Test Method and System for Anti-icing Performance of Superhydrophobic Surface Structures in Energy Equipment

Abstract

This invention discloses a method and system for testing the anti-icing performance of superhydrophobic surface structures in energy equipment, belonging to the field of materials physical performance testing. The method includes: preparing a working electrode pattern on a superhydrophobic surface specimen and establishing a physical connection circuit; implementing cooling control and activating a spray to form an ice layer, applying AC potential perturbation and calculating a complex impedance data sequence; performing iterative fitting on the complex impedance data sequence to extract the characteristic values ​​of double-layer capacitance and charge transfer resistance; driving a centrifugal rotary table to perform uniformly accelerated rotation to capture the critical speed and ice-covered area for ice layer peeling; acquiring three-dimensional point cloud data to calculate structural damage characteristic values ​​and establishing a multi-dimensional coupled attenuation model. This invention employs a technical solution combining online monitoring by electrochemical impedance spectroscopy, centrifugal mechanical peeling, and laser confocal microscopy morphological characterization, enabling multi-dimensional, dynamic, and quantitative coupled analysis of the anti-icing performance of superhydrophobic surfaces from the microscopic interface to macroscopic mechanics.

Description

Technical Field

[0001] This invention relates to the field of material physical property testing, and in particular to a method and system for testing the anti-icing performance of superhydrophobic surface structures of energy equipment. Background Technology

[0002] Energy equipment, such as wind turbine blades, power transmission cables, and photovoltaic modules, are highly susceptible to icing when operating in polar regions, high mountains, or in low-temperature and high-humidity winter environments. This can lead to reduced equipment efficiency, mechanical failures, and even safety accidents. To address this issue, superhydrophobic surface structures, due to their excellent hydrophobicity and ability to delay icing, are widely used in the anti-icing and de-icing of energy equipment. Accurate testing and evaluation of the anti-icing performance and stability under complex operating conditions are crucial steps in guiding surface structure design and engineering applications during the research and application of superhydrophobic surfaces.

[0003] In related technologies, Chinese invention patent application CN120992418A discloses a method, device, equipment, and storage medium for testing the anti-icing properties of superhydrophobic surface structures of energy equipment. This method extracts key environmental factors from an environmental condition matrix constructed based on environmental feature maps, designs a superhydrophobic surface structure based on these factors to obtain a set of structural parameters, simulates the superhydrophobic surface structure using the environmental load conditions determined by the environmental condition matrix and the set of structural parameters to obtain the critical vibration frequency of the equipment, determines the current surface morphology based on the set of structural parameters and the critical vibration frequency of the equipment, determines the morphology simulation error based on the current surface morphology and the actual surface morphology of the superhydrophobic surface structure, and monitors the superhydrophobic surface structure based on the morphology simulation error, the set of structural parameters, the critical vibration frequency of the equipment, and a preset control mechanical excitation frequency to obtain the ice growth rate and ice adhesion work.

[0004] Regarding the aforementioned technologies, this method primarily relies on environmental feature mapping and multiphysics numerical simulation to extrapolate anti-icing performance. Essentially, it's a virtual testing method based on theoretical models and ideal operating conditions. However, in actual service, superhydrophobic surface structures often face repeated freeze-thaw cycles and mechanical de-icing operations, leading to physical damage and evolution of their microstructure. Furthermore, the interfacial wetting state between the ice layer and the substrate exhibits highly dynamic time-varying characteristics. Simulation-based testing methods struggle to accurately reflect the structural degradation of physical surfaces under long-term cyclic loading and the complex interfacial phase transition processes. This results in discrepancies between the test results and the long-term anti-icing failure behavior under actual operating conditions, making it difficult to meet the reliability assessment requirements for engineering applications. Summary of the Invention

[0005] To address the aforementioned issues, this invention provides a method and system for testing the anti-icing performance of superhydrophobic surface structures in energy equipment. The method combines online monitoring using electrochemical impedance spectroscopy, mechanical exfoliation by centrifugation, and morphological characterization using laser confocal microscopy. This approach enables multi-dimensional, dynamic, and quantitative coupled analysis of the anti-icing performance of superhydrophobic surfaces, from the microscopic interface to the macroscopic mechanics.

[0006] The above objectives can be achieved through the following approach:

[0007] A method for testing the anti-icing performance of superhydrophobic surface structures for energy equipment includes: preparing a working electrode pattern on a superhydrophobic surface specimen using a conductive material deposition process; establishing a physical connection circuit and connecting it to an electrochemical workstation; reading hardware frequency response boundary data based on the electrochemical workstation; performing logarithmic interpolation to generate an impedance spectral scanning frequency point sequence list; installing the superhydrophobic surface specimen in a cryogenic environment chamber sample holder; setting the cooling rate and target freezing temperature; driving the cryogenic environment chamber sample holder to perform cooling control and activate spray to form an ice layer; sequentially applying AC potential perturbations according to the impedance spectral scanning frequency point sequence list; collecting potential and current responses to calculate a complex impedance data sequence; and processing the complex impedance data sequence... Iterative fitting is performed to construct an equivalent circuit topology. Based on the equivalent circuit topology, double-layer capacitance and charge transfer resistance feature values ​​are extracted, and an evolution sequence of interface electrochemical parameters is constructed in time stamp order. A centrifugal rotary table is driven to perform uniformly accelerated rotation on the superhydrophobic surface specimen, capturing the critical speed of ice peeling and the ice-covered area to calculate the adhesion shear stress, updating the cycle count, and triggering the next round of cooling, icing, and impedance acquisition according to the cycle logic. A laser confocal microscope is driven to acquire three-dimensional point cloud data to calculate structural damage feature values, and variable regression analysis is performed. A multidimensional coupled attenuation model is established based on the structural damage feature values, the evolution sequence of interface electrochemical parameters, and the adhesion shear stress.

[0008] Optionally, generating the impedance spectrum scanning frequency point sequence list includes: transferring nano-silver conductive ink onto the superhydrophobic surface specimen using a screen printing process, performing high-temperature curing treatment to form a grid-shaped working electrode pattern; connecting the grid-shaped working electrode pattern to the electrochemical workstation using a shielded coaxial cable, and connecting it to an external grounded shielding box to establish an anti-interference physical connection loop; calling the electrochemical workstation drive interface to obtain the frequency range extreme values, performing logarithmic discretization processing based on the number of sampling points per ten octave, and generating the impedance spectrum scanning frequency point sequence list.

[0009] Optionally, the step of acquiring potential and current responses to calculate the complex impedance data sequence includes: pressing the superhydrophobic surface specimen onto the thermally conductive bonding surface of the low-temperature environment chamber sample holder, performing an active cooling operation and triggering a spray ice-making action to form a surface icing state; traversing the impedance spectrum scanning frequency point sequence list, controlling the potentiostat to output AC potential disturbances, and using a current amplifier to synchronously capture the time-domain current response signal flowing through the physical connection loop; performing a fast Fourier transform on the AC potential disturbances and the time-domain current response signal, extracting the voltage vector and current vector, and calculating the magnitude and phase angle of each frequency point through complex division to generate the complex impedance data sequence.

[0010] Optionally, the active cooling operation and the triggering of the spray ice-making action include: coating the back of the superhydrophobic surface specimen with thermally conductive silicone grease and pressing it onto a semiconductor cooling chip, and connecting a thermocouple feedback loop; adjusting the DC input current based on the semiconductor cooling chip to track the linear cooling curve, and driving an ultrasonic atomizer to generate micron-level supercooled water mist to cover the superhydrophobic surface specimen.

[0011] Optionally, the step of constructing the interface electrochemical parameter evolution sequence in time-stamp order includes: connecting solution resistance elements in series to a parallel circuit based on double-layer capacitance elements and charge transfer resistance elements to define an equivalent circuit topology; processing the complex impedance data sequence using the complex least squares method, calculating the sum of squared residuals between the measured impedance and the model impedance, and performing parameter convergence calculation to complete iterative fitting; after convergence, reading the double-layer capacitance characteristic values ​​and charge transfer resistance characteristic values ​​based on the equivalent circuit topology, and performing key-value pair mapping with the sampling time points to construct the interface electrochemical parameter evolution sequence.

