Yuta Yamaji, K. Okaya, Gjergj Dodbiba, Li Pang Wang, T. Fujita
{"title":"一种利用拉曼光谱分离废弃电器中包括黑色塑料的新方法","authors":"Yuta Yamaji, K. Okaya, Gjergj Dodbiba, Li Pang Wang, T. Fujita","doi":"10.4144/RPSJ.60.65","DOIUrl":null,"url":null,"abstract":"Plastics have been used in various applications. The amount of domestic production in 2009 was 1.1 Mt. These days, mechanical recycling for the plastic is required, but one of the biggest problems of this method is how to separate black plastics. Black plastics contain carbon black as a colorant, which make them difficult to be identified by infrared adsorption (IR) spectroscopy. Thus, in this study, we are putting forward Raman spectroscopy for separating plastics (including black plastics) from the discarded appliances. There are reports which indicate that PP, PS, and ABS represent 70–80% of the discarded plastics. Each of them has its own characteristic peaks in Raman spectrum. In case of PP black plastics, nearly 100% of the feed can be identified, however, PS is difficult to be identified when carbon black content is about 3%. ABS of the discarded appliances was not identified. Finally, other fillers such as bromine flame retardants and calcium volume expander did not have any effect on Raman spectrum. In addition, we run some experiments for separating the discarded plastics by means of combining Raman identification with triboelectric separation. In Raman identification, the longer we exposure, the more amount of recovery we got, but grade was the highest in 1.0 s exposure, and it was over 95%. In triboelectric separation, however, the grade of ABS and PS were about 70%.","PeriodicalId":20971,"journal":{"name":"Resources Processing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A Novel Separation Method for Plastic of Discarded Appliance Including Black Plastic by Using Raman Spectroscopy\",\"authors\":\"Yuta Yamaji, K. Okaya, Gjergj Dodbiba, Li Pang Wang, T. Fujita\",\"doi\":\"10.4144/RPSJ.60.65\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Plastics have been used in various applications. The amount of domestic production in 2009 was 1.1 Mt. These days, mechanical recycling for the plastic is required, but one of the biggest problems of this method is how to separate black plastics. Black plastics contain carbon black as a colorant, which make them difficult to be identified by infrared adsorption (IR) spectroscopy. Thus, in this study, we are putting forward Raman spectroscopy for separating plastics (including black plastics) from the discarded appliances. There are reports which indicate that PP, PS, and ABS represent 70–80% of the discarded plastics. Each of them has its own characteristic peaks in Raman spectrum. In case of PP black plastics, nearly 100% of the feed can be identified, however, PS is difficult to be identified when carbon black content is about 3%. ABS of the discarded appliances was not identified. Finally, other fillers such as bromine flame retardants and calcium volume expander did not have any effect on Raman spectrum. In addition, we run some experiments for separating the discarded plastics by means of combining Raman identification with triboelectric separation. In Raman identification, the longer we exposure, the more amount of recovery we got, but grade was the highest in 1.0 s exposure, and it was over 95%. In triboelectric separation, however, the grade of ABS and PS were about 70%.\",\"PeriodicalId\":20971,\"journal\":{\"name\":\"Resources Processing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Resources Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4144/RPSJ.60.65\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Resources Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4144/RPSJ.60.65","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Novel Separation Method for Plastic of Discarded Appliance Including Black Plastic by Using Raman Spectroscopy
Plastics have been used in various applications. The amount of domestic production in 2009 was 1.1 Mt. These days, mechanical recycling for the plastic is required, but one of the biggest problems of this method is how to separate black plastics. Black plastics contain carbon black as a colorant, which make them difficult to be identified by infrared adsorption (IR) spectroscopy. Thus, in this study, we are putting forward Raman spectroscopy for separating plastics (including black plastics) from the discarded appliances. There are reports which indicate that PP, PS, and ABS represent 70–80% of the discarded plastics. Each of them has its own characteristic peaks in Raman spectrum. In case of PP black plastics, nearly 100% of the feed can be identified, however, PS is difficult to be identified when carbon black content is about 3%. ABS of the discarded appliances was not identified. Finally, other fillers such as bromine flame retardants and calcium volume expander did not have any effect on Raman spectrum. In addition, we run some experiments for separating the discarded plastics by means of combining Raman identification with triboelectric separation. In Raman identification, the longer we exposure, the more amount of recovery we got, but grade was the highest in 1.0 s exposure, and it was over 95%. In triboelectric separation, however, the grade of ABS and PS were about 70%.