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Savoj R, Agnew H, Zhou R, Paesani F. Molecular Insights into the Influence of Ions on the Water Structure. I. Alkali Metal Ions in Solution. J Phys Chem B 2024; 128:1953-1962. [PMID: 38373140 DOI: 10.1021/acs.jpcb.3c08150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/21/2024]
Abstract
In this study, we explore the impact of alkali metal ions (Li+, Na+, K+, Rb+, and Cs+) on the hydration structure of water using molecular dynamics simulations carried out with MB-nrg potential energy functions (PEFs). Our analyses include radial distribution functions, coordination numbers, dipole moments, and infrared spectra of water molecules, calculated as a function of solvation shells. The results collectively indicate a highly local influence of all of the alkali metal ions on the hydrogen-bond network established by the surrounding water molecules, with the smallest and most densely charged Li+ ion exerting the most pronounced effect. Remarkably, the MB-nrg PEFs demonstrate excellent agreement with available experimental data for the position and size of the first solvation shells, underscoring their potential as predictive models for realistic simulations of ionic aqueous solutions across various thermodynamic conditions and environments.
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Affiliation(s)
- Roya Savoj
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, United States
| | - Henry Agnew
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, United States
| | - Ruihan Zhou
- 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
- Halicioğlu Data Science Institute, 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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2
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Dasgupta S, Palos E, Pan Y, Paesani F. Balance between Physical Interpretability and Energetic Predictability in Widely Used Dispersion-Corrected Density Functionals. J Chem Theory Comput 2024; 20:49-67. [PMID: 38150541 DOI: 10.1021/acs.jctc.3c00903] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2023]
Abstract
We assess the performance of different dispersion models for several popular density functionals across a diverse set of noncovalent systems, ranging from the benzene dimer to molecular crystals. By analyzing the interaction energies and their individual components, we demonstrate that there exists variability across different systems for empirical dispersion models, which are calibrated for reproducing the interaction energies of specific systems. Thus, parameter fitting may undermine the underlying physics, as dispersion models rely on error compensation among the different components of the interaction energy. Energy decomposition analyses reveal that, the accuracy of revPBE-D3 for some aqueous systems originates from significant compensation between dispersion and charge transfer energies. However, revPBE-D3 is less accurate in describing systems where error compensation is incomplete, such as the benzene dimer. Such cases highlight the propensity for unpredictable behavior in various dispersion-corrected density functionals across a wide range of molecular systems, akin to the behavior of force fields. On the other hand, we find that SCAN-rVV10, a targeted-dispersion approach, affords significant reductions in errors associated with the lattice energies of molecular crystals, while it has limited accuracy in reproducing structural properties. Given the ubiquitous nature of noncovalent interactions and the key role of density functional theory in computational sciences, the future development of dispersion models should prioritize the faithful description of the dispersion energy, a shift that promises greater accuracy in capturing the underlying physics across diverse molecular and extended systems.
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Affiliation(s)
- Saswata Dasgupta
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, United States
| | - Etienne Palos
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, United States
| | - Yuanhui Pan
- 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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3
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Riera M, Knight C, Bull-Vulpe EF, Zhu X, Agnew H, Smith DGA, Simmonett AC, Paesani F. MBX: A many-body energy and force calculator for data-driven many-body simulations. J Chem Phys 2023; 159:054802. [PMID: 37526156 PMCID: PMC10550339 DOI: 10.1063/5.0156036] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 07/11/2023] [Indexed: 08/02/2023] Open
Abstract
Many-Body eXpansion (MBX) is a C++ library that implements many-body potential energy functions (PEFs) within the "many-body energy" (MB-nrg) formalism. MB-nrg PEFs integrate an underlying polarizable model with explicit machine-learned representations of many-body interactions to achieve chemical accuracy from the gas to the condensed phases. MBX can be employed either as a stand-alone package or as an energy/force engine that can be integrated with generic software for molecular dynamics and Monte Carlo simulations. MBX is parallelized internally using Open Multi-Processing and can utilize Message Passing Interface when available in interfaced molecular simulation software. MBX enables classical and quantum molecular simulations with MB-nrg PEFs, as well as hybrid simulations that combine conventional force fields and MB-nrg PEFs, for diverse systems ranging from small gas-phase clusters to aqueous solutions and molecular fluids to biomolecular systems and metal-organic frameworks.
