Design and preparation method of high zinc-repellent coating on surface of metal workpiece

Abstract

The application discloses a design and preparation method of a high-zinc-repellent coating on a metal piece surface, and the core principle is to calculate adsorption energy and binding energy based on a density functional theory, evaluate the zinc-repellent ability of the coating material and the binding strength of the coating material and a hanger base, and realize design and screening of the zinc-repellent coating material; the steps comprise establishing a coating material library, coating material adaptation, base material adaptation, determination of the coating material and base material combination, and the like. The application can quickly evaluate the zinc-repellent performance of the coating material, and the hanger coating material has high zinc-repellent performance and high binding strength with the hanger base. The method can reduce the time cost and trial and error cost of the design of the zinc-repellent coating material, and reduce the zinc consumption cost caused by the zinc hanging of the hanger in the zinc plating production.

Description

Technical Field

[0001] This invention relates to the technical field of zinc-repellent treatment in hot-dip galvanizing technology, and more particularly to a method for designing and preparing a highly zinc-repellent coating on the surface of metal parts. Background Technology

[0002] Hot-dip galvanizing is currently the mainstream process for corrosion protection of steel and metal parts. Due to its excellent corrosion resistance, controllable cost, and wide applicability, it is widely used in many fields such as power, municipal engineering, steel structures, and construction machinery. In the industrial production of hot-dip galvanizing, metal hangers, tooling fixtures, and other metal parts are needed to complete processes such as workpiece hoisting, zinc immersion, and transfer. However, most existing metal parts are made of ordinary carbon steel or alloy steel, and their surfaces lack a special protective modified coating. In the high-temperature molten zinc environment, they are extremely prone to wetting, adhesion, and metallurgical bonding with the zinc liquid.

[0003] Currently, a common problem in the industry is severe zinc adhesion to metal tooling components. Molten zinc layers continuously adhere and accumulate on the surface of the fixture, significantly increasing zinc raw material consumption and production costs. It also leads to uneven coating thickness, nodules, and protrusions on the tooling surface. Zinc adhesion causes dimensional inaccuracies in metal parts, resulting in unstable workpiece positioning and uneven stress on the plated parts, ultimately affecting the appearance quality and coating uniformity of the finished galvanized product. Furthermore, the adhered zinc layer is difficult to remove naturally, requiring frequent manual grinding, flame burning, and mechanical zinc removal during production. This significantly increases labor and equipment maintenance costs, reduces overall production line efficiency, and repeated zinc removal can cause surface damage, deformation, and cracking of the tooling components, greatly shortening their lifespan and increasing tooling replacement costs.

[0004] Currently, zinc-repellent treatment technologies for hot-dip galvanizing tooling still have many shortcomings. Traditional methods such as spraying protective coatings and simple passivation treatments generally suffer from poor adhesion between the coating and the metal substrate, insufficient high-temperature resistance, and limited zinc-repellent effects. Under long-term corrosion from high-temperature zinc liquid and repeated immersion plating conditions, they are prone to peeling, failure, and aging, failing to achieve long-term stable anti-zinc-sticking effects. Some high-end zinc-repellent coatings have complex preparation processes, high raw material costs, and stringent construction conditions, making them difficult to adapt to large-scale industrial production.

[0005] In summary, there is currently a lack of a simple, high-strength, high-temperature resistant, and zinc-repellent coating preparation scheme for metal parts that is suitable for industrial mass production. This scheme cannot effectively solve the industry pain points of hot-dip galvanizing tooling, such as zinc adhesion, high wear and tear, high maintenance costs, and short service life. Therefore, it is necessary to develop a new design and preparation method for a high zinc-repellent coating on the surface of metal parts to overcome the shortcomings of the existing technology. Summary of the Invention

[0006] The technical problem to be solved by this invention is to prepare a zinc-repellent coating on the surface of galvanized metal hangers to avoid zinc buildup on the hanger surface during galvanizing operations. Specifically, it proposes a design and preparation method for a highly zinc-repellent coating on the surface of metal parts. The advantage of this method is that multiple materials can be simultaneously input into the library and processed one by one.

[0007] To achieve the above-mentioned objectives, the technical solution adopted by the present invention includes steps S1) to S8).

[0008] S1) Establish a library of candidate coating materials; the library of candidate coating materials includes at least one coating material, wherein the coating material is an inorganic non-metallic solid material;

[0009] S2) Coating material compatibility; calculate the adsorption energy E of each coating material with zinc in the candidate coating material library. ads And select specific coating materials accordingly;

[0010] S3) Output and store the calculation results; output the calculation results of step S2) and store them in data table A;

[0011] S4) Establish a library of candidate matrix materials; the library of candidate matrix materials includes at least one matrix material, wherein the matrix material is a metallic material;

[0012] S5) Adaptation of substrate materials; Calculate the bonding energy E between each substrate material in the candidate substrate material library and the specific coating material selected in step S2). b And based on this, a specific matrix material is selected;

[0013] S6) Output and store the calculation results; Output the calculation results of step S5) and store them in data table B;

[0014] S7) Determine the combination of coating material and substrate material; based on the results of data table A and data table B, pair each coating material in data table A with each substrate material in data table B in sequence; determine the final combination of coating material and substrate material;

[0015] S8) Experimentally observe the zinc plating phenomenon; experimentally evaluate the zinc-repellent properties of the above coating material and substrate material combination.

[0016] Preferably, step S2) includes sub-steps S2-1) to S2-5).

