Method for evaluating fluid drag reduction properties of microfluidic devices and related apparatus

Abstract

The application belongs to the technical field of microfluids, and discloses a fluid drag reduction characteristic evaluation method of a microfluid device and related equipment. The method comprises the following steps: acquiring topographic data and interfacial energy data of the microfluid device to be tested; constructing a model according to the topographic data and the interfacial energy data to obtain a microfluid device simulation model corresponding to the microfluid device to be tested; setting fluid boundary conditions corresponding to the topographic data and the interfacial energy data for the microfluid device simulation model to obtain wall wetting boundary condition information; and performing fluid simulation on the microfluid device simulation model based on the wall wetting boundary condition information to obtain fluid drag reduction characteristic evaluation parameters of the microfluid device to be tested. Through the method, the evaluation accuracy of the fluid drag reduction characteristic of the microfluid device is improved.

Description

Technical Field

[0001] This application relates to the technical field of microfluidics, and more specifically, to a method and related equipment for evaluating the fluid drag reduction characteristics of microfluidic devices. Background Technology

[0002] Microfluidic devices are devices with internal fluid channels (i.e., microfluidic channels) at the micrometer or nanometer scale. They exhibit enormous market potential and broad application prospects in numerous high-tech fields such as micro / nano manufacturing, novel displays, artificial intelligence, and biomedicine. Fluid control is one of the core critical issues in microfluidic devices, and regulating the solid-liquid frictional resistance of the microchannel walls plays a crucial role in achieving precise fluid control. However, currently, a practical and efficient evaluation method is lacking for assessing the drag reduction performance at the solid-liquid interface.

[0003] Current technologies face numerous challenges in evaluating the drag reduction properties of solid-liquid interfaces in microchannels. First, traditional experimental methods are typically costly and time-consuming. Each time a new surface material or structure needs evaluation, the microfluidic device must be re-fabricated and extensive experimental verification must be conducted, significantly limiting the efficiency of rapid iteration and optimization. Second, existing methods struggle to effectively separate the influence of multiple factors on drag reduction characteristics. The effect of microchannel walls on the solid-liquid interface is the result of a complex coupling of morphology and surface energy, and existing evaluation methods often fail to distinguish the individual contributions of morphology and surface energy to drag reduction, leading to an insufficient understanding of the drag reduction mechanism.

[0004] Furthermore, existing evaluation methods often oversimplify wall conditions, failing to fully consider the actual rough profile on the wall and the influence of multiphase interfaces on fluid flow. This results in insufficient accuracy of the prediction results, making it difficult to accurately reflect the fluid drag reduction performance under real operating conditions.

[0005] To address the aforementioned issues, existing technologies urgently need improvement. Summary of the Invention

[0006] The purpose of this application is to provide a method and related equipment for evaluating the fluid drag reduction characteristics of microfluidic devices. By using wall wetting boundary condition information, fluid simulation is performed on the simulation model of the microfluidic device to obtain evaluation parameters of the fluid drag reduction characteristics of the microfluidic device under test. This solves the problems of existing methods for evaluating the fluid drag reduction characteristics of microfluidic devices, which are difficult to accurately evaluate due to high cost, long cycle, difficulty in effectively separating the influence of multiple factors and insufficient consideration of wall conditions. This method can quantitatively evaluate the local flow characteristics of the wall through simulation, thereby improving the evaluation accuracy of the fluid drag reduction characteristics of microfluidic devices.

[0007] In a first aspect, this application provides a method for evaluating the fluid drag reduction characteristics of microfluidic devices, including:

[0008] Acquire morphology and interfacial energy data of the microfluidic device under test;

[0009] Based on the morphology data and the interface energy data, a model is constructed to obtain the microfluidic device simulation model corresponding to the microfluidic device under test.

[0010] Set fluid boundary conditions corresponding to the morphology data and the interfacial energy data for the simulation model of the microfluidic device to obtain wall wetting boundary condition information;

[0011] Based on the wall wetting boundary condition information, fluid simulation is performed on the microfluidic device simulation model to obtain the fluid drag reduction characteristic evaluation parameters of the microfluidic device under test.

[0012] The fluid drag reduction characteristic evaluation method for microfluidic devices provided in this application can evaluate the fluid drag reduction characteristics of microfluidic devices. By using wall wetting boundary condition information, fluid simulation is performed on the simulation model of the microfluidic device to obtain the evaluation parameters of the fluid drag reduction characteristics of the microfluidic device under test. This method solves the problems of existing methods for evaluating the fluid drag reduction characteristics of microfluidic devices, which are difficult to accurately evaluate due to high cost, long cycle, difficulty in effectively separating the influence of multiple factors, and insufficient consideration of wall conditions. It can quantitatively evaluate the local flow characteristics of the wall through simulation, thereby improving the evaluation accuracy of the fluid drag reduction characteristics of microfluidic devices.

[0013] Optionally, the morphology and interfacial energy data of the microfluidic device under test are acquired, including:

[0014] The surface of the microfluidic device under test is scanned to obtain the morphological data of the microfluidic device under test;

[0015] A microchannel fluid of the corresponding fluid type is set for the microfluidic device under test, and the contact angle of the microchannel fluid is measured to obtain the contact angle data of the microchannel fluid;

[0016] The interfacial energy data of the microfluidic device under test is obtained by calculating based on the contact angle data.

[0017] Optionally, the interfacial energy data of the microfluidic device under test is calculated based on the contact angle data, including:

[0018] The contact angle data is input into a preset surface energy model for calculation to obtain the surface energy data of the microfluidic device under test.

[0019] The surface energy data is input into a preset interface energy model for calculation to obtain the interface energy data of the microfluidic device under test.

[0020] Optionally, the morphology data includes the overall dimensions of the microfluidic device and the dimensions of the microchannels; based on the morphology data and the interfacial energy data, a model is constructed to obtain a simulation model of the microfluidic device corresponding to the microfluidic device under test, including:

[0021] Obtain the preset initial microfluidic device simulation model;

[0022] Based on the overall device size data, the microchannel size data, and the interface energy data, the preset initial microfluidic device simulation model is adjusted to obtain the microfluidic device simulation model corresponding to the microfluidic device under test.

[0023] Optionally, the morphology data further includes surface roughness data; fluid boundary conditions corresponding to the morphology data and the interfacial energy data are set for the microfluidic device simulation model to obtain wall wetting boundary condition information, including:

[0024] Based on the microchannel size data, the microchannel location region and wall region are determined in the microfluidic device simulation model;

[0025] Set roughness contour information for the wall region that corresponds to the surface roughness data;

[0026] Set the microchannel location region to a fluid flow state and set the corresponding fluid flow conditions;

[0027] Based on the interface energy data, corresponding contact angle boundary conditions are set for the contact boundary between the microchannel location region and the wall region.

[0028] The rough contour information, the fluid flow conditions, and the contact angle boundary conditions are summarized and processed to obtain the wall wetting boundary condition information.

