A coarse-grained model of room-temperature ionic liquids between metal electrodes: a molecular dynamics study

Literature Information

Publication Date 2022-04-28
DOI 10.1039/D2CP00166G
Impact Factor 3.676
Authors

Benjamin Bobin Ye, Zhen-Gang Wang


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Abstract

Recent mean-field theories predict that room-temperature ionic liquid (RTIL) electric double-layer capacitors (EDLCs) undergo a spontaneous surface charge separation (SSCS) with no applied potential. In this study, we construct a coarse-grained molecular model that corresponds to the mean-field models to directly simulate the behavior of RTILs without invoking mean-field approximations. In addition to observing the SSCS transition, we highlight the importance of the image charge interactions and explore the enhanced in-plane ordering on the electrodes, two effects not accounted for by the mean-field theories. By calculating and comparing the differential capacitance for RTILs confined between perfectly conducting and non-metal electrodes, we show that the image charge interactions drastically improve the energy storage properties of RTIL EDLCs.

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Source Journal

Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
Articles per Year: 3036

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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