Micro-fluidic chip temperature control system and method based on heat conduction-heat insulation composite layer

Abstract

The invention discloses a micro-fluidic chip temperature control system and method based on a heat conduction-heat insulation composite layer, and relates to the technical field of temperature control, and the key points of the technical scheme comprise the following steps: a micro-fluidic chip with the heat conduction-heat insulation composite layer comprises a substrate, a micro-channel structure arranged on the substrate and the heat conduction-heat insulation composite layer covering the micro-channel structure, the heat conduction-heat insulation composite layer comprises a heat conduction area and a heat insulation area, the heat conduction area corresponds to a heating or cooling part of the micro-channel structure, and the heat insulation area is used for limiting heat diffusion; acquiring temperature distribution image information of the micro-fluidic chip, performing gray processing on the image information to obtain a gray image, and identifying a target area with abnormal temperature in the micro-channel structure based on the gray image; performing correlation analysis on the target area and the heat conduction area according to the gray level image to determine a temperature control parameter of the heat conduction area corresponding to the target area; the effect is that the temperature control efficiency and timeliness are improved.

Description

Technical Field

[0001] The present invention relates to the field of temperature control technology, and more particularly to a temperature control system and method for a microfluidic chip based on a heat-conducting-insulating composite layer. Background Art

[0002] Temperature control of microfluidic chips is a core element for ensuring the efficient conduct of experiments such as cell culture and drug screening. Application publication number "CN117193429A" discloses a microfluidic chip temperature control system and method, which describes "a heating element provides heat to the microfluidic chip via a heat-conducting element; a temperature-measuring element is mounted on the heat-conducting element and within the microfluidic chip, and is used to convert temperature changes into a potential difference signal; an analog-to-digital converter is used to convert the potential difference signal into a digital signal and transmit the digital signal to a microcontroller; the microcontroller is used to perform PID calculations based on the input signal and output the PID calculation results to an electronic switch; the electronic switch is used to adjust the output power based on the PID calculation results and provide it to the heating element; a DC power supply is used to provide DC power to the electronic switch; and a host computer is used to set the temperature of the microfluidic chip."

[0003] However, this method has the following limitations: on the one hand, the temperature control accuracy is insufficient, and conventional temperature control methods are difficult to cope with the complex heat transfer in the tiny space within the microchannel. Problems such as uneven temperature distribution and thermal crosstalk are prone to occur, resulting in poor experimental repeatability. For example, in cell culture experiments, local temperature fluctuations may affect cell activity and physiological characteristics, thereby interfering with experimental results; on the other hand, the temperature control lacks intelligence and adaptability. Most temperature control systems rely on manual experience to set parameters and cannot be dynamically adjusted according to the real-time temperature distribution and thermal conductivity characteristics of the chip. They have poor versatility in dealing with microfluidic chips with different structures (such as diverse microchannel layouts) and different experimental requirements (such as multiple reaction temperature requirements).

[0004] From a structural perspective, traditional microfluidic chip substrates and microchannels lack a highly efficient thermally conductive and insulating composite layer after fabrication, leading to disordered heat diffusion and difficulty achieving precise local temperature control. Traditional temperature acquisition methods (such as single-point contact temperature measurement) fail to fully reflect the chip's temperature distribution during temperature monitoring and analysis, and subsequent data processing fails to fully utilize technologies like image recognition and historical data correlation, making it difficult to accurately locate areas of temperature anomalies and intelligently derive temperature control strategies. Furthermore, an incomplete system for comprehensive consideration and quantitative analysis of factors influencing heat conduction leads to discrepancies between temperature control model predictions and actual heat transfer, making it difficult to provide a basis for parameter adjustment. Summary of the Invention

[0005] In view of the shortcomings of the prior art, the object of the present invention is to provide a temperature control system and method for a microfluidic chip based on a heat-conducting-insulating composite layer.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A temperature control method for a microfluidic chip based on a heat-conducting-insulating composite layer comprises the following steps:

[0008] The heat-conducting-insulating composite layer microfluidic chip includes a substrate, a microfluidic channel structure arranged on the substrate, and a heat-conducting-insulating composite layer covering the microfluidic channel structure. The heat-conducting-insulating composite layer includes a heat-conducting area and a heat-insulating area. The heat-conducting area corresponds to the heating or cooling part of the microfluidic channel structure, and the heat-insulating area is used to limit heat diffusion.

[0009] Collect temperature distribution image information of the microfluidic chip, perform grayscale processing on the image information to obtain a grayscale image, and identify the target area with abnormal temperature in the microfluidic structure based on the grayscale image;

[0010] Performing correlation analysis between the target area and the heat transfer area based on the grayscale image to determine the temperature control parameters of the heat transfer area corresponding to the target area; wherein the temperature control parameters include heating power, cooling rate and temperature control time;

[0011] Detect factors affecting heat conduction between the target area and the heat conduction area;

[0012] The temperature control parameters and heat conduction influencing factors are processed and analyzed to determine whether the temperature control of the target area meets the preset requirements and output temperature control adjustment instructions.

[0013] This invention achieves precise local temperature control through the thermal conductivity and thermal isolation properties of physical materials. High-purity copper foil is spliced ​​onto the bottom of the microfluidic chip as a thermally conductive layer, and a nano-ceramic aerogel plate is used as a thermal insulation layer. The copper foil is cut into a shape (such as a strip or circle) that matches the chip's target temperature control area and is attached to the bottom of the chip with thermal grease. The aerogel plate covers non-target areas to block heat diffusion. The bottom temperature control device uses a semiconductor refrigeration element (TEC) paired with a PID controller. The heat generated by the TEC is transferred to the copper foil via an aluminum heat sink and then efficiently transferred to the target area of ​​the chip. The PID controller monitors the temperature in real time and adjusts the TEC power to ensure that the temperature of the target area remains stable within an accuracy of ±0.5°C.

[0014] Preferably, the temperature control parameters and heat conduction influencing factors are processed and analyzed to determine whether the temperature control of the target area meets the preset requirements and output a temperature control adjustment instruction, which specifically includes the following steps:

[0015] Predicting the temperature change trend of the target area based on the temperature control parameters and the heat conduction influencing factors to obtain a temperature change rate set, and calculating the ratio of the temperature change rates of adjacent time periods in the temperature change rate set to obtain a first temperature change rate ratio and a second temperature change rate ratio;

[0016] The change ratio value between the first temperature change rate ratio and the second temperature change rate ratio is analyzed to determine whether the temperature control of the target area meets the preset requirements and output a temperature control adjustment instruction.

