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Huang J, Gao Y, Chang Y, Peng J, Yu Y, Wang B. Machine Learning in Bioelectrocatalysis. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2306583. [PMID: 37946709 PMCID: PMC10787072 DOI: 10.1002/advs.202306583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Indexed: 11/12/2023]
Abstract
At present, the global energy crisis and environmental pollution coexist, and the demand for sustainable clean energy has been highly concerned. Bioelectrocatalysis that combines the benefits of biocatalysis and electrocatalysis produces high-value chemicals, clean biofuel, and biodegradable new materials. It has been applied in biosensors, biofuel cells, and bioelectrosynthesis. However, there are certain flaws in the application process of bioelectrocatalysis, such as low accuracy/efficiency, poor stability, and limited experimental conditions. These issues can possibly be solved using machine learning (ML) in recent reports although the combination of them is still not mature. To summarize the progress of ML in bioelectrocatalysis, this paper first introduces the modeling process of ML, then focuses on the reports of ML in bioelectrocatalysis, and ultimately makes a summary and outlook about current issues and future directions. It is believed that there is plenty of scope for this interdisciplinary research direction.
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Affiliation(s)
- Jiamin Huang
- Department of Environmental Science and EngineeringUniversity of Science and Technology BeijingBeijing100083China
- CAS Key Laboratory of Nanosystem and Hierarchical FabricationNational Center for Nanoscience and TechnologyBeijing100190China
| | - Yang Gao
- CAS Key Laboratory of Nanosystem and Hierarchical FabricationNational Center for Nanoscience and TechnologyBeijing100190China
| | - Yanhong Chang
- Department of Environmental Science and EngineeringUniversity of Science and Technology BeijingBeijing100083China
| | - Jiajie Peng
- School of Computer ScienceNorthwestern Polytechnical UniversityXi'an710072China
| | - Yadong Yu
- College of Biotechnology and Pharmaceutical EngineeringNanjing Tech UniversityNanjing211816China
| | - Bin Wang
- CAS Key Laboratory of Nanosystem and Hierarchical FabricationNational Center for Nanoscience and TechnologyBeijing100190China
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Ma F, Ouyang T, Cheng Y, Zhu B, Ji P. Non-fragile guaranteed cost control of microbial fuel cells. ISA TRANSACTIONS 2023; 143:398-408. [PMID: 37690942 DOI: 10.1016/j.isatra.2023.08.032] [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: 03/17/2022] [Revised: 08/01/2023] [Accepted: 08/25/2023] [Indexed: 09/12/2023]
Abstract
A microbial fuel cell (MFC), which is a new type of energy source, utilises electrogenic bacteria in sewage or soil to convert chemical energy into electrical energy. MFCs typically require an external controller to provide a stable output voltage to the external load. This study develops a non-fragile guaranteed cost (NFGC) controller to suppress the interference of the controller of an MFC and ensure that the quadratic cost function of the system satisfies certain performance indexes. First, for the convenience of controller design, a Takagi-Sugeno fuzzy model is established to approximate a single-chamber single-population MFC model. Subsequently, the linear matrix inequality method is used to design the NFGC controller. This control scheme can reduce the influence of controller disturbances on the system and ensure asymptotic stability of the closed-loop system under the specified upper bound of the provided cost function. The simulation results demonstrate that the developed control method has a shorter adjustment time and smaller steady-state error than traditional control methods such as sliding mode control (SMC), backstepping control, and fuzzy SMC.
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Affiliation(s)
- Fengying Ma
- School of Information and Automation Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China
| | - Tianyu Ouyang
- School of Information and Automation Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China
| | - Yuyin Cheng
- Technical Services Department, Yunnan Phosphate Haikou Co., Ltd, Kunming, 650100, Yunnan, China
| | - Baolong Zhu
- School of Information and Automation Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China.
| | - Peng Ji
- School of Information and Automation Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China
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Leveraging artificial intelligence in bioelectrochemical systems. Trends Biotechnol 2021; 40:535-538. [PMID: 34893375 DOI: 10.1016/j.tibtech.2021.11.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2021] [Revised: 11/12/2021] [Accepted: 11/15/2021] [Indexed: 11/23/2022]
Abstract
Bioelectrochemical systems (BESs) are highly evolved and sophisticated systems that produce bioenergy via exoelectrogenic microbes. Artificial intelligence (AI) helps to understand, relate, model, and predict both process parameters and microbial diversity, resulting in higher performance. This approach has revolutionized BESs through highly advanced computational algorithms that best suit the systems' architecture.
