1
|
O'Neill N, Shi BX, Fong K, Michaelides A, Schran C. To Pair or not to Pair? Machine-Learned Explicitly-Correlated Electronic Structure for NaCl in Water. J Phys Chem Lett 2024:6081-6091. [PMID: 38820256 DOI: 10.1021/acs.jpclett.4c01030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/02/2024]
Abstract
The extent of ion pairing in solution is an important phenomenon to rationalize transport and thermodynamic properties of electrolytes. A fundamental measure of this pairing is the potential of mean force (PMF) between solvated ions. The relative stabilities of the paired and solvent shared states in the PMF and the barrier between them are highly sensitive to the underlying potential energy surface. However, direct application of accurate electronic structure methods is challenging, since long simulations are required. We develop wave function based machine learning potentials with the random phase approximation (RPA) and second order Møller-Plesset (MP2) perturbation theory for the prototypical system of Na and Cl ions in water. We show both methods in agreement, predicting the paired and solvent shared states to have similar energies (within 0.2 kcal/mol). We also provide the same benchmarks for different DFT functionals as well as insight into the PMF based on simple analyses of the interactions in the system.
Collapse
Affiliation(s)
- Niamh O'Neill
- Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom
- Cavendish Laboratory, Department of Physics, University of Cambridge, Cambridge CB3 0HE, United Kingdom
- Lennard-Jones Centre, University of Cambridge, Trinity Ln, Cambridge CB2 1TN, United Kingdom
| | - Benjamin X Shi
- Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom
- Lennard-Jones Centre, University of Cambridge, Trinity Ln, Cambridge CB2 1TN, United Kingdom
| | - Kara Fong
- Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom
- Lennard-Jones Centre, University of Cambridge, Trinity Ln, Cambridge CB2 1TN, United Kingdom
| | - Angelos Michaelides
- Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom
- Lennard-Jones Centre, University of Cambridge, Trinity Ln, Cambridge CB2 1TN, United Kingdom
| | - Christoph Schran
- Cavendish Laboratory, Department of Physics, University of Cambridge, Cambridge CB3 0HE, United Kingdom
- Lennard-Jones Centre, University of Cambridge, Trinity Ln, Cambridge CB2 1TN, United Kingdom
| |
Collapse
|
2
|
Zhai Y, Rashmi R, Palos E, Paesani F. Many-body interactions and deep neural network potentials for water. J Chem Phys 2024; 160:144501. [PMID: 38587225 DOI: 10.1063/5.0203682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Accepted: 03/23/2024] [Indexed: 04/09/2024] Open
Abstract
We present a detailed assessment of deep neural network potentials developed within the Deep Potential Molecular Dynamics (DeePMD) framework and trained on the MB-pol data-driven many-body potential energy function. Specific focus is directed at the ability of DeePMD-based potentials to correctly reproduce the accuracy of MB-pol across various water systems. Analyses of bulk and interfacial properties as well as many-body interactions characteristic of water elucidate inherent limitations in the transferability and predictive accuracy of DeePMD-based potentials. These limitations can be traced back to an incomplete implementation of the "nearsightedness of electronic matter" principle, which may be common throughout machine learning potentials that do not include a proper representation of self-consistently determined long-range electric fields. These findings provide further support for the "short-blanket dilemma" faced by DeePMD-based potentials, highlighting the challenges in achieving a balance between computational efficiency and a rigorous, physics-based representation of the properties of water. Finally, we believe that our study contributes to the ongoing discourse on the development and application of machine learning models in simulating water systems, offering insights that could guide future improvements in the field.
Collapse
Affiliation(s)
- Yaoguang Zhai
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, USA
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, California 92093, USA
| | - Richa Rashmi
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, USA
| | - Etienne Palos
- 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
- Halicioğlu Data Science Institute, University of California San Diego, La Jolla, California 92093, USA
- San Diego Supercomputer Center, University of California San Diego, La Jolla, California 92093, USA
| |
Collapse
|
3
|
Frank HO, Paesani F. Molecular driving forces for water adsorption in MOF-808: A comparative analysis with UiO-66. J Chem Phys 2024; 160:094703. [PMID: 38426523 DOI: 10.1063/5.0189569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 02/12/2024] [Indexed: 03/02/2024] Open
Abstract
Metal-organic frameworks (MOFs), with their unique porous structures and versatile functionality, have emerged as promising materials for the adsorption, separation, and storage of diverse molecular species. In this study, we investigate water adsorption in MOF-808, a prototypical MOF that shares the same secondary building unit (SBU) as UiO-66, and elucidate how differences in topology and connectivity between the two MOFs influence the adsorption mechanism. To this end, molecular dynamics simulations were performed to calculate several thermodynamic and dynamical properties of water in MOF-808 as a function of relative humidity (RH), from the initial adsorption step to full pore filling. At low RH, the μ3-OH groups of the SBUs form hydrogen bonds with the initial water molecules entering the pores, which triggers the filling of these pores before the μ3-OH groups in other pores become engaged in hydrogen bonding with water molecules. Our analyses indicate that the pores of MOF-808 become filled by water sequentially as the RH increases. A similar mechanism has been reported for water adsorption in UiO-66. Despite this similarity, our study highlights distinct thermodynamic properties and framework characteristics that influence the adsorption process differently in MOF-808 and UiO-66.
Collapse
Affiliation(s)
- Hilliary O Frank
- 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
- Halicioğlu Data Science Institute, University of California, San Diego, La Jolla, California 92093, USA
- San Diego Supercomputer Center, University of California, San Diego, La Jolla, California 92093, USA
| |
Collapse
|
4
|
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.
Collapse
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
| |
Collapse
|
5
|
Kanungo B, Kaplan AD, Shahi C, Gavini V, Perdew JP. Unconventional Error Cancellation Explains the Success of Hartree-Fock Density Functional Theory for Barrier Heights. J Phys Chem Lett 2024; 15:323-328. [PMID: 38170179 DOI: 10.1021/acs.jpclett.3c03088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Energy barriers, which control the rates of chemical reactions, are seriously underestimated by computationally efficient semilocal approximations for the exchange-correlation energy. The accuracy of a semilocal density functional approximation is strongly boosted for reaction barrier heights by evaluating that approximation non-self-consistently on Hartree-Fock electron densities, which has been known for ∼30 years. The conventional explanation is that the Hartree-Fock theory yields the more accurate density. This work presents a benchmark Kohn-Sham inversion of accurate coupled-cluster densities for the reaction H2 + F → HHF → H + HF and finds a strong, understandable cancellation between positive (excessively overcorrected) density-driven and large negative functional-driven errors (expected from stretched radical bonds in the transition state) within this Hartree-Fock density functional theory. This confirms earlier conclusions (Kaplan, A. D., et al. J. Chem. Theory Comput. 2023, 19, 532-543) based on 76 barrier heights and three less reliable, but less expensive, fully nonlocal density functional proxies for the exact density.