[0017] Based on the difference between the change ratio value and the threshold, combined with the heat conduction model and historical data, the adjustment amount of the temperature control parameters (such as the adjustment amplitude of the heating power, the change in the cooling rate, etc.) is reversely calculated to generate and output the temperature control adjustment instruction, so that the temperature control process of the target area is corrected in the direction that meets the preset requirements, thereby realizing precise and dynamic control of the temperature of the target area of ​​the microfluidic chip.

[0018] Preferably, the substrate is a silicon wafer or a glass wafer;

[0019] The microfluidic channel structure is formed on the substrate by photolithography and etching processes, and the microfluidic channel structure includes an inlet, an outlet, and a flow channel connected between the inlet and the outlet;

[0020] The heat-conducting and heat-insulating composite layer is formed by magnetron sputtering or chemical vapor deposition.

[0021] The present invention selects a silicon wafer or a glass wafer as a substrate, and utilizes its good physical and chemical stability to provide reliable support for subsequent structures.

[0022] Preferably, collecting temperature distribution image information of the microfluidic chip, grayscale processing the image information to obtain a grayscale image, and identifying the target area with abnormal temperature in the microfluidic structure based on the grayscale image specifically includes the following steps:

[0023] Use infrared thermal imager to collect temperature distribution image information of microfluidic chip;

[0024] Performing preliminary grayscale processing on the temperature distribution image information to obtain a first grayscale image;

[0025] Performing secondary grayscale processing on the first grayscale image to enhance the contrast between the temperature abnormality area and the normal area to obtain a second grayscale image;

[0026] Mark the area in the second grayscale image where the temperature is higher than a preset temperature threshold as the target area.

[0027] The present invention marks the area in the second grayscale image where the grayscale value corresponds to a temperature higher than the threshold as the target area, thereby accurately identifying the location of abnormal temperature in the microfluidic structure and providing an accurate regional positioning basis for subsequent temperature control adjustment and other operations.

[0028] Preferably, performing correlation analysis between the target area and the heat transfer area according to the grayscale image to determine the temperature control parameters of the heat transfer area corresponding to the target area specifically includes the following steps:

[0029] If there is a heat conduction connection area between the target area and the heat conduction area in the grayscale image, the target area and the corresponding heat conduction area are combined to form a temperature control associated area;

[0030] Collect the temperature gradients of the target area and the heat conduction area in the temperature control correlation area and output the temperature gradient to be judged;

[0031] A temperature gradient threshold is preset, and historical temperature control data is extracted when the temperature gradient to be determined is greater than or equal to the preset temperature gradient threshold;

[0032] Extracting historical temperature control case data similar to the temperature control-related area from the historical temperature control data, and determining the temperature control parameters based on the historical temperature control case data;

[0033] Historical temperature control case data similar to the temperature control associated area is extracted from the historical temperature control data, and the temperature control parameter is determined based on the historical temperature control case data.

[0034] The present invention uses an algorithm to analyze the correlation rules of case data (such as the corresponding curve between temperature gradient and heating power), derives the temperature control parameters required for the current temperature control-related area, and realizes the precise parameter setting of "historical experience migration + dynamic adaptation of scenarios", so that the temperature control strategy is based on mature practices and meets the actual thermal conduction requirements of current microfluidic chips.

[0035] Preferably, detecting the factors affecting heat conduction between the target area and the heat conduction area specifically includes the following steps:

[0036] Detect the straight-line distance between the target area and the heat transfer area and output distance data information;

[0037] After detecting the thermal conductivity distribution of the thermal conductive-insulating composite layer between the target area and the thermal conductive area, the thermal conductivity data information is output;

[0038] Detecting the flow velocity of the fluid in the microchannel near the target area and outputting flow velocity data information;

[0039] The distance data information, thermal conductivity data information and flow rate data information are combined to form heat conduction influencing factors.

[0040] The present invention jointly constitutes the factors affecting heat conduction, comprehensively reflecting the comprehensive effects of geometric distance, material thermal conductivity, fluid dynamic interaction and other aspects in the heat conduction process between the two regions, and provides basic data support for subsequent analysis of heat conduction laws and precise temperature control.

[0041] Preferably, the temperature change trend of the target area is predicted based on the temperature control parameters and the heat conduction influencing factors to obtain a temperature change rate set, and the ratio of the temperature change rates of adjacent time periods in the temperature change rate set is calculated to obtain a first temperature change rate ratio and a second temperature change rate ratio, which specifically includes the following steps:

[0042] After inputting the temperature control parameters and heat conduction influencing factors into the heat conduction model prediction, the first predicted temperature change rate of the target area is obtained;

[0043] After extracting temperature control data of a previous period and a subsequent period adjacent to the current temperature control period from the historical temperature control data, a second predicted temperature change rate and a third predicted temperature change rate of the target area are respectively predicted;

[0044] The first predicted temperature change rate, the second predicted temperature change rate and the third predicted temperature change rate are combined into a temperature change rate set;

[0045] Calculating a ratio of the first predicted temperature change rate to the second predicted temperature change rate to obtain a first temperature change rate ratio;

[0046] A ratio of the second predicted temperature change rate to the third predicted temperature change rate is calculated to obtain a second temperature change rate ratio.

[0047] The present invention associates the real-time prediction of the heat conduction model with the time period of historical data. The method constructs a rate set and rate ratio. The first rate ratio reflects the intervention effect of the current regulation on the historical trend, helping to judge whether the temperature control parameters are reasonable; the second rate ratio reveals the continuity of temperature changes, assisting in early adjustment of strategies (such as reducing the heating power in advance if it is predicted that the temperature will continue to rise); the comparison of historical data with real-time predictions can reversely optimize the heat conduction model parameters and improve the accuracy of subsequent predictions.

[0048] Preferably, analyzing the change ratio between the first temperature change rate ratio and the second temperature change rate ratio to determine whether the temperature control of the target area meets the preset requirements and outputting the temperature control adjustment instruction specifically includes the following steps:

[0049] Calculating a change ratio between the first temperature change rate ratio and the second temperature change rate ratio to obtain a change ratio value;

[0050] A preset temperature change rate ratio threshold is set, and if the change ratio value is less than or equal to the preset temperature change rate ratio threshold, it is determined that the temperature control of the target area meets the preset requirements;

[0051] If the change ratio value is greater than the preset temperature change rate change ratio threshold, it is determined that the temperature control of the target area does not meet the preset requirements;

[0052] If it is determined that the preset requirement is not met, the adjustment amount of the temperature control parameter is calculated based on the difference between the change ratio value and the preset temperature change rate change ratio threshold, and then a temperature control adjustment instruction is output.

