Element-resolved electrochemical database: AESEC polarization curves of ZnAlMg alloy coating constituents

Element-resolved electrochemical database: AESEC polarization curves of ZnAlMg alloy coating constituents | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Element-resolved electrochemical database: AESEC polarization curves of ZnAlMg alloy coating constituents Junsoo Han, Kevin Ogle This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6511055/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Jul, 2025 Read the published version in npj Materials Degradation → Version 1 posted 12 You are reading this latest preprint version Abstract An element-resolved electrochemical database of a ZnAlMg alloy coating is presented, obtained via atomic emission spectroelectrochemistry (AESEC) linear sweep voltammetry (LSV). Nominally pure Zn, Al and Mg metals as well as MgZn 2 , ZnAl intermetallic phases, and commercial ZnAl alloy coatings were investigated using AESEC-LSV to understand the complex electrochemical response of a multi-phase ZnAlMg alloys. The elemental dissolution rates extrapolated from AESEC-LSV curves showed a linear relationship with spontaneous elemental dissolution rates. This demonstrates the possible use of AESEC-LSV for determining long-term elemental corrosion rates, as well as the use of element-specific electrochemical data as input parameters for more accurate machine learning based corrosion resistant alloy design. Element-resolved electrochemistry reveals important corrosion phenomena not detectable in conventional electrochemistry such as cathodic dissolution, chemical dissolution, cathodic dealloying, negative correlation effects, and anomalous hydrogen evolution. These phenomena may be significant and should be taken into account in the rate equations used for numerical modeling. Physical sciences/Chemistry/Electrochemistry/Corrosion Physical sciences/Chemistry/Electrochemistry Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Introduction Since the 2010s, the materials science community has witnessed a significant paradigm shift in alloy design driven by artificial intelligence (AI) and leveraging data obtained from machine learning (ML). This approach can accelerate the discovery of optimal chemical compositions, reducing the waste of rare resources compared to conventional alloy design methods. Numerical simulations and AI are helping in the selection compositions to be tested experimentally. One major limitation of this approach is the difficulty in obtaining reliable experimental data needed to train ML models for improved predictive accuracy. In terms of data quantity, high-throughput approaches in metallurgy, electrochemistry and CALPHAD (CALculation of PHAse Diagrams) simulations have been employed to supply data for screening all possible material/environment scenarios of interest. 1 , 2 , 3 , 4 , 5 For corrosion-resistant alloy design, datasets used to train ML models have primarily been derived from conventional electrochemical analysis, providing an overview of materials’ corrosion resistance, often represented by a corrosion rate 6 based on conventional theories. 7 , 8 However, this method often neglects element-specific data, as conventional electrochemical techniques cannot provide in situ element-resolved information. The absence of element-resolved data as input parameters for ML-based alloy design is a critical limitation as the quality of input data is key to effective ML model training. Another example demonstrating the importance of element-resolved data is corrosion modeling using finite element methods (FEM). 9 , 10 For example, corrosion mechanisms on the cut-edge of galvanized steel have been modeled 11 , 12 , 13 , 14 , 15 using global electrochemical data as input for the FEM-based simulation. Cut-edge corrosion refers to the situation where galvanized steel has been cut and both the Zn alloy coating and the steel are exposed on the edge with an unfavorable Zn and steel surface ratios, typically 10 µm Zn / 700 µm Fe. The corrosion rates and mechanisms depend upon the nature of the precipitated corrosion products that are formed from the specific ions released at the anode and usually hydroxide released at the cathode. Attempts to include precipitation in numerical models have proven interesting, 14,15 however, they have been based on global electrochemical data and do not necessarily account for the possibility of selective dissolution. This is particularly significant for multi-phase alloy systems. In the present work, pure metals and pure phases consisting of ZnAlMg alloy coatings were analyzed by atomic emission spectroelectrochemistry (AESEC), providing element-resolved electrochemical parameters. The ZnAlMg alloy coating system is chosen because it exhibits a multi-phase structure with complicated chemistry, 16 , 17 , 18 , 19 making it difficult to interpret conventional electrochemical data without element-specific information. The ZnAlMg alloy coating was primarily developed in the automotive industry to enhance corrosion resistance and reduce the total weight of galvanized steel. 20 This alloy has also been used in the marine and offshore industries, 21 , 22 construction materials 23 and as a biodegradable material. 24 , 25 Recent research on ZnAlMg alloy coatings focusing on chemical composition, microstructure, and the formation of surface oxides/hydroxide and their effects on corrosion properties is summarized in Table S1 . This table illustrates the complex nature of this material in terms of its chemical composition, galvanic coupling between phases, and the effect of organic/inorganic coatings, all of which play an important role in estimating corrosion performance in diverse environments. It ultimately highlights the importance of establishing a catalog of element-resolved electrochemical data to better design ZnAlMg-based multi-phase alloys and more accurately predict their corrosion behavior. The elemental dissolution mechanism is a key consideration in the corrosion of ZnAlMg alloys. For example, the presence of Zn 2+ released from the galvanized steel alloy coating during cut-edge corrosion is reported to modify the Fe-based oxide resulting in the inhibition of direct oxygen reduction on steel surface. The exchange of Zn 2+ with Fe 2+ donor sites at the surface lowers the oxygen reduction activity, which is further enhanced in the presence of Mg 2+ in the electrolyte. 26 , 27 In the case of the corrosion resistant layered double hydroxide (LDH) film formation mechanism, the metal substrate and thin metallic oxide layer may act as sources of metallic cations that form the LDH. 28 For Zn-Al based LDHs, intermediate species such as Al(OH) 4 − and Zn(OH) + are considered precursors to LDH formation. However, in situ measurements of these species to verify the LDH formation mechanism have not been carried out. 29 In other words, if we had direct access to these dissolved species, we might be able to shed light on the existence of these precursors and their underlying formation mechanisms. An element-resolved electrochemical database is therefore necessary to provide high-quality datasets for training ML models to address these issues, taking into account the elemental contributions to the reaction mechanism and ultimately enabling the effective design of corrosion resistance ZnAlMg-based multi-phase alloys. In this work, the major anodic reactions of the multi-phase coating alloy were identified based on the relative reactivity of the individual phases and pure metals via AESEC-linear sweep voltammetry (AESEC-LSV). The spontaneous elemental dissolution rate, which represents the free corrosion rate (or AESEC open circuit potential, AESEC-OCP, measurement), can be predicted by extrapolating AESEC-LSV curves. These findings may contribute to the development of a new approach in ML-based training models for new alloy design by supplying element-resolved electrochemical datasets. Results Thermodynamic simulations Figure 1 . Saturation concentration, C M (sat), M = Zn, Al, and Mg, as a function of pH in the presence of 30 mM NaCl in the solution at T = 20°C. The arrows above indicate the predominant species. Soluble species used are: ZnOH + , ZnCl + , ZnCl 3 − , ZnCl 4 2− , HZnO 2 − , ZnHCO 3 + , Zn(OH) 3 − , ZnO 2 2− , Zn(CO 3 ) 2 2− , Zn(OH) 4 2− ; Al(OH) 4 − , AlO 2 − , Al(OH) 2 + , Al 3+ ; Mg 2+ , MgOH + , MgHCO 3 + , and insoluble species are: ZnO, Zn(OH) 2 , Zn 5 (OH) 8 Cl 2 , Al(OH) 3 , AlO(OH), Al 2 O 3 , Mg 4 Al 2 O 7 ·10H 2 O, Mg(OH) 2 . The subscripted “tot” indicates total concentration of the element. Vertical dashed lines indicate the three pH values investigated in this work. AESEC polarization curve of the material - Pure metals Figure 2 shows the AESEC-LSV curves for nominally pure Zn, Al and Mg measured at pH = 8.4, pH = 10.1 with 30 mM NaCl, as well as at pH = 12.8 with 0.1 M NaOH (without NaCl). All electrolytes were deaerated with Ar. For pure Zn (Fig. 2 (a) , left), an oxidation peak of j e near − 1.1 V vs. SCE ( a 1 ) was observed in the pH = 8.4 and 10.1 electrolytes. At this point, a non-faradaic reaction was indicated by the lower Zn dissolution rate (j Zn ) compared to j e . The unaccounted charge can be attributed to the formation of less soluble Zn species, such as Zn(OH) 2 . The difference between j e and j Zn is more pronounced at pH = 10.1 because the solubility of Zn(OH) 2 is lowest at this pH, as predicted by the thermodynamic simulations shown in Fig. 1 . Faradaic Zn dissolution was observed at potentials above this point in the pH = 8.4 and 10.1 electrolytes. At pH = 12.8, Zn dissolution was nearly faradaic, i.e. , j Zn ≈ j e , above the j = 0 potential (E j=0 ) because Zn(OH) 2 is highly soluble at this pH (Fig. 1 ). 32 , 33 For pure Al (Fig. 2 (a) , middle), anodic dissolution in the cathodic potential domain for the pH = 8.4 and 10.1 electrolytes, -1.8 V vs. SCE < E < E j=0 , was monitored. In this potential domain, Al dissolution was potential dependent and closely followed the cathodic current. This phenomenon is referred to as the cathodic dissolution of Al 31, 34 , 35 , 36 and cannot be detected using conventional electrochemical measurements. The dissolved Al species, such as Al(OH) 4 − , and the electron stoichiometry follow the ratio described by the following reaction: Al + 4H 2 O + e − ◊ Al(OH) 4 − + 2H 2 [1] This yields a mole ratio of Al : e − = 1, or a current density ratio of j Al : │j e │ = 3 : 1, where j Al = z Al F v Al . Here, v Al is the elemental dissolution rate of Al in mol cm − 2 s − 1 . For both pH = 8.4 and 10.1 electrolytes, the observed ratio j Al : │j e │ was approximately 2.9 : 1 in the cathodic potential domain, confirming the cathodic Al dissolution mechanism ( Reaction 1 ). Unlike pure Zn, insoluble species indicated by j e > j Al for pure Al at pH = 10.1 contradicts the thermodynamic predictions in Fig. 1 as higher Al solubility is expected at pH = 10.1 than at pH = 8.4. This discrepancy may be related to the enhanced cathodic reaction at pH = 8.4 (evidenced by higher j e and a larger cathodic potential domain) which increases the interfacial pH to a value even higher than that of the pH = 10.1 solution. At pH = 12.8, however, Al dissolution was potential independent, 33, 37 indicating that the dissolution was controlled by the steady state formation and dissolution of an Al(OH) 3 passive film as described by: Al + 3OH − ◊ Al(OH) 3 + 3e − [2] Al(OH) 3 + OH − ◊ Al(OH) 4 − [3] 3H 2 O + 3e − ◊ 3OH − + 1.5H 2 [4] Reactions 2 and 3 were in a steady state. There was no correlation between j e and j Al at pH = 12.8, suggesting that Al dissolution was not driven by the electrochemical reaction. This phenomenon has been referred to in the literature as “chemical corrosion”. 38 In this case, the mass transport of OH − in Reaction 4 was the rate determining step (RDS). It should be noted that the noise signal of j Al was proportional to the quantity of the evolved H 2 gas. The stoichiometry between the dissolved Al species (Al(OH) 4 − , Reaction 3 ) and the evolved H 2 gas ( Reaction 4 ), in a ratio of 1 : 1.5, has been demonstrated using AESEC coupled gravimetric gas measurement. 39 One important point to note in the case of AESEC-LSV curves for pure Al is the determination of the “true” corrosion rate. According to conventional Tafel extrapolation method, the corrosion rate may be estimated as the intersection of the anodic and cathodic Tafel lines extrapolated to E j=0 . However, this approach may significantly underestimate the true corrosion rate. The true Al dissolution rate at E j=0 determined using an “element-resolved mixed potential theory” as indicated by arrows in Fig. 2 , was more than an order of magnitude higher than the rate obtained from conventional method. 40 , 41 , 42 This highlights the critical importance of element-resolved analysis in accurately measuring corrosion rates as well as its value as an input parameter for ML modeling. Mg dissolution (Fig. 2 (a) , right) at pH = 8.4 and 10.1 occurred in the cathodic potential domain, i.e. , E < E j=0 , which again cannot be monitored by conventional electrochemical measurements. Mg dissolution was potential dependent at pH = 8.4 and 10.1 within the potential range investigated in this work. In these solutions, Mg dissolution exhibited perturbed j Mg signals, though not highly prominent on a logarithmic scale, especially at more positive potentials, i.e. , E > -1.2 V vs. SCE, which can be attributed to the evolution of hydrogen bubbles, 43 often referred to as anomalous anodic hydrogen evolution (AHE). The evolved gas bubbles were visibly present inside the capillary. In these solutions, j Mg > j e was monitored with j Mg / j e = 1.44 (pH = 8.4) and j Mg / j e = 1.14 (pH = 10.1). This also indicates AHE because the hydrogen evolution current (j H2 ) results from a cathodic reaction, i.e. , j H2 j e in the case of AHE. At pH = 12.8, no Mg dissolution was observed in agreement with the thermodynamic prediction shown in Fig. 1 . The spikes in j Mg observed under these conditions were due to the detachment of Mg(OH) 2 precipitates as indicated by the upward increase in j Mg . The same series of experiments was performed for pure metals in electrolytes saturated with O 2 by bubbling directly pure O 2 gas into the solution, as shown in Fig. 3 . Nearly the same conclusions as in the Ar deaerated solution can be drawn for pure Al and Mg. However, cathodic Zn dissolution was observed in the cathodic potential domain in the presence of O 2 in the solution (39 mg L − 1 as measured by an oxygen meter). Notably, this cathodic Zn dissolution was not observed in Ar deaerated electrolyte shown in Fig. 2 . This is likely due to the enhancement of the interfacial pH by oxygen reduction. The presence of O 2 increased the interfacial OH − concentration in the unbuffered solution via the reaction: O 2 + 2H 2 O + 4e − ◊ 4OH − [5] which accelerated the formation of soluble Zn(OH) 3 − and/or Zn(OH) 4 2− species. AESEC polarization curve of the material - Intermetallic phases Figure 4 shows the AESEC-LSV curves of intermetallic phases obtained in the same electrolyte as in Fig. 2 . For the MgZn 2 intermetallic phase at pH = 8.4 and 10.1, the j Mg value was decreased by a factor of 100 to 1000 compared to that measured for pure Mg (shown in Fig. 2 ). In these electrolytes, the onset potential of Zn dissolution, E c Zn , was shifted 30–100 mV in the more positive direction compared to pure Zn in Fig. 2 . Selective Mg dissolution was observed for E < E c Zn leading to the formation of a metallic Zn layer, Zn(0), on the surface. 