A method and device for precise liquid supplement of digital microfluidic droplets

Abstract

The application discloses a precision liquid supplement method and device for digital microfluidic droplets, and the application moves a pre-prepared solvent droplet to a target electrode region where a sample droplet is located when a current droplet proportion of the sample droplet is less than a preset proportion threshold by real-time detection on the areas of the sample droplet and the solvent droplet and calculation of the current droplet proportion of the sample droplet, merges and splits the sample droplet and the solvent droplet according to a preset rule, obtains a merged droplet and a redundant solvent droplet, removes the redundant solvent droplet, and then makes the merged droplet reciprocate along a preset path, and finally forms a sample droplet with uniform mixing. The scheme of the application realizes automatic liquid supplement of the digital microfluidic droplets by real-time and accurate measurement on the area of the sample droplet, can simultaneously control a large number of droplets, can finally stably maintain the substance concentration of the original reaction system, and thus avoids negative effects caused by droplet evaporation.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of digital microfluidics, and particularly relates to a precise liquid supplementing method and device for digital microfluidic droplets. BACKGROUND

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

[0003] Digital microfluidics (DMF) is a discrete droplet automated manipulation technology. By sequentially applying power to an electrode array, operations such as micro- to nano-liter droplet generation, transport, merging, and splitting can be achieved. DMF is becoming an increasingly popular tool in biological and biochemical applications. A DMF device is usually composed of two electrode plates, with a droplet sandwiched between the electrode plates. Evaporation of the droplet between the electrode plates is a major challenge for DMF, because reagent loss and concentration changes will directly lead to reaction result deviation and detection result distortion, and severe evaporation will also cause droplet driving failure. Therefore, effectively inhibiting microdroplet evaporation 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) the use of a sealing structure to contain the oil increases complexity; 2) unnecessary liquid-liquid extraction, which causes the reaction to enter the oil, is incompatible with oil-soluble liquids (such as organic solvents, such as alcohols); 3) unnecessary heat dissipation destroys the local droplet temperature control; 4) evaporation-promoting solute condensation and separation operations are limited. The second commonly used method is to place the air matrix DMF device in a closed humidified chamber, but this method has the disadvantage of relying on the experience of the operator. The third method is to use unit droplet supplementing (droplet volume on a single driving electrode), and the disadvantages of this method are: limited accuracy for maintaining a constant reaction volume (limiting supplementing accuracy = unit droplet volume / (2 * total reaction volume)), and the smaller the reaction volume, the greater the error; at the same time, environmental factors affecting evaporation are not considered, and the minimum volume of solvent droplet driving to supplement the reaction volume is prone to driving failure, especially in high-temperature conditions where the solvent droplet also evaporates.

[0005] Therefore, how to design an efficient, simple digital microfluidic droplet operation method that can inhibit droplet evaporation is a technical problem to be solved. SUMMARY

[0006] Therefore, it is necessary to provide a digital microfluidic droplet precise liquid supplement method and device to solve the existing problems.

[0007] The embodiment of the present application provides a digital microfluidic droplet precise liquid supplement method, which comprises the following steps:

[0008] Step S1: A pre-trained area detection model is used to detect the sample droplets on the digital microfluidic chip in real time, so as to obtain an initial area corresponding to an initial evaporation time and a current area corresponding to a current evaporation time of the sample droplets;

[0009] Step S2: According to the initial area and the current area, a current droplet proportion of the sample droplets is obtained;

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

[0011] Step S4: When the current droplet proportion is less than the preset proportion threshold, a pre-prepared solvent droplet is moved to a target electrode region where the sample droplet is located;

[0012] Step S5: The sample droplet and the solvent droplet are merged and split according to a preset rule, a merged droplet and a redundant solvent droplet are obtained, and the redundant solvent droplet is driven to an area away from the merged droplet;

[0013] Step S6: The merged droplet is uniformly mixed according to a preset path, and a uniformly mixed sample droplet is obtained.