Collapse
Affiliation(s)
- Bikash Kanungo
- Department of Mechanical Engineering, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - Aaron D Kaplan
- Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Chandra Shahi
- Department of Physics and Engineering Physics, Tulane University, New Orleans, Louisiana 70118, United States
| | - Vikram Gavini
- Department of Mechanical Engineering, University of Michigan, Ann Arbor, Michigan 48109, United States
| | - John P Perdew
- Department of Physics and Engineering Physics, Tulane University, New Orleans, Louisiana 70118, United States
| |
Collapse
|
6
|
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.
Collapse
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
| |
Collapse
|
7
|
Calegari Andrade M, Car R, Selloni A. Probing the self-ionization of liquid water with ab initio deep potential molecular dynamics. Proc Natl Acad Sci U S A 2023; 120:e2302468120. [PMID: 37931100 PMCID: PMC10655216 DOI: 10.1073/pnas.2302468120] [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: 02/12/2023] [Accepted: 09/29/2023] [Indexed: 11/08/2023] Open
Abstract
The chemical equilibrium between self-ionized and molecular water dictates the acid-base chemistry in aqueous solutions, yet understanding the microscopic mechanisms of water self-ionization remains experimentally and computationally challenging. Herein, Density Functional Theory (DFT)-based deep neural network (DNN) potentials are combined with enhanced sampling techniques and a global acid-base collective variable to perform extensive atomistic simulations of water self-ionization for model systems of increasing size. The explicit inclusion of long-range electrostatic interactions in the DNN potential is found to be crucial to accurately reproduce the DFT free energy profile of solvated water ion pairs in small (64 and 128 H2O) cells. The reversible work to separate the hydroxide and hydronium to a distance [Formula: see text] is found to converge for simulation cells containing more than 500 H2O, and a distance of [Formula: see text] 8 Å is the threshold beyond which the work to further separate the two ions becomes approximately zero. The slow convergence of the potential of mean force with system size is related to a restructuring of water and an increase of the local order around the water ions. Calculation of the dissociation equilibrium constant illustrates the key role of long-range electrostatics and entropic effects in the water autoionization process.
Collapse
Affiliation(s)
- Marcos Calegari Andrade
- Chemistry Department, Princeton University, Princeton, NJ08544
- Quantum Simulations Group, Materials Science Division, Lawrence Livermore National Laboratory, Livermore, CA94550
| | - Roberto Car
- Chemistry Department, Princeton University, Princeton, NJ08544
| | | |
Collapse
|
8
|
Palos E, Caruso A, Paesani F. Consistent density functional theory-based description of ion hydration through density-corrected many-body representations. J Chem Phys 2023; 159:181101. [PMID: 37947509 DOI: 10.1063/5.0174577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 10/23/2023] [Indexed: 11/12/2023] Open
Abstract
Delocalization error constrains the accuracy of density functional theory in describing molecular interactions in ion-water systems. Using Na+ and Cl- in water as model systems, we calculate the effects of delocalization error in the SCAN functional for describing ion-water and water-water interactions in hydrated ions, and demonstrate that density-corrected SCAN (DC-SCAN) predicts n-body and interaction energies with an accuracy approaching coupled cluster theory. The performance of DC-SCAN is size-consistent, maintaining an accurate description of molecular interactions well beyond the first solvation shell. Molecular dynamics simulations at ambient conditions with many-body MB-SCAN(DC) potentials, derived from the many-body expansion, predict the solvation structure of Na+ and Cl- in quantitative agreement with reference data, while simultaneously reproducing the structure of liquid water. Beyond rationalizing the accuracy of density-corrected models of ion hydration, our findings suggest that our unified density-corrected MB formalism holds great promise for efficient DFT-based simulations of condensed-phase systems with chemical accuracy.
Collapse
Affiliation(s)
- Etienne Palos
- Department of Chemistry and Biochemistry, 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
| | - 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
| |
Collapse
|
9
|
Riemelmoser S, Verdi C, Kaltak M, Kresse G. Machine Learning Density Functionals from the Random-Phase Approximation. J Chem Theory Comput 2023; 19:7287-7299. [PMID: 37800677 PMCID: PMC10601474 DOI: 10.1021/acs.jctc.3c00848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Indexed: 10/07/2023]
Abstract
Kohn-Sham density functional theory (DFT) is the standard method for first-principles calculations in computational chemistry and materials science. More accurate theories such as the random-phase approximation (RPA) are limited in application due to their large computational cost. Here, we use machine learning to map the RPA to a pure Kohn-Sham density functional. The machine learned RPA model (ML-RPA) is a nonlocal extension of the standard gradient approximation. The density descriptors used as ingredients for the enhancement factor are nonlocal counterparts of the local density and its gradient. Rather than fitting only RPA exchange-correlation energies, we also include derivative information in the form of RPA optimized effective potentials. We train a single ML-RPA functional for diamond, its surfaces, and liquid water. The accuracy of ML-RPA for the formation energies of 28 diamond surfaces reaches that of state-of-the-art van der Waals functionals. For liquid water, however, ML-RPA cannot yet improve upon the standard gradient approximation. Overall, our work demonstrates how machine learning can extend the applicability of the RPA to larger system sizes, time scales, and chemical spaces.
Collapse
Affiliation(s)
- Stefan Riemelmoser
- Faculty
of Physics and Center for Computational Materials Science, University of Vienna, Kolingasse 14-16, A-1090 Vienna, Austria
- Vienna
Doctoral School in Physics, University of
Vienna, Boltzmanngasse
5, A-1090 Vienna, Austria
| | - Carla Verdi
- Faculty
of Physics and Center for Computational Materials Science, University of Vienna, Kolingasse 14-16, A-1090 Vienna, Austria
- School
of Physics, The University of Sydney, Sydney, New South Wales 2006, Australia
- School
of Mathematics and Physics, The University
of Queensland, Brisbane, Queensland 4072, Australia
| | - Merzuk Kaltak
- VASP
Software GmbH, Sensengasse
8/12, A-1090 Vienna, Austria
| | - Georg Kresse
- Faculty
of Physics and Center for Computational Materials Science, University of Vienna, Kolingasse 14-16, A-1090 Vienna, Austria
- VASP
Software GmbH, Sensengasse
8/12, A-1090 Vienna, Austria
| |
Collapse
|
10
|
Yu H, Song S, Nam S, Burke K, Sim E. Density-Corrected Density Functional Theory for Open Shells: How to Deal with Spin Contamination. J Phys Chem Lett 2023; 14:9230-9237. [PMID: 37811877 DOI: 10.1021/acs.jpclett.3c02017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Density functional theory (DFT) is usually used self-consistently to predict chemical properties, but the use of the Hartree-Fock (HF) density improves energetics in certain, well-characterized cases. Density-corrected (DC) DFT provides the theory behind this, but unrestricted Hartree-Fock (UHF) densities yield poor energetics in cases of strong spin contamination. Here we compare with restricted open-shell HF (ROHF) across 13 different functionals and two DC-DFT methods. For significant spin contamination, ROHF densities outperform UHF densities by as much as a factor of 3, depending on the energy functional, and ROHF-DFT improves over self-consistent DFT for most of the tested functionals. We refine the DC(HF)-DFT algorithm to use ROHF densities in cases of severe spin contamination.
