1
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Sedano LF, Blazquez S, Vega C. Accuracy limit of non-polarizable four-point water models: TIP4P/2005 vs OPC. Should water models reproduce the experimental dielectric constant? J Chem Phys 2024; 161:044505. [PMID: 39046346 DOI: 10.1063/5.0211871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Accepted: 06/30/2024] [Indexed: 07/25/2024] Open
Abstract
The last generation of four center non-polarizable models of water can be divided into two groups: those reproducing the dielectric constant of water, as OPC, and those significantly underestimating its value, as TIP4P/2005. To evaluate the global performance of OPC and TIP4P/2005, we shall follow the test proposed by Vega and Abascal in 2011 evaluating about 40 properties to fairly address this comparison. The liquid-vapor and liquid-solid equilibria are computed, as well as the heat capacities, isothermal compressibilities, surface tensions, densities of different ice polymorphs, the density maximum, equations of state at high pressures, and transport properties. General aspects of the phase diagram are considered by comparing the ratios of different temperatures (namely, the temperature of maximum density, the melting temperature of hexagonal ice, and the critical temperature). The final scores are 7.2 for TIP4P/2005 and 6.3 for OPC. The results of this work strongly suggest that we have reached the limit of what can be achieved with non-polarizable models of water and that the attempt to reproduce the experimental dielectric constant deteriorates the global performance of the water force field. The reason is that the dielectric constant depends on two surfaces (potential energy and dipole moment surfaces), whereas in the absence of an electric field, all properties can be determined simply from just one surface (the potential energy surface). The consequences of the choice of the water model in the modeling of electrolytes in water are also discussed.
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Affiliation(s)
- L F Sedano
- Departamento de Química Física, Facultad de Ciencias Químicas, Universidad Complutense de Madrid, 28040 Madrid, Spain
| | - S Blazquez
- Departamento de Química Física, Facultad de Ciencias Químicas, Universidad Complutense de Madrid, 28040 Madrid, Spain
| | - C Vega
- Departamento de Química Física, Facultad de Ciencias Químicas, Universidad Complutense de Madrid, 28040 Madrid, Spain
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2
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Fisher KE, Herbst MF, Marzouk YM. Multitask methods for predicting molecular properties from heterogeneous data. J Chem Phys 2024; 161:014114. [PMID: 38958501 DOI: 10.1063/5.0201681] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Accepted: 06/12/2024] [Indexed: 07/04/2024] Open
Abstract
Data generation remains a bottleneck in training surrogate models to predict molecular properties. We demonstrate that multitask Gaussian process regression overcomes this limitation by leveraging both expensive and cheap data sources. In particular, we consider training sets constructed from coupled-cluster (CC) and density functional theory (DFT) data. We report that multitask surrogates can predict at CC-level accuracy with a reduction in data generation cost by over an order of magnitude. Of note, our approach allows the training set to include DFT data generated by a heterogeneous mix of exchange-correlation functionals without imposing any artificial hierarchy on functional accuracy. More generally, the multitask framework can accommodate a wider range of training set structures-including the full disparity between the different levels of fidelity-than existing kernel approaches based on Δ-learning although we show that the accuracy of the two approaches can be similar. Consequently, multitask regression can be a tool for reducing data generation costs even further by opportunistically exploiting existing data sources.
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Affiliation(s)
- K E Fisher
- Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - M F Herbst
- Mathematics for Materials Modelling, Institute of Mathematics and Institute of Materials, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
- National Centre for Computational Design and Discovery of Novel Materials (MARVEL), École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Y M Marzouk
- Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
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3
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Sami S, LaCour RA, Heindel JP, Head-Gordon T. Simple and Accurate One-Body Energy and Dipole Moment Surfaces for Water and Beyond. J Phys Chem Lett 2024; 15:6712-6721. [PMID: 38900596 PMCID: PMC11229074 DOI: 10.1021/acs.jpclett.4c00587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Revised: 06/07/2024] [Accepted: 06/13/2024] [Indexed: 06/22/2024]
Abstract
Water is often the testing ground for new, advanced force fields. While advanced functional forms for intermolecular interactions have been integral to the development of accurate water models, less attention has been paid to a transferable model for intramolecular valence terms. In this work, we present a one-body energy and dipole moment surface model, named 1B-UCB, that is simple yet accurate and can be feasibly adapted for both standard and advanced potentials. 1B-UCB for water is comparable in accuracy to those with much more complex functional forms, despite having drastically fewer parameters. The parametrization protocol has been implemented as part of the Q-Force automated workflow and requires only a quantum mechanical Hessian calculation as reference data, hence allowing it to be easily extended to a variety of molecular systems beyond water, which we demonstrate on a selection of small molecules with different symmetries.
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Affiliation(s)
- Selim Sami
- Kenneth
S. Pitzer Theory Center and Department of Chemistry, University of California, Berkeley, Berkeley, California 94720, United States
| | - R. Allen LaCour
- Kenneth
S. Pitzer Theory Center and Department of Chemistry, University of California, Berkeley, Berkeley, California 94720, United States
- Chemical
Sciences Division, Lawrence Berkeley National
Laboratory, Berkeley, California 94720, United States
| | - Joseph P. Heindel
- Kenneth
S. Pitzer Theory Center and Department of Chemistry, University of California, Berkeley, Berkeley, California 94720, United States
- Chemical
Sciences Division, Lawrence Berkeley National
Laboratory, Berkeley, California 94720, United States
| | - Teresa Head-Gordon
- Kenneth
S. Pitzer Theory Center and Department of Chemistry, University of California, Berkeley, Berkeley, California 94720, United States
- Chemical
Sciences Division, Lawrence Berkeley National
Laboratory, Berkeley, California 94720, United States
- Departments
of Bioengineering and Chemical and Biomolecular Engineering, University of California, Berkeley, Berkeley, California 94720, United States
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4
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Althorpe SC. Path Integral Simulations of Condensed-Phase Vibrational Spectroscopy. Annu Rev Phys Chem 2024; 75:397-420. [PMID: 38941531 DOI: 10.1146/annurev-physchem-090722-124705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/30/2024]
Abstract
Recent theoretical and algorithmic developments have improved the accuracy with which path integral dynamics methods can include nuclear quantum effects in simulations of condensed-phase vibrational spectra. Such methods are now understood to be approximations to the delocalized classical Matsubara dynamics of smooth Feynman paths, which dominate the dynamics of systems such as liquid water at room temperature. Focusing mainly on simulations of liquid water and hexagonal ice, we explain how the recently developed quasicentroid molecular dynamics (QCMD), fast-QCMD, and temperature-elevated path integral coarse-graining simulations (Te PIGS) methods generate classical dynamics on potentials of mean force obtained by averaging over quantum thermal fluctuations. These new methods give very close agreement with one another, and the Te PIGS method has recently yielded excellent agreement with experimentally measured vibrational spectra for liquid water, ice, and the liquid-air interface. We also discuss the limitations of such methods.
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Affiliation(s)
- Stuart C Althorpe
- Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, United Kingdom;
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5
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Hartke B. On the brink of self-hydration: the water heptadecamer. Phys Chem Chem Phys 2024; 26:15445-15451. [PMID: 38747364 DOI: 10.1039/d4cp00816b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/30/2024]
Abstract
For pure, neutral, isolated molecular clusters, (H2O)17 marks the transition from structures with all water molecules on the cluster surface to water self-hydration, i.e., cluster structures around one central water molecule. Getting this right with water model potentials turns out to be challenging. Even the best water potentials currently available, which reproduce collective properties very well, still deliver contradicting results for (H2O)17, when different low-energy isomers from global structure optimizations are examined. Interestingly, ab initio quantum chemistry also struggles with the only seemingly simple question if (H2O)17 is all-surface or water-centered. Hence, although the long history of water potential development may be entering its final phase, it is not quite finished yet.
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Affiliation(s)
- Bernd Hartke
- Institute for Physical Chemistry, Kiel University, 24118 Kiel, Germany.
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6
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Yu Q, Bowman JM. Fully Quantum Simulation of Polaritonic Vibrational Spectra of Large Cavity-Molecule System. J Chem Theory Comput 2024; 20:4278-4287. [PMID: 38717309 DOI: 10.1021/acs.jctc.4c00129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
The formation of molecular vibrational polaritons, arising from the interplay between molecular vibrations and infrared cavity modes, is a quantum phenomenon necessitating accurate quantum dynamical simulations. Here, we introduce the cavity vibrational self-consistent field/virtual state configuration interaction method, enabling quantum simulation of the vibrational spectra of many-molecule systems within the optical cavity. Focusing on the representative (H2O)21 system, we showcase this parameter-free quantum approach's ability to capture both linear and nonlinear vibrational spectral features. Our findings highlight the growing prominence of molecular couplings among OH stretches and bending excited bands with increased light-matter interaction, revealing distinctive nonlinear spectral features induced by vibrational strong coupling.
