The excess electron at polyethylene interfaces
Literature Information
Fernan Saiz, David Cubero, Nick Quirke
This work investigates the energy and spatial properties of excess electrons in polyethylene in bulk phases and, for the first time, at amorphous vacuum interfaces using a pseudopotential single-electron method (Lanczos diagonalisation) and density functional theory (DFT). DFT calculations are made employing two approaches: with pseudopotentials/plane waves and the local-density approximation; and with all-electron Gaussian basis functions at the B3LYP level of theory, supplemented with a lattice of ghost atoms. All three methods predict similar spatial localisation of the excess electron, but a reliable comparison of its energy can only be made between the Lanczos and DFT using Gaussian bases. While Lanczos predicts that an excess electron would preferentially localise in nanovoids with diameters smaller than 1 nm, DFT suggests that it would localise on surfaces in nanovoids larger than 1 nm. Overall we conclude that in DFT studies of polyethylene/vacuum interfaces at the current level of theory, orbital-based methods provide a useful representation of excess electron properties.
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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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