[0053] The present invention calculates the change ratio values ​​of the first temperature change rate ratio (the rate difference between the real-time control strategy and the historical initial trend) and the second temperature change rate ratio (the rate correlation between the historical continuation trend and the future trend prediction) based on the obtained ratio, further amplifying the difference characteristics of the temperature change trend - if the first rate ratio reflects the degree of change of the current control on history, and the second rate ratio reflects the continuation stability of the trend, then the change ratio value can be understood as a comprehensive comparison indicator of the control intervention effect and the trend stability, which can more keenly capture the dynamic deviation of the temperature control process.

[0054] The temperature control system of microfluidic chip based on thermal conductive and thermal insulating composite layer includes:

[0055] Composition module: The heat-conducting-insulating composite layer microfluidic chip includes a substrate, a microfluidic channel structure arranged on the substrate, and a heat-conducting-insulating composite layer covering the microfluidic channel structure. The heat-conducting-insulating composite layer includes a heat-conducting area and a heat-insulating area. The heat-conducting area corresponds to the heating or cooling part of the microfluidic channel structure, and the heat-insulating area is used to limit heat diffusion.

[0056] Acquisition and recognition module: collects temperature distribution image information of the microfluidic chip, performs grayscale processing on the image information to obtain a grayscale image, and identifies the target area with abnormal temperature in the microfluidic structure based on the grayscale image;

[0057] Analysis module: performs correlation analysis between the target area and the heat transfer area based on the grayscale image to determine the temperature control parameters of the heat transfer area corresponding to the target area; wherein the temperature control parameters include heating power, cooling rate and temperature control time;

[0058] Detection module: detects factors affecting heat conduction between the target area and the heat conduction area;

[0059] Judgment module: processes and analyzes the temperature control parameters and heat conduction influencing factors to determine whether the temperature control of the target area meets the preset requirements and outputs temperature control adjustment instructions.

[0060] An electronic device includes a memory, a processor, and a computer program stored in the memory and runnable on the processor. When the processor executes the program, a temperature control method for a microfluidic chip based on a heat-conducting-insulating composite layer is implemented.

[0061] Compared with the prior art, the present invention has the following beneficial effects:

[0062] (1) The present invention has achieved remarkable results in terms of temperature control accuracy, intelligent control and system adaptability. From the perspective of structural construction, the silicon wafer or glass wafer is used as the substrate, and the microchannel is accurately created by photolithography and etching processes, and a heat-conducting-insulating composite layer is formed by magnetron sputtering or chemical vapor deposition to build a stable and controllable temperature control foundation. Its temperature control process achieves high-precision temperature control through the collaboration of multiple links: using an infrared thermal imager to collect temperature distribution images and accurately identify the target area with abnormal temperature through grayscale processing, so as to clarify the target for subsequent control; the target area is correlated with the heat-conducting area and analyzed, and the adaptive temperature control parameters are determined in combination with historical temperature control data, so that the parameter setting has a reliable basis; the influencing factors of heat conduction are detected, covering distance, thermal conductivity, fluid flow rate and other comprehensive considerations of heat transfer interference conditions; based on the heat conduction model and historical data, the temperature change rate is predicted and the rate ratio and change ratio values ​​are calculated to scientifically judge whether the temperature control meets the standard. If it does not meet the standard, the parameters are intelligently adjusted based on the difference.

[0063] (2) In terms of accuracy, multi-dimensional temperature monitoring and analysis, combined with heat conduction models and historical data reuse, can control the temperature control accuracy within an extremely small range, meeting the strict temperature requirements of microfluidic chips, assisting experiments such as cell culture and biochemical reactions, and ensuring stable and reliable results. At the intelligent control level, a complete closed loop is formed from abnormal area identification to dynamic parameter adjustment, without the need for frequent manual intervention. It is automatically optimized based on real-time data and historical experience, improving the efficiency and timeliness of temperature control, and adapting to complex and changing experimental scenarios. In terms of system adaptability, the preparation process of the substrate, microchannel and composite layer is mature, which can be flexibly adapted to the design requirements of different microfluidic chips. Whether it is a simple channel or a complex structure, a corresponding heat conduction-insulation system can be constructed; and the temperature control logic does not rely on specific chip materials and structures, and has a wide range of applicability. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 A schematic diagram of the steps of the temperature control method of a microfluidic chip based on a heat-conducting-insulating composite layer proposed in the present invention;

[0065] Figure 2 The module schematic diagram of the temperature control system of the microfluidic chip based on the heat conduction-insulation composite layer proposed by the present invention;

[0066] Figure 3 is a schematic structural diagram of an electronic device provided by an embodiment of the present invention;

[0067] Figure 4 It is a schematic diagram of the effect during the experiment of the temperature control system of the microfluidic chip based on the heat-conducting-insulating composite layer according to the embodiment of the present invention.

[0068] 610 , processor; 620 , communication interface; 630 , memory; 640 , communication bus. DETAILED DESCRIPTION

[0069] Reference Figures 1 to 3 shown.

[0070] Example 1 further illustrates the temperature control system and method of the microfluidic chip based on the heat-conducting-insulating composite layer proposed by the present invention.

[0071] A temperature control method for a microfluidic chip based on a heat-conducting-insulating composite layer comprises the following steps:

[0072] The heat-conducting-insulating composite layer microfluidic chip includes a substrate, a microfluidic channel structure arranged on the substrate, and a heat-conducting-insulating composite layer covering the microfluidic channel structure. The heat-conducting-insulating composite layer includes a heat-conducting area and a heat-insulating area. The heat-conducting area corresponds to the heating or cooling part of the microfluidic channel structure, and the heat-insulating area is used to limit heat diffusion.

[0073] Collect temperature distribution image information of the microfluidic chip, perform grayscale processing on the image information to obtain a grayscale image, and identify the target area with abnormal temperature in the microfluidic structure based on the grayscale image;

[0074] Correlation analysis is performed between the target area and the heat transfer area based on the grayscale image to determine the temperature control parameters of the heat transfer area corresponding to the target area; wherein the temperature control parameters include heating power, cooling rate and temperature control time;

[0075] Detect factors affecting heat conduction between the target area and the heat conduction area;

[0076] The temperature control parameters and heat conduction influencing factors are processed and analyzed to determine whether the temperature control of the target area meets the preset requirements and output temperature control adjustment instructions.