Collapse
Affiliation(s)
- Hayoung Yu
- Department of Chemistry, Yonsei University, 50 Yonsei-ro Seodaemun-gu, Seoul 03722, Korea
| | - Suhwan Song
- Department of Chemistry, Yonsei University, 50 Yonsei-ro Seodaemun-gu, Seoul 03722, Korea
| | - Seungsoo Nam
- Department of Chemistry, Yonsei University, 50 Yonsei-ro Seodaemun-gu, Seoul 03722, Korea
| | - Kieron Burke
- Department of Chemistry, University of California, Irvine, California 92697, United States
| | - Eunji Sim
- Department of Chemistry, Yonsei University, 50 Yonsei-ro Seodaemun-gu, Seoul 03722, Korea
| |
Collapse
|
11
|
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.
Collapse
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
| |
Collapse
|
12
|
Cinq N, Simon A, Louisnard F, Cuny J. Accurate SCC-DFTB Parametrization of Liquid Water with Improved Atomic Charges and Iterative Boltzmann Inversion. J Phys Chem B 2023; 127:7590-7601. [PMID: 37603798 DOI: 10.1021/acs.jpcb.3c03479] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/23/2023]
Abstract
This work presents improvements of the description of liquid water within the self-consistent-charge density-functional based tight-binding scheme combining the use of Weighted Mulliken (WMull) charges and optimized O-H repulsive potential through the iterative Boltzmann inversion (IBI) process. The quality of the newly developed models is validated considering pair radial distribution functions (RDFs), as well as other structural, energetic, thermodynamic, and dynamic properties. The use of WMull charges certainly improves the agreement with experimental data, however leading to over-structured RDFs at short distance, that can be further improved by considering an optimized O-H repulsive potential obtained by the IBI process. Three different schemes were used to optimize this potential: (i) optimization including short O-H distances. This led to accurate RDFs as well as improved self-diffusion coefficient and heat of vaporization, while the proton transfer energy barrier is severely deteriorated; (ii) optimization starting at long distance. The proton transfer energy barrier is recovered while the heat of vaporization is deteriorated and the O-H RDF is less accurate at short distance; (iii) optimization within the path-integral molecular dynamics scheme which allows us to exclude nuclear quantum effects from the repulsive potential. The latter potential, in conjunction with the WMull improved atomic charges, provides similar results as (i) for structural, dynamic, and thermodynamic properties while recovering a large part of the proton transfer energy barrier. It therefore offers a good compromise to study both dynamic properties and chemistry within liquid water at a quantum chemical level.
Collapse
Affiliation(s)
- Nicolas Cinq
- Laboratoire de Chimie et Physique Quantiques (LCPQ), FeRMI Institute, Université de Toulouse [UT3] and CNRS, Toulouse F-31062, France
| | - Aude Simon
- Laboratoire de Chimie et Physique Quantiques (LCPQ), FeRMI Institute, Université de Toulouse [UT3] and CNRS, Toulouse F-31062, France
| | - Fernand Louisnard
- Laboratoire de Chimie et Physique Quantiques (LCPQ), FeRMI Institute, Université de Toulouse [UT3] and CNRS, Toulouse F-31062, France
| | - Jérôme Cuny
- Laboratoire de Chimie et Physique Quantiques (LCPQ), FeRMI Institute, Université de Toulouse [UT3] and CNRS, Toulouse F-31062, France
| |
Collapse
|
13
|
Graf D, Thom AJW. Simple and Efficient Route toward Improved Energetics within the Framework of Density-Corrected Density Functional Theory. J Chem Theory Comput 2023; 19:5427-5438. [PMID: 37525457 PMCID: PMC10448722 DOI: 10.1021/acs.jctc.3c00441] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2023] [Indexed: 08/02/2023]
Abstract
The crucial step in density-corrected Hartree-Fock density functional theory (DC(HF)-DFT) is to decide whether the density produced by the density functional for a specific calculation is erroneous and, hence, should be replaced by, in this case, the HF density. We introduce an indicator, based on the difference in noninteracting kinetic energies between DFT and HF calculations, to determine when the HF density is the better option. Our kinetic energy indicator directly compares the self-consistent density of the analyzed functional with the HF density, is size-intensive, reliable, and most importantly highly efficient. Moreover, we present a procedure that makes best use of the computed quantities necessary for DC(HF)-DFT by additionally evaluating a related hybrid functional and, in that way, not only "corrects" the density but also the functional itself; we call that procedure corrected Hartree-Fock density functional theory (C(HF)-DFT).
Collapse
Affiliation(s)
- Daniel Graf
- Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, United Kingdom
| | - Alex J. W. Thom
- Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, United Kingdom
| |
Collapse
|
14
|
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.
Collapse
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.
| |
Collapse
|
15
|
A cyclodextrin-based reagent for cis/trans-geometrical isomers separation by mobility measurements and chemical calculations. Food Chem 2023; 406:135027. [PMID: 36493573 DOI: 10.1016/j.foodchem.2022.135027] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 11/16/2022] [Accepted: 11/19/2022] [Indexed: 12/03/2022]
Abstract
Identification of cis/trans-carbon-carbon double-bond (CC) isomers remain challenging. Herein, a simple and rapid method for the separation and analysis of cis/trans-maleic acid (MA) and aconitic acid (AA) using Trapped Ion Mobility Spectrometry (TIMS) was developed. α-, β-, γ-cyclodextrin (CD) were served as the separation reagent, slight difference in mobility separation was obtained by [CD-MA/AA-H]-. Specially, with the addition of divalent metal ion (G2+) as coordination metal ion, the separation effect was much increased by [CD-MA/AA + G-H]+, and α-CD has better mobility separation effect than β-/γ-CD. Moreover, chemical calculations revealed the binary and ternary complexes are in the inclusion forms, and microscopic interactions between cis/trans-MA/AA, CDs, and G2+ are somewhat different that making their mobility separation. Finally, quantifications of cis/trans-isomers were analyzed in food samples, with good linearity (R2 > 0.99) and recoveries obtained from 87.25 % to 100.73 %.
Collapse
|
16
|
Essential Oil of Origanum vulgare as a Green Corrosion Inhibitor for Carbon Steel in Acidic Medium. ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2023. [DOI: 10.1007/s13369-023-07693-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/11/2023]
Abstract
AbstractIn this study, Oregano (Origanum vulgare) leaf essential oil was studied as an environmental-friendly anticorrosion agent for carbon steel in aggressive hydrochloric acid. The corrosion inhibition of O. vulgare was characterized by surface morphology, electrochemical, weight loss, theoretical and computational methods. It was found that the highest inhibition performance of O. vulgare was 85.64% at 2 g/l in 1 M HCl. The results of Langmuir isotherm and adsorption thermodynamics investigation demonstrated that the O. vulgare inhibitor adsorbed on the metal surface by the formation of rigid covalent bonds. The adsorption and inhibition centers of the selected inhibitor were studied by the computational methods, resulting in that the hydroxyl functional groups and benzoyl rings are mainly responsible for the high inhibition efficiency.
