Abdul Hai , Wan Mohd Ashri Wan Daud , Muhamad Fazly Abdul Patah , G. Bharath , Hamad AlMohamadi , Doris Ying Ying Tang , Pau Loke Show , Fawzi Banat
{"title":"对农业生物质活性炭生产的全面洞察:参数分析,挑战,未来建议和机器学习建模","authors":"Abdul Hai , Wan Mohd Ashri Wan Daud , Muhamad Fazly Abdul Patah , G. Bharath , Hamad AlMohamadi , Doris Ying Ying Tang , Pau Loke Show , Fawzi Banat","doi":"10.1016/j.rcradv.2025.200284","DOIUrl":null,"url":null,"abstract":"<div><div>The increasing accumulation of bio-waste poses significant environmental challenges worldwide. Sustainable and effective resource management is essential to restore ecosystems. Activated carbon produced from agricultural biomass through pyrolysis offers a sustainable solution to these issues. Therefore, this study provides detailed insights into the synthesis of activated carbon, highlighting critical parameters affecting the quality by extracting data from 240 published articles. The parametric analysis evaluates variables such as pyrolysis temperature, activation agent, and biomass type that impact the yield and specific surface area (SSA) of the synthesized activated carbon. Key findings reveal that optimizing pyrolysis conditions can enhance both yield and SSA. Furthermore, the paper presents the development of 03 different machine-learning regression models for predicting the performance of engineered biochar production by physical and chemical activation processes. This approach offers a dual benefit of waste reduction and resource efficiency by transforming agricultural waste into high-quality activated carbon. The study lays a foundation for further exploration of innovative applications, data science and advanced production techniques, aiming to make activated biochar production more environmentally friendly and economically viable.</div></div>","PeriodicalId":74689,"journal":{"name":"Resources, conservation & recycling advances","volume":"27 ","pages":"Article 200284"},"PeriodicalIF":6.4000,"publicationDate":"2025-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A comprehensive insight on activated carbon production from agricultural biomass: Parametric analysis, challenges, future recommendations & machine learning modelling\",\"authors\":\"Abdul Hai , Wan Mohd Ashri Wan Daud , Muhamad Fazly Abdul Patah , G. Bharath , Hamad AlMohamadi , Doris Ying Ying Tang , Pau Loke Show , Fawzi Banat\",\"doi\":\"10.1016/j.rcradv.2025.200284\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The increasing accumulation of bio-waste poses significant environmental challenges worldwide. Sustainable and effective resource management is essential to restore ecosystems. Activated carbon produced from agricultural biomass through pyrolysis offers a sustainable solution to these issues. Therefore, this study provides detailed insights into the synthesis of activated carbon, highlighting critical parameters affecting the quality by extracting data from 240 published articles. The parametric analysis evaluates variables such as pyrolysis temperature, activation agent, and biomass type that impact the yield and specific surface area (SSA) of the synthesized activated carbon. Key findings reveal that optimizing pyrolysis conditions can enhance both yield and SSA. Furthermore, the paper presents the development of 03 different machine-learning regression models for predicting the performance of engineered biochar production by physical and chemical activation processes. This approach offers a dual benefit of waste reduction and resource efficiency by transforming agricultural waste into high-quality activated carbon. The study lays a foundation for further exploration of innovative applications, data science and advanced production techniques, aiming to make activated biochar production more environmentally friendly and economically viable.</div></div>\",\"PeriodicalId\":74689,\"journal\":{\"name\":\"Resources, conservation & recycling advances\",\"volume\":\"27 \",\"pages\":\"Article 200284\"},\"PeriodicalIF\":6.4000,\"publicationDate\":\"2025-08-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Resources, conservation & recycling advances\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2667378925000410\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Resources, conservation & recycling advances","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2667378925000410","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
A comprehensive insight on activated carbon production from agricultural biomass: Parametric analysis, challenges, future recommendations & machine learning modelling
The increasing accumulation of bio-waste poses significant environmental challenges worldwide. Sustainable and effective resource management is essential to restore ecosystems. Activated carbon produced from agricultural biomass through pyrolysis offers a sustainable solution to these issues. Therefore, this study provides detailed insights into the synthesis of activated carbon, highlighting critical parameters affecting the quality by extracting data from 240 published articles. The parametric analysis evaluates variables such as pyrolysis temperature, activation agent, and biomass type that impact the yield and specific surface area (SSA) of the synthesized activated carbon. Key findings reveal that optimizing pyrolysis conditions can enhance both yield and SSA. Furthermore, the paper presents the development of 03 different machine-learning regression models for predicting the performance of engineered biochar production by physical and chemical activation processes. This approach offers a dual benefit of waste reduction and resource efficiency by transforming agricultural waste into high-quality activated carbon. The study lays a foundation for further exploration of innovative applications, data science and advanced production techniques, aiming to make activated biochar production more environmentally friendly and economically viable.