Intelligent identification method and system for endogenous inactivation process of metal-based coating anode

Abstract

The invention provides a metal-based coating anode endogenous inactivation process intelligent identification method and system, and the method comprises the steps: S1, monitoring the activity index of a metal-based coating anode in an electrodeposition process in real time, and positioning the metal-based coating anode with the activity abnormally attenuated; s2, surface element analysis scanning is conducted on the metal-based coating anode with the activity abnormally attenuated, and the element proportion of metal ions and oxygen atoms of a surface coating is obtained; determining a target metal-based coating anode of which the element ratio deviates from the initial ratio; s3, collecting the concentrations of lattice-state, segregation-state and molecular-state metal ions of the target metal-based coating anode, and obtaining a corresponding concentration distribution curve; s4, performing correlation analysis on the anode electrodeposition potential of the target metal-based coating anode and the metal ion concentration in different modes to obtain a time-resolved mapping relation between an anode electrodeposition potential change value and a metal ion concentration change value in different modes; and S5, judging the anode inactivation process type of the target metal-based coating according to the time resolution mapping relation.

Description

Technical Field

[0001] This invention belongs to the field of electrochemical engineering technology, specifically relating to an intelligent identification method and system for the intrinsic deactivation process of a metal-based coated anode. Background Technology

[0002] Metal-containing wastewater is a typical type of hazardous liquid waste, often containing valuable metals such as zinc, copper, manganese, and rhenium, as well as harmful elements such as fluorine and chlorine. Resource-based treatment of industrial wastewater is one of the important pathways to achieving sustainable development. Electrowinning, due to its high efficiency and environmental friendliness, is widely used to recover valuable metals, including zinc, copper, and manganese, from wastewater. In this process, the stability of the metal-based coated anode directly affects the overall system's operating efficiency and economic benefits.

[0003] However, in practical industrial applications, especially in wastewater environments with complex compositions and high concentrations of impurity ions, metal-based coated anodes often face the problem of early endogenous deactivation. During long-term operation, the anode's performance deteriorates due to the evolution of its own microstructure, mainly manifested as increased oxygen evolution overpotential, decreased current efficiency, accelerated anode dissolution, and increased anode sludge production. The essence of this phenomenon lies in the existence of multiple competing reactions at the anode solid-liquid interface, including the primary oxygen evolution reaction, the secondary oxidation reaction of impurity ions, and the anode's own corrosion and dissolution reactions. These reactions act collectively on the anode surface, causing dynamic transformations of ions from lattice state to segregated state to molecular state, ultimately leading to the loss of anode function.

[0004] In industrial wastewater electrowinning processes, the deactivation process of metal-based coatings is generally judged by the increase in cell voltage and the anode weight loss. However, this approach has significant limitations: the increase in cell voltage can only reflect the macroscopic change in the overall resistance of the electrowinning system, but cannot analyze the local conductivity decay caused by the deterioration of the coating's microstructure; the anode weight loss data lags behind the process of intrinsic damage to the coating, and by the time the mass loss reaches the detectable threshold, the coating has already undergone irreversible peeling or dissolution of active components; because the early intrinsic deactivation process of the coating cannot be accurately identified and predicted, the opportunity for coating repair is missed, increasing the risk of coating leaching deactivation and anode usage costs, and reducing the efficiency of wastewater electrowinning resource recovery processes.

[0005] In view of this, the present invention proposes a method and system for intelligent identification of the intrinsic deactivation process of anodes in metal-based coatings. Summary of the Invention

[0006] The purpose of this invention is to propose an intelligent identification method and system for the intrinsic deactivation process of metal-based coating anodes, which aims to address the problems of complex anode deactivation mechanisms and difficulties in judging the deactivation process in wastewater electrowinning environments, and the lagging perception of anode deactivation by traditional static structure-property rules.

[0007] To achieve the above objectives, the technical solution of the present invention is as follows:

[0008] A method for intelligently identifying the intrinsic deactivation process of an anode in a metal-based coating, the method comprising the following steps:

[0009] Step 1: Monitor the activity indicators of the metal-based coated anode during the electrodeposition process in real time, including the cell voltage and anode electrodeposition potential; and use the initial activity indicators of the metal-based coated anode as a reference to initially locate the metal-based coated anode with abnormal activity decay.

[0010] Step 2: Perform surface elemental analysis on the metal-based coated anode with abnormally decreased activity to obtain the elemental ratio of metal ions and oxygen atoms in the surface coating; and determine the target metal-based coated anode whose elemental ratio deviates from the initial ratio based on the deviation threshold.

[0011] Step 3: Collect the concentrations of lattice-state, segregated-state, and molecular-state metal ions of the target metal-based coated anode, and obtain the concentration distribution curves of the three modes of metal ions over time.

