{"title":"结合机器学习和原子模拟揭示了卤化物反离子存在下阳离子刷中的多态水合作用","authors":"Raashiq Ishraaq, Siddhartha Das","doi":"10.1039/d5cp02528a","DOIUrl":null,"url":null,"abstract":"In this communication, we employ a combination of all-atom molecular dynamics simulations and machine learning to establish the effect of different halide screening counterions (fluoride, chloride, bromide, and iodide ions) on the prevalence of two separate hydration states of the {N(CH<small><sub>3</sub></small>)<small><sub>3</sub></small>}<small><sup>+</sup></small> functional group of the PMETA (([poly(2-(methacryloyloxy)ethyl) trimethylammonium) cationic brushes.","PeriodicalId":99,"journal":{"name":"Physical Chemistry Chemical Physics","volume":"114 1","pages":""},"PeriodicalIF":2.9000,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Combined Machine Learning and Atomistic Simulations Reveal Multi-State Hydration in Cationic Brushes in the Presence of Halide Counterions\",\"authors\":\"Raashiq Ishraaq, Siddhartha Das\",\"doi\":\"10.1039/d5cp02528a\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this communication, we employ a combination of all-atom molecular dynamics simulations and machine learning to establish the effect of different halide screening counterions (fluoride, chloride, bromide, and iodide ions) on the prevalence of two separate hydration states of the {N(CH<small><sub>3</sub></small>)<small><sub>3</sub></small>}<small><sup>+</sup></small> functional group of the PMETA (([poly(2-(methacryloyloxy)ethyl) trimethylammonium) cationic brushes.\",\"PeriodicalId\":99,\"journal\":{\"name\":\"Physical Chemistry Chemical Physics\",\"volume\":\"114 1\",\"pages\":\"\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2025-10-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Physical Chemistry Chemical Physics\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://doi.org/10.1039/d5cp02528a\",\"RegionNum\":3,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"CHEMISTRY, PHYSICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physical Chemistry Chemical Physics","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1039/d5cp02528a","RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
Combined Machine Learning and Atomistic Simulations Reveal Multi-State Hydration in Cationic Brushes in the Presence of Halide Counterions
In this communication, we employ a combination of all-atom molecular dynamics simulations and machine learning to establish the effect of different halide screening counterions (fluoride, chloride, bromide, and iodide ions) on the prevalence of two separate hydration states of the {N(CH3)3}+ functional group of the PMETA (([poly(2-(methacryloyloxy)ethyl) trimethylammonium) cationic brushes.
期刊介绍:
Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions.
The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.