[0017] S2-1) Select a coating material;

[0018] S2-2) Construct a bulk atomic model of the coating material. Apply density functional theory to the PBE pseudopotential of the bulk atomic model using the generalized gradient approximation (GGA). Set the plane wave cutoff energy to 600 eV and the self-consistent calculation accuracy to 1.0 × 10⁻⁶ eV. -5Enable spin polarization, set the model calculation accuracy to Accurate, and set the K-point type to Gamma; optimize the total energy of the system's ground state to minimize its energy.

[0019] S2-3) Perform the optimization of the bulk structure atomic model obtained in the previous step. <001> By performing directional sectional processing, a surface structure model of the coating material is obtained. Density functional theory is then applied to calculate the structural energy E of the surface structure model. slab ;

[0020] An adsorption structure model of zinc atoms on the surface of the coating material was established, and the adsorption energy E of the model was calculated using density functional theory. slab+Zn ;

[0021] A model of a single zinc atom was established, and the energy E of a single zinc atom was calculated using density functional theory. Zn ;

[0022] S2-4) Based on the above adsorption energy E slab+Zn Structural energy E slab and the energy E of a single zinc atom Zn Calculate the adsorption energy E between the coating material and zinc. ads The calculation formula is:

[0023] E ads =E slab+Zn -E slab -E Zn

[0024] S2-5) with adsorption energy threshold Q i E represents the adsorption energy E of the coating material and zinc. ads The threshold value is selected as E. ads Q i Specific coating materials.

[0025] Preferably, in step S2-2), the method for constructing the bulk structure atomic model of the coating material is as follows: the original unit cell is built according to fractional coordinates; periodic boundary conditions are used to simulate the macroscopic bulk; and structural relaxation is performed to minimize the system energy and balance the forces on the atoms to obtain a stable atomic model that conforms to the characteristics of a real crystal; the bulk model obtained through optimization is formed by using density functional theory combined with GGA-PBE functional and setting corresponding calculation parameters to complete geometric relaxation optimization.

[0026] Preferably, step S5 includes sub-steps S5-1) to S5-4).

[0027] S5-1) Select a matrix material;

[0028] S5-2) Construct a layered model of the zinc-repellent coating material and the substrate, and calculate the energy E1 of the layered model of the zinc-repellent coating material and the energy E2 of the layered model of the substrate material;

[0029] S5-3) Construct a coating / substrate interface model and optimize it using density functional theory; obtain the coating / substrate interface model energy E. total And the interface area A;

[0030] S5-4) Based on the above-mentioned layered model energy E1 for zinc-repellent coating materials, layered model energy E2 for substrate materials, and coating / substrate interface model energy E... total Given the interfacial area A, calculate the coating / substrate interfacial bonding energy E. b The formula is

[0031] E b =[E total -(E1+E2)] / A

[0032] With the binding energy threshold P i Energy E of the coating / substrate interface model b The threshold value is selected as E. b <P i The matrix material.

[0033] Preferably, in step S5-3), the method for constructing the coating / substrate interface model includes:

[0034] By referencing the defect levels of actual materials, point defects and vacancies are constructed, and the edge lengths of the lattice of the coating and the substrate are adjusted simultaneously to make the lattice size of the model approximately equal to that of the actual material.

[0035] The coating lattice is scaled up and down in a small, uniform manner along the in-plane direction of the interface, so that the lattice sizes of the substrate crystal and the coating crystal are close to each other, thereby reducing the lattice mismatch at the interface, making the lattice sizes close, reducing the lattice mismatch between the substrate and the coating, and reducing the inherent lattice strain and internal stress at the interface.

[0036] Preferably, step S7) of determining the optimal coating material and substrate material includes:

[0037] Each coating material in data table A is paired sequentially with each substrate material in data table B. All paired data are standardized for both positive and negative reasons. The entropy value and difference coefficient of each indicator are calculated, and the objective weight of each indicator is automatically generated. The comprehensive score value of the objective weight × the comprehensive score is sorted, and the optimal combination is selected.

[0038] Preferably, in step S8), the method for experimentally observing the zinc plating phenomenon is as follows:

[0039] The substrate pretreatment involves sandblasting, grinding with 120-2000# sandpaper, and diamond spray polishing to control the surface roughness to Ra 0.1 μm to Ra 0.4 μm; then ultrasonic cleaning with anhydrous ethanol for 15 min is performed to thoroughly remove impurities and oxide layers.

[0040] The coating preparation parameters were as follows: an electric arc coating process was used, with a chamber pressure of 0.2 Pa, a temperature of 500 ℃, and a coating deposition time of 90 min. After completion, the coating was cooled to room temperature in the furnace.

[0041] Performance verification conditions: zinc bath temperature 442 ℃ to 445 ℃, immersion time 10 min; by comparing the zinc layer adhesion state on the sample surface, it was determined that the coating has excellent zinc-repellent effect.

[0042] A method for preparing a high zinc-repellent coating on the surface of a steel hanger, characterized in that, after the target coating material is screened using a design method, it is prepared according to the following steps:

[0043] The pretreatment of the hanger substrate involves sequentially degreasing and oil removal, pickling and rust removal, sandblasting and roughening, and compressed air blowing to obtain a clean and rough active surface.

[0044] The coating slurry is prepared by weighing the powder, binder and additives according to the formula, and then uniformly dispersing them by ball milling or high-speed stirring. After adjusting the viscosity of the slurry, vacuum degassing is performed to obtain the coating slurry.