[0012] Step 4: Perform correlation analysis on the anodic electrowinning potential of the target metal-based coated anode and the concentration of metal ions in different modes to obtain the time-resolved mapping relationship between the change value of anodic electrowinning potential and the change value of metal ion concentration in different modes;

[0013] Step 5: Determine the type of deactivation process of the target metal substrate coating anode based on the time-resolved mapping relationship between the anode electrowinning potential change value and the metal ion concentration change value of different modes, so as to intervene in the repair of the endogenously deactivated target metal substrate coating anode.

[0014] Preferably, in step 1, if the electrowinning potential and cell voltage of the metal-based coated anode increase by 10% or more compared to their respective initial values, it is identified as a metal-based coated anode with abnormal activity decay.

[0015] Preferably, in step 2, the metal-based coating anode with abnormally decreased activity is subjected to optical scanning or X-ray scanning to obtain the elemental ratio of metal ions and oxygen atoms in the surface coating.

[0016] Preferably, the optical scanning of the metal-based coated anode with abnormally decreased activity is specifically as follows: First, optical line scan analysis of the elemental content of the surface coating of the metal-based coated anode with abnormally decreased activity is performed. Based on the deviation threshold, abnormal points where the elemental ratio of metal ions and oxygen atoms deviates from the initial ratio are located. Then, local planar regions centered on the abnormal points are selected for point-by-point elemental content detection. The average elemental ratio of all detection points in all local planar regions is calculated as the elemental ratio of metal ions and oxygen atoms in the surface coating of the anode with abnormally decreased activity.

[0017] Preferably, in step 3, the method for obtaining the concentration of segregated metal ions is as follows:

[0018] The current response curves of the target metal-based coated anode were recorded at different potential scan rates v. Based on the current response curves, the difference ΔE between the peak current and the half-peak current was calculated. Logarithmic operations with base 10 were performed on different potential scan rates v. The difference ΔE was correlated with the logarithmic operation result log(v) to obtain the fitting curve ΔE=F[log(v)] of the difference ΔE with respect to the logarithmic operation result log(v), where F represents the functional mapping relationship between the difference ΔE and the logarithmic operation result log(v). The concentration of segregated metal ions was quantified based on the slope value of the fitting curve.

[0019] Preferably, in step 3, X-ray diffraction and X-ray photoelectron spectroscopy are used to obtain the concentration of lattice-state metal ions.

[0020] Preferably, in step 3, the concentration of molecular lead metal ions is determined by spectrophotometry.

[0021] Preferably, in step 4, the time-resolved mapping relationship between the anodic electrowinning potential change value and the metal ion concentration change value of different modes is obtained as follows:

[0022] Using the metal ion concentration x of each mode as the independent variable and the anodic electrowinning potential E as the dependent variable, a dynamic structure-property evolution model of the target metal-based coating under the corresponding mode of the anode is constructed. Where f represents the functional mapping relationship between the metal ion concentration x and the anodic electrowinning potential E in the corresponding mode; the correlation between the change in electrowinning potential and the change in metal ion concentration in different modes is determined based on the dynamic structure-property evolution model.

[0023] For any time interval, the slope of the model fitting curve under the three modes is calculated. By comparing the magnitude of the three slopes, the mode with the highest slope is determined, which is the mode of metal ion concentration change that is significantly correlated with the change value of anodic electrolytic potential in the current time interval.

[0024] Preferably, in step 5, the determination of the type of anodic deactivation process of the target metal-based coating is as follows:

[0025] The intervals in which the change in anodic electrowinning potential is significantly correlated with the change in the concentration of lattice-state or segregated metal ions are defined as the intrinsic deactivation intervals, and the intervals in which the change in anodic electrowinning potential is significantly correlated with the change in the concentration of molecular-state metal ions are defined as the extrinsic deactivation intervals.

[0026] A smart identification system for the intrinsic deactivation process of a metal-based coated anode includes a processor, a memory, and a computer program stored in the memory. When the processor executes the computer program, it specifically performs any of the steps of the aforementioned smart prediction method for identifying the characteristics of the early intrinsic deactivation process of a metal-based coated anode.

[0027] Compared with the prior art, the present invention has the following beneficial effects:

[0028] This invention proposes an intelligent identification method and system for the intrinsic deactivation process of metal-based coated anodes. Based on the study of the intrinsic deactivation process and mechanism of metal-based coated anodes before mechanical effects (including coating cracking, blistering, and peeling) appear, it solves the problem that the intrinsic deactivation stage of metal-based coated anodes in traditional wastewater electrowinning processes is difficult to define, leading to missed opportunities for coating repair. The time cost of optical scanning is proportional to the scanning range; therefore, the proposed fine scanning method, through "first-pass line scanning to locate abnormal points, second-pass local area scanning," can effectively reduce the analysis time of the elemental distribution of the coating on the metal-based anode surface. By collecting the segregation state concentration of metal ions, the diffusion and migration behavior of metal ions within the coating is quantified into comparable physical values. The constructed dynamic structure-property evolution model can be used to assist in the intelligent prediction of the intrinsic deactivation process of metal-based coated anodes during use, finding appropriate intervention opportunities for coating repair, ensuring optimal repair benefits, and significantly reducing environmental pollution and cost losses caused by coating damage, abandonment, and redeposition. Attached Figure Description

[0029] Figure 1 This is a flowchart illustrating the steps of feature identification and intelligent prediction of early intrinsic deactivation of metal-based coated anodes as described in Embodiment 1 of the present invention.

