{"title":"生物电化学系统的进展:电生菌和产甲烷菌的行为,压力适应,以及可持续生物能源的人工智能驱动方法","authors":"Monika Sharma , Indah Izza Muwakhidah , Nandini Thakur , Adel I. Alalawy , Saurabh Kulshrestha , Sedky H.A. Hassan , Maha Awjan Alreshidi , El-Sayed Salama","doi":"10.1016/j.rser.2025.116336","DOIUrl":null,"url":null,"abstract":"<div><div>Microbial fuel cells (MFCs) and microbial electrolysis cells integrated anaerobic digestion (MECs-AD) are the emerging technologies of bioelectrochemical systems (BES) that enhance bioenergy production from bio(mass)waste. This review has been dedicated to the understanding of technical and biological aspects of microbes (i.e., electrogens and methanogens) in MFCs and MECs-AD. A key focus lies in elucidating the bioelectrochemistry of BES, complex microbial behavior, and strategies for microbial inoculation (such as pure strains, mixed consortium, genetic engineering, and bioaugmentation) as mono-cultures and co-cultures. Approaches for methanogen suppression in MFCs and electrogens enhancement in MECs-AD systems are addressed systematically. The synergy between electroactive bacteria, methanogenic archaea, and nanowires in electrogens of BES is discussed. The application of <strong>stress</strong> (e.g., salinity, temperature fluctuations, pH extremes, hydraulic/shear stress, electromagnetic fields, and chemical inhibitors) to stabilize functional microbes is also explored. The implementation of mixed stresses on BES is recommended to be beneficial in stabilizing microbial communities. Highlights the artificial intelligence (AI) driven strain design and machine learning (ML) advancements in BES. Neural networks and random forest algorithms can predict gene knockouts/insertions to maximize electron transfer. Therefore, further research is needed to implement genetically modified strains using AI and ML algorithms. The review's findings underscore the need for continued study at the intersection of microbial ecology, materials science, and computational modeling to unlock the full potential of BES systems.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"226 ","pages":"Article 116336"},"PeriodicalIF":16.3000,"publicationDate":"2025-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Advancements in bioelectrochemical systems: Electrogens and methanogens behaviour, stress adaptation, and artificial intelligence-driven approaches for sustainable bioenergy\",\"authors\":\"Monika Sharma , Indah Izza Muwakhidah , Nandini Thakur , Adel I. Alalawy , Saurabh Kulshrestha , Sedky H.A. Hassan , Maha Awjan Alreshidi , El-Sayed Salama\",\"doi\":\"10.1016/j.rser.2025.116336\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Microbial fuel cells (MFCs) and microbial electrolysis cells integrated anaerobic digestion (MECs-AD) are the emerging technologies of bioelectrochemical systems (BES) that enhance bioenergy production from bio(mass)waste. This review has been dedicated to the understanding of technical and biological aspects of microbes (i.e., electrogens and methanogens) in MFCs and MECs-AD. A key focus lies in elucidating the bioelectrochemistry of BES, complex microbial behavior, and strategies for microbial inoculation (such as pure strains, mixed consortium, genetic engineering, and bioaugmentation) as mono-cultures and co-cultures. Approaches for methanogen suppression in MFCs and electrogens enhancement in MECs-AD systems are addressed systematically. The synergy between electroactive bacteria, methanogenic archaea, and nanowires in electrogens of BES is discussed. The application of <strong>stress</strong> (e.g., salinity, temperature fluctuations, pH extremes, hydraulic/shear stress, electromagnetic fields, and chemical inhibitors) to stabilize functional microbes is also explored. The implementation of mixed stresses on BES is recommended to be beneficial in stabilizing microbial communities. Highlights the artificial intelligence (AI) driven strain design and machine learning (ML) advancements in BES. Neural networks and random forest algorithms can predict gene knockouts/insertions to maximize electron transfer. Therefore, further research is needed to implement genetically modified strains using AI and ML algorithms. The review's findings underscore the need for continued study at the intersection of microbial ecology, materials science, and computational modeling to unlock the full potential of BES systems.</div></div>\",\"PeriodicalId\":418,\"journal\":{\"name\":\"Renewable and Sustainable Energy Reviews\",\"volume\":\"226 \",\"pages\":\"Article 116336\"},\"PeriodicalIF\":16.3000,\"publicationDate\":\"2025-09-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Renewable and Sustainable Energy Reviews\",\"FirstCategoryId\":\"1\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1364032125010093\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Renewable and Sustainable Energy Reviews","FirstCategoryId":"1","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1364032125010093","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
Advancements in bioelectrochemical systems: Electrogens and methanogens behaviour, stress adaptation, and artificial intelligence-driven approaches for sustainable bioenergy
Microbial fuel cells (MFCs) and microbial electrolysis cells integrated anaerobic digestion (MECs-AD) are the emerging technologies of bioelectrochemical systems (BES) that enhance bioenergy production from bio(mass)waste. This review has been dedicated to the understanding of technical and biological aspects of microbes (i.e., electrogens and methanogens) in MFCs and MECs-AD. A key focus lies in elucidating the bioelectrochemistry of BES, complex microbial behavior, and strategies for microbial inoculation (such as pure strains, mixed consortium, genetic engineering, and bioaugmentation) as mono-cultures and co-cultures. Approaches for methanogen suppression in MFCs and electrogens enhancement in MECs-AD systems are addressed systematically. The synergy between electroactive bacteria, methanogenic archaea, and nanowires in electrogens of BES is discussed. The application of stress (e.g., salinity, temperature fluctuations, pH extremes, hydraulic/shear stress, electromagnetic fields, and chemical inhibitors) to stabilize functional microbes is also explored. The implementation of mixed stresses on BES is recommended to be beneficial in stabilizing microbial communities. Highlights the artificial intelligence (AI) driven strain design and machine learning (ML) advancements in BES. Neural networks and random forest algorithms can predict gene knockouts/insertions to maximize electron transfer. Therefore, further research is needed to implement genetically modified strains using AI and ML algorithms. The review's findings underscore the need for continued study at the intersection of microbial ecology, materials science, and computational modeling to unlock the full potential of BES systems.
期刊介绍:
The mission of Renewable and Sustainable Energy Reviews is to disseminate the most compelling and pertinent critical insights in renewable and sustainable energy, fostering collaboration among the research community, private sector, and policy and decision makers. The journal aims to exchange challenges, solutions, innovative concepts, and technologies, contributing to sustainable development, the transition to a low-carbon future, and the attainment of emissions targets outlined by the United Nations Framework Convention on Climate Change.
Renewable and Sustainable Energy Reviews publishes a diverse range of content, including review papers, original research, case studies, and analyses of new technologies, all featuring a substantial review component such as critique, comparison, or analysis. Introducing a distinctive paper type, Expert Insights, the journal presents commissioned mini-reviews authored by field leaders, addressing topics of significant interest. Case studies undergo consideration only if they showcase the work's applicability to other regions or contribute valuable insights to the broader field of renewable and sustainable energy. Notably, a bibliographic or literature review lacking critical analysis is deemed unsuitable for publication.