Microdynamics-based electrocatalyst activity attenuation prediction method

Abstract

The invention discloses an electrocatalyst activity attenuation prediction method based on microdynamics, and relates to the field of electrochemical catalyst.According to the electrocatalyst activity attenuation prediction method based on microdynamics, an electrocatalytic reaction and an inactivation reaction are dynamically coupled in a microdynamics model for the first time, the limitation of traditional thermodynamic stability analysis is broken through, and the activity attenuation process under the working condition can be truly reflected. By introducing a residual active site coverage variable and adopting quasi-steady-state approximation, the modeling and solving problems of a dynamic process of continuous loss of active sites are successfully solved, and a complex rigid differential equation set is simplified into an analyzable linear problem. The method not only can predict a stability attenuation curve, but also can quantitatively diagnose key steps influencing the service life through half-life period control degree analysis, realizes crossing from'phenomenon prediction 'to'mechanism interpretation' and'reverse design ', and provides a powerful theoretical tool for rationally designing a high-stability electrocatalyst.

Description

Technical Field

[0001] This invention relates to the field of electrochemical catalysis, and more specifically to a method for predicting the activity decay of electrocatalysts based on microkinetics. Background Technology

[0002] Developing high-performance, long-life electrocatalysts is one of the core challenges in promoting the commercialization of clean energy technologies such as fuel cells and water electrolysis. Although many catalysts exhibit excellent electrocatalytic activity in the initial stage, their continuous performance degradation under real-world operating conditions severely limits the long-term durability and practical application potential of the entire energy device. Therefore, deeply elucidating the decay mechanisms of electrocatalysts in the operating environment and predicting their operating lifetime has become a key prerequisite for designing novel catalytic materials that combine high activity and high stability.

[0003] Currently, theoretical research methods in this field suffer from significant paradigmatic limitations. Existing simulations largely focus on the thermodynamic stability analysis of catalyst structures, primarily assessing deactivation tendencies through static descriptors such as metal-support bond strength. While these methods can explain to some extent why catalysts "might" deactivate, they struggle to characterize the dynamic evolution of deactivation "how" and "how quickly" it occurs within the reaction environment. In fact, the lifetime of a catalyst is essentially controlled by the kinetic rate of its deactivation reaction, which occurs simultaneously with and competes with the electrocatalytic reaction. This dynamic coupling creates a significant theoretical gap between traditional thermodynamic analysis and the correlation between microscopic degradation mechanisms and macroscopic performance decline. Therefore, developing a dynamic kinetic theoretical framework capable of simultaneously describing electrocatalytic and deactivation reactions, revealing how atomic-scale structural changes affect macroscopic stability evolution, and predicting the lifetime of electrocatalysts has become a crucial scientific challenge urgently requiring breakthroughs in this field.

[0004] However, the process of constructing such models faces significant theoretical challenges. The core difficulty lies in establishing a kinetic modeling method for dynamically deactivated systems with continuous loss of active sites that possesses both atomic-scale accuracy and ease of mechanistic analysis. In this system, traditional steady-state approximations are generally no longer applicable, and directly solving the rigid differential equations describing this process numerically not only results in high computational complexity but also makes it difficult to extract a clear physical picture and key control factors, thus failing to provide effective guidance for the rational design of catalysts. Summary of the Invention

[0005] To address the aforementioned shortcomings of existing technologies, this invention provides a method for predicting the activity decay of electrocatalysts based on microkinetics.

[0006] To achieve the above-mentioned objectives, the technical solution adopted by this invention is as follows: A method for predicting the activity decay of electrocatalysts based on microkinetics is provided, which adopts the following specific steps: S1: Based on the target electrochemical reaction system and operating conditions, determine the possible electrocatalytic reactions, deactivation reactions and other non-Radida processes at the electrocatalyst interface during the reaction process, and establish a solid-liquid interface model with the participation of the proposed electrocatalyst. S2: Based on existing literature reports and experimental characterization techniques, identify reaction intermediates in the solid-liquid interface model, construct an elementary reaction network including electrocatalytic and deactivation reactions, and calculate the Gibbs free energy change and kinetic energy barrier of all elementary reactions in the elementary reaction network using first-principles calculations. S3: Based on the Gibbs free energy change and kinetic energy barrier obtained in S2, the kinetic equation of the target electrochemical reaction system is established through the law of mass action and transition state theory; the proportion of the reaction intermediate in the total number of active sites that have not yet been deactivated is defined as the residual active site coverage, the residual active site coverage is introduced into the kinetic equation, and a set of differential equations about the residual active site coverage is established. S4: Using the quasi-steady-state approximation, the differential equations concerning the coverage of remaining active sites are simplified into a linear equation system. Solving the linear equation system yields the coverage of remaining active sites for all reaction intermediates. S5: Substitute the remaining active site coverage of all reaction intermediates into the kinetic differential equation of the deactivation reaction to obtain the integral expression for active site degradation. Then, use Faraday's law to replace the remaining active site density with the current density at any given time to obtain the relationship between the electrocatalytic reaction current density and time. This will give the predicted operating life of the target electrochemical reaction system and the proposed electrocatalyst under the operating conditions.

