System and method for measuring thermophysical property of soft material film

Abstract

The invention discloses a system and a method for measuring the thermophysical property of a soft material film. The system comprises a signal generator, a pump light path, a detection light path, a photoelectric detector, a signal processing module, a sample platform, a difference measurement module and a thermal parameter inversion unit. The system can be used for independently measuring the thermal conductivity, the specific heat capacity and the interface thermal resistance of liquid, gel and soft solid thin film materials at the same time on the premise that prior parameters are not needed. In combination with periodic heating of a square wave modulation heat source and a difference measurement strategy, high-precision measurement of micro-nano-scale thermophysical properties is realized, and the method is particularly suitable for various application scenes such as thermal interface materials (TIMs) and phase change energy storage materials.

Description

Technical Field

[0001] The present invention belongs to the technical field of thermophysical property parameter measurement, and specifically relates to a measurement system and method for measuring the thermal conductivity, specific heat capacity and interfacial thermal resistance of soft material films (such as liquid, gel or low modulus materials). The system and method are particularly suitable for characterizing the thermophysical properties of thermal interface materials (TIMs) at complex interfaces and under actual service conditions. Background Art

[0002] As the power density of electronic devices continues to increase, device packaging structures are becoming increasingly miniaturized and highly integrated, placing higher performance demands on thermal management materials. Thermal interface materials (TIMs) are widely used between chips and heat sinks to fill micro-gaps, reduce interfacial thermal resistance, and thus improve overall heat transfer efficiency. Common forms of TIMs include liquids, gels, phase change materials, and flexible polymer composites.

[0003] However, key thermophysical properties of TIMs, such as thermal conductivity, specific heat capacity, and interfacial thermal resistance, are affected by multiple factors in actual application environments, including temperature, mechanical pressure, and interfacial contact conditions, exhibiting significant nonlinear and time-varying characteristics. Therefore, it is urgent to develop methods that can measure these parameters with high temporal and spatial resolution under actual service conditions to support thermal design and material development.

[0004] Existing thermal property testing methods are mainly divided into steady-state methods and transient methods, each of which has the following limitations:

[0005] Steady-state methods (such as ASTM D5470) are typically used to measure the equivalent thermal conductivity of a sample under steady-state heat flow, but they struggle to distinguish between interfacial thermal resistance and the material's intrinsic thermal conductivity. Furthermore, steady-state methods are only suitable for large samples and cannot measure thermal properties in small or localized areas. They also have long measurement cycles and are highly sensitive to external environmental factors (such as pressure, surface roughness, and heat loss).

[0006] Among the transient methods used to measure the thermal properties of TIMs, there are laser flash method (FLA), transient hot wire method, time domain thermoreflectance (TDTR), frequency domain thermoreflectance (FDTR), and third harmonic method (3ω method). Among them, LFA has poor adaptability to liquid and gel materials, and has high requirements on sample size, making it difficult to characterize local thermal properties. Although the transient hot wire method can measure liquid and gel materials, it requires a large sample volume, and the measurement results are easily affected by the thermal resistance of the interface between the hot wire and the material. TDTR uses femtosecond laser excitation and detection. Although the spatial resolution is high, the thermal penetration depth is limited, making it difficult to accurately measure the interfacial thermal resistance of thicker liquid films or low thermal conductivity soft materials. For example, studies such as CN112268927A have used the TDTR method to extract the thermal conductivity of soft materials through sinusoidal wave modulation and frequency domain fitting. However, this approach still has the following shortcomings: (1) It can only measure thermal conductivity and cannot independently obtain specific heat capacity and interfacial thermal resistance; (2) It is not suitable for liquid or gel-like fluid materials, especially when the interfacial contact is unstable under pressure; (3) It is highly dependent on the excitation frequency, has a low signal-to-noise ratio, and requires high-power laser support. FDTR can adjust the thermal excitation frequency to control the thermal penetration depth and has good parameter decoupling capabilities, but it is not sensitive enough to measure the interfacial thermal resistance of low thermal conductivity materials. The 3ω method is suitable for measuring the thermal conductivity of solid films, but the experimental setup is complex and difficult to extend to soft or fluid materials. In addition, LFA, TDTR, and the 3ω method all require the specific heat capacity information of the sample to be known in advance, and cannot achieve independent inversion of thermal conductivity and specific heat capacity, which reduces the versatility and adaptability of the method.

[0007] In summary, existing technologies are still insufficient in the following aspects: (1) the ability to independently measure multiple parameters of soft matter and liquid interface materials; (2) the accuracy of thermal response extraction at the micro-nanoscale; and (3) the sensitivity and accuracy of interfacial thermal resistance measurement. Therefore, it is urgent to develop a high-sensitivity thermophysical property measurement system that can adapt to complex material morphologies and has a differential and multi-frequency combined strategy to overcome the measurement bottleneck of traditional methods under low thermal conductivity and dynamic interface conditions. Summary of the Invention

[0008] This invention aims to address the current technical bottlenecks in measuring the thermophysical properties of liquid, gel, and soft-solid thin-film materials. It provides a system and method for measuring the thermophysical properties of soft-matter thin films, capable of simultaneously measuring thermal conductivity, volumetric specific heat capacity, and solid-liquid or solid-solid interface thermal resistance. This method, combining periodic square-wave thermal excitation with a differential measurement strategy, enables high-precision characterization of micro- and nanoscale thermophysical properties without requiring prior specific heat capacity information. This method is particularly suitable for characterizing the service conditions of key thermal management materials, such as thermal interface materials and phase-change energy storage materials, providing reliable experimental support for the design and optimization of efficient thermal management systems.

[0009] Compared with existing methods such as CN112268927A, the present invention introduces periodic square wave thermal excitation and normalized difference strategy. Through the inversion algorithm dominated by multi-frequency signal acquisition and sensitivity analysis, it can simultaneously invert the thermal conductivity, volume specific heat capacity and solid-liquid / solid-solid interface thermal resistance of soft matter without relying on the prior specific heat capacity information of the sample. It is particularly suitable for measuring the interfacial heat transfer characteristics of liquid, gel and soft-solid TIMs under pressurized environment.

[0010] The differential strategy adopted in the present invention can effectively suppress system errors and enhance the independent mapping relationship between the signal and the thermal parameters to be measured, so that the system still has good measurement stability under actual working conditions such as changes in sample thickness and unstable interface contact state, providing a reliable and highly sensitive technical path for micro-nanoscale thermal physical property testing.