[0012] Optionally, the method further includes: extracting the characteristic value of the charge transfer resistance and the adhesion shear stress, performing numerical normalization and cross-correlation calculations, and generating an interface failure sensitivity index.

[0013] Optionally, triggering the next round of cooling, icing, and impedance acquisition based on the loop logic includes: monitoring the surface state of the superhydrophobic surface specimen using a high-speed camera; locking the instantaneous angular velocity of the centrifugal rotary table as the critical rotation speed for ice peeling when ice layer displacement is detected; calculating the icing area through image binarization processing; and calculating the adhesion shear stress by combining the ice layer mass and the rotation radius; reading the current loop count and performing a numerical comparison with a preset maximum loop count threshold; if the maximum loop count threshold is not reached, incrementing the loop count by one and sending a reset command to the low-temperature environment chamber sample holder to trigger the next round of cooling, icing, and impedance acquisition.

[0014] Optionally, establishing a multidimensional coupled attenuation model based on the structural damage feature values, the evolution sequence of the interface electrochemical parameters, and the adhesion shear stress includes: extracting the height matrix from the three-dimensional point cloud data, calculating the root mean square roughness increment and the change in peak-valley height difference, and generating structural damage feature values; performing data normalization processing on the structural damage feature values, the evolution sequence of the interface electrochemical parameters, and the adhesion shear stress, constructing a correlation analysis matrix and extracting principal component weights to generate a multidimensional coupled attenuation model.

[0015] Optionally, generating structural damage feature values ​​includes: projecting the spatial coordinates of the three-dimensional point cloud data onto a uniform grid reference plane, extracting the vertical depth values ​​of the grid nodes and arranging them in rows and columns to construct a surface height matrix; performing root mean square statistics and extreme value range search on the surface height matrix to obtain the current morphological statistical parameters, and performing numerical difference operations with the initial morphological statistical parameters to generate structural damage feature values.

[0016] Based on the same inventive concept, this invention also provides a testing system for the anti-icing performance of superhydrophobic surface structures of energy equipment. The system includes: an electrode preparation and frequency table generation module, used to prepare a working electrode pattern on a superhydrophobic surface specimen using a conductive material deposition process, establish a physical connection circuit and connect it to an electrochemical workstation, read hardware frequency response boundary data based on the electrochemical workstation, perform logarithmic interpolation, and generate an impedance spectrum scanning frequency sequence table; a low-temperature spray icing and impedance acquisition module, used to install the superhydrophobic surface specimen on a low-temperature environment chamber sample holder, set the cooling rate and target freezing temperature, drive the low-temperature environment chamber sample holder to perform cooling control and activate spray to form an ice layer, apply AC potential perturbations sequentially according to the impedance spectrum scanning frequency sequence table, and acquire potential and current responses to calculate a complex impedance data sequence; and an equivalent circuit fitting and parameter sequence generation module. The generation module is used to perform iterative fitting on the complex impedance data sequence, construct an equivalent circuit topology, extract double-layer capacitance and charge transfer resistance feature values ​​based on the equivalent circuit topology, and construct an interface electrochemical parameter evolution sequence in time stamp order. The centrifugal peeling and adhesion shear stress calculation module is used to drive a centrifugal rotary table to perform uniformly accelerated rotation on the superhydrophobic surface specimen, capture the critical speed of ice peeling and the ice-covered area to calculate the adhesion shear stress, update the cycle count, and trigger the next round of cooling ice covering and impedance acquisition according to the cycle logic. The point cloud morphology acquisition and attenuation model fitting module is used to drive a laser confocal microscope to acquire three-dimensional point cloud data to calculate structural damage feature values, perform variable regression analysis, and establish a multidimensional coupled attenuation model based on the structural damage feature values, the interface electrochemical parameter evolution sequence, and the adhesion shear stress.

[0017] Compared with the prior art, the present invention has the following advantages:

[0018] 1. By integrating multiple testing methods and establishing a multi-physics coupling model, a comprehensive and in-depth characterization of the anti-icing performance and degradation process of superhydrophobic surfaces was achieved. Traditional performance evaluation usually relies on a single mechanical peel test, which can only obtain the final failure data. However, this invention combines mechanical testing, electrochemical monitoring, and microstructure analysis, which can simultaneously obtain data from three dimensions: structure, interface, and macroscopic performance, and construct a multi-dimensional degradation model, thereby revealing the intrinsic mechanism of performance degradation more completely.

[0019] 2. Electrochemical impedance spectroscopy (EIS) was introduced as a non-destructive online monitoring tool, enabling dynamic tracking of the interface state between the ice layer and the superhydrophobic surface. During freeze-thaw cycles and stress cycling, this method can capture the evolution of key electrochemical parameters such as the interfacial double-layer capacitance and charge transfer resistance in real time. These parameters directly reflect microscopic processes such as water molecule intrusion and changes in the state of the interfacial trapped air layer, providing intermediate process information that traditional methods cannot obtain for understanding and predicting the early degradation of anti-icing performance.

[0020] 3. The degradation model enables the testing method to predict the service life of superhydrophobic surfaces. By correlating early changes in interfacial electrochemical parameters, microstructural damage, and final macroscopic adhesive shear stress and extracting principal component weights, this method can not only explain the reasons for performance degradation, but also establish a predictive model based on initial test data to evaluate the durability and reliability of superhydrophobic coatings under actual working conditions, providing important guidance for material selection and engineering applications.

[0021] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures pointed out in the description, claims and drawings. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a flowchart illustrating the method for testing the anti-icing performance of superhydrophobic surface structures for energy equipment according to an embodiment of the present invention.

[0024] Figure 2 This is a statistical graph showing the correlation between the normalized charge transfer resistance characteristic value and the adhesion shear stress in an embodiment of the present invention.

[0025] Figure 3 This is a performance evolution trajectory and contour plot based on a multidimensional coupled attenuation model according to an embodiment of the present invention.

[0026] Figure 4 This is a schematic diagram of the structure of the anti-icing performance testing system for superhydrophobic surface structures of energy equipment according to an embodiment of the present invention. Detailed Implementation

[0027] 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, 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.

[0028] Reference Figure 1 One embodiment of the present invention proposes a method for testing the anti-icing performance of superhydrophobic surface structures of energy equipment. The method combines online monitoring by electrochemical impedance spectroscopy, mechanical exfoliation by centrifugation, and morphological characterization by laser confocal microscopy. This method enables multi-dimensional, dynamic, and quantitative coupled analysis of the anti-icing performance of superhydrophobic surfaces from the microscopic interface to the macroscopic mechanics.

[0029] The method described in this embodiment specifically includes:

[0030] A working electrode pattern is prepared on a superhydrophobic surface specimen using a conductive material deposition process. A physical connection circuit is established and connected to an electrochemical workstation. Based on the electrochemical workstation, hardware frequency response boundary data is read, logarithmic interpolation is performed, and an impedance spectrum scanning frequency point sequence list is generated.

[0031] The superhydrophobic surface specimen was installed on the low-temperature environment chamber specimen holder. The cooling rate and target freezing temperature were set. The low-temperature environment chamber specimen holder was driven to perform cooling control and start spraying to form an ice layer. According to the impedance spectrum scanning frequency point sequence list, AC potential perturbation was applied sequentially. The potential response and current response were collected to calculate the complex impedance data sequence.

[0032] Iterative fitting is performed on the complex impedance data sequence to construct an equivalent circuit topology. Based on the equivalent circuit topology, double-layer capacitance feature values ​​and charge transfer resistance feature values ​​are extracted, and an evolution sequence of interface electrochemical parameters is constructed in time stamp order.

[0033] The centrifugal rotary table is driven to perform uniformly accelerated rotation on the superhydrophobic surface specimen, capture the critical speed of ice peeling and the ice-covered area to calculate the adhesion shear stress, update the cycle count, and trigger the next round of cooling ice covering and impedance acquisition according to the cycle logic.

[0034] A laser confocal microscope is used to acquire three-dimensional point cloud data to calculate structural damage characteristic values. Variable regression analysis is performed, and a multidimensional coupled attenuation model is established based on the structural damage characteristic values, the evolution sequence of the interface electrochemical parameters, and the adhesion shear stress.

