Simulation-guided design of a finger-like nickel-based anode for enhanced performance of direct carbon solid oxide fuel cells
Source abstract
Abstract
Direct carbon solid oxide fuel cells (DC-SOFCs) can convert solid carbon directly to electricity via electrochemical oxidation and require less investment compared to other liquid or gas-fed fuel cells. Anode characteristic is one of the important factors in achieving efficient and stable operation of DC-SOFCs. In this work, we have successfully designed and developed 2D multi-physics field models for DC-SOFCs with finger-like nickel-based anode (Cell-A) and traditional nickel-based anode (Cell-B), respectively. Simulation results revealed that the cell performance was significantly enhanced with increases in the anode porosity and decreases in the distance of carbon fuel to porous anode. More importantly, the anode featuring a finger-like pore structure assumed a pivotal role in cell performance. Specifically, Cell-A exhibited higher electrochemical performance compared to Cell-B due to the lower resistance for gas transport and more abundant amount of three-phase boundaries for electrochemical reactions. Experimental results verified the simulation findings by making and operating these two DC-SOFCs. The fabricated Cell-A with finger-like anode delivered higher power output of 858 and 371 mW cm−2 at 850 °C when fueled with hydrogen and activated carbon, respectively, relative to Cell-B with traditional anode. The beneficial characteristic of finger-like anode was further demonstrated by the ability of Cell-A to retain stable operation for 14.1 h at 100 mA with the fuel utilization of 15.8% at 850 °C. This study provides important guidance for the design and improvement of DC-SOFCs, and promotes the sustainable utilization of carbon resources.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advancements in Solid Oxide Fuel Cells · Fuel Cells and Related Materials · Semiconductor materials and devices
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (48)
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