化工矿物与加工2025，Vol.54Issue(11)：1-11,11.DOI:10.16283/j.cnki.hgkwyjg.2025.11.001
人工智能赋能新一代生物炭设计助力矿山生态修复
Artificial intelligence empowers design of new generation biochar for mine ecological restoration
摘要
Abstract
The mine ecosystem is affected by both mining disturbance and pollution accumulation,and there are widespread problems such as poor soil,structural degradation,serious pollution and lack of biodiversity,which has become a key area for the construction of"beautiful China".Biochar has large specific surface area,developed pore structure and excellent adsorption capacity,and has significant advantages in pollutant fixation,soil improvement and carbon sequestration.However,biochar still has limitations such as uncontrollable performance,poor raw material suitability,and single function,and it is difficult to cope with complex mine ecological restoration needs.This paper systematically reviewed the main challenges faced by mine ecological restoration in China,and explained the advanta-ges and limitations of biochar application in mine ecological restoration.Based on machine learning,digital twin and material genetic engineering technology,the intelligent prediction and optimization of raw material selection,pyrolysis path and functional performance were realized,and a new generation of biochar with pollution adsorption,nutrient release and stability functions was designed.In the future,smart algorithms coupled with multi-scale experimental validation,big-data restoration models and a standardized carbon-sink monitoring system will be used to propel the biochar design from"empirical manufacture"to"intelligent manufacture",providing novel technologies for the precise remediation and green reconstruction of mining ecosystems.关键词
人工智能/生物炭/生态修复/机器学习/基因工程/数字孪生/物联网Key words
artificial intelligence/biochar/ecological restoration/machine learning/genetic engineering/digital twin/internet of things分类
矿业与冶金引用本文复制引用
陈浮,骆占斌,朱朝冉,段雪颖,杨永均,马静..人工智能赋能新一代生物炭设计助力矿山生态修复[J].化工矿物与加工,2025,54(11):1-11,11.基金项目
国家自然科学基金项目(52374170,52474197). （52374170,52474197）