30 The lower j Mg for the MgZn 2 phase compared to pure Mg was attributed to the formation of this Zn(0) layer which inhibited further Mg dissolution. Under spontaneous corrosion conditions, 30 significantly reduced Mg and Zn dissolution rates were observed compared to those of the pure metals. Selective Mg dissolution was also observed in spontaneous corrosion, again forming a Mg depleted Zn(0) enriched layer that blocked elemental dissolution. The selective Mg dissolution maintained the potential just below the onset of Zn dissolution. For MgZn 2 in pH = 8.4 and 10.1 electrolytes, the onset potential for Mg dissolution was identical within experimental error to that of Zn (E c Zn ), indicating simultaneous dissolution of Mg and Zn. For E > E c Zn , Mg and Zn dissolved nearly congruently as indicated by j Zn / j Mg ≈ 2 (with oxidation states of Zn and Mg, z Zn = z Mg = 2). The faradaic yield of anodic dissolution (j Zn + j Mg ) / j e ≈ 1 indicated no significant formation of insoluble species. At pH = 12.8, no Mg dissolution was observed similar to pure Mg. Zn oxidized but at a significantly lower rate than pure Zn (Fig. 2 ) due to the blocking effect of Mg-based less soluble species formed at this pH. For all three Zn-Al intermetallic phases shown at pH = 8.4 and 10.1, selective Al dissolution in the cathodic potential domain, i.e. , cathodic dealloying, was observed. In these electrolytes, Al dissolution in the cathodic potential domain was potential dependent as seen for pure Al in Fig. 2 . This demonstrates that the Zn(0) layer formed by selective Al dissolution in Zn-Al intermetallic phases does not significantly alter the kinetics of cathodic Al dissolution, unlike in the case of MgZn 2 . At pH = 8.4 and 10.1, the Al dissolution rate profile in the cathodic potential domain for Zn68Al (Fig. 3 (d) ) is similar to that of Zn22Al (Fig. 3 (c) ) even though the latter contains significantly less Al, indicating that cathodic dealloying varies little with Al composition. For Zn68Al, the origin of the oxidation peak ( a 2 ) was previously demonstrated to be the oxidation of the Zn(0) layer formed during selective Al dissolution, as confirmed by the AESEC potentiodynamic step experiment. 31 At pH = 12.8, potential independent Al dissolution was observed similar to pure Al, indicating that the formation and dissolution of Al(OH) 3 were in a steady state. The onset dissolution of Zn resulted in a decrease in Al dissolution rates, a phenomenon previously referred to as the “negative correlation effect (NCE)”. 33 This effect was attributed to the dissolution of the Zn(0) enriched layer leading to the precipitation/dissolution of Zn(OH) 2 , which retards Al dissolution. In the passive domain where the Zn dissolution rate decreased and became independent of potential, the Al dissolution rate increased. In this domain, Al dissolution occurred through the passive ZnO layer, as indicated by a significantly reduced perturbation signal of j Al compared to that observed in the cathodic potential domain. 44 The NCE can be clearly seen in Fig. 5 where Zn22Al in a deaerated pH = 12.8, 0.1 M NaOH solution underwent a fixed frequency of f = 0.0046 Hz at an applied potential of -1.31 V vs. SCE (active domain as shown in Fig. 4 ). The j Zn oscillation was in-phase with the sinusoidal applied potential while j Al was 180° shifted. Figure 6 shows the same series of experiments for intermetallic phases in O 2 saturated electrolytes. Note that O 2 saturation did not change the dissolution profile for pure Al (Figs. 2 and 3 ). Significantly lower Mg dissolution in the cathodic potential domain compared to the Ar deaerated electrolyte was observed for the MgZn 2 intermetallic phase at pH = 8.4 and 10.1 due to the enhanced formation of Mg-based insoluble species caused by the increased interfacial OH − concentration. A slight Mg dissolution peak at E = -1.75 V vs. SCE was monitored for MgZn 2 in the pH = 12.8 solution which may be due to the dissolution of Mg-based particles released from insoluble Mg-based insoluble species. Cathodic Zn dissolution was monitored for Zn-Al intermetallic phases similar to pure Zn (Fig. 3 ) at this pH. In this case, Al dissolution was again restrained by Zn dissolution, confirming the NCE mechanism. AESEC polarization curve of the material - Commercial alloy coatings Commercial ZnAl (Zn5Al and Zn55Al) and ZnAlMg alloy coatings were investigated to compare them with the results for pure metals and intermetallic phases, as shown in Fig. 7 . Selective Al dissolution in the cathodic potential domain, i.e. , cathodic dealloying, was observed in all three alloys at pH = 8.4 and 10.1. The stoichiometry of cathodic dealloying was less evident than that of intermetallic phases because j Al : | j e | ≠ 3 : 1 for the alloy coatings. This demonstrates the effect of microstructure on cathodic reaction kinetics: selective dissolution of Al occurred not across the entire surface but at highly localized Al-rich phases. 45 Therefore, OH − did not sufficiently react with Al in multi-phase alloys. For ZnAlMg alloy at pH = 8.4 and 10.1, Mg also dissolved in the cathodic potential domain and followed an opposite trend to Al: when j Al increased, j Mg decreased, and vice versa . The origin of this opposing dissolution trend of Al and Mg in the cathodic domain remains unclear. One possible explanation is that, at pH = 8.4 and 10.1, the Al-rich α-phase Al ( i.e. , Zn68Al) is electrochemically more active than the MgZn 2 phase as evidenced by the more negative E oc of the α-phase Al compared to the MgZn 2 intermetallic phase. When a cathodic potential was applied, the α-phase Al selectively dissolved via the cathodic dealloying mechanism ( Reaction 1 ). This selective Al dissolution may expose the MgZn 2 phase to the electrolyte. As the potential was swept in a more positive direction (-1.6 V < E E j=0 at which Zn became electrochemically active. The elemental Tafel slopes determined from j Zn , b a, jZn , are provided in Supplementary Materials, Table S2 - S7 . For the ZnAlMg alloy b a, jZn was 55 mV decade − 1 at both pH = 8.4 ( Table S2 ) and 10.1 in Ar deaerated electrolytes ( Table S4 ), similar to that of the η-phase Zn (Zn0.7Al, ≈ 56 mV decade − 1 ) and other η-phase containing alloys, i.e. , Zn5Al (≈ 57 mV decade − 1 ) and Zn55Al (≈ 52 mV decade − 1 ) in deaerated electrolytes. For comparison, the b a, jZn values for non-η-phase of Zn containing specimens, e.g. , pure Zn (71 ~ 75 mV decade − 1 ), MgZn 2 (20 ~ 79 mV decade − 1 ), Zn22Al (39 ~ 48 mV decade − 1 ) and Zn68Al (27 ~ 47 mV decade − 1 ) differ from those of η-phase of Zn containing samples. This demonstrates that the dissolution of Zn occurs at the η-phase of Zn. The simultaneous dissolution of Zn and Mg in the ZnAlMg alloy for E > E c Zn at pH = 8.4 and 10.1 was attributed to the dissolution of the MgZn 2 intermetallic phase and Zn from the substrate. For E > E c Zn , the NCE was also observed for all ZnAl and ZnAlMg alloy coatings. 33 At pH = 12.8, the effect of microstructure was less pronounced than at the lower pH solutions. For example, Zn55Al (Fig. 7 ) exhibited an AESEC-LSV trend almost identical to that of Zn68Al (Fig. 4 ). Similarly, Zn5Al and ZnAlMg displayed analogous elemental dissolution trends to each other as well as to Zn0.7Al (Fig. 4 ), as a function of the potential sweep. This is primarily due to the highly reactive Al and non-solubility of Mg at pH = 12.8 which makes the chemical system predominant in determining the elemental dissolution profile. The decrease in j Al in Fig. 8 for O 2 saturated electrolytes was attributed to the enhanced Zn dissolution, particularly in the cathodic potential domain. This phenomenon, as observed in Fig. 6 for the intermetallic phases, is linked to the NCE. Predicting corrosion: galvanic series of materials The galvanic series of materials tested in this work was investigated via open circuit potential (E oc ) values in each electrolyte, as shown in Fig. 9 . The E oc values averaged over at least 300 s of measurement are provided as a function of Zn content (% Zn) for both Ar deaerated and O 2 saturated electrolytes under three pH conditions. For pH = 10.1 and 12.8, E oc increased with increasing % Zn because the presence of Al or Mg shifted the potential in a more negative direction. In this pH range, Al selectively dissolved while Zn and Mg formed stable oxides/hydroxides (Fig. 1 ). This is evidenced by the more positive E oc of MgZn 2 which does not contain Al. At pH = 8.4, no clear relationship between E oc and % Zn was observed. At this pH, both Mg and Zn are thermodynamically soluble whereas Al forms a stable oxide/hydroxide (Fig. 1 ). The effect Mg dissolution shifting E oc in a more negative direction may not be as significant as in the higher pH range because Zn dissolution shifted the potential in a more positive direction, potentially counteracting the effect of Mg dissolution. The spontaneous elemental dissolution rates at near steady state (j s M ) under open circuit condition were recorded via AESEC. The j s M values of pure metals and ZnAlMg alloy coating in three pH electrolytes are presented in Fig. 10 , while those for other pure metals and intermetallic phases are shown in Fig. 11 . Note that the j s M of the ZnAlMg alloy coating in Fig. 10 was normalized based on its molar composition. The trend of j s M for pure metals reasonably follows that of thermodynamically simulated solubility (Fig. 1 ). For example, at pH = 10.1 (Ar deaerated), j s Zn < j s Al < j s Mg , which aligns with thermodynamic predictions of solubility at this pH (Fig. 1 ). However, for the ZnAlMg alloy coating, j s Al exhibited the highest value in the Ar deaerated electrolyte at pH = 10.1, deviating from thermodynamic predictions. This discrepancy may be explained by the E oc values of the specimens shown in Fig. 9 : At pH = 10.1, the Al-rich α-phase (Zn68Al) is the most electrochemically reactive as evidenced by its more negative E oc compared to intermetallic phases, such as Zn0.7Al, Zn22Al, and MgZn 2 . Consequently, the selective dissolution of the Al-rich α-phase would result in higher Al dissolution than predicted by thermodynamic simulations. Figure 12 presents the spontaneous steady state elemental dissolution rates, j s M (AESEC-OCP), vs. the elemental dissolution rates extrapolated from AESEC-LSV curves at E j=0 , j M (AESEC-LSV). A linear relationship between the two measurements is observed, indicating that elemental dissolution rates extrapolated using the “element-resolved mixed potential theory” from AESEC-LSV curves can be used to estimate spontaneous elemental corrosion rates. 46 In this way, long-term elemental corrosion rates can be simply determined through an AESEC-LSV assessment. The slight discrepancy between the two methods may be attributed to the challenge of defining the corrosion potential, i.e. , the spontaneous potential (E oc ), which often differs from E j=0 . Discussion In this work, we have demonstrated a variety of different mechanisms and provided a database of electrochemical kinetics for a wide range of ZnAlMg alloys, intermetallic phases, and pure metals. The element-resolved dissolution mechanism depending on solution pH, alloy composition, and applied potential has been elucidated. The AESEC-LSV results of a multi-phase ZnAlMg alloy system can be predicted through a bottom-up analysis starting from pure metals and intermetallic phases. The cathodic dissolution mechanism, the negative correlation effect, and the anomalous hydrogen evolution mechanism were investigated across different pH values and elemental compositions. Elemental Tafel slopes determined from j Zn , as well as the onset dissolution potential of Zn, which are difficult to determine using conventional electrochemical analysis, are provided and can be used as input parameters to train ML models for predicting element-specific corrosion behavior. We have also demonstrated how to predict the elemental spontaneous dissolution (corrosion) rate using AESEC-LSV measurements. This approach alloys the true corrosion rate to be determined from elemental signals, enabling the development of an unprecedented element-resolved corrosion rate database. Conventionally, FEM has been used as a numerical method to simulate electrical, mechanical, and chemical systems using differential equations. FEM-based simulations have been conducted to understand galvanic corrosion 47 at the cut-edge of galvanized steel, 13, 48 cathodic delamination of paint on Zn, 49 , 50 galvanic corrosion from intermetallic particles in Al-based alloys, 51 , 52 metallic protective coatings, 53 , 54 atmospheric corrosion, 55 , 56 and localized corrosion. 57 , 58 More recently, FEM has also been applied to simulate localized corrosion 59 and the design of additive manufactured alloys. 