[0045] Coating application: The slurry is applied to the surface of the hanger substrate by spraying, dipping or brushing, and the total thickness of the wet film is controlled to be 120 μm to 200 μm.

[0046] Drying and sintering: The coated layer is successively processed through three steps: room temperature drying, low temperature pre-baking, and high temperature sintering. After cooling in the furnace, it is taken out and air-cooled to room temperature.

[0047] Coating quality inspection involves testing the appearance, thickness, adhesion, zinc repellency angle, and zinc penetration depth of the prepared coating.

[0048] Closed-loop feedback and iteration: The optimization compares the test results with the design indicators, and returns to the corresponding link for optimization iteration according to the deviation type, until the performance meets the standard or the iteration converges. Attached Figure Description

[0049] Figure 1 This is a flowchart illustrating the method of the present invention;

[0050] Figure 2 This is a schematic diagram of the crystal structure of the alternative zinc-repellent coating material in the embodiment;

[0051] Figure 3 This is a schematic diagram of the surface model of the alternative zinc-repellent coating material in the embodiment;

[0052] Figure 4 This is a schematic diagram of the surface model of different sites on the surface of the alternative coating material in the embodiment, showing the adsorption of zinc.

[0053] Figure 5 This is a schematic diagram of the interface model between the zinc-repellent coating and the substrate in the embodiment;

[0054] Figure 6 A schematic diagram comparing the zinc-repellent effect of coated hangers (A) and uncoated hangers. Detailed Implementation

[0055] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0056] The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein.

[0057] It should be understood that in the various embodiments of the present invention, the sequence number of each process does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0058] It should be understood that in this invention, "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such process, method, product, or device.

[0059] It should be understood that in this invention, "multiple" refers to two or more. "And / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "Contains A, B, and C", "Contains A, B, and C" means that all three A, B, and C are contained; "Contains A, B, or C" means that one of A, B, and C is contained; "Contains A, B, and / or C" means that any one, two, or three of A, B, and C are contained.

[0060] It should be understood that in this invention, "B corresponding to A", "B corresponding to A", "A and B correspond", or "B and A correspond" means that B is associated with A, and B can be determined based on A. Determining B based on A does not mean determining B solely based on A; B can also be determined based on A and / or other information. Matching A and B is defined as a similarity between A and B that is greater than or equal to a preset threshold.

[0061] Depending on the context, "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection."

[0062] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely for illustration and explanation and are not intended to limit the present invention.

[0063] Example 1: A method for designing a high zinc-repellent coating on the surface of a metal part;

[0064] This invention belongs to the technical field of zinc-repellent treatment in hot-dip galvanizing technology, and relates to a method for designing and preparing a highly zinc-repellent coating on the surface of metal parts. The technical problem this invention aims to solve is to prepare a zinc-repellent coating on the surface of ordinary metal galvanizing racks at a lower cost, thereby avoiding zinc buildup on the rack surface during galvanizing operations. This invention can significantly reduce zinc consumption caused by zinc buildup on the rack material while maintaining the structural strength of the metal rack.

[0065] This invention includes the following steps:

[0066] S1: Establish a library of candidate coating materials, selecting three inorganic non-metallic solid materials, A, B, and C, as candidate coating materials to be analyzed. The Materials Visualizer module in Materials Studio software is used to construct a model as follows: Figure 2 Save the atomic models of the bulk structures of the three candidate coating materials A, B, and C as POSCAR configuration files.

[0067] In this embodiment, A is a nitride; specifically, silicon nitride Si3N4.

[0068] In this embodiment, B is a metal oxide; specifically, chromium trioxide (Cr2O3).

[0069] In this embodiment, C is a metal oxide; specifically, titanium dioxide (TiO2).

[0070] S2: Density functional calculations were performed using VASP software to optimize the bulk model structure for materials A, B, and C one by one. The PBE pseudopotential of the generalized gradient approximation GGA was used, the plane wave cutoff energy was set to 600 eV, and the self-consistent calculation accuracy was 1.0 × 10⁻⁶ eV. -5 Enable spin polarization, set the model calculation precision to Accurate, and set the K-point type to Gamma;

[0071] Density functional theory is the most mainstream first-principles calculation method in the fields of materials, chemistry, and physics. Its core is to use electron density to replace complex electron wave functions to solve for the energy and properties of the system.

[0072] Based on the block model obtained from structural optimization calculations, surface structure modeling was performed using the MaterialsVisualizer module in Materials Studio software. This was done for block models of materials A, B, and C. <001> The directional sectional processing has a thickness of no less than 3 atomic layers, and the vacuum layer thickness is 20.0 Å, respectively along... <100> and <010> Expanding the cell by 2 times in the direction yields a surface structure model of the coating material, such as... Figure 3 As shown;

[0073] The atoms mentioned above refer to atomic layers (atomic planes) in a crystal structure, not individual atomic particles. Crystals are stacked along a certain crystallographic direction, with atoms at the same position on the same crystal plane forming an atomic layer; a thickness of at least three atomic layers refers to: along the normal direction of the tangent plane (i.e.,...) <001> (Direction), the cut matrix block portion contains at least 3 consecutive complete atomic layers.