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Affiliation(s)
- Marc Riera
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, USA
| | - Christopher Knight
- Argonne National Laboratory, Computational Science Division, Lemont, Illinois 60439, USA
| | - Ethan F. Bull-Vulpe
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, USA
| | - Xuanyu Zhu
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, USA
| | - Henry Agnew
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, USA
| | | | - Andrew C. Simmonett
- Laboratory of Computational Biology, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland 20892, USA
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4
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Zhai Y, Caruso A, Bore SL, Luo Z, Paesani F. A "short blanket" dilemma for a state-of-the-art neural network potential for water: Reproducing experimental properties or the physics of the underlying many-body interactions? J Chem Phys 2023; 158:084111. [PMID: 36859071 DOI: 10.1063/5.0142843] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
Deep neural network (DNN) potentials have recently gained popularity in computer simulations of a wide range of molecular systems, from liquids to materials. In this study, we explore the possibility of combining the computational efficiency of the DeePMD framework and the demonstrated accuracy of the MB-pol data-driven, many-body potential to train a DNN potential for large-scale simulations of water across its phase diagram. We find that the DNN potential is able to reliably reproduce the MB-pol results for liquid water, but provides a less accurate description of the vapor-liquid equilibrium properties. This shortcoming is traced back to the inability of the DNN potential to correctly represent many-body interactions. An attempt to explicitly include information about many-body effects results in a new DNN potential that exhibits the opposite performance, being able to correctly reproduce the MB-pol vapor-liquid equilibrium properties, but losing accuracy in the description of the liquid properties. These results suggest that DeePMD-based DNN potentials are not able to correctly "learn" and, consequently, represent many-body interactions, which implies that DNN potentials may have limited ability to predict the properties for state points that are not explicitly included in the training process. The computational efficiency of the DeePMD framework can still be exploited to train DNN potentials on data-driven many-body potentials, which can thus enable large-scale, "chemically accurate" simulations of various molecular systems, with the caveat that the target state points must have been adequately sampled by the reference data-driven many-body potential in order to guarantee a faithful representation of the associated properties.
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Affiliation(s)
- Yaoguang Zhai
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, California 92093, USA
| | - Alessandro Caruso
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, USA
| | - Sigbjørn Løland Bore
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, USA
| | - Zhishang Luo
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, USA
| | - Francesco Paesani
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, USA
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Zhuang D, Riera M, Zhou R, Deary A, Paesani F. Hydration Structure of Na + and K + Ions in Solution Predicted by Data-Driven Many-Body Potentials. J Phys Chem B 2022; 126:9349-9360. [PMID: 36326071 DOI: 10.1021/acs.jpcb.2c05674] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
The hydration structure of Na+ and K+ ions in solution is systematically investigated using a hierarchy of molecular models that progressively include more accurate representations of many-body interactions. We found that a conventional empirical pairwise additive force field that is commonly used in biomolecular simulations is unable to reproduce the extended X-ray absorption fine structure (EXAFS) spectra for both ions. In contrast, progressive inclusion of many-body effects rigorously derived from the many-body expansion of the energy allows the MB-nrg potential energy functions (PEFs) to achieve nearly quantitative agreement with the experimental EXAFS spectra, thus enabling the development of a molecular-level picture of the hydration structure of both Na+ and K+ in solution. Since the MB-nrg PEFs have already been shown to accurately describe isomeric equilibria and vibrational spectra of small ion-water clusters in the gas phase, the present study demonstrates that the MB-nrg PEFs effectively represent the long-sought-after models able to correctly predict the properties of ionic aqueous systems from the gas to the liquid phase, which has so far remained elusive.