Collapse
|
17
|
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.
Collapse
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
| |
Collapse
|
18
|
Chen Z, Liu Z, Xu X. Accurate descriptions of molecule-surface interactions in electrocatalytic CO 2 reduction on the copper surfaces. Nat Commun 2023; 14:936. [PMID: 36807556 PMCID: PMC9941474 DOI: 10.1038/s41467-023-36695-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 02/14/2023] [Indexed: 02/22/2023] Open
Abstract
Copper-based catalysts play a pivotal role in many industrial processes and hold a great promise for electrocatalytic CO2 reduction reaction into valuable chemicals and fuels. Towards the rational design of catalysts, the growing demand on theoretical study is seriously at odds with the low accuracy of the most widely used functionals of generalized gradient approximation. Here, we present results using a hybrid scheme that combines the doubly hybrid XYG3 functional and the periodic generalized gradient approximation, whose accuracy is validated against an experimental set on copper surfaces. A near chemical accuracy is established for this set, which, in turn, leads to a substantial improvement for the calculated equilibrium and onset potentials as against the experimental values for CO2 reduction to CO on Cu(111) and Cu(100) electrodes. We anticipate that the easy use of the hybrid scheme will boost the predictive power for accurate descriptions of molecule-surface interactions in heterogeneous catalysis.
Collapse
Affiliation(s)
- Zheng Chen
- grid.8547.e0000 0001 0125 2443Collaborative Innovation Center of Chemistry for Energy Materials, Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, MOE Key Laboratory of Computational Physical Sciences, Department of Chemistry, Fudan University, 200433 Shanghai, People’s Republic of China
| | - Zhangyun Liu
- grid.8547.e0000 0001 0125 2443Collaborative Innovation Center of Chemistry for Energy Materials, Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, MOE Key Laboratory of Computational Physical Sciences, Department of Chemistry, Fudan University, 200433 Shanghai, People’s Republic of China
| | - Xin Xu
- Collaborative Innovation Center of Chemistry for Energy Materials, Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, MOE Key Laboratory of Computational Physical Sciences, Department of Chemistry, Fudan University, 200433, Shanghai, People's Republic of China. .,Hefei National Laboratory, 230088, Hefei, P. R. China.
| |
Collapse
|
19
|
Ruan S, Jackson KA, Ruzsinszky A. Spin-crossover complexes: Self-interaction correction vs density correction. J Chem Phys 2023; 158:064303. [PMID: 36792493 DOI: 10.1063/5.0128950] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
Complexes containing a transition metal atom with a 3d4-3d7 electron configuration typically have two low-lying, high-spin (HS) and low-spin (LS) states. The adiabatic energy difference between these states, known as the spin-crossover energy, is small enough to pose a challenge even for electronic structure methods that are well known for their accuracy and reliability. In this work, we analyze the quality of electronic structure approximations for spin-crossover energies of iron complexes with four different ligands by comparing energies from self-consistent and post-self-consistent calculations for methods based on the random phase approximation and the Fermi-Löwdin self-interaction correction. Considering that Hartree-Fock densities were found by Song et al., J. Chem. Theory Comput. 14, 2304 (2018), to eliminate the density error to a large extent, and that the Hartree-Fock method and the Perdew-Zunger-type self-interaction correction share some physics, we compare the densities obtained with these methods to learn their resemblance. We find that evaluating non-empirical exchange-correlation energy functionals on the corresponding self-interaction-corrected densities can mitigate the strong density errors and improves the accuracy of the adiabatic energy differences between HS and LS states.
Collapse
Affiliation(s)
- Shiqi Ruan
- Department of Physics, Temple University, Philadelphia, Pennsylvania 19122, USA
| | - Koblar A Jackson
- Physics Department and Science of Advanced Materials Ph. D. Program, Central Michigan University, Mount Pleasant, Michigan 48858, USA
| | - Adrienn Ruzsinszky
- Department of Physics, Temple University, Philadelphia, Pennsylvania 19122, USA
| |
Collapse
|
20
|
Song S, Vuckovic S, Kim Y, Yu H, Sim E, Burke K. Extending density functional theory with near chemical accuracy beyond pure water. Nat Commun 2023; 14:799. [PMID: 36781855 PMCID: PMC9925738 DOI: 10.1038/s41467-023-36094-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 01/13/2023] [Indexed: 02/15/2023] Open
Abstract
Density functional simulations of condensed phase water are typically inaccurate, due to the inaccuracies of approximate functionals. A recent breakthrough showed that the SCAN approximation can yield chemical accuracy for pure water in all its phases, but only when its density is corrected. This is a crucial step toward first-principles biosimulations. However, weak dispersion forces are ubiquitous and play a key role in noncovalent interactions among biomolecules, but are not included in the new approach. Moreover, naïve inclusion of dispersion in HF-SCAN ruins its high accuracy for pure water. Here we show that systematic application of the principles of density-corrected DFT yields a functional (HF-r2SCAN-DC4) which recovers and not only improves over HF-SCAN for pure water, but also captures vital noncovalent interactions in biomolecules, making it suitable for simulations of solutions.
Collapse
Affiliation(s)
- Suhwan Song
- grid.15444.300000 0004 0470 5454Department of Chemistry, Yonsei University, 50 Yonsei-ro Seodaemun-gu, Seoul, 03722 Korea ,grid.266093.80000 0001 0668 7243Department of Chemistry, University of California, Irvine, CA 92697 USA
| | - Stefan Vuckovic
- grid.472716.10000 0004 1758 7362Institute for Microelectronics and Microsystems (CNR-IMM), Via Monteroni, Campus Unisalento, 73100 Lecce, Italy ,grid.12380.380000 0004 1754 9227Departments of Chemistry & Pharmaceutical Sciences and Amsterdam Institute of Molecular and Life Sciences (AIMMS), Faculty of Science, Vrije Universiteit, De Boelelaan 1083, 1081HV Amsterdam, The Netherlands
| | - Youngsam Kim
- grid.15444.300000 0004 0470 5454Department of Chemistry, Yonsei University, 50 Yonsei-ro Seodaemun-gu, Seoul, 03722 Korea
| | - Hayoung Yu
- grid.15444.300000 0004 0470 5454Department of Chemistry, Yonsei University, 50 Yonsei-ro Seodaemun-gu, Seoul, 03722 Korea
| | - Eunji Sim
- Department of Chemistry, Yonsei University, 50 Yonsei-ro Seodaemun-gu, Seoul, 03722, Korea.