[0029] The fluid drag reduction characteristic evaluation method for microfluidic devices provided in this application can evaluate the fluid drag reduction characteristics of microfluidic devices. Through the process of setting fluid boundary conditions, especially by introducing surface roughness data and contact angle boundary conditions, the simulation can more comprehensively consider the actual wall conditions and the influence of multiphase interfaces on fluid flow, thereby improving the accuracy of the evaluation results.

[0030] Optionally, based on the wall wetting boundary condition information, fluid simulation is performed on the microfluidic device simulation model to obtain the fluid drag reduction characteristic evaluation parameters of the microfluidic device under test, including:

[0031] Based on fluid dynamics, the microfluidic device simulation model is meshed to obtain the meshed microfluidic device simulation model.

[0032] Based on the wall wetting boundary condition information, fluid simulation is performed on the microfluidic device simulation model to obtain the average flow velocity of the microchannel and the average flow velocity of the wall of the microfluidic device under test.

[0033] Based on the difference between the average flow velocity of the microchannel and the average flow velocity of the wall, the wall velocity loss rate of the microfluidic device under test is calculated, and the fluid drag reduction characteristic evaluation parameters of the microfluidic device under test are obtained.

[0034] The fluid drag reduction characteristic evaluation method for microfluidic devices provided in this application can evaluate the fluid drag reduction characteristics of microfluidic devices. By calculating the specific calculation method of the fluid drag reduction characteristic evaluation parameters, the wall velocity loss rate can be calculated, which can directly quantify the local flow characteristics of the wall and provide more detailed and comprehensive information on fluid drag reduction characteristics.

[0035] Optionally, based on the wall wetting boundary condition information, fluid simulation is performed on the microfluidic device simulation model to obtain the average flow velocity of the microchannel and the average flow velocity of the wall of the microfluidic device under test, including:

[0036] Based on the wall wetting boundary condition information, fluid simulation is performed on the microfluidic device simulation model;

[0037] During fluid simulation, when the microchannel location region meets the preset fluid stability conditions, the microchannel fluid velocity in the microchannel location region and the wall velocity in the wall region are extracted.

[0038] The average values ​​of the microchannel fluid velocity and the wall velocity are calculated respectively to obtain the average microchannel velocity and the average wall velocity of the microfluidic device under test.

[0039] Secondly, this application provides a device for evaluating the fluid drag reduction characteristics of microfluidic devices, comprising:

[0040] The acquisition module is used to acquire the morphology data and interfacial energy data of the microfluidic device under test.

[0041] The construction module is used to construct a model based on the morphology data and the interface energy data to obtain a microfluidic device simulation model corresponding to the microfluidic device under test.

[0042] The setting module is used to set fluid boundary conditions corresponding to the morphology data and the interfacial energy data for the microfluidic device simulation model, so as to obtain wall wetting boundary condition information.

[0043] The simulation module is used to perform fluid simulation on the simulation model of the microfluidic device based on the wall wetting boundary condition information, and obtain the fluid drag reduction characteristic evaluation parameters of the microfluidic device under test.

[0044] This device for evaluating the fluid drag reduction characteristics of microfluidic devices uses wall wetting boundary condition information to perform fluid simulation on the simulation model of the microfluidic device, obtaining evaluation parameters for the fluid drag reduction characteristics of the microfluidic device under test. It solves the problems of existing methods for evaluating the fluid drag reduction characteristics of microfluidic devices, which are difficult to accurately evaluate due to high cost, long cycle, difficulty in effectively separating the influence of multiple factors and insufficient consideration of wall conditions. It can quantitatively evaluate the local flow characteristics of the wall through simulation, thus improving the evaluation accuracy of the fluid drag reduction characteristics of microfluidic devices.

[0045] Thirdly, this application provides an electronic device, including a processor and a memory, wherein the memory stores a computer program executable by the processor, and when the processor executes the computer program, it runs the steps in the fluid drag reduction characteristic evaluation method for microfluidic devices described above.

[0046] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the steps in the fluid drag reduction characteristic evaluation method for microfluidic devices described above.

[0047] Beneficial effects: The fluid drag reduction characteristic evaluation method and related equipment for microfluidic devices provided in this application use wall wetting boundary condition information to perform fluid simulation on the simulation model of the microfluidic device, thereby obtaining the fluid drag reduction characteristic evaluation parameters of the microfluidic device under test. This solves the problems of existing microfluidic device fluid drag reduction characteristic evaluation methods being difficult to accurately evaluate the fluid drag reduction characteristics of microfluidic devices due to high cost, long cycle, difficulty in effectively separating the influence of multiple factors, and insufficient consideration of wall conditions. It can quantitatively evaluate the local flow characteristics of the wall through simulation, thereby improving the evaluation accuracy of the fluid drag reduction characteristics of microfluidic devices. Attached Figure Description

[0048] Figure 1 A flowchart illustrating the method for evaluating the fluid drag reduction characteristics of microfluidic devices provided in this application embodiment.

[0049] Figure 2 This is a schematic diagram of the structure of the fluid drag reduction characteristic evaluation device for microfluidic devices provided in the embodiments of this application.

[0050] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0051] Labeling Explanation: 1. Acquisition Module; 2. Construction Module; 3. Setting Module; 4. Simulation Module; 301. Processor; 302. Memory; 303. Communication Bus. Detailed Implementation

[0052] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0053] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0054] Please refer to Figure 1 , Figure 1 This application discloses a method for evaluating the fluid drag reduction characteristics of a microfluidic device, as described in some embodiments. The method includes the following steps:

[0055] Step S101: Obtain the morphology data and interfacial energy data of the microfluidic device under test;

[0056] Step S102: Based on the morphology data and interfacial energy data, a model is constructed to obtain the microfluidic device simulation model corresponding to the microfluidic device under test.

[0057] Step S103: Set fluid boundary conditions corresponding to morphology data and interfacial energy data for the microfluidic device simulation model to obtain wall wetting boundary condition information;

[0058] Step S104: Based on the wall wetting boundary condition information, perform fluid simulation on the microfluidic device simulation model to obtain the fluid drag reduction characteristic evaluation parameters of the microfluidic device under test.

[0059] This method for evaluating the drag reduction characteristics of microfluidic devices uses wall wetting boundary condition information to perform fluid simulation on a microfluidic device simulation model, obtaining evaluation parameters for the drag reduction characteristics of the microfluidic device under test. It solves the problems of existing methods for evaluating the drag reduction characteristics of microfluidic devices, which are difficult to accurately evaluate due to high cost, long cycle, difficulty in effectively separating the influence of multiple factors, and insufficient consideration of wall conditions. It can quantitatively evaluate the local flow characteristics of the wall through simulation, thus improving the evaluation accuracy of the drag reduction characteristics of microfluidic devices.