[0011] To achieve the above object, the present invention provides the following technical solutions:

[0012] A system for measuring thermal properties of soft material films, comprising:

[0013] A signal generator, used for outputting a square wave modulation signal and providing a synchronization reference signal;

[0014] A pump optical circuit, comprising a pump laser, for receiving the square wave modulation signal and outputting modulated laser light, wherein the modulated laser light is focused on the sample surface via a dichroic mirror and an objective lens to achieve periodic thermal excitation;

[0015] The detection optical path includes a detection laser, a λ / 2 wave plate, a polarization beam splitter, a λ / 4 wave plate, the dichroic mirror and the objective lens arranged in sequence, and is used to coaxially focus the detection laser onto the sample surface and to separate the reflected detection light according to the polarization state;

[0016] a photoelectric detector, configured to convert the intensity of the reflected detection light into an electrical signal;

[0017] a signal processing module, comprising a periodic waveform analyzer for extracting a single-period amplitude of a thermal response signal synchronized with the reference signal;

[0018] A sample platform, including a transparent substrate and a metal film deposited on the surface thereof, serving as a temperature sensing structure;

[0019] a differential measurement module for collecting thermal response signals of the metal film when it is not covered and when it is covered with the material to be tested, and performing normalization processing and amplitude ratio calculation on the obtained signals;

[0020] The thermal parameter inversion unit is used to invert the thermal conductivity, volume specific heat capacity and interface thermal resistance of the material to be tested based on multi-frequency measurement signals and combined with a hybrid optimization algorithm.

[0021] Preferably, the square wave modulation signal output by the signal generator includes a low frequency part (f L <10kHz and high frequency part (f H >100kHz) to produce different thermal penetration depths, thereby achieving differentiated stimulation of the thermal response of each layer in a multi-layer structure.

[0022] As a preference, the differential measurement module adopts an amplitude ratio calculation strategy to reduce the influence of system parameter fluctuations on the measurement results and improve the sensitivity and accuracy of the interface thermal resistance measurement; the thermal parameter inversion unit performs sensitivity analysis and the calculation form is: The sensitivity coefficient is used to evaluate the influence of different thermal parameters on the response signal and realize parameter decoupling. The inversion process sets a unified normalized time point t0 to eliminate systematic deviations and improve the robustness of parameter decoupling. The optimization algorithm is a hybrid optimization strategy formed by combining the particle swarm optimization algorithm and the quasi-Newton method.

[0023] Preferably, the transparent substrate is ultra-white glass, optical-grade PMMA or other transparent materials with low thermal conductivity, and the metal film is aluminum, tantalum, hafnium nitride or titanium nitride, with a thickness ranging from 50 to 200 nm.

[0024] Preferably, a sample pressurizing assembly is further included, which includes a pressure plate, a bolt, a spring and a sample container with a light-through hole, and is used to apply quantitatively controllable mechanical pressure to the sample when measuring the thermal interface material to simulate the compression conditions under actual service conditions.

[0025] Preferably, a microscopic imaging module is also included for observing the position of the laser spot on the sample surface in real time and monitoring changes in the sample surface morphology.

[0026] The present invention also provides a method for measuring the thermal properties of a liquid film, comprising the following steps:

[0027] S1) Under the condition of not covering the liquid film, the reference thermal response signals at low frequency and high frequency are collected respectively, which are recorded as and

[0028] S2) After covering the liquid film, the measurement signal is collected under the same modulation frequency and laser power conditions, and is recorded as A L (t) and A H (t);

[0029] S3) normalizing the above signal to obtain a normalized thermal response signal and The normalization formula is:

[0030]

[0031] Where t is the normalized time variable, t1 = -0.02, t2 = 0.48;

[0032] S4) The high frequency measurement signal A H (t) and reference signal Perform benchmarking and calculate the ratio to obtain the amplitude ratio signal R(t), which is calculated as follows:

[0033]

[0034] S5) constructing a simulation response signal based on a multilayer heat transfer model, and fitting it with the normalized thermal response signal obtained in step S3 and the amplitude ratio signal obtained in step S4, respectively. By jointly minimizing the difference between the two types of signals and the corresponding simulation signals, the thermal conductivity k of the liquid film is inverted. f , volume specific heat capacity C f And interface thermal resistance R int .

[0035] The present invention also provides a method for measuring thermal properties of thermal interface materials (TIMs), comprising the following steps:

[0036] T1) without placing a thermal interface material, collecting reference thermal response signals at low and high frequencies, respectively, and inverting the thermal conductivity and volume specific heat capacity of the transparent substrate based on the signals;

[0037] T2) placing the thermal interface material between the metal film and the pressure member, applying a predetermined mechanical pressure, and collecting a thermal response signal comprising the thermal interface material under the same modulation frequency and laser power conditions;

[0038] T3) normalizing the reference signal and the measurement signal comprising the thermal interface material to obtain a normalized thermal response signal; and calculating an amplitude ratio signal based on the result at high frequency;

[0039] T4) constructing a heat conduction model, generating a corresponding simulation signal, and fitting it with the normalized thermal response signal and the amplitude ratio signal respectively; by minimizing the difference between the simulation signal and the experimental signal, jointly inverting to obtain the thermal conductivity k of the thermal interface material TIM , volume specific heat capacity C TIM And interface thermal resistance R int .

[0040] Preferably, the time points t1 and t2 used for normalization processing are set based on the stable section of the reference signal to improve the sensitivity of the normalized signal to the change of the interface thermal resistance and reduce the influence of the system error on the inversion result.

[0041] Preferably, the measurement can be performed within a temperature range of -50°C to 500°C, or in a vacuum environment or high pressure conditions to adapt to various extreme service environments.

[0042] The present invention has the following technical advantages over the existing technology:

[0043] 1. Multi-parameter simultaneous measurement. By using a differential strategy and joint fitting of multi-frequency signals, thermal conductivity, volume specific heat capacity, and interfacial thermal resistance can be simultaneously extracted without prior specific heat capacity information.

[0044] 2. Wide range of applicable materials. This method is not only applicable to liquid films, but also suitable for measuring thermal conductive gels, phase change energy storage materials, and soft solid-state TIMs, expanding the range of materials for thermal property measurement.

[0045] 3. High-precision measurement at the micro- and nano-scale. Periodic square wave heating and multi-frequency signal acquisition are used to improve the signal-to-noise ratio, meeting the high-precision requirements of micro- and nano-scale interface and material characterization.

