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Using Noncovalent Interactions to Test the Precision of Projector-Augmented Wave Data Sets

. 2023 Dec 12 ; 19 (23) : 8871-8885. [epub] 20231201

Status PubMed-not-MEDLINE Language English Country United States Media print-electronic

Document type Journal Article

The projector-augmented wave (PAW) method is one of the approaches that are widely used to approximately treat core electrons and thus to speed up plane-wave basis set electronic structure calculations. However, PAW involves approximations, and it is thus important to understand how they affect the results. Tests of the precision of PAW data sets often use the properties of isolated atoms or atomic solids. While this is sufficient to identify problematic PAW data sets, little information has been gained to understand the origins of the errors and suggest ways to correct them. Here, we show that the interaction energies of molecular dimers are very useful not only to identify problematic PAW data sets but also to uncover the origin of the errors. Using dimers from the S22 and S66 test sets and other dimers, we find that the error in the interaction energy is composed of a short-range component with an exponential decay and a long-range electrostatic part caused by an error in the total charge density. We propose and evaluate a simple improvable scheme to correct the long-range error and find that even in its simple and readily usable form, it is able to reduce the interaction energy errors to less than half on average for hydrogen-bonded dimers.

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Hamann D. R.; Schlüter M.; Chiang C. Norm-Conserving Pseudopotentials. Phys. Rev. Lett. 1979, 43, 1494–1497. 10.1103/PhysRevLett.43.1494. DOI

Troullier N.; Martins J. L. Efficient pseudopotentials for plane-wave calculations. Phys. Rev. B 1991, 43, 1993–2006. 10.1103/PhysRevB.43.1993. PubMed DOI

Vanderbilt D. Soft self-consistent pseudopotentials in a generalized eigenvalue formalism. Phys. Rev. B 1990, 41, 7892–7895. 10.1103/PhysRevB.41.7892. PubMed DOI

Blöchl P. E. Projector augmented-wave method. Phys. Rev. B 1994, 50, 17953–17979. 10.1103/PhysRevB.50.17953. PubMed DOI

Blöchl P. E.; Kästner J.; Först C. J.. Handbook of Materials Modeling: Methods; Yip S., Ed.; Springer Netherlands: Dordrecht, 2005; pp 93–119.

Kresse G.; Joubert D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B 1999, 59, 1758–1775. 10.1103/PhysRevB.59.1758. DOI

Rostgaard C.The Projector Augmented-wave Method. 2009, arXiv:0910.1921.

Marsman M.; Kresse G. Relaxed core projector-augmented-wave method. J. Chem. Phys. 2006, 125, 104101.10.1063/1.2338035. PubMed DOI

Martin R. M.Electronic Structure: Basic Theory and Practical Methods; Cambridge University Press, 2004.

Dal Corso A. Pseudopotentials periodic table: From H to Pu. Comput. Mater. Sci. 2014, 95, 337–350. 10.1016/j.commatsci.2014.07.043. DOI

Wimmer E.; Krakauer H.; Weinert M.; Freeman A. J. Full-potential self-consistent linearized-augmented-plane-wave method for calculating the electronic structure of molecules and surfaces: O2 molecule. Phys. Rev. B 1981, 24, 864–875. 10.1103/PhysRevB.24.864. DOI

Hill J. G. Gaussian basis sets for molecular applications. Int. J. Quantum Chem. 2013, 113, 21–34. 10.1002/qua.24355. DOI

Jensen F. Atomic orbital basis sets. Wiley Interdiscip. Rev. Comput. Mol. Sci. 2013, 3, 273–295. 10.1002/wcms.1123. DOI