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

[0015] A plurality of droplet images of the sample droplets on the digital microfluidic chip from the initial evaporation time to the complete evaporation time of the droplets are collected at equal time intervals, and a droplet image data set is obtained;

[0016] The image boundaries in the droplet image data set are data-labeled, and a training data set is obtained;

[0017] An initial pre-training model is obtained, wherein the initial pre-training model is a YOLOv8 instance segmentation model;

[0018] The initial pre-training model is trained through the training data set, and the area detection model is obtained.

[0019] Preferably, the area detection model is pre-trained in the following manner:

[0020] acquiring an initial droplet image and a current droplet image of the sample droplet on the digital microfluidic chip at an initial time and a current time respectively;

[0021] inputting the initial droplet image and the current droplet image into an area detection model for processing to obtain an initial area of the initial droplet and a current area of the current droplet.

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

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

[0024] obtaining a boundary contour of the initial droplet and a boundary contour of the current droplet based on the boundary mask of the initial droplet and the boundary mask of the current droplet;

[0025] calculating the boundary contour area of the initial droplet and the boundary contour area of the current droplet respectively to obtain the initial area of the initial droplet and the current area of the current droplet.

[0026] Preferably, the current droplet proportion of the sample droplet is represented by formula (1):

[0027]

[0028] wherein R is the current droplet proportion, S t is the current area of the sample droplet, and S0 is the initial area of the sample droplet.

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

[0030] Preferably, the sample droplet and the solvent droplet are merged and split according to a preset rule to obtain a merged droplet and a redundant solvent droplet, including:

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

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

[0033] wherein formula (2) is:

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

[0035] wherein, is rounded up, and a4 is the area of the droplet occupying a single electrode.

[0036] Preferably, the preset path is a closed loop formed by a plurality of adjacent electrodes; and the merged droplet is reciprocated in the closed loop so that the merged droplet is uniformly mixed to obtain a uniformly mixed sample droplet.

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

[0038] The droplet detection module: a pre-trained area detection model is used to detect the sample droplet on the digital microfluidic chip in real time, and the initial area corresponding to the initial evaporation time and the current area corresponding to the current evaporation time of the sample droplet are obtained.

[0039] The liquid supplementing calculation module: according to the initial area and the current area, the current droplet proportion of the sample droplet is obtained.

[0040] The liquid supplementing judgment module: whether the current droplet proportion is less than a preset proportion threshold is judged.

[0041] The droplet moving module: when the current droplet proportion is less than the preset proportion threshold, the pre-prepared solvent droplet is moved to the target electrode region where the sample droplet is located.

[0042] The droplet processing module: the sample droplet and the solvent droplet are merged and split according to a preset rule, a merged droplet and a redundant solvent droplet are obtained, and the redundant solvent droplet is driven to an area far away from the merged droplet.

[0043] The droplet mixing module: the merged droplet is uniformly mixed according to a preset path to obtain a uniformly mixed sample droplet.

[0044] The present application detects the areas of the sample droplet and the solvent droplet in real time, calculates the current droplet proportion of the sample droplet, merges the pre-prepared solvent droplet with the sample droplet when the current droplet proportion of the sample droplet is less than the preset proportion threshold, splits the merged droplet, removes the redundant droplet, and then reciprocates the droplet along the preset path to finally form a uniformly mixed sample droplet.

[0045] (1) High stability: compared with the traditional pinocytosis liquid supplementing method, the touch liquid supplementing scheme of the present application can more accurately supplement the evaporation reaction system to its original volume, and is not limited by the integer multiple of the minimum unit droplet. This kind of high-precision liquid supplementing method can stably maintain the material concentration of the reaction system and avoid the negative effects caused by droplet evaporation.

[0046] (2)High reliability, the touch liquid supplement technology of the application 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, while in the conventional technical solution, the cells will die due to evaporation within 20 hours, so the application can be applied in precise biochemistry experiments. BRIEF DESCRIPTION OF DRAWINGS

[0047] The exemplary embodiments of this application can be more fully understood by reference to the following drawings. The drawings are provided for illustrative purposes, and form a part of this specification, and together with the specification serve to explain the present application, and do not limit the present application in any way. In the drawings, like reference numerals refer to the same components throughout.