[0074] With the bottom atoms fixed, surface structure optimization was performed using density functional theory calculations in VASP software, with calculation parameters set consistent with step S1, to obtain the surface structure energy E of the coating material. slab ;

[0075] The Materials Visualizer module in Materials Studio software was used to model the contact structure of the selected coating surface / zinc atom. Zinc atoms were placed directly above different positions on the optimized coating material surface structure model, with the initial vertical distance between the zinc atoms and the surface atoms set to 3.5 Å. VASP structure optimization calculations were performed to obtain the adsorption energy E. slab+ZnThe calculation parameter settings are the same as in step S1. This case only calculates two sites above the surface of each material; the method for other sites is the same. The adsorption model settings for different sites are as follows: Figure 4 As shown;

[0076] A model containing only a single zinc atom was established, and density functional theory calculations were performed using VASP software to obtain the energy E of a single zinc atom. Zn ;

[0077] Based on the above adsorption energy E slab+Zn Structural energy E slab and the energy E of a single zinc atom Zn Calculate the adsorption energy E between the coating material and zinc. ads According to the formula:

[0078] E ads = E slab+Zn -E slab -E Zn

[0079] Adsorption energy E of coating material and zinc ads It is a negative value. When the adsorption energy E of the coating material with zinc is negative. ads Greater than Q i It exhibits physical adsorption and zinc-repellent properties; a higher Eads value (closer to 0) indicates a weaker interaction between zinc atoms and the coating, resulting in higher zinc-repellent potential. Screening is based on Eads > Q. i The coating material. Therefore, with E ads Q i Using a threshold value Q, coating materials with zinc-repellent properties are sorted and initially selected. i The value is -0.415 eV. The adsorption energies E of the coating materials A, B, and C for zinc atoms at different sites are shown. ads As shown in Table 1, coating material A exhibits the strongest zinc-repellent ability, coating material C shows a certain tendency for strong physical adsorption, while coating material B leads to significant zinc plating. Therefore, among the three coating materials, material A possesses the best zinc-repellent effect.

[0080] Table 1. Calculation results of adsorption energy for three coating materials

[0081] Alternative materials Adsorption energy (eV) A1 -0.186 A2 -0.097 B1 -7.298 B2 -5.980 C1 -0.469 C2 -0.471

[0082] S3: Output and store the calculation results of the coating material to data table A; the table contains the following: interfacial bonding energy, zinc-repellent properties, coating hardness, bonding stability, material unit price, material mass per unit area, porosity, preparation energy consumption, and difference in thermal expansion coefficient.

[0083] S4: Establish a library of alternative matrix materials and select Fe, 45# steel and 316L stainless steel as matrix materials.

[0084] S5: Using the Materials Visualizer module in Materials Studio software, create the layered model of the initially selected zinc-repellent coating material and the Fe matrix, as well as the coating / matrix interface model.

[0085] Preliminary layer models of the zinc-repellent coating material and 45# steel substrate, as well as the coating / substrate interface model, are shown below. Figure 5 As shown, save it as a POSCAR configuration file;

[0086] Density functional theory calculations using VASP software were performed to obtain the energy E1 for the zinc-repellent coating material, the energy E2 for the Fe matrix layered model, the energy E3 for the 45# steel matrix layered model, and the energy E4 for the 316L stainless steel matrix layered model. Furthermore, the coating / substrate interface model was structurally optimized to obtain the coating / substrate interface model energy E. total And the interface area A.

[0087] Based on the above energy E1 of the zinc-repellent coating material, the energy E2 of the Fe substrate layered model, the energy E3 of the 45# steel substrate layered model, the energy E4 of the 316L stainless steel substrate layered model, and the energy E of the coating / substrate interface model... total Calculate the bonding energy E of a specific coating material using the interface area A. b , formula E b =[E total -(E1+E i )] / A, determine the bonding strength between the coating material and the substrate material of the hanger; i=2,3,4,…,n. E b A more negative value indicates a higher coating-substrate interfacial bonding strength; Eb < P is selected. i (Compared to P) i A more negative matrix material is used to ensure that the interfacial bonding strength meets service requirements; Pi takes values ​​from -5.00 J / m² to -2.00 J / m². The threshold P of the above implementation method... i The value is -3.00 J / m 2 The bonding energy between coating material A and the Fe matrix is ​​-4.75 J / m. 2 The interfacial bonding strength meets the service requirements, therefore it is selected; the bonding energy between coating material A and the 45# steel substrate is -3.15 J / m. 2 The interfacial bonding strength meets the service requirements, therefore it is selected; the bonding energy between coating material A and the 316L stainless steel substrate is -3.65 J / m. 2The interface bonding strength meets the service requirements, so it is selected.

[0088] S6: Output and store the calculation results of the matrix material to data table B; the table contains the interfacial bonding energy, matrix thermal expansion coefficient, surface energy, bonding stability, matrix material unit price, and density.

[0089] S7: The entropy method is used to determine the combination of coating material and substrate material. Specifically, the entropy method involves pairing each coating material in data table A with each substrate material in data table B in turn, and standardizing all paired data positively and negatively. The entropy value and difference coefficient of each indicator are calculated, and the objective weight of each indicator is automatically generated. The comprehensive score value of the objective weight × the comprehensive score is sorted to determine the final combination of coating material and substrate material. The algorithm automatically calculates the weights based on the original data throughout the process, avoiding the bias of human subjective assignment.

[0090] The positive indicators include: interfacial bonding energy, zinc-repellent properties, coating hardness, and bonding stability; the higher the value, the better the overall performance.

