4.7 Article

Molecular Dynamics Simulation and PRISM Theory Study of Assembly in Solutions of Amphiphilic Bottlebrush Block Copolymers

期刊

MACROMOLECULES
卷 51, 期 19, 页码 7586-7599

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acs.macromol.8b01535

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资金

  1. National Science Foundation [NSF DMREF-1629156]
  2. Extreme Science and Engineering Discovery Environment (XSEDE) Stampede cluster at the University of Texas

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We use a coarse-grained model with both Polymer Reference Interaction Site Model (PRISM) theory and molecular dynamics (MD) simulations to study self-assembly of amphiphilic bottlebrush block copolymers (BCPs) in solution as a function of increasing solvophobicity of the solvophobic blocks. First, we evaluate the ability of PRISM theory to describe and predict structure (e.g., intermolecular pair correlation functions and structure factors) and thermodynamics (e.g., disorder to order/assembled state transition solvophobicity and critical micelle concentration) for solutions of bottlebrush BCPs for varying BCP sequence, composition and solution concentration. Direct comparison of intermolecular pair correlation functions and structure factors from PRISM theory with that from MD simulations shows excellent qualitative, with some quantitative, agreement. Additionally, PRISM theory results at low solvophobicities present signatures of the structures observed in MD simulations at higher solvophobicities. Comparisons of micro- and macrophase peaks of structure factors obtained from PRISM theory at low solvophobicities at various concentrations for linear and bottlebrush BCPs predict that linear BCPs have a lower critical micelle concentration (CMC) than bottlebrushes at the same molecular weight. These computationally less intensive theoretical predictions are confirmed by results from computationally more intensive MD simulations. Comparison of the microphase peak positions in the structure factors obtained from PRISM theory suggests that the bottlebrush BCPs form smaller micelles than linear BCPs at the same molecular weight, which is also confirmed visually and through cluster analysis of trajectories from MD simulations. Through this study, we show the power of using theory and simulations in an integrated and sequential manner to quickly explore a large set of soft materials design parameters for desired assembly.

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