Combined Machine Learning and Atomistic Simulations Reveal Multi-State Hydration in Cationic Brushes in the Presence of Halide Counterions

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dc.contributor.authorIshraaq, Raashiq
dc.contributor.authorDas, Siddhartha
dc.date.accessioned2026-07-01T23:51:21Z
dc.date.issued2025
dc.description.abstractIn 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)...
dc.description.urihttps://doi.org/10.1039/d5cp02528a
dc.identifierhttps://doi.org/10.13016/mei2-m38o
dc.identifier.citationIshraaq, R., & Das, S. (2025). Combined machine learning and atomistic simulations reveal Multi-State hydration in cationic brushes in the presence of halide counterions. Physical Chemistry Chemical Physics, 27(43), 22901�22905. https://doi.org/10.1039/d5cp02528a
dc.identifier.urihttp://hdl.handle.net/1903/35757
dc.language.isoen
dc.publisherPhysical Chemistry Chemical Physics
dc.rightsAttribution-NonCommercial 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/
dc.subjectmachine learning
dc.subjectatomistic simulations
dc.subjectpolyelectrolyte brushes
dc.titleCombined Machine Learning and Atomistic Simulations Reveal Multi-State Hydration in Cationic Brushes in the Presence of Halide Counterions
dc.typearticle
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