Accurate liquid supplementing method and device for digital micro-fluidic liquid drops

Abstract

The invention discloses an accurate liquid supplementing method and device for digital micro-fluidic droplets, and the method comprises the steps: carrying out the real-time detection of the area of a sample droplet and the area of a solvent droplet, calculating the current droplet proportion of the sample droplet, and when the current droplet proportion of the sample droplet is smaller than a preset proportion threshold value, carrying out the accurate liquid supplementing of the digital micro-fluidic droplets; solvent liquid drops prepared in advance are moved to a target electrode area where the sample liquid drops are located, the sample liquid drops and the solvent liquid drops are combined and split according to a preset rule, combined liquid drops and redundant solvent liquid drops are obtained, the redundant solvent liquid drops are removed, then the combined liquid drops do reciprocating motion along a preset path, and the target electrode area where the sample liquid drops are located is obtained. Finally, uniformly mixed sample liquid drops are formed. According to the scheme, automatic liquid supplementing of the digital micro-fluidic liquid drops is achieved by accurately measuring the area of the sample liquid drops in real time, a large number of liquid drops can be controlled at the same time, and finally the substance concentration of an original reaction system can be stably maintained, so that negative effects caused by evaporation of the liquid drops are avoided.

Description

Technical Field

[0001] The present invention belongs to the technical field of digital microfluidics, and in particular relates to a precise liquid replenishment method and device for digital microfluidics droplets. Background Art

[0002] Evaporation is a ubiquitous phenomenon in nature and is closely related to the most basic principles of thermodynamics. Evaporation can cause a droplet to decrease in volume, concentrate solutes, change the droplet shape, and may eventually cause the droplet to disappear completely. This phenomenon is a serious problem for a wide range of droplet applications, including microfluidics, chemical engineering, and biomedicine. Microdroplets are extremely small droplets at the micro-nanoscale, and the evaporation problem is more serious in such applications due to the relatively large surface area to volume ratio.

[0003] Digital microfluidics (DMF) is an automated manipulation technology for discrete droplets. By energizing the electrode array in sequence, operations such as the generation, transportation, merging, and splitting of droplets at the microliter to nanoliter scale can be achieved. DMF is becoming an increasingly popular tool in biological and biochemical applications. DMF devices usually consist of two plates with droplets sandwiched between them. The evaporation of droplets between the plates is a major challenge for DMF, because reagent loss and concentration changes will directly lead to reaction result offsets and distortion of detection results. When evaporation is severe, it will also cause droplet drive failure. Therefore, effectively suppressing the evaporation of microdroplets is crucial to ensure the reliability of experimental results.

[0004] In the prior art, there are many methods to reduce evaporation in DMF. The first common strategy is to block any open gas-liquid interface, and immiscible silicone oil is usually used to cap the exposed reaction solution. This method has the following defects: 1) Using a sealing structure to contain the oil increases complexity; 2) Unnecessary liquid-liquid extraction causes the reactants to enter the oil, which is incompatible with oil-soluble liquids (such as organic solvents, such as alcohols); 3) Unnecessary heat dissipation destroys the temperature control of local droplets; 4) The operation of evaporation to promote solute shrinkage and separation is limited. The second commonly used method is to place the air matrix DMF device in a closed humidification chamber, but the disadvantage of this method is that it relies on the operator's experience. The third method is to use unit droplet refill (droplet volume on a single drive electrode). The disadvantages of this method are: the accuracy of maintaining a constant reaction volume is limited (limit refill accuracy = unit droplet volume / (2*total volume of the reaction system)), and the smaller the reaction volume, the greater the error; at the same time, the impact of environmental factors on evaporation is not considered, and the minimum volume of solvent droplets driven to replenish the reaction volume is prone to drive failure, especially in high temperature states where solvent droplets will also evaporate.

[0005] Therefore, how to design an efficient and simple digital microfluidic droplet manipulation method that can inhibit droplet evaporation is a technical problem to be solved. Summary of the invention

[0006] Based on this, it is necessary to provide a precise liquid replenishment method and device for digital microfluidic droplets to address the existing problems.