[0035] Optionally, the generation of the impedance spectrum scan frequency point sequence list includes:

[0036] Nano-silver conductive ink is transferred to the superhydrophobic surface specimen using screen printing, followed by high-temperature curing to form a grid-like working electrode pattern.

[0037] The engineering challenge of constructing electrodes on superhydrophobic surfaces lies in ensuring good conductivity while minimizing disruption to the original hydrophobicity of the micro / nano structure. To address this, highly thixotropic nano-silver conductive inks are selected, with a solid content typically controlled between 60% and 80% and a viscosity controlled between 20 and 50 Pascals to prevent lateral wetting and dripping during the transfer process. The screen printing stencil is made of 300 to 500 mesh polyester or stainless steel, designed to deposit a fine mesh with linewidths of 10 to 50 micrometers. The operator pours the nano-silver conductive ink onto the screen and uses a squeegee to transfer the ink onto the superhydrophobic surface specimen using constant pressure and angle. The printed specimen is then placed in a forced-air drying oven or infrared sintering furnace for high-temperature curing at 100 to 150 degrees Celsius for 30 to 90 minutes. The curing process causes the organic coating agent on the surface of the silver nanoparticles to volatilize, and necking sintering occurs between the particles, thereby forming a grid-like working electrode pattern with low sheet resistance, for example less than 50 milliohms / square, and strong adhesion.

[0038] For example, a superhydrophobic surface specimen of a wind turbine blade was prepared using nano-silver ink with a solid content of 70%. A square grid pattern with a line width of 30 micrometers and a grid spacing of 2 millimeters was printed using a 400-mesh stainless steel screen. The specimen was placed in a precision oven, and the heating rate was set to 130 degrees Celsius per minute, maintained at that temperature for 60 minutes. After cooling, the grid-shaped working electrode pattern adhered tightly to the superhydrophobic surface without altering the contact angle characteristics of the non-electrode covered areas.

[0039] The grid-shaped working electrode pattern is connected to the electrochemical workstation using a shielded coaxial cable, and then connected to an external grounded shielding box to establish an anti-interference physical connection circuit.

[0040] Considering that ice is a high-impedance medium, the response current during electrochemical impedance spectroscopy is extremely weak and highly susceptible to interference from environmental electromagnetic noise. Establishing an anti-interference physical connection loop aims to create an electrostatically shielded environment. Low-noise Teflon-insulated shielded coaxial cables are selected, using the outer braided shielding mesh of the coaxial cable as a protective ground and the inner core as the signal transmission line, connecting the leads of the grid-shaped working electrode pattern to the working electrode interface of the electrochemical workstation. Simultaneously, the test platform carrying the superhydrophobic surface specimen is placed inside an externally grounded shielded box made of metal. Using a yellow-green grounding wire with a cross-sectional area greater than 4 square millimeters, the outer shell of the shielded box is connected to the laboratory's independent grounding stake, ensuring a grounding resistance of less than 4 ohms, thereby shielding against interference and spatial radio frequency radiation.

[0041] The frequency range extreme values ​​are obtained by calling the electrochemical workstation drive interface, and logarithmic discretization is performed based on the number of sampling points per ten octave to generate an impedance spectrum scanning frequency point sequence list.

[0042] Impedance spectroscopy scanning needs to be performed over an extremely wide frequency range, typically spanning 5 to 7 orders of magnitude. To obtain uniformly distributed data points on the Bode plot, a logarithmic discretization algorithm, rather than a nonlinear discretization, must be used. The control computer, via standard instrument communication protocols such as GPIB or USB-TMC, calls the low-level driver interface of the electrochemical workstation to read the highest output frequency and lowest measurement frequency supported by the hardware. Subsequently, the "number of sampling points per decibel" is introduced as a core parameter for controlling the frequency distribution density. This parameter determines how many valid data points are collected within each order of magnitude change in frequency, i.e., the frequency value multiplied by 10 or divided by 10. To accurately generate this list, the following logarithmic frequency distribution formula is used for calculation:

[0043] ;

[0044] in, The number in the impedance spectrum scan frequency sequence list The frequency value of each frequency point, in Hertz, is the instruction value that is ultimately written into the sequence list and controls the hardware output. This represents the maximum value of the hardware frequency range obtained from the driver interface, or the scan start frequency set by the user according to the test requirements, in Hertz. This parameter determines the starting point of the scan and usually corresponds to the rapid kinetic process in the electrochemical reaction. The index integer representing the discretized sequence, with a value range of 1. ,in The time corresponds to the starting frequency, and this parameter is used to control the number of steps generated in the iteration. This represents the number of sampling points per decibel, a dimensionless positive integer. This parameter is derived from user settings or standard test specifications, typically taking values ​​of 10, 20, or 50. Its physical meaning lies in determining the resolution of the frequency scan; a larger value results in a finer spectrum, but also a longer test time. The formula's calculation principle is: using the starting frequency as a reference, frequency decreases progressively through exponential operations. When the index... Increase When, the exponent term becomes That is, the frequency is reduced to one-tenth of its original value, thus strictly ensuring that each pass... At each point, the frequency decreases by an order of magnitude. The calculation process continues until the calculated value is obtained. Stop when the frequency is less than or equal to the minimum value of the hardware frequency range; all generated frequencies will be stopped. The set constitutes the impedance spectrum scanning frequency point sequence list.

[0045] For example, assume that the highest frequency supported by the hardware of the electrochemical workstation is read through the driver interface. The frequency is 100,000Hz, and the lowest frequency is 0.1Hz. Set the number of sampling points per decade. It is 10. When At that time, the first frequency point Hz; when At that time, the second frequency point Hz; ...when At that time, the 11th frequency point Hz. It can be seen that from point 1 to point 11, the frequency drops by exactly one order of magnitude, with 9 points evenly distributed in between. Calculations continue following this pattern until the frequency is below 0.1Hz, ultimately generating a sequence list containing approximately 61 frequency points for precise control of the applied frequency of AC potential disturbances.

[0046] Optionally, the acquisition of potential and current responses to calculate the complex impedance data sequence includes:

[0047] The superhydrophobic surface specimen is pressed onto the thermally conductive bonding surface of the low-temperature environment chamber sample holder, and an active cooling operation is performed to trigger a spray ice-making action to form a surface icing state.

[0048] To ensure precise control of thermodynamic boundary conditions, the contact thermal resistance between the specimen and the cooling source must first be eliminated. Test personnel or automated loading robots apply a layer of thermally conductive silicone grease with a thermal conductivity greater than 2.0 watts per meter Kelvin to the back of the superhydrophobic surface specimen, press it onto the metal thermally conductive mating surface of the cryogenic environment chamber specimen holder, and apply a constant preload using screws or spring clamps. Subsequently, the temperature control module drives the integrated semiconductor cooling chip or liquid nitrogen channel to perform active cooling, adjusting the cooling power to lower the specimen surface temperature below the freezing point. When the surface temperature reaches a supercooled state, for example, -5°C to -10°C, an ultrasonic atomizer or pneumatic nozzle is triggered to perform a spray ice-making action, continuously spraying micron-sized water mist onto the specimen surface. Upon contact with the cryogenic superhydrophobic surface, the supercooled water droplets rapidly undergo a phase change and freeze, gradually forming a continuous surface ice layer with controllable thickness as the spraying time continues.

[0049] For example, when testing the superhydrophobic skin of an aerospace-grade aluminum alloy substrate, the tester uniformly applied Dow Corning TC-5021 thermal grease to the back of the specimen and mounted it on a pure copper sample holder. A thermostat controlled the semiconductor cooler to cool the specimen at a rate of 2 degrees Celsius per minute until the surface temperature stabilized at -12 degrees Celsius. At this point, an ultrasonic atomizer was activated to generate water mist with an average particle size of 30 micrometers, and the spraying duration was set to 15 minutes. Ultimately, a dense, transparent ice layer with a thickness of approximately 2.5 millimeters was formed on the superhydrophobic surface, serving as the steady-state object for electrochemical testing.