[0091] The negative indicators include: material unit price, material mass per unit area, porosity, preparation energy consumption, and difference in thermal expansion coefficient; the smaller the value, the better the overall performance.

[0092] The standardized formula for the positive indicator is: Standardized value of a single item = (Original value of the indicator - Minimum value of the indicator column) ÷ (Maximum value of the indicator column - Minimum value of the indicator column);

[0093] The standardized formula for the negative indicator is: Standardized value of a single item = (maximum value of the indicator column - original value of the indicator) ÷ (maximum value of the indicator column - minimum value of the indicator column).

[0094] The range standardization process refers to performing dimensionless standardization on all nine indicators of the paired samples, mapping the data uniformly to the interval [0, 1], eliminating the influence of dimensions, and obtaining the standardized value Z for all samples. ij ;

[0095] If all sample values ​​of a certain indicator are completely identical, the standardized value is uniformly assigned to 0.

[0096] The entropy value of an indicator is equal to the ratio of negative 1 to the natural logarithm of the number of samples, multiplied by the sum of the products of the indicator's weight and its natural logarithm for all samples under that indicator.

[0097] The coefficient of difference reflects the effective information content of an indicator; the larger the coefficient of difference, the higher the evaluation value of the indicator. Coefficient of difference = 1 - the entropy value of the corresponding indicator.

[0098] Objective weight calculation refers to normalizing the difference coefficients of all indicators to obtain the final objective weight of each indicator, and the sum of all weights is 1. Single indicator weight = Difference coefficient of that indicator ÷ Sum of difference coefficients of all indicators.

[0099] The overall score is calculated as follows: Overall score = ∑(standardized index value × corresponding objective weight). The overall score is calculated for each pairing combination and sorted in descending order. The combination with the highest score is the optimal coating / substrate combination.

[0100] The objective weights of each indicator were calculated using entropy weighting: interfacial bonding energy 0.221, zinc phloem 0.243, coating hardness 0.082, bonding stability 0.145, material unit price 0.110, material mass per unit area 0.046, porosity 0.051, preparation energy consumption 0.032, and difference in thermal expansion coefficient 0.070; the sum of all weights equals 1.

[0101] The standardized scores and composite scores of the three paired combinations are shown in the table below.

[0102]

[0103] The comprehensive scores were sorted in descending order: A-Fe (0.927) > A-45# steel (0.834) > A-316L stainless steel (0.761). The comprehensive evaluation results show that the A-Fe substrate pairing of the coating material achieved the highest comprehensive score, making it the optimal coating-substrate material combination selected by the entropy weight method. This optimal combination was subsequently used in Experiment S8 to verify the zinc-repellent properties.

[0104] The fractional coordinates are a set of coordinates used in crystallography to describe the relative positions of atoms within a unit cell.

[0105] The periodic boundary condition (PBC) simulates a macroscopic bulk crystal, which in reality is an infinitely extending macroscopic bulk crystal, but the simulation can only capture a finite-sized unit cell / supercell. Enabling the periodic boundary condition allows the program to infinitely translate and replicate this finite box in three-dimensional space, with the left, right, front, back, and top / bottom boundaries of the box interconnected. Atoms / electrons / wave functions exiting from one side of the box immediately enter from the other side, perfectly replicating the long-range periodicity of the crystal. Its function is to eliminate surface and interface effects caused by the finite size, allowing the small-sized simulation system to equivalently represent a surfaceless macroscopic bulk crystal.

[0106] Structural relaxation, also known as geometric relaxation or ionic relaxation, involves fixing or unfixing the unit cell parameters, allowing all atoms in the system to move autonomously under forces, continuously adjusting the atomic arrangement. Essentially, the initial atomic model is mostly an ideal geometric position, not a real stable structure; relaxation allows the atoms to "find a comfortable position," approximating the real crystal configuration.

[0107] The lowest energy of the system refers to the atomic arrangement reaching the minimum total energy of the entire system. Moving any atom will increase the total energy, and the system is thermodynamically most stable.

[0108] Atom force balance means that the net force on each atom from the surrounding atoms approaches zero, and there is no longer a net force driving the atom to continue moving; when both conditions are met, it means that the model has achieved mechanical and thermodynamic stability, consistent with the state of a real crystal.

[0109] The electronic self-consistency (SCF) is a process of solving for the electronic wave function, charge density, and total energy of the system: the program iterates repeatedly until the difference between the energy / charge density of two iterations is less than a set value, at which point the electronic structure calculation is considered to have converged. This criterion is the electronic self-consistency convergence criterion.

[0110] S8: Prepare the selected coating material on the surface of the hanger and test the zinc-repellent properties of the coating:

[0111] Remove the oxide layer from the surface of the galvanized hanger using a sandblasting machine, grind the surface with 120-2000# sandpaper, polish the surface with 1 µm diamond polishing spray to a polishing precision of Ra 0.1 µm to 0.4 µm, and ultrasonically clean with anhydrous ethanol for 15 min.

[0112] The target material of coating material A is installed in the arc ignition area of ​​the arc coating equipment. The cleaned fixture to be coated is placed in the cathode area of ​​the arc coating equipment. The working pressure is 0.2 Pa, the cavity temperature is 500 ℃, and the coating deposition time is 90 min. After the coating deposition is completed, the furnace is cooled to room temperature.