| | - Kieron Burke
- grid.266093.80000 0001 0668 7243Department of Chemistry, University of California, Irvine, CA 92697 USA ,grid.266093.80000 0001 0668 7243Departments of Physics & Astronomy, University of California, Irvine, CA 92697 USA
| |
Collapse
|
21
|
Kaplan AD, Shahi C, Bhetwal P, Sah RK, Perdew JP. Understanding Density-Driven Errors for Reaction Barrier Heights. J Chem Theory Comput 2023; 19:532-543. [PMID: 36599075 DOI: 10.1021/acs.jctc.2c00953] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Delocalization errors, such as charge-transfer and some self-interaction errors, plague computationally efficient and otherwise accurate density functional approximations (DFAs). Evaluating a semilocal DFA non-self-consistently on the Hartree-Fock (HF) density is often recommended as a computationally inexpensive remedy for delocalization errors. For sophisticated meta-GGAs like SCAN, this approach can achieve remarkable accuracy. This HF-DFT (also known as DFA@HF) is often presumed to work, when it significantly improves over the DFA, because the HF density is more accurate than the self-consistent DFA density in those cases. By applying the metrics of density-corrected density functional theory (DFT), we show that HF-DFT works for barrier heights by making a localizing charge-transfer error or density overcorrection, thereby producing a somewhat reliable cancellation of density- and functional-driven errors for the energy. A quantitative analysis of the charge-transfer errors in a few randomly selected transition states confirms this trend. We do not have the exact functional and electron densities that would be needed to evaluate the exact density- and functional-driven errors for the large BH76 database of barrier heights. Instead, we have identified and employed three fully nonlocal proxy functionals (SCAN 50% global hybrid, range-separated hybrid LC-ωPBE, and SCAN-FLOSIC) and their self-consistent proxy densities. These functionals are chosen because they yield reasonably accurate self-consistent barrier heights and because their self-consistent total energies are nearly piecewise linear in fractional electron number─two important points of similarity to the exact functional. We argue that density-driven errors of the energy in a self-consistent density functional calculation are second order in the density error and that large density-driven errors arise primarily from incorrect electron transfers over length scales larger than the diameter of an atom.
Collapse
Affiliation(s)
- Aaron D Kaplan
- Department of Physics, Temple University, Philadelphia, Pennsylvania19122, United States
| | - Chandra Shahi
- Department of Physics, Temple University, Philadelphia, Pennsylvania19122, United States
| | - Pradeep Bhetwal
- Department of Physics, Temple University, Philadelphia, Pennsylvania19122, United States
| | - Raj K Sah
- Department of Physics, Temple University, Philadelphia, Pennsylvania19122, United States
| | - John P Perdew
- Department of Physics, Temple University, Philadelphia, Pennsylvania19122, United States
- Department of Chemistry, Temple University, Philadelphia, Pennsylvania19122, United States
| |
Collapse
|
22
|
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.
Collapse
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
| |
Collapse
|
23
|
Rana B, Beran GJO, Herbert JM. Correcting π-delocalisation errors in conformational energies using density-corrected DFT, with application to crystal polymorphs. Mol Phys 2022. [DOI: 10.1080/00268976.2022.2138789] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022]
Affiliation(s)
- Bhaskar Rana
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH, USA
| | | | - John M. Herbert
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH, USA
| |
Collapse
|
24
|
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.
Collapse
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
| |
Collapse
|
25
|
Méndez E, Videla PE, Laria D. Equilibrium and Dynamical Characteristics of Hydrogen Bond Bifurcations in Water-Water and Water-Ammonia Dimers: A Path Integral Molecular Dynamics Study. J Phys Chem A 2022; 126:4721-4733. [PMID: 35834556 DOI: 10.1021/acs.jpca.2c02525] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
We present path integral molecular dynamics results that describe the effects of nuclear quantum fluctuations on equilibrium and dynamical characteristics pertaining to bifurcation pathways in hydrogen bonded dimers combining water and ammonia, at cryogenic temperatures of the order of 20 K. Along these isomerizations, the hydrogen atoms in the molecules acting as hydrogen-bond donors interchange their original dangling/connective characters. Our results reveal that the resulting quantum transition paths comprise three stages: the initial and final ones involve overall rotations during which the two protons retain their classical-like characteristics. Effects from quantum fluctuation are clearly manifested in the changes operated at the intermediate passages over transition states, as the spatial extents of the protons stretch over typical lengths comparable to the distances between connective and dangling basins of attractions. Consequently, the classical over-the-hill path is replaced by a tunneling controlled mechanism which, within the path integral perspective, can be cast in terms of concerted inter-basin migrations of polymer beads from dangling-to-connective and from connective-to-dangling, at practically no energy costs. We also estimated the characteristic timescales describing such interconversions within the approximate ring polymer rate theory. Effects derived from full and partial deuteration are also discussed.
Collapse
Affiliation(s)
- Emilio Méndez
- Departamento de Química Inorgánica, Analítica y Química-Física and INQUIMAE-CONICET, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires Ciudad Universitaria, Pabellón II, 1428 Buenos Aires, Argentina
| | - Pablo E Videla
- Department of Chemistry and Energy Sciences Institute, Yale University, 225 Prospect Street, New Haven, Connecticut 06520, United States
| | - Daniel Laria
- Departamento de Física de la Materia Condensada, Comisión Nacional de Energía Atómica, Avenida Libertador 8250, 1429 Buenos Aires, Argentina
| |
Collapse
|
26
|
Dasgupta S, Shahi C, Bhetwal P, Perdew JP, Paesani F. How Good Is the Density-Corrected SCAN Functional for Neutral and Ionic Aqueous Systems, and What Is So Right about the Hartree-Fock Density? J Chem Theory Comput 2022; 18:4745-4761. [PMID: 35785808 DOI: 10.1021/acs.jctc.2c00313] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Density functional theory (DFT) is the most widely used electronic structure method, due to its simplicity and cost effectiveness. The accuracy of a DFT calculation depends not only on the choice of the density functional approximation (DFA) adopted but also on the electron density produced by the DFA. SCAN is a modern functional that satisfies all known constraints for meta-GGA functionals. The density-driven errors, defined as energy errors arising from errors of the self-consistent DFA electron density, can hinder SCAN from achieving chemical accuracy in some systems, including water. Density-corrected DFT (DC-DFT) can alleviate this shortcoming by adopting a more accurate electron density which, in most applications, is the electron density obtained at the Hartree-Fock level of theory due to its relatively low computational cost. In this work, we present extensive calculations aimed at determining the accuracy of the DC-SCAN functional for various aqueous systems. DC-SCAN (SCAN@HF) shows remarkable consistency in reproducing reference data obtained at the coupled cluster level of theory, with minimal loss of accuracy. Density-driven errors in the description of ionic aqueous clusters are thoroughly investigated. By comparison with the orbital-optimized CCD density in the water dimer, we find that the self-consistent SCAN density transfers a spurious fraction of an electron across the hydrogen bond to the hydrogen atom (H*, covalently bound to the donor oxygen atom) from the acceptor (OA) and donor (OD) oxygen atoms, while HF makes a much smaller spurious transfer in the opposite direction, consistent with DC-SCAN (SCAN@HF) reduction of SCAN overbinding due to delocalization error. While LDA seems to be the conventional extreme of density delocalization error, and HF the conventional extreme of (usually much smaller) density localization error, these two densities do not quite yield the conventional range of density-driven error in energy differences. Finally, comparisons of the DC-SCAN results with those obtained with the Fermi-Löwdin orbital self-interaction correction (FLOSIC) method show that DC-SCAN represents a more accurate approach to reducing density-driven errors in SCAN calculations of ionic aqueous clusters. While the HF density is superior to that of SCAN for noncompact water clusters, the opposite is true for the compact water molecule with exactly 10 electrons.