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

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

[0050] Figure 3 A precise liquid supplement process demonstration diagram of a digital microfluidic droplet according to an exemplary embodiment of the application;

[0051] Figure 4 A partial liquid supplement process demonstration diagram of a digital microfluidic droplet according to an exemplary embodiment of the application;

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

[0053] Figure 6 A structural schematic diagram of a precise liquid supplement device for a digital microfluidic droplet according to another exemplary embodiment of the application. DETAILED DESCRIPTION

[0054] Exemplary embodiments of the present disclosure will be described more fully hereinafter with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it is understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that the present disclosure can be more thoroughly understood, and the scope of the present disclosure can be accurately conveyed to those skilled in the art.

[0055] In the description of the present application, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer" and the like indicate the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application. In addition, the terms "first", "second", "third" are only for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0056] In the description of the present application, it should be noted that unless otherwise explicitly specified and limited, the terms "mounting", "connecting", "connecting" should be understood in a broad sense, for example, it can be fixedly connected, or it can be detachably connected, or integrally connected; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or it can be indirectly connected through an intermediate medium; it can be the communication inside two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

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

[0058] Embodiment 1

[0059] The embodiment of the present application provides a precise liquid supplementing method for digital microfluidic droplets, which will be described below with reference to the accompanying drawings.

[0060] Reference Figure 1 It shows a precise liquid supplementing method for digital microfluidic droplets provided by some embodiments of the present application, as shown in Figure 1 The method comprises the following steps:

[0061] Step S1: Real-time detection of sample droplets on a digital microfluidic chip is performed by using a pre-trained area detection model to obtain an initial area corresponding to an initial evaporation time and a current area corresponding to a current evaporation time of the sample droplets;

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

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

[0064] Data set preparation: A plurality of droplet images of sample droplets on a digital microfluidic chip from an initial evaporation time to a complete evaporation time of the droplets are collected at equal time intervals;

[0065] In this embodiment, the video of recording the droplet from the beginning to the complete evaporation process is taken at equal intervals to obtain 50 images of the droplet at different evaporation rates. Repeat the collection 10 times to obtain multiple droplet images. Figure 2 The structure of the digital microfluidic chip is shown, which is convenient for subsequent processing of droplet movement.

[0066] Image preprocessing: data labeling is performed on the image boundary in the droplet image data set to obtain a training data set;

[0067] In this embodiment, the labelme software is used to label the boundary information of each droplet, and the labeling result is in json format, which is then converted into a txt format supported by yolo. In this embodiment, all droplets in the intercepted images are labeled, and one or more droplets are included in one image. 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 [0, 1]; and the image is rotated, flipped, scaled, etc. to increase the diversity of the data; in this embodiment, the labelme software is used for data labeling, and it must be converted into a txt format supported by yolo.

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

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

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

[0071] Specifically, through training of the data set, a model capable of identifying the droplet category, the contour, and calculating the area thereof is obtained. During the training process of the model, parameters are optimized according to the characteristics of the data set to ensure the accuracy of the model, and the best model obtained through training, that is, the area detection model, is adopted. In this embodiment, the YOLOv8 algorithm is used for model training, and during the training process, the model iteratively optimizes the parameters to gradually improve the detection accuracy of the droplets. After the training is completed, the model weight is saved for use in subsequent detection of the droplets.

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

[0073] Image acquisition is performed on the sample droplets on the digital microfluidic chip at the initial time and the current time 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] The boundary mask of the initial droplet and the boundary mask of the current droplet are obtained;

[0077] Based on the boundary mask of the initial droplet and the boundary mask of the current droplet, the boundary contour of the initial droplet and the 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 the prediction process, the model outputs the boundary mask of 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 recognized droplet boundary and area data are labeled on the original image. The boundary and area of each droplet are displayed through image labeling, which provides an intuitive reference for subsequent droplet morphology analysis. This step ensures the intuitive presentation of the results to facilitate further analysis and application of the droplet morphology and characteristics by the user.

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

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

[0082]

[0083] wherein, R is the current droplet proportion, S t is the current area of the sample droplet, and S0 is the initial area of the sample droplet.