[0113] Zinc plating experiments were conducted on metal hangers with coating A and uncoated steel hangers. The hangers were immersed in molten zinc at a temperature controlled between 442 ℃ and 445 ℃. After 10 minutes of zinc plating, the hangers were removed from the zinc bath. The zinc-repellent effect of the coated hangers was as follows: Figure 6 As shown: the gold hook on the left is the hanger with coating A, and the gray-black hook on the right is the hanger without coating. The bent part is the part of the hanger immersed in the zinc liquid. The comparison results show that the coated hanger has almost no zinc layer adhering to its surface, while the uncoated hanger has a significant zinc adsorption phenomenon. Therefore, the hanger coating material A selected by the method of this patent has a significant zinc-repellent effect.

[0114] Example 2: A method for preparing a high zinc-repellent coating on the surface of a metal part;

[0115] Matrix material and pretreatment:

[0116] Hot-rolled 45# steel was selected as the base material for the hanger, and it was processed into sheet-shaped samples of 30 mm × 20 mm × 3 mm. The following pretreatment steps were performed sequentially:

[0117] Degreasing and oil removal: Immerse the sample in a 10 wt% NaOH aqueous solution at 60 ℃, clean it with ultrasonic assistance for 10 min, and then rinse it with deionized water until neutral.

[0118] Pickling for rust removal: Immerse the degreased sample in a 15 vol% hydrochloric acid aqueous solution (with 0.5 wt% hexamethylenetetramine added as a corrosion inhibitor), pickle at room temperature for 8 min, remove and rinse with deionized water and blow dry.

[0119] Sandblasting roughening: Use 60# brown corundum abrasive, sandblasting pressure 0.5 MPa, sandblasting distance 150 mm, sandblasting angle 75°, and process until the surface has a uniform grayish-white rough appearance.

[0120] Compressed air cleaning: The sample surface is swept with 0.6 MPa dry compressed air to remove floating dust and residual abrasive particles.

[0121] Fine polishing: The surface was polished step by step using 120#, 400#, 800#, 1200# and 2000# metallographic sandpaper. Then, mechanical polishing was performed on the polishing cloth using 2.5 μm diamond spray polishing agent. The final surface roughness Ra was measured to be 0.23 μm (using a stylus roughness meter, with a sampling length of 0.8 mm and an evaluation length of 4 mm).

[0122] Ultrasonic cleaning: Place the polished sample in anhydrous ethanol and ultrasonically clean for 15 min (power 200 W, frequency 40 kHz). After cleaning, dry it in an oven at 60 ℃ for 30 min and store it in a desiccator for later use.

[0123] Coating paste preparation:

[0124] Powder composition (by weight):

[0125] The total mass of the mixed powder is 100 g.

[0126]

[0127] Binder: Aqueous aluminum dihydrogen phosphate (Al(H2PO4)3 mass fraction 45%, density 1.45 g / cm³) is used, and the amount added is 35 wt% of the total mass of the powder.

[0128] Additives:

[0129] Polyethylene glycol (PEG-400, dispersant): 1.0 wt% of the total powder mass;

[0130] Polydimethylsiloxane (defoamer): 0.3 wt% of total powder mass;

[0131] Deionized water (diluent): 12 wt% of the total powder mass.

[0132] Preparation process: Weigh each powder according to the formula and place it in a zirconia ball mill jar. Add zirconia grinding balls (ball-to-powder mass ratio 2:1) and dry mix for 30 min (300 r / min). Then add aluminum dihydrogen phosphate binder, PEG-400 dispersant, and deionized water, and disperse by ball milling at 400 r / min for 4 h. After discharge, add defoamer and defoam in a vacuum degassing machine at -0.095 MPa for 15 min. Let stand and age for 2 h to obtain a uniform and stable coating slurry (viscosity controlled at 800–1200 mPa·s, measured by rotational viscometer at 25 ℃).

[0133] Coating application:

[0134] Air spraying was employed. The spray gun model was W-101, with a nozzle diameter of 1.0 mm, a spray pressure of 0.4 MPa, a spray distance of 200 mm, and a spray angle maintained at 90° vertically. A multi-coat, thin-layer spraying process was used: each coat was allowed to level at room temperature for 1 minute, for a total of 4 coats. The coating amount for each coat was approximately 0.12 g / cm², and the total wet film thickness was controlled at 150 ± 10 μm (measured in real-time using a wet film thickness gauge). The spraying operation was carried out in a constant temperature and humidity chamber (temperature 25 ± 2 ℃, relative humidity 45 ± 5%).

[0135] Drying and sintering:

[0136] The coated samples then undergo the following heat treatment processes in sequence:

[0137]

[0138] Furnace cooling: After sintering, the heating power is cut off, and the sample is allowed to cool naturally in the furnace to ≤ 100 ℃ (about 4 hours). After removal, it is placed in a desiccator to air cool to room temperature.

[0139] Coating quality inspection:

[0140]

[0141] Preparation of arc coating; the TiAl arc coating is only used as a comparative sample and is not the target coating of this invention.

[0142] Arc coating process parameters according to the claims:

[0143] Equipment: DML-V03 multi-arc ion plating machine;

[0144] Parameter settings: Target material: TiAl (atomic ratio 50:50); Chamber pressure: 0.2 Pa (high-purity Ar atmosphere); Substrate temperature: 500 ℃ (thermocouple temperature control); Arc current: 80 A; Bias voltage: –200 V; Deposition time: 90 min; Target-substrate distance: 250 mm.

