Crystal source metamaterial multilayer micro-fluidic chip laser-film stacking system and method

Abstract

The invention discloses a laser-film stacking system and method for a crystal source super-material multilayer micro-fluidic chip, relates to the technical field of film stacking, and aims to improve the precision and coverage dimension of laser processing quality monitoring of the micro-fluidic chip, adapt to differential processing requirements and energy density adjusting characteristics of different flow channel types, and improve the quality monitoring precision and coverage dimension of the micro-fluidic chip. Therefore, efficient and accurate runner forming processing is realized, the quality assurance efficiency and the product qualification rate level in the micro-fluidic chip production process are remarkably improved, the omission influence of a fixed pairing mode on a high-matching-degree combination can be effectively prevented, pairing deviation and packaging quality reduction caused by subjective judgment are avoided, and the production efficiency of the micro-fluidic chip is improved. According to the method, intelligent configuration and differentiated investment of lamination packaging resources can be realized, the pertinence and the implementation effect of an optimal lamination pairing scheme are effectively improved, and high conformity between quality control measures and actual processing defect risks is ensured by determining a deviation abnormal region which influences runner forming.

Description

Technical Field

[0001] This invention relates to the field of thin film stacking technology, specifically to a laser-thin film stacking system and method for multilayer microfluidic chips from Crystal Source Metamaterials. Background Technology

[0002] As core devices in various biochemical fields, microfluidic chips require precise machining of micron-level flow channels and reliable stacking and packaging of multilayer films during manufacturing. The quality of flow channel formation and interlayer bonding and sealing directly affect the chip's detection accuracy and lifespan. Therefore, it is essential to construct an intelligent multilayer stacking and packaging system based on laser processing parameter optimization and surface characteristic matching for in-depth processing quality analysis and differentiated bonding and matching control.

[0003] In existing technologies, most microfluidic chip laser processing systems rely on uniform laser power configurations and fixed processing parameter settings, which cannot cover the individualized processing characteristics and dynamic energy density adjustment rules of different channel types under different depth requirements. Although existing technologies have introduced basic morphology detection mechanisms and quality sampling functions, due to their single deviation evaluation dimension and high dependence on industry-standard tolerances, it is difficult to accurately judge the actual forming state of the channel, individualized defect patterns, and hidden processing deviations. When faced with complex blind groove hollowing mixed processing conditions or uneven distribution of channel edge contour deviations, problems such as low rework efficiency, missed defect detection, and inappropriate quality screening standards are likely to occur.

[0004] Furthermore, existing technologies lack a differentiated matching and identification mechanism for the surface characteristics of different laser-processed layers and the bonding area characteristics of the substrate layers during the stacking and packaging process. This makes it impossible to effectively achieve layer-specific pairing optimization and personalized packaging parameter adjustment. In addition, existing systems suffer from defects such as weak reconstituted height analysis capabilities, insufficient surface contact angle detection, lack of coupled analysis of geometric matching degree and bonding tolerance, lack of a global perspective in pairing optimization, and low packaging resource utilization efficiency. As a result, high-matching bonding pairing cannot be prioritized for identification and quality assurance. At the same time, there is a lack of adaptive packaging process adjustment strategies for pairing of different stacking matching degree levels, and the bonding pressure cannot be adaptively adjusted according to dynamic changes such as real-time surface state parameters of laser-processed layers and uniformity of substrate layer thickness. Summary of the Invention

[0005] The purpose of this invention is to provide a laser-thin film stacking system and method for multilayer microfluidic chips from Jingyuan Metamaterials, which solves the problems existing in the background art.

[0006] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: The first aspect of the present invention provides a laser-thin film stacking system for multilayer microfluidic chips from Jingyuan Metamaterials, comprising: a laser processing execution module, used to acquire the optical absorption characteristics of the thin film from Jingyuan Metamaterials and the geometric feature parameters and processing type identifiers of each flow channel segment of the target microfluidic chip, and generate a laser processing path matrix of the target microfluidic chip accordingly, thereby performing laser processing on each thin film to be processed to obtain each laser-processed layer.

[0007] The processing quality screening module is used to analyze the flow channel forming deviation value of each laser processing layer, and based on this, screen each qualified laser processing layer and each rework laser processing layer. The rework laser processing layer is cyclically reworked to obtain each target laser processing layer.

[0008] The surface characteristic detection module is used to acquire the design drawings of the substrate layers of the target microfluidic chip, and to process and generate each substrate layer accordingly. It performs surface state detection on each target laser-processed layer and each substrate layer to obtain the surface characteristic data of each target laser-processed layer and each substrate layer.

[0009] The bonding and matching analysis module is used to calculate the stacking matching degree between each target laser-processed layer and each plate layer based on the surface characteristic data of each target laser-processed layer and the surface characteristic data of each plate layer, and to screen the optimal bonding and matching combinations.

[0010] The packaging control module is used to precisely bond and package the target microfluidic chip according to each optimal bonding pairing combination, thereby obtaining each target microfluidic chip.

[0011] The second aspect of the present invention provides a laser-thin film stacking method for multilayer microfluidic chips from Jingyuan Metamaterials, which is implemented based on the laser-thin film stacking system of multilayer microfluidic chips from Jingyuan Metamaterials. The method is characterized by including: Step 1. Obtaining the optical absorption characteristics of the thin film from Jingyuan Metamaterials and the geometric feature parameters and processing type identifiers of each flow channel segment of the target microfluidic chip, and generating a laser processing path matrix of the target microfluidic chip accordingly, thereby performing laser processing on each thin film to be processed to obtain each laser-processed layer.

[0012] Step 2. Analyze the flow channel forming deviation value of each laser processing layer, and select each qualified laser processing layer and each rework laser processing layer accordingly. Repeatedly rework each rework laser processing layer to obtain each target laser processing layer.

[0013] Step 3. Obtain the design drawings of the substrate layers of the target microfluidic chip, and process and generate each substrate layer accordingly. Perform surface state detection on each target laser-processed layer and each substrate layer to obtain the surface characteristic data of each target laser-processed layer and the surface characteristic data of each substrate layer.