[0007] Furthermore, the solid-liquid interface model includes a periodic surface model of the proposed electrocatalyst, a solvation model of the solvation environment, and a molecular model of the adsorbed molecules or electrolytes. When assembling a solid-liquid interface model using periodic surface models, solvation models, and molecular models, additional charges are introduced into the simulation unit to simulate the real charged system. The model is established by calculating the work function to correlate the surface charge with the electrode potential of the target electrochemical reaction system and the operating conditions.

[0008] Furthermore, step S2 specifically calculates the Gibbs free energy change and kinetic energy barrier of the elementary reaction as follows: First, the absolute energy, Fermi level, and net charge number of any reaction intermediate at 0 K are calculated based on first principles; then, the vibrational frequency of any reaction intermediate is calculated using first principles, thereby obtaining the zero-point vibrational energy, entropy, isobaric thermal melting, and pressure correction quantities. The correction quantities and absolute energy are used to calculate the Gibbs free energy change of any reaction intermediate. The transition state structure of the target electrochemical reaction is determined by using a transition state search method or an enhanced sampling method; the kinetic energy barrier of the elementary reaction is obtained by calculating the energy difference between the reactants and the transition state.

[0009] Furthermore, the remaining active site coverage mentioned in step S3 The calculation formula is: ; in, For the first i The surface concentration of each reaction intermediate; c t In order to be in t At that time, the surface concentration of the remaining active sites; The total active site concentration of the target electrochemical reaction system; This represents the surface concentration of vacant sites after the loss of active sites.

[0010] Furthermore, the kinetic equation for the target electrochemical reaction system in step S3 is: ; Coverage of remaining active sites Introducing the dynamic equations, we obtain the following equations: ; in, r j For the first j The reaction rate of each elementary reaction; k j + For the first j The quasi-rate constant of the forward reaction of an elementary reaction. k j - For the first j The pseudo-rate constant of a basic reaction is the product of the transition state rate constant and other constant concentration terms. ν ij For the first i The reaction intermediate is in the first... j Stoichiometric coefficients in elementary reactions ν vj Empty space v In the j Stoichiometric coefficients in elementary reactions.

[0011] Furthermore, the coverage of remaining active sites The system of differential equations established after introducing the kinetic equations includes differential equations for all reaction intermediates, the first of which is... i The differential equations for the reaction intermediates are as follows: ; Right now ; The linear equations obtained by simplifying the differential equations in the system of differential equations are as follows: ; Solving the above equation yields θ i Under the quasi-steady-state approximation framework, its value should be a time-independent constant.

[0012] Furthermore, in step S5, the remaining active site coverage of all reaction intermediates is substituted into the kinetic differential equation of the deactivation reaction to obtain the vacancies. c v The generation rate equation is as follows: ; Solving this differential equation will yield the concentration of remaining active sites. c t and vacancy concentration c v The evolutionary function over time; After mathematical approximation and combining it with Faraday's law, the current density was finally obtained. The quantitative relationship of decay over time is as follows: ; in, z The number of electrons transferred in the electrocatalytic reaction; e The elementary charge; TOF catal,t for t Catalytic reversal frequency at a given time; TOF catal,0 for t Catalytic reversal frequency at time =0; If the catalyst only experiences the loss of active sites without drastic changes in the chemical environment, then the TOF value does not change over time, i.e.: .