[0050] The impedance spectrum scanning frequency sequence list is traversed, the potentiostat is controlled to output AC potential disturbance, and the time-domain current response signal flowing through the physical connection loop is synchronously captured using a current amplifier.

[0051] The data acquisition controller sequentially reads the frequency values ​​from the impedance spectrum scan frequency point sequence table stored in memory. For each specific frequency point, it sends a command to the potentiostat, driving it to output a sinusoidal AC potential perturbation between the working electrode and the reference electrode. The amplitude of this perturbation is typically limited to between 5 mV and 15 mV to ensure that the electrochemical reaction is in the linear polarization region, preventing large amplitude signals from altering the interfacial double-layer structure or causing dielectric breakdown of the ice layer. Simultaneously, a high-sensitivity current amplifier located in the physical connection loop is activated, monitoring the current change flowing through the working electrode in real time. It amplifies and converts the weak current signal in the nanoamp to microamp range into a voltage signal, which is then digitally sampled by an analog-to-digital converter (ADC) at a sampling rate at least 10 times higher than the signal frequency, thereby capturing the complete time-domain current response signal.

[0052] A fast Fourier transform is performed on the AC potential disturbance and the time-domain current response signal to extract the voltage vector and current vector. The magnitude and phase angle of each frequency point are calculated by complex division to generate a complex impedance data sequence.

[0053] To extract the frequency domain impedance characteristics from the time-domain waveform, the Fast Fourier Transform (FFT) algorithm is used. This algorithm converts discrete time-series data into a frequency-domain complex sequence, thereby extracting the amplitude and phase information at the fundamental frequency, i.e., the voltage and current vectors. Subsequently, based on the complex form of Ohm's law, the complex impedance at that frequency is calculated. The core formula for calculating the complex impedance is as follows:

[0054] ;

[0055] in, Representing angular frequency The complex impedance at time t is expressed in ohms. It is a comprehensive physical quantity that characterizes the interface's ability to impede current and its phase delay characteristics. Represents angular frequency, and its value is determined by the following principle: ,in This represents the frequency of the currently traversed scan point, in Hertz. This represents the voltage vector extracted through the Fast Fourier Transform, a physical quantity that contains information about the magnitude and initial phase of the applied AC potential disturbance. This represents the current vector extracted via Fast Fourier Transform, a physical quantity that contains information about the magnitude of the captured response current and its phase lag relative to the voltage. This represents the impedance magnitude, which is calculated by dividing the voltage magnitude by the current magnitude. It represents the impedance phase angle, which is calculated by subtracting the current phase from the voltage phase. The imaginary unit is used. Through calculation, the processor calculates the modulus value for each frequency point. and phase angle Arrange them in descending order of frequency to generate a complex impedance data sequence.

[0056] For example, suppose the current scanning frequency is... The frequency is 1000Hz. The potentiostat outputs a voltage disturbance with an amplitude of 10mV, and the current amplifier captures a current response amplitude of 5nA, with the current waveform lagging behind the voltage waveform by 45 degrees. First, an FFT transformation is performed to extract the vector: voltage vector. Volt, i.e., amplitude 10mV, phase 0°; current vector Amperes, i.e., amplitude 5 nA, phase -45°. Next, perform complex division: modulus... Phase angle Ultimately, the data at that frequency... The data was written into the complex impedance data sequence, which characterized the significant capacitive reactance of the icing interface at this frequency.

[0057] Optionally, the step of performing active cooling and triggering the spray ice-making action includes:

[0058] Thermally conductive silicone grease was coated on the back of the superhydrophobic surface specimen and pressed onto a semiconductor cooling chip, and a thermocouple feedback loop was connected.

[0059] The testers selected a thermally conductive silicone grease containing silver or ceramic particles with a thermal conductivity between 1.0 and 5.0 watts per meter (Kelvin). This grease was uniformly applied to the non-test surfaces of the superhydrophobic specimen, with a coating thickness controlled between 0.05 and 0.2 mm to fill microscopic interface voids. Subsequently, the specimen was mechanically pressed against the cold-end ceramic surface of the thermoelectric cooler (TEC) using bolts or pneumatic clamps, with the pressure controlled between 0.5 and 1.0 MPa to prevent hot spot effects due to poor contact. The thermoelectric cooler is a solid-state heat pump that operates using the Peltier effect. When a direct current flows through a thermocouple pair composed of two different semiconductor materials, heat is absorbed at one end and released at the other. For closed-loop control, the sensing ends of fine-diameter K-type or T-type thermocouples (0.1 to 0.3 mm in diameter) were fixed to the edge of the specimen or embedded in the temperature sensing hole of the specimen holder using low-temperature tape or thermally conductive adhesive, constructing a thermocouple feedback loop. This converts the real-time acquired temperature signal into a voltage signal and feeds it back to the temperature controller.

[0060] For example, when testing a 20mm × 20mm copper-based superhydrophobic specimen, the tester applied a layer of Shin-Etsu 7921 thermal grease approximately 0.1mm thick to the back of the copper substrate. A TEC1-12706 thermoelectric cooler was selected, with its hot end fixed to a circulating water-cooled radiator and its cold end pressed against the back of the specimen. A T-type thermocouple was placed tightly against the side of the specimen and secured with polyimide tape. This setup ensured efficient heat transfer from the cooler to the specimen, allowing the specimen surface temperature to respond rapidly to control commands.

[0061] Based on the semiconductor cooling chip, the DC input current is adjusted to track the linear cooling curve, and the ultrasonic atomizer is driven to generate micron-level supercooled water mist to cover the superhydrophobic surface specimen.

[0062] To simulate the real-world condition of a gradual temperature drop in nature, rather than the thermal shock of instantaneous freezing, the temperature controller executes a linear cooling algorithm. This controller integrates a PID control module, using the real-time temperature feedback from the thermocouple as the input variable and a set linear cooling curve as the target variable. Through pulse width modulation (PWM) or linear power supply regulation technology, it dynamically changes the magnitude and direction of the DC drive current applied across the thermoelectric cooler. This linear cooling control follows the following temperature-time evolution formula:

[0063] ;

[0064] in, Represents the moment At that time, the target temperature value set by the controller, in degrees Celsius, is the tracking target of the PID control loop. This represents the initial ambient temperature at which the cooling process begins, typically determined by a thermocouple. The temperature was measured at any time, and the unit is Celsius. This represents the cooling rate set by the user, measured in degrees Celsius per minute, typically ranging from 0.5 to 5.0 °C / min. Its physical significance lies in defining the rate of change of thermodynamic state, which directly affects the kinetic process of ice crystal nucleation. This represents the elapsed time in minutes since the cooling program started. When the surface temperature of the specimen reaches the preset spray trigger threshold, the controller outputs an enable signal to drive the ultrasonic atomizer. This atomizer utilizes the longitudinal vibration of a high-frequency piezoelectric ceramic transducer to generate cavitation and capillary wave effects at the water-air interface, breaking the liquid water into tiny droplets with diameters ranging from 1 to 10 micrometers. These tiny droplets are blown by the carrier gas flow to the surface of the low-temperature specimen, where they exchange heat with the low-temperature air during flight, becoming supercooled water droplets. Upon contact with the superhydrophobic surface, heterogeneous nucleation occurs, thus covering the specimen and growing an ice layer.

[0065] For example, for icing tests under simulated freezing rain conditions, an initial temperature is set. At 20℃, cooling rate The flow rate is 2℃ / min. Based on the formula, the controller aims for a target temperature of 10℃ at the 5th minute and -10℃ at the 15th minute. The controller outputs a gradually increasing DC current to the semiconductor cooling chip, causing the specimen temperature to decrease strictly along this slope. When the temperature drops to -5℃, the ultrasonic atomizing plate with a drive frequency of 1.7MHz is activated, generating water mist with an average particle size of 5 micrometers. Under gravity, the water mist settles onto the specimen surface, forming transparent and dense ice.

