Computational assignment of redox states to Coulomb blockade diamonds
文献信息
Stine T. Olsen, Vaida Arcisauskaite, Jacob Kongsted, Kurt V. Mikkelsen
With the advent of molecular transistors, electrochemistry can now be studied at the single-molecule level. Experimentally, the redox chemistry of the molecule manifests itself as features in the observed Coulomb blockade diamonds. We present a simple theoretical method for explicit construction of the Coulomb blockade diamonds of a molecule. A combined quantum mechanical/molecular mechanical method is invoked to calculate redox energies and polarizabilities of the molecules, including the screening effect of the metal leads. This direct approach circumvents the need for explicit modelling of the gate electrode. From the calculated parameters the Coulomb blockade diamonds are constructed using simple theory. We offer a theoretical tool for assignment of Coulomb blockade diamonds to specific redox states in particular, and a study of chemical details in the diamonds in general. With the ongoing experimental developments in molecular transistor experiments, our tool could find use in molecular electronics, electrochemistry, and electrocatalysis.
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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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