60 , 61 FEM corrosion models assume idealized corrosion conditions, such as uniform corrosion, constant environmental factors, and the results depend highly on how boundary conditions are defined, which may be difficult to determine accurately. The use of the FEM relies on the validated material data, e.g. , exchange current density, which may not always be available for all material/environment combinations. To leverage these issues, a ML-based surrogate model has recently been proposed, yielding more robust and reliable FEM simulations, 62 although the necessity of training the model with element-resolved electrochemical data still persists. The conventional polarization curve has been used to provide input parameters for ML model to design corrosion resistant alloys and predict corrosion rates. However, extracting elemental dissolution rates from the conventional j e vs. E curve is challenging. For example, anodic Al dissolution in the cathodic potential domain is completely masked by the intense cathodic current as evidenced by j Al (Al) > j e (Al) in Figs. 2 – 8 . Quantifying the potential dependent Al dissolution rate in the cathodic potential domain could be critical for layered double hydroxides (LDHs) conversion coating system using Al-containing alloys where cathodic Al dissolution could serve as a source of Al 3+ to form Zn-Al-based LDHs. This example demonstrates the importance of training ML models that incorporate element-resolved information. Another complexity in predicting corrosion behavior using the conventional polarization curve is defining a “corrosion potential”, as briefly introduced in Fig. 11 . Table 1 summarizes E oc , E j=0 , and E c Zn for all systems investigated at pH = 10.1 in Ar deaerated and O 2 saturated solutions containing 30 mM NaCl. Results for other electrolyte conditions including the b a, jZn and spontaneous elemental dissolution rates (j s M ) are provided in the Table S2 - S7 . Table 1 E oc , E j=0 , and E cZn obtained for each samples at pH = 10.1 in 30 mM NaCl, Ar deaerated and O 2 saturated electrolytes. V vs. SCE Zn Al Mg Zn0.7Al Zn22Al Zn68Al MgZn 2 Zn5Al Zn55Al ZnAlMg Ar deaerated E oc -0.98 -1.44 -1.65 -0.96 -1.30 -1.31 -1.06 -1.12 -1.22 -1.07 E j=0 -1.21 -1.41 -1.64 -1.27 -1.29 -1.28 -1.21 -1.31 -1.30 -1.31 E c Zn -1.10 - - -1.12 -1.13 -1.14 -0.96 -1.12 -1.10 -1.14 O 2 saturated E oc -0.93 -0.71 -1.60 -0.94 -1.05 -0.99 -0.99 -0.93 -0.98 -0.95 E j=0 -0.85 -0.75 -1.58 -0.90 -1.00 -0.91 -0.87 -0.91 -0.89 -0.90 E c Zn -0.90 - - -1.01 -1.08 -0.94 -0.87 -1.05 -0.91 -0.93 In most cases, E oc and E j=0 were different, with the difference ranging from 10 mV to 240 mV in Ar deaerated electrolytes. The E oc values did not show a clear relationship with chemical composition or microstructure. It should be noted that corrosion rate measurements are generally performed using separate cathodic and anodic polarization curves starting from E oc . Therefore, this difference can be critical in determining the true “corrosion potential” for predicting corrosion rates. The E oc values are currently used to train the ML model; thus, uncertainty in their determination could lead to inaccurate predictions of corrosion rate, even if the dataset is sufficiently large. To improve accuracy, it is necessary to investigate element-resolved electrochemical parameters such as E c Zn and b a, jZn , to provide higher-quality, element-specific information to ML models. In O 2 saturated electrolytes, this difference was less significant, ranging from 20 mV to 40 mV. The effect of dissolved O 2 on the discrepancy between E oc and E j=0 was evident for pure Zn, but not for pure Al and Mg. This can be attributed to the formation of ZnO or Zn(OH) 2 near E j=0 , (Fig. 2 , pure Zn at pH = 10.1) as evidenced by the non-faradaic dissolution of Zn in this potential range (j e > j Zn ), which indicates the formation of less soluble oxide/hydroxide. The E c Zn values in Ar deaerated electrolyte for all samples were close to -1.10 V vs. SCE, except for MgZn 2 . A 260 mV more positive E c Zn observed for MgZn 2 was attributed to the formation of a Zn(0) layer during the cathodic potential scan caused by selective Mg dissolution. In O 2 saturated electrolyte, the E c Zn values did not show a clear trend, likely due to the interplay with Al ( i.e. , NCE) and Mg. Conclusion A new approach to element−resolved mixed potential analysis may be obtained using AESEC LSV curves. The electrochemical responses of a multi−phase system could be predicted through a bottom−up analysis starting from pure metals and individual phases. An element−specific electrochemical database, including EcZn, jsM, and ba, jZn for pure metals, intermetallic phases and alloy coatings has been established across a pH range of 8.4 ~ 12.8. This database can be used for corrosion rate prediction more accurately than conventional analysis. The spontaneous elemental dissolution rates obtained from AESEC−OCP show a linear relationship with the elemental dissolution rates obtained from AESEC−LSV across a relatively wide range of pH and different chemical compositions and microstructure. This indicates that elemental corrosion rates can be estimated through a relatively short and simple AESEC−LSV measurement. Providing these element−specific data will enhance the reliability of the ML−based corrosion resistant alloy design approach. Element−resolved electrochemistry reveals important corrosion phenomena not detectable in conventional electrochemistry such as cathodic dissolution, chemical dissolution, cathodic dealloying, negative correlation effects, and anomalous hydrogen evolution. These phenomena may be significant in a corrosion process and should be taken into account in the rate equations for numerical modeling. Methods Materials Two ZnAl and one ZnAlMg commercial alloys were used in this work. The Zn-5 wt.% Al alloy (denoted as Zn5Al) has been reported to have a eutectic structure consisting of a dendritic η-phase of Zn interspersed within the lamella of the Zn-rich Al phase (β-phase of Al). 93 , 94 , 95 The Zn-55 wt.% Al-1.6 wt.% Si alloy (denoted as Zn55Al) is generally composed of a dendritic Al-rich phase (α-phase of Al) and a Zn-rich interdendritic phase. 96 , 97 , 98 , 99 A commercial ZnAlMg alloy exhibiting a microstructure comprising a dendritic η-phase of Zn, a Zn-MgZn 2 binary eutectic, and a Zn-Al-MgZn 2 ternary eutectic phase was used in this work. 100 , 101 , 102 , 103 , 104 Binary phases were obtained from the University of Chemistry and Technology in Prague . Detailed information on sample preparation and their characterization can be found elsewhere. 30,31,33,44 Atomic emission spectroelectrochemistry (AESEC) The AESEC technique has been described in detail in our previous publications. 105 , 106 An Ultima 2C™ inductively coupled plasma - atomic emission spectrometer (ICP-AES, Horiba France) coupled with an electrochemical measurement system was used. A Gamry Reference 600™ potentiostat was used to perform electrochemical tests. A saturated calomel electrode (SCE) was used as the reference electrode in pH = 8.4 and 10.1 solutions, while a Hg/HgO electrode in 0.1 M NaOH was used as the reference electrode in the pH = 12.8 solution. All potential values presented in this work are referenced to SCE for ease of comparison. A Pt foil was used as the counter electrode. The intensity information of each element at its specific wavelength was converted into elemental concentration using conventional ICP-AES calibration methods. Elemental dissolution rates ( v M ) were then obtained from the elemental concentrations using an electrolyte flow rate ( f ) of 2.8 mL min − 1 controlled by a peristaltic pump. It is often convenient to present v M as an equivalent elemental current density to facilitate comparison with the electrical current density: j M = z M F v M [6] where z M is the valence of the dissolved ion M, and F is the Faraday constant. In this work, z Zn and z Mg were taken as 2 and z Al was taken as 3 based on thermodynamic prediction shown in Fig. 1 . Declarations Author contributions JH carried out the AESEC experiments and performed analysis. JH and KO conceptualized the AESEC analysis. JH and KO contributed to write the paper and revision. JH and KO read and approved the final manuscript. Competing interests All authors declare no competing interests. Data availability The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request. Acknowledgement The authors would like to express our sincere gratitude to Dr. Jan Stoulil ( University of Chemistry and Technology in Prague, Czech Republic ) for supplying intermetallic phase samples. The authors also would like to express their appreciation to the coordinators: Prof. Tomáš Prošek ( University of Chemistry and Technology in Prague, Czech Republic ), Dr. Nathalie LeBozec and Dr. Dominique Thierry ( Institut de la Corrosion ) as well as the other partners of the project. This work was partially supported by Research Fund for Coal and Steel , grant n°RFSR-CT-2015-00011. This work was also supported by the French government’s “France 2030” initiative through the PEPR-DIADEM ( Priority Research Programs and Equipment - Integrated Devices for Accelerating the Deployment of Emerging Materials ) program, managed by the French National Research Agency ( Agence Nationale de la Recherche , ANR ), n°ANR-23-PEXD-0006. 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Opi. Electrochem. 41 , 101350 (2023), https://doi.org/10.1016/j.coelec.2023.101350 Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterials.docx Cite Share Download PDF Status: Published Journal Publication published 28 Jul, 2025 Read the published version in npj Materials Degradation → Version 1 posted Editorial decision: Revision requested 14 May, 2025 Reviews received at journal 14 May, 2025 Reviews received at journal 30 Apr, 2025 Reviewers agreed at journal 28 Apr, 2025 Reviewers agreed at journal 28 Apr, 2025 Reviewers agreed at journal 28 Apr, 2025 Reviewers agreed at journal 28 Apr, 2025 Reviewers agreed at journal 24 Apr, 2025 Reviewers invited by journal 24 Apr, 2025 Editor assigned by journal 24 Apr, 2025 Submission checks completed at journal 24 Apr, 2025 First submitted to journal 23 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6511055","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":448354771,"identity":"398eef00-120d-4b3d-b7f5-d99bb911f304","order_by":0,"name":"Junsoo Han","email":"data:image/png;base64,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","orcid":"","institution":"CNRS, Sorbonne Université","correspondingAuthor":true,"prefix":"","firstName":"Junsoo","middleName":"","lastName":"Han","suffix":""},{"id":448354772,"identity":"26e19462-ffe6-4d25-be20-deaafb1a68e8","order_by":1,"name":"Kevin Ogle","email":"","orcid":"","institution":"CNRS, Sorbonne Université","correspondingAuthor":false,"prefix":"","firstName":"Kevin","middleName":"","lastName":"Ogle","suffix":""}],"badges":[],"createdAt":"2025-04-23 09:23:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6511055/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6511055/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41529-025-00627-1","type":"published","date":"2025-07-28T16:13:05+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":81538319,"identity":"9f8e39c9-50ff-4ec6-9eec-aed6ccc85846","added_by":"auto","created_at":"2025-04-28 10:39:24","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":178357,"visible":true,"origin":"","legend":"\u003cp\u003eSaturation concentration, C\u003csub\u003eM\u003c/sub\u003e(sat), M = Zn, Al, and Mg, as a function of pH in the presence of 30 mM NaCl in the solution at T = 20 °C. The arrows above indicate the predominant species. Soluble species used are: ZnOH\u003csup\u003e+\u003c/sup\u003e, ZnCl\u003csup\u003e+\u003c/sup\u003e, ZnCl\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e, ZnCl\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2-\u003c/sup\u003e, HZnO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e, ZnHCO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e, Zn(OH)\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e, ZnO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e2-\u003c/sup\u003e, Zn(CO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e2-\u003c/sup\u003e, Zn(OH)\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2-\u003c/sup\u003e; Al(OH)\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e, AlO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e, Al(OH)\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e, Al\u003csup\u003e3+\u003c/sup\u003e; Mg\u003csup\u003e2+\u003c/sup\u003e, MgOH\u003csup\u003e+\u003c/sup\u003e, MgHCO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e, and insoluble species are: ZnO, Zn(OH)\u003csub\u003e2\u003c/sub\u003e, Zn\u003csub\u003e5\u003c/sub\u003e(OH)\u003csub\u003e8\u003c/sub\u003eCl\u003csub\u003e2\u003c/sub\u003e, Al(OH)\u003csub\u003e3\u003c/sub\u003e, AlO(OH), Al\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e, Mg\u003csub\u003e4\u003c/sub\u003eAl\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e7\u003c/sub\u003e·10H\u003csub\u003e2\u003c/sub\u003eO, Mg(OH)\u003csub\u003e2\u003c/sub\u003e. The subscripted “tot” indicates total concentration of the element. Vertical dashed lines indicate the three pH values investigated in this work.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-6511055/v1/2d51b6d34d1e64acb69aec64.png"},{"id":81538320,"identity":"8230bd0a-994b-4a64-a130-1af4ddcd3cbd","added_by":"auto","created_at":"2025-04-28 10:39:24","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":650201,"visible":true,"origin":"","legend":"\u003cp\u003eAESEC-LSV curves of pure metals in Ar deaerated electrolytes at pH = 8.4, 10.1 (with 30 mM NaCl) and pH = 12. 8 (with 0.1 M NaOH). Pure Zn and Mg at pH = 10.1,\u003csup\u003e30\u003c/sup\u003e pure Al at pH = 10,\u003csup\u003e31\u003c/sup\u003e and pure Zn and Al at pH = 12.8\u003csup\u003e33\u003c/sup\u003e were replotted with permission.