Lejaeghere K.; Bihlmayer G.; Björkman T.; Blaha P.; Blügel S.; Blum V.; Caliste D.; Castelli I. E.; Clark S. J.; Dal Corso A.; de Gironcoli S.; Deutsch T.; Dewhurst J. K.; Di Marco I.; Draxl C.; Dułak M.; Eriksson O.; Flores-Livas J. A.; Garrity K. F.; Genovese L.; Giannozzi P.; Giantomassi M.; Goedecker S.; Gonze X.; Grånäs O.; Gross E. K. U.; Gulans A.; Gygi F.; Hamann D. R.; Hasnip P. J.; Holzwarth N. A. W.; Iuşan D.; Jochym D. B.; Jollet F.; Jones D.; Kresse G.; Koepernik K.; Küçükbenli E.; Kvashnin Y. O.; Locht I. L. M.; Lubeck S.; Marsman M.; Marzari N.; Nitzsche U.; Nordström L.; Ozaki T.; Paulatto L.; Pickard C. J.; Poelmans W.; Probert M. I. J.; Refson K.; Richter M.; Rignanese G.-M.; Saha S.; Scheffler M.; Schlipf M.; Schwarz K.; Sharma S.; Tavazza F.; Thunström P.; Tkatchenko A.; Torrent M.; Vanderbilt D.; van Setten M. J.; Van Speybroeck V.; Wills J. M.; Yates J. R.; Zhang G.-X.; Cottenier S. Reproducibility in density functional theory calculations of solids. Science 2016, 351, aad3000.10.1126/science.aad3000. PubMed DOI

Lejaeghere K.; Van Speybroeck V.; Van Oost G.; Cottenier S. Error Estimates for Solid-State Density-Functional Theory Predictions: An Overview by Means of the Ground-State Elemental Crystals. Crit. Rev. Solid State Mater. Sci. 2014, 39, 1–24. 10.1080/10408436.2013.772503. DOI

Jollet F.; Torrent M.; Holzwarth N. Generation of Projector Augmented-Wave atomic data: A 71 element validated table in the XML format. Comput. Phys. Commun. 2014, 185, 1246–1254. 10.1016/j.cpc.2013.12.023. DOI

Talirz L.; Kumbhar S.; Passaro E.; Yakutovich A. V.; Granata V.; Gargiulo F.; Borelli M.; Uhrin M.; Huber S. P.; Zoupanos S.; Adorf C. S.; Andersen C. W.; Schütt O.; Pignedoli C. A.; Passerone D.; VandeVondele J.; Schulthess T. C.; Smit B.; Pizzi G.; Marzari N. Materials Cloud, a platform for open computational science. Sci. Data 2020, 7, 299.10.1038/s41597-020-00637-5. PubMed DOI PMC

Paier J.; Hirschl R.; Marsman M.; Kresse G. The Perdew–Burke–Ernzerhof exchange-correlation functional applied to the G2–1 test set using a plane-wave basis set. J. Chem. Phys. 2005, 122, 234102.10.1063/1.1926272. PubMed DOI

Curtiss L. A.; Raghavachari K.; Redfern P. C.; Pople J. A. Assessment of Gaussian-2 and density functional theories for the computation of enthalpies of formation. J. Chem. Phys 1997, 106, 1063.10.1063/1.473182. DOI

Perdew J. P.; Burke K.; Ernzerhof M. Generalized Gradient Approximation Made Simple. Phys. Rev. Lett. 1996, 77, 3865–3868. 10.1103/PhysRevLett.77.3865. PubMed DOI

Adamo C.; Barone V. Toward reliable density functional methods without adjustable parameters: The PBE0 model. J. Chem. Phys. 1999, 110, 6158–6170. 10.1063/1.478522. DOI

Kendall R. A.; Dunning T. H.; Harrison R. J. Electron affinities of the first-row atoms revisited. Systematic basis sets and wave functions. J. Chem. Phys. 1992, 96, 6796–6806. 10.1063/1.462569. DOI

Dunning T. H.; Peterson K. A.; Wilson A. K. Gaussian basis sets for use in correlated molecular calculations. X. The atoms aluminum through argon revisited. J. Chem. Phys. 2001, 114, 9244–9253. 10.1063/1.1367373. DOI

Maggio E.; Liu P.; van Setten M. J.; Kresse G. GW100: A Plane Wave Perspective for Small Molecules. J. Chem. Theory Comput. 2017, 13, 635–648. 10.1021/acs.jctc.6b01150. PubMed DOI