[0077] This application proposes an external temperature control system for a microfluidic chip based on a splicable thermal conductive-insulating composite layer. Its core working principle is to achieve precise local temperature control through the heat conduction and thermal isolation properties of physical materials. High-purity copper foil is spliced ​​on the bottom of the microfluidic chip as a thermal conductive layer, and a nano-ceramic aerogel plate is spliced ​​as a thermal insulation layer. The copper foil is cut into a shape that adapts to the target temperature control area of ​​the chip (such as strips or circles) and is attached to the bottom of the chip with thermal grease. The aerogel plate covers the non-target area to block heat diffusion. The bottom temperature control device uses a semiconductor refrigeration chip (TEC) combined with a PID controller. The heat generated by the TEC is transferred to the copper foil through an aluminum heat sink and then efficiently transferred to the target area of ​​the chip. The PID controller monitors the temperature in real time and adjusts the TEC power to ensure that the temperature of the target area is stable within an accuracy range of ±0.5°C.

[0078] During the heat conduction process, the system regulates the temperature conduction efficiency through multiple factors: the straight-line distance between the heat-conducting layer and the target area directly affects heat loss; the closer the distance, the higher the heat conduction efficiency; the low thermal conductivity of the aerogel plate creates thermal resistance, and its coverage area and thickness determine the thermal isolation strength of the non-target area; the fluid flow rate in the microchannel affects the heating rate through convection heat dissipation. When the flow rate is fast, the system automatically increases the heating power to compensate for heat loss, and when the flow rate is slow, the power is reduced to avoid overheating. Temperature anomaly identification relies on infrared thermal imagers to capture images and convert them into grayscale images. The mapping relationship between pixel values ​​and temperatures is used to mark target areas that exceed the preset threshold. The temperature change rate set is then predicted by combining historical temperature control data with the heat conduction model and the rate ratio of adjacent time periods is calculated. The temperature control effect is judged by comparing it with the preset threshold. If the standard is not met, the parameter adjustment amount (such as heating power and temperature control duration) is automatically calculated and the adjustment instruction is output.

[0079] By tailoring the shapes of copper foil and aerogel plates to suit different microchannel layouts, independent temperature control in multiple areas can be achieved (temperature difference between adjacent areas ≥5°C), and the purely physical heat transfer method avoids electromagnetic interference.

[0080] The temperature control parameters and heat conduction influencing factors are processed and analyzed to determine whether the temperature control of the target area meets the preset requirements and output the temperature control adjustment instructions, which specifically includes the following steps:

[0081] Predicting the temperature change trend of the target area based on the temperature control parameters and the heat conduction influencing factors to obtain a temperature change rate set, and calculating the ratio of the temperature change rates of adjacent time periods in the temperature change rate set to obtain a first temperature change rate ratio and a second temperature change rate ratio;

[0082] The change ratio value between the first temperature change rate ratio and the second temperature change rate ratio is analyzed to determine whether the temperature control of the target area meets the preset requirements and output a temperature control adjustment instruction.

[0083] This application determines whether the target area's temperature control meets preset requirements and outputs adjustment instructions. The principle behind predicting temperature changes is based on temperature control parameters (such as heating power, cooling rate, and temperature control duration) and heat conduction influencing factors (including the linear distance between the target area and the heat transfer area, the thermal conductivity distribution of the composite layer between the two, and the flow rate of the fluid in the microchannel near the target area). Relying on a heat conduction model, the system uses these parameters and factors as input to simulate the heat transfer process within the chip and predict the temperature change trend of the target area. This generates a set of temperature change rates for different time periods (such as the current control period and adjacent time periods), also known as the temperature change rate set.

[0084] To accurately determine the stability and trend of the temperature control process, the ratio of the temperature change rates in adjacent time periods within the temperature change rate set is calculated. For example, the first temperature change rate ratio is calculated by comparing the current predicted temperature change rate with the predicted rate for the previous time period; the second temperature change rate ratio is calculated by comparing the rates for the previous time period with those for the next time period. These two ratios reflect the relative changes in the temperature change rate and help identify whether the temperature is stabilizing or experiencing abnormal fluctuations.

[0085] Finally, the change ratio values ​​of the first temperature change rate ratio and the second temperature change rate ratio are analyzed. A temperature change rate change ratio threshold is preset, and the calculated change ratio value is compared with it. If the change ratio value is less than or equal to the threshold, it means that the temperature change rate fluctuation of the target area is within a reasonable range, and the temperature control effect meets the preset requirements; if it is greater than the threshold, it means that the fluctuation of the temperature change rate exceeds the expected temperature control standard. At this time, the system reversely calculates the adjustment amount of the temperature control parameters (such as the amplitude of the heating power adjustment, the change in the cooling rate, etc.) based on the difference between the change ratio value and the threshold, combined with the heat conduction model and historical data, and generates and outputs the temperature control adjustment instruction, so that the temperature control process of the target area is corrected in the direction that meets the preset requirements, thereby realizing accurate and dynamic regulation of the temperature of the target area of ​​the microfluidic chip.

[0086] The substrate is a silicon wafer or a glass wafer;

[0087] The microfluidic channel structure is formed on the substrate by photolithography and etching processes, and the microfluidic channel structure includes an inlet, an outlet, and a flow channel connected between the inlet and the outlet;

[0088] The thermal conductive-insulating composite layer is formed by magnetron sputtering or chemical vapor deposition process.

[0089] This application uses silicon wafers or glass wafers as substrates, and takes advantage of their good physical and chemical stability to provide reliable support for subsequent structures. The microfluidic structure is precisely constructed on the substrate through photolithography and etching processes. The inlet is responsible for introducing the fluid to be treated, and the outlet is used to discharge the treated fluid. The flow channel between the two is the channel for the fluid to react, transmit and other operations. With the help of the high-precision characteristics of photolithography and etching, flow channels of specific sizes, shapes and layouts can be prepared on demand to meet different experimental needs. A heat-conducting-insulating composite layer is formed by magnetron sputtering or chemical vapor deposition. Magnetron sputtering allows the composite layer material to be deposited evenly and densely, and chemical vapor deposition can achieve precise composition and thickness control. The heat-conducting area of ​​the composite layer can regulate the heat of specific parts of the microchannel, and the heat-insulating area limits heat diffusion to ensure precise control of the fluid environment temperature in the microchannel, so that the entire microfluidic chip can stably and efficiently carry out microscale fluid operations such as biochemical reactions and material separation.