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Affiliation(s)
- Debbie Zhuang
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California92093, United States
| | - Marc Riera
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California92093, United States
| | - Ruihan Zhou
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California92093, United States
| | - Alexander Deary
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California92093, United States
| | - Francesco Paesani
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California92093, United States.,Materials Science and Engineering, University of California San Diego, La Jolla, California92093, United States.,San Diego Supercomputer Center, University of California San Diego, La Jolla, California92093, United States
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6
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Yue S, Riera M, Ghosh R, Panagiotopoulos AZ, Paesani F. Transferability of data-driven, many-body models for CO2 simulations in the vapor and liquid phases. J Chem Phys 2022; 156:104503. [DOI: 10.1063/5.0080061] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Shuwen Yue
- Princeton University, United States of America
| | - Marc Riera
- Chemistry and Biochemistry, University of California San Diego Department of Chemistry and Biochemistry, United States of America
| | - Raja Ghosh
- University of California San Diego, United States of America
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7
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Bull-Vulpe EF, Riera M, Götz AW, Paesani F. MB-Fit: Software infrastructure for data-driven many-body potential energy functions. J Chem Phys 2021; 155:124801. [PMID: 34598567 DOI: 10.1063/5.0063198] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Many-body potential energy functions (MB-PEFs), which integrate data-driven representations of many-body short-range quantum mechanical interactions with physics-based representations of many-body polarization and long-range interactions, have recently been shown to provide high accuracy in the description of molecular interactions from the gas to the condensed phase. Here, we present MB-Fit, a software infrastructure for the automated development of MB-PEFs for generic molecules within the TTM-nrg (Thole-type model energy) and MB-nrg (many-body energy) theoretical frameworks. Besides providing all the necessary computational tools for generating TTM-nrg and MB-nrg PEFs, MB-Fit provides a seamless interface with the MBX software, a many-body energy and force calculator for computer simulations. Given the demonstrated accuracy of the MB-PEFs, particularly within the MB-nrg framework, we believe that MB-Fit will enable routine predictive computer simulations of generic (small) molecules in the gas, liquid, and solid phases, including, but not limited to, the modeling of quantum isomeric equilibria in molecular clusters, solvation processes, molecular crystals, and phase diagrams.
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Affiliation(s)
- Ethan F Bull-Vulpe
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, USA
| | - Marc Riera
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, USA
| | - Andreas W Götz
- San Diego Supercomputer Center, University of California San Diego, La Jolla, California 92093, USA
| | - Francesco Paesani
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, USA
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8
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Abstract
Cooperative or nonadditive effects contribute to the pairwise noncovalent interaction of two molecules in a cluster or the condensed phase in ways that depend on the specific arrangements and interactions of the other surrounding molecules that constitute their environment. General expressions for an effective two-body interaction are presented, which are correct to increasing orders in the many-body expansion. The simplest result, correct through third order, requires only seven individual calculations, in contrast to a linear number of three-body contributions. Two applications are presented. First, an error analysis is performed on a model (H2O)8 cluster which completes the first solvation shell of a central water-water hydrogen bond. Energy decomposition analysis is performed to show that the largest effects of cooperativity on the central hydrogen bond arise from electrical polarization. Second, the nature of cooperative effects on proton transfer in an HCl + (H2O)4 cluster is characterized.
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Affiliation(s)
- Cameron Mackie
- Department of Chemistry, University of California, Berkeley, California 94720, United States.,Chemical Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Alexander Zech
- Department of Chemistry, University of California, Berkeley, California 94720, United States
| | - Martin Head-Gordon
- Department of Chemistry, University of California, Berkeley, California 94720, United States.,Chemical Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
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9
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Caruso A, Paesani F. Data-driven many-body models enable a quantitative description of chloride hydration from clusters to bulk. J Chem Phys 2021; 155:064502. [PMID: 34391363 DOI: 10.1063/5.0059445] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
We present a new data-driven potential energy function (PEF) describing chloride-water interactions, which is developed within the many-body-energy (MB-nrg) theoretical framework. Besides quantitatively reproducing low-order many-body energy contributions, the new MB-nrg PEF is able to correctly predict the interaction energies of small chloride-water clusters calculated at the coupled cluster level of theory. Importantly, classical and quantum molecular dynamics simulations of a single chloride ion in water demonstrate that the new MB-nrg PEF predicts x-ray spectra in close agreement with the experimental results. Comparisons with an popular empirical model and a polarizable PEF emphasize the importance of an accurate representation of short-range many-body effect while demonstrating that pairwise additive representations of chloride-water and water-water interactions are inadequate for correctly representing the hydration structure of chloride in both gas-phase clusters and solution. We believe that the analyses presented in this study provide additional evidence for the accuracy and predictive ability of the MB-nrg PEFs, which can then enable more realistic simulations of ionic aqueous systems in different environments.