[0084] Step S3: determining whether the current droplet proportion is less than a preset proportion threshold value;

[0085] In this embodiment, the real-time area of the droplet on the digital microfluidic chip is obtained by top-view shooting, and when the droplet is reduced by a specified threshold value (such as 0.02 mm 2 , or 20% of the original droplet system, that is, the preset proportion threshold value), the liquid supplement instruction is triggered. 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 value.

[0086] Step S4: in response to whether the current droplet proportion is less than the preset proportion threshold value, moving the pre-prepared solvent droplet to the target electrode region where the sample droplet is located;

[0087] Specifically, after meeting the liquid supplement condition, the droplet merging operation is performed, and the solvent droplet is driven to the electrode region where the sample droplet is located for merging. The electrode where the sample droplet (target droplet) is located needs to be kept powered on during the droplet merging process, on the one hand, to ensure that the process of driving the supplemented solvent droplet will not move the position of the sample droplet; on the other hand, to reduce the substance diffusion caused by the movement of the droplet after merging, so that the boundary is clear and the supplement is more friendly, and the target droplet will not be taken away after separation.

[0088] Step S5: merging and splitting the sample droplet and the solvent droplet according to a preset rule to obtain a merged droplet and a redundant solvent droplet, and driving the redundant solvent droplet to an area away from the merged droplet;

[0089] Specifically, in order to keep the sample droplet after supplementing liquid as the original unit volume, it is necessary to remove the redundant droplet in all droplets after merging, that is, to perform a splitting operation on the droplet after merging, and the splitting process according to the preset rule 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 droplet evaporation satisfy formula (2), merging the sample droplet and the solvent droplet to obtain a merged droplet and a redundant solvent droplet, and removing the redundant solvent droplet through a3 continuous electrodes adjacent to the target electrode region; otherwise, repeating step S4;

[0092] wherein formula (2) is:

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

[0094] wherein, is rounding up, and a4 is the area of a droplet occupying a single electrode, i.e. 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 liquid replenishment scheme of the present application is shown, which is only explained by taking 32s as a process. Specifically, the sample droplet is two unit volumes (0.8uL) of pH reagent (gray, actually yellow in practice), and the solvent droplet is two units of KOH solution (transparent color). Here, the unit is calculated based on the bottom area of the system electrode 4mm 2 , and the height 0.2mm. Specifically, the unit droplet refers to the droplet on a driving electrode of the digital microfluidic, and the sample droplet before evaporation in this embodiment is only taken as an example of two units, and other preset initial unit volumes can also be used, which will be described in detail below.

[0096] Specifically, the original area of the sample droplet is two units (1 unit is defined as a4, i.e. the area is 2*a4); during the evaporation process: at the current time (0s, i.e. when the liquid replenishment starts), the area of the sample droplet is greater than one unit and less than two units, and the liquid replenishment operation is started, and the required solvent droplet area is two units; at 2s, the sample droplet and the solvent droplet are merged; at 4s, the sample droplet is filled to two units through the solvent droplet, at this time, the merged droplet and the excess solvent droplet are formed, and the area of the excess solvent droplet is (a1+a2-a0) units (a4

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

[0098] In this embodiment, Figure 4 ​The process of steps S1-S5 is shown. At 0s, the sample droplet reaction system before evaporation is two units of droplets. Under the action of evaporation, the sample droplet is reduced to less than two units; at 2s, the preset liquid supplement strategy is triggered, that is, the droplets are combined, and droplets with a volume of not less than two units of solvent droplets are combined with the evaporated sample droplets; at 4s, more than two units of droplets of solvent droplets (supplement liquid) are detected in the combined system, and the droplets are the excess droplets; the two electrodes covered by the original sample droplet are powered on; the droplets are split through the electrodes; at 6s, the excess solvent droplets are removed; and after 6s, the combined droplets are reciprocated according to the specified path, so that the mixing of the sample droplets and the solvent droplets is completed, and a new sample droplet is formed.