Hedin L. New Method for Calculating the One-Particle Green’s Function with Application to the Electron-Gas Problem. Phys. Rev. 1965, 139, A796–A823. 10.1103/PhysRev.139.A796. DOI

van Setten M. J.; Caruso F.; Sharifzadeh S.; Ren X.; Scheffler M.; Liu F.; Lischner J.; Lin L.; Deslippe J. R.; Louie S. G.; Yang C.; Weigend F.; Neaton J. B.; Evers F.; Rinke P. GW100: Benchmarking G0W0 for Molecular Systems. J. Chem. Theory Comput. 2015, 11, 5665–5687. 10.1021/acs.jctc.5b00453. PubMed DOI

Ahmed Adllan A.; Dal Corso A. Ultrasoft pseudopotentials and projector augmented-wave data sets: application to diatomic molecules. J. Condens. Matter Phys. 2011, 23, 425501.10.1088/0953-8984/23/42/425501. PubMed DOI

Tkatchenko A.; Scheffler M. Accurate Molecular Van Der Waals Interactions from Ground-State Electron Density and Free-Atom Reference Data. Phys. Rev. Lett. 2009, 102, 073005.10.1103/PhysRevLett.102.073005. PubMed DOI

Hofierka J.; Klimes J.. Understanding precision of binding energies of molecules and molecular solids. http://quantum.karlov.mff.cuni.cz/~jklimes/pq0519.pdf Accessed on September 22, 2023.

Witte J.; Neaton J. B.; Head-Gordon M. Push it to the limit: comparing periodic and local approaches to density functional theory for intermolecular interactions. Mol. Phys. 2019, 117, 1298–1305. 10.1080/00268976.2018.1542164. DOI

Perdew J. P.; Wang Y. Accurate and simple analytic representation of the electron-gas correlation energy. Phys. Rev. B 1992, 45, 13244–13249. 10.1103/PhysRevB.45.13244. PubMed DOI

Jurečka P.; Šponer J.; Černý J.; Hobza P. Benchmark database of accurate (MP2 and CCSD(T) complete basis set limit) interaction energies of small model complexes, DNA base pairs, and amino acid pairs. Phys. Chem. Chem. Phys. 2006, 8, 1985–1993. 10.1039/B600027D. PubMed DOI

Tosoni S.; Tuma C.; Sauer J.; Civalleri B.; Ugliengo P. A comparison between plane wave and Gaussian-type orbital basis sets for hydrogen bonded systems: Formic acid as a test case. J. Chem. Phys. 2007, 127, 154102.10.1063/1.2790019. PubMed DOI

Řezáč J.; Riley K. E.; Hobza P. S66: A Well-balanced Database of Benchmark Interaction Energies Relevant to Biomolecular Structures. J. Chem. Theory Comput. 2011, 7, 2427–2438. 10.1021/ct2002946. PubMed DOI PMC

Kresse G.; Hafner J. Ab initio molecular dynamics for liquid metals. Phys. Rev. B 1993, 47, 558–561. 10.1103/PhysRevB.47.558. PubMed DOI

Kresse G.; Furthmüller J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. Mater. Sci. 1996, 6, 15–50. 10.1016/0927-0256(96)00008-0. PubMed DOI

Kresse G.; Furthmüller J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 1996, 54, 11169–11186. 10.1103/PhysRevB.54.11169. PubMed DOI

Shishkin M.; Kresse G. Implementation and performance of the frequency-dependent GW method within the PAW framework. Phys. Rev. B 2006, 74, 035101.10.1103/PhysRevB.74.035101. DOI

Dal Corso A.pslibrary, a library of ultrasoft and PAW pseudopotentials. https://dalcorso.github.io/pslibrary/ Accessed on October 6, 2023.

Řezáč J.; Jurečka P.; Riley K. E.; Černý J.; Valdes H.; Pluháčková K.; Berka K.; Řezáč T.; Pitoňák M.; Vondrášek J.; et al. Quantum Chemical Benchmark Energy and Geometry Database for Molecular Clusters and Complex Molecular Systems (www.begdb.com): A Users Manual and Examples. Collect. Czech. Chem. Commun. 2008, 73, 1261–1270. 10.1135/cccc20081261. DOI

Structures, outputs, and processing script. https://github.com/klimes/wirt_paper1 Accessed on October 24, 2023.