[0060] Specifically, in step S101, the morphology data and interfacial energy data of the microfluidic device under test are acquired, including:

[0061] The surface of the microfluidic device under test is scanned to obtain the morphological data of the microfluidic device under test;

[0062] Set up a microchannel fluid of the corresponding fluid type for the microfluidic device under test, and measure the contact angle of the microchannel fluid to obtain the contact angle data of the microchannel fluid;

[0063] The interfacial energy data of the microfluidic device under test is obtained by calculating based on the contact angle data.

[0064] In step S101, existing non-contact optical measurement methods, such as laser profilometers, can be used to scan the surface of the microfluidic device point by point or line by line to accurately obtain its three-dimensional morphology information. The morphology data may include detailed information such as the overall dimensions of the microfluidic device (e.g., the length, width, and height of the microfluidic device), surface roughness data, and microchannel size data (e.g., the geometry, depth, and width of the microchannel).

[0065] For the microfluidic channel fluid (i.e., fluid) in the microfluidic device under test, at least two fluid types with known surface tensions (such as water, oil, 1-bromonaphthalene, etc.) are set up. Using existing methods such as titration or tilting plate method, the corresponding fluid types are dropped onto the surface of the microfluidic device under test. An optical system is used to capture the contact angle image formed between the droplet and the solid surface, and the contact angle data of the microfluidic channel fluid is measured. The contact angle data refers to the angle between the solid-liquid interface, through the liquid interior, and at the gas-liquid interface at the solid-liquid-gas three-phase interface. The contact angle data is an important parameter characterizing the wettability of the solid surface and directly reflects the interaction between the solid and liquid interfaces.

[0066] Specifically, in step S101, the interfacial energy data of the microfluidic device under test is calculated based on the contact angle data, including:

[0067] The contact angle data is input into a preset surface energy model for calculation to obtain the surface energy data of the microfluidic device under test.

[0068] The surface energy data is input into a preset interface energy model for calculation to obtain the interface energy data of the microfluidic device under test.

[0069] In step S101, the contact angle data is input into a preset surface energy model for calculation to obtain the surface energy data of the microfluidic device under test. The surface energy data includes the surface free energy, dispersion component, and polar component of the microfluidic device surface. The preset surface energy model is a mathematical model based on thermodynamic principles, such as the Owens-Wendt model, Zisman model, or Fowkes model. Its purpose is to calculate the surface energy data of the microfluidic device under test based on the contact angle data. For example, if the preset surface energy model is the Fowkes model, then the preset surface energy model is as follows:

[0070] ;

[0071] ;

[0072] in, This is contact angle data; The surface free energy of a liquid (fluid); The dispersive component of the liquid; This refers to the polar component of the liquid; The surface free energy of the microfluidic device surface; The dispersive component of the surface of the microfluidic device; The polar component represents the surface energy of the microfluidic device. The surface free energy, dispersive component, and polar component of the liquid can be obtained in advance from the corresponding database (or by searching relevant literature) based on the fluid type. The dispersive and polar components of the microfluidic device surface can be calculated by inputting the surface free energy, dispersive component, and polar component of at least two fluid types with known surface tensions into the aforementioned surface energy model and then solving a series of equations.

[0073] Surface energy data is input into a preset interface energy model for calculation to obtain the interface energy data of the microfluidic device under test. Interface energy data refers to the extra free energy generated at the interface due to atomic arrangement distortion within the crystal; here, it describes the energy of solid-liquid interface interaction. The preset interface energy model is a mathematical model based on thermodynamic principles, such as the Owens-Wendt model, Zisman model, or Fowkes model. Its purpose is to calculate the interface energy data of the microfluidic device under test based on the surface energy data. For example, if the preset interface energy model is the Owens-Wendt model, then the specific preset interface energy model is as follows:

[0074] ;

[0075] in, This is for interface data.

[0076] Specifically, in step S102, a model is constructed based on the morphology data and interfacial energy data to obtain a simulation model of the microfluidic device corresponding to the microfluidic device under test, including:

[0077] Obtain the preset initial microfluidic device simulation model;

[0078] Based on the overall device size data, microchannel size data, and interface energy data, the preset initial microfluidic device simulation model is adjusted to obtain the microfluidic device simulation model corresponding to the microfluidic device under test.

[0079] In step S102, a preset initial microfluidic device simulation model is obtained in simulation software. This initial microfluidic device simulation model can be obtained by constructing a two-dimensional simulation model using the two-phase flow field method. The two-phase flow field method is an advanced numerical simulation technique aimed at accurately describing and simulating the interfacial evolution process between two or more immiscible fluids, and is particularly suitable for the complex behavior of gas-liquid or liquid-liquid two-phase flows within microchannels. The two-dimensional simulation model constructed using this method achieves a balance between computational efficiency and simulation accuracy, especially when the channel changes in one dimension insignificantly or negligibly.

[0080] By utilizing overall device size data and microchannel size data, the initial microfluidic device simulation model is adjusted to precisely define the geometric boundaries and internal flow channel structure of the simulation model, ensuring dimensional consistency between the model and the actual device. Interfacial energy data is used to set appropriate interfacial characteristics in the simulation model, thereby accurately reflecting the interaction between the fluid and the microchannel walls, which is crucial for simulating fluid drag reduction behavior.

[0081] Specifically, in step S103, fluid boundary conditions corresponding to the morphology data and interfacial energy data are set for the microfluidic device simulation model to obtain wall wetting boundary condition information, including:

[0082] Based on the microchannel size data, the location region and wall region of the microchannel are determined in the simulation model of the microfluidic device;

[0083] Set roughness profile information for the wall area that corresponds to the surface roughness data;

[0084] Set the microchannel location region to a fluid flow state and set the corresponding fluid flow conditions;

[0085] Based on the interfacial energy data, corresponding contact angle boundary conditions are set for the contact boundaries of the microchannel location region and the wall region.

[0086] The rough profile information, fluid flow conditions, and contact angle boundary conditions are summarized and processed to obtain the wall wetting boundary condition information.

[0087] In step S103, the microchannel location region and the wall region are clearly defined in the simulation or modeling software based on the microchannel size data. The microchannel location region refers to the space where the fluid actually flows, while the wall region is the solid boundary in contact with the fluid. This division is the basis for setting precise boundary conditions.

[0088] The actual measured surface roughness data is mapped onto the wall surface of the simulation model to obtain roughness profile information. The purpose is to simulate the obstruction effect of real rough surfaces on fluid flow and the influence of micro-wetting behavior.

[0089] The microchannel region is set to a fluid flow state, and corresponding fluid flow conditions are set. Fluid flow conditions include, but are not limited to, parameters such as inlet location, outlet pressure, fluid velocity, fluid direction, fluid density, and viscosity. The purpose is to simulate the macroscopic flow behavior of fluid within the microchannel.

