Density Sensitivity of Empirical Functionals

Song, Suhwan; Vuckovic, Stefan; Sim, Eunji; Burke, Kieron

doi:10.1021/acs.jpclett.0c03545

Cited by 52 publications

(153 citation statements)

References 57 publications

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“…50,51 In this context, it has recently been shown that using the Hartree-Fock density in the density-corrected DFT formalism (DC-DFT) mitigates density-driven errors, particularly in the case of nonempirical functionals, because the standard fitting procedures for empirical functionals conflate density-driven errors with functional-driven errors. 62 In this study, we have demonstrated that the density-corrected SCAN (DC-SCAN) functional effectively removes density-driven errors from the water 2-body energies, which brings both binding and interaction energies of different water clusters very close to reference values calculated at CCSD(T)/CBS level of theory. Although not as pronounced as for the 2-body energies, the density correction also reduces density-driven errors in all higher-body terms of the many-body expansion (MBE) of the energy calculated for water using the DC-SCAN functional, with each individual many-body term being in quantitative agreement with the corresponding CCSD(T)/CBS reference values.…”

Section: Discussionmentioning

confidence: 90%

“…While the search for the "optimal" XC functional for water has been, in most cases, guided by evaluating the accuracy of a given functional based on its construction and/or its ability to reproduce experimental data, 43,44,52,[87][88][89][90] more complete assessments, which also include an understanding of density-driven errors, have shed light on both merits and shortcomings of existing XC functionals at the fundamental level. 46,47,50,51,59,62,91,92 In particular, the recent development of the nonempirical SCAN functional has sparked renewed interest in ab initio simulations of water since, by satisfying all 17 known constraints for meta-GGA functionals, it largely reduces functional-driven errors. 41,42 However, as all GGA and meta-GGA functionals, SCAN still suffers from density-driven errors that are intrinsic to computationally-efficient semilocal density functional approximations.…”

Section: Discussionmentioning

confidence: 99%

“…An approximate, yet efficient, approach to reducing density-driven errors in DFT calculations consists in using the Hartree-Fock density, n HF (r) because, by construction, it does not suffer from either electron over-delocalization or self-interaction errors. 56,[59][60][61][62] The resulting density-corrected DFT (DC-DFT) energy can then be written as: In the case of water, 1B (i) in eq 5 corresponds to the distortion energy of the ith water molecule in the system from the equilibrium geometry of the corresponding free molecule, and all higher-order n-body energies, nB (2, . .…”

Section: Discussionmentioning

confidence: 99%

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Elevating Density Functional Theory to Chemical Accuracy for Water Simulations through a Density-Corrected Many-Body Formalism

Dasgupta

Lambros

Perdew

et al. 2021

Preprint

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Kohn-Sham density functional theory (DFT) has been extensively used to model the properties of water. Albeit maintaining a good balance between accuracy and efficiency, no density functional has so far achieved the degree of accuracy necessary to correctly predict the properties of water across the entire phase diagram. The recent development of the strongly constrained and appropriately normed (SCAN) functional has renewed the interest in ab initio simulations of liquid water, yielding promising results that are, however, still unable to reproduce all the experimental data. Here, we present density-corrected SCAN (DC-SCAN) calculations for water which, minimizing density-driven errors, elevate the accuracy of the SCAN functional to that of coupled cluster theory, the "gold standard" for chemical accuracy. Building upon the accuracy and efficiency of DC-SCAN within a many-body formalism, we introduce a data-driven many-body potential energy function, the MB-SCAN(DC) PEF, that is able to quantitatively reproduce coupled cluster reference values for interaction, binding, and individual many-body energies of water clusters. Importantly, the properties of liquid water calculated from molecular dynamics simulations carried out with the MB-SCAN(DC) PEF are found to be in excellent agreement with the experimental data, which thus demonstrates that MB-SCAN(DC) is effectively the first DFT-based model that correctly describes water from the gas to the condensed phase. Since the many-body formalism adopted by the present MB-SCAN(DC) PEF for water is general, we believe it can open the door to the routine development of data-driven many-body PEFs for predictive simulations of generic (small) molecules in the gas, liquid, and solid phases.Its anomalous behavior 1 and importance to life 2 make water one of the most studied chemical compounds. Among its many unique properties is the high value of the heat capacity which allows water to resist sudden temperature changes, thus permitting living organisms to survive without experiencing significant temperature fluctuations. 3 In addition, the dynamic nature of the water hydrogen-bond network plays a central role in several fundamental processes, including transport and diffusion in bulk solutions and at interfaces, and hydration of hydrophobic and hydrophilic solutes. 4 For example, protein folding is thought to be driven by the hydrophobic effect. 5 Finally, countless chemical reactions involving charged species take place efficiently in liquid water due to

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Section: Discussionmentioning

confidence: 90%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Elevating Density Functional Theory to Chemical Accuracy for Water Simulations through a Density-Corrected Many-Body Formalism

Dasgupta

Lambros

Perdew

et al. 2021

Preprint

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“…However, for practical reasons and due to the fact that HF is SIE free, it has been suggested to use HF densities as a reliable proxy for exact densities in DC-DFT. 120,121,127,253,254 In this section, we exemplify the impact of the DC-DFT procedure for ten systems, some of which show large and other small binding strengths; see SI for all systems and numbers (Tables S12-S19). Fig.…”

Section: A Brief Analysis Of Density-driven Errorsmentioning

confidence: 99%

“…We recommend Ref. 253 for a very recent discussion on the topic of density errors and their impact on dispersion-corrected DFT results.…”

Section: A Brief Analysis Of Density-driven Errorsmentioning

confidence: 99%

CHAL336 Benchmark Set: How Well Do Quantum-Chemical Methods Describe Chalcogen-Bonding Interactions?

Mehta

Fellowes

White

et al. 2021

J. Chem. Theory Comput.

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We present the CHAL336 benchmark set-the most comprehensive database for the assessment of chalcogen-bonding (CB) interactions. After careful selection of suitable systems and identification of three high-level reference methods, the set comprises 336 dimers each consisting of up to 49 atoms and covers both σ-and π-hole interactions across four categories: chalcogen-chalcogen, chalcogen-π, chalcogen-halogen, and chalcogen-nitrogen interactions. In a subsequent study of DFT methods, we re-emphasize the need for using proper London dispersion corrections when treating noncovalent interactions. We also point out that the deterioration of results and systematic overestimation of interaction energies for some dispersion-corrected DFT methods does not hint at problems with the chosen dispersion correction, but is a consequence of large density-driven errors. We conclude this work by performing the most detailed DFT benchmark study for CB interactions to date. We assess 109 variations of dispersion-corrected and -uncorrected DFT methods, and carry out a detailed analysis of 80 of them. Double-hybrid functionals are the most reliable approaches for CB interactions, and they should be used whenever computationally feasible.The best three double hybrids are SOS0-PBE0-2-D3(BJ), revDSD-PBEP86-D3(BJ), and B2NCPLYP-D3(BJ). The best hybrids in this study are ωB97M-V, PW6B95-D3(0), and PW6B95-D3(BJ). We do not recommend using the popular B3LYP functional nor the MP2 approach, which have both been frequently used to describe CB interactions in the past. We hope to inspire a change in computational protocols surrounding CB interactions that leads away from the commonly used, popular methods to the more robust and accurate ones recommended herein. We would also like to encourage method developers to use our set for the investigation and reduction of density-driven errors in new density functional approximations. File list (5) download file view on ChemRxiv CHAL336.pdf (3.01 MiB) download file view on ChemRxiv CHAL336_SI_part1.pdf (1.01 MiB) download file view on ChemRxiv CHAL336_SI_part2_structures.zip (1.95 MiB) download file view on ChemRxiv CHAL336_SI_part3_refvalues.zip (78.17 KiB) download file view on ChemRxiv CHAL336_SI_part4_DFTMP2data.zip (0.90 MiB)

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Delocalization error: The greatest outstanding challenge in density‐functional theory

Bryenton

Adeleke

Dale

et al. 2022

WIREs Comput Mol Sci

100

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Every day, density-functional theory (DFT) is routinely applied to computational modeling of molecules and materials with the expectation of high accuracy. However, in certain situations, popular density-functional approximations (DFAs) have the potential to give substantial quantitative, and even qualitative, errors. The most common class of error is delocalization error, which is an overarching term that also encompasses the one-electron self-interaction error.In our opinion, its resolution remains the greatest outstanding challenge in DFT development. In this paper, we review the history of delocalization error and provide several complimentary conceptual pictures for its interpretation, along with illustrative examples of its various manifestations. Approaches to reduce delocalization error are discussed, as is its interplay with other shortcomings of popular DFAs, including treatment of non-bonded repulsion and neglect of London dispersion.

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Density Sensitivity of Empirical Functionals

Cited by 52 publications

References 57 publications

Elevating Density Functional Theory to Chemical Accuracy for Water Simulations through a Density-Corrected Many-Body Formalism

Elevating Density Functional Theory to Chemical Accuracy for Water Simulations through a Density-Corrected Many-Body Formalism

CHAL336 Benchmark Set: How Well Do Quantum-Chemical Methods Describe Chalcogen-Bonding Interactions?

Delocalization error: The greatest outstanding challenge in density‐functional theory

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