A method and device for characterizing the inhomogeneity of gels based on multi-field-of-view micro-rheology

Abstract

The present invention discloses a method and device for characterizing the inhomogeneity of a gel based on multi-field micro-rheology. The method includes: adding probe particles to a gel prepolymer solution, obtaining a sample after subjecting the gel prepolymer solution to gelation treatment; placing the sample on a micro-rheometer, and using a high-speed camera to capture videos of the thermal motion of particles in multiple fields of view under a fluorescence microscope; positioning the probe particles on the sample according to the videos of the thermal motion of the particles, connecting the probe particles to obtain a coordinate sequence of the particle trajectories in each field of view, and obtaining all the particle trajectory data after traversing the data of each field of view; calculating various observables based on the particle trajectory data to characterize the inhomogeneity of the gel. The present invention is based on multi-field micro-rheology technology, provides a new method for the research and characterization of inhomogeneity, and can accurately and completely characterize the change of gel inhomogeneity. The present invention can be widely applied to the field of micro-rheology characterization.

Description

Technical Field

[0001] The present invention relates to the field of micro-rheological characterization, and particularly to a method and device for micro-rheological characterization of the inhomogeneity of gels based on multiple fields of view. Background Art

[0002] Gel materials have a wide range of applications in production and life due to their flexibility and good biocompatibility, such as facial masks, medical hydrogels, flexible sensors, etc. Most gel materials have inhomogeneity during the synthesis process, which directly affects the macroscopic mechanical properties and other functions of the gel materials. Therefore, in order to produce gel materials with better performance, it is necessary to characterize the inhomogeneity during the gelation process to provide guidance for the production, design, and improvement of gel products.

[0003] Since the inhomogeneity of gels changes with time and space, traditional rheometers can only obtain the average viscoelastic spectrum of the gel at a spatial position, while micro-rheometers use the thermal motion of probe particles to shear the surrounding medium, so the local viscoelastic spectrum of the sample can be obtained. However, there is a fundamental contradiction in this technology: in order not to affect the rheological properties of the gel, the concentration of the added probe particles is extremely small, which results in not enough particles in a single field of view, affecting the accuracy and reliability of the statistical results. In addition, this technology can only characterize gel materials with inhomogeneity scales smaller than a field of view, and these deficiencies limit the application of micro-rheometers. For example, the prior art uses particle-tracking micro-rheology to study the inhomogeneity of protein solutions. Due to the small number of particles counted, the value of the non-Gaussian factor α2 calculated is not satisfactory. Summary of the Invention

[0004] To solve at least one of the technical problems existing in the prior art to a certain extent, the purpose of the present invention is to provide a method and device for micro-rheological characterization of the inhomogeneity of gels based on multiple fields of view.

[0005] The technical solution adopted by the present invention is as follows:

[0006] A method for micro-rheological characterization of the inhomogeneity of gels based on multiple fields of view, comprising the following steps:

[0007] Add probe particles to the gel prepolymer solution, and after gelation treatment of the gel prepolymer solution, obtain a sample;

[0008] Place the sample on a micro-rheometer, and use a high-speed camera to capture videos of the thermal motion of particles in multiple fields of view under a fluorescence microscope;

[0009] According to the videos of the thermal motion of particles, locate the probe particles on the sample, and after connecting the probe particles, obtain the coordinate sequence of the particle trajectories in each field of view. After traversing the data of each field of view, obtain all the particle trajectory data;

[0010] Calculate various observables based on the particle trajectory data to characterize the inhomogeneity of the gel.

[0011] Furthermore, the concentration of the probe particles in the gel prepolymer solution is between 0.00001 wt% and 0.0001 wt%.

[0012] Furthermore, the gelation treatment of the gel prepolymer solution includes:

[0013] Inject the gel prepolymer solution into a glass chamber, place the glass chamber in a thermostatic metal bath, and wait for the gel prepolymer solution to completely gel.

[0014] Among them, after the gel prepolymer solution is injected into the chamber, it needs to be sealed with vacuum silicone grease and placed in a 25°C metal bath for 24 h.

