掺杂剂
兴奋剂
选择(遗传算法)
材料科学
半导体
光电子学
纳米技术
计算机科学
人工智能
作者
Yifeng Zheng,Xuefen Cai,Su‐Huai Wei
出处
期刊:Journal of Semiconductors
[IOP Publishing]
日期:2024-11-01
卷期号:45 (11): 112101-112101
标识
DOI:10.1088/1674-4926/24050032
摘要
Abstract The choices of proper dopants and doping sites significantly influence the doping efficiency. In this work, using doping in AlN as an example, we discuss how to choose dopants and doping sites in semiconductors to create shallow defect levels. By comparing the defect properties of C N , O N , Mg Al , and Si Al in AlN and analyzing the pros and cons of different doping approaches from the aspects of size mismatch between dopant and host elements, electronegativity difference and perturbation to the band edge states after the substitution, we propose that Mg Al and Si Al should be the best dopants and doping sites for p-type and n-type doping, respectively. Further first-principles calculations verify our predictions as these defects present lower formation energies and shallower defect levels. The defect charge distributions also show that the band edge states, which mainly consist of N- s and p orbitals, are less perturbed when Al is substituted, therefore, the derived defect states turn out to be delocalized, opposite to the situation when N is substituted. This approach of analyzing the band structure of the host material and choosing dopants and doping sites to minimize the perturbation on the host band structure is general and can provide reliable estimations for finding shallow defect levels in semiconductors.
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