[0014] Step 4. Based on the surface characteristic data of each target laser processing layer and the surface characteristic data of each plate layer, calculate the stacking matching degree between each target laser processing layer and each plate layer, and select the optimal bonding pairing combination.

[0015] Step 5. Based on each optimal bonding and pairing combination, perform precision bonding and packaging of the target microfluidic chip to obtain each target microfluidic chip.

[0016] The beneficial effects of this invention are as follows: This invention improves the accuracy and coverage of laser processing quality monitoring for microfluidic chips. By classifying and identifying blind and hollowed-out channel sections and accurately calculating the number of layered scans and groove depth control parameters, it can adapt to the differentiated processing needs and energy density adjustment characteristics of different channel types, thereby achieving efficient and accurate channel forming processing. By improving the analytical accuracy and defect identification speed of channel forming quality monitoring, it significantly improves the quality assurance efficiency and product qualification rate in the microfluidic chip production process. By constructing a multi-dimensional surface characteristic data acquisition mechanism, it can dynamically adjust the bonding according to the surface state characteristics of different processing layers. By combining matching strategies and packaging process parameters, it effectively prevents the omission of high-matching combinations by fixed matching methods, avoids matching deviations and packaging quality degradation caused by subjective judgment, and can adjust the matching strategy in real time according to the changes in surface characteristics of the laser processing layer and the substrate layer and the matching degree threshold constraint. This enables intelligent configuration and differentiated investment of bonding and packaging resources, effectively improving the pertinence and implementation effect of the optimal bonding and matching scheme. Through accurate identification and analysis of internal and external deviations, combined with secondary processing area positioning and cyclic rework mechanism, it identifies abnormal deviation areas that affect the flow channel forming, ensuring a high degree of consistency between quality control measures and actual processing defect risks. Attached Figure Description

[0017] 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 only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of the system modules of the present invention.

[0019] Figure 2 This is a schematic diagram of the method flow of the present invention.

[0020] Figure 3 This is a schematic diagram showing the patch packaging relationship between the target laser processing layer and the substrate layer of the present invention.

[0021] Figure labels: 1 represents the plate layer, 2 represents the target laser processing layer. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] Reference Figure 1 As shown, the first aspect of the present invention provides a laser-thin film stacking system for multilayer microfluidic chips from Jingyuan Metamaterials, comprising: a laser processing execution module, a processing quality screening module, a surface characteristic detection module, a bonding and matching analysis module, and a packaging control module.

[0024] It should be noted that the laser processing execution module is connected to the processing quality screening module, the processing quality screening module is connected to the surface characteristic detection module, the surface characteristic detection module is connected to the bonding and matching analysis module, and the bonding and matching analysis module is connected to the packaging control module.

[0025] The laser processing execution module is used to acquire the optical absorption characteristics of the crystal source metamaterial thin film and the geometric feature parameters and processing type identifiers of each flow channel segment of the target microfluidic chip, and generate the laser processing path matrix of the target microfluidic chip accordingly, so as to perform laser processing on each film to be processed and obtain each laser processing layer.

[0026] In one specific embodiment, the optical absorption characteristics of the crystal source metamaterial thin film and the geometric feature parameters and processing type identifiers of each flow channel segment of the target microfluidic chip are obtained. The specific method for obtaining these parameters is as follows: the optical absorption characteristics of the crystal source metamaterial thin film and the geometric feature parameters and processing type identifiers of each flow channel segment of the target microfluidic chip are obtained from a local database. The optical absorption characteristics of the crystal source metamaterial thin film are obtained through laboratory experimental data, and the geometric feature parameters and processing type identifiers are obtained through the design drawings of the target microfluidic chip.

[0027] It should be noted that Jingyuan Metamaterials is a newly developed material based on polysiloxane, featuring a three-dimensional mesh framework structure. It can be used to fill different functional materials, thus adapting to the needs of various scenarios. These materials can be solid films (this application refers to them as solid films), liquid adhesives, semi-solid colloids, etc., with adjustable hardness and thickness. Here are some examples of characteristics of Jingyuan Metamaterials in different forms: I. Microcapsule type: Features include: 1. No initial tack; 2. Pressure-sensitive tackiness and high strength; 3. Hardness 70A, stable structure; 4. Thickness customizable from 10-200 micrometers; 5. Good biocompatibility and non-toxic; 6. Temperature resistance up to 110 degrees Celsius. II. Photosensitive type: Film-forming characteristics include: 1. Initial viscosity; 2. After UV irradiation, secondary curing increases viscosity at the bonding site, while non-bonding surfaces lose tack. Liquid form characteristics include: 1. Good fluidity, suitable as an adhesive layer; 2. Can be used as a flow channel structure layer in precision molds. III. Temperature-sensitive type: Its film-forming characteristics are 1. It may or may not have tack; 2. Its viscosity increases after heating; Its liquid characteristics are 1. It has good fluidity and can be used as an adhesive layer; 2. It can be used as a flow channel structure layer when used in precision molds.

[0028] It should also be noted that the geometric feature parameters include: centerline coordinates, width parameters, depth parameters, and edge contour coordinates of each ideal monitoring point, as well as the processing type identifier, including: blind groove type and hollow type.

[0029] It should also be noted that the local database is used to store the optical absorption characteristics of the Jingyuan Metamaterials thin film and the geometric feature parameters and processing type identifiers of each flow channel segment of the target microfluidic chip, the correspondence between the optical absorption characteristics of the Jingyuan Metamaterials thin film and the laser energy density, the material removal depth value of the Jingyuan Metamaterials thin film under a single laser energy density value scan, the film thickness corresponding to each hollowed-out flow channel segment, the basic cutting power value corresponding to each film thickness range, the cutting power safety factor, the processing sequence of each flow channel segment, the contour deviation coefficient threshold, the minimum allowable deviation coefficient, the substrate layer design drawings of the target microfluidic chip, the maximum compensable recombination height value corresponding to each thickness uniformity parameter range, the stacking matching degree threshold, the bonding pressure, bonding temperature and holding time corresponding to each stacking matching degree range.