[0090] The temperature distribution image information of the microfluidic chip is collected, the image information is gray-processed to obtain a gray-scale image, and the target area with abnormal temperature in the microfluidic structure is identified based on the gray-scale image. Specifically, the following steps are included:

[0091] Use infrared thermal imager to collect temperature distribution image information of microfluidic chip;

[0092] Performing preliminary grayscale processing on the temperature distribution image information to obtain a first grayscale image;

[0093] Performing secondary grayscale processing on the first grayscale image to enhance the contrast between the temperature abnormality area and the normal area to obtain a second grayscale image;

[0094] Mark the area in the second grayscale image where the temperature is higher than a preset temperature threshold as the target area.

[0095] This application uses an infrared thermal imager to scan a microfluidic chip. Based on infrared thermal imaging technology, infrared radiation signals generated by temperature differences across various chip components are captured and converted into temperature distribution image information, which forms the basis for obtaining temperature visualization data. The collected temperature distribution image is then subjected to preliminary grayscale processing, simplifying the rich color information into grayscale values. Temperature differences are converted into grayscale differences to generate a first grayscale image, allowing the temperature distribution to initially present a layered image. To more clearly distinguish between abnormal and normal temperature areas, the first grayscale image undergoes secondary grayscale processing to adjust the grayscale value range and enhance contrast. This makes abnormal temperature areas (such as overheated areas) more prominent in the second grayscale image, creating a clear visual difference from normal areas. Finally, a preset temperature threshold is set, and areas in the second grayscale image with grayscale values ​​corresponding to temperatures above the threshold are marked as target areas. This allows precise identification of temperature abnormalities within the microfluidic structure, providing accurate regional positioning for subsequent temperature control adjustments and other operations.

[0096] Correlation analysis is performed between the target area and the heat transfer area based on the grayscale image to determine the temperature control parameters of the heat transfer area corresponding to the target area, specifically including the following steps:

[0097] If there is a heat conduction connection area between the target area and the heat conduction area in the grayscale image, the target area and the corresponding heat conduction area are combined to form a temperature control associated area;

[0098] Collect the temperature gradients of the target area and the heat conduction area in the temperature control correlation area and output the temperature gradient to be judged;

[0099] A temperature gradient threshold is preset, and historical temperature control data is extracted when the temperature gradient to be determined is greater than or equal to the preset temperature gradient threshold;

[0100] Extracting historical temperature control case data similar to the temperature control-related area from the historical temperature control data, and determining the temperature control parameters based on the historical temperature control case data;

[0101] Historical temperature control case data similar to the temperature control-related area is extracted from the historical temperature control data, and the temperature control parameters are determined based on the historical temperature control case data.

[0102] This application uses spatial correlation logic in grayscale images to identify the thermal connection characteristics between the target area and the heat transfer area. When a thermal connection area with a continuous grayscale gradient (i.e., a temperature transition zone formed by heat transfer between the two areas) exists between the target area (temperature anomaly area) and the heat transfer area (the chip's pre-set heat control area) in the grayscale image, a thermal interaction is determined between the two areas and the areas are combined into a temperature control-related area.

[0103] Secondly, we focus on collecting thermal characteristics of the temperature-controlled area. High-precision temperature sensors are used to measure the temperature gradient (i.e., the rate of temperature change per unit distance) between the target area and the heat transfer area, outputting the temperature gradient to be determined. The magnitude of the temperature gradient directly reflects the driving force behind heat transfer between the two areas. A larger gradient indicates a more urgent need for heat control (e.g., if the target area is overheated, the temperature difference with the heat transfer area is significant, and the heat flow is strong).

[0104] Then, a temperature gradient threshold is set as the condition for triggering the call of historical data. When the temperature gradient to be judged is ≥ the preset threshold, it means that the current heat conduction state exceeds the basic control range, and the parameters need to be optimized with the help of historical experience. At this time, the system triggers the historical temperature control database to search and screen cases that are similar to the current temperature control-related area. The matching dimensions cover key features such as regional geometry (such as circular, strip-shaped), thermal conductivity distribution (thermal conductivity / insulation characteristics of the composite layer), and initial temperature difference to ensure that the historical cases are highly consistent with the heat conduction mechanism of the current scenario.

[0105] Finally, adapted temperature control parameters are extracted based on data mining of similar historical temperature control cases. Historical cases contain proven effective temperature control strategies (such as combinations of heating power, cooling rate, and temperature control duration) for similar areas under different heat conduction scenarios. The system uses algorithms to analyze correlation patterns in case data (such as the corresponding curve between temperature gradient and heating power) and derive the required temperature control parameters for the currently associated temperature control area. This achieves precise parameter setting through a combination of "historical experience transfer + dynamic scenario adaptation," ensuring that temperature control strategies are both based on established practices and tailored to the actual heat conduction requirements of current microfluidic chips.

[0106] Detecting factors affecting heat conduction between the target area and the heat conduction area specifically includes the following steps:

[0107] Detect the straight-line distance between the target area and the heat transfer area and output distance data information;

[0108] After detecting the thermal conductivity distribution of the thermal conductive-insulating composite layer between the target area and the thermal conductive area, the thermal conductivity data information is output;

[0109] Detecting the flow velocity of the fluid in the microchannel near the target area and outputting flow velocity data information;

[0110] Among them, the distance data information, thermal conductivity data information and flow rate data information are combined to become the factors affecting heat conduction.

[0111] This application collects key information that affects heat conduction between the target area and the heat conduction area from multiple dimensions. First, the straight-line distance between the target area and the heat conduction area is accurately obtained by distance measurement and the distance data is output, because the distance will directly affect the path length of heat conduction and the degree of heat loss. Then, the thermal conductivity distribution of the heat conduction-insulation composite layer between the two areas is detected and the data is output. The thermal conductivity characteristics of the composite layer determine the difficulty of heat transfer. The difference in thermal conductivity in different parts will change the efficiency and direction of heat conduction. At the same time, the flow rate of the fluid in the microchannel near the target area is detected and the flow rate data is output. The fluid flow rate will affect heat exchange through convection. Different flow rates have different effects on taking away or transferring heat. Finally, the three types of data information, distance, thermal conductivity, and flow rate, are integrated. They together constitute the factors affecting heat conduction, comprehensively reflecting the comprehensive effects of geometric distance, material thermal conductivity, fluid dynamic interaction, etc. in the heat conduction process between the two areas, and providing basic data support for subsequent analysis of heat conduction laws and precise temperature control.