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Affiliation(s)
- Qi Yu
- Department of Chemistry, Fudan University, Shanghai 200438, P. R. China
| | - Joel M Bowman
- Department of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, United States
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7
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Houston PL, Qu C, Yu Q, Pandey P, Conte R, Nandi A, Bowman JM. No Headache for PIPs: A PIP Potential for Aspirin Runs Much Faster and with Similar Precision Than Other Machine-Learned Potentials. J Chem Theory Comput 2024; 20:3008-3018. [PMID: 38593438 DOI: 10.1021/acs.jctc.4c00054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/11/2024]
Abstract
Assessments of machine-learning (ML) potentials are an important aspect of the rapid development of this field. We recently reported an assessment of the linear-regression permutationally invariant polynomial (PIP) method for ethanol, using the widely used (revised) rMD17 data set. We demonstrated that the PIP approach outperformed numerous other methods, e.g., ANI, PhysNet, sGDML, and p-KRR, with respect to precision and notably with respect to speed [Houston et al., J. Chem. Phys. 2022, 156, 044120]. Here, we extend this assessment to the 21-atom aspirin molecule, using the rMD17 data set, with a focus on the speed of evaluation. Both energies and forces are used for training, and the precision of several PIPs is examined for both. Normal mode frequencies, the methyl torsional potential, and 1d vibrational energies for an OH stretch are presented. We show that the PIP approach achieves the level of precision obtained from other ML methods, e.g., atom-centered neural network methods, linear regression ACE, and kernel methods, as reported by Kovács et al. in J. Chem. Theory Comput. 2021, 17, 7696-7711. More significantly, we show that the PIP PESs run much faster than all other ML methods, whose timings were evaluated in that paper. We also show that the PIP PES extrapolates well enough to describe several internal motions of aspirin, including an OH stretch.
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Affiliation(s)
- Paul L Houston
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, United States
- Department of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Chen Qu
- Independent Researcher, Toronto, Ontario M9B0E3, Canada
| | - Qi Yu
- Department of Chemistry, Fudan University, Shanghai 200438, P. R. China
| | - Priyanka Pandey
- Department of Chemistry, Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, United States
| | - Riccardo Conte
- Dipartimento di Chimica, Università degli Studi di Milano, via Golgi 19, 20133 Milano, Italy
| | - Apurba Nandi
- Department of Chemistry, Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, United States
- Department of Physics and Materials Science, University of Luxembourg, Luxembourg City L-1511, Luxembourg
| | - Joel M Bowman
- Department of Chemistry, Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, United States
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8
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Lambros E, Fetherolf JH, Hammes-Schiffer S, Li X. A Many-Body Perspective of Nuclear Quantum Effects in Aqueous Clusters. J Phys Chem Lett 2024; 15:4070-4075. [PMID: 38587257 DOI: 10.1021/acs.jpclett.4c00439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Nuclear quantum effects play an important role in the structure and thermodynamics of aqueous systems. By performing a many-body expansion with nuclear-electronic orbital (NEO) theory, we show that proton quantization can give rise to significant energetic contributions for many-body interactions spanning several molecules in single-point energy calculations of water clusters. Although zero-point motion produces a large increase in energy at the one-body level, nuclear quantum effects serve to stabilize higher-order molecular interactions. These results are significant because they demonstrate that nuclear quantum effects play a nontrivial role in many-body interactions of aqueous systems. Our approach also provides a pathway for incorporating nuclear quantum effects into water potential energy surfaces. The NEO approach is advantageous for many-body expansion analyses because it includes nuclear quantum effects directly in the energies.
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Affiliation(s)
- Eleftherios Lambros
- Department of Chemistry, University of Washington, Seattle, Washington 98195, United States
| | - Jonathan H Fetherolf
- Department of Chemistry, Princeton University, Princeton, New Jersey 08544, United States
| | - Sharon Hammes-Schiffer
- Department of Chemistry, Princeton University, Princeton, New Jersey 08544, United States
| | - Xiaosong Li
- Department of Chemistry, University of Washington, Seattle, Washington 98195, United States
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9
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Moscato D, Mandelli G, Bondanza M, Lipparini F, Conte R, Mennucci B, Ceotto M. Unraveling Water Solvation Effects with Quantum Mechanics/Molecular Mechanics Semiclassical Vibrational Spectroscopy: The Case of Thymidine. J Am Chem Soc 2024; 146:8179-8188. [PMID: 38470354 DOI: 10.1021/jacs.3c12700] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/13/2024]
Abstract
We introduce a quantum mechanics/molecular mechanics semiclassical method for studying the solvation process of molecules in water at the nuclear quantum mechanical level with atomistic detail. We employ it in vibrational spectroscopy calculations because this is a tool that is very sensitive to the molecular environment. Specifically, we look at the vibrational spectroscopy of thymidine in liquid water. We find that the C═O frequency red shift and the C═C frequency blue shift, experienced by thymidyne upon solvation, are mainly due to reciprocal polarization effects, that the molecule and the water solvent exert on each other, and nuclear zero-point energy effects. In general, this work provides an accurate and practical tool to study quantum vibrational spectroscopy in solution and condensed phase, incorporating high-level and computationally affordable descriptions of both electronic and nuclear problems.
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Affiliation(s)
- Davide Moscato
- Dipartimento di Chimica, Università degli Studi di Milano, Via Golgi, 19, 20133 Milano, Italy
| | - Giacomo Mandelli
- Dipartimento di Chimica, Università degli Studi di Milano, Via Golgi, 19, 20133 Milano, Italy
| | - Mattia Bondanza
- Dipartimento di Chimica e Chimica Industriale, Università di Pisa, Via Giuseppe Moruzzi, 13, 56124 Pisa, Italy
| | - Filippo Lipparini
- Dipartimento di Chimica e Chimica Industriale, Università di Pisa, Via Giuseppe Moruzzi, 13, 56124 Pisa, Italy
| | - Riccardo Conte
- Dipartimento di Chimica, Università degli Studi di Milano, Via Golgi, 19, 20133 Milano, Italy
| | - Benedetta Mennucci
- Dipartimento di Chimica e Chimica Industriale, Università di Pisa, Via Giuseppe Moruzzi, 13, 56124 Pisa, Italy
| | - Michele Ceotto
- Dipartimento di Chimica, Università degli Studi di Milano, Via Golgi, 19, 20133 Milano, Italy
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10
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Lüttschwager NOB. The strength of the OH-bend/OH-stretch Fermi resonance in small water clusters. Phys Chem Chem Phys 2024; 26:10120-10135. [PMID: 38487881 DOI: 10.1039/d3cp06255d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/28/2024]
Abstract
A novel Raman jet-spectrometer is used to study the Fermi resonance between the OH bending overtone and OH stretching fundamental in small cyclic water clusters (H2O)n with n = 3, 4, 5. The new setup features a recirculating vacuum system which reduces the gas consumption by 2 to 3 orders of magnitude and enables long-term measurements of very weak Raman signals. Raman spectra measured from highly diluted expansions with unprecedented signal-to-noise ratio are presented and cluster-specific intensity ratios and effective coupling constants are derived using Markov-Chain Monte-Carlo methods, yielding a high probability for an almost "perfect" resonance for the tetramer and pentamer, i.e. a close frequency match of bend overtone and stretch fundamental with intensity ratios close to 1, but a larger coupling constant for the trimer, with best estimates close to W5 ≲ 50 cm-1 < W4 ≲ 60 cm-1 < W3 ≈ 65 cm-1.
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Affiliation(s)
- Nils O B Lüttschwager
- Georg-August-Universität Göttingen, Institut für Physikalische Chemie, Tammannstraße 6, 37077 Göttingen, Germany.
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11
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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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12
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Kurnikov IV, Pereyaslavets L, Kamath G, Sakipov SN, Voronina E, Butin O, Illarionov A, Leontyev I, Nawrocki G, Darkhovskiy M, Olevanov M, Ivahnenko I, Chen Y, Lock CB, Levitt M, Kornberg RD, Fain B. Neural Network Corrections to Intermolecular Interaction Terms of a Molecular Force Field Capture Nuclear Quantum Effects in Calculations of Liquid Thermodynamic Properties. J Chem Theory Comput 2024; 20:1347-1357. [PMID: 38240485 PMCID: PMC11042917 DOI: 10.1021/acs.jctc.3c00921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
We incorporate nuclear quantum effects (NQE) in condensed matter simulations by introducing short-range neural network (NN) corrections to the ab initio fitted molecular force field ARROW. Force field NN corrections are fitted to average interaction energies and forces of molecular dimers, which are simulated using the Path Integral Molecular Dynamics (PIMD) technique with restrained centroid positions. The NN-corrected force field allows reproduction of the NQE for computed liquid water and methane properties such as density, radial distribution function (RDF), heat of evaporation (HVAP), and solvation free energy. Accounting for NQE through molecular force field corrections circumvents the need for explicit computationally expensive PIMD simulations in accurate calculations of the properties of chemical and biological systems. The accuracy and locality of pairwise NN NQE corrections indicate that this approach could be applicable to complex heterogeneous systems, such as proteins.
