High throughput first-principles calculations of bixbyite oxides for TCO applications

Literature Information

Publication Date 2014-07-07
DOI 10.1039/C4CP02788D
Impact Factor 3.676
Authors

Nasrin Sarmadian, Rolando Saniz, Bart Partoens, Dirk Lamoen, Kalpana Volety, Guido Huyberechts, Johan Paul


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Abstract

We present a high-throughput computing scheme based on density functional theory (DFT) to generate a class of oxides and screen them with the aim of identifying those that might be electronically appropriate for transparent conducting oxide (TCO) applications. The screening criteria used are a minimum band gap to ensure sufficient transparency, a band edge alignment consistent with easy n- or p-type dopability, and a minimum thermodynamic phase stability to be experimentally synthesizable. Following this scheme we screened 23 binary and 1518 ternary bixbyite oxides in order to identify promising candidates, which can then be a subject of an in-depth study. The results for the known TCOs are in good agreement with the reported data in the literature. We suggest a list of several new potential TCOs, including both n- and p-type compounds.

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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
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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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