{"title":"Photoluminescence Spectral Analysis of GaInAsSb Semiconductor Layers","authors":"L. Small, S. Iyer","doi":"10.1109/SSST.1992.712353","DOIUrl":null,"url":null,"abstract":"A program was written to simulate the peaks using a combination of the Gaussian and Lorentzian distributions. Each peak was simulated and normalized separately over the entire range and then all the data were added together to produce the final spectra. The fitting parameters used were peak intensity, half width, and wavenumber. In order to identify the origin of the spectral peaks, temperature dependence and incident intensity dependence was analyzed. Subroutines were included in the spectral program evaluating the Bimberg, ShockleyRheed, and Varshni relationships as well as output intensity as a function of input intensity. Error analysis was done using the least-square method. This was performed within the program itself so that the error was calculated for each run. The best fit was then determined by comparing the analytical data to the experimental data and minimizing the error.","PeriodicalId":359363,"journal":{"name":"The 24th Southeastern Symposium on and The 3rd Annual Symposium on Communications, Signal Processing Expert Systems, and ASIC VLSI Design System Theory","volume":"78 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 24th Southeastern Symposium on and The 3rd Annual Symposium on Communications, Signal Processing Expert Systems, and ASIC VLSI Design System Theory","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSST.1992.712353","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
A program was written to simulate the peaks using a combination of the Gaussian and Lorentzian distributions. Each peak was simulated and normalized separately over the entire range and then all the data were added together to produce the final spectra. The fitting parameters used were peak intensity, half width, and wavenumber. In order to identify the origin of the spectral peaks, temperature dependence and incident intensity dependence was analyzed. Subroutines were included in the spectral program evaluating the Bimberg, ShockleyRheed, and Varshni relationships as well as output intensity as a function of input intensity. Error analysis was done using the least-square method. This was performed within the program itself so that the error was calculated for each run. The best fit was then determined by comparing the analytical data to the experimental data and minimizing the error.