[0007] The present application embodiment provides a method for precise liquid replenishment of digital microfluidic droplets, comprising the following steps:

[0008] Step S1: using a pre-trained area detection model to perform real-time detection on a sample droplet on a digital microfluidic chip, and obtaining an initial area corresponding to an initial evaporation moment of the sample droplet and a current area corresponding to a current evaporation moment;

[0009] Step S2: obtaining a current droplet ratio of the sample droplets according to the initial area and the current area;

[0010] Step S3: determining whether the current droplet proportion is less than a preset proportion threshold;

[0011] Step S4: in response to the current droplet proportion being less than a preset proportion threshold, moving the pre-prepared solvent droplets to the target electrode region where the sample droplets are located;

[0012] Step S5: merging and splitting the sample droplets and the solvent droplets according to preset rules to obtain merged droplets and excess solvent droplets, and driving the excess solvent droplets to a region away from the merged droplets;

[0013] Step S6: uniformly mixing the merged droplets according to a preset path to obtain uniformly mixed sample droplets.

[0014] Preferably, the area detection model is pre-trained in the following manner:

[0015] Collect multiple droplet images of the sample droplet on the digital microfluidic chip at equal time intervals from the initial evaporation moment to the moment when the droplet is completely evaporated, to obtain a droplet image data set;

[0016] Annotating image boundaries in the droplet image dataset to obtain a training dataset;

[0017] Obtain an initial pre-trained model, wherein the initial pre-trained model is a YOLOv8 instance segmentation model;

[0018] The initial pre-training model is trained using the training data set to obtain the area detection model.

[0019] Preferably, a pre-trained area detection model is used to perform real-time detection on the sample droplets on the digital microfluidic chip to obtain an initial area corresponding to the initial evaporation moment of the sample droplets and a current area corresponding to the current evaporation moment, including:

[0020] Capturing images of sample droplets on the digital microfluidic chip at an initial moment and a current moment, respectively, to obtain an initial droplet image and a current droplet image;

[0021] The initial droplet image and the current droplet image are input into the area detection model for processing to obtain the initial area of ​​the initial droplet and the current area of ​​the current droplet.

[0022] Preferably, the area detection model processes the initial droplet and the current droplet, comprising the following steps:

[0023] Obtaining the boundary mask of the initial droplet and the boundary mask of the current droplet;

[0024] Based on the boundary mask of the initial droplet and the boundary mask of the current droplet, a boundary contour of the initial droplet and a boundary contour of the current droplet are obtained;

[0025] The boundary contour area of ​​the initial droplet and the boundary contour area of ​​the current droplet are calculated respectively to obtain the initial area of ​​the initial droplet and the current area of ​​the current droplet.

[0026] Preferably, the current droplet ratio of the sample droplets is expressed by formula (1):

[0027]

[0028] Among them, R is the current droplet ratio, S t is the current area of ​​the sample droplet, and S0 is the initial area of ​​the sample droplet.

[0029] Preferably, the preset percentage threshold is determined by the tolerance of the substance concentration error of the sample droplet.

[0030] Preferably, merging and splitting the sample droplets and the solvent droplets according to a preset rule to obtain a merged droplet and excess solvent droplets comprises:

[0031] Acquire a first area a1 of the sample droplet and a second area a2 of the solvent droplet at the current evaporation moment in the target electrode region;

[0032] When the first area a1, the second area a2 and the original area a0 of the sample droplet before the droplet evaporates satisfy formula (2), the sample droplet and the solvent droplet are merged to obtain the merged droplet and the excess solvent droplet, and the excess solvent droplet is removed through a3 continuous electrodes adjacent to the target electrode area; otherwise, repeat step S4;

[0033] Wherein, formula (2) is:

[0034] a1+a2>a0+a4 (2);

[0035] in, To round up, a4 is the area of ​​the droplet occupying a single electrode.

[0036] Preferably, the preset path is a closed loop composed of a plurality of adjacent electrodes; the merged droplets perform reciprocating motion in the closed loop so that the merged droplets are evenly mixed to obtain evenly mixed sample droplets.