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Hyun Chung T, Ranjan Dhar B. A multi-perspective review on microbial electrochemical technologies for food waste valorization. BIORESOURCE TECHNOLOGY 2021; 342:125950. [PMID: 34852436 DOI: 10.1016/j.biortech.2021.125950] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 09/08/2021] [Accepted: 09/12/2021] [Indexed: 06/13/2023]
Abstract
The worldwide generation of food waste (FW) has been increasing enormously due to the growing food industry and population. However, FW contains a large amount of biodegradable organics that can be converted to clean energy, which can potentially minimize the utilization of fossil fuels. Conventional biowaste valorization technologies, such as anaerobic digestion and composting, have been adopted for FW management for recovering useful biogas and compost. However, they are often limited by high capital and operation costs, low recovery efficiency, slow process kinetics, and system instability. On the other hand, microbial electrochemical technologies (METs) have been highly promising for efficiently harvesting bioenergy and high value-added products from FW. Hence, this article critically reviews up-to-date studies on applying various METs regarding their value-added products recovery efficiencies from FW. Moreover, this review lists existing challenges, ways to optimize the system performance and provides perspectives on future research needs.
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Affiliation(s)
- Tae Hyun Chung
- Department of Civil and Environmental Engineering, University of Alberta, 9211-116 Street NW, Edmonton, AB T6G 1H9, Canada
| | - Bipro Ranjan Dhar
- Department of Civil and Environmental Engineering, University of Alberta, 9211-116 Street NW, Edmonton, AB T6G 1H9, Canada.
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Chung TH, Dhar BR. Paper-based platforms for microbial electrochemical cell-based biosensors: A review. Biosens Bioelectron 2021; 192:113485. [PMID: 34274625 DOI: 10.1016/j.bios.2021.113485] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Revised: 06/30/2021] [Accepted: 07/02/2021] [Indexed: 12/13/2022]
Abstract
The development of low-cost analytical devices for on-site water quality monitoring is a critical need, especially for developing countries and remote communities in developed countries with limited resources. Microbial electrochemical cell-based (MXC) biosensors have been quite promising for quantitative and semi-quantitative (often qualitative) measurements of various water quality parameters due to their low cost and simplicity compared to traditional analytical methods. However, conventional MXC biosensors often encounter challenges, such as the slow establishment of biofilms, low sensitivity, and poor recoverability, making them unable to be applied for practical cases. In response, MXC biosensors assembled with paper-based materials demonstrated tremendous potentials to enhance sensitivity and field applicability. Furthermore, the paper-based platforms offer many prominent features, including autonomous liquid transport, rapid bacterial adhesion, lowered resistance, low fabrication cost (<$1 in USD), and eco-friendliness. Therefore, this review aims to summarize the current trend and applications of paper-based MXC biosensors, along with critical discussions on their field applicability. Moreover, future advancements of paper-based MXC biosensors, such as developing a novel paper-based biobatteries, increasing the system performance using an unique biocatalyst, such as yeast, and integrating the biosensor system with other advanced tools, such as machine learning and 3D printing, are highlighted.
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Affiliation(s)
- Tae Hyun Chung
- Department of Civil and Environmental Engineering, University of Alberta, 9211-116 Street NW, Edmonton, AB, T6G 1H9, Canada
| | - Bipro Ranjan Dhar
- Department of Civil and Environmental Engineering, University of Alberta, 9211-116 Street NW, Edmonton, AB, T6G 1H9, Canada.
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Aguzzi J, Costa C, Calisti M, Funari V, Stefanni S, Danovaro R, Gomes HI, Vecchi F, Dartnell LR, Weiss P, Nowak K, Chatzievangelou D, Marini S. Research Trends and Future Perspectives in Marine Biomimicking Robotics. SENSORS (BASEL, SWITZERLAND) 2021; 21:3778. [PMID: 34072452 PMCID: PMC8198061 DOI: 10.3390/s21113778] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Revised: 05/17/2021] [Accepted: 05/27/2021] [Indexed: 12/16/2022]
Abstract
Mechatronic and soft robotics are taking inspiration from the animal kingdom to create new high-performance robots. Here, we focused on marine biomimetic research and used innovative bibliographic statistics tools, to highlight established and emerging knowledge domains. A total of 6980 scientific publications retrieved from the Scopus database (1950-2020), evidencing a sharp research increase in 2003-2004. Clustering analysis of countries collaborations showed two major Asian-North America and European clusters. Three significant areas appeared: (i) energy provision, whose advancement mainly relies on microbial fuel cells, (ii) biomaterials for not yet fully operational soft-robotic solutions; and finally (iii), design and control, chiefly oriented to locomotor designs. In this scenario, marine biomimicking robotics still lacks solutions for the long-lasting energy provision, which presently hinders operation autonomy. In the research environment, identifying natural processes by which living organisms obtain energy is thus urgent to sustain energy-demanding tasks while, at the same time, the natural designs must increasingly inform to optimize energy consumption.