[0099] Specifically, the preset path is a closed loop formed by a plurality of adjacent electrodes, and the combined droplets are reciprocated in the closed loop to make the combined droplets uniformly mixed to obtain the uniformly mixed sample droplet. In this embodiment, refer to Figure 5 , the droplets are mixed according to the specified path (for example, the rectangular path indicated by the arrow), wherein ON is the power-on state of the electrode, and OFF is the power-off state of the electrode. It is found in experiments that the droplets rotate along the path by 2-5 times, for example, two units of droplets occupy two electrodes, and the mixing efficiency is higher when the mixing path is formed by 4-10 electrodes, and preferably 3 times (two units of droplets, mixed on 6 electrodes).

[0100] The present application detects the area of the sample droplet and the solvent droplet in real time, calculates the current liquid supplement precision coefficient of the sample droplet, merges the pre-prepared solvent droplet with the sample droplet when the current liquid supplement precision coefficient of the sample droplet is less than the preset precision threshold, splits the combined droplets, removes the excess droplets, and finally forms the uniformly mixed sample droplet. The scheme of the present application realizes the automatic liquid supplement of the droplet by accurately measuring the area of the sample droplet in real time, the droplet moves fast, which can greatly reduce the time consumption, and a large number of droplets can be controlled at the same time, and finally the concentration of the substances in the original reaction system can be stably maintained, thereby avoiding the negative effects caused by droplet evaporation.

[0101] Example 2

[0102] The embodiments of the present application provide a precise liquid supplement device for digital microfluidic droplets. The method provided by the foregoing embodiments of the present application has the same inventive concept and the same beneficial effects. The following will be described with reference to the accompanying drawings.

[0103] Referring to Figure 6 , a precise liquid supplement device 20 for digital microfluidic droplets provided by some embodiments of the present application is shown, and the system comprises:

[0104] The droplet detection module 201: using a pre-trained area detection model to detect the sample droplet on the digital microfluidic chip in real time, and obtain the initial area corresponding to the initial evaporation time of the sample droplet and the current area corresponding to the current evaporation time of the sample droplet;

[0105] The liquid supplement calculation module 202: obtaining the current droplet proportion of the sample droplet according to the initial area and the current area;

[0106] The liquid supplement judgment module 203: judging whether the current droplet proportion is less than a preset proportion threshold;

[0107] The droplet moving module 204: moving the pre-prepared solvent droplet to the target electrode region where the sample droplet is located in response to the current droplet proportion being less than the preset proportion threshold;

[0108] The droplet processing module 205: merging and splitting the sample droplet and the solvent droplet according to a preset rule, obtaining a merged droplet and a redundant solvent droplet, and driving the redundant solvent droplet to an area away from the merged droplet;

[0109] The droplet mixing module 206: uniformly mixing the merged droplet according to a preset path to obtain a uniformly mixed sample droplet.

[0110] It should be noted that the flowcharts and block diagrams in the drawings show the possible implementation architecture, functions and operations of the systems, methods and computer program products according to the embodiments of the present application. In this regard, each block in the flowchart or block diagram can represent a module, a program segment or a part of code, which contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions noted in the blocks can occur in different order from that noted in the drawings. For example, two consecutive blocks can actually be executed substantially in parallel, and sometimes they can be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and the combination of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system that performs the specified functions or actions, or can be implemented by 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 process of the system, device and unit described above can refer to the corresponding process in the foregoing method embodiments, which will not be described here.

[0112] In several embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented by other manners. The apparatus embodiments described above are merely illustrative, for example, the division of the units is merely a logical function division, and actual implementation can have another division manner, and for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units or components shown or discussed can be indirect coupling or communication connection through some communication interfaces, apparatuses or units, which can be electrical, mechanical or other forms.

[0113] The units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, i.e., they can be located in one place or distributed on a plurality of network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.

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

[0115] If the functions are realized in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application or the part of the present application that essentially contributes to the prior art or the part of the technical solutions can be embodied in the form of a software product, which is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various storage program codes.

[0116] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application, and they should be covered in the scope of the claims and the description of the present application.