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-6511055/v1/a392b43320f268e48ba34020.png"},{"id":81538323,"identity":"82647d53-3482-41cb-a80c-3eb96c7cf72e","added_by":"auto","created_at":"2025-04-28 10:39:24","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":626886,"visible":true,"origin":"","legend":"\u003cp\u003eAESEC-LSV curves of pure metals in O\u003csub\u003e2\u003c/sub\u003e saturated electrolytes at pH = 8.4, 10.1 (with 30 mM NaCl) and pH = 12. 8 (with 0.1 M NaOH). Pure Zn and Mg at pH = 10.1,\u003csup\u003e30\u003c/sup\u003e pure Al at pH = 10,\u003csup\u003e31\u003c/sup\u003e and pure Zn and Al at pH = 12.8\u003csup\u003e33\u003c/sup\u003e were replotted with permission.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-6511055/v1/6dae08407a0485ec7f0cdb4d.png"},{"id":81538567,"identity":"db73b02e-396e-4563-bd40-4e25903b3f61","added_by":"auto","created_at":"2025-04-28 10:47:24","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1116943,"visible":true,"origin":"","legend":"\u003cp\u003eAESEC-LSV curves of intermetallic phases in Ar deaerated electrolytes at pH = 8.4, 10.1 (with 30 mM NaCl) and pH = 12. 8 (with 0.1 M NaOH). MgZn\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e30\u003c/sup\u003e and Zn68Al\u003csup\u003e31\u003c/sup\u003e at pH = 10.1, and Zn68Al at pH = 12.8\u003csup\u003e33\u003c/sup\u003e were replotted with permission.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-6511055/v1/f7f8d717db773021811efb92.png"},{"id":81538565,"identity":"a61d5431-182d-4145-a2a9-149f4024c0c8","added_by":"auto","created_at":"2025-04-28 10:47:24","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":224663,"visible":true,"origin":"","legend":"\u003cp\u003eA fixed frequency (\u003cem\u003ef\u003c/em\u003e = 0.0046 Hz) measurement of Zn22Al in 0.1 M NaOH (pH = 12.8), deaerated solution at an applied potential of -1.31 V vs. SCE with a 10 mV\u003csub\u003erms\u003c/sub\u003e sinewave perturbation.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-6511055/v1/a157e124b0fefa16b36f6575.png"},{"id":81538332,"identity":"9919ee91-a965-4586-a45f-2ee3f63591b0","added_by":"auto","created_at":"2025-04-28 10:39:24","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":622412,"visible":true,"origin":"","legend":"\u003cp\u003eAESEC-LSV curves of intermetallic phases in O\u003csub\u003e2\u003c/sub\u003e saturated electrolytes at pH = 8.4, 10.1 (with 30 mM NaCl) and pH = 12. 8 (with 0.1 M NaOH). MgZn\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e30\u003c/sup\u003e and Zn68Al\u003csup\u003e31\u003c/sup\u003e at pH = 10.1, and Zn68Al at pH = 12.8\u003csup\u003e33\u003c/sup\u003e were replotted with permission.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-6511055/v1/9118000e8d183ba90ed55e0b.png"},{"id":81538330,"identity":"80250ee0-46e0-4906-9f4d-620ee7b06d37","added_by":"auto","created_at":"2025-04-28 10:39:24","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":893682,"visible":true,"origin":"","legend":"\u003cp\u003eAESEC-LSV curves of commercial ZnAl and ZnAlMg alloy coatings in Ar deaerated electrolytes at pH = 8.4, 10.1 (with 30 mM NaCl) and pH = 12. 8 (with 0.1 M NaOH).\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-6511055/v1/b11733b8eba4e1c26f624e65.png"},{"id":81539671,"identity":"c31accaf-fc09-48df-9f92-0f559d2ba16e","added_by":"auto","created_at":"2025-04-28 11:03:24","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":251433,"visible":true,"origin":"","legend":"\u003cp\u003eAESEC-LSV curves of commercial ZnAl and ZnAlMg alloy coatings in O\u003csub\u003e2\u003c/sub\u003e saturated electrolytes at pH = 8.4, 10.1 (with 30 mM NaCl) and pH = 12. 8 (with 0.1 M NaOH).\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-6511055/v1/7e21364f646ace0eeb0ad5ae.png"},{"id":81538335,"identity":"73cb5e35-2200-457f-a56b-0bc8c4fb7b61","added_by":"auto","created_at":"2025-04-28 10:39:24","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":331268,"visible":true,"origin":"","legend":"\u003cp\u003eE\u003csub\u003eoc\u003c/sub\u003e values as a function of increasing %Zn in Ar deaerated and O\u003csub\u003e2\u003c/sub\u003e saturated electrolytes at pH = 8.4, 10.1 (with 30 mM NaCl) and 12.8 (with 0.1 M NaOH).\u003c/p\u003e","description":"","filename":"image9.png","url":"https://assets-eu.researchsquare.com/files/rs-6511055/v1/e9df88a9dffc1a01139e230a.png"},{"id":81538333,"identity":"3dc4f900-858d-407d-8250-940c80da37f8","added_by":"auto","created_at":"2025-04-28 10:39:24","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":266206,"visible":true,"origin":"","legend":"\u003cp\u003eSpontaneous elemental dissolution rates at near steady state (j\u003csup\u003es\u003c/sup\u003e\u003csub\u003eM\u003c/sub\u003e) under open circuit conditions in the different pH solutions used in this work. \u003cstrong\u003eLeft\u003c/strong\u003e: pure metals; \u003cstrong\u003eright\u003c/strong\u003e: ZnAlMg alloy (normalized based on molar composition). Only Ar saturated electrolyte cases are shown.\u003c/p\u003e","description":"","filename":"image10.png","url":"https://assets-eu.researchsquare.com/files/rs-6511055/v1/0ae9c2cbaf0047bbe3b7a14e.png"},{"id":81538343,"identity":"cbdde253-b892-464f-8f5a-473606bb7cc5","added_by":"auto","created_at":"2025-04-28 10:39:24","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":111818,"visible":true,"origin":"","legend":"\u003cp\u003eSpontaneous elemental dissolution rates expressed as equivalent current (j\u003csup\u003es\u003c/sup\u003e\u003csub\u003eM\u003c/sub\u003e) in Ar deaerated and O\u003csub\u003e2\u003c/sub\u003e saturated electrolytes. Error bars represent the variability from repeated experiments. \u003cstrong\u003e(m)\u003c/strong\u003e: metals; \u003cstrong\u003e(i)\u003c/strong\u003e: intermetallic phases; \u003cstrong\u003e(a)\u003c/strong\u003e: alloys\u003c/p\u003e","description":"","filename":"image11.png","url":"https://assets-eu.researchsquare.com/files/rs-6511055/v1/a53a6cacfa6c87caa0f77df0.png"},{"id":81538572,"identity":"579120f8-4678-436e-852a-9e0a6a2ae66d","added_by":"auto","created_at":"2025-04-28 10:47:24","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":372557,"visible":true,"origin":"","legend":"\u003cp\u003eThe spontaneous elemental dissolution rates obtained from AESEC-OCP measurements, j\u003csup\u003es\u003c/sup\u003e\u003csub\u003eM\u003c/sub\u003e (AESEC-OCP) compared with elemental dissolution rates extrapolated from AESEC-LSV curves at E\u003csub\u003ej=0\u003c/sub\u003e, j\u003csub\u003eM\u003c/sub\u003e (AESEC-LSV). Data obtained from pure metals, intermetallic phases and commercial alloy coatings in 30 mM NaCl (pH = 8.4 and 10.1) as well as in 0.1 M NaOH (pH = 12.8) solutions are included. All repeated experimental data are also presented.\u003c/p\u003e","description":"","filename":"image12.png","url":"https://assets-eu.researchsquare.com/files/rs-6511055/v1/83d756610af6de8c772631c1.png"},{"id":88268258,"identity":"6e52ebef-6067-4cc0-93ae-b0da1c6eded5","added_by":"auto","created_at":"2025-08-04 16:50:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6939572,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6511055/v1/d2e8a221-85ba-4c0a-82e5-a4749376d14c.pdf"},{"id":81538318,"identity":"9643b156-1e08-4986-aa9b-18714f03b1c2","added_by":"auto","created_at":"2025-04-28 10:39:24","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":42567,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-6511055/v1/8c1e90bf9621594f601ef891.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Element-resolved electrochemical database: AESEC polarization curves of ZnAlMg alloy coating constituents","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSince the 2010s, the materials science community has witnessed a significant paradigm shift in alloy design driven by artificial intelligence (AI) and leveraging data obtained from machine learning (ML). This approach can accelerate the discovery of optimal chemical compositions, reducing the waste of rare resources compared to conventional alloy design methods. Numerical simulations and AI are helping in the selection compositions to be tested experimentally. One major limitation of this approach is the difficulty in obtaining reliable experimental data needed to train ML models for improved predictive accuracy. In terms of data quantity, high-throughput approaches in metallurgy, electrochemistry and CALPHAD (CALculation of PHAse Diagrams) simulations have been employed to supply data for screening all possible material/environment scenarios of interest.\u003csup\u003e1\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e2\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e3\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e4\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFor corrosion-resistant alloy design, datasets used to train ML models have primarily been derived from conventional electrochemical analysis, providing an overview of materials\u0026rsquo; corrosion resistance, often represented by a corrosion rate\u003csup\u003e6\u003c/sup\u003e based on conventional theories.\u003csup\u003e7\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e8\u003c/sup\u003e However, this method often neglects element-specific data, as conventional electrochemical techniques cannot provide \u003cem\u003ein situ\u003c/em\u003e element-resolved information. The absence of element-resolved data as input parameters for ML-based alloy design is a critical limitation as the quality of input data is key to effective ML model training.\u003c/p\u003e \u003cp\u003eAnother example demonstrating the importance of element-resolved data is corrosion modeling using finite element methods (FEM).\u003csup\u003e9\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e10\u003c/sup\u003e For example, corrosion mechanisms on the cut-edge of galvanized steel have been modeled\u003csup\u003e11\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e12\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e13\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e14\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e15\u003c/sup\u003e using global electrochemical data as input for the FEM-based simulation. Cut-edge corrosion refers to the situation where galvanized steel has been cut and both the Zn alloy coating and the steel are exposed on the edge with an unfavorable Zn and steel surface ratios, typically 10 \u0026micro;m Zn / 700 \u0026micro;m Fe. The corrosion rates and mechanisms depend upon the nature of the precipitated corrosion products that are formed from the specific ions released at the anode and usually hydroxide released at the cathode. Attempts to include precipitation in numerical models have proven interesting,\u003csup\u003e14,15\u003c/sup\u003e however, they have been based on global electrochemical data and do not necessarily account for the possibility of selective dissolution. This is particularly significant for multi-phase alloy systems.\u003c/p\u003e \u003cp\u003eIn the present work, pure metals and pure phases consisting of ZnAlMg alloy coatings were analyzed by atomic emission spectroelectrochemistry (AESEC), providing element-resolved electrochemical parameters. The ZnAlMg alloy coating system is chosen because it exhibits a multi-phase structure with complicated chemistry,\u003csup\u003e16\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e17\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e18\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e19\u003c/sup\u003e making it difficult to interpret conventional electrochemical data without element-specific information. The ZnAlMg alloy coating was primarily developed in the automotive industry to enhance corrosion resistance and reduce the total weight of galvanized steel.\u003csup\u003e20\u003c/sup\u003e This alloy has also been used in the marine and offshore industries,\u003csup\u003e21\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e22\u003c/sup\u003e construction materials\u003csup\u003e23\u003c/sup\u003e and as a biodegradable material.\u003csup\u003e24\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e25\u003c/sup\u003e Recent research on ZnAlMg alloy coatings focusing on chemical composition, microstructure, and the formation of surface oxides/hydroxide and their effects on corrosion properties is summarized in \u003cb\u003eTable S1\u003c/b\u003e. This table illustrates the complex nature of this material in terms of its chemical composition, galvanic coupling between phases, and the effect of organic/inorganic coatings, all of which play an important role in estimating corrosion performance in diverse environments. It ultimately highlights the importance of establishing a catalog of element-resolved electrochemical data to better design ZnAlMg-based multi-phase alloys and more accurately predict their corrosion behavior.\u003c/p\u003e \u003cp\u003eThe elemental dissolution mechanism is a key consideration in the corrosion of ZnAlMg alloys. For example, the presence of Zn\u003csup\u003e2+\u003c/sup\u003e released from the galvanized steel alloy coating during cut-edge corrosion is reported to modify the Fe-based oxide resulting in the inhibition of direct oxygen reduction on steel surface. The exchange of Zn\u003csup\u003e2+\u003c/sup\u003e with Fe\u003csup\u003e2+\u003c/sup\u003e donor sites at the surface lowers the oxygen reduction activity, which is further enhanced in the presence of Mg\u003csup\u003e2+\u003c/sup\u003e in the electrolyte.\u003csup\u003e26\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e27\u003c/sup\u003e In the case of the corrosion resistant layered double hydroxide (LDH) film formation mechanism, the metal substrate and thin metallic oxide layer may act as sources of metallic cations that form the LDH.\u003csup\u003e28\u003c/sup\u003e For Zn-Al based LDHs, intermediate species such as Al(OH)\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e and Zn(OH)\u003csup\u003e+\u003c/sup\u003e are considered precursors to LDH formation. However, \u003cem\u003ein situ\u003c/em\u003e measurements of these species to verify the LDH formation mechanism have not been carried out.