[0030] Figure 2 This is a schematic diagram illustrating the principle of feature identification and intelligent prediction of early intrinsic deactivation of metal-based coated anodes as described in Embodiment 1 of the present invention;

[0031] Figure 3 This is a flowchart illustrating the steps for acquiring different modal information as described in Embodiment 2 of the present invention;

[0032] Figure 4 This is a flowchart of the kinetic analysis of the passive reconstruction of the anodic solid-liquid reaction interface as described in Embodiment 3 of the present invention;

[0033] Figure 5 This is a schematic diagram illustrating the principle of the dynamic structure-effect database described in Embodiment 2 of the present invention. Detailed Implementation

[0034] The present invention will be further described in detail below with reference to specific embodiments, but this is not intended to limit the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not an exhaustive list of all embodiments. It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0035] Example 1

[0036] like Figure 1 As shown, this embodiment proposes an intelligent identification method for the intrinsic deactivation process of anodes in metal-based coatings. The specific steps include:

[0037] S101. Place the metal-based coated anode in the electrodeposition cell and record the anode activity indicators during the electrodeposition process, including the cell voltage and anode electrodeposition potential. Locate the anode with abnormally low activity by referring to the initial anode activity value.

[0038] Specifically, experiments were conducted on the electrowinning recovery of valuable metals in a simulated industrial copper-containing wastewater environment. The electrowinning solution consisted of CuSO4 (CuSO4) and CuSO4 (CuSO4). 2+ Concentration of 10 g·L –1 ~60 g·L –1 H2SO4 (concentration of 100 g·L) –1 ~160 g·L –1 In addition, FeSO4, CoSO4, and NiSO4 are added as typical coexisting impurity ions.

[0039] In this embodiment, a commercially available Ti / PbO2 anode (100 mm × 50 mm × 3 mm) and a 316L stainless steel cathode were used, with a fixed electrode spacing of 30 mm. The temperature of the copper-containing wastewater was set to 25 °C–55 °C, and the current density was set to 50 A·m. –2 ~600 A·m –2 It operates in a constant current continuous electrowinning mode, and recovers copper through metal electrowinning driven by electrical energy.

[0040] Record the electrowinning potential and cell voltage of the target Ti / PbO2 anode during the continuous electrowinning process. If the electrowinning potential and cell voltage increase by 10% or more from the initial values, it is considered a Ti / PbO2 anode with abnormal activity decay.

[0041] S102. Remove the Ti / PbO2 anode with abnormally decreased activity, perform optical / ray fine scanning on the Ti / PbO2 anode with abnormally decreased activity, obtain the elemental ratio of metal ions and oxygen atoms in the surface coating, compare it with the initial elemental ratio of the Ti / PbO2 anode coating, and determine the target Ti / PbO2 anode whose elemental ratio seriously deviates from the initial ratio based on the deviation threshold.

[0042] Specifically, optical line scan analysis of the elemental composition of the surface coating was performed on the Ti / PbO2 anode with abnormally decreased activity. Further local area elemental surface scan analysis was conducted on anomalies identified in the line scan results. The surface elemental ratio of the Ti / PbO2 anode with abnormally decreased activity was calculated as an average value based on the elemental ratios of all local areas.

[0043] S103. For the target Ti / PbO2 anode whose coating element ratio deviates significantly from the initial ratio, the concentrations of lattice state, segregated state, and molecular state metal ions are further collected to obtain the concentration distribution curves of lattice state, segregated state, and molecular state metal ions of the target Ti / PbO2 anode after different usage times.

[0044] In this embodiment, the current response curves of the target Ti / PbO2 anode were recorded at different potential scan rates. The difference ΔE between the peak current and the half-peak current corresponding to the potential was calculated. The logarithmic function log(v) with base 10 of the scan rate was used to obtain the fitting curve ΔE=F[log(v)] between the logarithmic function log(v) and the difference ΔE. The concentration of segregated metal ions was quantified based on the slope of the fitting curve. The concentration of lattice-state lead ions (lead dioxide and lead sulfate) was analyzed using X-ray diffraction (scanning range 2θ=10°~80°, target material CuKα) and X-ray photoelectron spectroscopy (excitation source AlKα). The concentration of molecular-state lead ions (dissolved Pb) was determined by spectrophotometry. 2+ The concentration of ions is measured. This embodiment allows for real-time analysis of three types of ions using a non-destructive method.

