A Model Based on Electronegativity and Orbital Radius for the Design of Low Hole Effective Mass P-Type TCMs
Source abstract
Abstract
Typical oxides have poor hole mobility and severely limit the development of current and future optoelectronic devices. The current challenge lies in the fact that the strong electronegativity of oxygen ions in transparent conducting oxide leads to low hole mobility and poor hole doping, and thus difficult to realize p-type materials with high conductivity. To achieve high hole mobility transparent conducting materials (TCMs), we establish a model for the design of low hole effective mass TCMs via electronegativity and orbital radius. Herein, two physical parameters are defined: the ratio of anion electronegativity to cation ( χ ∓ ) and the ratio of anion orbital radius to cation ( R ∓ ). This model describes the relationship between the hole effective mass and the two physical parameters. The low hole effective mass ( m h < 1.5 m 0 ) requires a large orbital radius ratio ( R ∓ > 0.49) to expect good hole mobility, where R n ∓ is highly dependent on χ n ∓ . We demonstrate the generality of our model on 50 oxides and chalcogenides, covering binary, ternary, and quaternary systems. Our analysis leads to the underlying mechanism for low hole effective mass due to electronegativity effects. Electronegativity decreases alongside group VI (O, S, Se, Te), leading to an increase in p-orbital size, capable of achieving greater valence band dispersion and lower hole effective mass. This work offers a simple and effective approach to guide the design of low hole effective mass TCMs, only requiring the hand-held parameters of electronegativity and orbital radius of the constituent elements.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: ZnO doping and properties · Semiconductor materials and devices · Copper-based nanomaterials and applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Sciences
Southwest Petroleum University
Institute for Artificial Intelligence
Key Laboratory of High Performance Scientific Computation, School of Science
Xihua University
Institute of Atomic and Molecular Physics
Sichuan University
Funding
Sichuan Provincial Science and Technology Support Program · Southwest Petroleum University
References (43)
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