[0112] The temperature change trend of the target area is predicted based on the temperature control parameters and the heat conduction influencing factors to obtain a temperature change rate set, and the ratio of the temperature change rates of adjacent time periods in the temperature change rate set is calculated to obtain a first temperature change rate ratio and a second temperature change rate ratio, specifically including the following steps:

[0113] After inputting the temperature control parameters and heat conduction influencing factors into the heat conduction model prediction, the first predicted temperature change rate of the target area is obtained;

[0114] After extracting temperature control data of a previous period and a subsequent period adjacent to the current temperature control period from the historical temperature control data, a second predicted temperature change rate and a third predicted temperature change rate of the target area are respectively predicted;

[0115] The first predicted temperature change rate, the second predicted temperature change rate, and the third predicted temperature change rate are combined into a temperature change rate set;

[0116] Calculating a ratio of the first predicted temperature change rate to the second predicted temperature change rate to obtain a first temperature change rate ratio;

[0117] A ratio of the second predicted temperature change rate to the third predicted temperature change rate is calculated to obtain a second temperature change rate ratio.

[0118] This application uses the currently set temperature control parameters (such as heating power, cooling rate, and temperature control duration) and the detected heat conduction influencing factors (including the straight-line distance between the target area and the heat conduction area, the thermal conductivity distribution of the composite layer, the flow rate of the microchannel fluid, etc.) as input conditions and substitutes them into a pre-built heat conduction model (such as a coupled model based on Fourier's law and the convection heat transfer equation). The model uses numerical simulation to calculate the heat transfer process within the chip and predicts the first predicted temperature change rate of the target area under the current temperature control strategy (i.e., the theoretical temperature change per unit time, reflecting the temperature response trend of real-time control).

[0119] Temperature control data from the historical temperature control database is selected for the time periods preceding and following the current temperature control period. The data from the preceding period represents the initial thermal state before control (e.g., the natural heat transfer rate when temperature control is not activated), while the data from the following period represents the continued trend after control (e.g., the temperature change trend after the temperature control strategy is continuously in effect). Based on this data from these two periods and combined with the current thermal characteristics of the target area (e.g., material heat capacity, initial temperature, etc.), a second predicted temperature change rate (temperature change trend from the preceding period to the present) and a third predicted temperature change rate (temperature change trend from the current period to the following period) are predicted.

[0120] The first, second, and third predicted temperature change rates are combined into a temperature change rate set, which covers temperature change information across three dimensions: real-time control response, historical trend, and future trend prediction. The ratio of the first to second rates (the first temperature change rate ratio) is then calculated to compare the difference between the real-time control strategy and the initial historical trend. A ratio greater than 1 indicates that the current temperature control strategy has significantly altered the temperature change rate; a ratio close to 1 indicates that the control effect has not yet been clearly demonstrated. The ratio of the second to third rates (the second temperature change rate ratio) is then calculated to analyze the correlation between the historical trend and the future trend prediction, determining whether the temperature change is stabilizing (a ratio close to 1 indicates a more stable trend) or continuing to fluctuate (a ratio deviating from 1 indicates that the fluctuation is likely to continue).

[0121] By associating the real-time predictions of the heat conduction model with the time periods of historical data, this method constructs rate sets and rate ratios. The first rate ratio reflects the intervention effect of current regulation on historical trends, helping to determine whether the temperature control parameters are reasonable; the second rate ratio reveals the continuity of temperature changes, assisting in early adjustment strategies (such as reducing heating power in advance if continued temperature rise is predicted); by comparing historical data with real-time predictions, the heat conduction model parameters can be reversely optimized to improve the accuracy of subsequent predictions.

[0122] Analyzing the change ratio value between the first temperature change rate ratio and the second temperature change rate ratio to determine whether the temperature control of the target area meets the preset requirements and outputting a temperature control adjustment instruction specifically includes the following steps:

[0123] Calculating a change ratio between the first temperature change rate ratio and the second temperature change rate ratio to obtain a change ratio value;

[0124] A temperature change rate ratio threshold is preset. If the change ratio value is less than or equal to the preset temperature change rate ratio threshold, it is determined that the temperature control of the target area meets the preset requirements;

[0125] If the change ratio value is greater than the preset temperature change rate change ratio threshold, it is determined that the temperature control of the target area does not meet the preset requirements;

[0126] If it is determined that the preset requirement is not met, the adjustment amount of the temperature control parameter is calculated based on the difference between the change ratio value and the preset temperature change rate change ratio threshold, and then a temperature control adjustment instruction is output.

[0127] This application calculates the change ratio values ​​of the first temperature change rate ratio (the rate difference between the real-time control strategy and the historical initial trend) and the second temperature change rate ratio (the rate correlation between the historical continuation trend and the future trend prediction) to further amplify the difference characteristics of the temperature change trend - if the first rate ratio reflects the degree of change of the current control to history, and the second rate ratio reflects the continuation stability of the trend, then the change ratio value can be understood as a comprehensive comparison indicator of the control intervention effect and the trend stability, which can more sensitively capture the dynamic deviation of the temperature control process.

[0128] A preset temperature change rate ratio threshold is set. When the ratio is ≤ the threshold, it indicates that the current temperature control strategy's intervention effect on the temperature change trend is in a "coordinated stable state" with the continuity of the trend itself. This means that the control has effectively reduced abnormal temperatures (e.g., reduced the overheating rate) without causing new fluctuations (e.g., a sharp change in the rate ratio). Therefore, it is determined that "temperature control in the target area meets the preset requirements." Conversely, if the ratio is greater than the threshold, it indicates an imbalance between the control effect and the trend stability. This may be due to the temperature control parameters being too strong (e.g., excessive heating power causing a sudden change in the temperature change rate) or too weak (e.g., insufficient cooling rate unable to suppress temperature rise), disrupting the correlation between the temperature change trend and determining that the temperature control fails to meet the preset requirements.