[0013] This invention also provides an application of microkinetic-based prediction of electrocatalyst activity decay. Based on the deactivation rate of the deactivation reaction, the elementary reaction that has the greatest impact on the half-life of activity decay is determined. An operating condition strategy for regulating the elementary reaction is generated based on experience. This strategy is then used again to predict the electrocatalyst activity decay using the above prediction method, thereby determining the target electrochemical reaction system and the optimal operating conditions for the proposed electrocatalyst.

[0014] The beneficial effects of this invention are as follows: This application, for the first time, dynamically couples electrocatalytic reactions and deactivation reactions in a microscopic kinetic model, overcoming the limitations of traditional thermodynamic stability analysis and realistically reflecting the activity decay process under operating conditions. By introducing the variable of "remaining active site coverage" and adopting the "quasi-steady-state approximation," it successfully solves the modeling and solving problem of the dynamic process of continuous loss of active sites, simplifying the complex rigid differential equation system into an analytical linear problem. This method can not only predict stability decay curves but also quantitatively diagnose key steps affecting lifetime through half-life control analysis, achieving a leap from "phenomenon prediction" to "mechanism explanation" and "reverse design," providing a powerful theoretical tool for the rational design of highly stable electrocatalysts. The method is applicable to various electrocatalysts and multiple deactivation modes, and has broad application prospects. Attached Figure Description

[0015] Figure 1 This is a graph showing the time variation of the remaining active site coverage and the conventional coverage in Example 1; Figure 2 This is a comparison chart of the absolute deviations between using the present invention and directly solving the system of differential equations in Example 1; Figure 3 This is a comparison chart of the current decay curves obtained by using the present invention and by directly solving the system of differential equations in Example 1; Figure 4 This is a comparison chart of the electrochemical test results using the present invention and existing methods in Example 1; Figure 5 The graph shows the relationship between DHC and electrode potential during the deactivation process of the Fe-NC catalyst in Example 2. Detailed Implementation

[0016] The specific embodiments of the present invention are described below to enable those skilled in the art to understand the present invention. However, it should be understood that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the present invention as defined and determined by the appended claims. All inventions utilizing the concept of the present invention are protected.

[0017] Example 1 The rapid decline in the early activity of Fe-NC catalyst under oxygen reduction reaction conditions was used as the prediction target; the reaction process is as follows: ; ; S1: Based on the solution environment of the Fe-NC catalyst, establish a Fe-NC / Water solid-liquid interface model corresponding to the operating conditions. The solid-liquid interface model includes a periodic surface model of the Fe-NC catalyst, a solvation model of the solvation environment, and a molecular model of adsorbed molecules or electrolytes; When assembling a solid-liquid interface model using periodic surface models, solvation models, and molecular models, additional charges are introduced into the simulation unit to simulate the real charged system. The model is established by calculating the work function to correlate the surface charge with the electrode potential of the target electrochemical reaction system and the operating conditions.

[0018] S2: Based on existing literature reports and experimental characterization techniques, reaction intermediates in the solid-liquid interface model were identified, and an elementary reaction network including electrocatalytic reactions and deactivation reactions was constructed. In this embodiment, two types of reactions mainly occur at the Fe-NC catalyst interface: oxygen reduction reaction and iron dissolution process. The oxygen reduction reaction includes the following elementary reactions: ; The iron dissolution process includes the following elementary reactions: ; Those marked with * are reaction intermediates in the electrochemical reaction system; Based on first-principles calculations, the density functional theory software VASP is used to calculate the vibrational frequencies of the intermediates to approximate the contributions of zero-point vibrational energy, entropy, isobaric thermal melting, and pressure to the Gibbs free energy. The giant potential under the grand canonical ensemble is obtained by performing a Legendre transformation on the Gibbs free energy. The transition state structure of the reaction is determined using a transition state search method or enhanced sampling method; the kinetic energy barrier of the elementary reaction is obtained by calculating the energy difference between the reactants and the transition state.

[0019] In practice, to ensure the reliability of the calculation results, the following rigorous calculation scheme was implemented: the transition state search adopted the CI-NEB method combined with the DIMER algorithm for refinement; all geometric structures were fully relaxed until mechanical equilibrium was reached; the electronic structure calculation adopted a plane wave basis set, with the kinetic energy cutoff set at 450 eV; a 5×3×1 k-point grid was used for Brillouin zone sampling; the convergence criterion was set to an electronic self-consistent iteration energy change of less than 10. -5 eV, the maximum atomic force during ion relaxation is less than 0.02 eV / Å. To accurately describe van der Waals interactions, all calculations employed the DFT-D3 method and incorporated the Grimme van der Waals correction.

