{"title":"基于官能团的方法(包含催化剂特性)为多种碳氢化合物混合物的催化热解建模","authors":"Dongyang Liu, Haiping He, Duo Li, Liang Zhao, Jinsen Gao, Chunming Xu","doi":"10.1016/j.fuel.2024.133531","DOIUrl":null,"url":null,"abstract":"<div><div>The intricate composition of naphtha poses a significant challenge in formulating a comprehensive modeling approach for the production of light olefins. In this study, the intricate composition of the feedstock was described based on the weight percentage of the functional groups. At the same time, the distribution variations of the pyrolysis products were characterized using their stoichiometric coefficients (SCs). Consequently, a functional group-based approach was proposed to model the catalytic pyrolysis of multiple hydrocarbon mixtures over ZSM-5 based catalysts by establishing a quantitative correlation between the composition of the functional groups and the SCs of the pyrolysis products. Furthermore, a comprehensive functional group-based approach was developed to integrate catalyst properties by relating their acidity to the SCs of pyrolysis products. This modeling approach allows for precise forecasting of product compositions across a range of feedstocks and catalyst systems, with a maximum error of 1.15 wt%. In addition, this modeling method can also be used to optimize feedstock blends and tailor acid properties to maximize light olefin production, highlighting its potential for use in various hydrocarbon mixtures.</div></div>","PeriodicalId":325,"journal":{"name":"Fuel","volume":"381 ","pages":"Article 133531"},"PeriodicalIF":6.7000,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A functional group-based approach containing catalyst properties to modeling catalytic pyrolysis of multiple hydrocarbon mixtures\",\"authors\":\"Dongyang Liu, Haiping He, Duo Li, Liang Zhao, Jinsen Gao, Chunming Xu\",\"doi\":\"10.1016/j.fuel.2024.133531\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The intricate composition of naphtha poses a significant challenge in formulating a comprehensive modeling approach for the production of light olefins. In this study, the intricate composition of the feedstock was described based on the weight percentage of the functional groups. At the same time, the distribution variations of the pyrolysis products were characterized using their stoichiometric coefficients (SCs). Consequently, a functional group-based approach was proposed to model the catalytic pyrolysis of multiple hydrocarbon mixtures over ZSM-5 based catalysts by establishing a quantitative correlation between the composition of the functional groups and the SCs of the pyrolysis products. Furthermore, a comprehensive functional group-based approach was developed to integrate catalyst properties by relating their acidity to the SCs of pyrolysis products. This modeling approach allows for precise forecasting of product compositions across a range of feedstocks and catalyst systems, with a maximum error of 1.15 wt%. In addition, this modeling method can also be used to optimize feedstock blends and tailor acid properties to maximize light olefin production, highlighting its potential for use in various hydrocarbon mixtures.</div></div>\",\"PeriodicalId\":325,\"journal\":{\"name\":\"Fuel\",\"volume\":\"381 \",\"pages\":\"Article 133531\"},\"PeriodicalIF\":6.7000,\"publicationDate\":\"2024-11-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Fuel\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0016236124026802\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fuel","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0016236124026802","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
A functional group-based approach containing catalyst properties to modeling catalytic pyrolysis of multiple hydrocarbon mixtures
The intricate composition of naphtha poses a significant challenge in formulating a comprehensive modeling approach for the production of light olefins. In this study, the intricate composition of the feedstock was described based on the weight percentage of the functional groups. At the same time, the distribution variations of the pyrolysis products were characterized using their stoichiometric coefficients (SCs). Consequently, a functional group-based approach was proposed to model the catalytic pyrolysis of multiple hydrocarbon mixtures over ZSM-5 based catalysts by establishing a quantitative correlation between the composition of the functional groups and the SCs of the pyrolysis products. Furthermore, a comprehensive functional group-based approach was developed to integrate catalyst properties by relating their acidity to the SCs of pyrolysis products. This modeling approach allows for precise forecasting of product compositions across a range of feedstocks and catalyst systems, with a maximum error of 1.15 wt%. In addition, this modeling method can also be used to optimize feedstock blends and tailor acid properties to maximize light olefin production, highlighting its potential for use in various hydrocarbon mixtures.
期刊介绍:
The exploration of energy sources remains a critical matter of study. For the past nine decades, fuel has consistently held the forefront in primary research efforts within the field of energy science. This area of investigation encompasses a wide range of subjects, with a particular emphasis on emerging concerns like environmental factors and pollution.