[0066] For example, in tests simulating rime ice environments in high-altitude and cold mountainous areas, a faster cooling rate was set. The flow rate was set at 5℃ / min to simulate a cold wave. A multi-stage cascaded semiconductor cooling system was used to achieve an even lower cold-end temperature. When the specimen temperature reached a cryogenic state of -15℃, a microporous atomizing plate was activated to generate extremely fine water mist with a particle size of approximately 3 micrometers. This water mist partially crystallized before contacting the specimen, and accumulated on the surface to form loose, white frost, used to test the interfacial impedance characteristics of the superhydrophobic surface under different ice accumulation types.

[0067] Optionally, the construction of the interface electrochemical parameter evolution sequence in time-stamp order includes:

[0068] Based on the double-layer capacitor element and the charge transfer resistor element, the solution resistor element is connected in series to the parallel circuit, and the equivalent circuit topology is defined.

[0069] To transform abstract spectral data into interface state indices with clear physical meaning, a physical model is constructed to simulate the charge transport mechanism between the ice layer, superhydrophobic coating, and substrate metal interface. An improved circuit model is defined as the equivalent circuit topology, consisting of three core components: a solution resistive element... Physically characterizing the ohmic resistance of an unfrozen water film or ice layer; double-layer capacitor element. Physically characterizing the dielectric properties and charge / discharge capability of the ice coating interface; charge transfer resistor element. Physically, the resistance to charge crossing an interface is a key indicator for evaluating corrosion resistance and coating density. In terms of topological connection, a double-layer capacitor element and a charge transfer resistor element are first connected in parallel to form a time constant unit to simulate the polarization process at the interface. Subsequently, this parallel unit is connected in series with a solution resistor element to reflect the series voltage division effect of the electrolyte pathway.

[0070] The complex impedance data sequence is processed by the complex least squares method, the sum of squared residuals between the measured impedance and the model impedance is calculated, and parameter convergence calculation is performed to complete the iterative fitting.

[0071] The complex impedance data sequence is retrieved, and a complex nonlinear least squares algorithm is employed to minimize the difference between the measured data points and the theoretical model curve. During each iteration, adjustments are made... , , The numerical values ​​are then used to calculate the objective function, which is the sum of squared residuals. The formula for the objective function is defined as follows:

[0072] ;

[0073] in, The sum of squared residuals is a dimensionless, non-negative real number. Its physical meaning represents the degree of deviation between the model and the actual data. The closer this value is to 0, the higher the fitting accuracy. This represents the total number of frequency points contained in the impedance spectrum scan frequency point sequence list, typically 30 to 60 points. This is a frequency index, with values ​​ranging from 1 to... . and Representing respectively in the The real and imaginary parts of the complex impedance measured by the electrochemical workstation at each frequency point, in ohms. and Representing respectively in the The real and imaginary parts of the theoretical impedance calculated at a given frequency point based on the current equivalent circuit topology and parameter estimates, in ohms. Representing the The weighting factors for each data point are determined by the impedance data, which spans multiple orders of magnitude, from a few ohms to several gigahertz. To prevent high impedance points from dominating the fitting error, a modulus-weighted method is typically used, i.e., taking... Its function is to balance the contributions of the high-frequency, low-resistivity region and the low-frequency, high-resistivity region to the fitting results. The criterion for judging whether the algorithm's parameters have converged is usually set as follows: the results obtained from two consecutive iterations... The rate of change of value is less than Alternatively, the parameter adjustment step size may be less than the preset tolerance. Once this condition is met, the iterative fitting is considered complete.

[0074] After convergence, the double-layer capacitance characteristic value and charge transfer resistance characteristic value are read based on the equivalent circuit topology, and key-value pair mapping is performed with the sampling time point to construct the interface electrochemical parameter evolution sequence.

[0075] After mathematical convergence, the current circuit element parameters are considered the physical truth values ​​characterizing the interface state. Optimized double-layer capacitance and charge transfer resistance characteristic values ​​are directly read from the converged model. Simultaneously, metadata for this set of impedance data is retrieved, and the absolute timestamp of the data acquisition moment is extracted. A key-value pair mapping operation is performed, using the timestamp as the primary key and the capacitance and resistance values ​​as the values, generating a structured data record. As the test cycle progresses, multiple such records are arranged chronologically, ultimately constructing an evolution sequence of interface electrochemical parameters. This sequence reflects the dynamic decay trajectory of the superhydrophobic surface's microscopic insulation properties and impermeability during repeated icing and de-icing processes.

[0076] For example, in the initial stage of testing, the superhydrophobic surface structure is intact and defect-free. The processed complex impedance data, after convergence, shows that the charge transfer resistance characteristic value... Gundam This indicates that the coating has excellent insulation properties, making it difficult for ions to penetrate, and the characteristic value of the double-layer capacitance is [value missing]. for This indicates that the water absorption rate is extremely low. This set of data is bound to the timestamp "2025-12-01 09:00:00" and stored in the first line of the evolutionary sequence.

[0077] For example, after undergoing 50 rigorous cycles of "cooling-freezing-centrifugation and detachment," the micro / nano structure suffered partial mechanical damage, leading to moisture infiltration. At this point, new impedance data was processed again, and the objective function was calculated. It reaches its minimum value after the 15th iteration. The characteristic value of the charge transfer resistance is read. Significantly decreased to The resistance decreased by three orders of magnitude, indicating corrosion or conductive pathways at the interface, and the characteristic value of the double-layer capacitance... Rise to The increased capacitance indicates that the dielectric constant has changed due to the infiltration of water molecules. By binding this set of data characterizing the failure state with the current timestamp "2025-12-03 14:30:00" and appending it to the evolution sequence, the decay process of anti-icing performance was quantitatively recorded.

[0078] Optionally, the method further includes:

[0079] The characteristic values ​​of the charge transfer resistance and the adhesion shear stress are extracted, and numerical normalization and cross-correlation are performed to generate an interface failure sensitivity index.

[0080] To establish a quantitative correlation between microscopic electrochemical parameters and macroscopic mechanical properties, a comprehensive index for evaluating the degree of coupling between interfacial states is generated. The aim is to correlate non-destructive electrochemical monitoring data with destructive mechanical test results through mathematical calculations, thereby deriving a sensitivity index that can predict mechanical failure. First, two key time-series data are read from memory: a sequence of charge transfer resistance characteristic values ​​parsed from multiple cyclic tests and a synchronously recorded adhesion shear stress sequence. Subsequently, numerical normalization is performed on these two sequences, which have different physical dimensions and significant numerical differences. The purpose is to eliminate calculation biases caused by differences in dimensions and orders of magnitude, mapping the data to a unified dimensionless interval. This processing uses a maximum-minimum normalization algorithm, and the calculation formula is as follows:

[0081] ;

[0082] in, Represents the normalized first The value of the next loop is strictly limited to a range of values. Between them is a dimensionless pure scalar. Represents the first in the original sequence The measured data points of each cycle, that is, the characteristic value of charge transfer resistance or the value of adhesion shear stress at a specific moment. and These represent the minimum and maximum values ​​of the original data sequence throughout the entire lifecycle testing process, derived from a comprehensive statistical analysis of historical data. After normalization, a cross-correlation operation is performed on the two resulting dimensionless sequences to measure the synchronicity and linear correlation strength between changes in microscopic resistance and macroscopic adhesion force, i.e., to determine whether a decrease in resistance is always accompanied by an increase in adhesion force. The algorithm calculates the absolute value of the Pearson product-moment correlation coefficient as the result, using the following formula:

[0083] ;

[0084] in, This represents the sensitivity index to interface failure, with a value range of [value range missing]. arrive The closer the value is to The stronger the correlation between the two, the better the electrochemical impedance is as a predictor of mechanical failure of the surface; the closer the value is to... This indicates that the two are unrelated, and the failure mechanism may be more complex. This represents the total number of loops. and Representing the first In each cycle, the normalized charge transfer resistance value and the normalized adhesion shear stress value are obtained. and These represent the arithmetic mean of the normalized resistance sequence and the normalized stress sequence, respectively. For example... Figure 2 As shown, the central region displays the linear regression fit and 95% confidence interval of the normalized charge transfer resistance eigenvalue and adhesion shear stress. The top and right sides of the graph show the frequency distribution density of the two physical quantities, confirming a significant negative correlation between microscopic electrochemical parameters and macroscopic mechanical properties.