\u003csup\u003e29\u003c/sup\u003e In other words, if we had direct access to these dissolved species, we might be able to shed light on the existence of these precursors and their underlying formation mechanisms. An element-resolved electrochemical database is therefore necessary to provide high-quality datasets for training ML models to address these issues, taking into account the elemental contributions to the reaction mechanism and ultimately enabling the effective design of corrosion resistance ZnAlMg-based multi-phase alloys.\u003c/p\u003e \u003cp\u003eIn this work, the major anodic reactions of the multi-phase coating alloy were identified based on the relative reactivity of the individual phases and pure metals \u003cem\u003evia\u003c/em\u003e AESEC-linear sweep voltammetry (AESEC-LSV). The spontaneous elemental dissolution rate, which represents the free corrosion rate (or AESEC open circuit potential, AESEC-OCP, measurement), can be predicted by extrapolating AESEC-LSV curves. These findings may contribute to the development of a new approach in ML-based training models for new alloy design by supplying element-resolved electrochemical datasets.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eThermodynamic simulations\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Saturation concentration, C\u003csub\u003eM\u003c/sub\u003e(sat), M\u0026thinsp;=\u0026thinsp;Zn, Al, and Mg, as a function of pH in the presence of 30 mM NaCl in the solution at T\u0026thinsp;=\u0026thinsp;20\u0026deg;C. The arrows above indicate the predominant species. Soluble species used are: ZnOH\u003csup\u003e+\u003c/sup\u003e, ZnCl\u003csup\u003e+\u003c/sup\u003e, ZnCl\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e, ZnCl\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, HZnO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e, ZnHCO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e, Zn(OH)\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e, ZnO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, Zn(CO\u003csub\u003e3\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, Zn(OH)\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e; Al(OH)\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e, AlO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e, Al(OH)\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e, Al\u003csup\u003e3+\u003c/sup\u003e; Mg\u003csup\u003e2+\u003c/sup\u003e, MgOH\u003csup\u003e+\u003c/sup\u003e, MgHCO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e, and insoluble species are: ZnO, Zn(OH)\u003csub\u003e2\u003c/sub\u003e, Zn\u003csub\u003e5\u003c/sub\u003e(OH)\u003csub\u003e8\u003c/sub\u003eCl\u003csub\u003e2\u003c/sub\u003e, Al(OH)\u003csub\u003e3\u003c/sub\u003e, AlO(OH), Al\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e, Mg\u003csub\u003e4\u003c/sub\u003eAl\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e7\u003c/sub\u003e\u0026middot;10H\u003csub\u003e2\u003c/sub\u003eO, Mg(OH)\u003csub\u003e2\u003c/sub\u003e. The subscripted \u0026ldquo;tot\u0026rdquo; indicates total concentration of the element. Vertical dashed lines indicate the three pH values investigated in this work.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAESEC polarization curve of the material - Pure metals\u003c/h3\u003e\n\u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the AESEC-LSV curves for nominally pure Zn, Al and Mg measured at pH\u0026thinsp;=\u0026thinsp;8.4, pH\u0026thinsp;=\u0026thinsp;10.1 with 30 mM NaCl, as well as at pH\u0026thinsp;=\u0026thinsp;12.8 with 0.1 M NaOH (without NaCl). All electrolytes were deaerated with Ar. For pure Zn (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e(a)\u003c/b\u003e, left), an oxidation peak of j\u003csub\u003ee\u003c/sub\u003e near \u0026minus;\u0026thinsp;1.1 V vs. SCE (\u003cem\u003ea\u003c/em\u003e\u003csub\u003e1\u003c/sub\u003e) was observed in the pH\u0026thinsp;=\u0026thinsp;8.4 and 10.1 electrolytes. At this point, a non-faradaic reaction was indicated by the lower Zn dissolution rate (j\u003csub\u003eZn\u003c/sub\u003e) compared to j\u003csub\u003ee\u003c/sub\u003e. The unaccounted charge can be attributed to the formation of less soluble Zn species, such as Zn(OH)\u003csub\u003e2\u003c/sub\u003e. The difference between j\u003csub\u003ee\u003c/sub\u003e and j\u003csub\u003eZn\u003c/sub\u003e is more pronounced at pH\u0026thinsp;=\u0026thinsp;10.1 because the solubility of Zn(OH)\u003csub\u003e2\u003c/sub\u003e is lowest at this pH, as predicted by the thermodynamic simulations shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Faradaic Zn dissolution was observed at potentials above this point in the pH\u0026thinsp;=\u0026thinsp;8.4 and 10.1 electrolytes. At pH\u0026thinsp;=\u0026thinsp;12.8, Zn dissolution was nearly faradaic, \u003cem\u003ei.e.\u003c/em\u003e, j\u003csub\u003eZn\u003c/sub\u003e \u0026asymp; j\u003csub\u003ee\u003c/sub\u003e, above the j\u0026thinsp;=\u0026thinsp;0 potential (E\u003csub\u003ej=0\u003c/sub\u003e) because Zn(OH)\u003csub\u003e2\u003c/sub\u003e is highly soluble at this pH (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003csup\u003e32\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e33\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFor pure Al (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e(a)\u003c/b\u003e, middle), anodic dissolution in the cathodic potential domain for the pH\u0026thinsp;=\u0026thinsp;8.4 and 10.1 electrolytes, -1.8 V vs. SCE\u0026thinsp;\u0026lt;\u0026thinsp;E\u0026thinsp;\u0026lt;\u0026thinsp;E\u003csub\u003ej=0\u003c/sub\u003e, was monitored. In this potential domain, Al dissolution was potential dependent and closely followed the cathodic current. This phenomenon is referred to as the cathodic dissolution of Al\u003csup\u003e31,\u003c/sup\u003e\u003csup\u003e34\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e35\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e36\u003c/sup\u003e and cannot be detected using conventional electrochemical measurements. The dissolved Al species, such as Al(OH)\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e, and the electron stoichiometry follow the ratio described by the following reaction:\u003c/p\u003e \u003cp\u003eAl\u0026thinsp;+\u0026thinsp;4H\u003csub\u003e2\u003c/sub\u003eO\u0026thinsp;+\u0026thinsp;e\u003csup\u003e\u0026minus;\u003c/sup\u003e \u0026loz; Al(OH)\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e + 2H\u003csub\u003e2\u003c/sub\u003e [1]\u003c/p\u003e \u003cp\u003eThis yields a mole ratio of Al : e\u003csup\u003e\u0026minus;\u003c/sup\u003e = 1, or a current density ratio of j\u003csub\u003eAl\u003c/sub\u003e : │j\u003csub\u003ee\u003c/sub\u003e│ = 3 : 1, where j\u003csub\u003eAl\u003c/sub\u003e = z\u003csub\u003eAl\u003c/sub\u003eF\u003cem\u003ev\u003c/em\u003e\u003csub\u003eAl\u003c/sub\u003e. Here, \u003cem\u003ev\u003c/em\u003e\u003csub\u003eAl\u003c/sub\u003e is the elemental dissolution rate of Al in mol cm\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. For both pH\u0026thinsp;=\u0026thinsp;8.4 and 10.1 electrolytes, the observed ratio j\u003csub\u003eAl\u003c/sub\u003e : │j\u003csub\u003ee\u003c/sub\u003e│ was approximately 2.9 : 1 in the cathodic potential domain, confirming the cathodic Al dissolution mechanism (\u003cb\u003eReaction 1\u003c/b\u003e). Unlike pure Zn, insoluble species indicated by j\u003csub\u003ee\u003c/sub\u003e \u0026gt; j\u003csub\u003eAl\u003c/sub\u003e for pure Al at pH\u0026thinsp;=\u0026thinsp;10.1 contradicts the thermodynamic predictions in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e as higher Al solubility is expected at pH\u0026thinsp;=\u0026thinsp;10.1 than at pH\u0026thinsp;=\u0026thinsp;8.4. This discrepancy may be related to the enhanced cathodic reaction at pH\u0026thinsp;=\u0026thinsp;8.4 (evidenced by higher j\u003csub\u003ee\u003c/sub\u003e and a larger cathodic potential domain) which increases the interfacial pH to a value even higher than that of the pH\u0026thinsp;=\u0026thinsp;10.1 solution.\u003c/p\u003e \u003cp\u003eAt pH\u0026thinsp;=\u0026thinsp;12.8, however, Al dissolution was potential independent,\u003csup\u003e33,\u003c/sup\u003e\u003csup\u003e37\u003c/sup\u003e indicating that the dissolution was controlled by the steady state formation and dissolution of an Al(OH)\u003csub\u003e3\u003c/sub\u003e passive film as described by:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eAl\u0026thinsp;+\u0026thinsp;3OH\u003csup\u003e\u0026minus;\u003c/sup\u003e \u0026loz; Al(OH)\u003csub\u003e3\u003c/sub\u003e + 3e\u003csup\u003e\u0026minus;\u003c/sup\u003e [2]\u003c/p\u003e\u003cp\u003eAl(OH)\u003csub\u003e3\u003c/sub\u003e + OH\u003csup\u003e\u0026minus;\u003c/sup\u003e \u0026loz; Al(OH)\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e [3]\u003c/p\u003e\u003cp\u003e3H\u003csub\u003e2\u003c/sub\u003eO\u0026thinsp;+\u0026thinsp;3e\u003csup\u003e\u0026minus;\u003c/sup\u003e \u0026loz; 3OH\u003csup\u003e\u0026minus;\u003c/sup\u003e + 1.5H\u003csub\u003e2\u003c/sub\u003e [4]\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eReactions 2\u003c/b\u003e and \u003cb\u003e3\u003c/b\u003e were in a steady state. There was no correlation between j\u003csub\u003ee\u003c/sub\u003e and j\u003csub\u003eAl\u003c/sub\u003e at pH\u0026thinsp;=\u0026thinsp;12.8, suggesting that Al dissolution was not driven by the electrochemical reaction. This phenomenon has been referred to in the literature as \u0026ldquo;chemical corrosion\u0026rdquo;.\u003csup\u003e38\u003c/sup\u003e In this case, the mass transport of OH\u003csup\u003e\u0026minus;\u003c/sup\u003e in \u003cb\u003eReaction 4\u003c/b\u003e was the rate determining step (RDS). It should be noted that the noise signal of j\u003csub\u003eAl\u003c/sub\u003e was proportional to the quantity of the evolved H\u003csub\u003e2\u003c/sub\u003e gas. The stoichiometry between the dissolved Al species (Al(OH)\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e, \u003cb\u003eReaction 3\u003c/b\u003e) and the evolved H\u003csub\u003e2\u003c/sub\u003e gas (\u003cb\u003eReaction 4\u003c/b\u003e), in a ratio of 1 : 1.5, has been demonstrated using AESEC coupled gravimetric gas measurement.\u003csup\u003e39\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eOne important point to note in the case of AESEC-LSV curves for pure Al is the determination of the \u0026ldquo;true\u0026rdquo; corrosion rate. According to conventional Tafel extrapolation method, the corrosion rate may be estimated as the intersection of the anodic and cathodic Tafel lines extrapolated to E\u003csub\u003ej=0\u003c/sub\u003e. However, this approach may significantly underestimate the true corrosion rate. The true Al dissolution rate at E\u003csub\u003ej=0\u003c/sub\u003e determined using an \u0026ldquo;element-resolved mixed potential theory\u0026rdquo; as indicated by arrows in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, was more than an order of magnitude higher than the rate obtained from conventional method.\u003csup\u003e40\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e41\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e42\u003c/sup\u003e This highlights the critical importance of element-resolved analysis in accurately measuring corrosion rates as well as its value as an input parameter for ML modeling.\u003c/p\u003e \u003cp\u003eMg dissolution (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e(a)\u003c/b\u003e, right) at pH\u0026thinsp;=\u0026thinsp;8.4 and 10.1 occurred in the cathodic potential domain, \u003cem\u003ei.e.\u003c/em\u003e, E\u0026thinsp;\u0026lt;\u0026thinsp;E\u003csub\u003ej=0\u003c/sub\u003e, which again cannot be monitored by conventional electrochemical measurements. Mg dissolution was potential dependent at pH\u0026thinsp;=\u0026thinsp;8.4 and 10.1 within the potential range investigated in this work. In these solutions, Mg dissolution exhibited perturbed j\u003csub\u003eMg\u003c/sub\u003e signals, though not highly prominent on a logarithmic scale, especially at more positive potentials, \u003cem\u003ei.e.\u003c/em\u003e, E \u0026gt; -1.2 V vs. SCE, which can be attributed to the evolution of hydrogen bubbles,\u003csup\u003e43\u003c/sup\u003e often referred to as anomalous anodic hydrogen evolution (AHE). The evolved gas bubbles were visibly present inside the capillary. In these solutions, j\u003csub\u003eMg\u003c/sub\u003e \u0026gt; j\u003csub\u003ee\u003c/sub\u003e was monitored with j\u003csub\u003eMg\u003c/sub\u003e / j\u003csub\u003ee\u003c/sub\u003e = 1.44 (pH\u0026thinsp;=\u0026thinsp;8.4) and j\u003csub\u003eMg\u003c/sub\u003e / j\u003csub\u003ee\u003c/sub\u003e = 1.14 (pH\u0026thinsp;=\u0026thinsp;10.1). This also indicates AHE because the hydrogen evolution current (j\u003csub\u003eH2\u003c/sub\u003e) results from a cathodic reaction, \u003cem\u003ei.e.\u003c/em\u003e, j\u003csub\u003eH2\u003c/sub\u003e \u0026lt; 0, and j\u003csub\u003ee\u003c/sub\u003e = j\u003csub\u003eMg\u003c/sub\u003e + j\u003csub\u003eH2\u003c/sub\u003e, thus yielding j\u003csub\u003eMg\u003c/sub\u003e \u0026gt; j\u003csub\u003ee\u003c/sub\u003e in the case of AHE. At pH\u0026thinsp;=\u0026thinsp;12.8, no Mg dissolution was observed in agreement with the thermodynamic prediction shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The spikes in j\u003csub\u003eMg\u003c/sub\u003e observed under these conditions were due to the detachment of Mg(OH)\u003csub\u003e2\u003c/sub\u003e precipitates as indicated by the upward increase in j\u003csub\u003eMg\u003c/sub\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe same series of experiments was performed for pure metals in electrolytes saturated with O\u003csub\u003e2\u003c/sub\u003e by bubbling directly pure O\u003csub\u003e2\u003c/sub\u003e gas into the solution, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Nearly the same conclusions as in the Ar deaerated solution can be drawn for pure Al and Mg. However, cathodic Zn dissolution was observed in the cathodic potential domain in the presence of O\u003csub\u003e2\u003c/sub\u003e in the solution (39 mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e as measured by an oxygen meter). Notably, this cathodic Zn dissolution was not observed in Ar deaerated electrolyte shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. This is likely due to the enhancement of the interfacial pH by oxygen reduction. The presence of O\u003csub\u003e2\u003c/sub\u003e increased the interfacial OH\u003csup\u003e\u0026minus;\u003c/sup\u003e concentration in the unbuffered solution \u003cem\u003evia\u003c/em\u003e the reaction:\u003c/p\u003e \u003cp\u003eO\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;2H\u003csub\u003e2\u003c/sub\u003eO\u0026thinsp;+\u0026thinsp;4e\u003csup\u003e\u0026minus;\u003c/sup\u003e \u0026loz; 4OH\u003csup\u003e\u0026minus;\u003c/sup\u003e [5]\u003c/p\u003e \u003cp\u003ewhich accelerated the formation of soluble Zn(OH)\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e and/or Zn(OH)\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e species.