ArticleNature communications2021
Elevating density functional theory to chemical accuracy for water simulations through a density-corrected many-body formalism.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Computational Methods for Molecular Dynamics of Supercooled Water Between 200 and 273 K.Entropy (Basel, Switzerland) · 2026Review
- Many-body interactions resolve halide distribution at the air/water interface.Nature communications · 2026Article
- An Energy-Corrected Fast Post-SCF Local-Hybrid Scheme for Highly Accurate Energy Differences of Large Main-Group Systems.Journal of computational chemistry · 2026Article
- Beyond Hydrogen Bonding: π···π Stacking Directed Self-Assembly of Carboxylic Acid Clusters in the Gas Phase.Angewandte Chemie (International ed. in English) · 2026Article
- Accurate Simulations of Water and Aqueous Solutions through Fine-Tuned Dispersion-Corrected Density Functional Theory and Machine-Learning Interatomic Potentials.Journal of chemical information and modeling · 2025Article
- Accelerating Variable Cell Shape Molecular Dynamics with a Position-Dependent Mass Matrix.Journal of chemical theory and computation · 2025Article
- Application of Density Functional Theory to Molecular Engineering of Pharmaceutical Formulations.International journal of molecular sciences · 2025Review
- Toward Explicit Solvation for Simulations of Electrocatalytic Reactions: AIMD for pThe journal of physical chemistry. A · 2025Article
- Getting the intermolecular forces correct: introducing the ASTA strategy for a water model.RSC advances · 2024Article
- To Pair or not to Pair? Machine-Learned Explicitly-Correlated Electronic Structure for NaCl in Water.The journal of physical chemistry letters · 2024Article
- Probing the self-ionization of liquid water with ab initio deep potential molecular dynamics.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Machine Learning Density Functionals from the Random-Phase Approximation.Journal of chemical theory and computation · 2023Article
- A Status Report on "Gold Standard" Machine-Learned Potentials for Water.The journal of physical chemistry letters · 2023Review
- Simple and Efficient Route toward Improved Energetics within the Framework of Density-Corrected Density Functional Theory.Journal of chemical theory and computation · 2023Article
- Realistic phase diagram of water from "first principles" data-driven quantum simulations.Nature communications · 2023Article
- Accurate descriptions of molecule-surface interactions in electrocatalytic CONature communications · 2023Article
- Extending density functional theory with near chemical accuracy beyond pure water.Nature communications · 2023Article
- A Benchmark Protocol for DFT Approaches and Data-Driven Models for Halide-Water Clusters.Molecules (Basel, Switzerland) · 2022Article
- Fragme∩t: An Open-Source Framework for Multiscale Quantum Chemistry Based on Fragmentation.Wiley interdisciplinary reviews. Computational molecular scienceArticle
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Authors and funding
4 authors.
Funding
Abstract
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. 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 "gold standard" coupled-cluster theory. Building upon the accuracy of DC-SCAN within a many-body formalism, we introduce a data-driven many-body potential energy function, MB-SCAN(DC), that quantitatively reproduces coupled cluster reference values for interaction, binding, and individual many-body energies of water clusters. Importantly, molecular dynamics simulations carried out with MB-SCAN(DC) also reproduce the properties of liquid water, which thus demonstrates that MB-SCAN(DC) is effectively the first DFT-based model that correctly describes water from the gas to the liquid phase.
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