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Affiliation(s)
- Igor V Kurnikov
- InterX Inc., (a Subsidiary of NeoTX Therapeutics Ltd.), 805 Allston Way, Berkeley, California 94710, United States
| | - Leonid Pereyaslavets
- InterX Inc., (a Subsidiary of NeoTX Therapeutics Ltd.), 805 Allston Way, Berkeley, California 94710, United States
| | - Ganesh Kamath
- InterX Inc., (a Subsidiary of NeoTX Therapeutics Ltd.), 805 Allston Way, Berkeley, California 94710, United States
| | - Serzhan N Sakipov
- InterX Inc., (a Subsidiary of NeoTX Therapeutics Ltd.), 805 Allston Way, Berkeley, California 94710, United States
| | - Ekaterina Voronina
- InterX Inc., (a Subsidiary of NeoTX Therapeutics Ltd.), 805 Allston Way, Berkeley, California 94710, United States
| | - Oleg Butin
- InterX Inc., (a Subsidiary of NeoTX Therapeutics Ltd.), 805 Allston Way, Berkeley, California 94710, United States
| | - Alexey Illarionov
- InterX Inc., (a Subsidiary of NeoTX Therapeutics Ltd.), 805 Allston Way, Berkeley, California 94710, United States
| | - Igor Leontyev
- InterX Inc., (a Subsidiary of NeoTX Therapeutics Ltd.), 805 Allston Way, Berkeley, California 94710, United States
| | - Grzegorz Nawrocki
- InterX Inc., (a Subsidiary of NeoTX Therapeutics Ltd.), 805 Allston Way, Berkeley, California 94710, United States
| | - Mikhail Darkhovskiy
- InterX Inc., (a Subsidiary of NeoTX Therapeutics Ltd.), 805 Allston Way, Berkeley, California 94710, United States
| | - Michael Olevanov
- InterX Inc., (a Subsidiary of NeoTX Therapeutics Ltd.), 805 Allston Way, Berkeley, California 94710, United States
| | - Ilya Ivahnenko
- InterX Inc., (a Subsidiary of NeoTX Therapeutics Ltd.), 805 Allston Way, Berkeley, California 94710, United States
| | - YuChun Chen
- InterX Inc., (a Subsidiary of NeoTX Therapeutics Ltd.), 805 Allston Way, Berkeley, California 94710, United States
| | - Christopher B Lock
- InterX Inc., (a Subsidiary of NeoTX Therapeutics Ltd.), 805 Allston Way, Berkeley, California 94710, United States
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Palo Alto, California 94304, United States
| | - Michael Levitt
- Department of Structural Biology, Stanford University School of Medicine, Stanford, California 94305, United States
| | - Roger D Kornberg
- Department of Structural Biology, Stanford University School of Medicine, Stanford, California 94305, United States
| | - Boris Fain
- InterX Inc., (a Subsidiary of NeoTX Therapeutics Ltd.), 805 Allston Way, Berkeley, California 94710, United States
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13
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Pandey P, Qu C, Nandi A, Yu Q, Houston PL, Conte R, Bowman JM. Ab Initio Potential Energy Surface for NaCl-H 2 with Correct Long-Range Behavior. J Phys Chem A 2024; 128:902-908. [PMID: 38271992 PMCID: PMC10860134 DOI: 10.1021/acs.jpca.3c07687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 12/26/2023] [Accepted: 01/04/2024] [Indexed: 01/27/2024]
Abstract
We report a full dimensional ab initio potential energy surface for NaCl-H2 based on precise fitting of a large data set of CCSD(T)/aug-cc-pVTZ energies. A major goal of this fit is to describe the very long-range interaction accurately. This is done in this instance via the dipole-quadrupole interaction. The NaCl dipole and the H2 quadrupole are available through previous works over a large range of internuclear distances. We use these to obtain exact effect charges on each atom. Diffusion Monte Carlo calculations are done for the ground vibrational state using the new potential.
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Affiliation(s)
- Priyanka Pandey
- Department
of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia, 30322, United States
| | - Chen Qu
- Independent
Researcher, Toronto ON M9B 0E3, Canada
| | - Apurba Nandi
- Department
of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia, 30322, United States
- Department
of Physics and Materials Science, University of Luxembourg, Luxembourg City L-1511, Luxembourg
| | - Qi Yu
- Department
of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia, 30322, United States
| | - Paul L. Houston
- Department
of Chemistry and Chemical Biology, Cornell
University, Ithaca, New York 14853, United States
- Department
of Chemistry and Biochemistry, Georgia Institute
of Technology, Atlanta, Georgia 30332, United States
| | - Riccardo Conte
- Dipartimento
di Chimica, Università Degli Studi
di Milano, Via Golgi 19, Milano 20133, Italy
| | - Joel M. Bowman
- Department
of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia, 30322, United States
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14
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Santis GD, Herman KM, Heindel JP, Xantheas SS. Descriptors of water aggregation. J Chem Phys 2024; 160:054306. [PMID: 38341703 DOI: 10.1063/5.0179815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 01/05/2024] [Indexed: 02/13/2024] Open
Abstract
We rely on a total of 23 (cluster size, 8 structural, and 14 connectivity) descriptors to investigate structural patterns and connectivity motifs associated with water cluster aggregation. In addition to the cluster size n (number of molecules), the 8 structural descriptors can be further categorized into (i) one-body (intramolecular): covalent OH bond length (rOH) and HOH bond angle (θHOH), (ii) two-body: OO distance (rOO), OHO angle (θOHO), and HOOX dihedral angle (ϕHOOX), where X lies on the bisector of the HOH angle, (iii) three-body: OOO angle (θOOO), and (iv) many-body: modified tetrahedral order parameter (q) to account for two-, three-, four-, five-coordinated molecules (qm, m = 2, 3, 4, 5) and radius of gyration (Rg). The 14 connectivity descriptors are all many-body in nature and consist of the AD, AAD, ADD, AADD, AAAD, AAADD adjacencies [number of hydrogen bonds accepted (A) and donated (D) by each water molecule], Wiener index, Average Shortest Path Length, hydrogen bond saturation (% HB), and number of non-short-circuited three-membered cycles, four-membered cycles, five-membered cycles, six-membered cycles, and seven-membered cycles. We mined a previously reported database of 4 948 959 water cluster minima for (H2O)n, n = 3-25 to analyze the evolution and correlation of these descriptors for the clusters within 5 kcal/mol of the putative minima. It was found that rOH and % HB correlated strongly with cluster size n, which was identified as the strongest predictor of energetic stability. Marked changes in the adjacencies and cycle count were observed, lending insight into changes in the hydrogen bond network upon aggregation. A Principal Component Analysis (PCA) was employed to identify descriptor dependencies and group clusters into specific structural patterns across different cluster sizes. The results of this study inform our understanding of how water clusters evolve in size and what appropriate descriptors of their structural and connectivity patterns are with respect to system size, stability, and similarity. The approach described in this study is general and can be easily extended to other hydrogen-bonded systems.
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Affiliation(s)
- Garrett D Santis
- Department of Chemistry, University of Washington, Seattle, Washington 98195, USA
| | - Kristina M Herman
- Department of Chemistry, University of Washington, Seattle, Washington 98195, USA
| | - Joseph P Heindel
- Department of Chemistry, University of Washington, Seattle, Washington 98195, USA
| | - Sotiris S Xantheas
- Department of Chemistry, University of Washington, Seattle, Washington 98195, USA
- Advanced Computing, Mathematics and Data Division, Pacific Northwest National Laboratory, 902 Battelle Boulevard, P.O. Box 999, MSIN J7-10, Richland, Washington 99352, USA
- Computational and Theoretical Chemistry Institute (CTCI), Pacific Northwest National Laboratory, Richland, Washington 99352, USA
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15
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Kapil V, Kovács DP, Csányi G, Michaelides A. First-principles spectroscopy of aqueous interfaces using machine-learned electronic and quantum nuclear effects. Faraday Discuss 2024; 249:50-68. [PMID: 37799072 PMCID: PMC10845015 DOI: 10.1039/d3fd00113j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 07/18/2023] [Indexed: 10/07/2023]
Abstract
Vibrational spectroscopy is a powerful approach to visualising interfacial phenomena. However, extracting structural and dynamical information from vibrational spectra is a challenge that requires first-principles simulations, including non-Condon and quantum nuclear effects. We address this challenge by developing a machine-learning enhanced first-principles framework to speed up predictive modelling of infrared, Raman, and sum-frequency generation spectra. Our approach uses machine learning potentials that encode quantum nuclear effects to generate quantum trajectories using simple molecular dynamics efficiently. In addition, we reformulate bulk and interfacial selection rules to express them unambiguously in terms of the derivatives of polarisation and polarisabilities of the whole system and predict these derivatives efficiently using fully-differentiable machine learning models of dielectric response tensors. We demonstrate our framework's performance by predicting the IR, Raman, and sum-frequency generation spectra of liquid water, ice and the water-air interface by achieving near quantitative agreement with experiments at nearly the same computational efficiency as pure classical methods. Finally, to aid the experimental discovery of new phases of nanoconfined water, we predict the temperature-dependent vibrational spectra of monolayer water across the solid-hexatic-liquid phases transition.