[0090] Based on interfacial energy data, corresponding contact angle boundary conditions are set for the contact boundaries of the microchannel location region and the wall region. Contact angle boundary conditions are key parameters describing the wetting characteristics of fluids on solid surfaces, aiming to reflect the spreading or contracting behavior of the fluid on the microchannel wall. This is crucial for simulating the drag reduction effect of superhydrophobic or superhydrophilic surfaces. For example, the top and bottom edges of the microchannel location region are both set as wetting walls with non-Gaussian rough profiles, the solid-liquid interface of the microchannel location region is set as slip, and the wetting wall is described by Young's equation, which is specifically:

[0091] ;

[0092] in, To simulate contact angle; For solid-gas interface energy data, and surface free energy of microfluidic device surfaces. Equal, that is .

[0093] Specifically, the simulated contact angle is a wettability parameter obtained by converting the experimentally calculated solid-gas and solid-liquid interfacial energies through Young's equation. This parameter is input into simulation software as a contact angle boundary condition to quantitatively describe the spreading and sliding behavior of fluids on a real wall profile. It is the core link between interfacial energy measurement and the evaluation of drag reduction characteristics of microchannel fluids, and also a key technical means to achieve the separation analysis of morphology and surface chemical factors.

[0094] By summarizing the above boundary conditions, we can obtain information on wall wetting boundary conditions, which enables fluid simulation to more accurately capture the fluid drag reduction characteristics of microfluidic devices.

[0095] Specifically, in step S104, based on the wall wetting boundary condition information, a fluid simulation is performed on the microfluidic device simulation model to obtain the fluid drag reduction characteristic evaluation parameters of the microfluidic device under test, including:

[0096] Based on fluid dynamics, the simulation model of the microfluidic device is meshed to obtain the meshed microfluidic device simulation model.

[0097] Based on the wall wetting boundary condition information, fluid simulation is performed on the microfluidic device simulation model to obtain the average flow velocity of the microchannel and the average flow velocity of the wall of the microfluidic device under test.

[0098] Based on the difference between the average flow velocity of the microchannel and the average flow velocity of the wall, the wall velocity loss rate of the microfluidic device under test is calculated, and the evaluation parameters of the fluid drag reduction characteristics of the microfluidic device under test are obtained.

[0099] In step S104, before performing fluid simulation, the microfluidic device simulation model needs to be meshed based on fluid dynamics principles. Mesh generation is the process of discretizing a continuous simulation region into a finite number of small elements, with the aim of solving fluid dynamics equations on these discrete elements. The quality of the mesh (such as mesh density, orthogonality, aspect ratio, etc.) directly affects the accuracy and computational efficiency of the simulation results. Typically, finer meshes are used near walls or in regions with large fluid velocity gradients to capture the details of fluid behavior.

[0100] Specifically, in step S104, based on the wall wetting boundary condition information, a fluid simulation is performed on the microfluidic device simulation model to obtain the average flow velocity of the microchannel and the average flow velocity of the wall of the microfluidic device under test, including:

[0101] Fluid simulation is performed on the simulation model of the microfluidic device based on the wall wetting boundary condition information.

[0102] During fluid simulation, when the microchannel location region meets the preset fluid stability conditions, the microchannel fluid velocity in the microchannel location region and the wall velocity in the wall region are extracted.

[0103] The average values ​​of the microchannel fluid velocity and the wall velocity are calculated separately to obtain the average microchannel velocity and the average wall velocity of the microfluidic device under test.

[0104] In step S104, fluid simulation is initiated on the microfluidic device simulation model in the simulation software based on the wall wetting boundary condition information (the fluid simulation process is an automatic execution process of the simulation software and will not be described in detail here). During the fluid simulation of the microfluidic device simulation model, the fluid velocity can be extracted at the centerline of the microchannel or a specific cross-section to obtain the velocity distribution of the fluid within the microchannel. When the fluid flow is not yet stable, the velocity may exhibit large instantaneous fluctuations, and the extracted data at this time cannot accurately reflect the true fluid behavior of the microfluidic device. More representative instantaneous fluid velocity data can only be obtained when the fluid reaches a stable state. Therefore, when the microchannel location region meets the preset fluid stability conditions, the microchannel fluid velocity in the microchannel location region and the wall velocity in the wall region are extracted (the wall velocity in the wall region can be obtained by setting a multiphase interface tracking probe on the wall region). The fluid stability condition refers to a relatively stable state in which the fluid flow in the microchannel reaches a state of equilibrium. For example, the inlet and outlet flow rates tend to be constant (the difference between the inlet and outlet flow rates is less than or equal to a preset flow stability threshold), or the velocity distribution within the microchannel no longer changes significantly (i.e., the standard deviation of the velocity at each location within the microchannel is less than or equal to a preset velocity stability threshold). In this case, the inlet and outlet fluid velocities are almost identical (i.e., the difference between the inlet and outlet fluid velocities is less than or equal to a preset velocity stability threshold), and the microchannel fluid velocity is also almost identical to the inlet (or outlet) fluid velocity (i.e., the difference between the microchannel fluid velocity and the inlet fluid velocity, and the difference between the microchannel fluid velocity and the outlet fluid velocity, are both less than or equal to the preset velocity stability threshold). This condition ensures that the extracted fluid velocity data is representative and accurately reflects the fluid behavior of the microchannel under normal operating conditions. The preset flow stability threshold and preset velocity stability threshold can be set according to actual conditions.

[0105] The average flow velocity in the microchannel and the average flow velocity at the wall are calculated separately to obtain the average flow velocity in the microfluidic device under test. This can be done using either time-averaging or spatial-averaging methods. For example, after the fluid reaches a steady state, the fluid velocity can be sampled multiple times over a period of time and the average value can be taken. Alternatively, multiple representative points can be selected in the microchannel and wall regions for velocity measurement and the average value can be taken. Obtaining the average value eliminates the influence of instantaneous fluctuations and yields a more statistically significant average flow velocity.

[0106] By calculating the difference between the average flow velocity in the microchannel and the average flow velocity at the wall, the wall velocity loss rate can be directly quantified. This allows for a direct quantification of the impact of wall friction on fluid velocity, and transforms this impact into a standardized evaluation parameter (i.e., the wall velocity loss rate). This parameter accurately reflects the fluid drag reduction characteristics of the microfluidic device, thus providing an evaluation parameter for the fluid drag reduction characteristics of the microfluidic device under test. The specific formula for calculating the wall velocity loss rate (fluid drag reduction characteristic evaluation parameter) is as follows:

[0107] ;

[0108] in, Wall velocity loss rate; The average flow velocity of the microchannel (i.e., the inlet fluid velocity). The average flow velocity at the wall surface is given.

[0109] In some alternative embodiments, the drag reduction characteristics of microfluidic devices made of different materials (such as alumina ceramics, nickel plating, gold plating, and single-crystal silicon) or with different fluid types (such as water or 1-bromonaphthalene) can be compared by calculating the wall velocity loss rate. Alternatively, by using the controlled variable method, different parameters (such as morphology data, interfacial energy data, and wall wetting boundary condition information) can be adjusted to obtain different simulation results. The impact of these different parameters on the evaluation parameters of the drag reduction characteristics can then be analyzed based on the simulation results. Thus, these methods provide guidance for optimizing the drag reduction surface of microchannels.

