The proton exchange membrane water electrolyzer (PEM-WE) is a well-known green technology for hydrogen production. The main obstacle to its development, on a large scale, is the sluggish kinetics of the oxygen evolution reaction (OER). At present, the design of acid-stable electrocatalysts with low overpotential and excellent stability for the OER constitutes an important activity in electrocatalysis. This review presents an analysis of the fundamentals and strategies for the design of advanced electrocatalysts for oxygen evolution, reaction mechanisms, and OER descriptors. The scrutiny of OER electrocatalysts, with elemental composition from single- to multielemental, are presented. In addition, the purpose of high-entropy alloys (HEAs), a recent research strategy, for the design of advanced materials is summarized. Briefly, the effect of support materials, which are beneficial for modulating the electronic properties of catalysts, is presented. Finally, the prospects for the development of acidic OER electrocatalysts are given.

Mathematical models are used for simulating the electrochemical phenomena of proton-exchange-membrane (PEM) fuel cells. They differ in the scale, modeling variables, precision in specific features, and the required parameters. Often, the input parameters are not measurable and need to be estimated by minimizing the error between the model output and experimental data; however, the estimated parameters could differ from one model to another, hence provoking uncertainty about the correct values and the model’s suitability for simulating the real phenomenon. To address these issues, we introduced a self-validating methodology using three different mathematical models: The first set of parameters was estimated with a semi-empirical (SE) model; then, it was used for computing several points of the polarization curve (PC). The SE parameters and points were used to estimate a second set of parameters and to compute a single point of the PC with a macro-homogeneous (MH) model. The parameters and concentration profiles from the MH solution were used to estimate the last set of parameters with the reaction–convection–diffusion (SP-RCD) model, increasing the detail of the simulation. The SP-RCD parameters were returned to the MH model to recover the complete PC. The proposed methodology requires a few data points to consistently recover the same PC from the three models through estimating parameters in one model and validating them in the others. As output, the method provides complete information about several variables and the physical properties of the catalysts. In addition to the consistent simulation, the numerical results are consistent with those reported in the literature, thus validating the proposed method.