\u003c/p\u003e\n\u003ch3\u003eAESEC polarization curve of the material - Intermetallic phases\u003c/h3\u003e\n\u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows the AESEC-LSV curves of intermetallic phases obtained in the same electrolyte as in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. For the MgZn\u003csub\u003e2\u003c/sub\u003e intermetallic phase at pH\u0026thinsp;=\u0026thinsp;8.4 and 10.1, the j\u003csub\u003eMg\u003c/sub\u003e value was decreased by a factor of 100 to 1000 compared to that measured for pure Mg (shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In these electrolytes, the onset potential of Zn dissolution, E\u003csub\u003ec\u003c/sub\u003e\u003csup\u003eZn\u003c/sup\u003e, was shifted 30\u0026ndash;100 mV in the more positive direction compared to pure Zn in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Selective Mg dissolution was observed for E\u0026thinsp;\u0026lt;\u0026thinsp;E\u003csub\u003ec\u003c/sub\u003e\u003csup\u003eZn\u003c/sup\u003e leading to the formation of a metallic Zn layer, Zn(0), on the surface.\u003csup\u003e30\u003c/sup\u003e The lower j\u003csub\u003eMg\u003c/sub\u003e for the MgZn\u003csub\u003e2\u003c/sub\u003e phase compared to pure Mg was attributed to the formation of this Zn(0) layer which inhibited further Mg dissolution. Under spontaneous corrosion conditions,\u003csup\u003e30\u003c/sup\u003e significantly reduced Mg and Zn dissolution rates were observed compared to those of the pure metals. Selective Mg dissolution was also observed in spontaneous corrosion, again forming a Mg depleted Zn(0) enriched layer that blocked elemental dissolution. The selective Mg dissolution maintained the potential just below the onset of Zn dissolution. For MgZn\u003csub\u003e2\u003c/sub\u003e in pH\u0026thinsp;=\u0026thinsp;8.4 and 10.1 electrolytes, the onset potential for Mg dissolution was identical within experimental error to that of Zn (E\u003csub\u003ec\u003c/sub\u003e\u003csup\u003eZn\u003c/sup\u003e), indicating simultaneous dissolution of Mg and Zn. For E\u0026thinsp;\u0026gt;\u0026thinsp;E\u003csub\u003ec\u003c/sub\u003e\u003csup\u003eZn\u003c/sup\u003e, Mg and Zn dissolved nearly congruently as indicated by j\u003csub\u003eZn\u003c/sub\u003e / j\u003csub\u003eMg\u003c/sub\u003e \u0026asymp; 2 (with oxidation states of Zn and Mg, z\u003csub\u003eZn\u003c/sub\u003e = z\u003csub\u003eMg\u003c/sub\u003e = 2). The faradaic yield of anodic dissolution (j\u003csub\u003eZn\u003c/sub\u003e + j\u003csub\u003eMg\u003c/sub\u003e) / j\u003csub\u003ee\u003c/sub\u003e \u0026asymp; 1 indicated no significant formation of insoluble species. At pH\u0026thinsp;=\u0026thinsp;12.8, no Mg dissolution was observed similar to pure Mg. Zn oxidized but at a significantly lower rate than pure Zn (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) due to the blocking effect of Mg-based less soluble species formed at this pH.\u003c/p\u003e \u003cp\u003eFor all three Zn-Al intermetallic phases shown at pH\u0026thinsp;=\u0026thinsp;8.4 and 10.1, selective Al dissolution in the cathodic potential domain, \u003cem\u003ei.e.\u003c/em\u003e, cathodic dealloying, was observed. In these electrolytes, Al dissolution in the cathodic potential domain was potential dependent as seen for pure Al in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. This demonstrates that the Zn(0) layer formed by selective Al dissolution in Zn-Al intermetallic phases does not significantly alter the kinetics of cathodic Al dissolution, unlike in the case of MgZn\u003csub\u003e2\u003c/sub\u003e. At pH\u0026thinsp;=\u0026thinsp;8.4 and 10.1, the Al dissolution rate profile in the cathodic potential domain for Zn68Al (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e(d)\u003c/b\u003e) is similar to that of Zn22Al (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e(c)\u003c/b\u003e) even though the latter contains significantly less Al, indicating that cathodic dealloying varies little with Al composition. For Zn68Al, the origin of the oxidation peak (\u003cem\u003ea\u003c/em\u003e\u003csub\u003e2\u003c/sub\u003e) was previously demonstrated to be the oxidation of the Zn(0) layer formed during selective Al dissolution, as confirmed by the AESEC potentiodynamic step experiment.\u003csup\u003e31\u003c/sup\u003e At pH\u0026thinsp;=\u0026thinsp;12.8, potential independent Al dissolution was observed similar to pure Al, indicating that the formation and dissolution of Al(OH)\u003csub\u003e3\u003c/sub\u003e were in a steady state. The onset dissolution of Zn resulted in a decrease in Al dissolution rates, a phenomenon previously referred to as the \u0026ldquo;negative correlation effect (NCE)\u0026rdquo;.\u003csup\u003e33\u003c/sup\u003e This effect was attributed to the dissolution of the Zn(0) enriched layer leading to the precipitation/dissolution of Zn(OH)\u003csub\u003e2\u003c/sub\u003e, which retards Al dissolution. In the passive domain where the Zn dissolution rate decreased and became independent of potential, the Al dissolution rate increased. In this domain, Al dissolution occurred through the passive ZnO layer, as indicated by a significantly reduced perturbation signal of j\u003csub\u003eAl\u003c/sub\u003e compared to that observed in the cathodic potential domain.\u003csup\u003e44\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe NCE can be clearly seen in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e where Zn22Al in a deaerated pH\u0026thinsp;=\u0026thinsp;12.8, 0.1 M NaOH solution underwent a fixed frequency of \u003cem\u003ef\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0046 Hz at an applied potential of -1.31 V vs. SCE (active domain as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The j\u003csub\u003eZn\u003c/sub\u003e oscillation was in-phase with the sinusoidal applied potential while j\u003csub\u003eAl\u003c/sub\u003e was 180\u0026deg; shifted.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e shows the same series of experiments for intermetallic phases in O\u003csub\u003e2\u003c/sub\u003e saturated electrolytes. Note that O\u003csub\u003e2\u003c/sub\u003e saturation did not change the dissolution profile for pure Al (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Significantly lower Mg dissolution in the cathodic potential domain compared to the Ar deaerated electrolyte was observed for the MgZn\u003csub\u003e2\u003c/sub\u003e intermetallic phase at pH\u0026thinsp;=\u0026thinsp;8.4 and 10.1 due to the enhanced formation of Mg-based insoluble species caused by the increased interfacial OH\u003csup\u003e\u0026minus;\u003c/sup\u003e concentration. A slight Mg dissolution peak at E = -1.75 V vs. SCE was monitored for MgZn\u003csub\u003e2\u003c/sub\u003e in the pH\u0026thinsp;=\u0026thinsp;12.8 solution which may be due to the dissolution of Mg-based particles released from insoluble Mg-based insoluble species. Cathodic Zn dissolution was monitored for Zn-Al intermetallic phases similar to pure Zn (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) at this pH. In this case, Al dissolution was again restrained by Zn dissolution, confirming the NCE mechanism.\u003c/p\u003e\n\u003ch3\u003eAESEC polarization curve of the material - Commercial alloy coatings\u003c/h3\u003e\n\u003cp\u003e \u003c/p\u003e \u003cp\u003eCommercial ZnAl (Zn5Al and Zn55Al) and ZnAlMg alloy coatings were investigated to compare them with the results for pure metals and intermetallic phases, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. Selective Al dissolution in the cathodic potential domain, \u003cem\u003ei.e.\u003c/em\u003e, cathodic dealloying, was observed in all three alloys at pH\u0026thinsp;=\u0026thinsp;8.4 and 10.1. The stoichiometry of cathodic dealloying was less evident than that of intermetallic phases because j\u003csub\u003eAl\u003c/sub\u003e : \u003cb\u003e|\u003c/b\u003e j\u003csub\u003ee\u003c/sub\u003e \u003cb\u003e|\u003c/b\u003e \u0026ne; 3 : 1 for the alloy coatings. This demonstrates the effect of microstructure on cathodic reaction kinetics: selective dissolution of Al occurred not across the entire surface but at highly localized Al-rich phases.\u003csup\u003e45\u003c/sup\u003e Therefore, OH\u003csup\u003e\u0026minus;\u003c/sup\u003e did not sufficiently react with Al in multi-phase alloys.\u003c/p\u003e \u003cp\u003eFor ZnAlMg alloy at pH\u0026thinsp;=\u0026thinsp;8.4 and 10.1, Mg also dissolved in the cathodic potential domain and followed an opposite trend to Al: when j\u003csub\u003eAl\u003c/sub\u003e increased, j\u003csub\u003eMg\u003c/sub\u003e decreased, and \u003cem\u003evice versa\u003c/em\u003e. The origin of this opposing dissolution trend of Al and Mg in the cathodic domain remains unclear. One possible explanation is that, at pH\u0026thinsp;=\u0026thinsp;8.4 and 10.1, the Al-rich α-phase Al (\u003cem\u003ei.e.\u003c/em\u003e, Zn68Al) is electrochemically more active than the MgZn\u003csub\u003e2\u003c/sub\u003e phase as evidenced by the more negative E\u003csub\u003eoc\u003c/sub\u003e of the α-phase Al compared to the MgZn\u003csub\u003e2\u003c/sub\u003e intermetallic phase. When a cathodic potential was applied, the α-phase Al selectively dissolved \u003cem\u003evia\u003c/em\u003e the cathodic dealloying mechanism (\u003cb\u003eReaction 1\u003c/b\u003e). This selective Al dissolution may expose the MgZn\u003csub\u003e2\u003c/sub\u003e phase to the electrolyte. As the potential was swept in a more positive direction (-1.6 V\u0026thinsp;\u0026lt;\u0026thinsp;E \u0026lt; -1.2 V vs. SCE) the Mg dissolution rate increased while the selective Al dissolution rate decreased. Both Mg and Al dissolution rates decreased for E\u0026thinsp;\u0026gt;\u0026thinsp;E\u003csub\u003ej=0\u003c/sub\u003e at which Zn became electrochemically active.\u003c/p\u003e \u003cp\u003eThe elemental Tafel slopes determined from j\u003csub\u003eZn\u003c/sub\u003e, b\u003csub\u003ea, jZn\u003c/sub\u003e, are provided in \u003cb\u003eSupplementary Materials, Table S2 - S7\u003c/b\u003e. For the ZnAlMg alloy b\u003csub\u003ea, jZn\u003c/sub\u003e was 55 mV decade\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e at both pH\u0026thinsp;=\u0026thinsp;8.4 (\u003cb\u003eTable S2\u003c/b\u003e) and 10.1 in Ar deaerated electrolytes (\u003cb\u003eTable S4\u003c/b\u003e), similar to that of the η-phase Zn (Zn0.7Al, \u0026asymp; 56 mV decade\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and other η-phase containing alloys, \u003cem\u003ei.e.\u003c/em\u003e, Zn5Al (\u0026asymp;\u0026thinsp;57 mV decade\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and Zn55Al (\u0026asymp;\u0026thinsp;52 mV decade\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) in deaerated electrolytes. For comparison, the b\u003csub\u003ea, jZn\u003c/sub\u003e values for non-η-phase of Zn containing specimens, \u003cem\u003ee.g.\u003c/em\u003e, pure Zn (71\u0026thinsp;~\u0026thinsp;75 mV decade\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), MgZn\u003csub\u003e2\u003c/sub\u003e (20\u0026thinsp;~\u0026thinsp;79 mV decade\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), Zn22Al (39\u0026thinsp;~\u0026thinsp;48 mV decade\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and Zn68Al (27\u0026thinsp;~\u0026thinsp;47 mV decade\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) differ from those of η-phase of Zn containing samples. This demonstrates that the dissolution of Zn occurs at the η-phase of Zn.\u003c/p\u003e \u003cp\u003eThe simultaneous dissolution of Zn and Mg in the ZnAlMg alloy for E\u0026thinsp;\u0026gt;\u0026thinsp;E\u003csub\u003ec\u003c/sub\u003e\u003csup\u003eZn\u003c/sup\u003e at pH\u0026thinsp;=\u0026thinsp;8.4 and 10.1 was attributed to the dissolution of the MgZn\u003csub\u003e2\u003c/sub\u003e intermetallic phase and Zn from the substrate. For E\u0026thinsp;\u0026gt;\u0026thinsp;E\u003csub\u003ec\u003c/sub\u003e\u003csup\u003eZn\u003c/sup\u003e, the NCE was also observed for all ZnAl and ZnAlMg alloy coatings.\u003csup\u003e33\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAt pH\u0026thinsp;=\u0026thinsp;12.8, the effect of microstructure was less pronounced than at the lower pH solutions. For example, Zn55Al (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e) exhibited an AESEC-LSV trend almost identical to that of Zn68Al (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Similarly, Zn5Al and ZnAlMg displayed analogous elemental dissolution trends to each other as well as to Zn0.7Al (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), as a function of the potential sweep. This is primarily due to the highly reactive Al and non-solubility of Mg at pH\u0026thinsp;=\u0026thinsp;12.8 which makes the chemical system predominant in determining the elemental dissolution profile.\u003c/p\u003e \u003cp\u003eThe decrease in j\u003csub\u003eAl\u003c/sub\u003e in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e for O\u003csub\u003e2\u003c/sub\u003e saturated electrolytes was attributed to the enhanced Zn dissolution, particularly in the cathodic potential domain. This phenomenon, as observed in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e for the intermetallic phases, is linked to the NCE.