[0110] For example, by calculating the wall velocity loss rate of microfluidic devices made of different materials and with different fluid types, the fluid drag reduction characteristics of microfluidic devices made of different materials and with different fluid types can be compared. The comparison results of the evaluation parameters of the fluid drag reduction characteristics of microfluidic devices are shown in Table 1:

[0111] Table 1 Comparison of evaluation parameters for fluid drag reduction characteristics of microfluidic devices

[0112]

[0113] Table 1 shows that, comparing microfluidic devices made of alumina ceramic, nickel plating, and monocrystalline silicon, the monocrystalline silicon microfluidic device exhibits the lowest wall velocity loss rate, indicating that it has the best drag reduction characteristics. Comparing microfluidic devices using 1-naphthalene bromide and water, the 1-naphthalene bromide microfluidic device also shows the lowest wall velocity loss rate, suggesting that it also has the best drag reduction characteristics.

[0114] As shown above, the proposed method for evaluating the fluid drag reduction characteristics of microfluidic devices involves acquiring the morphology and interfacial energy data of the microfluidic device under test. Based on these data, a model is constructed to obtain a simulation model of the microfluidic device. Fluid boundary conditions corresponding to the morphology and interfacial energy data are then set for the simulation model to obtain wall wetting boundary condition information. Based on this information, fluid simulation is performed on the simulation model to obtain the evaluation parameters for the fluid drag reduction characteristics of the microfluidic device under test. This method addresses the problems of existing methods for evaluating the fluid drag reduction characteristics of microfluidic devices, which suffer from high costs, long cycles, difficulty in effectively separating the influence of multiple factors, and insufficient consideration of wall conditions. It enables the quantitative evaluation of local flow characteristics at the wall through simulation, improving the accuracy of the evaluation of the fluid drag reduction characteristics of microfluidic devices.

[0115] refer to Figure 2 This application provides a device for evaluating the fluid drag reduction characteristics of microfluidic devices, used to evaluate the fluid drag reduction characteristics of microfluidic devices, including:

[0116] Acquisition module 1 is used to acquire the morphology data and interfacial energy data of the microfluidic device under test;

[0117] Module 2 is used to build a model based on morphology data and interface energy data to obtain a simulation model of the microfluidic device corresponding to the microfluidic device under test.

[0118] Module 3 is used to set fluid boundary conditions corresponding to morphology data and interfacial energy data for the simulation model of microfluidic devices, and to obtain wall wetting boundary condition information.

[0119] Simulation module 4 is used to perform fluid simulation on the simulation model of the microfluidic device based on the wall wetting boundary condition information, and obtain the evaluation parameters of the fluid drag reduction characteristics of the microfluidic device under test.

[0120] This device for evaluating the fluid drag reduction characteristics of microfluidic devices uses wall wetting boundary condition information to perform fluid simulation on the simulation model of the microfluidic device, obtaining evaluation parameters for the fluid drag reduction characteristics of the microfluidic device under test. It solves the problems of existing methods for evaluating the fluid drag reduction characteristics of microfluidic devices, which are difficult to accurately evaluate due to high cost, long cycle, difficulty in effectively separating the influence of multiple factors and insufficient consideration of wall conditions. It can quantitatively evaluate the local flow characteristics of the wall through simulation, thus improving the evaluation accuracy of the fluid drag reduction characteristics of microfluidic devices.

[0121] Specifically, when acquiring the morphology data and interfacial energy data of the microfluidic device under test, module 1 performs the following:

[0122] The surface of the microfluidic device under test is scanned to obtain the morphological data of the microfluidic device under test;

[0123] Set up a microchannel fluid of the corresponding fluid type for the microfluidic device under test, and measure the contact angle of the microchannel fluid to obtain the contact angle data of the microchannel fluid;

[0124] The interfacial energy data of the microfluidic device under test is obtained by calculating based on the contact angle data.

[0125] When module 1 is executed, it can utilize existing non-contact optical measurement methods, such as using a laser profilometer, to scan the surface of the microfluidic device point by point or line by line, thereby accurately acquiring its three-dimensional morphology information. The morphology data can include detailed information such as the overall dimensions of the microfluidic device (e.g., the length, width, and height of the microfluidic device), surface roughness data, and microchannel size data (e.g., the geometry, depth, and width of the microchannel).

[0126] For the microfluidic channel fluid (i.e., fluid) in the microfluidic device under test, at least two fluid types with known surface tensions (such as water, oil, 1-bromonaphthalene, etc.) are set up. Using existing methods such as titration or tilting plate method, the corresponding fluid types are dropped onto the surface of the microfluidic device under test. An optical system is used to capture the contact angle image formed between the droplet and the solid surface, and the contact angle data of the microfluidic channel fluid is measured. The contact angle data refers to the angle between the solid-liquid interface, through the liquid interior, and at the gas-liquid interface at the solid-liquid-gas three-phase interface. The contact angle data is an important parameter characterizing the wettability of the solid surface and directly reflects the interaction between the solid and liquid interfaces.

[0127] Specifically, when module 1 calculates the interfacial energy data of the microfluidic device under test based on the contact angle data, it executes the following:

[0128] The contact angle data is input into a preset surface energy model for calculation to obtain the surface energy data of the microfluidic device under test.

[0129] The surface energy data is input into a preset interface energy model for calculation to obtain the interface energy data of the microfluidic device under test.

[0130] When module 1 is executed, it inputs the contact angle data into a preset surface energy model for calculation, obtaining the surface energy data of the microfluidic device under test. The surface energy data includes the surface free energy, dispersion component, and polar component of the microfluidic device surface. The preset surface energy model is a mathematical model based on thermodynamic principles, such as the Owens-Wendt model, Zisman model, or Fowkes model. Its purpose is to calculate the surface energy data of the microfluidic device under test based on the contact angle data. For example, if the preset surface energy model is the Fowkes model, then the specific preset surface energy model is as follows:

[0131] ;

[0132] ;

[0133] in, This is contact angle data; The surface free energy of a liquid (fluid); The dispersive component of the liquid; This refers to the polar component of the liquid; The surface free energy of the microfluidic device surface; The dispersive component of the surface of the microfluidic device; The polar component represents the surface energy of the microfluidic device. The surface free energy, dispersive component, and polar component of the liquid can be obtained in advance from the corresponding database (or by searching relevant literature) based on the fluid type. The dispersive and polar components of the microfluidic device surface can be calculated by inputting the surface free energy, dispersive component, and polar component of at least two fluid types with known surface tensions into the aforementioned surface energy model and then solving a series of equations.