[0085] For example, a test was conducted on a brittle sol-gel superhydrophobic coating. The charge transfer resistance was measured during 20 freezing-shedding cycles. From the initial monotonically decreasing to While the adhesive shear stress from monotonous rise to Extract these two sets of data, normalize them, and then substitute them into the formula for calculation. Due to the highly negative correlation in their trends, the calculated Pearson coefficient is... Take its absolute value to generate an interface failure sensitivity index. This high index suggests to researchers that the coating's failure is primarily caused by through-cracks, and its de-icing life can be accurately predicted by monitoring changes in resistance.

[0086] Optionally, triggering the next round of cooling, icing, and impedance acquisition based on loop logic includes:

[0087] The surface state of the superhydrophobic surface specimen is monitored using a high-speed camera. When ice layer displacement is detected, the instantaneous angular velocity of the centrifugal rotating table is locked as the critical rotation speed for ice layer peeling. The ice-covered area is calculated by image binarization processing, and the adhesion shear stress is calculated by combining the ice layer mass and the rotation radius.

[0088] To accurately capture the ice peeling process and obtain core mechanical parameters, a visual feedback-based critical condition locking mechanism was implemented. This aimed to determine the instantaneous interface separation between the ice layer and the superhydrophobic surface without delay, and to calculate the adhesive shear stress characterizing the interfacial bonding strength. A high-speed camera with a frame rate set between 500 and 2000 frames per second continuously imaged and monitored the superhydrophobic surface specimen fixed to the end of the centrifuge rotating platform cantilever. The image processing unit analyzed the video stream in real time. When macroscopic displacement of the ice layer relative to the substrate was detected using inter-frame difference or optical flow methods, an interrupt signal was immediately triggered, locking the instantaneous angular velocity output by the centrifuge controller and recording it as the critical rotational speed for ice peeling. Simultaneously, a static image of the frame preceding ice peeling was captured. Based on a threshold set according to the grayscale difference between the ice layer and the background, image binarization was performed. This process segmented the image into a white region representing the ice layer and a black region representing the background. The total number of pixels in the white region was counted and multiplied by the actual physical area of ​​a single pixel to calculate the ice-covered area. Based on the acquired physical quantities, the adhesive shear stress was calculated. The core calculation formula is as follows:

[0089] ;

[0090] in, Represents the centrifugal peeling force, measured in Newtons. This parameter indicates the outward mechanical peeling force experienced by the ice layer during centrifugal rotation. This represents the adhesion shear stress, measured in Pascals. This parameter is the most direct indicator of the anti-ice adhesion performance of superhydrophobic surfaces. The value represents the mass of the ice layer, expressed in kilograms. It is obtained by weighing the total mass of the iced specimen using a high-precision electronic balance before centrifugation and then subtracting the mass of the specimen itself, or by estimating the ice layer volume by multiplying the density of the ice. The critical rotational speed for ice layer stripping is represented by radians per second. This parameter is determined by the centrifuge rotational speed at the moment the high-speed camera is triggered. The radius of rotation is the distance from the center of rotation of the centrifugal turntable to the geometric center of the icing area, expressed in meters. This parameter is determined by the mechanical structural dimensions of the centrifugal turntable. This represents the ice-covered area calculated through image binarization, in square meters.

[0091] For example, in a test on a micro / nanostructured surface, a high-speed camera ran at 1000 FPS. When ice was detected flying off the surface, the centrifuge speed was locked at 1500 rpm. The mass of the ice layer was measured before the test. for grams, radius of rotation for Meters. Image processing calculates the ice-covered area. for Square centimeters. Substituting these values ​​into the formula, centrifugal force... Newton. Adhesive shear stress Pascal. This value is then stored in the database as the mechanical performance evaluation result for the current cycle.

[0092] The current cycle count is read and compared with the preset maximum cycle count threshold. If the maximum cycle count threshold is not reached, the cycle count is incremented by one, and a reset command is sent to the low-temperature environment chamber sample holder to trigger the next round of cooling, icing and impedance acquisition.

[0093] To evaluate the durability of superhydrophobic surfaces under long-term service, a loop logic check is initiated. The purpose is to automatically determine, based on the experimental plan, whether to terminate the test and output a report, or to start the next round of aging and measurement. The current loop count stored in the register is read. And compared with the maximum number of cycles set by the user before the experiment began. Perform a numerical comparison operation. If the comparison result displays... This indicates that the durability test is not yet complete. Perform the following steps: First, increment the loop counter variable by one. Secondly, a reset command containing hardware initialization code is generated and sent to the low-temperature environment chamber sample holder via Ethernet. This command will reset the target temperature of the temperature controller, start the semiconductor cooling chip and ultrasonic atomizer, thereby automatically triggering the next round of cooling and icing and impedance acquisition process, realizing unattended and fully automated operation of the entire anti-icing performance degradation test process.

[0094] For example, a maximum cycle count threshold is set to 50. The 10th centrifugal de-icing test has just been completed, and the 10th set of adhesive shear stresses has been calculated. Read the current count. The comparison revealed The condition is met. Update the count to... The system then sends a "Reset_Start" command to the cryogenic chamber. The cryogenic chamber then removes any remaining water from the previous cycle, restarts the cooling coils to lower the specimen temperature to -10°C, and initiates the spraying process to begin the 11th icing cycle in order to obtain electrochemical impedance spectroscopy data for the 11th cycle.

[0095] Optionally, establishing a multidimensional coupled attenuation model based on the structural damage characteristic values, the evolution sequence of the interfacial electrochemical parameters, and the adhesive shear stress includes:

[0096] The height matrix is ​​extracted from the three-dimensional point cloud data, the root mean square roughness increment and the change in peak-valley height difference are calculated, and structural damage feature values ​​are generated.

[0097] To establish a multidimensional model capable of comprehensively evaluating and predicting the degradation of anti-icing properties of superhydrophobic surfaces, a quantitative characterization of surface physical damage is performed. The aim is to transform the complex geometric changes in microstructure after cyclic testing into a set of quantifiable structural damage characteristic values. First, height matrix extraction is performed on the acquired 3D point cloud data, i.e., the height matrix obtained from each point cloud obtained by laser confocal microscopy scanning... Coordinates corresponding to The axis height value is mapped to a In a two-dimensional array, a digitized surface height matrix is ​​formed. Based on this matrix, two key statistical parameters are calculated: root mean square roughness increment. Changes in peak-valley height difference The calculation process is as follows: based on the ISO25178 standard algorithm, the root mean square roughness of the surface height matrix after the current test cycle is calculated. and the maximum peak-to-valley distance Subsequently, the corresponding parameters of the initial surface recorded before the test were read. and Finally, the difference operation is performed, that is... and These two differences constitute the structural damage feature vector, which respectively characterizes the overall wear degree of the surface microtexture and the expansion of local deep defects.

[0098] For example, the initial root mean square roughness of a superhydrophobic surface of a nanopillar array structure was measured before testing. 150 nanometers, peak-to-valley difference The nanopillar is 800 nanometers in size. After 30 cycles of icing and shedding, laser scanning data showed that the nanopillar collapsed and fractured. The current... Become 120 nanometers, It becomes 600 nanometers. Perform differential calculation: root mean square roughness increment. Nanometers; variation in peak-valley height difference Nanoscale. This set of negative values ​​indicates that the surface micro / nanostructure has undergone "peak-shaving and valley-filling" abrasive damage.

[0099] The structural damage characteristic values, the evolution sequence of the interface electrochemical parameters, and the adhesion shear stress are normalized to construct a correlation analysis matrix and extract the principal component weights to generate a multidimensional coupled attenuation model.

