Compositional dependence of the direct and indirect band gaps in Ge1−ySny alloys from room temperature photoluminescence: implications for the indirect to direct gap crossover in intrinsic and n-type materials
Compositional dependence of the direct and indirect band gaps in Ge1−ySny alloys from room temperature photoluminescence: implications for the indirect to direct gap crossover in intrinsic and n-type materials
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DOI：
10.1088/0268-1242/29/11/115028
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发表时间：
2014-10
影响因子：
1.9
通讯作者：
L. Jiang;J. Gallagher;C. L. Senaratne;T. Aoki;J. Mathews;J. Kouvetakis;J. Menéndez
中科院分区：
文献类型：
--
作者：
L. Jiang;J. Gallagher;C. L. Senaratne;T. Aoki;J. Mathews;J. Kouvetakis;J. Menéndez
Ge1−ySny 合金中最低直接和间接带隙的成分依赖性已通过室温光致发光测量确定。该技术对于比较两个跃迁特别有吸引力，因为光谱中的不同特征可以与直接和间接间隙相关联。然而，需要对这些室温光谱进行详细建模，以高精度提取带隙值，以确定合金成为直接带隙半导体的 Sn 浓度 yc 。对于直接带隙，这是使用微观模型来完成的，该模型可以以兆伏级精度确定直接带隙能量。对于间接能隙，表明当前的理论模型不足以描述具有紧密间接和直接跃迁的系统的发射特性。因此，使用临时程序从数据中提取间接能隙能量。对于 y ，远低于基于虚拟晶体近似的早期理论预测，但与基于大型原子超晶胞的预测更加一致。
The compositional dependence of the lowest direct and indirect band gaps in Ge1−ySny alloys has been determined from room-temperature photoluminescence measurements. This technique is particularly attractive for a comparison of the two transitions because distinct features in the spectra can be associated with the direct and indirect gaps. However, detailed modeling of these room temperature spectra is required to extract the band gap values with the high accuracy required to determine the Sn concentration yc at which the alloy becomes a direct gap semiconductor. For the direct gap, this is accomplished using a microscopic model that allows the determination of direct gap energies with meV accuracy. For the indirect gap, it is shown that current theoretical models are inadequate to describe the emission properties of systems with close indirect and direct transitions. Accordingly, an ad hoc procedure is used to extract the indirect gap energies from the data. For y , much lower than early theoretical predictions based on the virtual crystal approximation, but in better agreement with predictions based on large atomic supercells.