[0045] S104. Perform correlation analysis on the anodic electrolysis potential and different mode metal ion concentrations of the target Ti / PbO2 anode collected by the deactivation feature recognition module to obtain the time-resolved mapping relationship between the anodic electrolysis potential change value and the different mode metal ion concentration change value.

[0046] Specifically, using the metal ion concentration of each mode as the independent variable and the anodic electrodeposition potential as the dependent variable, a dynamic structure-property evolution model of the target Ti / PbO2 anode under the corresponding mode is constructed. The correlation between the change in electrodeposition potential and the change in metal ion concentration of different modes is determined based on the slope of the model fitting curve.

[0047] Anode dynamic structure-property evolution model: ;

[0048] Where: E is the anodic electrowinning potential, x is the concentration of metal ions in different modes, and f(x) is the fitting equation.

[0049] S105. Determine the type of deactivation process corresponding to the abnormal decay range of the anodic electrodeposition potential; intelligently predict the deactivation process of the Ti / PbO2 anode in use, and intervene to repair the target Ti / PbO2 anode with endogenous deactivation.

[0050] In this embodiment, the intervals where the change in anodic electrodeposition potential is significantly correlated with the change in concentration of lattice-state and segregated-state metal ions are determined as the intrinsic deactivation intervals, and the intervals where the change in anodic electrodeposition potential is significantly correlated with the change in concentration of molecular-state metal ions are determined as the extrinsic deactivation intervals.

[0051] Although this embodiment uses a Ti / PbO2 anode as an example, its underlying principle ( Figure 2 The method, which involves "abnormal anode location → inactivation feature identification → dynamic structure-property evolution analysis → intelligent prediction of inactivation process," is also applicable to other metal-based coated anode systems. It can be widely used simply by adjusting the target elements and potential windows of the characterization methods.

[0052] Example 2

[0053] This method proposes an intelligent identification and prediction method for the intrinsic deactivation process of metal-based coatings anodes, the specific method including:

[0054] Waste zinc-manganese batteries are generally recycled using a wet electrowinning process. This involves preparing zinc-containing wastewater through crushing, washing, dilute sulfuric acid leaching, and filtration, followed by electrowinning to recover metallic zinc. Specifically, low-concentration sulfuric acid (0.2% V / V) is used at 70 °C and a relatively high solid-liquid ratio (1 / 10 g∙L⁻¹). –1 Zinc in zinc-manganese batteries can be extracted by leaching; or by using a high concentration of sulfuric acid (3% V / V) at 40 °C and a low solid-liquid ratio (1 / 30 g∙L). –1 Zinc and manganese were leached out while hydrogen peroxide was added.

[0055] In this embodiment, a valuable metal recovery experiment was conducted using a Pb / PbO2 anode (100 mm × 50 mm × 3 mm) and an aluminum cathode (100 mm × 50 mm × 3 mm), with the electrode spacing fixed at 30 mm. The temperature of the zinc-containing wastewater was controlled to 35 °C–45 °C, and the DC current density was set to 400 A∙m. –2 ~600 A∙m –2 Zinc metal is recovered through continuous electrowinning with constant current.

[0056] The Pb / PbO2 anode is placed in a zinc recovery electrowinning cell. During the electrowinning process, the anode activity indicators, including the cell voltage and the anode electrowinning potential, are recorded. The anode with abnormal activity decay is located by referring to the initial activity value of the target anode.

[0057] The Pb / PbO2 anode with abnormally decreased activity was removed, and optical / ray fine scanning was performed on the Pb / PbO2 anode with abnormally decreased activity to obtain the elemental ratio of metal ions and oxygen atoms in the surface coating, which was then compared with the initial elemental ratio of the Pb / PbO2 anode coating.

[0058] Optical line scan analysis of the elemental composition of the surface coating was performed on Pb / PbO2 anodes exhibiting abnormal activity degradation. Further localized area scan analysis was conducted on anomalies identified in the line scan results. The surface elemental ratios of the abnormally degraded Pb / PbO2 anodes were calculated as averages based on the elemental ratios of all localized areas.

[0059] like Figure 3 As shown, for the target Pb / PbO2 anode whose coating element ratio deviates significantly from the initial ratio, the concentrations of lattice state, segregated state, and molecular state metal ions were further collected to obtain the concentration distribution curves of lattice state, segregated state, and molecular state metal ions of the target Pb / PbO2 anode after different usage times.