[0037] Another embodiment of the present application discloses a precise liquid replenishment device for digital microfluidic droplets, comprising:

[0038] Droplet detection module: Use a pre-trained area detection model to perform real-time detection on the sample droplets on the digital microfluidic chip to obtain the initial area corresponding to the initial evaporation moment of the sample droplet and the current area corresponding to the current evaporation moment;

[0039] A liquid replenishment calculation module: obtaining a current droplet ratio of the sample droplet according to the initial area and the current area;

[0040] Liquid replenishment judgment module: judge whether the current droplet ratio is less than a preset ratio threshold;

[0041] A droplet moving module: in response to the current droplet proportion being less than a preset proportion threshold, moves the pre-prepared solvent droplets to the target electrode region where the sample droplets are located;

[0042] Droplet processing module: merge and split the sample droplets and the solvent droplets according to preset rules to obtain merged droplets and excess solvent droplets, and drive the excess solvent droplets to a region away from the merged droplets;

[0043] Droplet mixing module: uniformly mix the merged droplets according to a preset path to obtain uniformly mixed sample droplets.

[0044] The present invention detects the areas of sample droplets and solvent droplets in real time and calculates the current droplet ratio of sample droplets. When the current droplet ratio of sample droplets is less than a preset ratio threshold, the pre-prepared solvent droplets are merged with the sample droplets, and then the merged droplets are split, the excess droplets are removed, and the droplets are reciprocated along a preset path to finally form uniformly mixed sample droplets. Compared with the prior art, the present invention has the following beneficial effects:

[0045] (1) High stability. Compared with the traditional endocytic rehydration method, the touch rehydration scheme of the present invention can more accurately replenish the evaporation reaction system to its original volume, without being restricted by the integer multiples of the minimum unit droplet. This high-precision rehydration method can stably maintain the substance concentration of the reaction system and avoid the negative effects caused by droplet evaporation;

[0046] (2) High reliability. The touch rehydration technology of the present invention shows high reliability in cell culture and can successfully culture normal human dermal fibroblasts (NHDF) on a digital microfluidic chip for up to 4 days. In conventional technical solutions, the cells will die due to evaporation within 20 hours. Therefore, the present invention can be applied in precision biochemical experiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] By referring to the following drawings, the exemplary embodiments of the present invention can be more completely understood. The drawings are used to provide a further understanding of the embodiments of the present application, and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the present invention and do not constitute a limitation of the present invention. In the drawings, the same reference numerals generally represent the same parts or steps.

[0048] Figure 1 A flow chart of a precise liquid replenishment method for digital microfluidic droplets provided according to an exemplary embodiment of the present application;

[0049] Figure 2 A schematic diagram of the structure of a digital microfluidic chip provided according to an exemplary embodiment of the present application;

[0050] Figure 3 A diagram showing a precise liquid replenishment process of a digital microfluidic droplet provided according to an exemplary embodiment of the present application;

[0051] Figure 4 A diagram illustrating a partial refilling process of a digital microfluidic droplet provided according to an exemplary embodiment of the present application;

[0052] Figure 5 A diagram illustrating a mixing process of a digital microfluidic droplet according to an exemplary embodiment of the present application;

[0053] Figure 6 It is a schematic structural diagram of a digital microfluidic droplet precision liquid replenishment device provided according to another exemplary embodiment of the present application. DETAILED DESCRIPTION

[0054] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0055] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.

[0056] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0057] In addition, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0058] Example 1

[0059] The embodiment of the present application provides a method for precise liquid replenishment of digital microfluidic droplets, which is described below in conjunction with the accompanying drawings.

[0060] Reference Figure 1 , which shows a precise liquid replenishment method for digital microfluidic droplets provided by some embodiments of the present application, such as Figure 1 As shown, the following steps are included:

[0061] Step S1: using a pre-trained area detection model to perform real-time detection on the sample droplets on the digital microfluidic chip to obtain the initial area corresponding to the initial evaporation moment of the sample droplets and the current area corresponding to the current evaporation moment;

[0062] In this embodiment, the overhead video method is used to obtain the top view area of ​​the droplet, which is used to represent the volume of the droplet. Here, the flattened droplet between the upper and lower plates is regarded as a cylinder, and the top view area of ​​the droplet is proportional to the volume of the droplet, and the proportionality coefficient is equal to the gap height between the upper and lower plates.

[0063] Specifically, in this embodiment, the area detection model is pre-trained in the following manner:

[0064] Dataset preparation: Multiple droplet images of the sample droplets on the digital microfluidic chip are collected at equal time intervals from the initial evaporation moment to the moment when the droplets are completely evaporated;

[0065] In this embodiment, a video of the entire process of a droplet evaporating from the beginning to the complete evaporation is recorded, and 50 images are captured at equal intervals to obtain images of the droplet at different evaporation ratios. The acquisition is repeated 10 times to obtain multiple images of the droplet. Figure 2 A schematic diagram of the structure of the digital microfluidic chip of the present invention is given to facilitate the subsequent processing of droplet motion.