[0046] 3. Optimization of interfacial thermal resistance measurement. By enhancing signal differentiation with and without the material to be measured, the reliability of interfacial thermal resistance inversion is significantly improved, overcoming the insufficient sensitivity of traditional TDTR and FDTR in measuring low thermal conductivity TIMs. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] To more clearly illustrate the embodiments of the present invention and its improvements over the prior art, the following briefly describes the drawings cited in the present invention specification. Obviously, the drawings illustrate only several preferred embodiments of the present invention, and those skilled in the art can construct other forms of illustrations based on these drawings without inventive effort.

[0048] Figure 1 Schematic diagram of the structure of the soft material film thermal property measurement system of the present invention;

[0049] Figure 2 Schematic diagram of the data processing flow adopted by this system;

[0050] Figure 3 Flowchart for extracting thermophysical property parameters using a hybrid optimization algorithm coupled with particle swarm optimization and quasi-Newton method;

[0051] Figure 4 Schematic diagram of the signal processing process, thermal response signal and sensitivity analysis of peanut oil samples;

[0052] Figure 5 The thermal conductivity and specific heat capacity of various liquids are compared with literature data, and the schematic diagram of the thermal conductivity of the Al / liquid film interface is shown;

[0053] Figure 6The measurement signal and sensitivity analysis results of the thermal conductive gel sample at a pressure of 2.279 MPa;

[0054] Figure 7 Schematic diagram of the relationship between the thermal conductivity, specific heat capacity of the thermal conductive gel and the thermal conductivity of the aluminum interface as a function of pressure. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solutions and beneficial effects of the present invention more clear and easy to understand, the present invention is described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit the scope of protection thereof. Any equivalent variations or alternatives made by those of ordinary skill in the art without departing from the spirit of the present invention should be included within the scope of protection of the present invention.

[0056] Example 1:

[0057] like Figure 1 As shown, this embodiment provides a thermal property measurement system for liquid, gel and soft solid materials, including:

[0058] A signal generator is used to output a square wave modulation signal and provide a reference signal synchronized with the measurement system;

[0059] The pump optical circuit includes a pump laser, which is used to receive a square wave modulation signal and output a modulated laser. The laser is focused on the sample surface through a dichroic mirror and an objective lens to generate periodic thermal excitation.

[0060] A detection optical path, comprising a detection laser, a λ / 2 wave plate, a polarization beam splitter prism, a λ / 4 wave plate, a dichroic mirror, and an objective lens, arranged in sequence, for coaxially focusing the detection laser onto the sample surface and for separating the reflected detection light according to its polarization state;

[0061] A photodetector, used to convert the intensity of the reflected detection light into an electrical signal;

[0062] a signal processing module, comprising a periodic waveform analyzer for extracting a single-period amplitude of a thermal response signal synchronized with the reference signal;

[0063] A sample platform, including a transparent substrate and a metal film deposited on the surface thereof, serving as a temperature sensing structure;

[0064] The differential measurement module is used to collect signals when the metal film surface is not covered and covered with the material to be tested, and perform normalization and ratio calculations;

[0065] The thermal parameter inversion unit is used to invert the thermal conductivity, specific heat capacity and solid-liquid or solid-solid interface thermal resistance of the material to be tested based on multi-frequency signals and hybrid optimization algorithms.

[0066] In a preferred embodiment:

[0067] The square wave modulation frequency output by the signal generator includes low frequency f L (<10kHz) and high frequency f H (>100kHz) to achieve different heat penetration depths.

[0068] The thermal parameter inversion unit is calculated through sensitivity analysis in the form of The sensitivity coefficient is used to evaluate the sensitivity of the measurement signal to different thermal parameters, and the parameter fitting is performed in combination with particle swarm optimization and quasi-Newton method.

[0069] The transparent substrate can be made of ultra-white glass, optical-grade PMMA or other transparent materials with low thermal conductivity; the metal film material is aluminum, tantalum, hafnium nitride or titanium nitride, with a thickness ranging from 50 to 200 nm.

[0070] The system may further include a sample pressurizing assembly, which is composed of a pressing plate, a bolt, a spring, and a container with a light-through hole, and is used to apply quantitatively controllable mechanical pressure to the sample when measuring the thermal interface material.

[0071] The system may further include a microscopic imaging module for observing the laser spot position and sample surface morphology in real time to ensure accurate positioning of the measurement area.

[0072] Example 2:

[0073] An embodiment of the present invention further provides a soft material film thermophysical property measurement system, comprising: an optical system for periodic heating and detection, a sample system, and a signal processing system and a data analysis system for extracting thermophysical property parameters.

[0074] As an implementation method of an embodiment of the present invention, the optical system includes a pump optical path and a detection optical path. Among them, the pump optical path adopts a low-noise, high-quality, modulatable semiconductor laser, which can receive a square wave signal from a signal generator and directly output a modulated pump laser, which is reflected by a cold mirror and focused on the sample surface by an objective lens to form a periodic heating source. The detection optical path adopts a low-noise, high-quality, linearly polarized continuous wave laser, which adjusts the polarization state of the light through a λ / 2 wave plate, a polarization beam splitter prism and a λ / 4 wave plate in sequence, and is reflected from the sample surface to a photodetector. The thermal reflection signal is recorded by the photodetector to capture temperature change information. The optical system also includes an optical microscopy imaging system to facilitate the observation of the sample surface morphology and assist in laser focusing.

[0075] As an implementation method of an embodiment of the present invention, in order to realize the optical method of measuring the thermal properties of liquid, gel and soft solid thin film materials, a specially designed sample system is required. The sample system includes, from bottom to top: i) a transparent substrate with low thermal conductivity (such as ultra-white glass, optical grade PMMA), which provides an optical transmission path and improves the sensitivity of the signal to the thermal properties of the thin film material to be measured due to low thermal conductivity; ii) a metal sensing layer (such as 100nm aluminum film), which is used to absorb the pump laser and provide a temperature-dependent thermal reflection signal; iii) a liquid film or soft material layer to be measured: a liquid, gel or soft solid material (such as thermal conductive gel, phase change material, etc.). In differential measurement, the sample system used as differential comparison replaces the liquid film or soft material layer to be measured with air, which can reduce the influence of the parameters of the transparent substrate and the metal sensing layer on the parameters of the thermal properties to be measured.

[0076] As one implementation of an embodiment of the present invention, a signal processing system includes a periodic waveform analyzer for extracting the temperature response amplitude signal within a square wave heating cycle in phase-locked mode, thereby improving the signal-to-noise ratio and signal acquisition speed. The analyzer can be a commercially available signal analysis device with phase-locked detection capabilities. The data analysis system includes a computer-programmed analysis model that uses a hybrid algorithm combining particle swarm optimization (PSO) and quasi-Newton method (BFGS) to invert material thermal conductivity, specific heat capacity, and solid-liquid interface thermal resistance, while also analyzing signal sensitivity and error estimation.

