Estimation of Nanoparticle’s Surface Electrostatic Potential in Solution Using Acid–Base Molecular Probes II: Insight from Atomistic Simulations of Micelles


Exploiting acid–base indicators as molecular probes is one of the most popular methods for determining the surface electrostatic potential Ψ in hydrophilic colloids like micellar surfactant solutions and related systems. Specifically, the indicator’s apparent acidity constant index is measured in the colloid solution of interest and, as a rule, in a nonionic surfactant solution; the difference between the two is proportional to Ψ. Despite the widespread use of this approach, a major problem remains unresolved, namely, the dissimilarity of Ψ values obtained with different indicators for the same system. The common point of view recognizes the effect of several factors (the choice of the nonionic surfactant, the probe’s localization, and the degree of hydration of micellar pseudophase) but does not allow to quantitatively assess their impact and decide which indicator reports the most correct Ψ value. Here, based on the ability to predict the reported Ψ values in silico, we examined the role of these factors using molecular dynamics simulations for five probes and two surfactants. The probe’s hydration in the Stern layer was found responsible for approximately half of the dissimilarity range. The probe’s localization is found important but hard to quantify because of the irregular structure of the Stern layer. The most accurate indicators among the examined set were identified. Supplementing experiments on measuring Ψ with molecular dynamics simulation is proposed as a way of improving the efficacy of the indicator method: the simulations can guide the choice of the most suitable probe and nonionic surfactant for the given nanoparticles.

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Divisions: College of Engineering & Physical Sciences > Aston Institute of Urban Technology and the Environment (ASTUTE)
College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
College of Engineering & Physical Sciences
College of Engineering & Physical Sciences > School of Computer Science and Digital Technologies > Applied Mathematics & Data Science
College of Engineering & Physical Sciences > School of Computer Science and Digital Technologies
Additional Information: This document is the Accepted Manuscript version of a Published Work that appeared in final form in The Journal of Physical Chemistry B, copyright © 2023 American Chemical Society, after peer review and technical editing by the publisher. To access the final edited and published work see: Funding & Acknowledgements: V. F. thanks the Ministry of Education and Science of Ukraine for financial support in the frame of the project #0120U101064. V. F. and D. N. acknowledge the use of HPC Midlands supercomputer funded by EPSRC, grant number EP/P020232/1; the access to HPC Call Spring 2021, EPSRC Tier-2 Cirrus Service; the access to Sulis Tier 2 HPC platform hosted by the Scientific Computing Research Technology Platform at the University of Warwick. Sulis is funded by EPSRC Grant EP/T022108/1 and the HPC Midlands+ consortium. N. M.-P. thanks the Ministry of Education and Science of Ukraine for financial support by the project #0122U001485.
Uncontrolled Keywords: Materials Chemistry,Surfaces, Coatings and Films,Physical and Theoretical Chemistry
Publication ISSN: 1520-5207
Last Modified: 08 Dec 2023 12:20
Date Deposited: 06 Feb 2023 18:49
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Related URLs: ... cs.jpcb.2c07028 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2023-02-02
Published Online Date: 2023-01-19
Accepted Date: 2022-10-28
Authors: Farafonov, Vladimir S.
Lebed, Alexander V.
Nerukh, Dmitry A. (ORCID Profile 0000-0001-9005-9919)
Mchedlov-Petrossyan, Nikolay O.



Version: Accepted Version

Access Restriction: Restricted to Repository staff only until 19 January 2024.

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