[0066] Image preprocessing: annotate the image boundaries in the droplet image dataset to obtain a training dataset;

[0067] In this implementation, labelme software is used to annotate the boundary information of each droplet, and the annotation result is in json format, which is then converted to txt format supported by yolo. In this embodiment, all droplets in the captured image are annotated. One image contains one or more droplets. Before training the model, the image needs to be preprocessed: for example, the image is adjusted to a uniform size; the pixel value of the image is normalized to the range of [0,1]; and the image is rotated, flipped, scaled, and other operations are also included to increase the diversity of the data; in this embodiment, the data is annotated using labelme software, which must first be converted to txt format supported by yolo.

[0068] Model establishment: obtaining an initial pre-trained model, wherein the initial pre-trained model is a YOLOv8 instance segmentation model;

[0069] Specifically, YOLO (You Only Look Once) is a target detection algorithm based on deep learning. It directly predicts bounding boxes and category probabilities on an image at the same time, achieving fast and accurate target detection. The main feature of the YOLO algorithm is that it converts the target detection task into a regression problem by dividing the image into grids, each of which is responsible for detecting targets that fall into its area. This method greatly improves the processing speed while maintaining a high detection accuracy. The YOLO v8 instance segmentation model is the latest member of the YOLO family. It is an end-to-end deep learning model for target detection and instance segmentation.

[0070] Model training: The initial pre-training model is trained using the training data set to obtain the area detection model.

[0071] Specifically, by training the data set, a model capable of identifying the type and contour of droplets and calculating their area is obtained. During the model training process, the parameters are tuned according to the characteristics of the data set to ensure the accuracy of the model, and the best model obtained through training is adopted, that is, the area detection model. In this embodiment, the YOLOv8 algorithm is used for model training. During the training process, the model will continuously iterate and optimize the parameters to gradually improve the detection accuracy of droplets. After the training is completed, the model weights are saved for use in the subsequent droplet detection process.

[0072] In this embodiment, a pre-trained area detection model is used to perform real-time detection on a sample droplet on a digital microfluidic chip to obtain an initial area corresponding to an initial evaporation moment of the sample droplet and a current area corresponding to a current evaporation moment, including:

[0073] Capturing images of sample droplets on the digital microfluidic chip at an initial moment and a current moment, respectively, to obtain an initial droplet image and a current droplet image;

[0074] The initial droplet image and the current droplet image are input into the area detection model for processing to obtain the initial area of ​​the initial droplet and the current area of ​​the current droplet.

[0075] The area detection model processes the initial droplet and the current droplet, including the following steps:

[0076] Obtaining the boundary mask of the initial droplet and the boundary mask of the current droplet;

[0077] Based on the boundary mask of the initial droplet and the boundary mask of the current droplet, a boundary contour of the initial droplet and a boundary contour of the current droplet are obtained;

[0078] The boundary contour area of ​​the initial droplet and the boundary contour area of ​​the current droplet are calculated respectively to obtain the initial area of ​​the initial droplet and the current area of ​​the current droplet.

[0079] In this embodiment, during the prediction process, the model outputs a boundary mask for each droplet. Based on the mask, the boundary contour of the droplet is extracted, and the area information of the droplet is obtained by calculating the area of ​​the contour. Finally, the identified droplet boundary and area data are annotated on the original image. The boundary and area of ​​each droplet are displayed through image annotation, providing an intuitive reference for subsequent droplet morphology analysis. This step ensures an intuitive presentation of the results to facilitate further analysis and application of droplet morphology and features by users.

[0080] Step S2: obtaining the current droplet ratio of the sample droplets according to the initial area and the current area;

[0081] Specifically, the current droplet ratio of the sample droplet is expressed by formula (1):

[0082]

[0083] Among them, R is the current droplet ratio, S t is the current area of ​​the sample droplet, and S0 is the initial area of ​​the sample droplet.