[0030] In a specific embodiment of the present invention, the laser processing path matrix of the target microfluidic chip is generated by extracting the width and depth parameters of each flow channel segment of the target microfluidic chip based on the geometric feature parameters of each flow channel segment.

[0031] Based on the processing type identification of each flow channel segment of the target microfluidic chip, each flow channel segment of the target microfluidic chip is divided into blind groove flow channel segments and hollow flow channel segments.

[0032] In one specific embodiment, the flow channel segments of the target microfluidic chip are divided into blind groove flow channel segments and hollow flow channel segments. The specific method is as follows: if the processing type of a certain flow channel segment of the target microfluidic chip is identified as blind groove type, then the flow channel segment is marked as blind groove flow channel segment; otherwise, it is marked as hollow flow channel segment, thereby screening each blind groove flow channel segment and each hollow flow channel segment.

[0033] Based on the width and depth parameters of each blind channel segment of the target microfluidic chip, and combined with the optical absorption characteristics of the Jingyuan Metamaterial thin film, the number of layer scans and the depth control parameters of each blind channel segment of the target microfluidic chip are calculated.

[0034] In one specific embodiment, the method for calculating the number of layer-by-layer scans and the groove depth control parameters of each blind groove channel segment of the target microfluidic chip is as follows: The correspondence between the optical absorption characteristics of the crystal source metamaterial thin film and the laser energy density is obtained from a local database. Based on the optical absorption characteristics of the crystal source metamaterial thin film, the laser energy density value of each blind groove channel segment is determined and used as the groove depth control parameter of each blind groove channel segment of the target microfluidic chip. Based on the depth parameters of each blind groove channel segment of the target microfluidic chip, the material removal depth value of the crystal source metamaterial thin film under a single laser energy density scan is obtained from the local database. The depth parameters of each blind groove channel segment are compared with the single material removal depth value and rounded up to obtain the number of layer-by-layer scans of each blind groove channel segment of the target microfluidic chip.

[0035] It should be noted that the relationship between the optical absorption characteristics of the Jingyuan Metamaterial thin film and the laser energy density, as well as the material removal depth value of the Jingyuan Metamaterial thin film under a single laser energy density scan, were obtained by researchers based on actual experimental conditions.

[0036] The film thickness corresponding to each hollowed-out channel segment is obtained from the local database. Combined with the optical absorption characteristics of the Jingyuan Metamaterial film, the cutting power parameters of each hollowed-out channel segment of the target microfluidic chip are determined.

[0037] In one specific embodiment, the cutting power parameters of each hollow channel segment of the target microfluidic chip are determined by the following method: based on the film thickness corresponding to each hollow channel segment and combined with the optical absorption characteristics of the Jingyuan Metamaterial film, the basic cutting power value corresponding to each film thickness range is obtained from the local database, and the basic cutting power value of each hollow channel segment is mapped to obtain the basic cutting power value of each hollow channel segment. The cutting power safety factor is obtained from the local database, and the basic cutting power value is multiplied by the cutting power safety factor to obtain the cutting power parameters of each hollow channel segment of the target microfluidic chip.

[0038] The laser processing path matrix of the target microfluidic chip is formed by arranging and integrating the layered scanning times, groove depth control parameters, and cutting power parameters of each blind groove channel segment of the target microfluidic chip.

[0039] In one specific embodiment, the laser processing path matrix of the target microfluidic chip is formed by arranging and integrating the data. The specific method is as follows: the processing order of each channel segment is obtained from the local database, and the number of layer scans, groove depth control parameters and cutting power parameters of each blind groove channel segment of the target microfluidic chip are arranged according to the processing order of each channel segment to obtain the laser processing path matrix of the target microfluidic chip.

[0040] In one specific embodiment, laser processing is performed on each film to be processed to obtain each laser-processed layer. The specific method for obtaining the laser-processed layer is as follows: based on the laser processing path matrix of the target microfluidic chip, the number of layer-by-layer scanning, groove depth control parameters, and cutting power parameters of each hollowed-out groove channel segment are extracted. Each film to be processed is fixed sequentially on the laser processing platform. For each blind groove channel segment, the laser is controlled to scan layer by layer according to the groove depth control parameters, and the number of layer-by-layer scanning is executed. For each hollowed-out groove channel segment, the laser is controlled to cut along the channel contour according to the cutting power parameters until the film is completely cut through. The processing is carried out according to the processing order of each channel segment. After all channel segments of each film to be processed are processed, each laser-processed layer is obtained.

[0041] It should be noted that all the films to be processed were made by Crystal Source Advanced Materials.

[0042] The processing quality screening module is used to analyze the flow channel forming deviation value of each laser processing layer, and based on this, screen each qualified laser processing layer and each rework laser processing layer. The rework laser processing layer is cyclically reworked to obtain each target laser processing layer.

[0043] In a specific embodiment of the present invention, the flow channel forming deviation value of each laser processing layer is analyzed, and each qualified laser processing layer and each reworked laser processing layer are selected accordingly. The specific method is as follows: the morphology of each flow channel segment of each laser processing layer is detected, and the actual edge contour coordinates of each flow channel segment of each laser processing layer at each monitoring point are obtained.

[0044] In one specific embodiment, the laser processing path matrix of the target microfluidic chip is formed by arranging and integrating the paths. The specific method is to obtain the actual edge contour coordinates of each flow channel segment of each laser processing layer at each monitoring point through a micron-level laser ranging sensor.

[0045] Based on the geometric feature parameters of each flow channel segment of the target microfluidic chip, and by comparing the actual edge contour coordinates of each monitoring point of each flow channel segment of each laser processing layer, the contour deviation coefficient of each flow channel segment of each laser processing layer is calculated, and each qualified laser processing layer and each deviated laser processing layer are selected accordingly.