[0145] After deposition, the material is cooled to ≤ 80 ℃ in the furnace (approximately 3 h), then removed and placed in a desiccator.

[0146] Coating thickness: 42±4 μm as measured by a profilometer;

[0147] Zinc-repellent performance verification, experimental conditions: Zinc bath: pure zinc ingots (Zn ≥ 99.995 wt%), melted in a graphite crucible; Zinc bath temperature: 443 ± 1 ℃ (K-type thermocouple temperature control, temperature control accuracy ± 1 ℃); Immersion time: 10 min; Immersion / removal speed: 20 mm / s; Oxide slag on the zinc bath surface: removed with a graphite scraper before immersion.

[0148] Sample grouping:

[0149]

[0150] Results observation and characterization:

[0151] Group A (blank control): After immersion plating, the sample surface was completely covered by molten zinc, forming a continuous zinc layer with a visible metallic luster. Upon removal, obvious zinc droplets were observed. Cross-sectional SEM observation showed a zinc layer thickness of approximately 80–120 μm, with a distinct Fe–Zn diffusion layer (approximately 15–25 μm) at the interface with the steel substrate, indicating a significant reaction between the molten zinc and the substrate.

[0152] Group B (Arc-coated TiAl): After immersion coating, most of the sample surface was covered by molten zinc, with scattered unwetted patches in some areas. Cross-sectional SEM showed a zinc layer thickness of 30–60 μm, with localized Fe–Zn diffusion at the substrate / coating interface (5–12 μm), and localized microcracks in the coating. The zinc-repellent effect was limited.

[0153] Group C (Al2O3–ZrO2 ceramic coating of this invention): Immediately after immersion coating, the zinc liquid rapidly slid off the surface of the sample upon removal from the zinc bath. After removal, there was virtually no zinc liquid adhering to the surface, with only a small amount of zinc residue at the edge where the sample was held. Cross-sectional SEM observation (×500–×2000):

[0154] No continuous zinc layer was observed on the sample surface; isolated zinc particles (diameter < 10 μm) were only found in local depressions; the ceramic coating structure was intact, without cracks or peeling; the coating / substrate interface was clear, and no Fe–Zn diffusion layer was formed (no cross-diffusion of Fe and Zn elements was observed at the interface in the EDS line scan).

[0155] Zinc-repellent angle measurement: The contact angle of molten zinc on the coating surface of the C group sample was measured at 443 ℃ using the high-temperature drop method. The result was 142° ± 3°, which is much higher than that of the A group (about 28° ± 5°) and the B group (about 67° ± 8°), indicating that the coating has excellent high-temperature zinc-repellent properties.

[0156] Zinc penetration depth detection: The C group samples after immersion plating were cut along the cross section, mounted and polished, and observed in SEM-BSE mode. The Zn element surface was scanned on the substrate side using EDS. No zinc element penetration signal was detected (detection limit ≥ 0.1wt%), and the zinc penetration depth was 0.

[0157] This embodiment uses 45# steel as the substrate and prepares a highly zinc-repellent coating using an Al2O3–ZrO2 composite ceramic slurry via a spray-sintering process. Verification was performed by immersion plating in molten zinc (443 ℃, 10 min). The zinc completely slids off without residue, the zinc contact angle reaches 142°, the zinc penetration depth is 0, and the coating structure remains intact, exhibiting excellent zinc-repellent and anti-adhesion effects. This preparation process is simple to operate, cost-controllable, and suitable for large-scale surface protection treatment of steel hangers.

Claims

1. A method for designing a high zinc-repellent coating on the surface of a metal part, characterized in that, Including steps S1) to S8). S1) Establish a library of candidate coating materials; the library of candidate coating materials includes at least one coating material, wherein the coating material is an inorganic non-metallic solid material; S2) Adaptation of coating materials; Calculate the adsorption energy E of zinc for each coating material in the candidate coating material library. ads And select specific coating materials accordingly; S3) Output and store the calculation results; output the calculation results of step S2) and store them in data table A; S4) Establish a library of candidate matrix materials; the library of candidate matrix materials includes at least one matrix material, wherein the matrix material is a metallic material; S5) Adaptation of matrix materials; Calculate the bonding energy E between each substrate material in the candidate substrate material library and the specific coating material selected in step S2). b ; and select specific matrix materials accordingly; S6) Output and store the calculation results; Output the calculation results of step S5) and store them in data table B; S7) Use the entropy method to determine the combination of coating material and substrate material; according to the results of data table A and data table B, pair each coating material in data table A with each substrate material in data table B in turn; Determine the final combination of coating and substrate materials; S8) Experimentally observe the zinc plating phenomenon; evaluate the zinc-repellent properties of the above coating material and substrate material combination.

2. The method for designing a zinc-repellent coating on the surface of a metal part according to claim 1, characterized in that, The metal component is a hot-dip galvanized hanger, and step S2) includes sub-steps S2-1) to S2-5). S2-1) Select a coating material; S2-2) Construct a bulk atomic model of the coating material and optimize the model structure with the goal of minimizing the total ground state energy of the model structure system; S2-3) Perform the optimization of the bulk structure atomic model obtained in the previous step. <001> By processing the directional tangent, a surface structure model of the coating material is obtained. Density functional theory is then applied to calculate the structural energy E of the surface structure model of the coating material. slab ; An adsorption structure model of zinc atoms on the surface of the coating material was established, and the adsorption energy E of the model was calculated using density functional theory. slab+Zn ; A model of a single zinc atom was established, and the energy E of a single zinc atom was calculated using density functional theory. Zn ; S2-4) Based on the above adsorption energy E slab+Zn Structural energy E slab and the energy E of a single zinc atom Zn Calculate the adsorption energy E between the coating material and zinc. ads The calculation formula is: AND ads =E slab+Zn -AND slab -AND Zn S2-5) with adsorption energy threshold Q i E represents the adsorption energy E of the coating material and zinc. ads The threshold value is selected as E. ads Q i Specific coating materials.

