CaltechAUTHORS
  A Caltech Library Service

Wetting behavior of polyelectrolyte complex coacervates on solid surfaces

Balzer, Christopher and Zhang, Pengfei and Wang, Zhen-Gang (2022) Wetting behavior of polyelectrolyte complex coacervates on solid surfaces. Soft Matter, 18 (34). pp. 6326-6339. ISSN 1744-683X. doi:10.1039/d2sm00859a. https://resolver.caltech.edu/CaltechAUTHORS:20220817-896295000

[img] PDF - Supplemental Material
See Usage Policy.

817kB

Use this Persistent URL to link to this item: https://resolver.caltech.edu/CaltechAUTHORS:20220817-896295000

Abstract

The wetting behavior of complex coacervates underpins their use in many emerging applications of surface science, particularly wet adhesives and coatings. Many factors dictate if a coacervate phase will condense on a solid surface, including solution conditions, the nature of the polymer–substrate interaction, and the underlying supernatant–coacervate bulk phase behavior. In this work, we use a simple inhomogeneous mean-field theory to study the wetting behavior of complex coacervates on solid surfaces both off-coexistence (wetting transitions) and on-coexistence (contact angles). We focus on the effects of salt concentration, the polycation/polyanion surface affinity, and the applied electrostatic potential on the wettability. We find that the coacervate generally wets the surface via a first order wetting transition with second order transitions possible above a surface critical point. Applying an electrostatic potential to a solid surface always improves the surface wettability when the polycation/polyanion–substrate interaction is symmetric. For asymmetric surface affinity, the wettability has a nonmonotonic dependence with the applied potential. We use simple scaling and thermodynamic arguments to explain our results.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1039/D2SM00859ADOIArticle
https://www.rsc.org/suppdata/d2/sm/d2sm00859a/d2sm00859a1.pdfPublisherSupporting Information
ORCID:
AuthorORCID
Balzer, Christopher0000-0002-9767-8437
Zhang, Pengfei0000-0002-4226-1394
Wang, Zhen-Gang0000-0002-3361-6114
Additional Information:© The Royal Society of Chemistry 2022. Received 28th June 2022, Accepted 11th August 2022. C. B. is supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research, Department of Energy Computational Science Graduate Fellowship under Award Number DE-SC0020347. P. Z. acknowledges the financial support provided by the National Natural Science Foundation of China (NSFC grant no. 21803011 and 22073016). Z.-G. W. acknowledges financial support from the Hong Kong Quantum AI Lab Ltd. There are no conflicts to declare.
Funders:
Funding AgencyGrant Number
Department of Energy (DOE)DE-SC0020347
National Natural Science Foundation of China21803011
National Natural Science Foundation of China22073016
Hong Kong Quantum AI Lab Ltd.UNSPECIFIED
Issue or Number:34
DOI:10.1039/d2sm00859a
Record Number:CaltechAUTHORS:20220817-896295000
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20220817-896295000
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:116347
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:18 Aug 2022 22:13
Last Modified:02 Sep 2022 19:25

Repository Staff Only: item control page