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Affiliation(s)
- Venkat Kapil
- Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, UK.
| | | | - Gábor Csányi
- Engineering Laboratory, University of Cambridge, Cambridge, CB2 1PZ, UK
| | - Angelos Michaelides
- Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, UK.
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16
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Vogt E, Simkó I, Császár AG, Kjaergaard HG. Quantum Chemical Investigation of the Cold Water Dimer Spectrum in the First OH-Stretching Overtone Region Provides a New Interpretation. J Phys Chem A 2023; 127:9409-9418. [PMID: 37930939 DOI: 10.1021/acs.jpca.3c03705] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2023]
Abstract
Intramolecular vibrational transition wavenumbers and intensities were calculated in the fundamental HOH-bending, fundamental OH-stretching, first OH-stretching-HOH-bending combination, and first OH-stretching overtone (ΔvOH = 2) regions of the water dimer's spectrum. Furthermore, the rotational-vibrational spectrum was calculated in the ΔvOH = 2 region at 10 K, corresponding to the temperature of the existing jet-expansion experiments. The calculated spectrum was obtained by combining results from a full-dimensional (12D) vibrational and a reduced-dimensional vibrational-rotational-tunneling model. The ΔvOH = 2 spectral region is rich in features due to contributions from multiple vibrational-rotational-tunneling sub-bands. Origins of the experimental vibrational bands depend on the assignment of the observed sub-bands. Based on our calculations, we assign the observed sub-bands, and our reassignment leads to new values for the vibrational band origins of the free donor and antisymmetric acceptor OH-stretching first overtones of ∼7227 and ∼7238 cm-1, respectively. The observed bands with origins at 7192.34 and ∼7366 cm-1 are assigned to the symmetric acceptor OH-stretching first overtone and the OH-stretching combination of the donor, respectively.
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Affiliation(s)
- Emil Vogt
- Department of Chemistry, University of Copenhagen, Universitetsparken 5, Copenhagen Ø DK-2100, Denmark
| | - Irén Simkó
- Laboratory of Molecular Structure and Dynamics, Institute of Chemistry ELTE Eötvös Loránd University, Pázmány Péter Sétány 1/A, Budapest H-1117, Hungary
- HUN-REN-ELTE Complex Chemical Systems Research Group, P.O. Box 32, Budapest 112 H-1518, Hungary
| | - Attila G Császár
- Laboratory of Molecular Structure and Dynamics, Institute of Chemistry ELTE Eötvös Loránd University, Pázmány Péter Sétány 1/A, Budapest H-1117, Hungary
- HUN-REN-ELTE Complex Chemical Systems Research Group, P.O. Box 32, Budapest 112 H-1518, Hungary
| | - Henrik G Kjaergaard
- Department of Chemistry, University of Copenhagen, Universitetsparken 5, Copenhagen Ø DK-2100, Denmark
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17
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Plé T, Lagardère L, Piquemal JP. Force-field-enhanced neural network interactions: from local equivariant embedding to atom-in-molecule properties and long-range effects. Chem Sci 2023; 14:12554-12569. [PMID: 38020379 PMCID: PMC10646944 DOI: 10.1039/d3sc02581k] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 10/03/2023] [Indexed: 12/01/2023] Open
Abstract
We introduce FENNIX (Force-Field-Enhanced Neural Network InteraXions), a hybrid approach between machine-learning and force-fields. We leverage state-of-the-art equivariant neural networks to predict local energy contributions and multiple atom-in-molecule properties that are then used as geometry-dependent parameters for physically-motivated energy terms which account for long-range electrostatics and dispersion. Using high-accuracy ab initio data (small organic molecules/dimers), we trained a first version of the model. Exhibiting accurate gas-phase energy predictions, FENNIX is transferable to the condensed phase. It is able to produce stable Molecular Dynamics simulations, including nuclear quantum effects, for water predicting accurate liquid properties. The extrapolating power of the hybrid physically-driven machine learning FENNIX approach is exemplified by computing: (i) the solvated alanine dipeptide free energy landscape; (ii) the reactive dissociation of small molecules.
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Affiliation(s)
- Thomas Plé
- Sorbonne Université, LCT, UMR 7616 CNRS F-75005 Paris France thomas.ple@sorbonne-université louis.lagardere@sorbonne-université jean-philip.piquemal@sorbonne-université
| | - Louis Lagardère
- Sorbonne Université, LCT, UMR 7616 CNRS F-75005 Paris France thomas.ple@sorbonne-université louis.lagardere@sorbonne-université jean-philip.piquemal@sorbonne-université
| | - Jean-Philip Piquemal
- Sorbonne Université, LCT, UMR 7616 CNRS F-75005 Paris France thomas.ple@sorbonne-université louis.lagardere@sorbonne-université jean-philip.piquemal@sorbonne-université
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18
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Broderick DR, Herbert JM. Scalable generalized screening for high-order terms in the many-body expansion: Algorithm, open-source implementation, and demonstration. J Chem Phys 2023; 159:174801. [PMID: 37921253 DOI: 10.1063/5.0174293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Accepted: 10/16/2023] [Indexed: 11/04/2023] Open
Abstract
The many-body expansion lies at the heart of numerous fragment-based methods that are intended to sidestep the nonlinear scaling of ab initio quantum chemistry, making electronic structure calculations feasible in large systems. In principle, inclusion of higher-order n-body terms ought to improve the accuracy in a controllable way, but unfavorable combinatorics often defeats this in practice and applications with n ≥ 4 are rare. Here, we outline an algorithm to overcome this combinatorial bottleneck, based on a bottom-up approach to energy-based screening. This is implemented within a new open-source software application ("Fragme∩t"), which is integrated with a lightweight semi-empirical method that is used to cull subsystems, attenuating the combinatorial growth of higher-order terms in the graph that is used to manage the calculations. This facilitates applications of unprecedented size, and we report four-body calculations in (H2O)64 clusters that afford relative energies within 0.1 kcal/mol/monomer of the supersystem result using less than 10% of the unique subsystems. We also report n-body calculations in (H2O)20 clusters up to n = 8, at which point the expansion terminates naturally due to screening. These are the largest n-body calculations reported to date using ab initio electronic structure theory, and they confirm that high-order n-body terms are mostly artifacts of basis-set superposition error.
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Affiliation(s)
- Dustin R Broderick
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - John M Herbert
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
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19
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Mouhat F, Peria M, Morresi T, Vuilleumier R, Saitta AM, Casula M. Thermal dependence of the hydrated proton and optimal proton transfer in the protonated water hexamer. Nat Commun 2023; 14:6930. [PMID: 37903819 PMCID: PMC10616126 DOI: 10.1038/s41467-023-42366-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 09/25/2023] [Indexed: 11/01/2023] Open
Abstract
Water is a key ingredient for life and plays a central role as solvent in many biochemical reactions. However, the intrinsically quantum nature of the hydrogen nucleus, revealing itself in a large variety of physical manifestations, including proton transfer, gives rise to unexpected phenomena whose description is still elusive. Here we study, by a combination of state-of-the-art quantum Monte Carlo methods and path-integral molecular dynamics, the structure and hydrogen-bond dynamics of the protonated water hexamer, the fundamental unit for the hydrated proton. We report a remarkably low thermal expansion of the hydrogen bond from zero temperature up to 300 K, owing to the presence of short-Zundel configurations, characterised by proton delocalisation and favoured by the synergy of nuclear quantum effects and thermal activation. The hydrogen bond strength progressively weakens above 300 K, when localised Eigen-like configurations become relevant. Our analysis, supported by the instanton statistics of shuttling protons, reveals that the near-room-temperature range from 250 K to 300 K is optimal for proton transfer in the protonated water hexamer.