[0100] To reveal the intrinsic coupling relationship between surface structural damage, changes in interfacial electrochemical properties, and the degradation of macroscopic adhesion mechanical properties, and to express this relationship in the form of a mathematical model, it is necessary to eliminate the differences in physical dimensions and data ranges. The structural damage characteristic values, charge transfer resistance extracted from the evolution sequence of interfacial electrochemical parameters, and adhesion shear stress are uniformly normalized. Typically, the minimum-maximum normalization method is used to linearly map the values ​​in each sequence to... Interval. Subsequently, a correlation analysis matrix is ​​constructed based on the preprocessed data, and a multidimensional coupling decay model is established using principal component analysis (PCA). The general linear combination form of this model can be expressed as:

[0101] ;

[0102] in, The overall anti-icing performance degradation index is a dimensionless scalar. The higher the value, the more severe the decline in the overall anti-icing performance of the superhydrophobic surface. , , These represent the normalized structural damage characteristic values, the normalized interfacial electrochemical parameters, and the normalized adhesion shear stress, respectively. , , The principal component weights are obtained through principal component analysis. The covariance matrix of a multidimensional dataset consisting of three variables is calculated, and its eigenvalues ​​and eigenvectors are solved. The absolute values ​​of the components of the eigenvector corresponding to the largest eigenvalue are selected, and after normalization, these three weights are obtained. The physical meaning of these weights lies in quantifying the contribution of each individual factor to the overall failure. The large scale indicates that the damage to the appearance is the main cause; The main cause is likely the chemical corrosion or wetting transformation at the interface. The large scale indicates that the macroscopic mechanical binding force is the primary cause. For example... Figure 3 As shown in the figure, the gray gradient represents the theoretical distribution of the comprehensive decay index, the black solid line trajectory shows the state evolution path of a typical superhydrophobic surface specimen during cyclic testing, and the arrows indicate the direction of damage accumulation as the number of cycles increases.

[0103] For example, a full lifecycle assessment was performed on a superhydrophobic coating on a metal substrate. During the data processing phase, a dataset containing 50 cycles was constructed. PCA analysis showed that the first principal component explained 92% of the data variability. The extracted weights were: structural damage weight... Electrochemical weight Mechanical weights The generated attenuation model is This model indicates that the failure of the coating is primarily driven by changes in the interfacial electrochemical properties, while physical wear due to surface morphology contributes relatively little. Therefore, the focus should be on improving the coating's density and impermeability, rather than simply increasing its hardness.

[0104] Optionally, the generated structural damage feature values ​​include:

[0105] The spatial coordinates of the three-dimensional point cloud data are projected onto a uniform grid reference plane, the vertical depth values ​​of the grid nodes are extracted and arranged in rows and columns to construct a surface height matrix;

[0106] To transform the unstructured, scattered 3D point cloud data acquired by laser confocal microscopy into a structured data format suitable for mathematical statistics and image processing, a two-dimensional matrix mapping is performed. The aim is to establish a digital elevation model (DEM) to describe the undulations of the microscopic surface in a pixel-based manner. First, a uniform grid reference plane corresponding to the physical dimensions of the scanning area is defined, with a grid resolution typically set to 0.5 to 2.0 micrometers to match the optical resolution of the microscope. Then, each spatial coordinate point in the 3D point cloud data is traversed. Project it onto the corresponding grid coordinates on the reference plane. For each grid node, its corresponding vertical depth value is extracted as the grayscale value or height value at that location. If a grid contains multiple point cloud data points, the arithmetic mean is taken; if a grid contains no data, bilinear interpolation is used to fill it. Finally, all extracted data are processed... Values ​​are filled in row and column order to a single... OK The surface height matrix is ​​constructed from the two-dimensional array of columns.

[0107] For example, for a scan area of The superhydrophobic surface specimen was set with a mesh resolution of [value missing]. , build a An empty matrix. Read the point cloud file and map the points with physical coordinates to the matrix index. The position, and assigned a value After traversing and interpolating millions of point cloud data points, a surface height matrix containing one million height data points is finally generated, which fully reproduces the morphological details of the micro-nano structure.

[0108] The root mean square statistics and extreme value range search are performed on the surface height matrix to obtain the current morphological statistical parameters, and numerical difference operation is performed with the initial morphological statistical parameters to generate structural damage feature values.

[0109] The aim is to extract key indicators that can quantify the degree of surface wear and defect depth from massive matrix data, performing two core mathematical operations on the surface height matrix. The first is root mean square (RMS) statistics, used to calculate the root mean square roughness, as shown in the following formula:

[0110] ;

[0111] in, Representing root mean square roughness, measured in micrometers, it reflects the degree of dispersion of the surface micro-profile from the average plane and is a core indicator for measuring the overall "roughness" or "smoothness" of a surface. and These represent the number of rows and columns of the surface height matrix, respectively. The first in the matrix represents the first Line 1 The vertical depth value of the column element. The first is the arithmetic mean of all height values ​​in the entire matrix, i.e., the height of the reference plane. The second is extreme value range search, where the computational unit traverses the entire matrix to search for the maximum height value. and minimum height value Calculate the peak-valley height difference The formula is:

[0112] ;

[0113] This parameter characterizes the maximum vertical span of the surface micro / nanostructure and is often used to assess the depth of deep pit defects or coating peeling. Finally, numerical difference calculations are performed. To eliminate individual differences and quantify the damage caused by the test, the initial morphological statistical parameters recorded before the test are retrieved. and , and the parameters obtained from the current calculation and The difference generated by subtraction and This is defined as a structural damage characteristic value.

[0114] For example, suppose that after the 50th test cycle, the current root mean square roughness is calculated from the surface height matrix. Peak-valley height difference The initial state parameters of the specimen recorded in the database are... , Perform the difference operation to calculate the root mean square roughness increment. Changes in peak-valley height difference This set of positively increasing eigenvalues ​​( The increased surface roughness and deep defects caused by mechanical wear and frost heave are quantified and will be used as input variables for the multidimensional coupling model.

[0115] Based on the same inventive concept, this invention also provides a testing system for the anti-icing performance of superhydrophobic surface structures in energy equipment, such as... Figure 4 As shown, the system includes:

[0116] The electrode preparation and frequency point table generation module is used to prepare working electrode patterns on superhydrophobic surface specimens using conductive material deposition processes, establish physical connection circuits and connect to an electrochemical workstation, read hardware frequency response boundary data based on the electrochemical workstation, perform logarithmic interpolation operations, and generate an impedance spectrum scanning frequency point sequence table.

[0117] The low-temperature spray icing and impedance acquisition module is used to install the superhydrophobic surface specimen on the low-temperature environment chamber sample holder, set the cooling rate and target freezing temperature, drive the low-temperature environment chamber sample holder to perform cooling control and start spraying to form an ice layer, apply AC potential perturbation sequentially according to the impedance spectrum scanning frequency point sequence list, and collect potential response and current response to calculate complex impedance data sequence.

[0118] The equivalent circuit fitting and parameter sequence generation module is used to perform iterative fitting on the complex impedance data sequence, construct the equivalent circuit topology, extract double-layer capacitance feature values ​​and charge transfer resistance feature values ​​based on the equivalent circuit topology, and construct the interface electrochemical parameter evolution sequence in time stamp order.

[0119] The centrifugal peeling and adhesion shear stress calculation module is used to drive the centrifugal rotary table to perform uniformly accelerated rotation on the superhydrophobic surface specimen, capture the critical speed of ice peeling and the ice-covered area to calculate the adhesion shear stress, update the cycle count, and trigger the next round of cooling ice covering and impedance acquisition according to the cycle logic.

[0120] The point cloud morphology acquisition and attenuation model fitting module is used to drive a laser confocal microscope to acquire three-dimensional point cloud data to calculate structural damage characteristic values, perform variable regression analysis, and establish a multidimensional coupled attenuation model based on the structural damage characteristic values, the evolution sequence of the interface electrochemical parameters, and the adhesion shear stress.

[0121] It should be noted that the functional division and information interaction between the various modules described above are logical, but in terms of physical implementation, they can be integrated on the same software platform or deployed in a distributed manner. The connections between them represent data flow and control flow, aiming to collaboratively achieve the objectives of this invention. The above descriptions are merely exemplary embodiments of this invention and should not be construed as limiting the scope of protection of this invention.