[0060] The current response curves of the target Pb / PbO2 anode were recorded at different potential scan rates. The difference ΔE between the peak current and the half-peak current was calculated. The logarithmic function log(v) with base 10 of the scan rate was used to obtain the fitting curve ΔE=F[log(v)] between the logarithmic function log(v) and the difference ΔE. The concentration of segregated metal ions was quantified based on the slope of the fitting curve.

[0061] Specifically, in this embodiment, such as Figure 4 As shown, a triangular voltage pulse is applied to the Pb / PbO2 anode starting from the anodic corrosion reaction initiation potential using an electrochemical analysis device with variable frequency or variable scan speed; first, a positive scan is performed from the initiation potential to –0.1 V vs. RHE, and then a negative scan is performed from –0.1 V vs. RHE back to the initiation potential to obtain a rapid current-potential curve.

[0062] The starting potential is the open circuit potential, and the open circuit potential test time is 5 times the total scan time of the current-potential curve analysis.

[0063] The potential response was precisely measured using an oscilloscope with an external load resistor of ≤15 Ω; the potential pulse was provided by a combination of a function generator and a self-made power amplifier.

[0064] The current-potential curves require further data extraction and processing. The volt-ampere charge is calculated based on the oxidation current (value greater than zero), defined as the substrate lead corrosion current (Pb→PbSO4) of the Pb / PbO2 anode. The volt-ampere charge is calculated based on the reduction current (value less than zero), defined as the reversible phase transition current (PbSO4→Pb) of the corrosion phase at the Pb / PbO2 anode. This is achieved through q*–(v) 0.5 Plot the graphs and determine the potential path of corrosion reconstruction at the solid-liquid reaction interface of the Pb / PbO2 anode based on the linear fit of the results, and verify the dependence of this path on the migration and diffusion of segregated ions.

[0065] Furthermore, in a liquid-phase reaction environment, the dependence of the anodic activation current of the metal-based coating on the metal corrosion process was visualized using variable scan rate triangular voltage analysis.

[0066] Specifically, in this embodiment, an electrochemical analysis device with variable frequency or variable scan speed is used to apply a triangular voltage pulse to the Pb / PbO2 anode starting from the anodic activation potential; first, a positive scan is performed from the activation potential to 2.1 V vs. RHE, and then a negative scan is performed from 2.1 V vs. RHE to the starting potential to obtain a rapid current-potential curve.

[0067] The activation potential is set with reference to the actual oxygen evolution potential.

[0068] The current-potential curves require further data extraction and processing. Based on the reverse scan oxidation current, the oxygen evolution current without interference from solid-phase anodic oxidation and liquid-phase impurity oxidation is calculated. Based on the forward scan oxidation current, the composite oxidation current coupling solid-phase anodic oxidation, liquid-phase impurity oxidation, and oxygen evolution reactions is calculated. Correlation analysis is performed between the difference in oxidation current between the forward and reverse scan curves and the scan rate. The dependence of the activation current of the Pb / PbO2 anode on the migration of segregated lead ions and its corrosion reaction is analyzed based on the significant influence of the scan rate on the current difference.

[0069] like Figure 5 The correlation analysis of the anodic electrowinning potential and the concentration of metal ions in different modes of the target Pb / PbO2 anode collected by the deactivation feature identification module is performed to obtain the time-resolved mapping relationship between the change value of the anodic electrowinning potential and the change value of the concentration of metal ions in different modes.

[0070] The time-resolved mapping relationship includes: using the metal ion concentration of each mode as the independent variable and the anode electrowinning potential as the dependent variable, constructing a dynamic structure-property evolution model of the target Pb / PbO2 anode in the corresponding mode, and judging whether the correlation between the electrowinning potential change value and the metal ion concentration change value of different modes is significant based on the slope of the model fitting curve.

[0071] Anode dynamic structure-property evolution model: ;

[0072] Where: E is the anodic electrowinning potential, x is the concentration of metal ions in different modes, and f(x) is the fitting equation.

[0073] Determine the type of deactivation process corresponding to the abnormal decay range of the anodic electrodeposition potential; intelligently predict the deactivation process of the Pb / PbO2 anode in use; and intervene to repair the target Pb / PbO2 anode that has undergone intrinsic deactivation.

[0074] The intervals where the change in anodic electrodeposition potential is significantly correlated with the change in concentration of lattice-state and segregated-state metal ions are defined as the intrinsic deactivation intervals, and the intervals where the change in anodic electrodeposition potential is significantly correlated with the change in concentration of molecular-state metal ions are defined as the extrinsic deactivation intervals.

[0075] Through the implementation of this system, a dynamic structure-property evolution model can be used to intelligently predict the early intrinsic deactivation process of the anode during the zinc recovery electrodeposition process. Although this embodiment uses a Pb / PbO2 anode as an example, its methodological framework is also applicable to other metal-based coated anode systems, and can be extended to other applications simply by appropriately adjusting the potential window of the characterization method.

