Advanced Materials and Enhanced Performance of Solid Oxide Fuel Cells/Electrolyzers

A special issue of Inorganics (ISSN 2304-6740). This special issue belongs to the section "Inorganic Solid-State Chemistry".

Deadline for manuscript submissions: 30 September 2024 | Viewed by 1702

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Department of Mechanical, Energy and Management Engineering, University of Calabria, Arcavacata, 87036 Rende, CS, Italy
Interests: fuel cells; batteries; electrolyzers; hydrogen production; polygenerative systems; green mobility
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Guest Editor
Institute of Advanced Energy Technologies (ITAE), The Italian National Research Council (CNR), 98126 Messina, Italy
Interests: smart material; electrocatalysts; protonic conductor; oxygen ion conductor; mixed ionic electronic conductors; ceramics; renewable; energy conversion; energy storage; solid oxide electrochemical devices
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Solid oxide fuel cells/electrolyzers (SOFCs/SOEs) offer efficient electric and thermal energies as well as hydrogen production for residential or industrial users. Solid oxide cells (SOCs) consist of a solid-state proton and/or anion conductive electrolyte sandwiched between two porous, electronically conductive, and catalytically active electrodes. The solid electrolyte ensures the conduction of protonic or anionic charge carriers between the electrodes, and it is electronically insulating. Each of the electrodes comprises a catalyst layer (CL), where the electrocatalysts and/or high temperature promote charge transfer kinetics. 

An SOC is encased by gas manifold bipolar plates (BPPs) on each side, which direct and distribute gases in flow channels and connect the positive electrode electronically to the negative electrode of the adjacent cell in the case of an SOC stack. When an SOC is operated in fuel cell mode (SOFC), hydrogen or a mixture of syngas or methane or biogas and steam is supplied to the negative electrode, where it oxidizes mainly to steam, carbon dioxide, and electrons. 

At the positive electrode oxygen produces anions, which migrate to the negative electrode through the electrolyte or the protons migrate to the positive electrode through the electrolyte and react with oxygen to produce steam, while the electrons travel through the external circuit and deliver electrical work.

In an SOC that operates in electrolyzer mode (SOEC), the current and all the processes are reversed. An SOEC fed by steam and/or carbon dioxide and electric energy produces hydrogen and/or carbon monoxide. 

Moreover, a reversible SOC (rSOC) can work alternately in fuel cell mode and in electrolyzer mode.

This Special Issue will focus on the collection of the latest developments in solid oxide materials and components of an SOFC, SOE, and rSOC, including all recent approaches used to enhance their performance and lifetime, as well as in their technological applications.

Dr. Giuseppe De Lorenzo
Dr. Massimiliano Lo Faro
Guest Editors

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  • solid oxide fuel cell (SOFC)
  • solid oxide electrolyzer (SOE)
  • reversible solid oxide cell (rSOC)
  • SOFC applications
  • SOE applications
  • rSOC applications

Published Papers (1 paper)

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16 pages, 3845 KiB  
A Single-Stack Output Power Prediction Method for High-Power, Multi-Stack SOFC System Requirements
by Daihui Zhang, Jiangong Hu, Wei Zhao, Meilin Lai, Zilin Gao and Xiaolong Wu
Inorganics 2023, 11(12), 474; - 06 Dec 2023
Viewed by 1198
The prediction of stack output power in solid oxide fuel cell (SOFC) systems is a key technology that urgently needs improvement, which will promote SOFC systems towards high-power multi-stack applications. The accuracy of power prediction directly determines the control effect and working condition [...] Read more.
The prediction of stack output power in solid oxide fuel cell (SOFC) systems is a key technology that urgently needs improvement, which will promote SOFC systems towards high-power multi-stack applications. The accuracy of power prediction directly determines the control effect and working condition recognition accuracy of the SOFC system controller. In order to achieve this goal, a genetic algorithm back propagation (GA-BP) neural network is constructed to predict output power in the SOFC system. By testing 40 sets of sample data collected from the experimental platform, it is found that the GA-BP method overcomes the limitation of the traditional back propagation (BP) method—falling into local optima. Further analysis shows that the average relative error of GA-BP has decreased to 1%. The reduction of the relative error improves the accuracy of the prediction results and the average prediction accuracy. Compared with the long short-term memory (LSTM) and BP algorithm, the GA-BP prediction model significantly reduces the relative error of power output prediction, which provides a solid foundation for multi-stack SOFC systems. Full article
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