[0015] Furthermore, placing the sample on the microrheometer includes:

[0016] Set the working parameters of the microrheometer, where the working parameters include temperature, number of video frames, frame rate, and exposure time.

[0017] In addition, it is necessary to take videos of the thermal motion of particles in multiple fields of view, ensuring that there are at least 20 particles in each field of view. Before taking videos of each field of view, it needs to be stationary for more than 1 min to ensure that the particle motion is not affected by other factors except temperature.

[0018] Furthermore, before positioning the probe particles, the following steps are also included:

[0019] Perform image preprocessing on the video of particle thermal motion, calculate the average background noise of the image using gate integration, and subtract the average background noise to improve the signal-to-noise ratio of the image.

[0020] Furthermore, positioning the probe particles on the sample includes:

[0021] Use the positioning program to identify the coordinates of the probe particles in each frame of the image, record the coordinates (i, j) of the probe particles, and use the variable k for field-of-view marking.

[0022] Furthermore, after connecting the probe particles, obtaining the coordinate sequence of the particle trajectories in each field of view includes:

[0023] Find out and connect the coordinates of the same particle in different frames according to the random walk probability to obtain the coordinate sequence of the particle trajectory in a single field of view.

[0024] Furthermore, after traversing the data of each field of view, obtaining all the particle trajectory data includes:

[0025] Read the sequence of particle trajectory coordinates in each field of view one by one. At this time, the total number of particles N = ∑n1 + n2 + … + n k , and calculate the mean square displacement of the particles according to the principles of statistical thermodynamics.

[0026] Furthermore, the ranges of mean square displacement statistics are different, and the scales of inhomogeneity characterized by the calculated non-Gaussian factors are different:

[0027]

[0028] Equation (1) means that the mean square displacement of a single particle is first statistically analyzed, and the numerical average of the mean square displacements of all particles is calculated. It can only characterize the inhomogeneity of the medium within the trajectory of a single particle;

[0029]

[0030] Equation (2) means that the mean square displacements of all particles in a single field of view are first statistically analyzed, and the numerical average of the mean square displacements between different fields of view is calculated. It characterizes the inhomogeneity of the medium within a single field of view;

[0031] <Δx 2 (Δt)>| mp =∫ 所有视场所有粒子的位移 Δx 2 p(Δx)d(Δx) (3)

[0032] Equation (3) means that the mean square displacements of all particles in all fields of view are statistically analyzed, and it characterizes the inhomogeneity exceeding the scale of one field of view;

[0033] Among them, Δx is the displacement, Δt is the time interval, N is the total number of probe particles, p(Δx) is the probability that the displacement of the probe particle is Δx, M is the total number of fields of view, sp indicates that the statistics are for single particles, sf indicates that the statistics are for single fields of view, mp indicates that the statistics are for multiple fields of view, and <> indicates taking the average of the variables within the symbol.

[0034] Another technical solution adopted by the present invention is:

[0035] An apparatus for characterizing the inhomogeneity of a gel based on multi-field micro-rheology, comprising:

[0036] At least one processor;

[0037] At least one memory for storing at least one program;

[0038] When the at least one program is executed by the at least one processor, the at least one processor implements the above method.

[0039] The beneficial effects of the present invention are as follows: Based on the multi-field micro-rheology technology, the present invention provides a new method for the research and characterization of inhomogeneity, and can completely and accurately characterize the change of gel inhomogeneity. Description of the Drawings

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following introduces the drawings related to the technical solutions in the embodiments of the present invention or the prior art. It should be understood that the drawings introduced below are only for conveniently and clearly expressing some embodiments of the technical solutions in the present invention. For those skilled in the art, without creative work, other drawings can also be obtained based on these drawings.