[0077] It should be noted that while the inversion algorithm of the present invention ensures measurement accuracy, some optimization parameters (such as the PSO initial population distribution and inertia weight) are not fully disclosed due to commercial sensitivity. However, this does not affect those skilled in the art from implementing the present invention based on the disclosed content. Specific parameters can be obtained based on actual application scenarios through technical support provided by the applicant.

[0078] Figure 1The experimental setup for measuring the thermal properties of liquid films and thermal interface materials (TIMs) using the differential square pulse heat source method is shown. A schematic diagram of the principle of the optical system and related equipment is shown. The experiment uses a periodically modulated pump laser to heat the sample surface, causing the surface temperature to change periodically; at the same time, another probe laser is used to detect this temperature change. Since changes in the sample surface temperature will cause changes in the reflectivity of the sample surface to the probe laser, the periodic temperature changes of the sample surface can be obtained by measuring the periodic changes in the intensity of the probe light reflected by the sample, and the thermal physical properties of the sample to be measured can be extracted in reverse. Specifically, the pump laser is intensity modulated by a square wave signal generated by a signal generator, and a reference signal is synchronously output to a periodic waveform analyzer. After reflection from the dichroic mirror, the pump laser is focused on the sample surface by the objective lens. The detection laser passes through the λ / 2 wave plate, polarization beam splitter prism, λ / 4 wave plate, and dichroic mirror in sequence, and is focused onto the sample surface by the objective lens; the reflected detection laser returns along the original path, is separated at the polarization beam splitter prism, and then enters the photodetector, which converts the light intensity signal into an electrical signal, and the amplitude information of a single cycle is extracted by the periodic waveform analyzer.

[0079] Figure 1 The sample structure used in the experiment is also shown. A metal film (such as aluminum) with a thickness of approximately 100 nm is deposited on a transparent substrate as the sensing layer. Laser light penetrates the transparent substrate and focuses at the interface between the aluminum film and the substrate. Measurements were performed using the differential method, with two sets of experiments performed: one without liquid or TIMs placed on the aluminum film surface, and the other with liquid or TIMs placed on the aluminum film surface. The experimental conditions (including laser power, spot size, and modulation frequency) remained the same for both sets.

[0080] Figure 1 On the left is a schematic diagram of the sample support device for measuring liquids, in which a reflector is used to vertically deflect the laser light path upward. The sample is placed on a perforated support frame so that the laser can pass through the holes and focus on the interface between the transparent substrate and the metal film, thereby performing heating and temperature detection.

[0081] Figure 1 The right side shows the sample pressurization device used for measuring TIMs. The laser beam is deflected downward by a mirror, passing through a small hole in the pressurization device and focusing onto the sample surface.

[0082] Figure 1 The right side also details the structure of the sample pressurization device, including the pressure plate, bolts, coated substrate, TIMs, container, spring, and base plate. The pressure plate secures the sample, the bolts apply pressure, and the rubber gasket prevents localized sample pressure from causing breakage. The container holds the TIMs material, and the applied pressure is quantitatively controlled by measuring the spring deformation.

[0083] Figure 2 The experimental measurement and data processing schemes are given. Figure 2 As shown in (a), the original amplitude signal of the reference group (without liquid or TIMs) is recorded as A0(t), and the original amplitude signal of the test group (with liquid or TIMs) is recorded as A(t). Figure 2 As shown in (b), the two groups of original signals are normalized separately to obtain the normalized amplitude signal A 0,norm (t) and A norm (t); and further perform a division operation between the two groups of signals to obtain the amplitude ratio signal R(t) = (A(t)-A(t1)) / (A0(t)-A0(t1)). In order to achieve different thermal penetration depths to measure multiple thermophysical parameters, it is necessary to select two pump light modulation frequencies with large differences in magnitude for the experiment during the measurement process, namely a low frequency (less than 10kHz) and a high frequency (greater than 100kHz). Therefore, each experiment generates a total of 6 groups of signals that can be used for fitting analysis. Among them, the low-frequency amplitude ratio signal cannot provide additional information to help extract thermophysical parameters, so it is invalid. The valid signals are the remaining 5 groups, namely and R H (t), where the superscripts H and L represent high-frequency and low-frequency measurements, respectively. The normalized signal is primarily used to improve signal stability and specific heat capacity identification, while the amplitude ratio signal is more sensitive to interfacial thermal resistance. By jointly minimizing the fitting residuals of these two types of signals, the three parameters of thermal conductivity, specific heat capacity, and interfacial thermal resistance can be effectively decoupled, improving fitting accuracy and robustness.

[0084] Figure 3 This article presents a flow chart for using a hybrid optimization algorithm, particle swarm optimization (PSO) and the quasi-Newton method, to optimally fit experimental measurement signals and automatically extract multiple thermophysical property parameters. The overall process includes: T1: establishing a heat transfer model; T2: importing experimental signals; T3: setting the parameters to be optimized and the corresponding fitting intervals; T4: invoking the hybrid optimization algorithm for parameter optimization and fitting; and T5: outputting the parameter fitting results after optimization is complete.

[0085] The process of the hybrid optimization algorithm of particle swarm optimization and quasi-Newton method is as follows: U1: initialize the particle swarm under the set particle swarm size (parameters are randomly selected within the given initial value range); U2: update the particle swarm according to the formula; U3: calculate the corresponding objective function value under the parameter, check whether the convergence condition or the upper limit of the iteration number is met, if not, return to U2, if it has been reached, proceed to U4; U4: switch to the quasi-Newton algorithm for local optimization, and use the parameter combination corresponding to the best objective function value in the particle swarm algorithm as the initial value of the quasi-Newton algorithm to start optimization.

[0086] Different from the existing algorithm based on single least squares fitting, the algorithm described in the present invention introduces a global + local collaborative optimization strategy and automatically adjusts parameters according to the frequency response sensitivity weight of the normalized amplitude signal.