[0084] Step S3: Determine whether the current droplet ratio is less than a preset ratio threshold;

[0085] In this embodiment, the real-time area of ​​the droplet on the digital microfluidic chip is obtained by taking a top-down shot. When the droplet is reduced to a specified threshold (for example, 0.02 mm 2 , or 20% of the original droplet system, that is, the preset proportion threshold) triggers the liquid replenishment instruction; specifically, the droplet reduction specified value is positively correlated with the substance concentration error tolerance of the liquid reaction system, and the substance concentration error tolerance directly determines the setting of the above threshold.

[0086] Step S4: in response to whether the current droplet ratio is less than a preset ratio threshold, moving the pre-prepared solvent droplets to the target electrode area where the sample droplets are located;

[0087] Specifically, after the refilling conditions are met, the droplet merging operation is performed to drive the solvent droplets to the electrode area where the sample droplets are located for merging. During the droplet merging process, the electrode where the sample droplet (target droplet) is located needs to remain energized. On the one hand, this is to ensure that the process of driving the replenishing solvent droplets does not move the position of the sample droplets; on the other hand, it is also to reduce the diffusion of substances caused by the movement of the droplets after the droplet merging, so that the boundaries are clear and more friendly to the touch refill, and the solutes in the target droplets will not be taken away after separation.

[0088] Step S5: merging and splitting the sample droplets and the solvent droplets according to preset rules to obtain merged droplets and excess solvent droplets, and driving the excess solvent droplets to a region away from the merged droplets;

[0089] Specifically, in order to keep the original unit volume of the sample droplets after rehydration, it is necessary to remove the excess droplets from all the droplets after merging, that is, to split the droplets after merging. The process of splitting according to the preset rules is as follows:

[0090] (1) obtaining a first area a1 of the sample droplet and a second area a2 of the solvent droplet at the current evaporation moment in the target electrode region;

[0091] (2) When the first area a1, the second area a2, and the original area a0 of the sample droplet before the droplet evaporates satisfy formula (2), the sample droplet and the solvent droplet are merged to obtain a merged droplet and excess solvent droplets, and the excess solvent droplets are removed by a3 continuous electrodes adjacent to the target electrode area; otherwise, repeat step S4;

[0092] Among them, formula (2) is:

[0093] a1 + a2 > a0 + a4 (2);

[0094] Among them, is the ceiling function, a4 is the area of the droplet occupying a single electrode, that is, the area of the smallest droplet that can be driven by a single driving electrode.

[0095] Figure 3 The demonstration process of the precise touch replenishment solution of the present invention is shown. Only 32 s is taken as a process for illustration. Specifically, the sample droplet is a pH reagent (gray, yellow in reality) with a volume of two units (0.8 uL), and the solvent droplet is a KOH solution of two units (transparent). Here, the unit is calculated based on the bottom area of the system electrode of 4 mm 2 , and the height of 0.2 mm. Specifically, the unit droplet refers to the droplet on a single driving electrode of digital microfluidics. In this embodiment, the sample droplet before evaporation is only taken as an example of 2 units, and it can also be other preset initial unit volumes, which will be described in detail below.

[0096] Specifically, the original area of the sample droplet is 2 units (defining 1 unit = a4, that is, the area is 2 * a4); during the evaporation process: at the current moment (0 s, that is, when the replenishment starts), the area of the sample droplet is greater than 1 unit and less than 2 units, and the replenishment operation is started. At this time, the area of the solvent droplet required is 2 units; at 2 s, the sample droplet and the solvent droplet are merged; at 4 s, the sample droplet is filled to 2 units through the solvent droplet. At this time, a merged droplet and an excess solvent droplet are formed. The area of the excess solvent droplet is (a1 + a2 - a0) units (a4 < a1 + a2 - a0 < 2 * a4). In order to effectively remove the excess droplet, at this time, it is necessary to power on all 2 (that is, ) electrodes to remove it to an area outside the merged droplet.

[0097] S6: Uniformly mix the merged droplet along a preset path to obtain a uniformly mixed sample droplet.

[0098] In this embodiment, Figure 4The process of steps S1-S5 is demonstrated. At 0s, the sample droplet reaction system before evaporation is 2 unit droplets. Under the action of evaporation, the sample droplet is reduced to less than 2 units. At 2s, the preset rehydration strategy is triggered, that is, the droplets are merged, driving solvent droplets of not less than 2 unit volumes to merge with the evaporated sample droplets. At 4s, more than 2 unit droplets of solvent droplets (replenishing liquid) are detected in the merged system, and the extra droplets are excess droplets. The two electrodes covered by the original sample droplets are energized. The droplets are split by the electrodes. At 6s, the excess solvent droplets are removed. After 6s, the merged droplets are reciprocated along the specified path to complete the mixing of the sample droplets and the solvent droplets to form new sample droplets.