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Affiliation(s)
- Félix Mouhat
- Saint Gobain Research Paris, 39, Quai Lucien Lefranc, 93300, Aubervilliers, France
| | - Matteo Peria
- IMPMC, Sorbonne Université, CNRS, MNHN, UMR 7590, 4 Place Jussieu, 75252, Paris, France
| | - Tommaso Morresi
- ECT*-Fondazione Bruno Kessler*, 286 Strada delle Tabarelle, 38123, Trento, Italy
| | - Rodolphe Vuilleumier
- PASTEUR, Département de Chimie, École normale supérieure, PSL Research University, Sorbonne Université, CNRS, 24 Rue Lhomond, 75005, Paris, France
| | - Antonino Marco Saitta
- IMPMC, Sorbonne Université, CNRS, MNHN, UMR 7590, 4 Place Jussieu, 75252, Paris, France
| | - Michele Casula
- IMPMC, Sorbonne Université, CNRS, MNHN, UMR 7590, 4 Place Jussieu, 75252, Paris, France.
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20
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Herman KM, Stone AJ, Xantheas SS. Accurate Calculation of Many-Body Energies in Water Clusters Using a Classical Geometry-Dependent Induction Model. J Chem Theory Comput 2023; 19:6805-6815. [PMID: 37703063 DOI: 10.1021/acs.jctc.3c00575] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/14/2023]
Abstract
We incorporate geometry-dependent distributed multipole and polarizability surfaces into an induction model that is used to describe the 3- and 4-body terms of the interaction between water molecules. The moment expansion is carried out up to the hexadecapole with the multipoles distributed on the atom sites. Dipole-dipole, dipole-quadrupole, and quadrupole-quadrupole distributed polarizabilities are used to represent the response of the multipoles to an electric field. We compare the model against two large databases consisting of 43,844 3-body terms and 3,603 4-body terms obtained from high level ab initio calculations previously used to fit the MB-pol and q-AQUA classical interaction potentials for water. The classical induction model with no adjustable parameters reproduces the ab initio 3-/4-body terms contained in these two databases with a root-mean-square error (RMSE) of 0.104/0.058 and a mean-absolute error (MAE) of 0.054/0.026 kcal/mol, respectively. These results are on par with the ones obtained by fitting the same data using over 14,000 (for the 3-body) and 200 (for the 4-body) parameters via Permutationally Invariant Polynomials (PIPs). This demonstrates the accuracy of this physically motivated model in describing the 3- and 4-body terms in the interactions between water molecules with no adjustable parameters. The triple-dipole-dispersion energy, included in the calculation of the 3-body energy, was found to be small but not quite negligible. The model represents a practical, efficient, and transferable approach for obtaining accurate nonadditive interactions for multicomponent systems without the need to perform tens of thousands of high level electronic structure calculations and fitting them with PIPs.
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Affiliation(s)
- Kristina M Herman
- Department of Chemistry, University of Washington, Seattle, Washington 98185, United States
| | - Anthony J Stone
- Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, U.K
| | - Sotiris S Xantheas
- Department of Chemistry, University of Washington, Seattle, Washington 98185, United States
- Advanced Computing Mathematics and Data Division, Pacific Northwest National Laboratory, 902 Battelle Boulevard, P.O. Box 999, MSIN J7-10, Richland, Washington 99352, United States
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21
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Yu Q, Qu C, Houston PL, Nandi A, Pandey P, Conte R, Bowman JM. A Status Report on "Gold Standard" Machine-Learned Potentials for Water. J Phys Chem Lett 2023; 14:8077-8087. [PMID: 37656898 PMCID: PMC10510435 DOI: 10.1021/acs.jpclett.3c01791] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 08/28/2023] [Indexed: 09/03/2023]
Abstract
Owing to the central importance of water to life as well as its unusual properties, potentials for water have been the subject of extensive research over the past 50 years. Recently, five potentials based on different machine learning approaches have been reported that are at or near the "gold standard" CCSD(T) level of theory. The development of such high-level potentials enables efficient and accurate simulations of water systems using classical and quantum dynamical approaches. This Perspective serves as a status report of these potentials, focusing on their methodology and applications to water systems across different phases. Their performances on the energies of gas phase water clusters, as well as condensed phase structural and dynamical properties, are discussed.
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Affiliation(s)
- Qi Yu
- Department
of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, United States
| | - Chen Qu
- Independent
Researcher, Toronto, Ontario M9B 0E3, Canada
| | - Paul L. Houston
- Department
of Chemistry and Chemical Biology, Cornell
University, Ithaca, New York 14853, United States
- Department of Chemistry
and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Apurba Nandi
- Department
of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, United States
- Department
of Physics and Materials Science, University
of Luxembourg, L-1511, Luxembourg City, Luxembourg
| | - Priyanka Pandey
- Department
of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, United States
| | - Riccardo Conte
- Dipartimento
di Chimica, Università degli Studi
di Milano, via Golgi 19, 20133 Milano, Italy
| | - Joel M. Bowman
- Department
of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, United States
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22
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Fu L, Yang S, Zhang DH. Neural network potential energy surfaces and dipole moment surfaces for SO 2(H 2O) and SO 2(H 2O) 2 complexes. Phys Chem Chem Phys 2023; 25:22804-22812. [PMID: 37584113 DOI: 10.1039/d3cp03113f] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/17/2023]
Abstract
Full-dimensional, ab initio-based many-body potential energy surfaces and dipole moment surfaces constructed using the neural network method for SO2(H2O)n (n = 1,2) complexes are reported. The database of the SO2 1-body PES, SO2(H2O) 2-body PES and SO2(H2O)2 3-body PES consists of 11 952, 79 882 and 84 159 ab initio energies, respectively. All 1-body energies were calculated at the CCSD(T)/CBS(AVTZ:AVQZ) level and all 2,3-body energies were calculated at the DSD-PBEP86/AVTZ level. The database of DMSs is the same as that of PESs and all dipole moments were calculated at the MP2/AVTZ level. Harmonic frequencies and dissociation energies of SO2(H2O) and SO2(H2O)2 were calculated on these PESs and compared with ab initio results to examine the fidelity of these PESs.
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Affiliation(s)
- Liangfei Fu
- State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, P. R. China.
- University of Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - Shuo Yang
- State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, P. R. China.
| | - Dong H Zhang
- State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, P. R. China.
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23
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Atsango AO, Morawietz T, Marsalek O, Markland TE. Developing machine-learned potentials to simultaneously capture the dynamics of excess protons and hydroxide ions in classical and path integral simulations. J Chem Phys 2023; 159:074101. [PMID: 37581418 DOI: 10.1063/5.0162066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 07/31/2023] [Indexed: 08/16/2023] Open
Abstract
The transport of excess protons and hydroxide ions in water underlies numerous important chemical and biological processes. Accurately simulating the associated transport mechanisms ideally requires utilizing ab initio molecular dynamics simulations to model the bond breaking and formation involved in proton transfer and path-integral simulations to model the nuclear quantum effects relevant to light hydrogen atoms. These requirements result in a prohibitive computational cost, especially at the time and length scales needed to converge proton transport properties. Here, we present machine-learned potentials (MLPs) that can model both excess protons and hydroxide ions at the generalized gradient approximation and hybrid density functional theory levels of accuracy and use them to perform multiple nanoseconds of both classical and path-integral proton defect simulations at a fraction of the cost of the corresponding ab initio simulations. We show that the MLPs are able to reproduce ab initio trends and converge properties such as the diffusion coefficients of both excess protons and hydroxide ions. We use our multi-nanosecond simulations, which allow us to monitor large numbers of proton transfer events, to analyze the role of hypercoordination in the transport mechanism of the hydroxide ion and provide further evidence for the asymmetry in diffusion between excess protons and hydroxide ions.
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Affiliation(s)
- Austin O Atsango
- Department of Chemistry, Stanford University, Stanford, California 94305, USA
| | - Tobias Morawietz
- Department of Chemistry, Stanford University, Stanford, California 94305, USA
| | - Ondrej Marsalek
- Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic
| | - Thomas E Markland
- Department of Chemistry, Stanford University, Stanford, California 94305, USA
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24
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Barbiero D, Bertaina G, Ceotto M, Conte R. Anharmonic Assignment of the Water Octamer Spectrum in the OH Stretch Region. J Phys Chem A 2023; 127:6213-6221. [PMID: 37477983 PMCID: PMC10405218 DOI: 10.1021/acs.jpca.3c02902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 07/03/2023] [Indexed: 07/23/2023]
Abstract
We interface the quasi-classical trajectory approach with an ab initio potential energy surface for water to assign the vibrational spectroscopical features of the OH stretch region of the water octamer cluster, which is considered to be a precursor of ice. An attempt by Li et al. to assign their recent reference experiment involved lower-level calculations based on an ad hoc scaled harmonic approach. Differently from the conclusions of this previous assignment, which invoked the contribution of 5 conformers and a solvated form of the water heptamer in the spectrum, we find out that the spectroscopic features can be related to the 4 conformers of the octamer lying lower in energy.