[0087] Figure 4 An example of using the present technology to measure a peanut oil film is shown. Here, ultra-white glass, with its low thermal conductivity, is chosen as the transparent substrate. The laser forms an 11μm spot radius at the aluminum / glass interface, and two modulation frequencies, f0, are used, 500Hz and 1MHz, respectively. Figure 4 (a–d) Four sets of original signals are given; among the six sets of processed data, five are valid signals, and the low-frequency amplitude ratio signal is difficult to provide additional independent parameters. Figure 4 (e–h) show the normalized signal and sensitivity of the reference group at two frequencies, and the sensitivity coefficient S of the signal R to the parameter α. α Defined as At 500Hz, the signal is related to the thermal diffusivity of the glass k sub / C sub is extremely sensitive, where k is the thermal conductivity, C is the specific heat capacity, and the subscript sub represents the substrate. By iteratively adjusting the model input to best match the simulation curve with the experimental curve, k can be obtained. sub / C sub =0.4688mm 2 / s. At 1MHz, the square of the heat dissipation rate of the signal to the glass is k sub C sub The sensitivity to the thermal conductivity G1 of the aluminum / glass interface is very weak, so G1 is fixed to 100±50MW / (m 2 K). Here, the interface thermal conductivity G is the interface thermal resistance R int The reciprocal of G = 1 / R int The present invention adopts the method of using G as the inversion variable to perform sensitivity analysis and fitting to improve parameter convergence and numerical stability. The fitting result gives k sub C sub =1.5411MJ 2 / (m 4 ·K 2 ·s). Combining the two equations, we can get the thermal conductivity of glass k sub =0.85±0.04W / (m·K), volumetric heat capacity C sub =1.813±0.09MJ / (m 3 ·K).

[0088] Figure 4(i, j) shows the amplitude ratio and sensitivity of the test group and the reference group at high frequency. During the measurement process, as the heating time goes by, the heat gradually diffuses into the liquid film, and the signal sensitivity to the thermal conductivity G2 of the aluminum / peanut oil interface gradually decreases, while the sensitivity to the square of the peanut oil thermal dissipation rate k f C f The sensitivity of both parameters is negative, which means that the larger the parameter, the less heat is accumulated in the metal film. Figure 4 (k–n) is the normalized signal of the test group at two frequencies: at 1 MHz, G2 and k f C f The impact on the signal is opposite in sign, and the fitting Figure 4 (i) with Figure 4 (k) get k f C f =0.315MJ 2 / (m 4 ·K 2 ·s), G2=16±2MW / (m 2 ·K). At 500Hz, k f and C f No longer coupled in the form of a product; k f C f Fixed to the above value, adjust C f Until the best fit, the thermal conductivity k of peanut oil can be obtained f =0.17±0.01W / (m·K), volume heat capacity C f =1.85±0.09MJ / (m 3 ·K).

[0089] In comparison, traditional methods (such as CN112268927A) can only obtain limited parameters at a single frequency. The present invention utilizes the five groups of normalized / difference signals shown in the figure, combined with sensitivity curve superposition analysis, to significantly improve parameter decoupling.

[0090] At a low frequency of 500 Hz, the heat penetration depth d p =k f 0.5 (πf0C f ) -0.5 Calculated to be 8μm. If the film thickness is greater than three times this depth, that is, at least 24μm, heat cannot penetrate the film. In this case, the film thickness can be ignored and it can be considered as a semi-infinite material. Otherwise, the film thickness must be known to determine the film thermal conductivity and specific heat capacity, or the film specific heat capacity must be known to determine the film thermal conductivity and thickness.

[0091] The technology of the present invention is also applied to a variety of liquids for verification at room temperature, including WD-40 lubricating oil, a TBP-n-dodecane mixture with a volume ratio of 3:7, peanut oil, ethanol, a 25wt% NaCl aqueous solution and pure water. Figure 5 The results show that the thermal conductivity measured for a variety of liquid samples is consistent with the literature values, further verifying the accuracy of this method; at the same time, the thermal resistance of the interface between the liquid and the aluminum film is obtained, filling the gap in the existing literature.

[0092] In addition to liquid materials, the technology of the present invention is also applicable to the measurement of soft materials such as polymer gels. Figure 6 Taking thermal conductive gel (a thermal interface material) under a pressure of 2.279MPa as an example, the specific implementation of the technology of the present invention in TIMs measurement is explained. The substrate is still glass coated with 100nmAl, but since applying mechanical pressure to Al will change its thermal reflection coefficient, it is necessary to add a new parameter to be determined - the thermal reflection coefficient ratio TRR, which is the ratio of the thermal reflection coefficient of Al after pressing the TIM to the thermal reflection coefficient of Al in the blank state. The new parameter makes the low-frequency amplitude ratio signal also have information content. The experiment uses two modulation frequencies of 4kHz and 1MHz, and the laser spot radius is 15μm; the four sets of observation data are two sets of normalized amplitude signals with TIM, and two sets of amplitude ratio signals.

[0093] Figure 6 (ab), Figure 6 (cd) is the normalized amplitude signal and sensitivity analysis at low and high frequencies, Figure 6 (ef), Figure 6 (gh) is the amplitude ratio and sensitivity analysis at low and high frequencies. The parameters to be measured include the thermal conductivity k of the thermal conductive gel. TIM , volume heat capacity C TIM , Al / thermal gel interface thermal conductivity G2 and TRR. k TIM and C TIM The sensitivity signs are opposite, and k TIM and C TIM The sensitivity curves coincide with each other. Figure 6 The G2 sensitivity curve in (h) has a zero point, which is related to k TIM C TIM Different. The sensitivity curve of TRR is a horizontal line, which is different from other parameters. The above characteristics show that four sets of signals can simultaneously determine four parameters. Fitting the four sets of signals to obtain k TIM =2.94±0.11W / (m·K), C TIM =1.088±0.052MJ / (m 3 ·K), G2=1.03±0.05MW / (m 2 ·K), TRR=1.103.

[0094] The structure adopted by the present invention allows multi-frequency periodic thermal excitation under pressurized state without the need for frequency domain Fourier transformation, thereby avoiding high-order harmonic interference caused by unclear sine wave boundaries in the CN112268927A solution.

[0095] The same method was used to measure the thermal properties of the thermally conductive gel at different pressures. The results of thermal conductivity, specific heat capacity and interface thermal conductivity are shown in the figure below. Figure 7 As shown in (a, b, c), under high pressure, the network of thermally conductive fillers in the gel and the polymer matrix is ​​sheared or "pumped out," squeezing the matrix material out of the gaps between the fillers. This increases the porosity, destroying the original thermal channel network and reducing the effective thermal conductivity.

[0096] The specific heat capacity shows an increasing trend. During the compression process, the air or solvent voids in the gel are squeezed out, and the overall density of the material increases, so that more heat-capacity substances are contained per unit volume, and the volumetric heat capacity increases accordingly.