Collapse
Affiliation(s)
- Saswata Dasgupta
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, United States
| | - Chandra Shahi
- Department of Physics, Temple University, Philadelphia, Pennsylvania 19122, United States
| | - Pradeep Bhetwal
- Department of Physics, Temple University, Philadelphia, Pennsylvania 19122, United States
| | - John P Perdew
- Department of Physics, Temple University, Philadelphia, Pennsylvania 19122, United States.,Department of Chemistry, Temple University, Philadelphia, Pennsylvania 19122, 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
| |
Collapse
|
27
|
Bryenton KR, Adeleke AA, Dale SG, Johnson ER. Delocalization error: The greatest outstanding challenge in density‐functional theory. WIRES COMPUTATIONAL MOLECULAR SCIENCE 2022. [DOI: 10.1002/wcms.1631] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Affiliation(s)
- Kyle R. Bryenton
- Department of Physics and Atmospheric Science Dalhousie University Halifax Nova Scotia Canada
| | | | - Stephen G. Dale
- Queensland Micro‐ and Nanotechnology Centre Griffith University Nathan Queensland Australia
| | - Erin R. Johnson
- Department of Physics and Atmospheric Science Dalhousie University Halifax Nova Scotia Canada
- Department of Chemistry Dalhousie University Halifax Nova Scotia Canada
| |
Collapse
|
28
|
Liu J, Lan J, He X. Toward High-level Machine Learning Potential for Water Based on Quantum Fragmentation and Neural Networks. J Phys Chem A 2022; 126:3926-3936. [PMID: 35679610 DOI: 10.1021/acs.jpca.2c00601] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Accurate and efficient simulation of liquids, such as water and salt solutions, using high-level wave function theories is still a formidable task for computational chemists owing to the high computational costs. In this study, we develop a deep machine learning potential based on fragment-based second-order Møller-Plesset perturbation theory (DP-MP2) for water through neural networks. We show that the DP-MP2 potential predicts the structural, dynamical, and thermodynamic properties of liquid water in better agreement with the experimental data than previous studies based on density functional theory (DFT). The nuclear quantum effects (NQEs) on the properties of liquid water are also examined, which are noticeable in affecting the structural and dynamical properties of liquid water under ambient conditions. This work provides a general framework for quantitative predictions of the properties of condensed-phase systems with the accuracy of high-level wave function theory while achieving significant computational savings compared to ab initio simulations.
Collapse
Affiliation(s)
- Jinfeng Liu
- Department of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing 210009, China.,Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, Shanghai Frontiers Science Center of Molecule Intelligent Syntheses, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China
| | - Jinggang Lan
- Chaire de Simulation à l'Echelle Atomique (CSEA), Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Xiao He
- Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, Shanghai Frontiers Science Center of Molecule Intelligent Syntheses, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China.,New York University-East China Normal University Center for Computational Chemistry, NYU Shanghai, Shanghai 200062, China
| |
Collapse
|
29
|
Rana B, Coons MP, Herbert JM. Detection and Correction of Delocalization Errors for Electron and Hole Polarons Using Density-Corrected DFT. J Phys Chem Lett 2022; 13:5275-5284. [PMID: 35674719 DOI: 10.1021/acs.jpclett.2c01187] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Modeling polaron defects is an important aspect of computational materials science, but the description of unpaired spins in density functional theory (DFT) often suffers from delocalization error. To diagnose and correct the overdelocalization of spin defects, we report an implementation of density-corrected (DC-)DFT and its analytic energy gradient. In DC-DFT, an exchange-correlation functional is evaluated using a Hartree-Fock density, thus incorporating electron correlation while avoiding self-interaction error. Results for an electron polaron in models of titania and a hole polaron in Al-doped silica demonstrate that geometry optimization with semilocal functionals drives significant structural distortion, including the elongation of several bonds, such that subsequent single-point calculations with hybrid functionals fail to afford a localized defect even in cases where geometry optimization with the hybrid functional does localize the polaron. This has significant implications for traditional workflows in computational materials science, where semilocal functionals are often used for structure relaxation. DC-DFT calculations provide a mechanism to detect situations where delocalization error is likely to affect the results.
Collapse
Affiliation(s)
- Bhaskar Rana
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States
| | - Marc P Coons
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States
| | - John M Herbert
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States
| |
Collapse
|
30
|
Tran H, Toland A, Stellmach K, Paul MK, Gutekunst W, Ramprasad R. Toward Recyclable Polymers: Ring-Opening Polymerization Enthalpy from First-Principles. J Phys Chem Lett 2022; 13:4778-4785. [PMID: 35613074 DOI: 10.1021/acs.jpclett.2c00995] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Ring-opening polymerization (ROP) enthalpy ΔHROP is an important thermodynamic property controlling the polymerization of cyclic monomers. While ΔHROP can be measured, computing ΔHROP for realistic polymer systems with an error of ≃5-10 kJ/mol is critical for designing new monomer systems for depolymerizable polymers. We have developed a first-principles computational scheme in which multiple challenges in computing ΔHROP are resolved definitively including extensive exploration of conformational states and adequately addressing finite size effects. This scheme is validated on a diverse benchmark set of 42 ROP polymers for which reliable experimental values of ΔHROP are available. For this set, the ΔHROP root-mean-square error is ≃7 kJ/mol, about 3-times smaller than conventional approaches. This development opens up new pathways to build up a high-quality database of ΔHROP for downstream predictive machine-learning models and ultimately to accelerate the design of depolymerizable polymers with desired properties.