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Affiliation(s)
- Davide Barbiero
- Dipartimento
di Chimica, Università degli Studi
di Milano, via Golgi 19, 20133 Milano, Italy
| | - Gianluca Bertaina
- Istituto
Nazionale di Ricerca Metrologica, Strada delle Cacce 91, I-10135 Torino, Italy
| | - Michele Ceotto
- Dipartimento
di Chimica, Università degli Studi
di Milano, via Golgi 19, 20133 Milano, Italy
| | - Riccardo Conte
- Dipartimento
di Chimica, Università degli Studi
di Milano, via Golgi 19, 20133 Milano, Italy
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25
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Chen MS, Lee J, Ye HZ, Berkelbach TC, Reichman DR, Markland TE. Data-Efficient Machine Learning Potentials from Transfer Learning of Periodic Correlated Electronic Structure Methods: Liquid Water at AFQMC, CCSD, and CCSD(T) Accuracy. J Chem Theory Comput 2023; 19:4510-4519. [PMID: 36730728 DOI: 10.1021/acs.jctc.2c01203] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Obtaining the atomistic structure and dynamics of disordered condensed-phase systems from first-principles remains one of the forefront challenges of chemical theory. Here we exploit recent advances in periodic electronic structure and provide a data-efficient approach to obtain machine-learned condensed-phase potential energy surfaces using AFQMC, CCSD, and CCSD(T) from a very small number (≤200) of energies by leveraging a transfer learning scheme starting from lower-tier electronic structure methods. We demonstrate the effectiveness of this approach for liquid water by performing both classical and path integral molecular dynamics simulations on these machine-learned potential energy surfaces. By doing this, we uncover the interplay of dynamical electron correlation and nuclear quantum effects across the entire liquid range of water while providing a general strategy for efficiently utilizing periodic correlated electronic structure methods to explore disordered condensed-phase systems.
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Affiliation(s)
- Michael S Chen
- Department of Chemistry, Stanford University, Stanford, California94305, United States
| | - Joonho Lee
- Department of Chemistry, Columbia University, New York, New York10027, United States
| | - Hong-Zhou Ye
- Department of Chemistry, Columbia University, New York, New York10027, United States
| | - Timothy C Berkelbach
- Department of Chemistry, Columbia University, New York, New York10027, United States
- Center for Computational Quantum Physics, Flatiron Institute, New York, New York10010, United States
| | - David R Reichman
- Department of Chemistry, Columbia University, New York, New York10027, United States
| | - Thomas E Markland
- Department of Chemistry, Stanford University, Stanford, California94305, United States
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26
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Yu Q, Bowman JM. Manipulating hydrogen bond dissociation rates and mechanisms in water dimer through vibrational strong coupling. Nat Commun 2023; 14:3527. [PMID: 37316497 DOI: 10.1038/s41467-023-39212-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Accepted: 05/31/2023] [Indexed: 06/16/2023] Open
Abstract
The vibrational strong coupling (VSC) between molecular vibrations and cavity photon modes has recently emerged as a promising tool for influencing chemical reactivities. Despite numerous experimental and theoretical efforts, the underlying mechanism of VSC effects remains elusive. In this study, we combine state-of-art quantum cavity vibrational self-consistent field/configuration interaction theory (cav-VSCF/VCI), quasi-classical trajectory method, along with the quantum-chemical CCSD(T)-level machine learning potential, to simulate the hydrogen bond dissociation dynamics of water dimer under VSC. We observe that manipulating the light-matter coupling strength and cavity frequencies can either inhibit or accelerate the dissociation rate. Furthermore, we discover that the cavity surprisingly modifies the vibrational dissociation channels, with a pathway involving both water fragments in their ground vibrational states becoming the major channel, which is a minor one when the water dimer is outside the cavity. We elucidate the mechanisms behind these effects by investigating the critical role of the optical cavity in modifying the intramolecular and intermolecular coupling patterns. While our work focuses on single water dimer system, it provides direct and statistically significant evidence of VSC effects on molecular reaction dynamics.
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Affiliation(s)
- Qi Yu
- Department of Chemistry, Yale University, New Haven, CT, 06520, USA.
- Department of Chemistry, Emory University and Cherry L. Emerson Center for Scientific Computation, Atlanta, GA, 30322, USA.
| | - Joel M Bowman
- Department of Chemistry, Emory University and Cherry L. Emerson Center for Scientific Computation, Atlanta, GA, 30322, USA
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27
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Bore SL, Paesani F. Realistic phase diagram of water from "first principles" data-driven quantum simulations. Nat Commun 2023; 14:3349. [PMID: 37291095 DOI: 10.1038/s41467-023-38855-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Accepted: 05/12/2023] [Indexed: 06/10/2023] Open
Abstract
Since the experimental characterization of the low-pressure region of water's phase diagram in the early 1900s, scientists have been on a quest to understand the thermodynamic stability of ice polymorphs on the molecular level. In this study, we demonstrate that combining the MB-pol data-driven many-body potential for water, which was rigorously derived from "first principles" and exhibits chemical accuracy, with advanced enhanced-sampling algorithms, which correctly describe the quantum nature of molecular motion and thermodynamic equilibria, enables computer simulations of water's phase diagram with an unprecedented level of realism. Besides providing fundamental insights into how enthalpic, entropic, and nuclear quantum effects shape the free-energy landscape of water, we demonstrate that recent progress in "first principles" data-driven simulations, which rigorously encode many-body molecular interactions, has opened the door to realistic computational studies of complex molecular systems, bridging the gap between experiments and simulations.
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Affiliation(s)
- Sigbjørn Løland Bore
- Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Francesco Paesani
- Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA, 92093, USA.
- Materials Science and Engineering, University of California San Diego, La Jolla, CA, 92093, USA.
- Halicioğlu Data Science Institute, University of California San Diego, La Jolla, CA, 92093, USA.
- San Diego Supercomputer Center, University of California San Diego, La Jolla, CA, 92093, USA.
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28
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Schiltz C, Rappoport D, Mandelshtam VA. Implementation of the self-consistent phonons method with ab initio potentials (AI-SCP). J Chem Phys 2023; 158:2890485. [PMID: 37184023 DOI: 10.1063/5.0146682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 04/24/2023] [Indexed: 05/16/2023] Open
Abstract
The self-consistent phonon (SCP) method allows one to include anharmonic effects when treating a many-body quantum system at thermal equilibrium. The system is then described by an effective temperature-dependent harmonic Hamiltonian, which can be used to estimate its various dynamic and static properties. In this paper, we combine SCP with ab initio (AI) potential energy evaluation in which case the numerical bottleneck of AI-SCP is the evaluation of Gaussian averages of the AI potential energy and its derivatives. These averages are computed efficiently by the quasi-Monte Carlo method utilizing low-discrepancy sequences leading to a fast convergence with respect to the number, S, of the AI energy evaluations. Moreover, a further substantial (an-order-of-magnitude) improvement in efficiency is achieved once a numerically cheap approximation of the AI potential is available. This is based on using a perturbation theory-like (the two-grid) approach in which it is the average of the difference between the AI and the approximate potential that is computed. The corresponding codes and scripts are provided.
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Affiliation(s)
- Colin Schiltz
- Department of Chemistry, University of California, Irvine, California 92697, USA
| | - Dmitrij Rappoport
- Department of Chemistry, University of California, Irvine, California 92697, USA
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29
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Ferretti A, Canal L, Sorodoc RA, Sinha S, Brancato G. Fine Tuning the Intermolecular Interactions of Water Clusters Using the Dispersion-Corrected Density Functional Theory. Molecules 2023; 28:molecules28093834. [PMID: 37175249 PMCID: PMC10180381 DOI: 10.3390/molecules28093834] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 04/26/2023] [Accepted: 04/28/2023] [Indexed: 05/15/2023] Open
Abstract
Dispersion-inclusive density functional theory (DFT) methods have unequivocally demonstrated improved performances with respect to standard DFT approximations for modeling large and extended molecular systems at the quantum mechanical level. Yet, in some cases, disagreements with highly accurate reference calculations, such as CCSD(T) and quantum Monte Carlo (MC) calculations, still remain. Furthermore, the application of general-purpose corrections, such as the popular Grimme's semi-classical models (DFT-D), to different Kohn-Sham exchange-correlation functionals sometimes leads to variable and inconsistent results, which recommend a careful prior evaluation. In a recent study, we proposed a simple optimization protocol for enhancing the accuracy of these DFT-D methods by following an alternative and system-specific approach. Here, adopting the same computational strategy, we show how the accurate MC intermolecular interactions of a large set of water clusters of variable sizes (i.e., 300 (H2O)n structures, n = 9, 15, 27) can be reproduced remarkably well by dispersion-corrected DFT models (i.e., B3LYP-D4, PBE-D4, revPBE(0)-D4) upon re-optimization, reaching a mean absolute error per monomer of ~0.1 kcal/mol. Hence, the obtained results support the use of this procedure for fine-tuning tailored DFT-D models for the accurate description of targeted molecular systems.
