Glass transition and dynamics of semiflexible polymer brushes

Literature Information

Publication Date 2021-05-28
DOI 10.1039/D1CP00089F
Impact Factor 3.676
Authors

Jian-Hua Huang, Dan-Dan Sun, Rong-Xing Lu


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Abstract

The glass transition and dynamics of densely grafted semiflexible polymer brushes are studied by molecular dynamics simulation. The glass transition temperature (Tg) increases with the polymer rigidity. The local glass transition temperature (Tg,local) is estimated from the temperature-dependent dynamics of individual segments including the lateral position fluctuation and lateral mean square displacement. Different from the flexible polymer brush, Tg,local of semiflexible polymer brushes is roughly independent of the segment height. Our simulation reveals that the glass transition is in synchronism with an abrupt change of the chain conformation in semiflexible polymer brushes. When the temperature drops to near Tg, the semiflexible polymer chains elongate, tilt, and become more ordered. Moreover, enhanced segmental dynamics is observed at temperatures just above Tg for the semiflexible polymer brushes.

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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
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Self-citation Rate: 10.3%
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Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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