[0020] The results are shown in Table 1 below; Table 1

[0021] S3: Based on the thermodynamic parameters and kinetic energy barrier obtained in S2, the kinetic equations are established using the law of mass action and transition state theory. ; The remaining active site coverage is defined as the proportion of reaction intermediates among the total number of active sites that have not yet been inactivated. The calculation formula is: ; in, For the first i The surface concentration of each reaction intermediate; c t In order to be in t At that time, the surface concentration of the remaining active sites; The total active site concentration of the target electrochemical reaction system; This represents the surface concentration of vacant sites after the loss of active sites.

[0022] Introducing the remaining active site coverage into the traditional coverage variable yields a system of differential equations concerning coverage: ; in, r j For the first j The reaction rate of each elementary reaction; k j + For the first j The quasi-rate constant of the forward reaction of an elementary reaction. k j - For the first j The pseudo-rate constant of a basic reaction is the product of the transition state rate constant and other constant concentration terms. ν ij For the first i The reaction intermediate is in the first... j Stoichiometric coefficients in elementary reactions ν vj Empty space v In the j Stoichiometric coefficients in elementary reactions.

[0023] The rate constants of each elementary reaction are calculated using transition state theory. k j The following formula is used for calculation: ; in, k B Boltzmann's constant; TThermodynamic temperature; h It is Planck's constant; F ≠ ( U ) is the kinetic energy barrier; S4: Using the quasi-steady-state approximation, the differential equations about coverage obtained in S3 are simplified into a linear equation system. Solving the linear equation system yields the remaining active site coverage of all reaction intermediates. Remaining active site coverage The system of differential equations established after introducing the kinetic equations includes differential equations for all reaction intermediates, the first of which is... i The differential equations for the reaction intermediates are as follows: ; Right now ; The linear equations obtained by simplifying the differential equations in the system of differential equations are as follows: ; Solving the above equation yields θ i Under the quasi-steady-state approximation framework, its value should be a time-independent constant.

[0024] The quasi-steady-state approximation principle is: When considering changes in surface coverage, the relatively slowly changing total active site density is approximated as constant. Specifically, when the active site density on the catalyst surface changes over time, the surface density of each intermediate will no longer remain stable, and the steady-state approximation fails. ; When the residual active site density as defined by this invention is taken into account, the above equation becomes: ; On the other hand, the law of mass action states: ; Comparing the two equations, we get: ; The first term on the right side of the equation represents the catalytic rate, indicating the competition and balance among various intermediates for active sites. The second term represents the deactivation rate, indicating the loss of active sites. Both contribute to the rate of change in the remaining active site coverage. Typically, catalytic reactions are thermodynamically and kinetically more favorable than deactivation reactions, meaning that intermediates involved in the catalytic reaction will occupy most of the active sites in a very short time. For example, the turnover frequency (TOF) of electrocatalysts with promising industrial applications is typically between 0.1 and 1 s at the operating potential. -1However, the activity decay of catalysts often spans tens or even hundreds of hours. Preliminary estimates suggest that the deactivation rate is typically 5 to 7 orders of magnitude slower than the catalytic reaction rate. Therefore, in most cases, the first term on the right-hand side of the equation becomes 0 in a very short time, while the second term is negligible due to its small size, leading to the quasi-steady-state approximation. Applying this approximation, the rigid, non-homogeneous differential equations originally describing the change in coverage are transformed into a linear equation system concerning the coverage of remaining active sites. The first term in this linear equation system... i The equation can be expressed as: ; Any reaction intermediate can be obtained by solving a system of linear equations consisting of the above equations. i Remaining active site coverage Consider the rate at which vacancies are generated: ; S5: Substitute the remaining active site coverage of all reaction intermediates into the kinetic differential equation of the deactivation reaction to obtain the integral expression for active site degradation. Then, through the substitution relationship between active site density and current density, obtain the relationship between the electrocatalytic reaction current density and time. Thus, obtain the predicted operating life of the target electrochemical reaction system and the proposed electrocatalyst under the operating conditions.

