{"title":"基于软计算的砷化镓衬底量子点纳米结构分类与设计","authors":"A. Ürmös, Z. Farkas, T. Sandor, Á. Nemcsics","doi":"10.1109/SISY.2017.8080537","DOIUrl":null,"url":null,"abstract":"The parameters of the semiconductor devices can be improved by nanostructures significantly. For this reason, it is necessary to produce nanostructures with given parameters. The soft-computing design of the self-organized nanostructures and a new classification model will be discussed in this paper. These nanostructures are formed by droplet epitaxy on compound semiconductor substrate. The parameters of the nanostructures (type, size, distribution) depend on the applied technology. The key factors of the technology (substrate temperature, Ga flux, As pressure, annealing time and annealing temperature) will be determined as design parameters. These parameters are set in order to produce nanostructures with the desired property. The revised version of previously introduced nanostructure fuzzy-based classification model will be also discussed.","PeriodicalId":352891,"journal":{"name":"2017 IEEE 15th International Symposium on Intelligent Systems and Informatics (SISY)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Soft-computing based classification and design of quantum dot nanostructures on GaAs substrate\",\"authors\":\"A. Ürmös, Z. Farkas, T. Sandor, Á. Nemcsics\",\"doi\":\"10.1109/SISY.2017.8080537\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The parameters of the semiconductor devices can be improved by nanostructures significantly. For this reason, it is necessary to produce nanostructures with given parameters. The soft-computing design of the self-organized nanostructures and a new classification model will be discussed in this paper. These nanostructures are formed by droplet epitaxy on compound semiconductor substrate. The parameters of the nanostructures (type, size, distribution) depend on the applied technology. The key factors of the technology (substrate temperature, Ga flux, As pressure, annealing time and annealing temperature) will be determined as design parameters. These parameters are set in order to produce nanostructures with the desired property. The revised version of previously introduced nanostructure fuzzy-based classification model will be also discussed.\",\"PeriodicalId\":352891,\"journal\":{\"name\":\"2017 IEEE 15th International Symposium on Intelligent Systems and Informatics (SISY)\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE 15th International Symposium on Intelligent Systems and Informatics (SISY)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SISY.2017.8080537\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE 15th International Symposium on Intelligent Systems and Informatics (SISY)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SISY.2017.8080537","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Soft-computing based classification and design of quantum dot nanostructures on GaAs substrate
The parameters of the semiconductor devices can be improved by nanostructures significantly. For this reason, it is necessary to produce nanostructures with given parameters. The soft-computing design of the self-organized nanostructures and a new classification model will be discussed in this paper. These nanostructures are formed by droplet epitaxy on compound semiconductor substrate. The parameters of the nanostructures (type, size, distribution) depend on the applied technology. The key factors of the technology (substrate temperature, Ga flux, As pressure, annealing time and annealing temperature) will be determined as design parameters. These parameters are set in order to produce nanostructures with the desired property. The revised version of previously introduced nanostructure fuzzy-based classification model will be also discussed.