[0134] Surface energy data is input into a preset interface energy model for calculation to obtain the interface energy data of the microfluidic device under test. Interface energy data refers to the extra free energy generated at the interface due to atomic arrangement distortion within the crystal; here, it describes the energy of solid-liquid interface interaction. The preset interface energy model is a mathematical model based on thermodynamic principles, such as the Owens-Wendt model, Zisman model, or Fowkes model. Its purpose is to calculate the interface energy data of the microfluidic device under test based on the surface energy data. For example, if the preset interface energy model is the Owens-Wendt model, then the specific preset interface energy model is as follows:

[0135] ;

[0136] in, This is for interface data.

[0137] Specifically, when module 2 constructs a model based on morphology data and interfacial energy data to obtain a simulation model of the microfluidic device corresponding to the microfluidic device under test, it executes the following:

[0138] Obtain the preset initial microfluidic device simulation model;

[0139] Based on the overall device size data, microchannel size data, and interface energy data, the preset initial microfluidic device simulation model is adjusted to obtain the microfluidic device simulation model corresponding to the microfluidic device under test.

[0140] When module 2 is executed, it acquires a preset initial microfluidic device simulation model from the simulation software. This initial microfluidic device simulation model can be obtained by constructing a two-dimensional simulation model using the two-phase flow field method. The two-phase flow field method is an advanced numerical simulation technique aimed at accurately describing and simulating the interfacial evolution process between two or more immiscible fluids, and is particularly suitable for the complex behavior of gas-liquid or liquid-liquid two-phase flows within microchannels. The two-dimensional simulation model constructed using this method achieves a balance between computational efficiency and simulation accuracy, especially when the channel changes in one dimension insignificantly or negligibly.

[0141] By utilizing overall device size data and microchannel size data, the initial microfluidic device simulation model is adjusted to precisely define the geometric boundaries and internal flow channel structure of the simulation model, ensuring dimensional consistency between the model and the actual device. Interfacial energy data is used to set appropriate interfacial characteristics in the simulation model, thereby accurately reflecting the interaction between the fluid and the microchannel walls, which is crucial for simulating fluid drag reduction behavior.

[0142] Specifically, when setting the fluid boundary conditions corresponding to the morphology data and interfacial energy data for the microfluidic device simulation model and obtaining the wall wetting boundary condition information, module 3 executes the following:

[0143] Based on the microchannel size data, the location region and wall region of the microchannel are determined in the simulation model of the microfluidic device;

[0144] Set roughness profile information for the wall area that corresponds to the surface roughness data;

[0145] Set the microchannel location region to a fluid flow state and set the corresponding fluid flow conditions;

[0146] Based on the interfacial energy data, corresponding contact angle boundary conditions are set for the contact boundaries of the microchannel location region and the wall region.

[0147] The rough profile information, fluid flow conditions, and contact angle boundary conditions are summarized and processed to obtain the wall wetting boundary condition information.

[0148] When module 3 is executed, it clearly delineates the microchannel location region and the wall region in the simulation software based on the microchannel size data. The microchannel location region refers to the space where the fluid actually flows, while the wall region is the solid boundary in contact with the fluid. This division is the basis for setting precise boundary conditions.

[0149] The actual measured surface roughness data is mapped onto the wall surface of the simulation model to obtain roughness profile information. The purpose is to simulate the obstruction effect of real rough surfaces on fluid flow and the influence of micro-wetting behavior.

[0150] The microchannel region is set to a fluid flow state, and corresponding fluid flow conditions are set. Fluid flow conditions include, but are not limited to, parameters such as inlet location, outlet pressure, fluid velocity, fluid direction, fluid density, and viscosity. The purpose is to simulate the macroscopic flow behavior of fluid within the microchannel.

[0151] Based on interfacial energy data, corresponding contact angle boundary conditions are set for the contact boundaries of the microchannel location region and the wall region. Contact angle boundary conditions are key parameters describing the wetting characteristics of fluids on solid surfaces, aiming to reflect the spreading or contracting behavior of the fluid on the microchannel wall. This is crucial for simulating the drag reduction effect of superhydrophobic or superhydrophilic surfaces. For example, the top and bottom edges of the microchannel location region are both set as wetting walls with non-Gaussian rough profiles, the solid-liquid interface of the microchannel location region is set as slip, and the wetting wall is described by Young's equation, which is specifically:

[0152] ;

[0153] in, To simulate contact angle; For solid-gas interface energy data, and surface free energy of microfluidic device surfaces. Equal, that is .

[0154] Specifically, the simulated contact angle is a wettability parameter obtained by converting the experimentally calculated solid-gas and solid-liquid interfacial energies through Young's equation. This parameter is input into simulation software as a contact angle boundary condition to quantitatively describe the spreading and sliding behavior of fluids on a real wall profile. It is the core link between interfacial energy measurement and the evaluation of drag reduction characteristics of microchannel fluids, and also a key technical means to achieve the separation analysis of morphology and surface chemical factors.

[0155] By summarizing the above boundary conditions, we can obtain information on wall wetting boundary conditions, which enables fluid simulation to more accurately capture the fluid drag reduction characteristics of microfluidic devices.

[0156] Specifically, when simulation module 4 performs fluid simulation on the microfluidic device simulation model based on wall wetting boundary condition information to obtain the fluid drag reduction characteristic evaluation parameters of the microfluidic device under test, it executes the following:

[0157] Based on fluid dynamics, the simulation model of the microfluidic device is meshed to obtain the meshed microfluidic device simulation model.

[0158] Based on the wall wetting boundary condition information, fluid simulation is performed on the microfluidic device simulation model to obtain the average flow velocity of the microchannel and the average flow velocity of the wall of the microfluidic device under test.

[0159] Based on the difference between the average flow velocity of the microchannel and the average flow velocity of the wall, the wall velocity loss rate of the microfluidic device under test is calculated, and the evaluation parameters of the fluid drag reduction characteristics of the microfluidic device under test are obtained.

[0160] Before performing fluid simulation, simulation module 4 needs to mesh the microfluidic device simulation model based on fluid dynamics principles. Mesh generation is the process of discretizing a continuous simulation region into a finite number of small elements, with the aim of solving fluid dynamics equations on these discrete elements. The quality of the mesh (such as mesh density, orthogonality, aspect ratio, etc.) directly affects the accuracy and computational efficiency of the simulation results. Typically, finer meshes are used near walls or in regions with large fluid velocity gradients to capture the details of fluid behavior.

[0161] Specifically, when simulation module 4 performs fluid simulation on the microfluidic device simulation model based on wall wetting boundary condition information to obtain the average flow velocity of the microchannel and the average flow velocity of the wall of the microfluidic device under test, it executes the following:

[0162] Fluid simulation is performed on the simulation model of the microfluidic device based on the wall wetting boundary condition information.

[0163] During fluid simulation, when the microchannel location region meets the preset fluid stability conditions, the microchannel fluid velocity in the microchannel location region and the wall velocity in the wall region are extracted.

[0164] The average values ​​of the microchannel fluid velocity and the wall velocity are calculated separately to obtain the average microchannel velocity and the average wall velocity of the microfluidic device under test.

