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(CH<sub>3</sub>)<sub>3</sub>}<sup>+</sup> functional group of the PMETA (([poly(2-(methacryloyloxy)ethyl) trimethylammonium) cationic brushes.
Authors
- Siddhartha Das (ORCID: https://orcid.org/0000-0002-1705-721X)
- Raashiq Ishraaq (ORCID: https://orcid.org/0000-0002-5935-2284)
Institutions
- University of Maryland, College Park (US)
Publication Details
- Journal
- Physical Chemistry Chemical Physics
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d5cp02528a
- Primary Topic
- Radioactive element chemistry and processing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- U.S. Department of Energy
- Office of Science