Controlling ion transport through nanopores: modeling transistor behavior
文献信息
Eszter Mádai, Bartłomiej Matejczyk, András Dallos, Mónika Valiskó
We present a modeling study of a nanopore-based transistor computed by a mean-field continuum theory (Poisson–Nernst–Planck, PNP) and a hybrid method including particle simulation (Local Equilibrium Monte Carlo, LEMC) that is able to take ionic correlations into account including the finite size of ions. The model is composed of three regions along the pore axis with the left and right regions determining the ionic species that is the main charge carrier, and the central region tuning the concentration of that species and, thus, the current flowing through the nanopore. We consider a model of small dimensions with the pore radius comparable to the Debye-screening length (Rpore/λD ≈ 1), which, together with large surface charges provides a mechanism for creating depletion zones and, thus, controlling ionic current through the device. We report the scaling behavior of the device as a function of the Rpore/λD parameter. Qualitative agreement between PNP and LEMC results indicates that mean-field electrostatic effects predominantly determine device behavior.
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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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