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Microscopic Mechanism of Proton Transfer in Pure Water under Ambient Conditions
Water molecules and the associated proton transfer (PT) are prevalent in chemical and biological systems and have been a hot research topic. Spectroscopic characterization and ab initio molecular dynamics (AIMD) simulations have previously revealed insights into acidic and basic liquids. Presumably,...
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Published in: | Journal of chemical theory and computation 2023-07, Vol.19 (13), p.4243-4254 |
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creator | Huo, Jun Chen, Jianghao Liu, Pei Hong, Benkun Zhang, Jian Dong, Hao Li, Shuhua |
description | Water molecules and the associated proton transfer (PT) are prevalent in chemical and biological systems and have been a hot research topic. Spectroscopic characterization and ab initio molecular dynamics (AIMD) simulations have previously revealed insights into acidic and basic liquids. Presumably, the situation in the acidic/basic solution is not necessarily the same as in pure water; in addition, the autoionization constant for water is only 10–14 under ambient conditions, making the study of PT in pure water challenging. To overcome this issue, we modeled periodic water box systems containing 1000 molecules for tens of nanoseconds based on a neural network potential (NNP) with quantum mechanical accuracy. The NNP was generated by training a dataset containing the energies and atomic forces of 17 075 configurations of periodic water box systems, and these data points were calculated at the MP2 level that considers electron correlation effects. We found that the size of the system and the duration of the simulation have a significant impact on the convergence of the results. With these factors considered, our simulations showed that hydronium (H3O+) and hydroxide (OH–) ions in water have distinct hydration structures, thermodynamic and kinetic properties, e.g., the longer-lasting and more stable hydrated structure of OH– ions than that of H3O+, as well as a significantly higher free energy barrier for the OH–-associated PT than that of H3O+, leading the two to exhibit completely different PT behaviors. Given these characteristics, we further found that PT via OH– ions tends not to occur multiple times or between many molecules. In contrast, PT via H3O+ can synergistically occur among multiple molecules and prefers to adopt a cyclic pattern among three water molecules, while it occurs mostly in a chain pattern when more water molecules are involved. Therefore, our studies provide a detailed and solid microscopic explanation for the PT process in pure water. |
doi_str_mv | 10.1021/acs.jctc.3c00244 |
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Spectroscopic characterization and ab initio molecular dynamics (AIMD) simulations have previously revealed insights into acidic and basic liquids. Presumably, the situation in the acidic/basic solution is not necessarily the same as in pure water; in addition, the autoionization constant for water is only 10–14 under ambient conditions, making the study of PT in pure water challenging. To overcome this issue, we modeled periodic water box systems containing 1000 molecules for tens of nanoseconds based on a neural network potential (NNP) with quantum mechanical accuracy. The NNP was generated by training a dataset containing the energies and atomic forces of 17 075 configurations of periodic water box systems, and these data points were calculated at the MP2 level that considers electron correlation effects. We found that the size of the system and the duration of the simulation have a significant impact on the convergence of the results. With these factors considered, our simulations showed that hydronium (H3O+) and hydroxide (OH–) ions in water have distinct hydration structures, thermodynamic and kinetic properties, e.g., the longer-lasting and more stable hydrated structure of OH– ions than that of H3O+, as well as a significantly higher free energy barrier for the OH–-associated PT than that of H3O+, leading the two to exhibit completely different PT behaviors. Given these characteristics, we further found that PT via OH– ions tends not to occur multiple times or between many molecules. In contrast, PT via H3O+ can synergistically occur among multiple molecules and prefers to adopt a cyclic pattern among three water molecules, while it occurs mostly in a chain pattern when more water molecules are involved. Therefore, our studies provide a detailed and solid microscopic explanation for the PT process in pure water.