[0099] Specifically, the preset path is a closed loop composed of a plurality of adjacent electrodes, and the merged droplets make a reciprocating motion in the closed loop so that the merged droplets are evenly mixed to obtain uniformly mixed sample droplets. Figure 5 The droplets are mixed along a specified path (the rectangular path indicated by the arrow as an example), where ON is the power-on state of the electrode and OFF is the power-off state of the electrode. It is found in the experiment that the droplets circle along a path 2-5 times longer. For example, when two unit droplets occupy two electrodes and the mixing path is composed of 4-10 electrodes, the mixing efficiency is higher, preferably 3 times (two unit droplets are mixed on 6 electrodes).

[0100] The present invention detects the areas of sample droplets and solvent droplets in real time and calculates the current refill accuracy coefficient of the sample droplets. When the current refill accuracy coefficient of the sample droplets is less than a preset accuracy threshold, the pre-prepared solvent droplets are merged with the sample droplets, and then the merged droplets are split, the excess droplets are removed, and the droplets are reciprocated along a preset path to finally form evenly mixed sample droplets. The solution of the present invention realizes automatic refill of droplets by accurately measuring the area of ​​sample droplets in real time. The droplets move quickly, which can greatly reduce the time consumption. A large number of droplets can be manipulated at the same time, and finally the substance concentration of the original reaction system can be stably maintained, thereby avoiding the negative impact of droplet evaporation.

[0101] Example 2

[0102] The embodiment of the present application provides a precise liquid replenishment device for digital microfluidic droplets, which is based on the same inventive concept as the method provided in the previous embodiment of the present application and has the same beneficial effects.

[0103] Reference Figure 6 , which shows a digital microfluidic droplet precision liquid replenishment device 20 provided in some embodiments of the present application, the system includes:

[0104] Droplet detection module 201: Use a pre-trained area detection model to perform real-time detection on the sample droplets on the digital microfluidic chip to obtain the initial area corresponding to the initial evaporation moment of the sample droplets and the current area corresponding to the current evaporation moment;

[0105] Liquid replenishment calculation module 202: obtaining a current droplet ratio of the sample droplets according to the initial area and the current area;

[0106] Liquid replenishment judgment module 203: judging whether the current liquid drop proportion is less than a preset proportion threshold;

[0107] Droplet moving module 204: in response to the current droplet proportion being less than a preset proportion threshold, moves the pre-prepared solvent droplets to the target electrode region where the sample droplets are located;

[0108] Droplet processing module 205: merge and split the sample droplets and the solvent droplets according to preset rules to obtain merged droplets and excess solvent droplets, and drive the excess solvent droplets to a region away from the merged droplets;

[0109] Droplet mixing module 206: uniformly mixes the merged droplets according to a preset path to obtain uniformly mixed sample droplets.

[0110] It should be noted that the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the systems, methods and computer program products according to multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of a code contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of the boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0111] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0112] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0113] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0114] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0115] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0116] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application, and they should all be included in the scope of the claims and specification of the present application.

Claims

1. A method for precise liquid replenishment of digital microfluidic droplets, characterized in that: The steps include: Step S1: using a pre-trained area detection model to perform real-time detection on a sample droplet on a digital microfluidic chip, and obtaining an initial area corresponding to an initial evaporation moment of the sample droplet and a current area corresponding to a current evaporation moment; Step S2: obtaining a current droplet ratio of the sample droplets according to the initial area and the current area; Step S3: determining whether the current droplet proportion is less than a preset proportion threshold; Step S4: in response to the current droplet proportion being less than a preset proportion threshold, moving the pre-prepared solvent droplets to the target electrode region where the sample droplets are located; Step S5: merging and splitting the sample droplets and the solvent droplets according to preset rules to obtain merged droplets and excess solvent droplets, and driving the excess solvent droplets to a region away from the merged droplets; Step S6: uniformly mixing the merged droplets according to a preset path to obtain uniformly mixed sample droplets.