[0076] Example 3

[0077] This method proposes an intelligent identification method for the intrinsic deactivation process of anodized metal-based coatings. The method includes:

[0078] The metal-based coated anode is placed in a manganese electrowinning cell for use. During the electrowinning process, anode activity indicators, including cell voltage and anode electrowinning potential, are recorded. Anodes with abnormally low activity are located by referring to the initial activity value of the target anode.

[0079] If the electrodeposition potential and cell voltage of the manganese electrodeposition target Pb / PbO2 anode increase by 10% or more compared with the initial values, it is identified as an abnormal metal-based coating anode with abnormal activity decay.

[0080] Specifically, in the manganese electrodeposition experiment, a Pb / PbO2 anode and a 316L stainless steel cathode were used, and the electrodeposition solution composition included MnSO4 (Mn 2+ The concentration is 15 g∙L –1 ), (NH4)2SO4 (110 g∙L) –1 ) and SeO2 (35 g∙L –1 ), and add FeSO4 (Fe 2+ ≤15~20 mg∙L –1 ), CoSO4 (Co 2+ ≤0.5 mg∙L –1 NiSO4 (Ni 2+ ≤1 mg∙L–1 ) and CuSO4 (Cu 2+ ≤5 mg∙L –1 () is a typical coexisting impurity ion.

[0081] A 500 mL jacketed electrolytic cell was used, with the temperature controlled at 50±1 ℃ via a constant temperature water bath; the mechanical stirring speed was set to 150 rpm to ensure uniform ion transport; the electrode spacing was fixed at 35 mm; and the current density was set to 400~600 A∙m. –2 It operates in constant current mode.

[0082] The Pb / PbO2 anode with abnormally decreased activity was removed, and optical / ray fine scanning was performed on the Pb / PbO2 anode with abnormally decreased activity to obtain the elemental ratio of metal ions and oxygen atoms in the surface coating, which was then compared with the initial elemental ratio of the anode coating.

[0083] Specifically, optical line scan analysis of the elemental composition of the surface coating was performed on Pb / PbO2 anodes exhibiting abnormal activity degradation. Further localized area scan analysis was conducted on anomalies identified in the line scan results. The surface elemental ratios of the Pb / PbO2 anodes with abnormal activity degradation were calculated as averages based on the elemental ratios from all localized areas.

[0084] For the target Pb / PbO2 anode where the coating element ratio deviates significantly from the initial ratio, the concentrations of lattice-state, segregated-state, and molecular-state metal ions were further collected to obtain the concentration distribution curves of lattice-state, segregated-state, and molecular-state metal ions of the target Pb / PbO2 anode after different usage times.

[0085] In this embodiment, due to the liquid phase impurity ion Mn 2+ Similarly, deposition on the Pb / PbO2 anode surface triggers phenomena such as interface reconstruction and anode slime release. During continuous electrodeposition experiments at 0 h, 8 h, 16 h, 24 h, and longer, it is necessary to collect ionic information at the anode solid-liquid reaction interface in different modes, including molecular, segregated, and lattice-state manganese ion information, to provide feedback on the anode slime deposition process.

[0086] Specifically, in this embodiment, spectrophotometry is used to determine the molecular state of Mn. 2+ (corresponding to MnSO4) and Mn 3+ (Corresponding to MnOOH), the segregated state of Mn was characterized using synchrotron radiation micro-region X-ray fluorescence-X-ray absorption near-edge structure spectroscopy, and the lattice state of Mn was analyzed using X-ray diffraction (scanning range 2θ = 10°–80°, target material CuKα) and X-ray photoelectron spectroscopy (excitation source AlKα). 4+ Mn 3+ Mn 2+ .

[0087] In this embodiment, an electrochemical quartz crystal microbalance was used to study the dissolution / redeposition kinetics of metallic manganese ions on the Pb / PbO2 anode surface, and synchrotron X-ray fluorescence microscopy was used to reveal the reversible mass change at the solid-liquid reaction interface and establish its correlation with molecular species.

[0088] The correlations include the manganese oxidation pathway, the type of active sites on the anode surface and their valence distribution, and the dynamic changes between molecular species, segregated states and lattice states at the Pb / PbO2 anode solid-liquid reaction interface.

[0089] In manganese-containing electrodepositers, the current response curves of the target metal-based coated anode are recorded at different potential scan rates using variable scan rate triangular voltage analysis. The difference ΔE between the peak current and the half-peak current is calculated. The logarithmic function log(v) with base 10 of the scan rate is used to obtain the fitting curve ΔE=F[log(v)] between the logarithmic function log(v) and the difference ΔE. The concentration of segregated metal ions is quantified based on the slope of the fitting curve.

