Comparison of Current Density and Power Density Obtained From a Double Chamber Microbial Fuel Cell For Different Sludges

Uddin, Sheikh Shehab; Roni, Kazi Shoffiuddin; Kabir, Fahmid; Uddin, Sheikh Nayeem; Shatil, Abu Hena

doi:10.1109/icrest.2019.8644198

Cited by 2 publications

(1 citation statement)

References 11 publications

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“…It was also discovered that power production increased and internal resistance decreased, favoring MFC [39]. The biological treatment of sewage sludge and wastewater can also generate energy using MFC [40]. We can certainly generate electricity by increasing the COD removal rate and changing the concentration of total dissolved solids and salinity of the waste using MFC [14,29,41].…”

Section: Applications Of Mfcmentioning

confidence: 99%

A Survey of Applications of MFC and Recent Progress of Artificial Intelligence and Machine Learning Techniques and Applications, with competing fuel cells

et al. 2022

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Tomorrow is a technology for Microbial fuel cells (MFC). It has attracted numerous studies for the continuous development of cell efficiency since the problem of the coming era can be resolved. Implementing artificial learning and machine learning is a change that can effectively achieve the goals. A microbial fuel cell constitutes a complex non-linear procedure that preferably needs a strategy that is not a linear control strategy for the most optimum result. Rather than making a computationally tedious and heavy non-linear control strategy, a superior single linear model or gain scheduling, or multiple models-based control techniques are the practical and feasible ways to tackle the non-linearity existing in the Microbial Fuel Cell. Machine learning and Artificial Intelligence help reduce computation and model costs. It saves time and is more efficient than previously used manual methods, which are now obsolete. In order to find the most accurate results, the study would compare all currently available research efforts and focus on implementing Artificial Intelligence and Machine learning concepts within the Microbial Fuel Cell and comparison with other fuel cells.

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Section: Applications Of Mfcmentioning

confidence: 99%

A Survey of Applications of MFC and Recent Progress of Artificial Intelligence and Machine Learning Techniques and Applications, with competing fuel cells

et al. 2022

View full text Add to dashboard Cite

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Fabrication of Single Chamber Microbial Fuel Cell (SMFC) Using Soil as a Substrate

Sahari¹,

Rosli²,

Butit³

et al. 2022

JST

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This paper presents a Single-chamber Microbial Fuel Cell (SMFC) design by utilizing soil as a substrate with two sets of electrode combinations, which are graphite-activated carbon and copper-zinc of different sizes. It was found that graphite and activated carbon produced greater power density compared to copper and zinc. Moreover, it was observed that the graphite-activated carbon cloth electrode with a bigger surface area of 51cm2, resulted in a higher power density of 904mW/m2. To further improve the voltage production of this model, four SMFCs were stacked in series and connected to a DC-DC boost converter to increase the voltage to 1.482 V for the copper-zinc electrode and 1.722 V for the graphite-activated carbon electrode, respectively, which was sufficient to light up an LED light.

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Comparison of Current Density and Power Density Obtained From a Double Chamber Microbial Fuel Cell For Different Sludges

Cited by 2 publications

References 11 publications

A Survey of Applications of MFC and Recent Progress of Artificial Intelligence and Machine Learning Techniques and Applications, with competing fuel cells

A Survey of Applications of MFC and Recent Progress of Artificial Intelligence and Machine Learning Techniques and Applications, with competing fuel cells

Fabrication of Single Chamber Microbial Fuel Cell (SMFC) Using Soil as a Substrate

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