Accurate Density Functional Theory for Non-Covalent Interactions in Charged Systems Article Swipe
YOU?
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· 2025
· Open Access
·
· DOI: https://doi.org/10.26434/chemrxiv-2025-jx112
Accurately modeling non-covalent interactions (NCIs) involving charged systems remains an outstanding challenge in Density Functional Theory (DFT), with implications across natural and life sciences, engineering, e.g., in biochemistry, catalysis, and materials science. For these interactions, the interplay between electrostatics, polarization, and dispersion leads to systematic errors of up to tens of kcal/mol in standard dispersion-enhanced DFT methods. We solve this problem by introducing (r2SCAN+MBD)@HF, a DFT method without empirically fitted parameters that combines the r2SCAN functional and many-body dispersion, both evaluated on Hartree-Fock densities. We show that the unique synergy of these three components enables balanced treatment of short- and long-range correlation, which is crucial for accurate description of NCIs involving charged systems. Evaluations on standard benchmarks and a new Metal Ion Protein Clusters dataset introduced here show that (r2SCAN+MBD)@HF significantly improves accuracy for NCIs involving charged systems while maintaining robust performance for neutral systems. Given the ubiquity of such interactions, (r2SCAN+MBD)@HF is broadly applicable from biochemistry and materials science, including for generating high-quality data to train machine-learning force fields.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.26434/chemrxiv-2025-jx112
- https://chemrxiv.org/engage/api-gateway/chemrxiv/assets/orp/resource/item/6823e916927d1c2e66a1e612/original/accurate-density-functional-theory-for-non-covalent-interactions-in-charged-systems.pdf
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Raw OpenAlex JSON
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https://openalex.org/W4410498363Canonical identifier for this work in OpenAlex
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https://doi.org/10.26434/chemrxiv-2025-jx112Digital Object Identifier
- Title
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Accurate Density Functional Theory for Non-Covalent Interactions in Charged SystemsWork title
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-05-19Full publication date if available
- Authors
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Heng Zhao, Balázs D. Lőrincz, Tobias Henkes, Dénes Berta, Péter R. Nagy, Alexandre Tkatchenko, Stefan VuckovicList of authors in order
- Landing page
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https://doi.org/10.26434/chemrxiv-2025-jx112Publisher landing page
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https://chemrxiv.org/engage/api-gateway/chemrxiv/assets/orp/resource/item/6823e916927d1c2e66a1e612/original/accurate-density-functional-theory-for-non-covalent-interactions-in-charged-systems.pdfDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://chemrxiv.org/engage/api-gateway/chemrxiv/assets/orp/resource/item/6823e916927d1c2e66a1e612/original/accurate-density-functional-theory-for-non-covalent-interactions-in-charged-systems.pdfDirect OA link when available
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Density functional theory, Covalent bond, Computer science, Physics, Chemistry, Computational chemistry, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.challenge | 11 |
| abstract_inverted_index.evaluated | 80 |
| abstract_inverted_index.including | 160 |
| abstract_inverted_index.interplay | 36 |
| abstract_inverted_index.involving | 5, 110, 135 |
| abstract_inverted_index.many-body | 77 |
| abstract_inverted_index.materials | 30, 158 |
| abstract_inverted_index.sciences, | 23 |
| abstract_inverted_index.treatment | 96 |
| abstract_inverted_index.Accurately | 0 |
| abstract_inverted_index.Functional | 14 |
| abstract_inverted_index.applicable | 154 |
| abstract_inverted_index.benchmarks | 116 |
| abstract_inverted_index.catalysis, | 28 |
| abstract_inverted_index.components | 93 |
| abstract_inverted_index.densities. | 83 |
| abstract_inverted_index.dispersion | 41 |
| abstract_inverted_index.functional | 75 |
| abstract_inverted_index.generating | 162 |
| abstract_inverted_index.introduced | 125 |
| abstract_inverted_index.long-range | 100 |
| abstract_inverted_index.parameters | 70 |
| abstract_inverted_index.systematic | 44 |
| abstract_inverted_index.Evaluations | 113 |
| abstract_inverted_index.description | 107 |
| abstract_inverted_index.dispersion, | 78 |
| abstract_inverted_index.empirically | 68 |
| abstract_inverted_index.introducing | 62 |
| abstract_inverted_index.maintaining | 139 |
| abstract_inverted_index.outstanding | 10 |
| abstract_inverted_index.performance | 141 |
| abstract_inverted_index.Hartree-Fock | 82 |
| abstract_inverted_index.biochemistry | 156 |
| abstract_inverted_index.correlation, | 101 |
| abstract_inverted_index.engineering, | 24 |
| abstract_inverted_index.high-quality | 163 |
| abstract_inverted_index.implications | 18 |
| abstract_inverted_index.interactions | 3 |
| abstract_inverted_index.non-covalent | 2 |
| abstract_inverted_index.biochemistry, | 27 |
| abstract_inverted_index.interactions, | 34, 150 |
| abstract_inverted_index.polarization, | 39 |
| abstract_inverted_index.significantly | 130 |
| abstract_inverted_index.(r2SCAN+MBD)@HF | 129, 151 |
| abstract_inverted_index.electrostatics, | 38 |
| abstract_inverted_index.(r2SCAN+MBD)@HF, | 63 |
| abstract_inverted_index.machine-learning | 167 |
| abstract_inverted_index.dispersion-enhanced | 54 |
| cited_by_percentile_year | |
| countries_distinct_count | 3 |
| institutions_distinct_count | 7 |
| citation_normalized_percentile.value | 0.1578099 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |