Predicting Microbial Fuel Cell Biofilm Communities and Bioreactor Performance using Artificial Neural Networks by Lesnik, Keaton Larson, Liu, Hong

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Establishing a core microbiome in acetate-fed microbial fuel cells by Lesnik, Keaton Larson, Liu, Hong

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Stay connected: Electrical conductivity of microbial aggregates by Li, Cheng, Lesnik, Keaton Larson, Liu, Hong

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Redox Conductivity of Current-Producing Mixed Species Biofilms by Li, Cheng, Lesnik, Keaton Larson, Fan, Yanzhen, Liu, Hong

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Millimeter scale electron conduction through exoelectrogenic mixed species biofilms by Li, Cheng, Lesnik, Keaton Larson, Fan, Yanzhen, Liu, Hong

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Impact of tobramycin on the performance of microbial fuel cell by Wu, Wenguo, Lesnik, Keaton Larson, Xu, Shoutao, Wang, Luguang, Liu, Hong

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Microbial Community Predicts Functional Stability of Microbial Fuel Cells by Lesnik, Keaton Larson, Cai, Wenfang, Liu, Hong

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Suppression of methanogenesis for hydrogen production in single-chamber microbial electrolysis cells using various antibiotics by Catal, Tunc, Lesnik, Keaton Larson, Liu, Hong

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Performance prediction of ZVI-based anaerobic digestion reactor using machine learning algorithms by Xu, Weichao, Long, Fei, Zhao, He, Zhang, Yaobin, Liang, Dawei, Wang, Luguang, Lesnik, Keaton Larson, Cao, Hongbin, Zhang, Yuxiu, Liu, Hong

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Incorporating microbial community data with machine learning techniques to predict feed substrates in microbial fuel cells by Cai, Wenfang, Lesnik, Keaton Larson, Wade, Matthew J., Heidrich, Elizabeth S., Wang, Yunhai, Liu, Hong

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Conductive properties of methanogenic biofilms by Li, Cheng, Lesnik, Keaton Larson, Liu, Hong

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Enhanced power generation and energy conversion of sewage sludge by CEA–microbial fuel cells by Abourached, Carole, Lesnik, Keaton Larson, Liu, Hong

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