[0046] In one specific embodiment, the contour deviation coefficient of each flow channel segment of each laser processing layer is calculated, and qualified laser processing layers and deviated laser processing layers are selected accordingly. The specific method is as follows: Based on the geometric feature parameters of each flow channel segment of the target microfluidic chip, the ideal edge contour coordinates of each monitoring point of each flow channel segment of the target microfluidic chip are extracted. Then, the values ​​of each ideal edge contour coordinate point of each flow channel segment of the target microfluidic chip at each monitoring point are extracted. Similarly, the values ​​of each actual edge contour coordinate point of each flow channel segment of each laser processing layer at each monitoring point are extracted. The values ​​of each ideal edge contour coordinate point at each monitoring point are subtracted from the values ​​of the corresponding actual edge contour coordinate points, and the absolute value of the subtraction is taken. Then, a positive or negative sign is added to the absolute value of the subtraction, where a negative sign indicates that the cutting part is too large, and a positive sign indicates that the cutting part is too small. Thus, the deviation coefficient between the ideal edge contour coordinate points and the actual edge contour coordinate points of each flow channel segment of each laser processing layer at each monitoring point is obtained. Where x represents the number of each laser processing layer, y is a positive integer greater than 2, and n represents the number of each flow channel segment. m is a positive integer greater than 2, and i represents the number of each monitoring point. j is a positive integer greater than 2, and p represents the index of each ideal edge contour coordinate point. q is a positive integer greater than 2. Calculate the profile deviation coefficient of each flow channel segment in each laser processing layer. The contour deviation coefficient threshold is obtained from the local database. If the contour deviation coefficient of a certain flow channel segment of a certain laser processing layer is less than the contour deviation coefficient threshold, the laser processing layer is marked as a qualified laser processing layer. Otherwise, the laser processing layer is marked as a deviated laser processing layer, thereby filtering each qualified laser processing layer and each deviated laser processing layer.

[0047] Internal and external deviation analyses were performed on each deviation laser processing layer to screen out each rework laser processing layer.

[0048] In one specific embodiment, the method for selecting each rework laser processing layer is as follows: extract the ideal edge contour coordinate point with the smallest deviation coefficient of each flow channel segment of each deviation laser processing layer at each monitoring point, thereby obtaining the minimum deviation coefficient of each flow channel segment of each deviation laser processing layer at each monitoring point. Obtain the minimum allowable deviation coefficient from the local database. If the minimum deviation coefficient of each flow channel segment of a certain deviation laser processing layer at each monitoring point is greater than the minimum allowable deviation coefficient, and there exists a flow channel segment of the deviation laser processing layer at a certain monitoring point where the sign of the deviation coefficient between the ideal edge contour coordinate point and the actual deviation coefficient is positive, then the deviation laser processing layer is marked as a rework laser processing layer, thereby selecting each rework laser processing layer.

[0049] In a specific embodiment of the present invention, each reworked laser processing layer is cyclically reworked to screen out each target laser processing layer. The specific method is as follows: based on the actual edge contour coordinates of each flow channel segment of each laser processing layer at each monitoring point, the actual edge contour coordinates of each flow channel segment of each reworked laser processing layer at each monitoring point are extracted, and the secondary processing areas of each flow channel segment of each reworked laser processing layer at each monitoring point are screened accordingly.

[0050] In one specific embodiment, the secondary processing area of ​​each flow channel segment of each rework laser processing layer at each monitoring point is selected by means of: statistically analyzing the coordinate points of each ideal edge contour of each flow channel segment of each laser processing layer at each monitoring point where the deviation coefficient from the actual value is positive as the secondary processing area, thereby obtaining the secondary processing area of ​​each flow channel segment of each rework laser processing layer at each monitoring point.

[0051] Laser processing is performed on each flow channel segment of each reworked laser processing layer in the secondary processing area at each monitoring point. The flow channel forming deviation value of each reworked laser processing layer is analyzed, thereby secondary screening of each qualified laser processing layer and each secondary reworked laser processing layer. This process is repeated until there are no laser processing layers that need to be reworked. All qualified laser processing layers that appear in this process are taken as target laser processing layers.

[0052] In one specific embodiment, the flow channel forming deviation value of each rework laser processing layer is analyzed to screen each qualified laser processing layer and each rework laser processing layer for a second time. The specific method is as follows: based on the method of analyzing the flow channel forming deviation value of each laser processing layer and screening each qualified laser processing layer and each rework laser processing layer accordingly, the flow channel forming deviation value of each rework laser processing layer is analyzed in the same way to screen each qualified laser processing layer and each rework laser processing layer for a second time.

[0053] The surface characteristic detection module is used to acquire the design drawings of the substrate layers of the target microfluidic chip, and to process and generate each substrate layer accordingly. It performs surface state detection on each target laser-processed layer and each substrate layer to obtain the surface characteristic data of each target laser-processed layer and each substrate layer.

[0054] In one specific embodiment, the design drawings of the substrate layer of the target microfluidic chip are obtained, and each substrate layer is processed and generated accordingly. The specific method is as follows: the design drawings of the substrate layer of the target microfluidic chip are obtained from the local database, and the overall appearance of the substrate layer is determined according to the design drawings. The thin film formed by the crystal source metamaterial is then made into the corresponding overall appearance.

[0055] It should be noted that the sensors and mechanical devices used in this application are all sensors and mechanical devices with a data detection range of micrometers.

[0056] Reference Figure 3As shown, the target laser processing layer and the substrate layer are two layers, one above the other. The side of the target laser processing layer with blind groove processing is encapsulated and patched with the substrate layer.

[0057] In a specific embodiment of the present invention, the surface characteristic data of each target laser processing layer and the surface characteristic data of each plate layer are obtained by means of: scanning the surface morphology of each target laser processing layer, and obtaining the recombination height value of the flow channel region of each target laser processing layer at each edge monitoring point and the flatness of each surface monitoring point.

[0058] In one specific embodiment, the method for obtaining the reconstituted height value of the flow channel region of each target laser processing layer at each edge monitoring point and the flatness of each surface monitoring point is as follows: a laser confocal microscope is used to perform a three-dimensional morphological scan of the flow channel edge region of each target laser processing layer to obtain the height distribution data at each edge monitoring point, the protruding regions above the reference surface in the height distribution data are identified, the maximum height value of the protruding regions is extracted as the reconstituted height value of each edge monitoring point of each target laser processing layer, and a surface profilometer is used to measure the roughness of each surface monitoring point of each target laser processing layer to obtain the flatness of each surface monitoring point of each target laser processing layer.