</description><identifier>ISSN: 1549-9618</identifier><identifier>EISSN: 1549-9626</identifier><identifier>DOI: 10.1021/acs.jctc.3c00244</identifier><identifier>PMID: 37365994</identifier><language>eng</language><publisher>United States: American Chemical Society</publisher><subject>Autoionization ; Condensed Matter, Interfaces, and Materials ; Data points ; Free energy ; Molecular dynamics ; Neural networks ; Protons ; Quantum mechanics ; Simulation ; Water chemistry</subject><ispartof>Journal of chemical theory and computation, 2023-07, Vol.19 (13), p.4243-4254</ispartof><rights>2023 American Chemical Society</rights><rights>Copyright American Chemical Society Jul 11, 2023</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a364t-111ecfbcbe608adec0a05b2f609eb5c220265a4230684ee9f020955af5bf1ac83</citedby><cites>FETCH-LOGICAL-a364t-111ecfbcbe608adec0a05b2f609eb5c220265a4230684ee9f020955af5bf1ac83</cites><orcidid>0000-0001-6756-057X ; 0000-0003-2338-0395 ; 0000-0001-7280-7506 ; 0000-0002-4462-6414</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37365994$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Huo, Jun</creatorcontrib><creatorcontrib>Chen, Jianghao</creatorcontrib><creatorcontrib>Liu, Pei</creatorcontrib><creatorcontrib>Hong, Benkun</creatorcontrib><creatorcontrib>Zhang, Jian</creatorcontrib><creatorcontrib>Dong, Hao</creatorcontrib><creatorcontrib>Li, Shuhua</creatorcontrib><title>Microscopic Mechanism of Proton Transfer in Pure Water under Ambient Conditions</title><title>Journal of chemical theory and computation</title><addtitle>J. Chem. Theory Comput</addtitle><description>Water molecules and the associated proton transfer (PT) are prevalent in chemical and biological systems and have been a hot research topic. Spectroscopic characterization and ab initio molecular dynamics (AIMD) simulations have previously revealed insights into acidic and basic liquids. Presumably, the situation in the acidic/basic solution is not necessarily the same as in pure water; in addition, the autoionization constant for water is only 10–14 under ambient conditions, making the study of PT in pure water challenging. To overcome this issue, we modeled periodic water box systems containing 1000 molecules for tens of nanoseconds based on a neural network potential (NNP) with quantum mechanical accuracy. The NNP was generated by training a dataset containing the energies and atomic forces of 17 075 configurations of periodic water box systems, and these data points were calculated at the MP2 level that considers electron correlation effects. We found that the size of the system and the duration of the simulation have a significant impact on the convergence of the results. With these factors considered, our simulations showed that hydronium (H3O+) and hydroxide (OH–) ions in water have distinct hydration structures, thermodynamic and kinetic properties, e.g., the longer-lasting and more stable hydrated structure of OH– ions than that of H3O+, as well as a significantly higher free energy barrier for the OH–-associated PT than that of H3O+, leading the two to exhibit completely different PT behaviors. Given these characteristics, we further found that PT via OH– ions tends not to occur multiple times or between many molecules. In contrast, PT via H3O+ can synergistically occur among multiple molecules and prefers to adopt a cyclic pattern among three water molecules, while it occurs mostly in a chain pattern when more water molecules are involved. Therefore, our studies provide a detailed and solid microscopic explanation for the PT process in pure water.</description><subject>Autoionization</subject><subject>Condensed Matter, Interfaces, and Materials</subject><subject>Data points</subject><subject>Free energy</subject><subject>Molecular dynamics</subject><subject>Neural networks</subject><subject>Protons</subject><subject>Quantum mechanics</subject><subject>Simulation</subject><subject>Water chemistry</subject><issn>1549-9618</issn><issn>1549-9626</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNp1kEtLAzEURoMotlb3rmTAjQtbb5JJOrMsxRe0tIuKy5DJJJjSSWoys_Dfm9rWheAmDzjfdy8HoWsMIwwEP0gVR2vVqhFVACTPT1Afs7wclpzw0983LnroIsY1AKU5oeeoR8eUs7LM-2gxtyr4qPzWqmyu1Yd0NjaZN9ky-Na7bBWki0aHzLps2QWdvcs2_TpXp3PSVFa7Npt6V9vWehcv0ZmRm6ivDvcAvT09rqYvw9ni-XU6mQ0l5Xk7xBhrZSpVaQ6FrLUCCawihkOpK6YIAcKZTMsCL3KtSwMESsakYZXBUhV0gO72vdvgPzsdW9HYqPRmI532XRSkoEkQ4wVP6O0fdO274NJ2icqhACjKcaJgT-10xKCN2AbbyPAlMIidbJFki51scZCdIjeH4q5qdP0bONpNwP0e-Ikeh_7b9w0F5Ipv</recordid><startdate>20230711</startdate><enddate>20230711</enddate><creator>Huo, Jun</creator><creator>Chen, Jianghao</creator><creator>Liu, Pei</creator><creator>Hong, Benkun</creator><creator>Zhang, Jian</creator><creator>Dong, Hao</creator><creator>Li, Shuhua</creator><general>American Chemical