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Affiliation(s)
- Jacopo Aguzzi
- Department of Renewable Marine Resources, Instituto de Ciencias del Mar (ICM-CSIC), 08003 Barcelona, Spain
- Stazione Zoologica Anton Dohrn (SZN), 80122 Naples, Italy; (V.F.); (S.S.); (R.D.); (F.V.)
| | - Corrado Costa
- Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria (CREA), 00015 Rome, Italy
| | - Marcello Calisti
- The BioRobotics Institute, Scuola Superiore Sant’Anna (SSAA), 56127 Pisa, Italy;
- Lincoln Institute for Agri-food Technology (LIAT), University of Lincoln, Lincoln LN6 7TS, UK
| | - Valerio Funari
- Stazione Zoologica Anton Dohrn (SZN), 80122 Naples, Italy; (V.F.); (S.S.); (R.D.); (F.V.)
- Consiglio Nazionale delle Ricerche (CNR), Istituto di Scienze Marine (ISMAR), 40129 Bologna, Italy
| | - Sergio Stefanni
- Stazione Zoologica Anton Dohrn (SZN), 80122 Naples, Italy; (V.F.); (S.S.); (R.D.); (F.V.)
| | - Roberto Danovaro
- Stazione Zoologica Anton Dohrn (SZN), 80122 Naples, Italy; (V.F.); (S.S.); (R.D.); (F.V.)
- Department of Life and Environmental Science, Università Politecnica delle Marche, 60121 Ancona, Italy
| | - Helena I. Gomes
- Faculty of Engineering, University of Nottingham, Nottingham NG7 2RD, UK;
| | - Fabrizio Vecchi
- Stazione Zoologica Anton Dohrn (SZN), 80122 Naples, Italy; (V.F.); (S.S.); (R.D.); (F.V.)
| | - Lewis R. Dartnell
- School of Life Sciences, University of Westminster, London W1W 6UW, UK;
| | | | - Kathrin Nowak
- Compagnie Maritime d’Expertises (COMEX), 13275 Marseille, France;
| | | | - Simone Marini
- Consiglio Nazionale delle Ricerche (CNR), Istituto di Scienze Marine (ISMAR), 19032 La Spezia, Italy;
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Jadhav DA, Carmona-Martínez AA, Chendake AD, Pandit S, Pant D. Modeling and optimization strategies towards performance enhancement of microbial fuel cells. BIORESOURCE TECHNOLOGY 2021; 320:124256. [PMID: 33120058 DOI: 10.1016/j.biortech.2020.124256] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 10/07/2020] [Accepted: 10/09/2020] [Indexed: 06/11/2023]
Abstract
Considering the complexity associated with bioelectrochemical processes, the performance of a microbial fuel cell (MFC) is governed by input operating parameters. For scaled-up applications, a MFC system needs to be modeled from engineering perspectives in terms of optimum operating conditions to get higher performance and energy recovery. Several conceptual numerical models to advanced computational simulation approaches have been developed to represent simple-form of a complex MFC system. Application of mathematical and computation models are explored to establish the relationship between operating input-variables and power output. The present review discusses about the complexity of system, modeling strategies used and reality of such modeling for scaling-up applications of MFCs. Additionally, the selection of an appropriate mathematical model reduces the computational duration and provides better understanding of the system process. It also explores the possibility and progress towards commercialization of MFCs and thus the need of development of model-based optimization and process-control approaches.
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Affiliation(s)
- Dipak A Jadhav
- Department of Agricultural Engineering, Maharashtra Institute of Technology, Aurangabad, Maharashtra 431010, India.
| | - Alessandro A Carmona-Martínez
- Department of Chemical Engineering and Environmental Technology, School of Industrial Engineering, Valladolid University, Dr. Mergelina, s/n, 47011 Valladolid, Spain; Institute of Sustainable Processes, Dr. Mergelina, s/n, 47011 Valladolid, Spain
| | - Ashvini D Chendake
- Shiv Shankar College of Agricultural Engineering, Mirajgaon, Ahmednagar, Maharashtra 414401, India
| | - Soumya Pandit
- Department of Life Sciences, School of Basic Sciences and Research, Sharda University, Greater Noida 201306, India
| | - Deepak Pant
- Separation and Conversion Technology, Flemish Institute for Technological Research (VITO), Boeretang 200, 2400 Mol, Belgium
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