Makov G.; Payne M. C. Periodic boundary conditions in ab initio calculations. Phys. Rev. B 1995, 51, 4014–4022. 10.1103/PhysRevB.51.4014. PubMed DOI

Gygi F.; Baldereschi A. Self-consistent Hartree-Fock and screened-exchange calculations in solids: Application to silicon. Phys. Rev. B 1986, 34, 4405–4408. 10.1103/PhysRevB.34.4405. PubMed DOI

Hofierka J.; Klimeš J. Binding energies of molecular solids from fragment and periodic approaches. Electron. Struct. 2021, 3, 034010.10.1088/2516-1075/ac25d6. DOI

Bader R. F. W.Atoms in Molecules—A Quantum Theory; Oxford University Press: Oxford, 1990.

Bultinck P.; Van Alsenoy C.; Ayers P. W.; Carbó-Dorca R. Critical analysis and extension of the Hirshfeld atoms in molecules. J. Chem. Phys. 2007, 126, 144111.10.1063/1.2715563. PubMed DOI

Bultinck P.; Ayers P. W.; Fias S.; Tiels K.; Van Alsenoy C. Uniqueness and basis set dependence of iterative Hirshfeld charges. Chem. Phys. Lett. 2007, 444, 205–208. 10.1016/j.cplett.2007.07.014. DOI

Bučko T.; Lebègue S.; Hafner J.; Ángyán J. G. Improved Density Dependent Correction for the Description of London Dispersion Forces. J. Chem. Theory Comput. 2013, 9, 4293–4299. 10.1021/ct400694h. PubMed DOI

Henkelman G.; Arnaldsson A.; J’onsson H. A fast and robust algorithm for Bader decomposition of charge density. Comput. Mater. Sci. 2006, 36, 354–360. 10.1016/j.commatsci.2005.04.010. DOI

Sanville E.; Kenny S. D.; Smith R.; Henkelman G. Improved grid-based algorithm for Bader charge allocation. J. Comput. Chem. 2007, 28, 899–908. 10.1002/jcc.20575. PubMed DOI

Tang W.; Sanville E.; Henkelman G. A grid-based Bader analysis algorithm without lattice bias. J. Phys.: Condens. Matter 2009, 21, 084204.10.1088/0953-8984/21/8/084204. PubMed DOI

Yu M.; Trinkle D. R. Accurate and efficient algorithm for Bader charge integration. J. Chem. Phys. 2011, 134, 064111.10.1063/1.3553716. PubMed DOI

Giannozzi P.; Baroni S.; Bonini N.; Calandra M.; Car R.; Cavazzoni C.; Ceresoli D.; Chiarotti G. L.; Cococcioni M.; Dabo I.; Dal Corso A.; de Gironcoli S.; Fabris S.; Fratesi G.; Gebauer R.; Gerstmann U.; Gougoussis C.; Kokalj A.; Lazzeri M.; Martin-Samos L.; Marzari N.; Mauri F.; Mazzarello R.; Paolini S.; Pasquarello A.; Paulatto L.; Sbraccia C.; Scandolo S.; Sclauzero G.; Seitsonen A. P.; Smogunov A.; Umari P.; Wentzcovitch R. M. QUANTUM ESPRESSO: a modular and open-source software project for quantum simulations of materials. J. Phys.: Condens. Matter 2009, 21, 395502.10.1088/0953-8984/21/39/395502. PubMed DOI

Giannozzi P.; Andreussi O.; Brumme T.; Bunau O.; Buongiorno Nardelli M.; Calandra M.; Car R.; Cavazzoni C.; Ceresoli D.; Cococcioni M.; Colonna N.; Carnimeo I.; Dal Corso A.; de Gironcoli S.; Delugas P.; DiStasio R. A.; Ferretti A.; Floris A.; Fratesi G.; Fugallo G.; Gebauer R.; Gerstmann U.; Giustino F.; Gorni T.; Jia J.; Kawamura M.; Ko H.-Y.; Kokalj A.; Küçükbenli E.; Lazzeri M.; Marsili M.; Marzari N.; Mauri F.; Nguyen N. L.; Nguyen H.-V.; Otero-de-la-Roza A.; Paulatto L.; Poncé S.; Rocca D.; Sabatini R.; Santra B.; Schlipf M.; Seitsonen A. P.; Smogunov A.; Timrov I.; Thonhauser T.; Umari P.; Vast N.; Wu X.; Baroni S. Advanced capabilities for materials modelling with Quantum ESPRESSO. J. Phys.: Condens. Matter 2017, 29, 465901.10.1088/1361-648x/aa8f79. PubMed DOI