[0059] Contact angle detection was performed on the flow channel edge region of each target laser processing layer, and the surface contact angle value of the flow channel region of each target laser processing layer at each edge monitoring point was analyzed.

[0060] The flatness of each surface monitoring point of each target laser-processed layer, the surface contact angle value of the flow channel region at each edge monitoring point, and the height value of the recrystallized material are used as the surface characteristic data of each target laser-processed layer.

[0061] Based on the geometric feature parameters of each flow channel segment of the target microfluidic chip, the bonding area between each plate layer and the target laser processing layer is determined and recorded as the bonding area of ​​each plate layer.

[0062] In one specific embodiment, the bonding area corresponding to each plate layer and the target laser processing layer is determined by the following method: based on the geometric feature parameters of each flow channel segment of the target microfluidic chip, the centerline coordinates and width parameters of each flow channel segment are extracted, and projected accordingly to obtain the projection contour of each flow channel segment on the plate layer. The projection contour of each flow channel segment on the plate layer is subtracted from the surface of the plate layer to obtain the bonding area corresponding to each plate layer and the target laser processing layer.

[0063] The surface condition of the bonding area of ​​each board layer is detected, and the surface flatness parameters, thickness uniformity parameters and contact angle parameters of the bonding area of ​​each board layer at each surface monitoring point are obtained, which are used as the surface characteristic data of each board layer.

[0064] In one specific embodiment, the surface flatness parameters, thickness uniformity parameters, and contact angle parameters of the bonding area of ​​each sheet layer at each surface monitoring point are obtained. The specific method is as follows: Based on the bonding area of ​​each sheet layer, each surface monitoring point corresponding to the target laser processing layer in the bonding area of ​​each sheet layer is selected and recorded as the surface monitoring point of the bonding area of ​​each sheet layer. The height of each surface monitoring point is measured using a laser displacement sensor to obtain the surface flatness parameters of each surface monitoring point. The thickness of each surface monitoring point is measured using an ultrasonic thickness gauge to obtain the deviation ratio between the thickness value of each surface monitoring point and the nominal thickness, and this is used as the thickness uniformity parameter of each surface monitoring point. Standard test droplets are added to each surface monitoring point, the droplet morphology image is collected, and the tangent angle of the droplet edge is analyzed, and this is used as the contact angle parameter of each surface monitoring point.

[0065] In a specific embodiment of the present invention, the surface contact angle value of the flow channel region of each target laser processing layer at each edge monitoring point is analyzed. The specific method is as follows: based on the actual edge contour coordinates of each flow channel segment of each target laser processing layer at each monitoring point, the actual position of the flow channel region of each target laser processing layer at each edge monitoring point is determined.

[0066] In one specific embodiment, the actual position of the flow channel region of each target laser processing layer at each edge monitoring point is determined by selecting the monitoring point in each flow channel segment that has a part in contact with the plate layer as the edge monitoring point, and then determining the actual position of the flow channel region of each target laser processing layer at each edge monitoring point based on the actual edge contour coordinates of each flow channel segment of each target laser processing layer at each monitoring point.

[0067] Standard test droplets are added to the actual positions of each edge monitoring point in the flow channel region of each target laser processing layer. The droplet morphology images of the flow channel region of each target laser processing layer at each edge monitoring point are collected. The droplet edge tangent angle of the flow channel region of each target laser processing layer at each edge monitoring point is analyzed and used as the local contact angle value of each target laser processing layer at each detection position.

[0068] It should be noted that standard test solutions can use liquid reagents such as ultrapure water.

[0069] In one specific embodiment, droplet morphology images of the flow channel region of each target laser processing layer at each edge monitoring point are acquired. The specific method is as follows: droplet morphology images of the flow channel region of each target laser processing layer at each edge monitoring point are acquired using a micron-level camera.

[0070] In one specific embodiment, the droplet edge tangent angle of the flow channel region of each target laser processing layer at each edge monitoring point is analyzed. The specific method is as follows: based on the droplet morphology image of the flow channel region of each target laser processing layer at each edge monitoring point, the droplet morphology image is grayscaled and edge detected to identify the droplet contour boundary line, the position of the three-phase contact point where the droplet contacts the surface of the target laser processing layer is extracted, the droplet contour boundary line is tangent fitted at the three-phase contact point, the angle between the tangent and the baseline of the target laser processing layer surface is calculated, and it is used as the droplet edge tangent angle of the flow channel region of each target laser processing layer at each edge monitoring point.

[0071] The bonding and matching analysis module is used to calculate the stacking matching degree between each target laser-processed layer and each plate layer based on the surface characteristic data of each target laser-processed layer and the surface characteristic data of each plate layer, and to screen the optimal bonding and matching combinations.

[0072] In a specific embodiment of the present invention, the stacking matching degree between each target laser processing layer and each plate layer is calculated, and each optimal bonding pairing combination is selected. The specific method is as follows: based on the flatness of each surface monitoring point of each target laser processing layer, and combined with the surface flatness parameters of the bonding area of ​​each plate layer at each surface monitoring point, the geometric matching degree between each target laser processing layer and each plate layer is calculated.

[0073] In one specific embodiment, the geometric matching degree between each target laser-processed layer and each substrate layer is calculated. The specific method is as follows: based on the flatness of each surface monitoring point of each target laser-processed layer, the roughness standard deviation of each target laser-processed layer is calculated. Where r represents the number of each target laser processing zone, s is a positive integer greater than 2. Based on the surface flatness parameters of the bonding area of ​​each board layer at each surface monitoring point, the standard deviation of the surface flatness of the bonding area of ​​each board layer is calculated. Where t represents the number of each sheet layer, w is a positive integer greater than 2, used to calculate the geometric matching degree between each target laser processing layer and each plate layer. .