Claims

1. A method for precise reagent addition to digital microfluidic droplets, comprising: The method comprises the following steps: Step S1: using a pre-trained area detection model to perform real-time detection on a sample droplet on a digital microfluidic chip, to obtain an initial area corresponding to an initial evaporation time of the sample droplet and a current area corresponding to a current evaporation time of the sample droplet; Step S2: obtaining a current droplet proportion of the sample droplet 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 the preset proportion threshold, moving a pre-prepared solvent droplet to a target electrode region where the sample droplet is located; Step S5: merging and splitting the sample droplet and the solvent droplet according to a preset rule, to obtain a merged droplet and a redundant solvent droplet, and driving the redundant solvent droplet to an area away from the merged droplet; Step S6: uniformly mixing the merged droplet according to a preset path, to obtain a uniformly mixed sample droplet; The area detection model is pre-trained in the following manner: Collecting a plurality of droplet images of a sample droplet on a digital microfluidic chip from an initial evaporation time to a complete evaporation time of the droplet at equal time intervals, to obtain a droplet image dataset; Data labeling is performed on image boundaries in the droplet image dataset, to obtain a training dataset; An initial pre-training model is obtained, wherein the initial pre-training model is a YOLOv8 instance segmentation model; The initial pre-training model is trained by using the training dataset, to obtain the area detection model; According to the preset rule, the sample droplet and the solvent droplet are merged and split to obtain a merged droplet and a redundant solvent droplet, which comprises: acquiring a first area of the sample droplet and a second area of the solvent droplet at the current evaporation time point in the target electrode region ; and acquiring a first area of the sample droplet and a second area of the solvent droplet at the current evaporation time point in the target electrode region ; and acquiring a first area of the sample When the first area Second area and the original area of ​​the sample droplet before evaporation When formula (2) is satisfied, the sample droplet and the solvent droplet are merged to obtain the merged droplet and the excess solvent droplet, and then passed through the region adjacent to the target electrode. One continuous electrode removes excess solvent droplets; otherwise, repeat step S4. Formula (2) is as follows: wherein , is rounded up, is the area of the droplet occupying a single electrode.

2. The method of claim 1, wherein, The 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 time of the sample droplet and a current area corresponding to a current evaporation time of the sample droplet, which comprises: Image collection is performed on a sample droplet on a digital microfluidic chip at an initial time and a current time, 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 an initial area of the initial droplet and a current area of the current droplet.

3. The method of claim 1, wherein, The area detection model processes the initial droplet and the current droplet, which comprises the following steps: Boundary masks of the initial droplet and the current droplet are obtained; Based on the boundary masks of the initial droplet and the current droplet, boundary contours of the initial droplet and the current droplet are obtained; The boundary contour areas of the initial droplet and the current droplet are calculated respectively, to obtain the initial area of the initial droplet and the current area of the current droplet.

4. The method of claim 1, wherein, The current droplet proportion of the sample droplet is represented by formula (1): wherein, is the current droplet fraction, is the current area of the sample droplet, is the initial area of the sample droplet.

5. The method of claim 1, wherein, The preset proportion threshold is determined by a substance concentration error tolerance of the sample droplet.

6. The method of claim 1, wherein, The preset path is a closed loop formed by a plurality of adjacent electrodes; the merged droplet reciprocates in the closed loop, so that the merged droplet is uniformly mixed, to obtain a uniformly mixed sample droplet.

7. A digital microfluidic droplet precise reagent replenishment device for performing the digital microfluidic droplet precise reagent replenishment method of claim 1, wherein, It comprises: The droplet detection module: a pre-trained area detection model is used to detect the sample droplet on the digital microfluidic chip in real time, and the initial area corresponding to the initial evaporation time and the current area corresponding to the current evaporation time of the sample droplet are obtained; The liquid supplement calculation module: according to the initial area and the current area, the current droplet proportion of the sample droplet is obtained; The liquid supplement judgment module: whether the current droplet proportion is less than the preset proportion threshold is judged; The droplet moving module: in response to the current droplet proportion being less than the preset proportion threshold, the pre-prepared solvent droplet is moved to the target electrode region where the sample droplet is located; The droplet processing module: according to the preset rule, the sample droplet and the solvent droplet are merged and split to obtain the merged droplet and the excess solvent droplet, and the excess solvent droplet is driven to an area away from the merged droplet; The droplet mixing module: the merged droplet is uniformly mixed according to the preset path to obtain the uniformly mixed sample droplet.

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