[0097] Under moderate pressure, the actual contact area of ​​the aluminum / gel interface increases, a large amount of air (thermal conductivity is only ~0.026W / (m·K)) is replaced by the thermally conductive gel, the microscopic voids on the interface are reduced, the contact thermal resistance is significantly reduced, and the thermal conductivity of the interface is improved. As the pressure continues to increase, the high thermal conductivity filler and the polymer matrix in the gel begin to undergo microscopic rearrangement: the polymer matrix "squeezes out" the real contact area under high stress, or creep migration occurs, causing the filler particles to cluster near the interface, while a resin-rich layer or tiny voids appear at the interface. Another common failure mechanism is "dry-out": low molecular weight components in the polymer matrix are forced out, the filler separates from the matrix, and the originally uniform thermal conduction channel fails locally, so the thermal resistance at the interface rises again.

[0098] It should be noted that the embodiments of the present invention are not limited to the above examples. For example, the modulation waveform of the differential square pulse heat source (DSPS) can use periodic pulses such as trapezoidal and sawtooth waves in addition to square waves; the transparent substrate material can be replaced with sapphire, quartz, or polyimide film; and the metal sensing layer can also be made of other materials with high thermal reflectivity, such as gold or copper, depending on the wavelength of the detection light. Any equivalent substitutions or improvements made within the technical framework of this invention are intended to be included within the scope of protection of this invention.

[0099] The method described herein can be implemented at ambient temperature and pressure, but is also applicable to extreme environments (e.g., temperatures ranging from -50°C to 300°C, under vacuum, or under high pressure). In practice, the optical window material (e.g., sapphire for high temperatures) and seal design may need to be adjusted based on the environment. Such adaptability improvements remain within the technical scope of the present invention.

[0100] To minimize the influence of experimental system parameters (including laser spot size and the thermal properties of the substrate material and metal layer), this paper employs a differential measurement method, conducting two sets of experiments: i) a reference experiment (without a liquid film or soft material layer), recording the temperature response signals of the substrate and metal sensing layer; and ii) a measurement experiment (with the material layer to be measured), recording the temperature response signals of the liquid film or soft material layer. By normalizing the signals and calculating the ratio of the two experimental signals, the sensitivity of the signals to the interfacial thermal resistance is increased, enabling simultaneous measurement of both material thermal conductivity and interfacial thermal resistance. This also reduces the influence of the substrate and metal sensing layer parameters on the measured thermal properties, improving measurement accuracy and reducing experimental system errors.

[0101] Based on Fourier's law of heat conduction, a heat transport model of the multilayer thin film structure is established to solve the temperature response of the metal sensing layer under periodic heating conditions. Parameter inversion is performed based on experimental data to extract thermal conductivity, specific heat capacity and interfacial thermal resistance.

[0102] The inversion algorithm adopts a hybrid strategy of particle swarm optimization (PSO) and quasi-Newton method (BFGS) to quickly and accurately achieve the best fit between experimental data and theoretical simulation curves.

[0103] Different pump laser modulation frequencies (e.g., 100 Hz-1 MHz) are used to control the heat penetration depth and heat diffusion direction, and to distinguish the heat transport contributions of different physical parameters.

[0104] Low frequency (~100 Hz) is used to measure the in-plane thermal diffusivity (α r ), defined as the ratio of the in-plane thermal conductivity to the volume specific heat capacity (k r / C); high frequency (~1MHz) is used to measure the longitudinal thermal dissipation rate of thin film materials (e z ), defined as the square root of the product of longitudinal thermal conductivity and volume specific heat capacity ((k z C) 0.5 ). Through multi-frequency joint fitting, and based on the isotropic properties of the material to be tested, the thermal conductivity and volume specific heat capacity of the material can be determined simultaneously.

[0105] The present invention solves the following key problems:

[0106] 1. Overcoming the parameter coupling problem: Existing methods require the pre-assumption of specific heat capacity. The present invention uses a multi-frequency strategy to achieve simultaneous measurement of thermal conductivity and specific heat capacity.

[0107] 2. Improve the measurement accuracy of low thermal conductivity materials: Traditional methods have low sensitivity to the interface thermal resistance of low thermal conductivity materials, or it is difficult to separate the intrinsic thermal resistance of the material and the interface thermal resistance. The present invention improves the sensitivity of the signal to the interface thermal resistance through differential measurement, thereby achieving simultaneous measurement of the material thermal conductivity and interface thermal resistance.

[0108] 3. Applicable to soft solid and liquid TIMs: Existing methods are mainly targeted at solid films, while the present invention expands to application fields such as liquids, gels, and phase change materials.

[0109] The present invention has the following alternatives to achieve the purpose of the invention:

[0110] 1. Selection of light source and metal film material

[0111] The wavelengths of the pump and probe lasers can be flexibly selected within the 400-800nm ​​range. The metal film material should be selected based on the probe laser wavelength, ensuring a high thermal reflectivity at that wavelength. For example, if the probe laser wavelength is 785nm, aluminum, tantalum, or hafnium nitride can be used as the metal sensing layer material; if the probe laser wavelength is 532nm, gold, tantalum, or molybdenum can be used as the metal sensing layer material.

[0112] 2. Selection of detection method

[0113] A periodic waveform analyzer can be replaced by an oscilloscope, although the signal-to-noise ratio and measurement speed are relatively poor.

[0114] 3. Data processing optimization

[0115] Introducing deep learning algorithms, training data models through neural networks, optimizing the signal fitting process, and improving computing efficiency.

[0116] The present invention is applicable to multiple high-precision thermal measurement scenarios, including but not limited to:

[0117] 1. Heat dissipation of microelectronic devices (such as chip TIMs optimization)

[0118] 2. Research on phase change energy storage materials (such as measurement of thermal transport properties of phase change materials)

[0119] 3. Characterization of flexible electronics and thermal conductive gels (such as thermal conductive gels and polymer composites)

[0120] 4. Nuclear industry and aerospace materials (measurement of small-size samples under high temperature and high pressure environments)

[0121] This invention achieves a significant breakthrough in measuring the thermal properties of thermal interface materials (TIMs), phase-change energy storage materials, gels, and soft solid-state thin film materials. Compared to existing technologies, this invention can simultaneously measure the thermal conductivity, specific heat capacity, and solid-liquid interface thermal resistance of materials, effectively overcoming the parameter coupling problem. The measurement error of liquid thermal conductivity is reduced from ±14% to ±4%, improving measurement accuracy and providing a scientific basis for the design and optimization of efficient thermal management systems. This invention achieves the following technical effects:

[0122] 1. Improved measurement accuracy

[0123] The differential measurement strategy eliminates the influence of experimental system parameters on the measurement signal, improving the ability to independently measure thermal conductivity, specific heat capacity, and interfacial thermal resistance. Experimental data show that the present invention measures the thermal conductivity of liquids and gels with an error of less than ±5%, which is at least 50% higher than the traditional TDTR method (error of ±10-15%).