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Affiliation(s)
- Alessandro Caruso
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, USA
| | - Francesco Paesani
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, USA
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10
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Wagle K, Santra B, Bhattarai P, Shahi C, Pederson MR, Jackson KA, Perdew JP. Self-interaction correction in water–ion clusters. J Chem Phys 2021; 154:094302. [DOI: 10.1063/5.0041620] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Kamal Wagle
- Department of Physics, Temple University, Philadelphia, Pennsylvania 19122, USA
| | - Biswajit Santra
- Department of Physics, Temple University, Philadelphia, Pennsylvania 19122, USA
| | - Puskar Bhattarai
- Department of Physics, Temple University, Philadelphia, Pennsylvania 19122, USA
| | - Chandra Shahi
- Department of Physics, Central Michigan University, Mount Pleasant, Michigan 48859, USA
| | - Mark R. Pederson
- Department of Physics, University of Texas at El Paso, El Paso, Texas 79968, USA
| | - Koblar A. Jackson
- Department of Physics, Central Michigan University, Mount Pleasant, Michigan 48859, USA
| | - John P. Perdew
- Department of Physics, Temple University, Philadelphia, Pennsylvania 19122, USA
- Department of Chemistry, Temple University, Philadelphia, Pennsylvania 19122, USA
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11
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Dereka B, Yu Q, Lewis NHC, Carpenter WB, Bowman JM, Tokmakoff A. Crossover from hydrogen to chemical bonding. Science 2021; 371:160-164. [DOI: 10.1126/science.abe1951] [Citation(s) in RCA: 66] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Accepted: 10/20/2020] [Indexed: 11/02/2022]
Affiliation(s)
- Bogdan Dereka
- Department of Chemistry, Institute for Biophysical Dynamics, and James Franck Institute, The University of Chicago, Chicago, IL 60637, USA
| | - Qi Yu
- Department of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, GA 30322, USA
| | - Nicholas H. C. Lewis
- Department of Chemistry, Institute for Biophysical Dynamics, and James Franck Institute, The University of Chicago, Chicago, IL 60637, USA
| | - William B. Carpenter
- Department of Chemistry, Institute for Biophysical Dynamics, and James Franck Institute, The University of Chicago, Chicago, IL 60637, USA
| | - Joel M. Bowman
- Department of Chemistry and Cherry L. Emerson Center for Scientific Computation, Emory University, Atlanta, GA 30322, USA
| | - Andrei Tokmakoff
- Department of Chemistry, Institute for Biophysical Dynamics, and James Franck Institute, The University of Chicago, Chicago, IL 60637, USA
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12
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Riera M, Hirales A, Ghosh R, Paesani F. Data-Driven Many-Body Models with Chemical Accuracy for CH4/H2O Mixtures. J Phys Chem B 2020; 124:11207-11221. [DOI: 10.1021/acs.jpcb.0c08728] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Affiliation(s)
- Marc Riera
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, United States
| | - Alan Hirales
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, United States
| | - Raja Ghosh
- 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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13
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Lambros E, Paesani F. How good are polarizable and flexible models for water: Insights from a many-body perspective. J Chem Phys 2020; 153:060901. [DOI: 10.1063/5.0017590] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Affiliation(s)
- Eleftherios Lambros
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, USA
| | - Francesco Paesani
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, USA
- Materials Science and Engineering, University of California San Diego, La Jolla, California 92093, USA
- San Diego Supercomputer Center, University of California San Diego, La Jolla, California 92093, USA
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14
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Egan CK, Bizzarro BB, Riera M, Paesani F. Correction to “Nature of Alkali Ion–Water Interactions: Insights from Many-Body Representations and Density Functional Theory. II”. J Chem Theory Comput 2020; 16:5422-5424. [DOI: 10.1021/acs.jctc.0c00713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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