硅基Ⅳ族SiGeSn三元合金晶格结构、电子结构和光学性质的第一性原理
Journal of Synthetic Crystals（2021）
北京信息科技大学
Abstract
SiGeSn三元合金由于具有较二元合金更大的晶格和能带性质调控范围,是当前用于制作硅基激光器的热点材料.为全面且精确地研究其晶格结构、电子结构和光学性质,本文采用基于密度泛函理论(DFT)的第一性原理方法,并结合准随机近似和杂化泛函带隙修正,首先研究SiGeSn晶格常数及其弯曲系数的变化规律,并给出了解决GeSn二元晶格失配和压应变问题的方案.其次比较研究了SiGeSn与GeSn合金的能带结构,并通过态密度计算分析了Si的引入对合金带隙变化的物理机制.最后比较研究了SiGeSn与GeSn合金的介电函数谱、吸收系数、消光系数、反射率、折射率和发射率等光学性质.结果表明,SiGeSn晶格常数弯曲系数的变化与合金电负性差值的变化规律一致,Si-p电子态是SiGeSn合金带隙变化的最主要贡献.相比于同Sn浓度的GeSn合金,SiGeSn能保持直接带隙特征,且其带隙值和光吸收波长呈现更宽的变化范围.因此在拓宽硅基高效光源和光电探测器应用波段方面,SiGeSn相较于GeSn合金具有更大的应用潜力和优势.
More求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined