Mass transfer in heterogeneous biofilms: Key issues in biofilm reactors and AI-driven performance prediction  

作　　者：Huize Chen Ao Xia Huchao Yan Yun Huang Xianqing Zhu Xun Zhu Qiang Liao 

机构地区：[1]Key Laboratory of Low-grade Energy Utilization Technologies and Systems,Chongqing University,Ministry of Education,Chongqing,400044,China [2]Institute of Engineering Thermophysics,School of Energy and Power Engineering,Chongqing University,Chongqing,400044,China

出　　处：《Environmental Science and Ecotechnology》2024年第6期109-123,共15页环境科学与生态技术（英文）

基　　金：National Natural Science Foundation of China(Nos.52022015,52021004);Natural Science Foundation of Chongqing(Nos.CSTB2023NSCQ-JQX0005,cstc2021ycjh-bgzxm0160);Fundamental Research Funds for the Central Universities(No.2022ZFJH04).

摘　　要：Biofilm reactors,known for utilizing biofilm formation for cell immobilization,offer enhanced biomass concentration and operational stability over traditional planktonic systems.However,the dense nature of biofilms poses challenges for substrate accessibility to cells and the efficient release of products,making mass transfer efficiency a critical issue in these systems.Recent advancements have unveiled the intricate,heterogeneous architecture of biofilms,contradicting the earlier view of them as uniform,porous structures with consistent mass transfer properties.In this review,we explore six biofilm reactor configurations and their potential combinations,emphasizing how the spatial arrangement of biofilms within reactors influences mass transfer efficiency and overall reactor performance.Furthermore,we discuss how to apply artificial intelligence in processing biofilm measurement data and predicting reactor performance.This review highlights the role of biofilm reactors in environmental and energy sectors,paving the way for future innovations in biofilm-based technologies and their broader applications.

关 键 词：BIOFILM REACTOR Heterogeneous structure Mass transfer Artificial intelligence 

分 类 号：X703[环境科学与工程—环境工程]