[0129] When it is determined that the preset requirements have not been met, the difference between the change ratio value and the preset threshold is first calculated. This difference quantifies the degree of actual control deviation. Then, based on a pre-established deviation-parameter mapping model (trained through a large amount of historical data to correlate the change ratio difference with the temperature control parameter adjustment amount), the temperature control parameters that need to be adjusted (such as the increase or decrease in heating power, cooling rate correction value, etc.) are derived. For example, if the difference is +0.3 (the change ratio value exceeds the threshold of 0.3), the model may output an instruction to reduce the heating power by 5%. By accurately correcting the parameters, the change ratio value of the subsequent temperature control process is allowed to return to the threshold range to achieve closed-loop control.

[0130] Example 2

[0131] The following technical features are added based on Example 1:

[0132] The temperature control system of microfluidic chip based on thermal conductive and thermal insulating composite layer includes:

[0133] Composition module: The heat-conducting-insulating composite layer microfluidic chip includes a substrate, a microfluidic channel structure arranged on the substrate, and a heat-conducting-insulating composite layer covering the microfluidic channel structure. The heat-conducting-insulating composite layer includes a heat-conducting area and a heat-insulating area. The heat-conducting area corresponds to the heating or cooling part of the microfluidic channel structure, and the heat-insulating area is used to limit heat diffusion.

[0134] Acquisition and recognition module: collects temperature distribution image information of the microfluidic chip, performs grayscale processing on the image information to obtain a grayscale image, and identifies the target area with abnormal temperature in the microfluidic structure based on the grayscale image;

[0135] Analysis module: performs correlation analysis between the target area and the heat transfer area based on the grayscale image to determine the temperature control parameters of the heat transfer area corresponding to the target area; the temperature control parameters include heating power, cooling rate and temperature control time;

[0136] Detection module: detects factors affecting heat conduction between the target area and the heat conduction area;

[0137] Judgment module: processes and analyzes the temperature control parameters and heat conduction influencing factors to determine whether the temperature control of the target area meets the preset requirements and outputs temperature control adjustment instructions.

[0138] The electronic device includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor. When the processor executes the program, a temperature control method for a microfluidic chip based on a heat-conducting-insulating composite layer is implemented.

[0139] like Figure 4 As shown, the present invention relates to a temperature control system of a microfluidic chip based on a thermal conductive-insulating composite layer, which has demonstrated remarkable precision in local temperature control capabilities and efficient experimental compatibility in biomedical research. The specific effects are as follows: We use a temperature control system of a microfluidic chip based on a thermal conductive-insulating composite layer to perform local temperature changes on the cell bodies and axons of peripheral sensory neurons of mice cultured in a microfluidic system, and use antibodies to label the endogenous G3BP1 protein of mouse neurons to indicate the formation of stress granules (SG). The formation of SG is an important stress mechanism for cells to resist adverse environmental stimuli (such as oxidative stress, nutrient deficiency, heat shock, viral infection, etc.). In this experiment, we subjected neurons to adverse environmental stimulation (local 42°C heat stimulation) Figure 4AD). The results showed that when we gave the axon side of the neurons a constant heat treatment at 42°C for 20 min, we could observe the formation of obvious SGs in the axon, while no SGs were formed in the cell bodies of the cells in the culture chamber on the other side.

[0140] Through the external modular design of the thermal conductive-insulating composite layer, this system achieves high-precision, low-cost, and low-damage local temperature control of the microfluidic chip, significantly improving the spatial resolution and data reliability of cellular stress mechanism research. At the same time, it provides a universal technology platform for cutting-edge fields such as drug-targeted hyperthermia and neurodegenerative disease model construction.

[0141] like Figure 3 As shown, the electronic device may include: a processor 610, a communication interface 620, a memory 630, and a communication bus 640, wherein the processor 610, the communication interface 620, and the memory 630 communicate with each other via the communication bus 640. The processor 610 may call the logic instructions in the memory 630 to execute the temperature control method of the thermal conductive-insulating composite layer microfluidic chip.

[0142] Furthermore, the logic instructions in the aforementioned memory 630 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0143] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the temperature control method of the thermal conductive-insulating composite layer microfluidic chip.

[0144] In another aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, which is implemented when the computer program is executed by a processor to perform a temperature control method for a heat-conducting-insulating composite layer microfluidic chip.

[0145] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0146] Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented using software plus a necessary general-purpose hardware platform, or of course, hardware. Based on this understanding, the essence of the above technical solution, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, or an optical disk, and includes a number of instructions for causing a computer device (such as a personal computer, server, or network device) to execute the methods described in each embodiment or certain portions of the embodiments.

[0147] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention 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 make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A temperature control method for a microfluidic chip based on a heat-conducting-insulating composite layer, characterized by: The method comprises the following steps, The heat-conducting-insulating composite layer microfluidic chip includes a substrate, a microfluidic channel structure arranged on the substrate, and a heat-conducting-insulating composite layer covering the microfluidic channel structure. The heat-conducting-insulating composite layer includes a heat-conducting area and a heat-insulating area. The heat-conducting area corresponds to the heating or cooling part of the microfluidic channel structure, and the heat-insulating area is used to limit heat diffusion. Collect temperature distribution image information of the microfluidic chip, perform grayscale processing on the image information to obtain a grayscale image, and identify the target area with abnormal temperature in the microfluidic structure based on the grayscale image; Performing correlation analysis between the target area and the heat transfer area based on the grayscale image to determine the temperature control parameters of the heat transfer area corresponding to the target area; wherein the temperature control parameters include heating power, cooling rate and temperature control time; Detect factors affecting heat conduction between the target area and the heat conduction area; The temperature control parameters and heat conduction influencing factors are processed and analyzed to determine whether the temperature control of the target area meets the preset requirements and output temperature control adjustment instructions.

2. The temperature control method of a microfluidic chip based on a heat-conducting-insulating composite layer according to claim 1, characterized in that: The temperature control parameters and heat conduction influencing factors are processed and analyzed to determine whether the temperature control of the target area meets the preset requirements and output the temperature control adjustment instructions, which specifically includes the following steps: Predicting the temperature change trend of the target area based on the temperature control parameters and the heat conduction influencing factors to obtain a temperature change rate set, and calculating the ratio of the temperature change rates of adjacent time periods in the temperature change rate set to obtain a first temperature change rate ratio and a second temperature change rate ratio; The change ratio value between the first temperature change rate ratio and the second temperature change rate ratio is analyzed to determine whether the temperature control of the target area meets the preset requirements and output a temperature control adjustment instruction.