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Affiliation(s)
- Alfonso Ferretti
- Scuola Normale Superiore and CSGI, Classe di Scienze, Piazza dei Cavalieri 7, I-56126 Pisa, Italy
- Istituto Nazionale di Fisica Nucleare (INFN) Sezione di Pisa, Largo Bruno Pontecorvo 3, I-56127 Pisa, Italy
| | - Laura Canal
- Dipartimento di Ingegneria Civile ed Industriale, Università di Pisa, Largo Lucio Lazzarino 2, I-56124 Pisa, Italy
| | - Robert A Sorodoc
- Dipartimento di Ingegneria Civile ed Industriale, Università di Pisa, Largo Lucio Lazzarino 2, I-56124 Pisa, Italy
| | - Sourab Sinha
- Scuola Normale Superiore and CSGI, Classe di Scienze, Piazza dei Cavalieri 7, I-56126 Pisa, Italy
| | - Giuseppe Brancato
- Scuola Normale Superiore and CSGI, Classe di Scienze, Piazza dei Cavalieri 7, I-56126 Pisa, Italy
- Istituto Nazionale di Fisica Nucleare (INFN) Sezione di Pisa, Largo Bruno Pontecorvo 3, I-56127 Pisa, Italy
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30
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Shea JE, Crawford TD, Zanni MT, Hartland GV, Aumiller W. 50 and 100 Years Ago in The Journal of Physical Chemistry 2023. J Phys Chem B 2023; 127:2103-2106. [PMID: 36924063 DOI: 10.1021/acs.jpcb.3c01129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2023]
Affiliation(s)
- Joan-Emma Shea
- Department of Chemistry and Biochemistry and Department of Physics, University of California, Santa Barbara, California 93106, United States
| | - T Daniel Crawford
- Department of Chemistry, Virginia Tech, Blacksburg, Virginia 24061, United States.,Molecular Sciences Software Institute, Blacksburg, Virginia 24060, United States
| | - Martin T Zanni
- Department of Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
| | - Gregory V Hartland
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana 46556, United States
| | - William Aumiller
- American Chemical Society, 1155 Sixteenth Street N.W., Washington, D.C. 20036, United States
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31
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Shea JE, Crawford TD, Zanni MT, Hartland GV, Aumiller W. 50 and 100 Years Ago in The Journal of Physical Chemistry 2023. J Phys Chem A 2023; 127:2061-2064. [PMID: 36891676 DOI: 10.1021/acs.jpca.3c01130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/10/2023]
Affiliation(s)
- Joan-Emma Shea
- Department of Chemistry and Biochemistry and Department of Physics, University of California, Santa Barbara, California 93106, United States
| | - T Daniel Crawford
- Department of Chemistry, Virginia Tech, Blacksburg, Virginia 24061, United States.,Molecular Sciences Software Institute, Blacksburg, Virginia 24060, United States
| | - Martin T Zanni
- Department of Chemistry, University of Wisconsin─Madison, Madison, Wisconsin 53706, United States
| | - Gregory V Hartland
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana 46556, United States
| | - William Aumiller
- American Chemical Society, 1155 Sixteenth Street N.W., Washington, D.C. 20036, United States
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32
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Herman KM, Xantheas SS. An extensive assessment of the performance of pairwise and many-body interaction potentials in reproducing ab initio benchmark binding energies for water clusters n = 2-25. Phys Chem Chem Phys 2023; 25:7120-7143. [PMID: 36853239 DOI: 10.1039/d2cp03241d] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
We assess the performance of 7 pairwise additive (TIP3P, TIP4P, TIP4P-ice, TIP5P, OPC, SPC, SPC/E) and 8 families of many-body potentials (q-AQUA, HIPPO, AMOEBA, EFP, TTM, WHBB, MB-pol, MB-UCB) in reproducing high-level ab initio benchmark values, CCSD(T) or MP2 at the complete basis set (CBS) limit for the binding energy and the many-body expansion (MBE) of water clusters n = 2-11, 16-17, 20, 25. By including a large range of cluster sizes having dissimilar hydrogen bonding networks, we obtain an understanding of how these potentials perform for different hydrogen bonding arrangements that are mostly outside of their parameterization range. While it is appropriate to compare the results of ab initio based many-body potentials directly to the electronic binding energies (De's), the pairwise additive ones are compared to the enthalpies at T = 298 K, ΔH(298 K), as the latter class of force fields are parametrized to reproduce enthalpies (implicitly accounting for zero-point energy corrections) rather than binding energies. We find that all pairwise additive potentials considered overestimate the reference ΔH values for the n = 2-25 clusters by >13%. For the water dimer (n = 2) in particular, the errors are in the range 83-119% for the pairwise additive potentials studied since these are based on an effective rather than the true 2-body interaction specifically designed as a means of partially accounting for the missing many-body terms. This stronger 2-body interaction is achieved by an enhanced monomer dipole moment that mimics its increase from the gas phase monomer to the condensed phase value. Indeed, for cluster sizes n ≥ 4 the percent deviations become slightly smaller (albeit all exceeding 13%). In contrast, we find that the many-body potentials perform more accurately in reproducing the electronic binding energies (De's) throughout the entire cluster range (n = 2-25), all reproducing the ab initio benchmark binding energies within ±7% of the respective CBS values. We further assess the ability of a subset of the many-body potentials (MB-UCB, q-AQUA, MB-pol, and TTM2.1-F) to also reproduce the magnitude of the ab initio many-body energy terms for water cluster sizes n = 7, 10, 16 and 17. The potentials show an overall good agreement with the available benchmark values. However, we identify characteristic differences upon comparing the many-body terms at both the ab initio-optimized geometries and the respective potential-optimized geometries to the reference ab initio values. Additionally, by applying this analysis to a wide range of cluster sizes, trends in the MBE of the potentials with increasing cluster size can be identified. Finally, in an attempt to draw a parallel between the pairwise additive and many-body potentials, we report the analysis of the individual molecular dipole moments for water clusters with 1 to ∼4 solvation shells with the TTM2.1-F potential. We find that the internally solvated water molecules have in general a larger molecular dipole moment ranging from 2.6-3.0 D. This justifies the use of an enhanced, with respect to the gas-phase value, molecular dipole moment for the pairwise additive potentials, which is intended to fold in the many body terms into an effective (enhanced) pairwise interaction through the choice of the charges. These results have important implications for the development of future generations of efficient, transferable, and highly accurate classical interaction potentials in both the pairwise additive and many-body categories.
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Affiliation(s)
- Kristina M Herman
- Department of Chemistry, University of Washington, Seattle, WA 98195, USA.
| | - Sotiris S Xantheas
- Department of Chemistry, University of Washington, Seattle, WA 98195, USA. .,Advanced Computing, Mathematics and Data Division, Pacific Northwest National Laboratory, 902 Battelle Boulevard, P.O. Box 999, MS K1-83, WA, 99352, USA.
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33
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Herman KM, Xantheas SS. A Formulation of the Many-Body Expansion (MBE) for Periodic Systems: Application to Several Ice Phases. J Phys Chem Lett 2023; 14:989-999. [PMID: 36692897 DOI: 10.1021/acs.jpclett.2c03822] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
We introduce a new formulation of the many-body expansion (MBE) for periodic systems and apply it to 7 ice polymorphs (Ih, II, VIII, IX, XIII, XIV, and XV). This new formulation is built via a hierarchical procedure that connects gas-phase clusters that mimic unit cells over finite supercells to infinite solids. For periodic systems, the method is validated by showing that the lattice energies computed up to the 4-body in the MBE reproduce the lattice energies obtained using periodic boundary conditions with an Ewald summation for the 7 ice polymorphs. This development makes it possible to quantify, for the first time, the many-body contributions to the lattice energy of various ice polymorphs, which vary significantly among the 7 ice phases, amounting to between 7 and 24% of the total lattice energies. This development opens the door for obtaining insights into solid-state properties, while leveraging the computational benefits of the MBE.
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Affiliation(s)
- Kristina M Herman
- Department of Chemistry, University of Washington, Seattle, Washington98195, United States
| | - Sotiris S Xantheas
- Department of Chemistry, University of Washington, Seattle, Washington98195, United States
- Advanced Computing, Mathematics and Data Division, Pacific Northwest National Laboratory, 902 Battelle Boulevard, P.O. Box 999, MSIN J7-10, Richland, Washington99352, United States
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34
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Houston PL, Qu C, Yu Q, Conte R, Nandi A, Li JK, Bowman JM. PESPIP: Software to fit complex molecular and many-body potential energy surfaces with permutationally invariant polynomials. J Chem Phys 2023; 158:044109. [PMID: 36725524 DOI: 10.1063/5.0134442] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
We wish to describe a potential energy surface by using a basis of permutationally invariant polynomials whose coefficients will be determined by numerical regression so as to smoothly fit a dataset of electronic energies as well as, perhaps, gradients. The polynomials will be powers of transformed internuclear distances, usually either Morse variables, exp(-ri,j/λ), where λ is a constant range hyperparameter, or reciprocals of the distances, 1/ri,j. The question we address is how to create the most efficient basis, including (a) which polynomials to keep or discard, (b) how many polynomials will be needed, (c) how to make sure the polynomials correctly reproduce the zero interaction at a large distance, (d) how to ensure special symmetries, and (e) how to calculate gradients efficiently. This article discusses how these questions can be answered by using a set of programs to choose and manipulate the polynomials as well as to write efficient Fortran programs for the calculation of energies and gradients. A user-friendly interface for access to monomial symmetrization approach results is also described. The software for these programs is now publicly available.