[0074] Based on the recombination height value of the flow channel area of ​​each target laser processing layer at each edge monitoring point, and combined with the thickness uniformity parameter of the bonding area of ​​each plate layer at each surface monitoring point, the bonding tolerance between each target laser processing layer and each plate layer is calculated.

[0075] In one specific embodiment, the bonding tolerance between each target laser-processed layer and each plate layer is calculated. The specific method is as follows: Based on the edge monitoring points of the flow channel region of each target laser-processed layer, surface monitoring points corresponding to the edge monitoring points in the bonding region of each plate layer are extracted and used as the edge monitoring points corresponding to the bonding region of each plate layer. Thickness uniformity parameters of the edge monitoring points corresponding to the bonding region of each plate layer are extracted. The maximum compensable reconstituted height value corresponding to each thickness uniformity parameter interval is obtained from a local database. This mapping relationship is obtained by researchers based on actual experimental data, mapping to obtain the maximum compensable reconstituted height value of each edge monitoring point corresponding to the bonding region of each plate layer. Where k represents the number of each edge monitoring point, , It is a positive integer greater than 2, based on the reconstituted material height value of each edge monitoring point in the flow channel region of each target laser processing layer. Calculate the adhesion tolerance between each target laser processing layer and each substrate layer. ,in This represents the number of edge monitoring points.

[0076] Based on the surface contact angle values ​​of the flow channel area of ​​each target laser processing layer at each edge monitoring point, and combined with the contact angle parameters of the bonding area of ​​each sheet layer at each surface monitoring point, the contact angle matching degree between each target laser processing layer and each sheet layer is calculated.

[0077] In one specific embodiment, the contact angle matching degree between each target laser processing layer and each substrate layer is calculated. The specific method is as follows: based on the contact angle parameters of the bonding area of ​​each substrate layer at each surface monitoring point, the contact angle parameters of the bonding area of ​​each substrate layer at each edge monitoring point are extracted. Based on the surface contact angle values ​​of the flow channel region of each target laser processing layer at each edge monitoring point. Calculate the contact angle matching degree between each target laser processing layer and each plate layer. , where D represents the contact angle value used for comparison, which can be set to any value other than 0.

[0078] The stacking matching degree between each target laser processing layer and each plate layer is obtained by calculating the geometric matching degree, bonding tolerance and contact angle matching degree between each target laser processing layer and each plate layer.

[0079] In one specific embodiment, the stacking matching degree between each target laser-processed layer and each substrate layer is obtained by: calculating the stacking matching degree between each target laser-processed layer and each substrate layer based on the geometric matching degree, bonding tolerance, and contact angle matching degree between each target laser-processed layer and each substrate layer. , where e represents the natural constant.

[0080] Global optimization allocation is performed based on the stacking matching degree between each target laser processing layer and each board layer, and the optimal bonding and matching combination is selected.

[0081] In a specific embodiment of the present invention, global optimization allocation is performed to select the best bonding pairing combination. The specific method is as follows: taking each target laser processing layer as the row and each plate layer as the column, the stacking matching degree between each target laser processing layer and each plate layer is filled into the corresponding position to construct the matching degree matrix between the target laser processing layer and the plate layer, thereby obtaining the stacking matching degree of each pairing in the matrix.

[0082] Obtain the stacking match threshold from the local database and filter each valid pair accordingly.

[0083] In one specific embodiment, each valid pair is filtered by the following method: if the stacking matching degree of a pair in the matrix is ​​greater than the stacking matching degree threshold, it is marked as a valid pair, thereby filtering each valid pair.

[0084] Each effective pair is optimized and allocated. The constraint is set that each target laser processing layer is paired with only one plate layer and each plate layer is paired with only one target laser processing layer, so as to obtain each allocation scheme. The optimization objective is to maximize the sum of the stacking matching degree of each effective pair in each allocation scheme, and the optimal allocation scheme is selected.

[0085] It should be noted that each allocation scheme contains valid pairings. For example, if there are three target laser processing layers 1, 2, and 3, and plate layers 4, 5, and 6, and assuming that the stacking match degree of any target laser processing layer paired with a plate layer is greater than the stacking match degree threshold, then the following six allocation schemes are possible, and each combination contains three valid pairings: I. 1 and 4, 2 and 5, 3 and 6; II. 1 and 4, 2 and 6, 3 and 5; III. 1 and 5, 2 and 4, 3 and 6; IV. 1 and 5, 2 and 6, 3 and 4; V. 1 and 6, 2 and 5, 3 and 4; VI. 1 and 6, 2 and 4, 3 and 5.

[0086] Each effective pairing in the optimal allocation scheme is taken as the optimal fitting pairing combination.

[0087] The packaging control module is used to precisely bond and package the target microfluidic chip according to each optimal bonding pairing combination, thereby obtaining each target microfluidic chip.

[0088] In a specific embodiment of the present invention, the target microfluidic chip is precisely bonded and packaged to obtain each target microfluidic chip. The specific method is as follows: the bonding pressure, bonding temperature and holding time corresponding to each stack matching degree interval are obtained from the local database, and the bonding pressure, bonding temperature and holding time of each optimal bonding pairing combination are mapped according to the stack matching degree of each optimal bonding pairing combination.

[0089] It should be noted that the bonding pressure, bonding temperature, and holding time corresponding to each stacking matching degree range were obtained by researchers based on laboratory test data.

[0090] The target laser-processed layer in each optimal bonding pairing is aligned and positioned with the corresponding substrate layer, and then bonded and encapsulated according to the bonding pressure, bonding temperature and holding time of each optimal bonding pairing, thereby obtaining each target microfluidic chip.

[0091] Reference Figure 2 As shown, the second aspect of the present invention provides a laser-thin film stacking method for multilayer microfluidic chips from Jingyuan Metamaterials, which is implemented based on the laser-thin film stacking system of multilayer microfluidic chips from Jingyuan Metamaterials. The method is characterized by including: Step 1. Obtaining the optical absorption characteristics of the thin film from Jingyuan Metamaterials and the geometric feature parameters and processing type identifiers of each flow channel segment of the target microfluidic chip, and generating a laser processing path matrix of the target microfluidic chip accordingly, thereby performing laser processing on each thin film to be processed to obtain each laser-processed layer.