Collapse
Affiliation(s)
- Huan Tran
- School of Materials Science and Engineering, Georgia Institute of Technology, 771 Ferst Drive Northwest, Atlanta, Georgia 30332, United States
| | - Aubrey Toland
- School of Materials Science and Engineering, Georgia Institute of Technology, 771 Ferst Drive Northwest, Atlanta, Georgia 30332, United States
| | - Kellie Stellmach
- School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - McKinley K Paul
- School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Will Gutekunst
- School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Rampi Ramprasad
- School of Materials Science and Engineering, Georgia Institute of Technology, 771 Ferst Drive Northwest, Atlanta, Georgia 30332, United States
| |
Collapse
|
31
|
Palos E, Lambros E, Swee S, Hu J, Dasgupta S, Paesani F. Assessing the Interplay between Functional-Driven and Density-Driven Errors in DFT Models of Water. J Chem Theory Comput 2022; 18:3410-3426. [PMID: 35506889 DOI: 10.1021/acs.jctc.2c00050] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
We investigate the interplay between functional-driven and density-driven errors in different density functional approximations within density functional theory (DFT) and the implications of these errors for simulations of water with DFT-based data-driven potentials. Specifically, we quantify density-driven errors in two widely used dispersion-corrected functionals derived within the generalized gradient approximation (GGA), namely BLYP-D3 and revPBE-D3, and two modern meta-GGA functionals, namely strongly constrained and appropriately normed (SCAN) and B97M-rV. The effects of functional-driven and density-driven errors on the interaction energies are first assessed for the water clusters of the BEGDB dataset. Further insights into the nature of functional-driven errors are gained from applying the absolutely localized molecular orbital energy decomposition analysis (ALMO-EDA) to the interaction energies, which demonstrates that functional-driven errors are strongly correlated with the nature of the interactions. We discuss cases where density-corrected DFT (DC-DFT) models display higher accuracy than the original DFT models and cases where reducing the density-driven errors leads to larger deviations from the reference energies due to the presence of large functional-driven errors. Finally, molecular dynamics simulations are performed with data-driven many-body potentials derived from DFT and DC-DFT data to determine the effect that minimizing density-driven errors has on the description of liquid water. Besides rationalizing the performance of widely used DFT models of water, we believe that our findings unveil fundamental relations between the shortcomings of some common DFT approximations and the requirements for accurate descriptions of molecular interactions, which will aid the development of a consistent, DFT-based framework for the development of data-driven and machine-learned potentials for simulations of condensed-phase systems.
Collapse
Affiliation(s)
- Etienne Palos
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, United States
| | - Eleftherios Lambros
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, United States
| | - Steven Swee
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, United States
| | - Jie Hu
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, United States
| | - Saswata Dasgupta
- 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
| |
Collapse
|
32
|
Palos E, Lambros E, Dasgupta S, Paesani F. Density Functional Theory of Water with the Machine-Learned DM21 Functional. J Chem Phys 2022; 156:161103. [DOI: 10.1063/5.0090862] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
The delicate interplay between functional-driven and density-driven errors in density functional theory (DFT) has hindered traditional density functional approximations (DFAs) from providing an accurate description of water for over 30 years. Recently, the deep-learned DeepMind 21 (DM21) functional has been shown to overcome the limitations of traditional DFAs as it is free of delocalization error. To determine if DM21 can enable a molecular-level description of the physical properties of aqueous systems within Kohn-Sham DFT, we assess the accuracy of the DM21 functional for neutral, protonated, and deprotonated water clusters. We find that the ability of DM21 to accurately predict the energetics of aqueous clusters varies significantly with cluster size. Additionally, we introduce the many-body MB-DM21 potential derived from DM21 data within the many-body expansion of the energy and use it in simulations of liquid water as a function of temperature at ambient pressure. We find that size-dependent functional-driven errors identified in the analysis of the energetics of small clusters calculated with the DM21 functional result in the MB-DM21 potential systematically overestimating the hydrogen-bond strength and, consequently, predicting a more ice-like local structure of water at room temperature.
Collapse
Affiliation(s)
- Etienne Palos
- Chemistry and Biochemistry, University of California San Diego, United States of America
| | | | | | | |
Collapse
|
33
|
Withanage KPK, Sharkas K, Johnson JK, Perdew JP, Peralta JE, Jackson KA. Fermi–Löwdin orbital self-interaction correction of adsorption energies on transition metal ions. J Chem Phys 2022; 156:134102. [DOI: 10.1063/5.0078970] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
Density functional theory (DFT)-based descriptions of the adsorption of small molecules on transition metal ions are prone to self-interaction errors. Here, we show that such errors lead to a large over-estimation of adsorption energies of small molecules on Cu+, Zn+, Zn2+, and Mn+ in local spin density approximation (LSDA) and Perdew, Burke, Ernzerhof (PBE) generalized gradient approximation calculations compared to reference values computed using the coupled-cluster with single, doubles, and perturbative triple excitations method. These errors are significantly reduced by removing self-interaction using the Perdew–Zunger self-interaction correction (PZ-SIC) in the Fermi–Löwdin Orbital (FLO) SIC framework. In the case of FLO-PBE, typical errors are reduced to less than 0.1 eV. Analysis of the results using DFT energies evaluated on self-interaction-corrected densities [DFT(@FLO)] indicates that the density-driven contributions to the FLO-DFT adsorption energy corrections are roughly the same size in DFT = LSDA and PBE, but the total corrections due to removing self-interaction are larger in LSDA.
Collapse
Affiliation(s)
- Kushantha P. K. Withanage
- Department of Physics and Science of Advanced Materials Program, Central Michigan University, Mount Pleasant, Michigan 48859, USA
- Department of Physics, University of Texas at El Paso, El Paso, Texas 79968, USA
| | - Kamal Sharkas
- Department of Physics, Central Michigan University, Mount Pleasant, Michigan 48859, USA
| | - J. Karl Johnson
- Department of Chemical and Petroleum Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, USA
| | - John P. Perdew
- Department of Physics and Department of Chemistry, Temple University, Philadelphia, Pennsylvania 19122, USA
| | - Juan E. Peralta
- Department of Physics and Science of Advanced Materials Program, Central Michigan University, Mount Pleasant, Michigan 48859, USA
| | - Koblar A. Jackson
- Department of Physics and Science of Advanced Materials Program, Central Michigan University, Mount Pleasant, Michigan 48859, USA
| |
Collapse
|
34
|
Sim E, Song S, Vuckovic S, Burke K. Improving Results by Improving Densities: Density-Corrected Density Functional Theory. J Am Chem Soc 2022; 144:6625-6639. [PMID: 35380807 DOI: 10.1021/jacs.1c11506] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Density functional theory (DFT) calculations have become widespread in both chemistry and materials, because they usually provide useful accuracy at much lower computational cost than wavefunction-based methods. All practical DFT calculations require an approximation to the unknown exchange-correlation energy, which is then used self-consistently in the Kohn-Sham scheme to produce an approximate energy from an approximate density. Density-corrected DFT is simply the study of the relative contributions to the total energy error. In the vast majority of DFT calculations, the error due to the approximate density is negligible. But with certain classes of functionals applied to certain classes of problems, the density error is sufficiently large as to contribute to the energy noticeably, and its removal leads to much better results. These problems include reaction barriers, torsional barriers involving π-conjugation, halogen bonds, radicals and anions, most stretched bonds, etc. In all such cases, use of a more accurate density significantly improves performance, and often the simple expedient of using the Hartree-Fock density is enough. This Perspective explains what DC-DFT is, where it is likely to improve results, and how DC-DFT can produce more accurate functionals. We also outline challenges and prospects for the field.
