Bridging Quantum Mechanics to Liquid Properties via a Universal Organic Force Field

[2508.08575] Bridging Quantum Mechanics to Liquid Properties via a Universal Organic Force Field Skip to main content Search Submit Donate Log in Physics > Computational Physics arXiv:2508.08575 (physics) [Submitted on 12 Aug 2025 ( v1 ), last revised 27 Aug 2026 (this version, v5)] Title: Bridging Quantum Mechanics to Liquid Properties via a Universal Organic Force Field Authors: Tianze Zheng , Xingyuan Xu , Zhi Wang , Zhenze Yang , Yuanheng Wang , Xu Han , Lei Chen , Zhenliang Mu , Ziqing Zhang , Siyuan Liu , Sheng Gong , Kuang Yu , Wen Yan View PDF Abstract: Molecular dynamics simulations are essential tools for unraveling atomic-level insights into the structure and behavior of condensed-phase systems. However, the universal and accurate prediction of macroscopic properties based on quantum mechanical calculations remains a significant challenge, often hindered by the trade-off between computational cost and simulation accuracy. Here we present ByteFF-Pol, a polarizable force field parameterized by a graph neural network and trained exclusively on high-level quantum mechanical data. By leveraging physically-motivated force field forms and training strategies, ByteFF-Pol predicts thermodynamic and transport properties for a wide range of small-molecule liquids and electrolytes with high accuracy, surpassing current classical and machine learning force fields. This ability to make predictions without system-specific training bridges the gap between microscopic calculations and macroscopic liquid properties, enabling the exploration of previously intractable chemical spaces. This advancement enables the precise design of new electrolytes and custom-tailored solvents, establishing a robust foundation for data-driven materials discovery. Subjects: Computational Physics (physics.comp-ph) ; Chemical Physics (physics.chem-ph) Cite as: arXiv:2508.08575 [physics.comp-ph] (or arXiv:2508.08575v5 [physics.comp-ph] for this version) https://doi.org/10.48550/arXiv.2508.08575 Focus to learn more arXiv-issued DOI via DataCite Journal reference: Nat Commun 17, 8276 (2026) Related DOI : https://doi.org/10.1038/s41467-026-73566-3 Focus to learn more DOI(s) linking to related resources Submission history From: Tianze Zheng [ view email ] [v1] Tue, 12 Aug 2025 02:22:38 UTC (2,231 KB) [v2] Wed, 13 Aug 2025 02:36:23 UTC (2,230 KB) [v3] Thu, 14 Aug 2025 01:21:21 UTC (2,239 KB) [v4] Thu, 15 Jan 2026 09:48:35 UTC (2,457 KB) [v5] Thu, 27 Aug 2026 03:22:01 UTC (7,307 KB) Full-text links: Access Paper: View PDF TeX Source view license Current browse context: physics.comp-ph < prev | next > new | recent | 2025-08 Change to browse by: physics physics.chem-ph References & Citations SciX Google Scholar Semantic Scholar export BibTeX citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab)

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