[0092] Step 2. Analyze the flow channel forming deviation value of each laser processing layer, and select each qualified laser processing layer and each rework laser processing layer accordingly. Repeatedly rework each rework laser processing layer to obtain each target laser processing layer.

[0093] Step 3. Obtain the design drawings of the substrate layers of the target microfluidic chip, and process and generate each substrate layer accordingly. Perform surface state detection on each target laser-processed layer and each substrate layer to obtain the surface characteristic data of each target laser-processed layer and the surface characteristic data of each substrate layer.

[0094] Step 4. Based on the surface characteristic data of each target laser processing layer and the surface characteristic data of each plate layer, calculate the stacking matching degree between each target laser processing layer and each plate layer, and select the optimal bonding pairing combination.

[0095] Step 5. Based on each optimal bonding and pairing combination, perform precision bonding and packaging of the target microfluidic chip to obtain each target microfluidic chip.

[0096] All formulas in this manual are dimensionless and calculated numerically. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters and thresholds in the formulas are set by those skilled in the art according to the actual situation.

[0097] The above content is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, and all such modifications and additions should fall within the protection scope of the present invention.

Claims

1. A multilayer microfluidic chip laser-thin film stacking system from Jingyuan Metamaterials, characterized in that, include: The laser processing execution module is used to acquire the optical absorption characteristics of the crystal source metamaterial thin film and the geometric feature parameters and processing type identifiers of each flow channel segment of the target microfluidic chip, and generate the laser processing path matrix of the target microfluidic chip accordingly, so as to perform laser processing on each film to be processed and obtain each laser processing layer. The processing quality screening module is used to analyze the flow channel forming deviation value of each laser processing layer, and based on this, screen each qualified laser processing layer and each rework laser processing layer, and perform cyclic rework on each rework laser processing layer to obtain each target laser processing layer. The surface characteristic detection module is used to acquire the design drawings of the substrate layers of the target microfluidic chip, and process and generate each substrate layer accordingly. It performs surface state detection on each target laser-processed layer and each substrate layer to obtain the surface characteristic data of each target laser-processed layer and the surface characteristic data of each substrate layer. The bonding and matching analysis module is used to calculate the stacking matching degree between each target laser processing layer and each plate layer based on the surface characteristic data of each target laser processing layer and the surface characteristic data of each plate layer, and to screen the optimal bonding and matching combination. The packaging control module is used to precisely bond and package the target microfluidic chip according to each optimal bonding pairing combination, thereby obtaining each target microfluidic chip.

2. The Crystal Source Metamaterials multilayer microfluidic chip laser-thin film stacking system according to claim 1, characterized in that, The specific method for generating the laser processing path matrix of the target microfluidic chip is as follows: Based on the geometric feature parameters of each flow channel segment of the target microfluidic chip, the width and depth parameters of each flow channel segment of the target microfluidic chip are extracted. Based on the processing type identification of each flow channel segment of the target microfluidic chip, each flow channel segment of the target microfluidic chip is divided into blind groove flow channel segments and hollow flow channel segments; Based on the width and depth parameters of each blind channel segment of the target microfluidic chip, and combined with the optical absorption characteristics of the Jingyuan Metamaterial thin film, the number of layer scans and the depth control parameters of each blind channel segment of the target microfluidic chip are calculated. The film thickness corresponding to each hollowed-out flow channel segment is obtained from the local database. Combined with the optical absorption characteristics of the Jingyuan Metamaterial film, the cutting power parameters of each hollowed-out flow channel segment of the target microfluidic chip are determined. The laser processing path matrix of the target microfluidic chip is formed by arranging and integrating the layered scanning times, groove depth control parameters, and cutting power parameters of each blind groove channel segment of the target microfluidic chip.

3. The crystal source metamaterial multilayer microfluidic chip laser-thin film stacking system according to claim 2, characterized in that, The specific method for analyzing the flow channel forming deviation values ​​of each laser processing layer and selecting qualified and reworked laser processing layers based on these deviations is as follows: The morphology of each flow channel segment in each laser processing layer is detected to obtain the actual edge contour coordinates of each flow channel segment at each monitoring point. Based on the geometric feature parameters of each flow channel segment of the target microfluidic chip, and by comparing the actual edge contour coordinates of each monitoring point of each flow channel segment of each laser processing layer, the contour deviation coefficient of each flow channel segment of each laser processing layer is calculated, and each qualified laser processing layer and each deviated laser processing layer are selected accordingly. Internal and external deviation analyses were performed on each deviation laser processing layer to screen out each rework laser processing layer.

4. The crystal source metamaterial multilayer microfluidic chip laser-thin film stacking system according to claim 3, characterized in that, The specific method for cyclically reworking each reworked laser processing layer to select each target laser processing layer is as follows: Based on the actual edge contour coordinates of each flow channel segment of each laser processing layer at each monitoring point, the actual edge contour coordinates of each flow channel segment of each rework laser processing layer at each monitoring point are extracted, and the secondary processing areas of each flow channel segment of each rework laser processing layer at each monitoring point are selected accordingly. Laser processing is performed on each flow channel segment of each reworked laser processing layer in the secondary processing area at each monitoring point. The flow channel forming deviation value of each reworked laser processing layer is analyzed, thereby secondary screening of each qualified laser processing layer and each secondary reworked laser processing layer. This process is repeated until there are no laser processing layers that need to be reworked. All qualified laser processing layers that appear in this process are taken as target laser processing layers.

5. The crystal source metamaterial multilayer microfluidic chip laser-thin film stacking system according to claim 2, characterized in that, The specific method for obtaining the surface characteristic data of each target laser-processed layer and the surface characteristic data of each plate layer is as follows: Surface morphology scanning was performed on each target laser processing layer to obtain the recombination height value of the flow channel region of each target laser processing layer at each edge monitoring point and the flatness of each surface monitoring point; Contact angle detection was performed on the flow channel edge region of each target laser processing layer, and the surface contact angle value of the flow channel region of each target laser processing layer at each edge monitoring point was analyzed. The surface flatness of each surface monitoring point of each target laser processing layer, the surface contact angle value of the flow channel area at each edge monitoring point, and the recrystallization height value are used as the surface characteristic data of each target laser processing layer. Based on the geometric feature parameters of each flow channel segment of the target microfluidic chip, the bonding area between each plate layer and the target laser processing layer is determined and recorded as the bonding area of ​​each plate layer. The surface condition of the bonding area of ​​each board layer is detected, and the surface flatness parameters, thickness uniformity parameters and contact angle parameters of the bonding area of ​​each board layer at each surface monitoring point are obtained, which are used as the surface characteristic data of each board layer.

6. The crystal source metamaterial multilayer microfluidic chip laser-thin film stacking system according to claim 5, characterized in that, The specific method for analyzing the surface contact angle values ​​of the flow channel region of each target laser processing layer at each edge monitoring point is as follows: Based on the actual edge contour coordinates of each flow channel segment of each target laser processing layer at each monitoring point, the actual position of the flow channel region of each target laser processing layer at each edge monitoring point is determined; Standard test droplets are added at the actual positions of each edge monitoring point in the flow channel region of each target laser processing layer. Droplet morphology images of the flow channel region of each target laser processing layer at each edge monitoring point are collected. The droplet edge tangent angle of the flow channel region of each target laser processing layer at each edge monitoring point is analyzed and used as the local contact angle value of each target laser processing layer at each edge monitoring point.

7. The Crystal Source Metamaterials multilayer microfluidic chip laser-thin film stacking system according to claim 5, characterized in that, The specific method for calculating the stacking matching degree between each target laser processing layer and each substrate layer, and selecting the optimal bonding combination, is as follows: Based on the flatness of each surface monitoring point of each target laser processing layer, and combined with the surface flatness parameters of each plate layer's bonding area at each surface monitoring point, the geometric matching degree between each target laser processing layer and each plate layer is calculated. Based on the height of the reconstituted material in the flow channel area of ​​each target laser processing layer at each edge monitoring point, and combined with the thickness uniformity parameters of the bonding area of ​​each plate layer at each surface monitoring point, the bonding tolerance between each target laser processing layer and each plate layer is calculated. Based on the surface contact angle values ​​of the flow channel area of ​​each target laser processing layer at each edge monitoring point, and combined with the contact angle parameters of the bonding area of ​​each sheet layer at each surface monitoring point, the contact angle matching degree between each target laser processing layer and each sheet layer is calculated. The stacking degree between each target laser processing layer and each plate layer is obtained by calculating the geometric matching degree, bonding tolerance and contact angle matching degree between each target laser processing layer and each plate layer. Global optimization allocation is performed based on the stacking matching degree between each target laser processing layer and each board layer, and the optimal bonding and matching combination is selected.

8. The Crystal Source Metamaterials multilayer microfluidic chip laser-thin film stacking system according to claim 7, characterized in that, The specific method for performing global optimization allocation and selecting the best fitting pairings is as follows: Using each target laser processing layer as a row and each plate layer as a column, the stacking matching degree between each target laser processing layer and each plate layer is filled into the corresponding position to construct the matching degree matrix between the target laser processing layer and the plate layer, thereby obtaining the stacking matching degree of each pair in the matrix; Obtain the stacking match threshold from the local database and filter each valid pair accordingly; Each effective pair is optimized and allocated. The constraint is set that each target laser processing layer is paired with only one plate layer and each plate layer is paired with only one target laser processing layer, so as to obtain each allocation scheme. The optimal allocation scheme is obtained by maximizing the sum of the stacking matching degree of each effective pair in each allocation scheme. Each effective pairing in the optimal allocation scheme is taken as the optimal fitting pairing combination.

9. The Crystal Source Metamaterials multilayer microfluidic chip laser-thin film stacking system according to claim 8, characterized in that, The specific method for precisely bonding and packaging the target microfluidic chip to obtain each target microfluidic chip is as follows: The bonding pressure, bonding temperature, and holding time corresponding to each stack matching degree range are obtained from the local database. Based on the stack matching degree of each optimal bonding pairing combination, the bonding pressure, bonding temperature, and holding time of each optimal bonding pairing combination are mapped. The target laser-processed layer in each optimal bonding pairing is aligned and positioned with the corresponding substrate layer, and then bonded and encapsulated according to the bonding pressure, bonding temperature and holding time of each optimal bonding pairing, thereby obtaining each target microfluidic chip.

10. A laser-thin film stacking method for multilayer microfluidic chips from Jingyuan Metamaterials, implemented based on the laser-thin film stacking system for multilayer microfluidic chips from Jingyuan Metamaterials according to any one of claims 1-9, characterized in that, include: Step 1. Obtain the optical absorption characteristics of the crystal source metamaterial thin film and the geometric feature parameters and processing type identifiers of each flow channel segment of the target microfluidic chip, and generate the laser processing path matrix of the target microfluidic chip accordingly, so as to perform laser processing on each film to be processed and obtain each laser processing layer; Step 2. Analyze the flow channel forming deviation value of each laser processing layer, and select each qualified laser processing layer and each rework laser processing layer accordingly. Perform cyclic rework on each rework laser processing layer to obtain each target laser processing layer. Step 3. Obtain the design drawings of the substrate layers of the target microfluidic chip, and process and generate each substrate layer accordingly. Perform surface state detection on each target laser-processed layer and each substrate layer to obtain the surface characteristic data of each target laser-processed layer and the surface characteristic data of each substrate layer. Step 4. Based on the surface characteristic data of each target laser processing layer and the surface characteristic data of each plate layer, calculate the stacking matching degree between each target laser processing layer and each plate layer, and select the optimal bonding pairing combination; Step 5. Based on each optimal bonding and pairing combination, perform precision bonding and packaging of the target microfluidic chip to obtain each target microfluidic chip.

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