Collapse
Affiliation(s)
- Eunji Sim
- Department of Chemistry, Yonsei University, 50 Yonsei-ro Seodaemun-gu, Seoul 03722, Korea
| | - Suhwan Song
- Department of Chemistry, Yonsei University, 50 Yonsei-ro Seodaemun-gu, Seoul 03722, Korea
| | - Stefan Vuckovic
- Institute for Microelectronics and Microsystems (CNR-IMM), Via Monteroni,Campus Unisalento, 73100 Lecce, Italy.,Department of Chemistry & Pharmaceutical Sciences and Amsterdam Institute of Molecular and Life Sciences (AIMMS), Faculty of Science, Vrije Universiteit, De Boelelaan 1083, 1081HV Amsterdam, The Netherlands
| | - Kieron Burke
- Departments of Chemistry and of Physics, University of California, Irvine, California 92697, United States
| |
Collapse
|
35
|
A Benchmark Protocol for DFT Approaches and Data-Driven Models for Halide-Water Clusters. MOLECULES (BASEL, SWITZERLAND) 2022; 27:molecules27051654. [PMID: 35268757 PMCID: PMC8924895 DOI: 10.3390/molecules27051654] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Revised: 02/18/2022] [Accepted: 02/26/2022] [Indexed: 11/17/2022]
Abstract
Dissolved ions in aqueous media are ubiquitous in many physicochemical processes, with a direct impact on research fields, such as chemistry, climate, biology, and industry. Ions play a crucial role in the structure of the surrounding network of water molecules as they can either weaken or strengthen it. Gaining a thorough understanding of the underlying forces from small clusters to bulk solutions is still challenging, which motivates further investigations. Through a systematic analysis of the interaction energies obtained from high-level electronic structure methodologies, we assessed various dispersion-corrected density functional approaches, as well as ab initio-based data-driven potential models for halide ion-water clusters. We introduced an active learning scheme to automate the generation of optimally weighted datasets, required for the development of efficient bottom-up anion-water models. Using an evolutionary programming procedure, we determined optimized and reference configurations for such polarizable and first-principles-based representation of the potentials, and we analyzed their structural characteristics and energetics in comparison with estimates from DF-MP2 and DFT+D quantum chemistry computations. Moreover, we presented new benchmark datasets, considering both equilibrium and non-equilibrium configurations of higher-order species with an increasing number of water molecules up to 54 for each F, Cl, Br, and I anions, and we proposed a validation protocol to cross-check methods and approaches. In this way, we aim to improve the predictive ability of future molecular computer simulations for determining the ongoing conflicting distribution of different ions in aqueous environments, as well as the transition from nanoscale clusters to macroscopic condensed phases.
Collapse
|
36
|
Furness JW, Kaplan AD, Ning J, Perdew JP, Sun J. Construction of meta-GGA functionals through restoration of exact constraint adherence to regularized SCAN functionals. J Chem Phys 2022; 156:034109. [DOI: 10.1063/5.0073623] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Affiliation(s)
- James W. Furness
- Department of Physics and Engineering Physics, Tulane University, New Orleans, Louisiana 70118, USA
| | - Aaron D. Kaplan
- Department of Physics, Temple University, Philadelphia, Pennsylvania 19122, USA
| | - Jinliang Ning
- Department of Physics and Engineering Physics, Tulane University, New Orleans, Louisiana 70118, USA
| | - John P. Perdew
- Department of Physics, Temple University, Philadelphia, Pennsylvania 19122, USA
- Department of Chemistry, Temple University, Philadelphia, Pennsylvania 19122, USA
| | - Jianwei Sun
- Department of Physics and Engineering Physics, Tulane University, New Orleans, Louisiana 70118, USA
| |
Collapse
|
37
|
Song S, Vuckovic S, Sim E, Burke K. Density-Corrected DFT Explained: Questions and Answers. J Chem Theory Comput 2022; 18:817-827. [DOI: 10.1021/acs.jctc.1c01045] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Suhwan Song
- Department of Chemistry, Yonsei University, 50 Yonsei-ro Seodaemun-gu, Seoul, 03722, Korea
| | - Stefan Vuckovic
- Institute for Microelectronics and Microsystems (CNR-IMM), Via Monteroni, Campus Unisalento, Lecce, 73100, Italy
- Department of Chemistry&Pharmaceutical Sciences and Amsterdam Institute of Molecular and Life Sciences (AIMMS), Faculty of Science, Vrije Universiteit, De Boelelaan 1083, Amsterdam, 1081HV, The Netherlands
| | - Eunji Sim
- Department of Chemistry, Yonsei University, 50 Yonsei-ro Seodaemun-gu, Seoul, 03722, Korea
| | - Kieron Burke
- Departments of Chemistry and of Physics, University of California, Irvine, California 92697, United States
| |
Collapse
|
38
|
Mishra P, Yamamoto Y, Johnson JK, Jackson KA, Zope RR, Baruah T. Study of self-interaction-errors in barrier heights using locally scaled and Perdew-Zunger self-interaction methods. J Chem Phys 2022; 156:014306. [PMID: 34998352 DOI: 10.1063/5.0070893] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
We study the effect of self-interaction errors on the barrier heights of chemical reactions. For this purpose, we use the well-known Perdew-Zunger self-interaction-correction (PZSIC) [J. P. Perdew and A. Zunger, Phys. Rev. B 23, 5048 (1981)] as well as two variations of the recently developed, locally scaled self-interaction correction (LSIC) [Zope et al., J. Chem. Phys. 151, 214108 (2019)] to study the barrier heights of the BH76 benchmark dataset. Our results show that both PZSIC and especially the LSIC methods improve the barrier heights relative to the local density approximation (LDA). The version of LSIC that uses the iso-orbital indicator z as a scaling factor gives a more consistent improvement than an alternative version that uses an orbital-dependent factor w based on the ratio of orbital densities to the total electron density. We show that LDA energies evaluated using the self-consistent and self-interaction-free PZSIC densities can be used to assess density-driven errors. The LDA reaction barrier errors for the BH76 set are found to contain significant density-driven errors for all types of reactions contained in the set, but the corrections due to adding SIC to the functional are much larger than those stemming from the density for the hydrogen transfer reactions and of roughly equal size for the non-hydrogen transfer reactions.
Collapse
Affiliation(s)
- Prakash Mishra
- Computational Science Program, University of Texas at El Paso, El Paso, Texas 79968, USA
| | - Yoh Yamamoto
- Department of Physics, University of Texas at El Paso, El Paso, Texas 79968, USA
| | - J Karl Johnson
- Department of Chemical and Petroleum Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, USA
| | - Koblar A Jackson
- Physics Department and Science of Advanced Materials Program, Central Michigan University, Mount Pleasant, Michigan 48859, USA
| | - Rajendra R Zope
- Computational Science Program, University of Texas at El Paso, El Paso, Texas 79968, USA
| | - Tunna Baruah
- Computational Science Program, University of Texas at El Paso, El Paso, Texas 79968, USA
| |
Collapse
|