhyperflächen großer molekularer und kondensierter Systeme. Angew Chem Int Ed Engl 2017. [DOI: 10.1002/ange.201703114] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Jörg Behler
- Universität Göttingen; Institut für Physikalische Chemie, Theoretische Chemie; Tammannstraße 6 37077 Göttingen Deutschland
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Marsalek O, Markland TE. Quantum Dynamics and Spectroscopy of Ab Initio Liquid Water: The Interplay of Nuclear and Electronic Quantum Effects. J Phys Chem Lett 2017; 8:1545-1551. [PMID: 28296422 DOI: 10.1021/acs.jpclett.7b00391] [Citation(s) in RCA: 137] [Impact Index Per Article: 19.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Understanding the reactivity and spectroscopy of aqueous solutions at the atomistic level is crucial for the elucidation and design of chemical processes. However, the simulation of these systems requires addressing the formidable challenges of treating the quantum nature of both the electrons and nuclei. Exploiting our recently developed methods that provide acceleration by up to 2 orders of magnitude, we combine path integral simulations with on-the-fly evaluation of the electronic structure at the hybrid density functional theory level to capture the interplay between nuclear quantum effects and the electronic surface. Here we show that this combination provides accurate structure and dynamics, including the full infrared and Raman spectra of liquid water. This allows us to demonstrate and explain the failings of lower-level density functionals for dynamics and vibrational spectroscopy when the nuclei are treated quantum mechanically. These insights thus provide a foundation for the reliable investigation of spectroscopy and reactivity in aqueous environments.
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Affiliation(s)
- Ondrej Marsalek
- Department of Chemistry, Stanford University , Stanford, California 94305, United States
| | - Thomas E Markland
- Department of Chemistry, Stanford University , Stanford, California 94305, United States
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