Nitrogen doped graphene/cobalt-based catalyst layers of a PEM fuel cell: Performance evaluation and multi-objective optimization

Kazeminasab, Bagher; Rowshanzamir, Soosan; Ghadamian, Hossein

doi:10.1007/s11814-017-0202-2

Cited by 10 publications

(3 citation statements)

References 17 publications

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“…The fminimax algorithm has the advantage of easily determining the optimum design point from an arbitrarily-selected initial design point. This method also requires fewer gradient and function evaluations compared with other nonlinear optimizations functions subject to constraints [34,35]. Using this method, the same results are obtained using different initial guesses.…”

Section: Multi-objective Optimization (Moo)mentioning

confidence: 85%

Single- and Multi-Objective Optimization of a Dual-Chamber Microbial Fuel Cell Operating in Continuous-Flow Mode at Steady State

Abu-Reesh

2020

Processes

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Microbial fuel cells (MFCs) are a promising technology for bioenergy generation and wastewater treatment. Various parameters affect the performance of dual-chamber MFCs, such as substrate flow rate and concentration. Performance can be assessed by power density ( PD ), current density ( CD ) production, or substrate removal efficiency ( SRE ). In this study, a mathematical model-based optimization was used to optimize the performance of an MFC using single- and multi-objective optimization (MOO) methods. Matlab’s fmincon and fminimax functions were used to solve the nonlinear constrained equations for the single- and multi-objective optimization, respectively. The fminimax method minimizes the worst-case of the two conflicting objective functions. The single-objective optimization revealed that the maximum PD , CD , and SRE were 2.04 W/m2, 11.08 A/m2, and 73.6%, respectively. The substrate concentration and flow rate significantly impacted the performance of the MFC. Pareto-optimal solutions were generated using the weighted sum method for maximizing the two conflicting objectives of PD and CD in addition to PD and SRE simultaneously. The fminimax method for maximizing PD and CD showed that the compromise solution was to operate the MFC at maximum PD conditions. The model-based optimization proved to be a fast and low-cost optimization method for MFCs and it provided a better understanding of the factors affecting an MFC’s performance. The MOO provided Pareto-optimal solutions with multiple choices for practical applications depending on the purpose of using the MFCs.

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Section: Multi-objective Optimization (Moo)mentioning

confidence: 85%

Single- and Multi-Objective Optimization of a Dual-Chamber Microbial Fuel Cell Operating in Continuous-Flow Mode at Steady State

Abu-Reesh

2020

Processes

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“…A large number of empirical studies have been carried out to evaluate the performance of the polymer electrolyte membrane fuel cell (PEMFC) and the effects of various parameters on their efficiency [1][2][3][4][5][6][7][8][9][10][11]. Many models have also been proposed to examine the processes occurring in the PEMFC up to now.…”

Section: Introductionmentioning

confidence: 99%

Investigation of the Fuel Utilization Factor in PEM Fuel Cell Considering the Effect of Relative Humidity at the Cathode

et al. 2020

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This research consists of both theoretical and experimental sections presenting a novel scenario for the consumption of hydrogen in the polymer electrolyte membrane fuel cell (PEMFC). In the theory section, a new correction factor called parameter δ is used for the calculation of fuel utilization by introducing concepts of “useful water” and “non-useful water”. The term of “useful water” refers to the state that consumed hydrogen leads to the production of liquid water and external electric current. In the experimental section, the effect of the relative humidity of the cathode side on the performance and power density is investigated by calculating the parameter δ and the modified fuel utilization at 50% and 80% relative humidity. Based on the experimental results, the maximum power density obtained at 50% and 80% relative humidity of the cathode side is about 645 mW/cm2 and 700 mW/cm2, respectively. On the other hand, the maximum value of parameter δ for a value of 50% relative humidity in the cathode side is about 0.88, while for 80% relative humidity it is about 0.72. This means that the modified fuel utilization for 50% relative humidity has a higher value than that for 80%, which is not aligned with previous literature. Therefore, it is necessary to find an optimal range for the relative humidity of the cathode side to achieve the best cell performance in terms of the power generation and fuel consumption as increasing the relative humidity of the cathode itself cannot produce the best result.

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“…This is attributed to formation of the Co catalyst during calcination. [32][33][34] Therefore, the Ndoped, graphitic carbon nanotubes derived from ZIF-67 are employed as the electrochemical catalyst because of their excellent electrical conductivity, high surface area, and a large number of catalytic sites.…”

mentioning

confidence: 99%

Vanadium Redox Flow Battery Using Electrocatalyst Decorated with Nitrogen-Doped Carbon Nanotubes Derived from Metal-Organic Frameworks

Noh

Lee

Seok

et al. 2018

J. Electrochem. Soc.

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Highly porous zeolitic-imidazole frameworks (ZIFs) are synthesized to produce N-doped mesoporous carbon electrocatalysts via calcination. The N-doped carbon (m-NC) and carbon nanotubes (m-NCNT) are obtained from ZIF-8 and ZIF-67, while the core-shell structure of ZIF-8@ZIF-67 produced with ZIF-8 seeds (m-NC@NCNT) is prepared by hydrothermal method. Chemical and optical evaluations of the catalysts are characterized using BET, FT-IR, XPS, XRD, Raman spectroscopy and SEM/STEM and they are used as the catalysts for redox reactions of vanadium ions and redox flow battery (VRFB) performance. In the utilization, m-NC@NCNT and m-NCNT are effective for improving VO 2+ /VO 2 + redox reaction, although m-NC does not influence that. Even in VRFB tests using the catalysts, charge/discharge potential and energy efficiency (EE) of m-NC@NCNT and m-NCNT are highest, not to mention excellent EE resilience after undergoing tougher cycling condition. These results are due to the large graphitic-N portion of the two catalysts. Namely, electrons produced by the graphitic-N are delocalized, forming pi-conjugated system and vanadium-nitrogen transition state. This state then promotes electron transfer during VO 2+ /VO 2 + redox reaction and VRFB performance.

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Nitrogen doped graphene/cobalt-based catalyst layers of a PEM fuel cell: Performance evaluation and multi-objective optimization

Cited by 10 publications

References 17 publications

Single- and Multi-Objective Optimization of a Dual-Chamber Microbial Fuel Cell Operating in Continuous-Flow Mode at Steady State

Single- and Multi-Objective Optimization of a Dual-Chamber Microbial Fuel Cell Operating in Continuous-Flow Mode at Steady State

Investigation of the Fuel Utilization Factor in PEM Fuel Cell Considering the Effect of Relative Humidity at the Cathode

Vanadium Redox Flow Battery Using Electrocatalyst Decorated with Nitrogen-Doped Carbon Nanotubes Derived from Metal-Organic Frameworks

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