[0124] By adopting a multi-frequency measurement strategy and combining the optimization algorithm of particle swarm optimization and quasi-Newton method, the uncertainty of solid-liquid interface thermal resistance measurement is reduced from ±50% to within ±10%, effectively solving the problem of insufficient sensitivity of traditional methods in measuring the interface thermal resistance of low thermal conductivity materials.

[0125] 2. Wide range of applicable materials

[0126] The traditional LFA and steady-state methods are mainly applicable to solid thin films, while the present invention is applicable to liquid, gel and soft solid thin film materials, including:

[0127] Polymer thermal conductive gel (such as thermal conductive silica gel, phase change thermal conductive material)

[0128] Low thermal conductivity TIMs (such as oil-based and grease-based TIMs)

[0129] Phase change energy storage materials (such as organic phase change materials, porous structure energy storage materials)

[0130] The present invention can be used to measure materials with thermal conductivity ranging from 0.1 to 2000 W / (m·K), and can simultaneously measure the thermal conductivity and specific heat capacity of the material, with a typical measurement error of less than 5%. Traditional TDTR / FDTR thermal reflection methods require known material specific heat capacity, and the measurement error of thermal conductivity is usually greater than 10%.

[0131] 3. Improved micro- and nano-scale measurement capabilities

[0132] While existing TIMs testing standards (such as ASTM D5470) typically require samples with millimeter-level thicknesses, the present invention can measure the thermal properties of thin films ranging from 10nm to infinity. Combined with a transmissive substrate design (such as quartz or sapphire), the present invention can measure the thermal transport characteristics of microscale liquid films, making it particularly suitable for thermal management research in nanoelectronic devices and MEMS systems.

[0133] 4. Improve TIMs material development efficiency and reduce R&D costs

[0134] Currently, the TIMs industry requires multiple methods for thermophysical property measurements during material development. For example, thermal conductivity can only be measured by combining differential calorimetry (DSC) to measure specific heat capacity, water displacement to measure density, and thermal diffusivity using FLA. This results in long testing cycles and high costs. The present invention can simultaneously measure multiple parameters, including thermal conductivity, specific heat capacity, and interfacial thermal resistance, in a single measurement, shortening experimental time by over 50% and reducing testing costs by approximately 70%.

[0135] Research on thermal conductive materials suitable for high-power electronic devices (such as 5G base station chips and SiC power devices) will help promote the industrialization process of new TIMs.

[0136] 5. Improve the application efficiency of phase change energy storage materials

[0137] The present invention can measure the thermal conductivity and specific heat capacity of phase-change energy storage materials at different temperatures, providing key data for optimizing the heat transfer performance of energy storage materials and promoting the development of the renewable energy field.

[0138] Taking common paraffin-based phase change materials as an example, their thermal conductivity is as low as 0.2W / (m·K). Traditional measurement methods have large errors, while the accuracy of the present invention can be controlled within ±5%, providing reliable support for the engineering application of energy storage materials.

[0139] 6. Support the development of high-end thermal management technology

[0140] This device is suitable for measuring heat transport in tiny samples in extreme environments such as aerospace and nuclear power, filling a gap in existing measurement technology. It can measure small-scale TIMs (such as polymer thermally conductive fillers and nanocomposite thermally conductive gels) in high-temperature (1000K) and high-pressure (100MPa) environments, significantly contributing to the development of advanced thermal management technologies in aerospace, nuclear power, and other fields.

[0141] The present invention has been verified by experiments on a variety of typical liquid films and gel materials, and the measurement results are shown in the following table:

[0142] Material Traditional TDTR measurement error The measurement error of the present invention Improved measurement accuracy pure water ±14％ ±4％ 71％ Polymer thermal conductive gel ±18％ ±4％ 78％

[0143] Experimental results show that the present invention has higher accuracy and stability in measuring low thermal conductivity liquid films and gel materials than traditional methods.

[0144] Compared with the prior art (such as CN112268927A), the present invention has the following breakthroughs:

[0145] 1) Innovative excitation method: Using a periodic square wave heat source, the signal boundary is clear and the temperature response feature extraction is more accurate;

[0146] 2) Measurement parameter expansion: Achieve simultaneous inversion of thermal conductivity, specific heat capacity, and interfacial thermal resistance without assuming prior information;

[0147] 3) Differential measurement strategy: eliminate systematic errors and enhance the sensitivity of measurement to interface thermal resistance;

[0148] 4) Applicable materials expansion: Applicable to highly deformable materials such as liquid, gel and soft solid;

[0149] 5) Intelligent inversion algorithm: Combined with sensitivity-driven parameter optimization, it improves the algorithm’s convergence speed and stability;

[0150] 6) Strong ability to simulate actual working conditions: The pressurized component simulates the real interface state and enhances the adaptability of measurement scenarios.

[0151] In summary, the technical solution of the present invention is significantly superior to the existing technology in terms of structural design, signal processing, scope of application and parameter extraction capability, and has outstanding substantive features and significant technological progress.

[0152] This method overcomes the limitations of traditional TIMs and solid-liquid interface thermal resistance measurement techniques, demonstrating significant advantages in measurement accuracy, material applicability, micro- and nanoscale adaptability, and economic and social benefits. It has broad application prospects in high-power electronic device heat dissipation, phase change energy storage material development, nuclear energy, and aerospace thermal management.

[0153] Example 3:

[0154] An embodiment of the present invention provides a method for measuring thermophysical parameters of liquid thin film materials, comprising the following steps:

[0155] S1) Under the condition of not covering the liquid film, the reference signals at low frequency and high frequency are collected respectively, which are recorded as and

[0156] S2) After covering the liquid film, the measured signal is collected with the same modulation frequency and laser power, which are respectively recorded as A L (t) and A H (t);

[0157] S3) normalize the above signal to obtain a normalized signal and The normalization calculation formula is:

[0158]

[0159] Where t is the normalized time variable, t1 = -0.02, t2 = 0.48;

[0160] S4) The high frequency signal A H (t) and After benchmarking and division, the amplitude ratio signal R(t) is obtained, which is calculated as follows:

[0161]

[0162] S5) By fitting the heat conduction model, the liquid thermal conductivity k is obtained by minimizing the experimental-simulation deviation. f , volume heat capacity C f And the solid-liquid interface thermal conductivity G.