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003ePredicting corrosion: galvanic series of materials\u003c/h3\u003e\n\u003cp\u003eThe galvanic series of materials tested in this work was investigated \u003cem\u003evia\u003c/em\u003e open circuit potential (E\u003csub\u003eoc\u003c/sub\u003e) values in each electrolyte, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e. The E\u003csub\u003eoc\u003c/sub\u003e values averaged over at least 300 s of measurement are provided as a function of Zn content (% Zn) for both Ar deaerated and O\u003csub\u003e2\u003c/sub\u003e saturated electrolytes under three pH conditions. For pH\u0026thinsp;=\u0026thinsp;10.1 and 12.8, E\u003csub\u003eoc\u003c/sub\u003e increased with increasing % Zn because the presence of Al or Mg shifted the potential in a more negative direction. In this pH range, Al selectively dissolved while Zn and Mg formed stable oxides/hydroxides (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This is evidenced by the more positive E\u003csub\u003eoc\u003c/sub\u003e of MgZn\u003csub\u003e2\u003c/sub\u003e which does not contain Al.\u003c/p\u003e \u003cp\u003eAt pH\u0026thinsp;=\u0026thinsp;8.4, no clear relationship between E\u003csub\u003eoc\u003c/sub\u003e and % Zn was observed. At this pH, both Mg and Zn are thermodynamically soluble whereas Al forms a stable oxide/hydroxide (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The effect Mg dissolution shifting E\u003csub\u003eoc\u003c/sub\u003e in a more negative direction may not be as significant as in the higher pH range because Zn dissolution shifted the potential in a more positive direction, potentially counteracting the effect of Mg dissolution.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe spontaneous elemental dissolution rates at near steady state (j\u003csup\u003es\u003c/sup\u003e\u003csub\u003eM\u003c/sub\u003e) under open circuit condition were recorded \u003cem\u003evia\u003c/em\u003e AESEC. The j\u003csup\u003es\u003c/sup\u003e\u003csub\u003eM\u003c/sub\u003e values of pure metals and ZnAlMg alloy coating in three pH electrolytes are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e, while those for other pure metals and intermetallic phases are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e. Note that the j\u003csup\u003es\u003c/sup\u003e\u003csub\u003eM\u003c/sub\u003e of the ZnAlMg alloy coating in Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e was normalized based on its molar composition. The trend of j\u003csup\u003es\u003c/sup\u003e\u003csub\u003eM\u003c/sub\u003e for pure metals reasonably follows that of thermodynamically simulated solubility (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). For example, at pH\u0026thinsp;=\u0026thinsp;10.1 (Ar deaerated), j\u003csup\u003es\u003c/sup\u003e\u003csub\u003eZn\u003c/sub\u003e \u0026lt; j\u003csup\u003es\u003c/sup\u003e\u003csub\u003eAl\u003c/sub\u003e \u0026lt; j\u003csup\u003es\u003c/sup\u003e\u003csub\u003eMg\u003c/sub\u003e, which aligns with thermodynamic predictions of solubility at this pH (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). However, for the ZnAlMg alloy coating, j\u003csup\u003es\u003c/sup\u003e\u003csub\u003eAl\u003c/sub\u003e exhibited the highest value in the Ar deaerated electrolyte at pH\u0026thinsp;=\u0026thinsp;10.1, deviating from thermodynamic predictions. This discrepancy may be explained by the E\u003csub\u003eoc\u003c/sub\u003e values of the specimens shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e: At pH\u0026thinsp;=\u0026thinsp;10.1, the Al-rich α-phase (Zn68Al) is the most electrochemically reactive as evidenced by its more negative E\u003csub\u003eoc\u003c/sub\u003e compared to intermetallic phases, such as Zn0.7Al, Zn22Al, and MgZn\u003csub\u003e2\u003c/sub\u003e. Consequently, the selective dissolution of the Al-rich α-phase would result in higher Al dissolution than predicted by thermodynamic simulations.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003e presents the spontaneous steady state elemental dissolution rates, j\u003csup\u003es\u003c/sup\u003e\u003csub\u003eM\u003c/sub\u003e (AESEC-OCP), vs. the elemental dissolution rates extrapolated from AESEC-LSV curves at E\u003csub\u003ej=0\u003c/sub\u003e, j\u003csub\u003eM\u003c/sub\u003e (AESEC-LSV). A linear relationship between the two measurements is observed, indicating that elemental dissolution rates extrapolated using the \u0026ldquo;element-resolved mixed potential theory\u0026rdquo; from AESEC-LSV curves can be used to estimate spontaneous elemental corrosion rates.\u003csup\u003e46\u003c/sup\u003e In this way, long-term elemental corrosion rates can be simply determined through an AESEC-LSV assessment. The slight discrepancy between the two methods may be attributed to the challenge of defining the corrosion potential, \u003cem\u003ei.e.\u003c/em\u003e, the spontaneous potential (E\u003csub\u003eoc\u003c/sub\u003e), which often differs from E\u003csub\u003ej=0\u003c/sub\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this work, we have demonstrated a variety of different mechanisms and provided a database of electrochemical kinetics for a wide range of ZnAlMg alloys, intermetallic phases, and pure metals. The element-resolved dissolution mechanism depending on solution pH, alloy composition, and applied potential has been elucidated. The AESEC-LSV results of a multi-phase ZnAlMg alloy system can be predicted through a bottom-up analysis starting from pure metals and intermetallic phases. The cathodic dissolution mechanism, the negative correlation effect, and the anomalous hydrogen evolution mechanism were investigated across different pH values and elemental compositions. Elemental Tafel slopes determined from j\u003csub\u003eZn\u003c/sub\u003e, as well as the onset dissolution potential of Zn, which are difficult to determine using conventional electrochemical analysis, are provided and can be used as input parameters to train ML models for predicting element-specific corrosion behavior. We have also demonstrated how to predict the elemental spontaneous dissolution (corrosion) rate using AESEC-LSV measurements. This approach alloys the true corrosion rate to be determined from elemental signals, enabling the development of an unprecedented element-resolved corrosion rate database.\u003c/p\u003e\n\u003cp\u003eConventionally, FEM has been used as a numerical method to simulate electrical, mechanical, and chemical systems using differential equations. FEM-based simulations have been conducted to understand galvanic corrosion\u003csup\u003e47\u003c/sup\u003e at the cut-edge of galvanized steel,\u003csup\u003e13,\u003c/sup\u003e\u003csup\u003e48\u003c/sup\u003e cathodic delamination of paint on Zn,\u003csup\u003e49\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e50\u003c/sup\u003e galvanic corrosion from intermetallic particles in Al-based alloys,\u003csup\u003e51\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e52\u003c/sup\u003e metallic protective coatings,\u003csup\u003e53\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e54\u003c/sup\u003e atmospheric corrosion,\u003csup\u003e55\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e56\u003c/sup\u003e and localized corrosion.\u003csup\u003e57\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e58\u003c/sup\u003e More recently, FEM has also been applied to simulate localized corrosion\u003csup\u003e59\u003c/sup\u003e and the design of additive manufactured alloys.\u003csup\u003e60\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e61\u003c/sup\u003e FEM corrosion models assume idealized corrosion conditions, such as uniform corrosion, constant environmental factors, and the results depend highly on how boundary conditions are defined, which may be difficult to determine accurately. The use of the FEM relies on the validated material data, \u003cem\u003ee.g.\u003c/em\u003e, exchange current density, which may not always be available for all material/environment combinations. To leverage these issues, a ML-based surrogate model has recently been proposed, yielding more robust and reliable FEM simulations,\u003csup\u003e62\u003c/sup\u003e although the necessity of training the model with element-resolved electrochemical data still persists.\u003c/p\u003e\n\u003cp\u003eThe conventional polarization curve has been used to provide input parameters for ML model to design corrosion resistant alloys and predict corrosion rates. However, extracting elemental dissolution rates from the conventional j\u003csub\u003ee\u003c/sub\u003e vs. E curve is challenging. For example, anodic Al dissolution in the cathodic potential domain is completely masked by the intense cathodic current as evidenced by j\u003csub\u003eAl\u003c/sub\u003e (Al)\u0026thinsp;\u0026gt;\u0026thinsp;j\u003csub\u003ee\u003c/sub\u003e (Al) in Figs.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e. Quantifying the potential dependent Al dissolution rate in the cathodic potential domain could be critical for layered double hydroxides (LDHs) conversion coating system using Al-containing alloys where cathodic Al dissolution could serve as a source of Al\u003csup\u003e3+\u003c/sup\u003e to form Zn-Al-based LDHs. This example demonstrates the importance of training ML models that incorporate element-resolved information.\u003c/p\u003e\n\u003cp\u003eAnother complexity in predicting corrosion behavior using the conventional polarization curve is defining a \u0026ldquo;corrosion potential\u0026rdquo;, as briefly introduced in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e11\u003c/span\u003e. Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes E\u003csub\u003eoc\u003c/sub\u003e, E\u003csub\u003ej=0\u003c/sub\u003e, and E\u003csub\u003ec\u003c/sub\u003e\u003csup\u003eZn\u003c/sup\u003e for all systems investigated at pH\u0026thinsp;=\u0026thinsp;10.1 in Ar deaerated and O\u003csub\u003e2\u003c/sub\u003e saturated solutions containing 30 mM NaCl. Results for other electrolyte conditions including the b\u003csub\u003ea, jZn\u003c/sub\u003e and spontaneous elemental dissolution rates (j\u003csup\u003es\u003c/sup\u003e\u003csub\u003eM\u003c/sub\u003e) are provided in the \u003cstrong\u003eTable S2 - S7\u003c/strong\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eE\u003csub\u003eoc\u003c/sub\u003e, E\u003csub\u003ej=0\u003c/sub\u003e, and E\u003csub\u003ecZn\u003c/sub\u003e obtained for each samples at pH\u0026thinsp;=\u0026thinsp;10.1 in 30 mM NaCl, Ar deaerated and O\u003csub\u003e2\u003c/sub\u003e saturated electrolytes.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eV vs. SCE\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eZn\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eAl\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eMg\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eZn0.7Al\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eZn22Al\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eZn68Al\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eMgZn\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eZn5Al\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eZn55Al\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eZnAlMg\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"11\" align=\"left\"\u003e\n\u003cp\u003eAr deaerated\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eE\u003csub\u003eoc\u003c/sub\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.98\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.44\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.96\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.31\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.06\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.07\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eE\u003csub\u003ej=0\u003c/sub\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.41\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.29\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.31\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.31\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eE\u003csub\u003ec\u003c/sub\u003e\u003csup\u003eZn\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.96\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.14\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"11\" align=\"left\"\u003e\n\u003cp\u003eO\u003csub\u003e2\u003c/sub\u003e saturated\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eE\u003csub\u003eoc\u003c/sub\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.93\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.71\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.94\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.93\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.98\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.95\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eE\u003csub\u003ej=0\u003c/sub\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.85\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.58\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.90\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.91\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.87\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.91\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.89\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.90\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eE\u003csub\u003ec\u003c/sub\u003e\u003csup\u003eZn\u003c/sup\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.90\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.01\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.94\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.87\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-1.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.91\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e-0.93\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;In most cases, E\u003csub\u003eoc\u003c/sub\u003e and E\u003csub\u003ej=0\u003c/sub\u003e were different, with the difference ranging from 10 mV to 240 mV in Ar deaerated electrolytes. The E\u003csub\u003eoc\u003c/sub\u003e values did not show a clear relationship with chemical composition or microstructure. It should be noted that corrosion rate measurements are generally performed using separate cathodic and anodic polarization curves starting from E\u003csub\u003eoc\u003c/sub\u003e. Therefore, this difference can be critical in determining the true \u0026ldquo;corrosion potential\u0026rdquo; for predicting corrosion rates. The E\u003csub\u003eoc\u003c/sub\u003e values are currently used to train the ML model; thus, uncertainty in their determination could lead to inaccurate predictions of corrosion rate, even if the dataset is sufficiently large. To improve accuracy, it is necessary to investigate element-resolved electrochemical parameters such as E\u003csub\u003ec\u003c/sub\u003e\u003csup\u003eZn\u003c/sup\u003e and b\u003csub\u003ea, jZn\u003c/sub\u003e, to provide higher-quality, element-specific information to ML models.