Claims

1. A method for testing the anti-icing performance of superhydrophobic surface structures in energy equipment, characterized in that, The method includes: A working electrode pattern is prepared on a superhydrophobic surface specimen using a conductive material deposition process. A physical connection loop is established and connected to an electrochemical workstation. Based on the hardware frequency response boundary data read by the electrochemical workstation, logarithmic interpolation is performed to generate an impedance spectrum scanning frequency point sequence list. The generation of the impedance spectrum scanning frequency point sequence list includes: transferring nano-silver conductive ink to the superhydrophobic surface specimen using a screen printing process, performing high-temperature curing treatment to form a grid-like working electrode pattern; connecting the grid-like working electrode pattern to the electrochemical workstation using a shielded coaxial cable and connecting it to an external grounded shielding box to establish an anti-interference physical connection loop; calling the electrochemical workstation's driver interface to obtain the frequency range extreme values, performing logarithmic discretization processing based on the number of sampling points per ten octave band to generate the impedance spectrum scanning frequency point sequence list. The superhydrophobic surface specimen was installed on the low-temperature environment chamber specimen holder. The cooling rate and target freezing temperature were set. The low-temperature environment chamber specimen holder was driven to perform cooling control and start spraying to form an ice layer. According to the impedance spectrum scanning frequency point sequence list, AC potential perturbation was applied sequentially. The potential response and current response were collected to calculate the complex impedance data sequence. Iterative fitting is performed on the complex impedance data sequence to construct an equivalent circuit topology. Based on the equivalent circuit topology, double-layer capacitance and charge transfer resistance feature values ​​are extracted, and an interface electrochemical parameter evolution sequence is constructed in time-stamp order. The construction of the interface electrochemical parameter evolution sequence in time-stamp order includes: connecting solution resistance elements in series to a parallel circuit based on double-layer capacitance and charge transfer resistance elements to define an equivalent circuit topology; processing the complex impedance data sequence using the complex least squares method, calculating the sum of squared residuals between the measured impedance and the model impedance, and performing parameter convergence calculation to complete iterative fitting; after convergence, double-layer capacitance and charge transfer resistance feature values ​​are read based on the equivalent circuit topology, and key-value pair mapping is performed with the sampling time points to construct the interface electrochemical parameter evolution sequence. The centrifugal rotary table is driven to perform uniformly accelerated rotation on the superhydrophobic surface specimen, capture the critical speed of ice peeling and the ice-covered area to calculate the adhesion shear stress, update the cycle count, and trigger the next round of cooling ice covering and impedance acquisition according to the cycle logic. A laser confocal microscope is used to acquire three-dimensional point cloud data to calculate structural damage characteristic values. Variable regression analysis is performed, and a multidimensional coupled attenuation model is established based on the structural damage characteristic values, the evolution sequence of the interface electrochemical parameters, and the adhesion shear stress.

2. The method for testing the anti-icing performance of superhydrophobic surface structures for energy equipment according to claim 1, characterized in that, The data sequence for acquiring potential and current responses to calculate complex impedance includes: The superhydrophobic surface specimen is pressed onto the thermally conductive bonding surface of the low-temperature environment chamber sample holder, and an active cooling operation is performed to trigger a spray ice-making action to form a surface icing state. The impedance spectrum scanning frequency sequence list is traversed, the potentiostat is controlled to output AC potential disturbance, and the time-domain current response signal flowing through the physical connection loop is synchronously captured using a current amplifier. A fast Fourier transform is performed on the AC potential disturbance and the time-domain current response signal to extract the voltage vector and current vector. The magnitude and phase angle of each frequency point are calculated by complex division to generate a complex impedance data sequence.

3. The method for testing the anti-icing performance of superhydrophobic surface structures for energy equipment according to claim 2, characterized in that, The process of performing active cooling and triggering spray ice-making includes: Thermally conductive silicone grease was coated on the back of the superhydrophobic surface specimen and pressed onto a semiconductor cooling chip, and a thermocouple feedback loop was connected. Based on the semiconductor cooling chip, the DC input current is adjusted to track the linear cooling curve, and the ultrasonic atomizer is driven to generate micron-level supercooled water mist to cover the superhydrophobic surface specimen.

4. The method for testing the anti-icing performance of superhydrophobic surface structures for energy equipment according to claim 1, characterized in that, The process of triggering the next round of cooling, icing, and impedance acquisition based on loop logic includes: The surface state of the superhydrophobic surface specimen is monitored using a high-speed camera. When ice layer displacement is detected, the instantaneous angular velocity of the centrifugal rotating table is locked as the critical rotation speed for ice layer peeling. The ice-covered area is calculated by image binarization processing, and the adhesion shear stress is calculated by combining the ice layer mass and the rotation radius. The current cycle count is read and compared with the preset maximum cycle count threshold. If the maximum cycle count threshold is not reached, the cycle count is incremented by one, and a reset command is sent to the low-temperature environment chamber sample holder to trigger the next round of cooling, icing and impedance acquisition.

5. The method for testing the anti-icing performance of superhydrophobic surface structures for energy equipment according to claim 1, characterized in that, The establishment of a multidimensional coupled attenuation model based on the structural damage characteristic values, the evolution sequence of interfacial electrochemical parameters, and the adhesion shear stress includes: The height matrix is ​​extracted from the three-dimensional point cloud data, the root mean square roughness increment and the change in peak-valley height difference are calculated, and structural damage feature values ​​are generated. The structural damage characteristic values, the evolution sequence of the interface electrochemical parameters, and the adhesion shear stress are normalized to construct a correlation analysis matrix and extract the principal component weights to generate a multidimensional coupled attenuation model.

6. The method for testing the anti-icing performance of superhydrophobic surface structures for energy equipment according to claim 5, characterized in that, The generated structural damage feature values ​​include: The spatial coordinates of the three-dimensional point cloud data are projected onto a uniform grid reference plane, the vertical depth values ​​of the grid nodes are extracted and arranged in rows and columns to construct a surface height matrix; The root mean square statistics and extreme value range search are performed on the surface height matrix to obtain the current morphological statistical parameters, and numerical difference operation is performed with the initial morphological statistical parameters to generate structural damage feature values.

7. The method for testing the anti-icing performance of superhydrophobic surface structures for energy equipment according to claim 1, characterized in that, The method further includes: extracting the characteristic value of the charge transfer resistance and the adhesion shear stress, performing numerical normalization and cross-correlation calculations, and generating an interface failure sensitivity index, which is used to evaluate the correlation between changes in interface electrochemical parameters and changes in adhesion shear stress.

8. A testing system for the anti-icing performance of superhydrophobic surface structures of energy equipment, applied to the testing method for the anti-icing performance of superhydrophobic surface structures of energy equipment as described in any one of claims 1-7, characterized in that, The system includes: The electrode preparation and frequency point table generation module is used to prepare working electrode patterns on superhydrophobic surface specimens using conductive material deposition processes, establish physical connection circuits and connect to an electrochemical workstation, read hardware frequency response boundary data based on the electrochemical workstation, perform logarithmic interpolation operations, and generate an impedance spectrum scanning frequency point sequence table. The low-temperature spray icing and impedance acquisition module is used to install the superhydrophobic surface specimen on the low-temperature environment chamber sample holder, set the cooling rate and target freezing temperature, drive the low-temperature environment chamber sample holder to perform cooling control and start spraying to form an ice layer, apply AC potential perturbation sequentially according to the impedance spectrum scanning frequency point sequence list, and collect potential response and current response to calculate complex impedance data sequence. The equivalent circuit fitting and parameter sequence generation module is used to perform iterative fitting on the complex impedance data sequence, construct the equivalent circuit topology, extract double-layer capacitance feature values ​​and charge transfer resistance feature values ​​based on the equivalent circuit topology, and construct the interface electrochemical parameter evolution sequence in time stamp order. The centrifugal peeling and adhesion shear stress calculation module is used to drive the centrifugal rotary table to perform uniformly accelerated rotation on the superhydrophobic surface specimen, capture the critical speed of ice peeling and the ice-covered area to calculate the adhesion shear stress, update the cycle count, and trigger the next round of cooling ice covering and impedance acquisition according to the cycle logic. The point cloud morphology acquisition and attenuation model fitting module is used to drive a laser confocal microscope to acquire three-dimensional point cloud data to calculate structural damage characteristic values, perform variable regression analysis, and establish a multidimensional coupled attenuation model based on the structural damage characteristic values, the evolution sequence of the interface electrochemical parameters, and the adhesion shear stress.

Images