[0090] Specifically, in this embodiment, an electrochemical analysis device with variable frequency or variable scan speed is used to apply a triangular voltage pulse to the Pb / PbO2 anode starting from the manganese oxidation initiation potential; first, a positive scan is performed from the initiation potential to 1.65 V vs. RHE, and then a negative scan is performed from 1.65 V vs. RHE back to the initiation potential to obtain a rapid current-potential curve.

[0091] The initiation potential is in a solution containing 15 g·L –1 Mn 2+ The electrolyte environment was 1.25 V vs. RHE, and the scan rates were 10, 20, 30, 40, and 50 mV / s. –1 .

[0092] The current-potential curves require further data extraction and processing. The volt-ampere charge is calculated based on the oxidation current (value greater than zero), defined as the anolyte deposition current (MnSO4→MnO2) on the Pb / PbO2 anode surface; the volt-ampere charge is calculated based on the reduction current (value less than zero), defined as the reversible phase transition current (MnO2→MnSO4) of the anolyte. This is achieved through q*–(v) 0.5 Plot the graphs and determine the degree of dependence of the formation process of anodic mud on the Pb / PbO2 anode surface on the migration and diffusion of segregated ions based on the linear fit of the results.

[0093] Furthermore, within the Pb / PbO2 anode activation potential window, the influence of anode mud deposition on the Pb / PbO2 anode activation current was visualized using variable scan rate triangular voltage analysis.

[0094] Specifically, in this embodiment, an electrochemical analysis device with variable frequency or variable scan rate is used to apply a triangular voltage pulse to the Pb / PbO2 anode starting from the anodic activation potential. First, a positive scan is performed from the activation potential to 2.1 V vs. RHE, and then a negative scan is performed from 2.1 V vs. RHE back to the starting potential, obtaining a rapid current-potential curve. Correlation analysis is performed between the difference in oxidation current between the positive and negative scan curves and the scan rate. Based on the significant influence of the scan rate on the current difference, the dependence of the activation current of the Pb / PbO2 anode on the migration and oxidation reaction of segregated manganese ions is analyzed.

[0095] In this embodiment, a correlation analysis is further performed on the anodic electrolysis potential of the target Pb / PbO2 anode and the concentration of metal ions in different modes collected by the deactivation feature recognition module to obtain the time-resolved mapping relationship between the change value of the anodic electrolysis potential and the change value of the concentration of metal ions in different modes.

[0096] Using the metal ion concentration of each mode as the independent variable and the anodic electrowinning potential as the dependent variable, a dynamic structure-property evolution model of the target Pb / PbO2 anode under the corresponding mode is constructed. The correlation between the change in electrowinning potential and the change in metal ion concentration of different modes is determined based on the slope of the model fitting curve.

[0097] Anode dynamic structure-property evolution model: ;

[0098] Where: E is the anodic electrowinning potential, x is the concentration of metal ions in different modes, and f(x) is the fitting equation.

[0099] Intelligent prediction of the deactivation process of the currently used manganese electrodeposited Pb / PbO2 anode, and intervention to repair the target Pb / PbO2 anode that has undergone intrinsic deactivation.

[0100] Specifically, the intervals where the change in anodic electrowinning potential of manganese electrowinning is significantly correlated with the change in concentration of lattice-state and segregated-state metal ions are determined as the intrinsic deactivation intervals, and the intervals where the change in anodic electrowinning potential is significantly correlated with the change in concentration of molecular-state metal ions are determined as the extrinsic deactivation intervals.

[0101] Through the implementation of this embodiment, a dynamic structure-property evolution model can be used to track and guide the identification and intelligent prediction of early endogenous deactivation induced by the formation of hazardous anode sludge on the Pb / PbO2 anode surface during the manganese electrodeposition process. Although this embodiment uses a manganese-containing electrodeposition solution as an example, its methodological framework is also applicable to other impurity metal electrodeposition solution systems, and can be extended to other applications simply by appropriately adjusting the potential window of the characterization method.

Claims

1. A method for intelligently identifying the intrinsic deactivation process of an anode in a metal-based coating, characterized in that, The method includes the following steps: Step 1: Monitor the activity indicators of the metal-based coated anode during the electrodeposition process in real time, including the cell voltage and anode electrodeposition potential; and use the initial activity indicators of the metal-based coated anode as a reference to initially locate the metal-based coated anode with abnormal activity decay. Step 2: Perform surface elemental analysis on the metal-based coated anode with abnormally decreased activity to obtain the elemental ratio of metal ions and oxygen atoms in the surface coating; and determine the target metal-based coated anode whose elemental ratio deviates from the initial ratio based on the deviation threshold. Step 3: Collect the concentrations of lattice-state, segregated-state, and molecular-state metal ions of the target metal-based coated anode, and obtain the concentration distribution curves of the three modes of metal ions over time. Step 4: Perform correlation analysis on the anodic electrowinning potential of the target metal-based coated anode and the concentration of metal ions in different modes to obtain the time-resolved mapping relationship between the change value of anodic electrowinning potential and the change value of metal ion concentration in different modes; Step 5: Determine the type of deactivation process of the target metal substrate coating anode based on the time-resolved mapping relationship between the anode electrowinning potential change value and the metal ion concentration change value of different modes, so as to intervene in the repair of the endogenously deactivated target metal substrate coating anode.

