生态与农村环境学报2025，Vol.41Issue(9)：1134-1142,9.DOI:10.19741/j.issn.1673-4831.2025.0340
人工智能赋能工业固废基吸附剂开发的研究进展与前景展望
Research Progress and Prospects of AI-enabled Development of Adsorbents Derived from Industrial Solid Waste
摘要
Abstract
Artificial intelligence(AI)technologies are becoming vital tools in promoting the resource utilization of indus-trial solid waste(ISW)and the intelligent development of waste-derived adsorbents.As the preparation of ISW-based ad-sorbents is increasingly regarded as a promising utilization pathway,it still faces major obstacles such as the complexity and variability of raw materials,the lack of rule-based guidance in process design,and a heavy reliance on trial-and-error parameter optimization.In this context,AI demonstrates significant potential in key stages of adsorbent development,in-cluding experimental data extraction and structuring,synthesis pathway design using algorithmic optimization,property-performance relationship modeling through machine learning,and high-throughput virtual screening enabled by intelligent surrogate models.This review summarizes the progress of AI applications in representative porous materials such as metal-organic frameworks,zeolites and biochar,with emphasis on how different AI models,such as artificial neural networks,decision trees and support vector machines,have been employed to guide synthesis conditions,predict adsorption capacity and identify key descriptors.In addition,practical explorations of AI-enabled ISW-derived adsorbent development are re-viewed.Finally,key challenges such as fragmented data,limited model interpretability and complex pollutant-material in-teractions,are discussed.Future research is suggested to focus on building standardized and shareable data infrastruc-tures,incorporating multiscale simulations that couple quantum-level and process-level insights,enhancing model inter-pretability via explainable AI techniques and fostering interdisciplinary collaboration to advance the intelligent development of ISW-based adsorbents.关键词
人工智能/工业固体废物/吸附剂/机器学习/资源化利用Key words
artificial intelligence/industrial solid waste/adsorbents/machine learning/resource utilization分类
资源环境引用本文复制引用
杨子溢,卜元卿,张后虎..人工智能赋能工业固废基吸附剂开发的研究进展与前景展望[J].生态与农村环境学报,2025,41(9):1134-1142,9.基金项目
国家重点研发计划(2023YFC3706603) （2023YFC3706603）
生态环境部预算项目 （）
国家重点研发计划(2022YFC2105405) （2022YFC2105405）
