首页|有机固废高值化为CO2吸附剂研究进展:交叉研究综述

有机固废高值化为CO2吸附剂研究进展:交叉研究综述

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碳捕集技术对于实现碳中和目标不可或缺。特别地,将有机固体废弃物高值化为多孔炭吸附剂并捕集CO2,被认为是一种能够同时缓解气候变化以及固废污染的可持续方法,因此其吸附剂的合成与应用得到广泛关注。近年来,除化工、材料、热工研究方法外,在该领域内许多学者应用分子模拟、机器学习、生命周期评价等研究方法,在固废高值化为CO2吸附剂方面进行了卓有特色的交叉研究。然而,上述交叉研究仍较为分散,缺乏脉络总结,其丰厚潜力还未得到系统阐明。本文综述了固废高值化为多孔炭吸附剂的研究进展,除常规工艺方法、制取吸附剂的性能水平外,侧重于展示该领域中应用的交叉研究,包含分子模拟、机器学习、生命周期评价三方面。本文通过脉络梳理可为该领域内交叉研究的潜在发展方向提供指引。
Research advances on upcycling organic solid waste into CO2 adsorbents:A cross-research review
Carbon capture technologies is indispensable to achieve carbon neutrality goals.In particular,upcycling organic solid waste into porous carbon materials for capturing CO2 is a sustainable and practical approach that simultaneously mitigates climate change and solid waste pollutions,and thus the syntheses and applications of its adsorbents have been extensively explored.In recent years,in addition to chemical engineering,material science and thermal engineering research methods,many scholars in this field have used molecular simulation,machine learning,life cycle assessment and other research methods to carry out distinctive cross-research on valorization of organic solid waste into CO2 adsorbents.However,the above-mentioned cross-cutting research is still relatively scattered,lacking a contextual summary,and its rich potential has not been systematically elucidated.This review addressed the research advances on upcycling organic solid waste into porous carbons for adsorbing CO2.In addition to the conventional process methods and the performance level of the adsorbents,it focused on the application of cross-research in this field,mainly including molecular simulation,machine learning and life cycle assessment.This review provided valuable guidelines for the potential development direction of cross-research in this field through contextual analyses.

carbon neutralporous carboncarbon capturemolecular simulationmachine learninglife cycle assessment

黄致新、王珺瑶、袁湘洲、邓帅、赵洁、张欣懿

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中低温热能高效利用教育部重点实验室,天津 300350

广东工业大学材料与能源学院,广东 广州 510006

东南大学能源与环境学院,能源热转换及其过程测控教育部重点实验室,江苏南京 210096

新加坡国立大学工程学院化学与生物分子工程系,新加坡肯特岗 119260

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碳中和 多孔炭 碳捕集 分子模拟 机器学习 生命周期评价

国家自然科学基金青年项目天津市自然科学基金重点项目

7210425722JCZDJC00540

2024

化工进展
中国化工学会,化学工业出版社

化工进展

CSTPCD北大核心
影响因子:1.062
ISSN:1000-6613
年,卷(期):2024.43(10)