{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T20:16:24Z","timestamp":1788466584541,"version":"build-2803163510"},"reference-count":57,"publisher":"American Chemical Society (ACS)","issue":"35","license":[{"start":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T00:00:00Z","timestamp":1787616000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100006151","name":"Basic Energy Sciences","doi-asserted-by":"publisher","award":["DE-SC0007347"],"award-info":[{"award-number":["DE-SC0007347"]}],"id":[{"id":"10.13039\/100006151","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,9,3]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Methanol\u2013water mixtures find use in many applications, particularly catalytic energy conversion processes. Their importance has motivated numerous computational studies, most of which employed molecular dynamics based on classical force fields. These enable simulations of large systems on long time scales but do not reliably describe reactive dynamics involving bond breaking and bond formation. In contrast, ab initio molecular dynamics (AIMD) based on density functional theory (DFT) is generally more reliable for such applications but has a high computational cost, which discourages systematic studies of alcohol-water mixtures. To remedy this, we trained a machine learning interatomic potential capable of probing the properties of aqueous methanol mixtures at the DFT level using the SCAN functional. Our results show that SCAN qualitatively reproduces multiple key experimental features arising from the amphiphilic nature of methanol, including density, diffusion coefficients, X-ray structure factors, and Kirkwood\u2013Buff integrals. We also find that structural correlations between water molecules are somewhat overestimated, leading to a stronger preferential association than that predicted by experiments. However, increasing the temperature by 30 K mitigates this effect and also recovers the correct mobilities of both methanol and water. These results indicate that SCAN provides an accurate description of methanol\u2013water mixtures, making it a reliable choice for investigating the reactive dynamics in such systems.<\/jats:p>","DOI":"10.1021\/acs.jpcb.6c03340","type":"journal-article","created":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:24:56Z","timestamp":1788222296000},"page":"8907-8915","source":"Crossref","is-referenced-by-count":0,"title":["Ab Initio Modeling\nof Aqueous Methanol Mixtures at\nDFT-SCAN Level Using Machine Learning Interatomic Potentials"],"prefix":"10.1021","volume":"130","author":[{"given":"Sanghyun J.","family":"Park","sequence":"first","affiliation":[{"name":"Princeton University , , , ,","place":["Princeton, New Jersey, United States, 08544"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5896-3158","authenticated-orcid":true,"given":"Annabella","family":"Selloni","sequence":"additional","affiliation":[{"name":"Princeton University , , , ,","place":["Princeton, New Jersey, United States, 08544"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"316","published-online":{"date-parts":[[2026,8,25]]},"reference":[{"key":"2026090315290481200_cit1","doi-asserted-by":"publisher","first-page":"342","DOI":"10.1038\/nchem.1595","article-title":"A homogeneous transition metal complex for clean hydrogen\nproduction from methanol\u2013water mixtures","volume":"5","author":"Rodri\u0301guez-Lugo","year":"2013","journal-title":"Nat. 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Liq."},{"key":"2026090315290481200_cit10","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1016\/j.molliq.2014.12.047","article-title":"Effect of\nhydrogen bonding on self-diffusion in methanol\/water liquid mixtures:\nA molecular dynamics simulation study","volume":"203","author":"Zhang","year":"2015","journal-title":"J. Mol.\nLiq."},{"key":"2026090315290481200_cit11","doi-asserted-by":"publisher","DOI":"10.1016\/j.molliq.2020.113664","article-title":"Temperature-dependent structure of methanol-water mixtures\non cooling: X-ray and neutron diffraction and molecular dynamics simulations","volume":"314","author":"Pethes","year":"2020","journal-title":"J. Mol. Liq."},{"key":"2026090315290481200_cit12","doi-asserted-by":"publisher","DOI":"10.1063\/5.0233900","article-title":"Molecular diffusion in aqueous methanol solutions:\nThe combined influence of hydrogen bonding and hydrophobic ends","volume":"161","author":"Zhu","year":"2024","journal-title":"J. Chem. 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Chem.\nPhys."},{"key":"2026090315290481200_cit54","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1021\/jz301992u","article-title":"Kirkwood\u2013Buff\nintegrals for\nfinite volumes","volume":"4","author":"Kru\u0308ger","year":"2013","journal-title":"J. Phys. Chem. Lett."},{"key":"2026090315290481200_cit55","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.97.051301","article-title":"Size and shape dependence of finite-volume Kirkwood-Buff\nintegrals","volume":"97","author":"Kru\u0308ger","year":"2018","journal-title":"Phys. Rev. E"},{"key":"2026090315290481200_cit56","doi-asserted-by":"publisher","first-page":"2856","DOI":"10.1063\/1.447034","article-title":"Solute\u2013solute\ninteractions in water. II. An\nanalysis through the Kirkwood\u2013Buff integrals for 14 organic\nsolutes","volume":"80","author":"Matteoli","year":"1984","journal-title":"J. Chem. Phys."},{"key":"2026090315290481200_cit57","doi-asserted-by":"publisher","first-page":"2496","DOI":"10.1021\/jp983387p","article-title":"Kirkwood-\nBuff Integrals in Aqueous Alcohol Systems:\nComparison between Thermodynamic Calculations and X-Ray Scattering\nExperiments","volume":"103","author":"Shulgin","year":"1999","journal-title":"J. Phys. Chem. B"}],"container-title":["The Journal of Physical\nChemistry B"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/pubs.acs.org\/doi\/pdf\/10.1021\/acs.jpcb.6c03340","content-type":"application\/pdf","content-version":"vor","intended-application":"unspecified"},{"URL":"https:\/\/pubs.acs.org\/jpcbfk\/article-pdf\/130\/35\/8907\/67408836\/acs.jpcb.6c03340.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/pubs.acs.org\/jpcbfk\/article-pdf\/130\/35\/8907\/67408836\/acs.jpcb.6c03340.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T19:29:07Z","timestamp":1788463747000},"score":1,"resource":{"primary":{"URL":"https:\/\/pubs.acs.org\/jpcbfk\/article\/130\/35\/8907\/5329067\/Ab-Initio-Modeling-of-Aqueous-Methanol-Mixtures-at"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,25]]},"references-count":57,"journal-issue":{"issue":"35","published-online":{"date-parts":[[2026,8,25]]},"published-print":{"date-parts":[[2026,9,3]]}},"URL":"https:\/\/doi.org\/10.1021\/acs.jpcb.6c03340","relation":{},"ISSN":["1520-6106","1520-5207"],"issn-type":[{"value":"1520-6106","type":"print"},{"value":"1520-5207","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,25]]}}}