[0163] Example 4:

[0164] The present invention also provides a method for measuring the thermal properties of soft material films, which is used to test the thermal properties of thermal interface materials (TIMs), and includes the following steps:

[0165] T1) obtaining a reference signal and determining the substrate thermophysical parameters when there are no TIMs;

[0166] T2) placing the thermal interface material between the metal film and the pressure plate and applying a predetermined pressure, and collecting the signal to be measured;

[0167] T3) Normalize the reference and measured signals and calculate the amplitude ratio, combine the low-frequency and high-frequency four-group signal fitting simultaneously, and obtain the thermal conductivity k of the thermal interface material. TIM , volume heat capacity C TIM , metal / interface material interface thermal conductivity G and thermal reflectivity ratio TRR.

[0168] The embodiments described above are merely descriptions of preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Without departing from the spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by persons skilled in the art should fall within the scope of protection defined by the claims of the present invention.

Claims

1. A system for measuring the thermal properties of soft material films, characterized in that: include: A signal generator, used for outputting a square wave modulation signal and providing a synchronization reference signal; A pump optical circuit, comprising a pump laser, for receiving the square wave modulation signal and outputting modulated laser light, wherein the modulated laser light is focused on the sample surface via a dichroic mirror and an objective lens to achieve periodic thermal excitation; The detection optical path includes a detection laser, a λ / 2 wave plate, a polarization beam splitter, a λ / 4 wave plate, the dichroic mirror and the objective lens arranged in sequence, and is used to coaxially focus the detection laser onto the sample surface and to separate the reflected detection light according to the polarization state; a photoelectric detector, configured to convert the intensity of the reflected detection light into an electrical signal; a signal processing module, comprising a periodic waveform analyzer for extracting a single-period amplitude of a thermal response signal synchronized with the reference signal; A sample platform, including a transparent substrate and a metal film deposited on the surface thereof, serving as a temperature sensing structure; a differential measurement module for collecting thermal response signals of the metal film when it is not covered and when it is covered with the material to be tested, and performing normalization processing and amplitude ratio calculation on the obtained signals; The thermal parameter inversion unit is used to invert the thermal conductivity, volume specific heat capacity and interface thermal resistance of the material to be tested based on multi-frequency measurement signals and combined with a hybrid optimization algorithm.

2. The system according to claim 1, wherein The square wave modulation signal output by the signal generator includes a low frequency part (f L <10kHz and high frequency part (f H >100kHz) to produce different thermal penetration depths, thereby achieving differentiated stimulation of the thermal response of each layer in a multi-layer structure.

3. The system according to claim 1, wherein The differential measurement module adopts an amplitude ratio calculation strategy to reduce the impact of system parameter fluctuations on the measurement results and improve the sensitivity and accuracy of the interface thermal resistance measurement; the thermal parameter inversion unit performs sensitivity analysis and the calculation form is: The sensitivity coefficient is used to evaluate the influence of different thermal parameters on the response signal and realize parameter decoupling. The inversion process sets a unified normalized time point t0 to eliminate systematic deviations and improve the robustness of parameter decoupling. The optimization algorithm is a hybrid optimization strategy formed by combining the particle swarm optimization algorithm and the quasi-Newton method.

4. The system according to claim 1, wherein: The transparent substrate is ultra-white glass, optical-grade PMMA or other transparent materials with low thermal conductivity. The metal film is aluminum, tantalum, hafnium nitride or titanium nitride, and has a thickness ranging from 50 to 200 nm.

5. The system according to claim 1, wherein: It also includes a sample pressurizing assembly, which includes a pressure plate, a bolt, a spring and a sample container with a light-through hole, and is used to apply quantitatively controllable mechanical pressure to the sample when measuring the thermal interface material to simulate the compression conditions under actual service conditions.

6. The system according to claim 1, wherein: It also includes a microscopic imaging module for observing the position of the laser spot on the sample surface in real time and monitoring changes in the sample surface morphology.

7. A method for measuring the thermal properties of liquid films, characterized in that: The following steps are involved: S1) Under the condition of not covering the liquid film, the reference thermal response signals at low frequency and high frequency are collected respectively, which are recorded as and S2) After covering the liquid film, the measurement signal is collected under the same modulation frequency and laser power conditions, and is recorded as A L (t) and A H (t); S3) normalizing the above signal to obtain a normalized thermal response signal and The normalization formula is: Where t is the normalized time variable, t1 = -0.02, t2 = 0.48; S4) The high frequency measurement signal A H (t) and reference signal Perform benchmarking and calculate the ratio to obtain the amplitude ratio signal R(t), which is calculated as follows: S5) constructing a simulation response signal based on a multilayer heat transfer model, and fitting it with the normalized thermal response signal obtained in step S3 and the amplitude ratio signal obtained in step S4, respectively. By jointly minimizing the difference between the two types of signals and the corresponding simulation signals, the thermal conductivity k of the liquid film is inverted. f , volume specific heat capacity C f And interface thermal resistance R int .

8. A method for measuring thermal properties of thermal interface materials (TIMs), characterized in that: The following steps are involved: T1) without placing a thermal interface material, collecting reference thermal response signals at low and high frequencies, respectively, and inverting the thermal conductivity and volume specific heat capacity of the transparent substrate based on the signals; T2) placing the thermal interface material between the metal film and the pressure member, applying a predetermined mechanical pressure, and collecting a thermal response signal comprising the thermal interface material under the same modulation frequency and laser power conditions; T3) normalizing the reference signal and the measurement signal comprising the thermal interface material to obtain a normalized thermal response signal; and calculating an amplitude ratio signal based on the result at high frequency; T4) constructing a heat conduction model, generating a corresponding simulation signal, and fitting it with the normalized thermal response signal and the amplitude ratio signal respectively; by minimizing the difference between the simulation signal and the experimental signal, jointly inverting to obtain the thermal conductivity k of the thermal interface material TIM , volume specific heat capacity C TIM And interface thermal resistance R int .

9. The method according to claim 7 or 8, characterized in that The time points t1 and t2 used in the normalization process are set based on the stable section of the reference signal to improve the sensitivity of the normalized signal to the change of the interface thermal resistance and reduce the influence of the system error on the inversion result.

10. The method according to claim 7 or 8, characterized in that Measurements can be performed in a temperature range of -50°C to 500°C, or in vacuum or high-pressure conditions to accommodate a variety of extreme service environments.

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