Society</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SR</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>JG9</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-6756-057X</orcidid><orcidid>https://orcid.org/0000-0003-2338-0395</orcidid><orcidid>https://orcid.org/0000-0001-7280-7506</orcidid><orcidid>https://orcid.org/0000-0002-4462-6414</orcidid></search><sort><creationdate>20230711</creationdate><title>Microscopic Mechanism of Proton Transfer in Pure Water under Ambient Conditions</title><author>Huo, Jun ; Chen, Jianghao ; Liu, Pei ; Hong, Benkun ; Zhang, Jian ; Dong, Hao ; Li, Shuhua</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a364t-111ecfbcbe608adec0a05b2f609eb5c220265a4230684ee9f020955af5bf1ac83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Autoionization</topic><topic>Condensed Matter, Interfaces, and Materials</topic><topic>Data points</topic><topic>Free energy</topic><topic>Molecular dynamics</topic><topic>Neural networks</topic><topic>Protons</topic><topic>Quantum mechanics</topic><topic>Simulation</topic><topic>Water chemistry</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Huo, Jun</creatorcontrib><creatorcontrib>Chen, Jianghao</creatorcontrib><creatorcontrib>Liu, Pei</creatorcontrib><creatorcontrib>Hong, Benkun</creatorcontrib><creatorcontrib>Zhang, Jian</creatorcontrib><creatorcontrib>Dong, Hao</creatorcontrib><creatorcontrib>Li, Shuhua</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of chemical theory and computation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Huo, Jun</au><au>Chen, Jianghao</au><au>Liu, Pei</au><au>Hong, Benkun</au><au>Zhang, Jian</au><au>Dong, Hao</au><au>Li, Shuhua</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Microscopic Mechanism of Proton Transfer in Pure Water under Ambient Conditions</atitle><jtitle>Journal of chemical theory and computation</jtitle><addtitle>J. Chem. Theory Comput</addtitle><date>2023-07-11</date><risdate>2023</risdate><volume>19</volume><issue>13</issue><spage>4243</spage><epage>4254</epage><pages>4243-4254</pages><issn>1549-9618</issn><eissn>1549-9626</eissn><abstract>Water molecules and the associated proton transfer (PT) are prevalent in chemical and biological systems and have been a hot research topic. Spectroscopic characterization and ab initio molecular dynamics (AIMD) simulations have previously revealed insights into acidic and basic liquids. Presumably, the situation in the acidic/basic solution is not necessarily the same as in pure water; in addition, the autoionization constant for water is only 10–14 under ambient conditions, making the study of PT in pure water challenging. To overcome this issue, we modeled periodic water box systems containing 1000 molecules for tens of nanoseconds based on a neural network potential (NNP) with quantum mechanical accuracy. The NNP was generated by training a dataset containing the energies and atomic forces of 17 075 configurations of periodic water box systems, and these data points were calculated at the MP2 level that considers electron correlation effects. We found that the size of the system and the duration of the simulation have a significant impact on the convergence of the results. With these factors considered, our simulations showed that hydronium (H3O+) and hydroxide (OH–) ions in water have distinct hydration structures, thermodynamic and kinetic properties, e.g., the longer-lasting and more stable hydrated structure of OH– ions than that of H3O+, as well as a significantly higher free energy barrier for the OH–-associated PT than that of H3O+, leading the two to exhibit completely different PT behaviors. Given these characteristics, we further found that PT via OH– ions tends not to occur multiple times or between many molecules. In contrast, PT via H3O+ can synergistically occur among multiple molecules and prefers to adopt a cyclic pattern among three water molecules, while it occurs mostly in a chain pattern when more water molecules are involved. Therefore, our studies provide a detailed and solid microscopic explanation for the PT process in pure water.</abstract><cop>United States</cop><pub>American Chemical Society</pub><pmid>37365994</pmid><doi>10.1021/acs.jctc.3c00244</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0001-6756-057X</orcidid><orcidid>https://orcid.org/0000-0003-2338-0395</orcidid><orcidid>https://orcid.org/0000-0001-7280-7506</orcidid><orcidid>https://orcid.org/0000-0002-4462-6414</orcidid></addata></record> |
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subjects | Autoionization Condensed Matter, Interfaces, and Materials Data points Free energy Molecular dynamics Neural networks Protons Quantum mechanics Simulation Water chemistry |
title | Microscopic Mechanism of Proton Transfer in Pure Water under Ambient Conditions |
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