2. The intelligent identification method for the intrinsic deactivation process of metal-based coating anodes according to claim 1, characterized in that, In step 1, if the electrowinning potential and cell voltage of the metal-based coated anode increase by 10% or more compared to their respective initial values, it is identified as a metal-based coated anode with abnormal activity decay.

3. The intelligent identification method for the intrinsic deactivation process of the metal-based coating anode according to claim 1, characterized in that, In step 2, the metal-based coating anode with abnormally decreased activity is subjected to optical scanning or X-ray scanning to obtain the elemental ratio of metal ions and oxygen atoms in the surface coating.

4. The intelligent identification method for the intrinsic deactivation process of the metal-based coating anode according to claim 3, characterized in that, The optical scanning of the metal-based coated anode with abnormally decreased activity is as follows: First, optical line scan analysis of the elemental content of the surface coating of the metal-based coated anode with abnormally decreased activity is performed. According to the deviation threshold, the abnormal points where the elemental ratio of metal ions and oxygen atoms deviates from the initial ratio are located. Then, local planar areas centered on the abnormal points are selected for point-by-point elemental content detection. The average elemental ratio of all detection points in all local planar areas is calculated as the elemental ratio of metal ions and oxygen atoms in the surface coating of the anode with abnormally decreased activity.

5. The intelligent identification method for the intrinsic deactivation process of the metal-based coating anode according to claim 1, characterized in that, In step 3, the method for obtaining the concentration of segregated metal ions is as follows: Scan rate at different potentials v Record the current response curve of the target metal-based coated anode, and calculate the difference Δ between the peak current and the half-peak current based on the current response curve. E Scan rates at different potentials v Perform a logarithmic operation to base 10, and calculate the difference Δ. E The result of the logarithmic operation is log( v Perform correlation fitting to obtain the difference Δ E Regarding the result of logarithmic operation log( v The fitted curve Δ E = F [log( v )],in F Indicates the difference Δ E The result of the logarithmic operation is log( v The functional mapping relationship between the two is used to quantify the concentration of segregated metal ions based on the slope of the fitted curve.

6. The intelligent identification method for the intrinsic deactivation process of a metal-based coating anode according to claim 1, characterized in that, In step 3, X-ray diffraction and X-ray photoelectron spectroscopy are used to obtain the concentration of lattice-state metal ions.

7. The intelligent identification method for the intrinsic deactivation process of the metal-based coating anode according to claim 1, characterized in that, In step 3, the concentration of molecular lead metal ions is determined by spectrophotometry.

8. The intelligent identification method for the intrinsic deactivation process of a metal-based coating anode according to claim 1, characterized in that, In step 4, the time-resolved mapping relationship between the anodic electrowinning potential change value and the metal ion concentration change value of different modes is obtained as follows: Using the metal ion concentration x of each mode as the independent variable, and the anodic electrowinning potential as the independent variable... E As the dependent variable, a dynamic structure-property evolution model is constructed under the corresponding modes of the target metal-based coated anode. E = f (x), where f This represents the metal ion concentration x and the anodic electrolysis potential under the corresponding mode. E The functional mapping relationship between them; judging the significance of the correlation between the change in electrowinning potential and the change in metal ion concentration in different modes based on the dynamic structure-property evolution model: For any time interval, the slope of the model fitting curve under the three modes is calculated. By comparing the magnitude of the three slopes, the mode with the highest slope is determined, which is the mode of metal ion concentration change that is significantly correlated with the change value of anodic electrolytic potential in the current time interval.

9. The intelligent identification method for the intrinsic deactivation process of a metal-based coating anode according to claim 8, characterized in that, In step 5, the determination of the type of anodic deactivation process of the target metal-based coating is as follows: The intervals in which the change in anodic electrowinning potential is significantly correlated with the change in the concentration of lattice-state or segregated metal ions are defined as the intrinsic deactivation intervals, and the intervals in which the change in anodic electrowinning potential is significantly correlated with the change in the concentration of molecular-state metal ions are defined as the extrinsic deactivation intervals.

10. A smart identification system for the intrinsic deactivation process of a metal-based coated anode, characterized in that, The device includes a processor, a memory, and a computer program stored in the memory. When the processor executes the computer program, it specifically performs the steps of the intelligent prediction method for identifying early intrinsic deactivation process characteristics of metal-based coated anodes as described in any one of claims 1-9.

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