Fei-Yu Chang, Mi Zhong, Zheng-Tang Liu, Qi-Jun Liu
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引用次数: 0
Abstract
Context
Due to the limitations of existing p-type transparent conductive oxides (TCOs), this study aims to identify alternative p-type TCO materials with improved performance through first-principles calculations. The electronic, optical, and transport properties of Mg3TeO6 were systematically investigated. Calculations show that Mg3TeO6 is a TCOs with a wide bandgap and good visible light transmittance at different thicknesses, indicating its potential applications in the field of transparent materials. The transport properties of Mg3TeO6 at room temperature were calculated, and it was found that the p-type conductivity of Mg3TeO6 can reach 6.95 S cm−1. It has certain comparability with some reported theoretical values of p-type TCO. These results suggest that Mg3TeO6 is a promising candidate for transparent electronics, although further experimental validation is required.
Method
First-principles calculations based on density functional theory and density functional perturbation theory were employed to execute all calculations in this work. The structural properties were optimized using GGA-PBE functionals, while HSE06 mixed functionals were used for accurate prediction of electronic band structures.
由于现有p型透明导电氧化物(TCO)的局限性,本研究旨在通过第一性原理计算确定具有改进性能的替代p型TCO材料。系统地研究了Mg3TeO6的电子、光学和输运性质。计算结果表明,Mg3TeO6是一种在不同厚度下具有宽禁带和良好可见光透过率的tco,表明其在透明材料领域具有潜在的应用前景。计算了Mg3TeO6在室温下的输运特性,发现Mg3TeO6的p型电导率可达6.95 S cm−1。它与一些已报道的p型TCO理论值具有一定的可比性。这些结果表明,Mg3TeO6是透明电子器件的有前途的候选者,尽管需要进一步的实验验证。方法采用基于密度泛函理论和密度泛函微扰理论的第一性原理计算方法进行计算。利用GGA-PBE泛函优化结构性能,利用HSE06混合泛函精确预测电子能带结构。
期刊介绍:
The Journal of Molecular Modeling focuses on "hardcore" modeling, publishing high-quality research and reports. Founded in 1995 as a purely electronic journal, it has adapted its format to include a full-color print edition, and adjusted its aims and scope fit the fast-changing field of molecular modeling, with a particular focus on three-dimensional modeling.
Today, the journal covers all aspects of molecular modeling including life science modeling; materials modeling; new methods; and computational chemistry.
Topics include computer-aided molecular design; rational drug design, de novo ligand design, receptor modeling and docking; cheminformatics, data analysis, visualization and mining; computational medicinal chemistry; homology modeling; simulation of peptides, DNA and other biopolymers; quantitative structure-activity relationships (QSAR) and ADME-modeling; modeling of biological reaction mechanisms; and combined experimental and computational studies in which calculations play a major role.