As energy sources diminish and ecological damage escalates, exploring green energy conversion and storage technologies becomes crucial. Electrocatalysis effectively converts green energy into chemical energy through electricity. In general, these reactions occur at double-layer interfaces, amidst a complex interface environment. It is essential for advancing electrochemistry research and the development of green energy technologies to clarify the interplay of ion-electron interactions, local potentials and electric fields. In the past decades, some researches on surface electrocatalysis have made significant progress since the standard hydrogen electrode model proposed by Nørskov et al. The model has effectively explained some origins of catalytic performance, and predicted some catalytic activity trends. However, the model has some limitations. The “electrocatalysts” encompass both “electricity” and “catalysts”. In this model, ignoring the potential effect on the electronic properties of catalysts leads to the deviation from experimental results. In addition, the failure to consider the influence of the solution in theoretical calculations also becomes another factor affecting the reaction process.This review represented the development and application on the Fixed Potential Method (FPM) based on first-principles calculations in complex interfacial electrochemistry. FPM emerges as a powerful tool for elucidating electrochemical reaction mechanisms, predicting material properties, and optimizing the design of electrochemical systems. The FPM significantly enhances the accuracy of simulating electrochemical reactions via precisely controlling the Fermi level of the reaction system and maintaining a constant electrode potential throughout simulations. Nowadays, FPM is extensively applied in the field of electrocatalysis to investigate the potential effects on the mechanisms of the oxygen evolution reaction (OER) and oxygen reduction reaction (ORR). Some work on transition metal-doped graphene (TM@graphene) catalysts reveal that the applied potential significantly affects the adsorption capacity of catalytic intermediates, charge transfer processes, and reaction pathways. The charge states of reaction intermediates exhibit a strong linear dependence on the applied potential, highlighting the importance of potential effects in catalytic mechanisms. In the realm of lithium-ion batteries, FPM is used to investigate the phase transformation processes of electrode materials. Some studies show that activation polarization induces a phase transition from the 2H phase to the 1T’ phase in MoS₂, which is crucial for understanding capacity fade in lithium-ion batteries. A research provides a theoretical framework for predicting phase transformations and discharge behavior via constructing an electrochemical phase diagram and fitting discharge curves based on zero-charge potential. In addition, FPM elucidates the concerted proton-electron transfer mechanism in proton migration within the electric double layer. Some studies demonstrate that proton migration from the outer Helmholtz layer to the electrode surface is accompanied by electron transfer, thus facilitating the migration process. The free energy changes during proton migration are affected by the applied potential and the local pH value gradient near the electrode surface, providing a theoretical basis for optimizing proton transport processes. These discoveries can enhance the comprehension of electrochemical interfacial reactions, and provide invaluable insights for the development of innovative catalysts and energy storage materials.Summary and prospectsFPM is proven to be an advanced computational method with broad application prospects in electrochemical research, such as exploring the potential effects in electrocatalytic water splitting, the activation polarization in the kinetics of lithium-ion batteries, and the concerted mechanism of proton-electron transfer within the electric double layer. These applications reveal the profound potential effects on the catalytic intermediate adsorption, charge transfer, and reaction pathways in both OER and ORR. Some researches on material phase transitions in lithium-ion batteries and their impact on battery performance also offer new avenues for improving cycle stability and energy density. Furthermore, studies on proton migration mechanisms provide theoretical guidance for optimizing proton transport at electrochemical interfaces, enhancing reaction selectivity, and boosting energy conversion efficiency. As computing power is enhanced and theoretical models are refined, the application of the FPM in electrochemical research becomes more widespread and in-depth. In addition, FPM enhances the accuracy and reliability of simulations, providing theoretical backing for the design of novel electrochemical materials, and shows promising potential for application in frontier fields like gate-controlled material phase transitions, magnetism, and electrosynthesis, offering innovative solutions to energy and environmental challenges with prospects.However, FPM has its limitations. It can control the system to achieve fractional electron numbers, thereby realizing the grand canonical ensemble for electrons, but the complex interactions among multiple atoms are difficult to accurately describe. As a result, it cannot achieve non-integer changes in ion numbers to maintain a constant chemical potential, particularly for the systems with dynamic ion concentrations at chemical reaction interfaces. It is possible that machine learning potential fitting approaches based on first-principles calculations can offer a way to balance accuracy with the advantages of large-scale simulations. Nevertheless, the development of machine learning potentials for constant potential simulations is still in its early stage. Therefore, addressing large-scale and complex simulations under constant potential remains a challenge in future theoretical developments.