2. The precise liquid replenishment method of a digital microfluidic droplet according to claim 1, characterized in that: The area detection model is obtained by pre-training in the following manner: Collect multiple droplet images of the sample droplet on the digital microfluidic chip at equal time intervals from the initial evaporation moment to the moment when the droplet is completely evaporated, to obtain a droplet image data set; Annotating image boundaries in the droplet image dataset to obtain a training dataset; Obtain an initial pre-trained model, wherein the initial pre-trained model is a YOLOv8 instance segmentation model; The initial pre-training model is trained using the training data set to obtain the area detection model.

3. The precise liquid replenishment method of a digital microfluidic droplet according to claim 2, characterized in that: The sample droplets on the digital microfluidic chip are detected in real time using a pre-trained area detection model to obtain an initial area corresponding to an initial evaporation moment of the sample droplets and a current area corresponding to a current evaporation moment, including: Capturing images of sample droplets on the digital microfluidic chip at an initial moment and a current moment, respectively, to obtain an initial droplet image and a current droplet image; The initial droplet image and the current droplet image are input into the area detection model for processing to obtain the initial area of ​​the initial droplet and the current area of ​​the current droplet.

4. The precise liquid replenishment method of a digital microfluidic droplet according to claim 1, characterized in that: The area detection model processes the initial droplet and the current droplet, including the following steps: Obtaining the boundary mask of the initial droplet and the boundary mask of the current droplet; Based on the boundary mask of the initial droplet and the boundary mask of the current droplet, a boundary contour of the initial droplet and a boundary contour of the current droplet are obtained; The boundary contour area of ​​the initial droplet and the boundary contour area of ​​the current droplet are calculated respectively to obtain the initial area of ​​the initial droplet and the current area of ​​the current droplet.

5. The precise liquid replenishment method of a digital microfluidic droplet according to claim 1, characterized in that: The current droplet ratio of the sample droplet is expressed by formula (1): Among them, R is the current droplet ratio, S t is the current area of ​​the sample droplet, and S0 is the initial area of ​​the sample droplet.

6. The precise liquid replenishment method of a digital microfluidic droplet according to claim 1, characterized in that: The preset percentage threshold is determined by the error tolerance of the substance concentration of the sample droplet.

7. The precise liquid replenishment method of a digital microfluidic droplet according to claim 1, characterized in that: The sample droplets and the solvent droplets are merged and split according to a preset rule to obtain merged droplets and excess solvent droplets, including: Acquire a first area a1 of the sample droplet and a second area a2 of the solvent droplet at the current evaporation moment in the target electrode region; When the first area a1, the second area a2 and the original area a0 of the sample droplet before the droplet evaporates satisfy formula (2), the sample droplet and the solvent droplet are merged to obtain the merged droplet and the excess solvent droplet, and the excess solvent droplet is removed through a3 continuous electrodes adjacent to the target electrode area; otherwise, repeat step S4; Wherein, formula (2) is: a1+a2>a0+a4 (2); in, To round up, a4 is the area of ​​the droplet occupying a single electrode.

8. The precise liquid replenishment method of a digital microfluidic droplet according to claim 1, characterized in that: The preset path is a closed loop composed of a plurality of adjacent electrodes; the merged droplets perform reciprocating motion in the closed loop so that the merged droplets are evenly mixed to obtain evenly mixed sample droplets.

9. A digital microfluidic droplet precision liquid replenishment device, characterized in that: include: Droplet detection module: Use a pre-trained area detection model to perform real-time detection on the sample droplets on the digital microfluidic chip to obtain the initial area corresponding to the initial evaporation moment of the sample droplet and the current area corresponding to the current evaporation moment; A liquid replenishment calculation module: obtaining a current droplet ratio of the sample droplet according to the initial area and the current area; Liquid replenishment judgment module: judge whether the current droplet ratio is less than a preset ratio threshold; A droplet moving module: in response to the current droplet proportion being less than a preset proportion threshold, moves the pre-prepared solvent droplets to the target electrode region where the sample droplets are located; Droplet processing module: merge and split the sample droplets and the solvent droplets according to preset rules to obtain merged droplets and excess solvent droplets, and drive the excess solvent droplets to a region away from the merged droplets; Droplet mixing module: uniformly mix the merged droplets according to a preset path to obtain uniformly mixed sample droplets.

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