[0165] When simulation module 4 is executed, it begins fluid simulation of the microfluidic device simulation model within the simulation software, based on the wall wetting boundary condition information (the fluid simulation process is an automatic execution process of the simulation software and will not be detailed here). During the fluid simulation of the microfluidic device simulation model, fluid velocity can be extracted at the centerline of the microchannel or a specific cross-section to obtain the velocity distribution of the fluid within the microchannel. When the fluid flow is not yet stable, the velocity may exhibit large instantaneous fluctuations, and the extracted data at this time cannot accurately reflect the true fluid behavior of the microfluidic device. More representative instantaneous fluid velocity data can only be obtained when the fluid reaches a stable state. Therefore, when the microchannel location region meets the preset fluid stability conditions, the microchannel fluid velocity in the microchannel location region and the wall velocity in the wall region are extracted (the wall velocity in the wall region can be obtained by setting a multiphase interface tracking probe on the wall region). The fluid stability condition refers to a relatively stable state in which the fluid flow in the microchannel reaches a state of equilibrium. For example, the inlet and outlet flow rates tend to be constant (the difference between the inlet and outlet flow rates is less than or equal to a preset flow stability threshold), or the velocity distribution within the microchannel no longer changes significantly (i.e., the standard deviation of the velocity at each location within the microchannel is less than or equal to a preset velocity stability threshold). In this case, the inlet and outlet fluid velocities are almost identical (i.e., the difference between the inlet and outlet fluid velocities is less than or equal to a preset velocity stability threshold), and the microchannel fluid velocity is also almost identical to the inlet (or outlet) fluid velocity (i.e., the difference between the microchannel fluid velocity and the inlet fluid velocity, and the difference between the microchannel fluid velocity and the outlet fluid velocity, are both less than or equal to the preset velocity stability threshold). This condition ensures that the extracted fluid velocity data is representative and accurately reflects the fluid behavior of the microchannel under normal operating conditions. The preset flow stability threshold and preset velocity stability threshold can be set according to actual conditions.

[0166] The average flow velocity in the microchannel and the average flow velocity at the wall are calculated separately to obtain the average flow velocity in the microfluidic device under test. This can be done using either time-averaging or spatial-averaging methods. For example, after the fluid reaches a steady state, the fluid velocity can be sampled multiple times over a period of time and the average value can be taken. Alternatively, multiple representative points can be selected in the microchannel and wall regions for velocity measurement and the average value can be taken. Obtaining the average value eliminates the influence of instantaneous fluctuations and yields a more statistically significant average flow velocity.

[0167] By calculating the difference between the average flow velocity in the microchannel and the average flow velocity at the wall, the wall velocity loss rate can be directly quantified. This allows for a direct quantification of the impact of wall friction on fluid velocity, and transforms this impact into a standardized evaluation parameter (i.e., the wall velocity loss rate). This parameter accurately reflects the fluid drag reduction characteristics of the microfluidic device, thus providing an evaluation parameter for the fluid drag reduction characteristics of the microfluidic device under test. The specific formula for calculating the wall velocity loss rate (fluid drag reduction characteristic evaluation parameter) is as follows:

[0168] ;

[0169] in, Wall velocity loss rate; The average flow velocity of the microchannel (i.e., the inlet fluid velocity). The average flow velocity at the wall surface is given.

[0170] In some alternative embodiments, the drag reduction characteristics of microfluidic devices made of different materials (such as alumina ceramics, nickel plating, gold plating, and single-crystal silicon) or with different fluid types (such as water or 1-bromonaphthalene) can be compared by calculating the wall velocity loss rate. Alternatively, by using the controlled variable method, different parameters (such as morphology data, interfacial energy data, and wall wetting boundary condition information) can be adjusted to obtain different simulation results. The impact of these different parameters on the evaluation parameters of the drag reduction characteristics can then be analyzed based on the simulation results. Thus, these methods provide guidance for optimizing the drag reduction surface of microchannels.

[0171] For example, by calculating the wall velocity loss rate of microfluidic devices with different materials and different fluid types, the fluid drag reduction characteristics of microfluidic devices with different materials and different fluid types can be compared. The comparison results of the evaluation parameters of fluid drag reduction characteristics of microfluidic devices are shown in Table 1.

[0172] Table 1 shows that, comparing microfluidic devices made of alumina ceramic, nickel plating, and monocrystalline silicon, the monocrystalline silicon microfluidic device exhibits the lowest wall velocity loss rate, indicating that it has the best drag reduction characteristics. Comparing microfluidic devices using 1-naphthalene bromide and water, the 1-naphthalene bromide microfluidic device also shows the lowest wall velocity loss rate, suggesting that it also has the best drag reduction characteristics.

[0173] As shown above, this device for evaluating the fluid drag reduction characteristics of microfluidic devices acquires the morphology and interfacial energy data of the microfluidic device under test. Based on the morphology and interfacial energy data, a model is constructed to obtain a simulation model of the microfluidic device. Fluid boundary conditions corresponding to the morphology and interfacial energy data are set for the simulation model to obtain wall wetting boundary condition information. Based on the wall wetting boundary condition information, fluid simulation is performed on the microfluidic device simulation model to obtain the evaluation parameters of the fluid drag reduction characteristics of the microfluidic device under test. Thus, by using the wall wetting boundary condition information to perform fluid simulation on the microfluidic device simulation model, the evaluation parameters of the fluid drag reduction characteristics of the microfluidic device under test are obtained. This solves the problems of existing methods for evaluating the fluid drag reduction characteristics of microfluidic devices, which are difficult to accurately evaluate due to high cost, long cycle, difficulty in effectively separating the influence of multiple factors, and insufficient consideration of wall conditions. It can quantitatively evaluate the local flow characteristics of the wall through simulation, thus improving the evaluation accuracy of the fluid drag reduction characteristics of microfluidic devices.

[0174] Please refer to Figure 3 , Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device includes a processor 301 and a memory 302. The processor 301 and the memory 302 are interconnected and communicate with each other via a communication bus 303 and / or other connection mechanisms (not shown). The memory 302 stores a computer program executable by the processor 301. When the electronic device is running, the processor 301 executes the computer program to perform a method for evaluating the fluid drag reduction characteristics of a microfluidic device in any optional implementation of the above embodiments, to achieve the following functions: acquiring morphological data and interfacial energy data of the microfluidic device under test; constructing a model based on the morphological data and interfacial energy data to obtain a microfluidic device simulation model corresponding to the microfluidic device under test; setting fluid boundary conditions corresponding to the morphological data and interfacial energy data for the microfluidic device simulation model to obtain wall wetting boundary condition information; and performing fluid simulation on the microfluidic device simulation model based on the wall wetting boundary condition information to obtain fluid drag reduction characteristic evaluation parameters of the microfluidic device under test.