Giannozzi P.; Baseggio O.; Bonfà P.; Brunato D.; Car R.; Carnimeo I.; Cavazzoni C.; de Gironcoli S.; Delugas P.; Ferrari Ruffino F.; Ferretti A.; Marzari N.; Timrov I.; Urru A.; Baroni S. Quantum ESPRESSO toward the exascale. J. Chem. Phys. 2020, 152, 154105.10.1063/5.0005082. PubMed DOI

Hjorth Larsen A.; Jørgen Mortensen J.; Blomqvist J.; Castelli I. E.; Christensen R.; Dułak M.; Friis J.; Groves M. N.; Hammer B.; Hargus C.; Hermes E. D.; Jennings P. C.; Bjerre Jensen P.; Kermode J.; Kitchin J. R.; Leonhard Kolsbjerg E.; Kubal J.; Kaasbjerg K.; Lysgaard S.; Bergmann Maronsson J.; Maxson T.; Olsen T.; Pastewka L.; Peterson A.; Rostgaard C.; Schiøtz J.; Schütt O.; Strange M.; Thygesen K. S.; Vegge T.; Vilhelmsen L.; Walter M.; Zeng Z.; Jacobsen K. W. The atomic simulation environment a Python library for working with atoms. J. Phys.: Condens. Matter 2017, 29, 273002.10.1088/1361-648x/aa680e. PubMed DOI

Werner H.-J.; Knowles P. J.; Knizia G.; Manby F. R.; Schütz M. Molpro: a general-purpose quantum chemistry program package. Wiley Interdiscip. Rev. Comput. Mol. Sci. 2012, 2, 242–253. 10.1002/wcms.82. DOI

Werner H.-J.; Knowles P. J.; Manby F. R.; Black J. A.; Doll K.; Heßelmann A.; Kats D.; Köhn A.; Korona T.; Kreplin D. A.; Ma Q.; Miller T. F.; Mitrushchenkov A.; Peterson K. A.; Polyak I.; Rauhut G.; Sibaev M. The Molpro quantum chemistry package. J. Chem. Phys. 2020, 152, 144107.10.1063/5.0005081. PubMed DOI

Balasubramani S. G.; Chen G. P.; Coriani S.; Diedenhofen M.; Frank M. S.; Franzke Y. J.; Furche F.; Grotjahn R.; Harding M. E.; Hättig C.; Hellweg A.; Helmich-Paris B.; Holzer C.; Huniar U.; Kaupp M.; Marefat Khah A.; Karbalaei Khani S.; Müller T.; Mack F.; Nguyen B. D.; Parker S. M.; Perlt E.; Rappoport D.; Reiter K.; Roy S.; Rückert M.; Schmitz G.; Sierka M.; Tapavicza E.; Tew D. P.; van Wüllen C.; Voora V. K.; Weigend F.; Wodyński A.; Yu J. M. TURBOMOLE: Modular program suite for ab initio quantum-chemical and condensed-matter simulations. J. Chem. Phys. 2020, 152, 184107.10.1063/5.0004635. PubMed DOI PMC

Woon D. E.; Dunning T. H. Gaussian basis sets for use in correlated molecular calculations. IV. Calculation of static electrical response properties. J. Chem. Phys. 1994, 100, 2975–2988. 10.1063/1.466439. DOI

Van Mourik T.; Wilson A. K.; Dunning T. H. Benchmark calculations with correlated molecular wavefunctions. XIII. Potential energy curves for He2, Ne2 and Ar2 using correlation consistent basis sets through augmented sextuple zeta. Mol. Phys. 1999, 96, 529–547. 10.1080/002689799165396. DOI