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Affiliation(s)
- Paul L Houston
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, USA and Department of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | - Chen Qu
- Independent Researcher, Toronto, Ontario M9B0E3, Canada
| | - Qi Yu
- Department of Chemistry, Yale University, New Haven, Connecticut 06520, USA
| | - Riccardo Conte
- Dipartimento di Chimica, Università Degli Studi di Milano, Via Golgi 19, 20133 Milano, Italy
| | - Apurba Nandi
- Department of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, USA
| | - Jeffrey K Li
- Department of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, USA
| | - Joel M Bowman
- Department of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, USA
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35
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Kříž K, Schmidt L, Andersson AT, Walz MM, van der Spoel D. An Imbalance in the Force: The Need for Standardized Benchmarks for Molecular Simulation. J Chem Inf Model 2023; 63:412-431. [PMID: 36630710 PMCID: PMC9875315 DOI: 10.1021/acs.jcim.2c01127] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Indexed: 01/12/2023]
Abstract
Force fields (FFs) for molecular simulation have been under development for more than half a century. As with any predictive model, rigorous testing and comparisons of models critically depends on the availability of standardized data sets and benchmarks. While such benchmarks are rather common in the fields of quantum chemistry, this is not the case for empirical FFs. That is, few benchmarks are reused to evaluate FFs, and development teams rather use their own training and test sets. Here we present an overview of currently available tests and benchmarks for computational chemistry, focusing on organic compounds, including halogens and common ions, as FFs for these are the most common ones. We argue that many of the benchmark data sets from quantum chemistry can in fact be reused for evaluating FFs, but new gas phase data is still needed for compounds containing phosphorus and sulfur in different valence states. In addition, more nonequilibrium interaction energies and forces, as well as molecular properties such as electrostatic potentials around compounds, would be beneficial. For the condensed phases there is a large body of experimental data available, and tools to utilize these data in an automated fashion are under development. If FF developers, as well as researchers in artificial intelligence, would adopt a number of these data sets, it would become easier to compare the relative strengths and weaknesses of different models and to, eventually, restore the balance in the force.
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Affiliation(s)
- Kristian Kříž
- Department
of Cell and Molecular Biology, Uppsala University, Box 596, SE-75124Uppsala, Sweden
| | - Lisa Schmidt
- Faculty
of Biosciences, University of Heidelberg, Heidelberg69117, Germany
| | - Alfred T. Andersson
- Department
of Cell and Molecular Biology, Uppsala University, Box 596, SE-75124Uppsala, Sweden
| | - Marie-Madeleine Walz
- Department
of Cell and Molecular Biology, Uppsala University, Box 596, SE-75124Uppsala, Sweden
| | - David van der Spoel
- Department
of Cell and Molecular Biology, Uppsala University, Box 596, SE-75124Uppsala, Sweden
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36
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Bowman JM, Qu C, Conte R, Nandi A, Houston PL, Yu Q. Δ-Machine Learned Potential Energy Surfaces and Force Fields. J Chem Theory Comput 2023; 19:1-17. [PMID: 36527383 DOI: 10.1021/acs.jctc.2c01034] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
There has been great progress in developing machine-learned potential energy surfaces (PESs) for molecules and clusters with more than 10 atoms. Unfortunately, this number of atoms generally limits the level of electronic structure theory to less than the "gold standard" CCSD(T) level. Indeed, for the well-known MD17 dataset for molecules with 9-20 atoms, all of the energies and forces were obtained with DFT calculations (PBE). This Perspective is focused on a Δ-machine learning method that we recently proposed and applied to bring DFT-based PESs to close to CCSD(T) accuracy. This is demonstrated for hydronium, N-methylacetamide, acetyl acetone, and ethanol. For 15-atom tropolone, it appears that special approaches (e.g., molecular tailoring, local CCSD(T)) are needed to obtain the CCSD(T) energies. A new aspect of this approach is the extension of Δ-machine learning to force fields. The approach is based on many-body corrections to polarizable force field potentials. This is examined in detail using the TTM2.1 water potential. The corrections make use of our recent CCSD(T) datasets for 2-b, 3-b, and 4-b interactions for water. These datasets were used to develop a new fully ab initio potential for water, termed q-AQUA.
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Affiliation(s)
- Joel M Bowman
- Department of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, United States
| | - Chen Qu
- Independent Researcher, Toronto, Canada 66777
| | - Riccardo Conte
- Dipartimento di Chimica, Università Degli Studi di Milano, via Golgi 19, 20133 Milano, Italy
| | - Apurba Nandi
- Department of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, Georgia 30322, United States
| | - Paul L Houston
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, United States.,Department of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Qi Yu
- Department of Chemistry, Yale University, New Haven, Connecticut 06520, United States
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37
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Daru J, Forbert H, Behler J, Marx D. Coupled Cluster Molecular Dynamics of Condensed Phase Systems Enabled by Machine Learning Potentials: Liquid Water Benchmark. PHYSICAL REVIEW LETTERS 2022; 129:226001. [PMID: 36493459 DOI: 10.1103/physrevlett.129.226001] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 09/05/2022] [Accepted: 10/05/2022] [Indexed: 06/17/2023]
Abstract
Coupled cluster theory is a general and systematic electronic structure method, but in particular the highly accurate "gold standard" coupled cluster singles, doubles and perturbative triples, CCSD(T), can only be applied to small systems. To overcome this limitation, we introduce a framework to transfer CCSD(T) accuracy of finite molecular clusters to extended condensed phase systems using a high-dimensional neural network potential. This approach, which is automated, allows one to perform high-quality coupled cluster molecular dynamics, CCMD, as we demonstrate for liquid water including nuclear quantum effects. The machine learning strategy is very efficient, generic, can be systematically improved, and is applicable to a variety of complex systems.
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Affiliation(s)
- János Daru
- Lehrstuhl für Theoretische Chemie, Ruhr-Universität Bochum, 44780 Bochum, Germany
| | - Harald Forbert
- Center for Solvation Science ZEMOS, Ruhr-Universität Bochum, 44780 Bochum, Germany
| | - Jörg Behler
- Universität Göttingen, Institut für Physikalische Chemie, Theoretische Chemie, Tammannstrasse 6, 37077 Göttingen, Germany
| | - Dominik Marx
- Lehrstuhl für Theoretische Chemie, Ruhr-Universität Bochum, 44780 Bochum, Germany
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38
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Bull-Vulpe EF, Riera M, Bore SL, Paesani F. Data-Driven Many-Body Potential Energy Functions for Generic Molecules: Linear Alkanes as a Proof-of-Concept Application. J Chem Theory Comput 2022. [PMID: 36113028 DOI: 10.1021/acs.jctc.2c00645] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
We present a generalization of the many-body energy (MB-nrg) theoretical/computational framework that enables the development of data-driven potential energy functions (PEFs) for generic covalently bonded molecules, with arbitrary quantum mechanical accuracy. The "nearsightedness of electronic matter" is exploited to define monomers as "natural building blocks" on the basis of their distinct chemical identity. The energy of generic molecules is then expressed as a sum of individual many-body energies of incrementally larger subsystems. The MB-nrg PEFs represent the low-order n-body energies, with n = 1-4, using permutationally invariant polynomials derived from electronic structure data carried out at an arbitrary quantum mechanical level of theory, while all higher-order n-body terms (n > 4) are represented by a classical many-body polarization term. As a proof-of-concept application of the general MB-nrg framework, we present MB-nrg PEFs for linear alkanes. The MB-nrg PEFs are shown to accurately reproduce reference energies, harmonic frequencies, and potential energy scans of alkanes, independently of their length. Since, by construction, the MB-nrg framework introduced here can be applied to generic covalently bonded molecules, we envision future computer simulations of complex molecular systems using data-driven MB-nrg PEFs, with arbitrary quantum mechanical accuracy.
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Affiliation(s)
- Ethan F. Bull-Vulpe
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, United States
| | - Marc Riera
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, United States
| | - Sigbjørn L. Bore
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, United States
| | - Francesco Paesani
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, United States
- Materials Science and Engineering, University of California San Diego, La Jolla, California 92093, United States
- San Diego Supercomputer Center, University of California San Diego, La Jolla, California 92093, United States
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