Band alignment in quantum wells from automatically tuned DFT+U
Literature Information
Chungwei Lin, Andrew Knyazev, Keisuke Kojima, Joseph Katz, Koichi Akiyama, Eiji Nakai, Hiroyuki Kawahara
Band alignment between two materials is of fundamental importance for a multitude of applications. However, density functional theory (DFT) either underestimates the bandgap – as is the case with the local density approximation (LDA) or generalized gradient approximation (GGA) – or is highly computationally demanding, as is the case with hybrid-functional methods. The latter can become prohibitive in electronic-structure calculations of supercells which describe quantum wells. We propose to apply the DFT+U method, with U for each atomic shell being treated as set of tuning parameters, to automatically fit the bulk bandgap and the lattice constant, and then use the thus obtained U parameters in large supercell calculations to determine the band alignment. We apply this procedure to InP/In0.5Ga0.5As, In0.5Ga0.5As/In0.5Al0.5As and InP/In0.5Al0.5As quantum wells, and obtain good agreement with experimental results. Although this procedure requires some experimental input, it provides both meaningful valence and conduction band offsets while, crucially, lattice relaxation is taken into account. The computational cost of this procedure is comparable to that of LDA. We believe that this is a practical procedure that can be useful for providing accurate estimates of band alignments between more complicated alloys.
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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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