Boys S.; Bernardi F. The calculation of small molecular interactions by the differences of separate total energies. Some procedures with reduced errors. Mol. Phys. 1970, 19, 553–566. 10.1080/00268977000101561. DOI

Jensen F. Polarization consistent basis sets: Principles. J. Chem. Phys. 2001, 115, 9113–9125. 10.1063/1.1413524. DOI

Jensen F. Polarization consistent basis sets. II. Estimating the Kohn–Sham basis set limit. J. Chem. Phys. 2002, 116, 7372–7379. 10.1063/1.1465405. DOI

Jeziorski B.; Moszynski R.; Szalewicz K. Perturbation Theory Approach to Intermolecular Potential Energy Surfaces of van der Waals Complexes. Chem. Rev. 1994, 94, 1887–1930. 10.1021/cr00031a008. DOI

Heßelmann A. DFT-SAPT Intermolecular Interaction Energies Employing Exact-Exchange Kohn–Sham Response Methods. J. Chem. Theory Comput. 2018, 14, 1943–1959. 10.1021/acs.jctc.7b01233. PubMed DOI

Heßelmann A.; Jansen G.; Schütz M. Density-functional theory-symmetry-adapted intermolecular perturbation theory with density fitting: A new efficient method to study intermolecular interaction energies. J. Chem. Phys. 2005, 122, 014103.10.1063/1.1824898. PubMed DOI

Görling A. Exact exchange kernel for time-dependent density-functional theory. Int. J. Quantum Chem. 1998, 69, 265–277. 10.1002/(SICI)1097-461X(1998)69:3<265::AID-QUA6>3.0.CO;2-T. DOI

Görling A. Exact exchange-correlation kernel for dynamic response properties and excitation energies in density-functional theory. Phys. Rev. A 1998, 57, 3433–3436. 10.1103/PhysRevA.57.3433. DOI

Blanco M. A.; Martín Pendás A.; Francisco E. Interacting Quantum Atoms: A Correlated Energy Decomposition Scheme Based on the Quantum Theory of Atoms in Molecules. J. Chem. Theory Comput. 2005, 1, 1096–1109. 10.1021/ct0501093. PubMed DOI

Francisco E.; Martín Pendás A.; Blanco M. A. A Molecular Energy Decomposition Scheme for Atoms in Molecules. J. Chem. Theory Comput. 2006, 2, 90–102. 10.1021/ct0502209. PubMed DOI

Keith T. A.AIMAll. Version 19.10.12, 2016;.

Witte J.; Neaton J. B.; Head-Gordon M. Push it to the limit: Characterizing the convergence of common sequences of basis sets for intermolecular interactions as described by density functional theory. J. Chem. Phys. 2016, 144, 194306.10.1063/1.4949536. PubMed DOI

Bučko T.; Lebègue S.; Hafner J.; Ángyán J. G. Tkatchenko-Scheffler van der Waals correction method with and without self-consistent screening applied to solids. Phys. Rev. B 2013, 87, 064110.10.1103/PhysRevB.87.064110. DOI

Thürlemann M.; Böselt L.; Riniker S. Learning Atomic Multipoles: Prediction of the Electrostatic Potential with Equivariant Graph Neural Networks. J. Chem. Theory Comput. 2022, 18, 1701–1710. 10.1021/acs.jctc.1c01021. PubMed DOI

Hintzsche L. E.; Fang C. M.; Marsman M.; Jordan G.; Lamers M. W. P. E.; Weeber A. W.; Kresse G. Defects and defect healing in amorphous Si3N4–xHy: An ab initio density functional theory study. Phys. Rev. B 2013, 88, 155204.10.1103/PhysRevB.88.155204. DOI

Chin H.-T.; Klimes J.; Hu I.-F.; Chen D.-R.; Nguyen H.-T.; Chen T.-W.; Ma S.-W.; Hofmann M.; Liang C.-T.; Hsieh Y.-P. Ferroelectric 2D ice under graphene confinement. Nat. Commun. 2021, 12, 6291.10.1038/s41467-021-26589-x. PubMed DOI PMC

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