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Zwitterionic materials are an important class of antifouling biomaterials for various applications. Despite such desirable antifouling properties, molecular-level understanding of the structure–property relationship associated with surface chemistry/topology/hydration and antifouling performance still remains to be elucidated. In this work, we computationally studied the packing structure, surface hydration, and antifouling property of three zwitterionic polymer brushes of poly(carboxybetaine methacrylate) (pCBMA), poly(sulfobetaine methacrylate) (pSBMA), and poly((2-(methacryloyloxy)ethyl)phosporylcoline) (pMPC) brushes and a hydrophilic PEG brush using a combination of molecular mechanics (MM), Monte Carlo (MC), molecular dynamics (MD), and steered MD (SMD) simulations. We for the first time determined the optimal packing structures of all polymer brushes from a wide variety of unit cells and chain orientations in a complex energy landscape. Under the optimal packing structures, MD simulations were further conducted to study the structure, dynamics, and orientation of water molecules and protein adsorption on the four polymer brushes, while SMD simulations to study the surface resistance of the polymer brushes to a protein. The collective results consistently revealed that the three zwitterionic brushes exhibited stronger interactions with water molecules and higher surface resistance to a protein than the PEG brush. It was concluded that both the carbon space length between zwitterionic groups and the nature of the anionic groups have a distinct effect on the antifouling performance, leading to the following antifouling ranking of pCBMA > pMPC > pSBMA. This work hopefully provides some structural insights into the design of new antifouling materials beyond traditional PEG-based antifouling materials.
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polyGraft 1.0: A program for molecular structure and topology generation of polymer‐grafted hybrid nanostructures
Abstract Polymer‐grafted hybrid materials have been ubiquitously employed in various engineering applications. The design of these hybrid materials with superior performances requires a molecularly detailed understanding of the structure and dynamics of the polymer brushes and their interactions with the grafting substrate. Molecular dynamics (MD) simulations are very well suited for the study of these materials which can provide molecular insights into the effects of polymer composition and length, grafting density, substrate composition and curvatures, and nanoconfinement. However, few existing tools are available to generate such systems, which would otherwise reduce the barrier of preparation for such systems to enable high throughput simulations. Here polyGraft, a general, flexible, and easy to use Python program, is introduced for automated generation of molecular structure and topology of polymer grafted hybrid materials for MD simulations purposes, ranging from polymer brushes grafted to hard substrates, to densely grafted bottlebrush polymers. polyGraft is openly accessible on GitHub (https://github.com/nanogchen/polyGraft).
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- Award ID(s):
- 1916864
- PAR ID:
- 10452847
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Journal of Computational Chemistry
- Volume:
- 44
- Issue:
- 28
- ISSN:
- 0192-8651
- Page Range / eLocation ID:
- p. 2230-2239
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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