{"title":"基于机器学习的塑料衍生多孔碳用于高性能二氧化碳捕获","authors":"Shuangjun Li, Yan Xie, Shuai Deng, Xiangzhou Yuan","doi":"10.1021/accountsmr.5c00185","DOIUrl":null,"url":null,"abstract":"Plastic pollution and climate change are interconnected global environmental challenges. Conventional methods (incineration and landfills) exacerbate these issues by emitting greenhouse gases and releasing micro/nanoplastics. To simultaneously address these two critical environmental issues, we upcycle plastic waste into porous carbon materials, enabling high-performance postcombustion CO<sub>2</sub> capture in a transformative and practical manner. This strategy tackles environmental pollution, aligns with circular economy principles, and supports several of UN Sustainable Development Goals (SDGs). We conduct systematic studies, including experimental validations, numerical simulations, and machine learning (ML)-empowered optimizations, to provide detailed guidelines for upcycling plastic waste into porous carbons with high-performance CO<sub>2</sub> capture.","PeriodicalId":72040,"journal":{"name":"Accounts of materials research","volume":"1 1","pages":""},"PeriodicalIF":14.7000,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Machine Learning-Empowered Plastic-Derived Porous Carbons for High-Performance CO2 Capture\",\"authors\":\"Shuangjun Li, Yan Xie, Shuai Deng, Xiangzhou Yuan\",\"doi\":\"10.1021/accountsmr.5c00185\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Plastic pollution and climate change are interconnected global environmental challenges. Conventional methods (incineration and landfills) exacerbate these issues by emitting greenhouse gases and releasing micro/nanoplastics. To simultaneously address these two critical environmental issues, we upcycle plastic waste into porous carbon materials, enabling high-performance postcombustion CO<sub>2</sub> capture in a transformative and practical manner. This strategy tackles environmental pollution, aligns with circular economy principles, and supports several of UN Sustainable Development Goals (SDGs). We conduct systematic studies, including experimental validations, numerical simulations, and machine learning (ML)-empowered optimizations, to provide detailed guidelines for upcycling plastic waste into porous carbons with high-performance CO<sub>2</sub> capture.\",\"PeriodicalId\":72040,\"journal\":{\"name\":\"Accounts of materials research\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":14.7000,\"publicationDate\":\"2025-09-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Accounts of materials research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1021/accountsmr.5c00185\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accounts of materials research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1021/accountsmr.5c00185","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
Machine Learning-Empowered Plastic-Derived Porous Carbons for High-Performance CO2 Capture
Plastic pollution and climate change are interconnected global environmental challenges. Conventional methods (incineration and landfills) exacerbate these issues by emitting greenhouse gases and releasing micro/nanoplastics. To simultaneously address these two critical environmental issues, we upcycle plastic waste into porous carbon materials, enabling high-performance postcombustion CO2 capture in a transformative and practical manner. This strategy tackles environmental pollution, aligns with circular economy principles, and supports several of UN Sustainable Development Goals (SDGs). We conduct systematic studies, including experimental validations, numerical simulations, and machine learning (ML)-empowered optimizations, to provide detailed guidelines for upcycling plastic waste into porous carbons with high-performance CO2 capture.