3. The method for designing a zinc-repellent coating on the surface of a metal part according to claim 2, characterized in that: In step S2-2), the method for constructing the bulk structure atomic model of the coating material is as follows: the original unit cell is built according to fractional coordinates; periodic boundary conditions are used to simulate the macroscopic bulk; and then structural relaxation is performed to minimize the system energy and balance the forces on the atoms, thus obtaining a stable atomic model that conforms to the characteristics of a real crystal.

4. The method for designing a zinc-repellent coating on the surface of a metal part according to claim 1, characterized in that, Step S5) Adaptation of the matrix material includes sub-steps S5-1) to S5-4). S5-1) Select a matrix material; S5-2) Construct a layered model of the zinc-repellent coating material and the substrate, and calculate the energy E1 of the layered model of the zinc-repellent coating material and the energy E2 of the layered model of the substrate material; S5-3) Construct a coating / substrate interface model and optimize it using density functional theory; obtain the coating / substrate interface model energy E. total And the interface area A; S5-4) Based on the above-mentioned layered model energy E1 for zinc-repellent coating materials, layered model energy E2 for substrate materials, and coating / substrate interface model energy E... total Given the interfacial area A, calculate the coating / substrate interfacial bonding energy E. b The formula is THE b =[E total -(E1+E2)] / A; With binding energy threshold P i Energy E of the coating / substrate interface model b The threshold value is selected as E. b < P i The matrix material.

5. The method for designing a zinc-repellent coating on the surface of a metal part according to claim 4, characterized in that, In step S5-3), the method for constructing the coating / substrate interface model is as follows: By referencing the defect levels of actual materials, point defects and vacancies are constructed, and the edge lengths of the lattice of the coating and the substrate are adjusted simultaneously to make the lattice size of the model approximately equal to that of the actual material.

6. The method for designing a zinc-repellent coating on the surface of a metal part according to claim 1, characterized in that, In step S7), the entropy method specifically refers to: Each coating material in data table A is paired with each substrate material in data table B in turn. Positive and negative index standardization is performed on all paired data. The entropy value and difference coefficient of each index are calculated, and the objective weight of each index is automatically generated. The results of the objective weights multiplied by the comprehensive score are sorted, and the optimal combination is selected.

7. The method for designing a zinc-repellent coating on the surface of a metal part according to claim 1, characterized in that, In step S8), the method for experimentally observing the zinc plating phenomenon is as follows: The substrate pretreatment involves sandblasting, grinding with 120-2000# sandpaper, and diamond spray polishing to control the surface roughness to Ra 0.1 μm to Ra 0.4 μm; then ultrasonic cleaning with anhydrous ethanol for 15 min is performed to thoroughly remove impurities and oxide layers. The coating preparation parameters were as follows: an electric arc coating process was used, with a chamber pressure of 0.2 Pa, a temperature of 500 ℃, and a coating deposition time of 90 min. After completion, the coating was cooled to room temperature in the furnace. Performance verification conditions: zinc bath temperature 442 ℃ to 445 ℃, immersion time 10 min; by comparing the zinc layer adhesion state on the sample surface, it was determined that the coating has excellent zinc-repellent effect.

8. The method for designing a zinc-repellent coating on the surface of a metal part according to claim 2, characterized in that: The adsorption energy threshold Q i The range is from -0.6 eV to -0.1 eV.

9. The method for designing a zinc-repellent coating on the surface of a metal part according to claim 4, characterized in that: The binding energy threshold P i The range is -5.00 J / m 2 Up to -2.00 J / m 2 .

10. A method for preparing a high zinc-repellent coating on the surface of a steel hanger, used to implement the zinc-repellent coating design method for the surface of a metal part as described in any one of claims 1 to 9, characterized in that, The metal component is a hot-dip galvanized hanger, and the process includes the following steps: Pretreatment of the mounting bracket substrate: The steel mounting bracket substrate is subjected to degreasing, pickling and rust removal, sandblasting and roughening and compressed air blowing to obtain a clean and rough active surface; Coating slurry preparation: Weigh each component powder, binder and additives according to the formula, and achieve uniform dispersion by ball milling or high-speed stirring. After adjusting the viscosity of the slurry, degas it under vacuum to obtain the coating slurry. Coating application; The slurry is applied to the surface of the hanger substrate by spraying, dipping, or brushing, and the total thickness of the wet film is controlled to be between 120 μm and 200 μm. Drying and sintering: The coated layer is successively processed through three steps: room temperature drying, low temperature pre-baking, and high temperature sintering. After cooling in the furnace, it is taken out and air-cooled to room temperature. Coating quality inspection; the appearance, thickness, adhesion, zinc repellency angle, and zinc penetration depth of the prepared coating are tested. Closed-loop feedback and iterative optimization: The test results are compared with the design indicators, and the corresponding links are returned for optimization and iteration according to the type of deviation, until the performance meets the standard or the iteration converges.

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