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arXiv 2302.14547cond-mat.mtrl-sci
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应变工程三元III-V族半导体的精确第一性原理带隙预测

Accurate first-principle bandgap predictions in strain-engineered ternary III-V semiconductors

Badal Mondal, Marcel Kröner, Thilo Hepp, Kerstin Volz, Ralf Tonner-Zech

AI总结:

本文提出基于TB09密度泛函、能带展开和特殊准随机结构的计算协议,高效预测三元III-V半导体带隙随组分和应变的变化,并绘制多种材料的带隙相图以指导光电器件设计。

摘要:

通过改变材料组分或应变来调控三元III-V族半导体的带隙,是设计光电材料的主要途径。对大量可能目标结构进行筛选的实验方法受到巨大努力的阻碍,因为需要为每一个目标结构优化材料合成。我们提出了一种基于密度泛函理论的方法,能够高效地给出带隙随组分和应变的变化关系。利用专门为精确带隙计算而设计的特定密度泛函(TB09),结合能带展开程序和特殊准随机结构,我们开发了一种能够高效预测带隙的计算协议。通过与选定的实验数据进行比较,验证了该方法的准确性。因此,我们绘制了几个重要III-V化合物半导体的组分-应变相空间图(我们称之为“带隙相图”):GaAsP、GaAsN、GaPSb、GaAsSb、GaPBi和GaAsBi。我们展示了这些相图在识别最有前景的器件设计材料方面的应用。此外,我们的计算协议可以很容易地推广,以探索III-V材料中所有其他可能的III族和V族元素组合所构成的广阔化学空间。

英文摘要:

Tuning the bandgap in ternary III-V semiconductors via modification of the composition or the strain in the material is a major approach for the design of optoelectronic materials. Experimental approaches screening a large range of possible target structures are hampered by the tremendous effort to optimize the material synthesis for every target structure. We present an approach based on density functional theory efficiently capable of providing the bandgap as a function of composition and strain. Using a specific density functional designed for accurate bandgap computation (TB09) together with a band unfolding procedure and special quasirandom structures, we develop a computational protocol efficiently able to predict bandgaps. The approach's accuracy is validated by comparison to selected experimental data. We thus map the phase space of composition and strain (we call this the ``bandgap phase diagram'') for several important III-V compound semiconductors: GaAsP, GaAsN, GaPSb, GaAsSb, GaPBi, and GaAsBi. We show the application of these diagrams for identifying the most promising materials for device design. Furthermore, our computational protocol can easily be generalized to explore the vast chemical space of III-V materials with all other possible combinations of III- and V-elements.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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