Transport phenomena of Cu–S–Te chalcogenide nanocomposites: frequency response and AC conductivity
Literature Information
Madhab Roy, Anil Chamuah, Koyel Bhattacharya
In this work, the development and electrical characterization of several chalcogenide nanocomposites have been reported. X-ray diffraction (XRD) has been used to reveal their microstructures. Mott's variable range hopping model has been used to interpret the DC conductivity data of the nanocomposites at lower temperatures. The DC conductivity data at higher temperatures has been explained well using Greave's model. To explain the AC conductivity data, the Meyer–Neldel (MN) conduction rule has been employed. The AC conductivity spectra at different temperatures have been analyzed using Almond–West formalism. Different conduction models, namely, correlated barrier hopping (CBH) and modified non-overlapping small polaron tunneling (NSPT), have been used to interpret the conduction mechanism of the nanocomposites. Scaling of the AC conductivity spectra reveals that the electrical relaxation process is independent of temperature, but depends on the nanocomposite composition. The conductivity mechanism is explained using a schematic structural model.
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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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