3. The temperature control method of a microfluidic chip based on a heat-conducting-insulating composite layer according to claim 1, characterized in that: The substrate is a silicon wafer or a glass wafer; The microfluidic channel structure is formed on the substrate by photolithography and etching processes, and the microfluidic channel structure includes an inlet, an outlet, and a flow channel connected between the inlet and the outlet; The heat-conducting and heat-insulating composite layer is formed by magnetron sputtering or chemical vapor deposition.

4. The temperature control system and method of a microfluidic chip based on a heat-conducting and heat-insulating composite layer according to claim 1, characterized in that: The temperature distribution image information of the microfluidic chip is collected, the image information is gray-processed to obtain a gray-scale image, and the target area with abnormal temperature in the microfluidic structure is identified based on the gray-scale image. Specifically, the following steps are included: Use infrared thermal imager to collect temperature distribution image information of microfluidic chip; Performing preliminary grayscale processing on the temperature distribution image information to obtain a first grayscale image; Performing secondary grayscale processing on the first grayscale image to enhance the contrast between the temperature abnormality area and the normal area to obtain a second grayscale image; Mark the area in the second grayscale image where the temperature is higher than a preset temperature threshold as the target area.

5. The temperature control method of a microfluidic chip based on a heat-conducting-insulating composite layer according to claim 1, characterized in that: According to the grayscale image, the target area and the heat conduction area are correlated and analyzed to determine the temperature control parameters of the heat conduction area corresponding to the target area, specifically including the following steps: If there is a heat conduction connection area between the target area and the heat conduction area in the grayscale image, the target area and the corresponding heat conduction area are combined to form a temperature control associated area; Collect the temperature gradients of the target area and the heat conduction area in the temperature control correlation area and output the temperature gradient to be judged; A temperature gradient threshold is preset, and historical temperature control data is extracted when the temperature gradient to be determined is greater than or equal to the preset temperature gradient threshold; Extracting historical temperature control case data similar to the temperature control-related area from the historical temperature control data, and determining the temperature control parameters based on the historical temperature control case data; Historical temperature control case data similar to the temperature control associated area is extracted from the historical temperature control data, and the temperature control parameter is determined based on the historical temperature control case data.

6. The temperature control method of a microfluidic chip based on a heat-conducting-insulating composite layer according to claim 1, characterized in that: Detect the factors affecting heat conduction between the target area and the heat conduction area, specifically The following steps are included: Detect the straight-line distance between the target area and the heat transfer area and output distance data information; After detecting the thermal conductivity distribution of the thermal conductive-insulating composite layer between the target area and the thermal conductive area, the thermal conductivity data information is output; The flow velocity of the fluid in the microchannel near the target area is detected and the flow velocity data information is output.

7. The temperature control method of a microfluidic chip based on a heat-conducting-insulating composite layer according to claim 6, characterized in that: The distance data information, thermal conductivity data information and flow rate data information are combined to form heat conduction influencing factors; The temperature change trend of the target area is predicted based on the temperature control parameters and the heat conduction influencing factors to obtain a temperature change rate set, and the ratio of the temperature change rates of adjacent time periods in the temperature change rate set is calculated to obtain a first temperature change rate ratio and a second temperature change rate ratio, specifically including the following steps: After inputting the temperature control parameters and heat conduction influencing factors into the heat conduction model prediction, the first predicted temperature change rate of the target area is obtained; After extracting temperature control data of a previous period and a subsequent period adjacent to the current temperature control period from the historical temperature control data, a second predicted temperature change rate and a third predicted temperature change rate of the target area are predicted respectively.

8. The temperature control method of a microfluidic chip based on a heat-conducting-insulating composite layer according to claim 7, characterized in that: The first predicted temperature change rate, the second predicted temperature change rate and the third predicted temperature change rate are combined into a temperature change rate set; Calculating a ratio of the first predicted temperature change rate to the second predicted temperature change rate to obtain a first temperature change rate ratio; A ratio of the second predicted temperature change rate to the third predicted temperature change rate is calculated to obtain a second temperature change rate ratio.

9. The temperature control method of a microfluidic chip based on a heat-conducting-insulating composite layer according to claim 8, characterized in that: Analyzing the change ratio between the first temperature change rate ratio and the second temperature change rate ratio to determine whether the temperature control of the target area meets the preset requirements and outputting a temperature control adjustment instruction specifically includes the following steps: Calculating a change ratio between the first temperature change rate ratio and the second temperature change rate ratio to obtain a change ratio value; A preset temperature change rate ratio threshold is set, and if the change ratio value is less than or equal to the preset temperature change rate ratio threshold, it is determined that the temperature control of the target area meets the preset requirements; If the change ratio value is greater than the preset temperature change rate change ratio threshold, it is determined that the temperature control of the target area does not meet the preset requirements; If it is determined that the preset requirement is not met, the adjustment amount of the temperature control parameter is calculated based on the difference between the change ratio value and the preset temperature change rate change ratio threshold, and then a temperature control adjustment instruction is output.

10. A temperature control system for a microfluidic chip based on a heat-conducting and heat-insulating composite layer, applied to a temperature control method for a microfluidic chip based on a heat-conducting and heat-insulating composite layer according to any one of claims 1 to 9, characterized in that: include, Composition module: The heat-conducting-insulating composite layer microfluidic chip includes a substrate, a microfluidic channel structure arranged on the substrate, and a heat-conducting-insulating composite layer covering the microfluidic channel structure. The heat-conducting-insulating composite layer includes a heat-conducting area and a heat-insulating area. The heat-conducting area corresponds to the heating or cooling part of the microfluidic channel structure, and the heat-insulating area is used to limit heat diffusion. Acquisition and recognition module: collects temperature distribution image information of the microfluidic chip, performs grayscale processing on the image information to obtain a grayscale image, and identifies the target area with abnormal temperature in the microfluidic structure based on the grayscale image; Analysis module: performs correlation analysis between the target area and the heat transfer area based on the grayscale image to determine the temperature control parameters of the heat transfer area corresponding to the target area; wherein the temperature control parameters include heating power, cooling rate and temperature control time; Detection module: detects factors affecting heat conduction between the target area and the heat conduction area; Judgment module: processes and analyzes the temperature control parameters and heat conduction influencing factors to determine whether the temperature control of the target area meets the preset requirements and outputs temperature control adjustment instructions.

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