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For: Chung TH, Shahidi M, Mezbahuddin S, Dhar BR. Ensemble machine learning approach for examining critical process parameters and scale-up opportunities of microbial electrochemical systems for hydrogen peroxide production. Chemosphere 2023;324:138313. [PMID: 36878371 DOI: 10.1016/j.chemosphere.2023.138313] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 02/23/2023] [Accepted: 03/03/2023] [Indexed: 06/18/2023]
Number Cited by Other Article(s)
1
Li C, Xie Y, Wang J, Guo C, Han L, Xia Z, Zhang Z, Wang J, Li M, Han W, Huang L, Yan J, Zhang H. Advances in sulfate-reducing bacteria-driven bioelectrolysis: mechanisms and applications in microbial electrolysis cell technology. ENVIRONMENTAL RESEARCH 2025;279:121857. [PMID: 40379000 DOI: 10.1016/j.envres.2025.121857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2025] [Revised: 04/29/2025] [Accepted: 05/13/2025] [Indexed: 05/19/2025]
2
Jin J, Wu Y, Cao P, Zheng X, Zhang Q, Chen Y. Potential and challenge in accelerating high-value conversion of CO2 in microbial electrosynthesis system via data-driven approach. BIORESOURCE TECHNOLOGY 2024;412:131380. [PMID: 39214179 DOI: 10.1016/j.biortech.2024.131380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/17/2024] [Revised: 08/26/2024] [Accepted: 08/27/2024] [Indexed: 09/04/2024]
3
Deng Z, Choi SJ, Li G, Wang X. Advancing H2O2 electrosynthesis: enhancing electrochemical systems, unveiling emerging applications, and seizing opportunities. Chem Soc Rev 2024;53:8137-8181. [PMID: 39021095 DOI: 10.1039/d4cs00412d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/20/2024]
4
Sun J, Xu Y, Yang H, Liu J, He Z. Machine learning facilitated the conceptual design of an alum dosing system for phosphorus removal in a wastewater treatment plant. CHEMOSPHERE 2024;351:141154. [PMID: 38211785 DOI: 10.1016/j.chemosphere.2024.141154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 12/19/2023] [Accepted: 01/06/2024] [Indexed: 01/13/2024]
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