[0025] Based on electrochemical principles, the change in electrocatalytic reaction current density with operating time is derived through the conversion relationship between active site density and current density (based on Faraday's law). In this embodiment, only equation "ox5" involves vacancy generation, and only... θ * ox4 Since the quantile is not 0 and equal to -1, and the quantile of the vacancy v is also 1, the equation for the rate of vacancy generation is expressed by the following simplified law of mass action: ; This equation is a first-order differential equation, and its analytical solution can be expressed as: ; Through mathematical approximation and incorporating Faraday's law, the quantitative relationship between current density decay over time is finally obtained: ; By defining the residual active site coverage and using the quasi-steady-state approximation, the decay of oxygen reduction activity on the Fe-NC catalyst over time can be quantified using the above formula.

[0026] To verify the accuracy of the above theoretical predictions, a direct numerical solution of the original rigid differential equations without approximation was used for comparative verification. The results are as follows: Figure 1 As shown, the residual active site coverage defined in this invention θi Compared with the traditionally defined surface coverage Θ i They exhibited significantly different evolutionary behaviors: the results showed θ *O It remained stable over 35 hours, while Θ *O The concentration of the intermediate decreases significantly due to the continuous loss of active sites, which confirms that the intermediate does indeed maintain a steady-state equilibrium within the remaining active site system. Figure 1 Further, it was shown that the *O reaction intermediate was produced within a very short time at the beginning of the reaction (approximately 3.0 × 10⁻⁶). -5 The quasi-equilibrium coverage is achieved within hours, indicating that the intermediate can rapidly establish dynamic equilibrium in the active site system.

[0027] The absolute deviation between the quasi-steady-state approximate solution and the direct numerical solution of the differential equation system is calculated, and the results are as follows: Figure 2 As shown, by Figure 2 It can be seen that the coverage of all intermediates calculated using the quasi-steady-state approximation of this invention is... θ i Compared with the direct numerical solution of the differential equation system, the solution results are all less than 0.05% within this time range. At the same time, the relative error is less than 0.05% within the time range under consideration.

[0028] Furthermore, the current decay curve simulated using the quasi-steady-state approximation method of this invention is overlaid with the current curve obtained by direct numerical solution of the differential equations. The result is as follows: Figure 3 As shown, by Figure 3 It can be seen that the current density decay curve obtained based on the quasi-steady-state approximation proposed in this invention is in high agreement with the numerical solution results, and the maximum deviation is always less than 3×10⁻⁶ within a 100-hour period. -5 (Approximately 0.03%), which fully verifies the accuracy and reliability of this method.

[0029] Depend on Figure 3As can be seen, this invention eliminates the need for preparing physical catalysts and conducting time-consuming stability experiments. It directly predicts through theoretical calculations that the Fe–N–C catalyst will experience rapid activity decay within tens of hours under oxygen reduction reaction conditions, with a current density half-life of 7.53 h. Therefore, this invention can directly calculate the expected lifetime of the catalyst at the theoretical level and use this to evaluate its practical application value. Furthermore, a comparison is made between the prediction method proposed in this invention and the results obtained from existing electrochemical tests. Among them, existing method 1 is the method disclosed in "DU L, PRABHAKARAN V, XIE XH, et al. Low-PGM and PGM-free catalysts for proton exchange membrane fuel cells: stability challenges and material solutions[J]. Advanced Materials, 2021, 33(6): 1908232."; existing method 2 is the method disclosed in "XIE ZY, ZHANG CY, XIE ZY, et al. Hypervelocity kineticsblocks harmful intermediates to enhance stability of Fe-NC catalysts[J]. Science China Materials, 2025, 68(3): 812-819."; existing method 3 is the method disclosed in "XUE LF, LI YC, LIU XF, et al. Zigzag carbon as efficient and stable oxygenreduction electrocatalyst for proton exchange membrane fuel cells[J]. Nature Communications, 2018, 9(1): 3819."; Figure 4This paper presents the prediction results of the kinetic model constructed in this invention for the deactivation half-life of Fe-NC catalyst under different electrode potentials, and compares and verifies them with experimental data in the prior art. The analysis results show that the model of this invention exhibits excellent prediction accuracy within the critical operating potential range of fuel cells (0.6V to 0.7V). At 0.6V, the half-life data points measured by existing method 1 fall on the model prediction curve; at 0.7V, the data points measured by existing methods 2 and 3 are highly similar and almost completely overlap with the prediction points of this model. In kinetic stability studies, the half-life measured by different experiments often exhibits absolute errors of several hours or even several times due to the influence of test conditions (such as temperature, flow rate, and bubble interference). However, as can be seen from the figure, the experimental data points and the model prediction points are always within the same order of magnitude. Considering the dynamic range spanning multiple orders of magnitude, the small absolute deviation between the experimental and predicted values ​​is statistically negligible.

