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定量阴极发光映射:CdMgSeTe薄膜案例研究。

Quantitative Cathodoluminescence Mapping: A CdMgSeTe Thin-Film Case Study.

作者信息

Torabi Aida, Sullivan James, Reich Carey, Wunch Melissa A, Garcia Juan Alexandro, Beck Claudia, Munshi Amit H, Shimpi Tushar, Roberts Mienie, Sampath Walajabad, Harvey Taylor B

机构信息

Department of Science and Mathematics, Texas A&M University-Central Texas, Killeen, Texas 76549, United States.

Department of Mechanical Engineering, Colorado State University, Fort Collins, Colorado 80523, United States.

出版信息

ACS Omega. 2022 Oct 5;7(41):36873-36879. doi: 10.1021/acsomega.2c05640. eCollection 2022 Oct 18.

DOI:10.1021/acsomega.2c05640
PMID:36278043
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9583303/
Abstract

Full-spectrum cathodoluminescence (CL) mapping provides a point-by-point spatial measurement of the apparent band gap of a semiconductor thin film. In most studies, analysis of the electrical film properties from CL is presented as color mapping images. We have developed a spectra data analysis algorithm to functionalize, analyze, and generate statistical measurements of the luminescence data to provide additional insights. This algorithm was coded in the R language program, and a set of CdMgSeTe films were studied as an application case study. CL maps were measured for samples with different luminescent responses. A quantitative measure of the heterogeneity of the films was generated by statistical analysis of luminescent intensity and wavelength, spectra type curves, frequency distributions of peak wavelength, and relative intensity maps. The final CL analysis facilitates the investigation of the CdMgSeTe films and has potential applications for many semiconductor films.

摘要

全光谱阴极发光(CL)映射提供了半导体薄膜表观带隙的逐点空间测量。在大多数研究中,从CL对薄膜电学性质的分析以彩色映射图像呈现。我们开发了一种光谱数据分析算法,用于对发光数据进行功能化、分析和生成统计测量,以提供更多见解。该算法用R语言程序编码,并以一组CdMgSeTe薄膜作为应用案例进行研究。对具有不同发光响应的样品测量了CL映射。通过对发光强度和波长、光谱类型曲线、峰值波长频率分布以及相对强度映射的统计分析,生成了薄膜异质性的定量度量。最终的CL分析有助于对CdMgSeTe薄膜进行研究,并对许多半导体薄膜具有潜在应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7555/9583303/c3bda967204a/ao2c05640_0008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7555/9583303/c3a31d0b33cf/ao2c05640_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7555/9583303/8214497b1227/ao2c05640_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7555/9583303/7d88bc61df45/ao2c05640_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7555/9583303/f111a4a27769/ao2c05640_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7555/9583303/33f607691638/ao2c05640_0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7555/9583303/695eb920a839/ao2c05640_0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7555/9583303/c3bda967204a/ao2c05640_0008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7555/9583303/c3a31d0b33cf/ao2c05640_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7555/9583303/8214497b1227/ao2c05640_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7555/9583303/7d88bc61df45/ao2c05640_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7555/9583303/f111a4a27769/ao2c05640_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7555/9583303/33f607691638/ao2c05640_0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7555/9583303/695eb920a839/ao2c05640_0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7555/9583303/c3bda967204a/ao2c05640_0008.jpg

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本文引用的文献

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Nanoscale light element identification using machine learning aided STEM-EDS.使用机器学习辅助的扫描透射电子显微镜-能谱仪进行纳米级轻元素识别。
Sci Rep. 2020 Aug 13;10(1):13699. doi: 10.1038/s41598-020-70674-y.
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Understanding semiconductor nanostructures via advanced electron microscopy and spectroscopy.通过先进电子显微镜和光谱学理解半导体纳米结构。
Nanotechnology. 2019 Jun 28;30(26):262001. doi: 10.1088/1361-6528/ab0b0a. Epub 2019 Feb 27.
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Cathodoluminescence in the scanning transmission electron microscope.扫描透射电子显微镜中的阴极发光
Ultramicroscopy. 2017 May;176:112-131. doi: 10.1016/j.ultramic.2017.03.014. Epub 2017 Mar 16.
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Influence of composition on the performance of sintered Cu(In,Ga)Se2 nanocrystal thin-film photovoltaic devices.组成对烧结 Cu(In,Ga)Se2 纳米晶薄膜光伏器件性能的影响。
ChemSusChem. 2013 Mar;6(3):481-6. doi: 10.1002/cssc.201200677. Epub 2013 Feb 11.