Elevating density functional theory to chemical accuracy for water simulations through a density-corrected many-body formalism

Dasgupta, Saswata; Lambros, Eleftherios; Perdew, John P.; Paesani, Francesco

doi:10.1038/s41467-021-26618-9

Cited by 58 publications

(77 citation statements)

References 124 publications

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“…Herein, DC-DFT is employed in the form of HF-DFT, and we preserve the DC-DFT notation, since the HF density is a good proxy for the exact density in a water cluster. DC-SCAN has recently been found to improve the accuracy of DFT calculations for water, effectively elevating the accuracy of the SCAN functional to that of coupled cluster theory, the “gold standard” for chemical accuracy . DC-SCAN does not achieve this level of accuracy for all systems, but it is overall somewhat more accurate than self-consistent SCAN for a large and diverse data set of main-group molecular properties …”

Section: Introductionmentioning

confidence: 99%

How Good Is the Density-Corrected SCAN Functional for Neutral and Ionic Aqueous Systems, and What Is So Right about the Hartree–Fock Density?

Dasgupta

Shahi

Bhetwal

et al. 2022

J. Chem. Theory Comput.

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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.

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Section: Introductionmentioning

confidence: 99%

How Good Is the Density-Corrected SCAN Functional for Neutral and Ionic Aqueous Systems, and What Is So Right about the Hartree–Fock Density?

Dasgupta

Shahi

Bhetwal

et al. 2022

J. Chem. Theory Comput.

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“…This is the case of ions, and depending on their charge and size could be strongly hydrated or disrupt the structure of the surrounding water hydrogen bonding [ 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 ]. Ion hydration is a key point in understanding a variety of physicochemical processes; thus both experimental and theoretical studies are seeking to give a definitive picture of how ions influence the water molecules around them [ 10 , 12 , 14 , 15 , 16 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 ]. On the one hand, it has been possible to obtain a clearer approximation of specific structure effects thanks to neutron and X-ray diffraction experiments [ 4 , 6 , 16 , 38 , 39 ].…”

Section: Introductionmentioning

confidence: 99%

“…Interaction potentials can be parameterized either from experimental data or first-principles values, with the latter representing a more adequate way to reproduce energies, as they are not biased by the subsequent reinterpretation that must be made of the laboratory data. Indeed, very valuable information has been obtained from numerous quantum chemistry calculations of water and ion–water clusters [ 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 40 , 41 , 42 , 43 , 44 , 45 , 46 ], at different levels of theory; however, they are usually limited to a few water molecules systems. A systematic analysis of the cluster properties as a function of its size provides a protocol for the selection of the best computational method for modeling ion–water interactions when going from systems in gas to condensed phase.…”

Section: Introductionmentioning

confidence: 99%

A Benchmark Protocol for DFT Approaches and Data-Driven Models for Halide-Water Clusters

2022

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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.

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“…Density-driven errors (whether they arise from self-interaction errors or other "delocalization" errors [101]) tend to dominate the errors of DFAs in hydrogen-bonded networks. For example, applying a "density-correction" to SCAN (in this case, evaluating SCAN on the Hartree-Fock density) reduces SCAN's MAE in the binding energies of water clusters from a few kcal/mol to less than 1 kcal/mol [131]. The empirical ωB97M-V (a range-separated hybrid based on the B97M-V meta-GGA) has the lowest WTMAD-2 on the GMKTN55 of any hybrid at 3.53 kcal/mol, but makes a 35.02 kcal/mol MAE on the MB16-43 set [119], much higher than the 12.1 kcal/mol r 2 SCAN MAE.…”

Section: Ascending the Ladder In Real Systemsmentioning

confidence: 99%

Predictive Power of the Exact Constraints and Appropriate Norms in Density Functional Theory

Kaplan,

Levy,

Perdew

2022

Preprint

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Ground-state Kohn-Sham density functional theory provides, in principle, the exact ground-state energy and electronic spin-densities of real interacting electrons in a static external potential. In practice, the exact density functional for the exchange-correlation (xc) energy must be approximated in a computationally efficient way. About twenty mathematical properties of the exact xc functional are known. In this work, we review and discuss these known constraints on the xc energy and hole. By analyzing a sequence of increasingly sophisticated density functional approximations (DFAs), we argue that: (1) the satisfaction of more exact constraints and appropriate norms makes a functional more predictive over the immense space of many-electron systems; (2) fitting to bonded systems yields an interpolative DFA that may not extrapolate well to systems unlike those in the fitting set. We discuss how the class of well-described systems has grown along with constraint satisfaction, and the possibilities for future functional development.

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Elevating density functional theory to chemical accuracy for water simulations through a density-corrected many-body formalism

Cited by 58 publications

References 124 publications

How Good Is the Density-Corrected SCAN Functional for Neutral and Ionic Aqueous Systems, and What Is So Right about the Hartree–Fock Density?

How Good Is the Density-Corrected SCAN Functional for Neutral and Ionic Aqueous Systems, and What Is So Right about the Hartree–Fock Density?

A Benchmark Protocol for DFT Approaches and Data-Driven Models for Halide-Water Clusters

Predictive Power of the Exact Constraints and Appropriate Norms in Density Functional Theory

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