A scheme to quantify surface coverages of reactants at triple phase boundary (TPB) by electrochemical measurements was constructed to evaluate the electrode performance of solid oxide fuel cells and electrolysis cells (SOFC/EC). The developments of electrode requires that the intrinsic properties of materials separated from the effect of geometric structure of the electrode. The proposed reaction model at TPB of H₂/H₂O electrodes is composed of competitive adsorptions and Langmure‐type surface reactions under the relationship between oxygen activity (a_O) and the electrode potential. To determine the reaction constant (k_a) and four adsorption equilibrium constants at TPB (K_H, K_H2O, K_O and K_OH), a mashine learning approach with a genetic algorithm as an optimization method and the experimental data of reversible SOFC/ECs with different H₂/H₂O partial pressures as the learning data was developed. As a result, even though all experimental curves of the current density vs. a_O in SOFC operation were fitted by numerous sets of the five constants, the coverages under different conditions could be uniquely determined. Results suggest that TPB at 900 °C was almost vacant with a small amount of H₂O in SOEC operation, and was not vacant and the OH coverage increased with increasing a_O in SOFC operation.

中文翻译：

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可逆SOFC / EC操作下基于电化学动力学的H2 / H2O电极反应物覆盖率的遗传算法确定▴

构建了一种通过电化学测量量化反应物在三相边界（TPB）的表面覆盖率的方案，以评估固体氧化物燃料电池和电解电池（SOFC / EC）的电极性能。电极的发展要求材料的固有特性与电极的几何结构的影响分开。拟议的H ₂ / H ₂ O电极在TPB处的反应模型由竞争性吸附和Langmure型表面反应在氧活度（a _O）与电极电位之间的关系下组成。确定TPB（K _H）的反应常数（k _a）和四个吸附平衡常数。，K _H2O，K _O和K _OH），以遗传算法为优化方法进行了混合学习，并以H ₂ / H ₂ O分压不同的可逆SOFC / ECs的实验数据作为学习数据。结果，即使SOFC操作中电流密度与_O的所有实验曲线都由这五个常数的许多集合拟合，但可以唯一确定不同条件下的覆盖率。结果表明，在SOEC操作中，TPB在900°C时几乎是空的，带有少量的H ₂ O，并且不是空的，并且OH的覆盖率随增加而增加SOFC操作中为_O。