Hammad Hussain , Sonia Arshed , Shahbaz Nasir Khan , Sameera Haq Nawaz , Muhammad Yasin Naz , Rao Adeel Un Nabi
{"title":"利用统计导出的动力学速率常数将废弃高密度塑料热裂解成有价值的燃料","authors":"Hammad Hussain , Sonia Arshed , Shahbaz Nasir Khan , Sameera Haq Nawaz , Muhammad Yasin Naz , Rao Adeel Un Nabi","doi":"10.1016/j.clce.2025.100172","DOIUrl":null,"url":null,"abstract":"<div><div>Experimentally, empirical rate constants are used to extract liquid fuels and gases from the thermal decomposition of high-density plastics (HDPs). However, this approach is costly, time-consuming, and not commercially viable for producing a sustainable volume of liquid fuel. The prediction of rate constants is, therefore, imperative to boost the efficiency of the scaled destruction of plastic waste into fuels and other valuable products. We used the Box-Behnken technique in response surface methodology (RSM) to forecast temperature-dependent rate constants for thermal destruction of HDP. Most appropriate combinations of activation energies (Ea), exponential factors (Ao) and rate constants (k) were predicted statistically for better insight into HDP reaction mechanism for commercial scale production of oils and gases. The predicted parameters were used in a 2nd order ordinary differential solver to simulate the amount of oil and gases. The thermal treatment of HDP under optimized conditions resulted in 99 % oil production after 240 min of reaction. The formation of heavy wax was observed at the start of the reaction, and it changed to oil, light wax, and gases after 1 hour of processing. After 2 h, light wax production declined and oil production increased over time.</div></div>","PeriodicalId":100251,"journal":{"name":"Cleaner Chemical Engineering","volume":"11 ","pages":"Article 100172"},"PeriodicalIF":0.0000,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Thermal pyrolysis of wasted high-density plastic into valuable fuels using statistically derived kinetic rate constants\",\"authors\":\"Hammad Hussain , Sonia Arshed , Shahbaz Nasir Khan , Sameera Haq Nawaz , Muhammad Yasin Naz , Rao Adeel Un Nabi\",\"doi\":\"10.1016/j.clce.2025.100172\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Experimentally, empirical rate constants are used to extract liquid fuels and gases from the thermal decomposition of high-density plastics (HDPs). However, this approach is costly, time-consuming, and not commercially viable for producing a sustainable volume of liquid fuel. The prediction of rate constants is, therefore, imperative to boost the efficiency of the scaled destruction of plastic waste into fuels and other valuable products. We used the Box-Behnken technique in response surface methodology (RSM) to forecast temperature-dependent rate constants for thermal destruction of HDP. Most appropriate combinations of activation energies (Ea), exponential factors (Ao) and rate constants (k) were predicted statistically for better insight into HDP reaction mechanism for commercial scale production of oils and gases. The predicted parameters were used in a 2nd order ordinary differential solver to simulate the amount of oil and gases. The thermal treatment of HDP under optimized conditions resulted in 99 % oil production after 240 min of reaction. The formation of heavy wax was observed at the start of the reaction, and it changed to oil, light wax, and gases after 1 hour of processing. After 2 h, light wax production declined and oil production increased over time.</div></div>\",\"PeriodicalId\":100251,\"journal\":{\"name\":\"Cleaner Chemical Engineering\",\"volume\":\"11 \",\"pages\":\"Article 100172\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-04-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cleaner Chemical Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2772782325000270\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cleaner Chemical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772782325000270","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Thermal pyrolysis of wasted high-density plastic into valuable fuels using statistically derived kinetic rate constants
Experimentally, empirical rate constants are used to extract liquid fuels and gases from the thermal decomposition of high-density plastics (HDPs). However, this approach is costly, time-consuming, and not commercially viable for producing a sustainable volume of liquid fuel. The prediction of rate constants is, therefore, imperative to boost the efficiency of the scaled destruction of plastic waste into fuels and other valuable products. We used the Box-Behnken technique in response surface methodology (RSM) to forecast temperature-dependent rate constants for thermal destruction of HDP. Most appropriate combinations of activation energies (Ea), exponential factors (Ao) and rate constants (k) were predicted statistically for better insight into HDP reaction mechanism for commercial scale production of oils and gases. The predicted parameters were used in a 2nd order ordinary differential solver to simulate the amount of oil and gases. The thermal treatment of HDP under optimized conditions resulted in 99 % oil production after 240 min of reaction. The formation of heavy wax was observed at the start of the reaction, and it changed to oil, light wax, and gases after 1 hour of processing. After 2 h, light wax production declined and oil production increased over time.