Ion conducting particle networks in liquids: modeling of network percolation and stability
文献信息
Anna Jarosik, Uwe Traub, Joachim Maier, Armin Bunde
Networks of inorganic particles (here SiO2) formed within organic liquids play an important role in science. Recently they have been considered as ‘soggy sand’ electrolytes for Li-based batteries with a fascinating combination of mechanical and electrical properties. In this communication we model formation and stability of the networks by Cluster–Cluster Aggregation followed by coarsening on a different time scale. The comparison of computer simulations based on our model with experimental results obtained for LiClO4 containing polyethylene glycol reveals (i) that the percolation threshold for interfacial conductivity is very small, (ii) that the networks once formed coarsen with a time constant that is roughly independent of volume fraction and size—to a denser aggregate which then stays stable under operating condition. (iii) Trapping of the conducting solvent at high packing is also revealed.
期刊推荐

Saudi Pharmaceutical Journal

Russian Chemical Bulletin

Chemistry Education Research and Practice

Acta Materialia

Current Opinion in Solid State & Materials Science

Russian Journal of Applied Chemistry

Russian Journal of Coordination Chemistry

Current Opinion in Colloid & Interface Science

Russian Journal of General Chemistry

Russian Journal of Organic Chemistry
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Physical Chemistry Chemical Physics

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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