[0030] The results are shown in Table 2 below; Table 2

[0031] As shown in Table 2, the calculated half-life of the Fe–N–C catalyst current density in this invention shows good quantitative consistency with the experimentally measured value, which fully verifies the reliability and effectiveness of this method in lifetime prediction.

[0032] Example 2 Based on the established kinetic model, the deactivation process was further analyzed in depth through half-life control degree analysis, identifying the key elementary steps controlling the half-life rate of activity decay, and proposing targeted strategies to improve the stability of the electrocatalyst. The functional relationship between DHC and electrode potential during the deactivation process of the Fe-NC catalyst in Example 1 under the oxygen reduction reaction condition is shown in the figure below. Figure 5 As shown, the following key information was obtained by calculating the degree of control of each elementary step over the deactivation process: (1) The elementary steps (*ox1→*O and *ox2→*OH) that lead to the recovery of the inactivated intermediate to the oxygen reduction intermediate have negative values, indicating that they have an inhibitory effect on the loss of active sites.

[0033] (2) The *O protonation step (*O→*OH), which is the rate-determining step (RDS) of the oxygen reduction reaction, shows the most significant positive value at 0.85V vs. RHE voltage. This indicates that accelerating the oxygen reduction reaction kinetics not only enhances the redox reaction activity but also exacerbates the loss of active sites, revealing the fundamental cause of the trade-off between activity and stability in Fe-NC catalysts. Based on the above kinetic characteristics, a stability enhancement strategy for Fe–N–C catalysts is proposed. For example, additional sites can be designed through interface engineering to stabilize key dissolution intermediates, thereby achieving independent regulation of catalyst stability. Specific methods include constructing heterogeneous interfaces between Fe–N–C and other materials, or designing diatomic or triatomic structures to introduce site-site interactions, thereby suppressing the deactivation process of active sites.

[0034] This invention successfully constructs a concise and efficient microscopic dynamics modeling framework by introducing two core theoretical concepts: "residual active site coverage" and "quasi-steady-state approximation." This framework significantly simplifies the originally complex and difficult-to-solve electrocatalyst operating condition loss dynamics problem, providing it with a clear mathematical description and a feasible analytical path. The significance of this invention lies not only in providing a specific modeling method but also in its profound theoretical value and wide applicability. Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can implement the steps of the above-described method embodiments.

Claims

1. A method for predicting the activity decay of an electrocatalyst based on microkinetics, characterized in that, The specific steps are as follows: S1: Based on the target electrochemical reaction system and operating conditions, determine the possible electrocatalytic reactions, deactivation reactions and other non-Radida processes at the electrocatalyst interface during the reaction process, and establish a solid-liquid interface model with the participation of the proposed electrocatalyst. S2: Based on existing literature reports and experimental characterization techniques, identify reaction intermediates in the solid-liquid interface model, construct an elementary reaction network including electrocatalytic and deactivation reactions, and calculate the Gibbs free energy change and kinetic energy barrier of all elementary reactions in the elementary reaction network using first-principles calculations. S3: Based on the Gibbs free energy change and kinetic energy barrier obtained in S2, the kinetic equation of the target electrochemical reaction system is established through the law of mass action and transition state theory; the proportion of the reaction intermediate in the total number of active sites that have not yet been deactivated is defined as the residual active site coverage, the residual active site coverage is introduced into the kinetic equation, and a set of differential equations about the residual active site coverage is established. S4: Using the quasi-steady-state approximation, the differential equations concerning the coverage of remaining active sites are simplified into a linear equation system. Solving the linear equation system yields the coverage of remaining active sites for all reaction intermediates. S5: Substitute the remaining active site coverage of all reaction intermediates into the kinetic differential equation of the deactivation reaction to obtain the integral expression for active site degradation. Then, use Faraday's law to replace the remaining active site density with the current density at any given time to obtain the relationship between the electrocatalytic reaction current density and time. This will give the predicted operating life of the target electrochemical reaction system and the proposed electrocatalyst under the operating conditions.