[0175] This application provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it executes the fluid drag reduction characteristic evaluation method for microfluidic devices in any optional implementation of the above embodiments to achieve the following functions: acquiring morphological data and interfacial energy data of the microfluidic device under test; constructing a model based on the morphological data and interfacial energy data to obtain a microfluidic device simulation model corresponding to the microfluidic device under test; setting fluid boundary conditions corresponding to the morphological data and interfacial energy data for the microfluidic device simulation model to obtain wall wetting boundary condition information; and performing fluid simulation on the microfluidic device simulation model based on the wall wetting boundary condition information to obtain fluid drag reduction characteristic evaluation parameters of the microfluidic device under test. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0176] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some communication interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0177] Furthermore, the units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0178] Furthermore, the functional modules in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0179] In this document, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, without necessarily requiring or implying any such actual relationship or order between these entities or operations.

[0180] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for evaluating the fluid drag reduction characteristics of a microfluidic device, characterized in that, Including the following steps: Acquire morphology and interfacial energy data of the microfluidic device under test; Based on the morphology data and the interface energy data, a model is constructed to obtain the microfluidic device simulation model corresponding to the microfluidic device under test. Set fluid boundary conditions corresponding to the morphology data and the interfacial energy data for the simulation model of the microfluidic device to obtain wall wetting boundary condition information; Based on the wall wetting boundary condition information, fluid simulation is performed on the microfluidic device simulation model to obtain the fluid drag reduction characteristic evaluation parameters of the microfluidic device under test. The morphology data includes surface roughness data of the microfluidic device and microchannel size data; To set fluid boundary conditions corresponding to the morphology data and interfacial energy data for the microfluidic device simulation model, wall wetting boundary condition information is obtained, including: Based on the microchannel size data, the microchannel location region and wall region are determined in the microfluidic device simulation model; Set roughness contour information for the wall region that corresponds to the surface roughness data; Set the microchannel location region to a fluid flow state and set the corresponding fluid flow conditions; Based on the interface energy data, corresponding contact angle boundary conditions are set for the contact boundary between the microchannel location region and the wall region. The rough contour information, the fluid flow conditions, and the contact angle boundary conditions are summarized and processed to obtain the wall wetting boundary condition information.

2. The method of claim 1, wherein the fluid drag reduction property of the microfluidic device is evaluated by, Acquire morphological and interfacial energy data of the microfluidic device under test, including: The surface of the microfluidic device under test is scanned to obtain the morphological data of the microfluidic device under test; A microchannel fluid of the corresponding fluid type is set for the microfluidic device under test, and the contact angle of the microchannel fluid is measured to obtain the contact angle data of the microchannel fluid; The interfacial energy data of the microfluidic device under test is obtained by calculating based on the contact angle data.

3. The method of claim 2, wherein the fluid drag reduction property of the microfluidic device is evaluated by, Based on the contact angle data, the interfacial energy data of the microfluidic device under test is calculated, including: The contact angle data is input into a preset surface energy model for calculation to obtain the surface energy data of the microfluidic device under test. The surface energy data is input into a preset interface energy model for calculation to obtain the interface energy data of the microfluidic device under test.

4. The method of claim 1, wherein The morphology data also includes the overall dimensions of the microfluidic device; Based on the morphology data and the interfacial energy data, a model is constructed to obtain a simulation model of the microfluidic device corresponding to the microfluidic device under test, including: Obtain the preset initial microfluidic device simulation model; Based on the overall device size data, the microchannel size data, and the interface energy data, the preset initial microfluidic device simulation model is adjusted to obtain the microfluidic device simulation model corresponding to the microfluidic device under test.

5. The method of claim 1, wherein the fluid drag reduction characteristics of the microfluidic device are evaluated by, Based on the wall wetting boundary condition information, fluid simulation is performed on the microfluidic device simulation model to obtain the fluid drag reduction characteristic evaluation parameters of the microfluidic device under test, including: Based on fluid dynamics, the microfluidic device simulation model is meshed to obtain the meshed microfluidic device simulation model. Based on the wall wetting boundary condition information, fluid simulation is performed on the microfluidic device simulation model to obtain the average flow velocity of the microchannel and the average flow velocity of the wall of the microfluidic device under test. Based on the difference between the average flow velocity of the microchannel and the average flow velocity of the wall, the wall velocity loss rate of the microfluidic device under test is calculated, and the fluid drag reduction characteristic evaluation parameters of the microfluidic device under test are obtained.

6. The method of claim 5, wherein the fluid drag reduction property of the microfluidic device is evaluated by, Based on the wall wetting boundary condition information, fluid simulation is performed on the microfluidic device simulation model to obtain the average flow velocity of the microchannel and the average flow velocity of the wall of the microfluidic device under test, including: Based on the wall wetting boundary condition information, fluid simulation is performed on the microfluidic device simulation model; During fluid simulation, when the microchannel location region meets the preset fluid stability conditions, the microchannel fluid velocity in the microchannel location region and the wall velocity in the wall region are extracted. The average values ​​of the microchannel fluid velocity and the wall velocity are calculated respectively to obtain the average microchannel velocity and the average wall velocity of the microfluidic device under test.

7. An apparatus for evaluating fluid drag reduction characteristics of a microfluidic device, comprising: a microfluidic device; a fluid source; a flow channel; a flow sensor; and a controller. include: The acquisition module is used to acquire the morphology data and interfacial energy data of the microfluidic device under test. The construction module is used to construct a model based on the morphology data and the interface energy data to obtain a microfluidic device simulation model corresponding to the microfluidic device under test. The setting module is used to set fluid boundary conditions corresponding to the morphology data and the interfacial energy data for the microfluidic device simulation model, so as to obtain wall wetting boundary condition information. The simulation module is used to perform fluid simulation on the simulation model of the microfluidic device based on the wall wetting boundary condition information, and obtain the fluid drag reduction characteristic evaluation parameters of the microfluidic device under test. The morphology data includes surface roughness data of the microfluidic device and microchannel size data; The setting module is used to set fluid boundary conditions corresponding to the morphology data and the interfacial energy data for the microfluidic device simulation model, and to obtain wall wetting boundary condition information, including: Based on the microchannel size data, the microchannel location region and wall region are determined in the microfluidic device simulation model; Set roughness contour information for the wall region that corresponds to the surface roughness data; Set the microchannel location region to a fluid flow state and set the corresponding fluid flow conditions; Based on the interface energy data, corresponding contact angle boundary conditions are set for the contact boundary between the microchannel location region and the wall region. The rough contour information, the fluid flow conditions, and the contact angle boundary conditions are summarized and processed to obtain the wall wetting boundary condition information.

8. An electronic device, comprising: It includes a processor and a memory, the memory storing a computer program executable by the processor, and when the processor executes the computer program, it performs the steps in the method for evaluating the fluid drag reduction characteristics of the microfluidic device as described in any one of claims 1-6.

9. A computer readable storage medium having stored thereon a computer program, characterized in that, When the computer program is executed by the processor, it performs the steps in the method for evaluating the fluid drag reduction characteristics of the microfluidic device as described in any one of claims 1-6.

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