\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003eIn O\u003csub\u003e2\u003c/sub\u003e saturated electrolytes, this difference was less significant, ranging from 20 mV to 40 mV. The effect of dissolved O\u003csub\u003e2\u003c/sub\u003e on the discrepancy between E\u003csub\u003eoc\u003c/sub\u003e and E\u003csub\u003ej=0\u003c/sub\u003e was evident for pure Zn, but not for pure Al and Mg. This can be attributed to the formation of ZnO or Zn(OH)\u003csub\u003e2\u003c/sub\u003e near E\u003csub\u003ej=0\u003c/sub\u003e, (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, pure Zn at pH\u0026thinsp;=\u0026thinsp;10.1) as evidenced by the non-faradaic dissolution of Zn in this potential range (j\u003csub\u003ee\u003c/sub\u003e \u0026gt; j\u003csub\u003eZn\u003c/sub\u003e), which indicates the formation of less soluble oxide/hydroxide.\u003c/p\u003e\n\u003cp\u003eThe E\u003csub\u003ec\u003c/sub\u003e\u003csup\u003eZn\u003c/sup\u003e values in Ar deaerated electrolyte for all samples were close to -1.10 V vs. SCE, except for MgZn\u003csub\u003e2\u003c/sub\u003e. A 260 mV more positive E\u003csub\u003ec\u003c/sub\u003e\u003csup\u003eZn\u003c/sup\u003e observed for MgZn\u003csub\u003e2\u003c/sub\u003e was attributed to the formation of a Zn(0) layer during the cathodic potential scan caused by selective Mg dissolution. In O\u003csub\u003e2\u003c/sub\u003e saturated electrolyte, the E\u003csub\u003ec\u003c/sub\u003e\u003csup\u003eZn\u003c/sup\u003e values did not show a clear trend, likely due to the interplay with Al (\u003cem\u003ei.e.\u003c/em\u003e, NCE) and Mg.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003eA new approach to element\u0026minus;resolved mixed potential analysis may be obtained using AESEC LSV curves. The electrochemical responses of a multi\u0026minus;phase system could be predicted through a bottom\u0026minus;up analysis starting from pure metals and individual phases.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eAn element\u0026minus;specific electrochemical database, including EcZn, jsM, and ba, jZn for pure metals, intermetallic phases and alloy coatings has been established across a pH range of 8.4 ~ 12.8. This database can be used for corrosion rate prediction more accurately than conventional analysis. The spontaneous elemental dissolution rates obtained from AESEC\u0026minus;OCP show a linear relationship with the elemental dissolution rates obtained from AESEC\u0026minus;LSV across a relatively wide range of pH and different chemical compositions and microstructure. This indicates that elemental corrosion rates can be estimated through a relatively short and simple AESEC\u0026minus;LSV measurement. Providing these element\u0026minus;specific data will enhance the reliability of the ML\u0026minus;based corrosion resistant alloy design approach.\u003c/p\u003e\n\u003c/li\u003e\n\u003cli\u003e\n\u003cp\u003eElement\u0026minus;resolved electrochemistry reveals important corrosion phenomena not detectable in conventional electrochemistry such as cathodic dissolution, chemical dissolution, cathodic dealloying, negative correlation effects, and anomalous hydrogen evolution. These phenomena may be significant in a corrosion process and should be taken into account in the rate equations for numerical modeling.\u003c/p\u003e\n\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eMaterials\u003c/h2\u003e \u003cp\u003eTwo ZnAl and one ZnAlMg commercial alloys were used in this work. The Zn-5 wt.% Al alloy (denoted as Zn5Al) has been reported to have a eutectic structure consisting of a dendritic η-phase of Zn interspersed within the lamella of the Zn-rich Al phase (β-phase of Al).\u003csup\u003e93\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e94\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e95\u003c/sup\u003e The Zn-55 wt.% Al-1.6 wt.% Si alloy (denoted as Zn55Al) is generally composed of a dendritic Al-rich phase (α-phase of Al) and a Zn-rich interdendritic phase.\u003csup\u003e96\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e97\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e98\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e99\u003c/sup\u003e A commercial ZnAlMg alloy exhibiting a microstructure comprising a dendritic η-phase of Zn, a Zn-MgZn\u003csub\u003e2\u003c/sub\u003e binary eutectic, and a Zn-Al-MgZn\u003csub\u003e2\u003c/sub\u003e ternary eutectic phase was used in this work.\u003csup\u003e100\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e101\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e102\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e103\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e104\u003c/sup\u003e Binary phases were obtained from the \u003cem\u003eUniversity of Chemistry and Technology in Prague\u003c/em\u003e. Detailed information on sample preparation and their characterization can be found elsewhere.\u003csup\u003e30,31,33,44\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eAtomic emission spectroelectrochemistry (AESEC)\u003c/h2\u003e \u003cp\u003eThe AESEC technique has been described in detail in our previous publications.\u003csup\u003e105\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e106\u003c/sup\u003e An Ultima 2C\u0026trade; inductively coupled plasma - atomic emission spectrometer (ICP-AES, Horiba France) coupled with an electrochemical measurement system was used. A Gamry Reference 600\u0026trade; potentiostat was used to perform electrochemical tests. A saturated calomel electrode (SCE) was used as the reference electrode in pH\u0026thinsp;=\u0026thinsp;8.4 and 10.1 solutions, while a Hg/HgO electrode in 0.1 M NaOH was used as the reference electrode in the pH\u0026thinsp;=\u0026thinsp;12.8 solution. All potential values presented in this work are referenced to SCE for ease of comparison. A Pt foil was used as the counter electrode. The intensity information of each element at its specific wavelength was converted into elemental concentration using conventional ICP-AES calibration methods. Elemental dissolution rates (\u003cem\u003ev\u003c/em\u003e\u003csub\u003eM\u003c/sub\u003e) were then obtained from the elemental concentrations using an electrolyte flow rate (\u003cem\u003ef\u003c/em\u003e) of 2.8 mL min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e controlled by a peristaltic pump. It is often convenient to present \u003cem\u003ev\u003c/em\u003e\u003csub\u003eM\u003c/sub\u003e as an equivalent elemental current density to facilitate comparison with the electrical current density:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003ej\u003csub\u003eM\u003c/sub\u003e = z\u003csub\u003eM\u003c/sub\u003e F \u003cem\u003ev\u003c/em\u003e\u003csub\u003eM\u003c/sub\u003e [6]\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere z\u003csub\u003eM\u003c/sub\u003e is the valence of the dissolved ion M, and F is the Faraday constant. In this work, z\u003csub\u003eZn\u003c/sub\u003e and z\u003csub\u003eMg\u003c/sub\u003e were taken as 2 and z\u003csub\u003eAl\u003c/sub\u003e was taken as 3 based on thermodynamic prediction shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJH carried out the AESEC experiments and performed analysis. JH and KO conceptualized the AESEC analysis. JH and KO contributed to write the paper and revision. JH and KO read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to express our sincere gratitude to Dr. Jan Stoulil (\u003cem\u003eUniversity of Chemistry and Technology in Prague, Czech Republic\u003c/em\u003e) for supplying intermetallic phase samples. The authors also would like to express their appreciation to the coordinators: Prof. Tomáš Prošek\u0026nbsp;(\u003cem\u003eUniversity of Chemistry and Technology in Prague, Czech Republic\u003c/em\u003e), Dr. Nathalie LeBozec and Dr. Dominique Thierry (\u003cem\u003eInstitut de la Corrosion\u003c/em\u003e) as well as the other partners of the project. This work was partially supported by \u003cem\u003eResearch Fund for Coal and Steel\u003c/em\u003e, grant n°RFSR-CT-2015-00011. This work was also supported by the French government’s “France 2030” initiative through the \u003cem\u003ePEPR-DIADEM\u003c/em\u003e (\u003cem\u003ePriority Research Programs and Equipment - Integrated Devices for Accelerating the Deployment of Emerging Materials\u003c/em\u003e) program, managed by the \u003cem\u003eFrench National Research Agency\u003c/em\u003e (\u003cem\u003eAgence Nationale de la Recherche\u003c/em\u003e, \u003cem\u003eANR\u003c/em\u003e), n°ANR-23-PEXD-0006.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e Sur D., Joress H., Hattrick-Simpers J., \u0026amp; Scully J. R. A high throughput aqueous passivation testing methodology for compositionally complex alloys using a scanning droplet cell, \u003cem\u003eJ. Electrochem. 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On-line inductively coupled plasma-atomic emission spectroelectrochemistry: Real-time element-resolved electrochemistry, \u003cem\u003eCurr. Opi. Electrochem.\u003c/em\u003e \u003cb\u003e41\u003c/b\u003e, 101350 (2023),\u003c/span\u003e \u003cdiv id=\"Par181\" class=\"Para\"\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.coelec.2023.101350\u003c/span\u003e\u003cspan address=\"10.1016/j.coelec.2023.101350\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e \u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"npj-materials-degradation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"npjmatdeg","sideBox":"Learn more about [npj Materials Degradation](http://www.nature.com/npjmatdeg/)","snPcode":"41529","submissionUrl":"https://submission.springernature.com/new-submission/41529/3","title":"npj Materials Degradation","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6511055/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6511055/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAn element-resolved electrochemical database of a ZnAlMg alloy coating is presented, obtained \u003cem\u003evia\u003c/em\u003e atomic emission spectroelectrochemistry (AESEC) linear sweep voltammetry (LSV). Nominally pure Zn, Al and Mg metals as well as MgZn\u003csub\u003e2\u003c/sub\u003e, ZnAl intermetallic phases, and commercial ZnAl alloy coatings were investigated using AESEC-LSV to understand the complex electrochemical response of a multi-phase ZnAlMg alloys. The elemental dissolution rates extrapolated from AESEC-LSV curves showed a linear relationship with spontaneous elemental dissolution rates. This demonstrates the possible use of AESEC-LSV for determining long-term elemental corrosion rates, as well as the use of element-specific electrochemical data as input parameters for more accurate machine learning based corrosion resistant alloy design. Element-resolved electrochemistry reveals important corrosion phenomena not detectable in conventional electrochemistry such as cathodic dissolution, chemical dissolution, cathodic dealloying, negative correlation effects, and anomalous hydrogen evolution. These phenomena may be significant and should be taken into account in the rate equations used for numerical modeling.\u003c/p\u003e","manuscriptTitle":"Element-resolved electrochemical database: AESEC polarization curves of ZnAlMg alloy coating constituents","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-28 10:39:19","doi":"10.21203/rs.3.rs-6511055/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-14T23:11:34+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-14T16:13:54+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-30T10:10:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"47281577972580903162540638254459172807","date":"2025-04-29T02:40:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"338543819734078929350172746532946150137","date":"2025-04-28T15:05:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"74803600900183388056244585783424074478","date":"2025-04-28T13:44:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"216215472343677026128400251940395549943","date":"2025-04-28T05:45:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"166848607345853722676181070391889986523","date":"2025-04-24T10:43:11+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-24T07:23:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-24T06:58:47+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-24T05:12:15+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Materials Degradation","date":"2025-04-23T09:13:36+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-materials-degradation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"npjmatdeg","sideBox":"Learn more about [npj Materials Degradation](http://www.nature.com/npjmatdeg/)","snPcode":"41529","submissionUrl":"https://submission.springernature.com/new-submission/41529/3","title":"npj Materials Degradation","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1cfcb87d-39be-40f8-ad02-99326e52eadb","owner":[],"postedDate":"April 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":47720382,"name":"Physical sciences/Chemistry/Electrochemistry/Corrosion"},{"id":47720383,"name":"Physical sciences/Chemistry/Electrochemistry"}],"tags":[],"updatedAt":"2025-08-04T16:41:14+00:00","versionOfRecord":{"articleIdentity":"rs-6511055","link":"https://doi.org/10.1038/s41529-025-00627-1","journal":{"identity":"npj-materials-degradation","isVorOnly":false,"title":"npj Materials Degradation"},"publishedOn":"2025-07-28 16:13:05","publishedOnDateReadable":"July 28th, 2025"},"versionCreatedAt":"2025-04-28 10:39:19","video":"","vorDoi":"10.1038/s41529-025-00627-1","vorDoiUrl":"https://doi.org/10.1038/s41529-025-00627-1","workflowStages":[]},"version":"v1","identity":"rs-6511055","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6511055","identity":"rs-6511055","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}