2. The method for predicting the activity decay of electrocatalysts based on microkinetics according to claim 1, characterized in that, The solid-liquid interface model includes a periodic surface model of the proposed electrocatalyst, a solvation model of the solvation environment, and a molecular model of adsorbed molecules or electrolytes. When assembling a solid-liquid interface model using periodic surface models, solvation models, and molecular models, additional charges are introduced into the simulation unit to simulate the real charged system. The model is established by calculating the work function to correlate the surface charge with the electrode potential of the target electrochemical reaction system and the operating conditions.

3. The method for predicting the activity decay of electrocatalysts based on microkinetics according to claim 1, characterized in that, The calculation of the Gibbs free energy change and kinetic energy barrier of the elementary reaction in step S2 is as follows: First, the absolute energy, Fermi level and net charge number of any reaction intermediate at 0 K are calculated based on first principles; then, the vibrational frequency of any reaction intermediate is calculated using first principles, thereby obtaining the zero-point vibrational energy, entropy, isobaric thermal melting and pressure correction quantities. The correction quantities and absolute energy are used to calculate the Gibbs free energy change of any reaction intermediate. The transition state structure of the target electrochemical reaction is determined by using transition state search methods or enhanced sampling methods. The kinetic energy barrier of the elementary reaction is obtained by calculating the energy difference between the reactants and the transition state.

4. The method for predicting the activity decay of electrocatalysts based on microkinetics according to claim 1, characterized in that, The remaining active site coverage mentioned in step S3 The calculation formula is: ； in, For the first i The surface concentration of each reaction intermediate; c t In order to be in t At that time, the surface concentration of the remaining active sites; The total active site concentration of the target electrochemical reaction system; This represents the surface concentration of vacant sites after the loss of active sites.

5. The method for predicting the activity decay of electrocatalysts based on microkinetics according to claim 4, characterized in that, The kinetic equation for the target electrochemical reaction system in step S3 is: ； Coverage of remaining active sites Introducing the dynamic equations, we obtain the following equations: ； in, r j For the first j The reaction rate of each elementary reaction; k j + For the first j The quasi-rate constant of the forward reaction of an elementary reaction. k j - For the first j The pseudo-rate constant of a basic reaction is the product of the transition state rate constant and other constant concentration terms. ν ij For the first i The reaction intermediate is in the first... j Stoichiometric coefficients in elementary reactions ν vj Empty space v In the j Stoichiometric coefficients in elementary reactions.

6. The method for predicting the activity decay of electrocatalysts based on microkinetics according to claim 5, characterized in that, Remaining active site coverage The system of differential equations established after introducing the kinetic equations includes differential equations for all reaction intermediates, the first of which is... i The differential equations for the reaction intermediates are as follows: ； Right now ; The linear equations obtained by simplifying the differential equations in the system of differential equations are as follows: ； Solving the above equation yields θ i Under the quasi-steady-state approximation framework, its value should be a time-independent constant.

7. The method for predicting the activity decay of electrocatalysts based on microkinetics according to claim 6, characterized in that, In step S5, the remaining active site coverage of all reaction intermediates is substituted into the kinetic differential equation of the deactivation reaction to obtain the vacancies. c v The generation rate equation is as follows: ； Solving this differential equation will yield the concentration of remaining active sites. c t and vacancy concentration c v The evolutionary function over time; After mathematical approximation and combining it with Faraday's law, the current density was finally obtained. The quantitative relationship of decay over time is as follows: ； in, z The number of electrons transferred in the electrocatalytic reaction; e The elementary charge; TOF catal,t for t Catalytic reversal frequency at a given time; TOF catal,0 for t =0 is the catalytic flip-flop frequency at time 0; if the catalyst only experiences loss of active sites without drastic changes in the chemical environment, then the TOF value does not change with time, i.e.: 。 8. An application of predicting the activity decay of electrocatalysts based on microkinetics, characterized in that, Based on the deactivation rate of the deactivation reaction, the elementary reaction that has the greatest impact on the half-life of activity decay is determined. Based on experience, an operating condition strategy for regulating this elementary reaction is generated. The solid-liquid interface model is re-established based on this strategy to predict the activity decay of the electrocatalyst, and the target electrochemical reaction system and the optimal operating conditions of the proposed electrocatalyst are determined.

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