[0041] Figure 1 It is a flowchart of the steps of a method for characterizing the inhomogeneity of a gel based on multi-field micro-rheology in an embodiment of the present invention. Detailed Embodiments

[0042] The following details the embodiments of the present invention. The examples of the embodiments are shown in the drawings, where the same or similar reference numerals represent the same or similar elements or elements with the same or similar functions from beginning to end. The embodiments described below with reference to the drawings are exemplary and are only used to explain the present invention, and should not be construed as a limitation of the present invention. For the step numbers in the following embodiments, they are only set for the convenience of explanation, and no limitation is imposed on the order between the steps. The execution order of each step in the embodiments can be adaptively adjusted according to the understanding of those skilled in the art.

[0043] In the description of the present invention, it should be understood that for the orientation description, such as the upper, lower, front, rear, left, right, etc., the orientation or positional relationship indicated is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention.

[0044] In the description of the present invention, the meaning of "several" is one or more, the meaning of "multiple" is two or more, and the understanding of "greater than", "less than", "exceeding", etc. does not include the present number, and the understanding of "above", "below", "within", etc. includes the present number. If there is a description of "first" and "second", it is only for the purpose of distinguishing technical features and should not be understood as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features or implicitly indicating the sequence of the indicated technical features.

[0045] In the description of the present invention, unless otherwise clearly defined, words such as "set", "installed", "connected", etc. should be understood in a broad sense, and those skilled in the art can reasonably determine the specific meanings of the above words in the present invention in combination with the specific content of the technical solution.

[0046] As shown Figure 1 in the figure, this embodiment provides a method for characterizing the inhomogeneity of a gel based on multi-field micro-rheology. By characterizing the inhomogeneity of the gel based on multi-field micro-rheology and combining techniques such as particle positioning, connection, labeling, and statistics, the non-Gaussian factor of the system can be calculated more accurately and reliably, and the large-scale inhomogeneity of the gel can be characterized. The method includes the following steps:

[0047] S1. Add probe particles to the gel prepolymer solution, and after subjecting the gel prepolymer solution to gelation treatment, obtain a sample.

[0048] In this embodiment, first add probe particles to the gel prepolymer solution, then inject the prepolymer solution into a glass chamber, and place it in a thermostatic metal bath until it is completely gelled. Among them, the addition of probe particles should not affect the rheological properties of the gel, and the concentration of probe particles in the gel solution is between 0.00001wt% and 0.0001wt%. After the gel prepolymer solution is injected into the chamber, it needs to be sealed with vacuum silicone grease and placed in a 25°C metal bath for 24 hours.

[0049] S2. Place the sample on a micro-rheometer, and use a high-speed camera to capture videos of the thermal motion of particles in multiple fields of view under a fluorescence microscope.

[0050] Place the sample on a micro-rheometer. After setting parameters such as temperature, number of video frames, frame rate, and exposure time, use a high-speed camera to capture videos of the thermal motion of particles in multiple fields of view under a fluorescence microscope. Specifically, use a 60× phase contrast oil immersion objective, set the temperature control chamber to 30°C, set the parameters of the high-speed camera to 2000 frames, frame rate 50fps, exposure time 0.01s, and the pixel of each frame is 2560px×2160px. It is necessary to capture videos of the thermal motion of particles in multiple fields of view to ensure that there are at least 20 particles in each field of view. Each field of view needs to be stationary for more than 1 minute before shooting to ensure that the particle motion is not affected by other factors except temperature.

[0051] As an optional implementation method, image preprocessing is performed before probe particle positioning. The average background noise of the image is calculated using gate integration, and the average background noise is subtracted to improve the signal-to-noise ratio of the image.

[0052] S3. Based on the videos of particle thermal motion, locate the probe particles on the sample, connect the probe particles, and obtain the coordinate sequence of the particle trajectories in each field of view. After traversing the data of each field of view, all the particle trajectory data is obtained.

[0053] Use the positioning program to identify the coordinates of the particles in each frame of the image, record their coordinates (i, j), and use the variable k to mark which field of view it belongs to. Find and connect the coordinates of the same particle in different frames according to the random walk probability to obtain the coordinate sequence of the particle trajectory in a single field of view.

[0054] Read the coordinate sequences of particle trajectories in each field of view one by one. At this time, the total number of particles N = ∑n1 + n2 + … + n k , and calculate the mean square displacement of the particles according to the principles of statistical thermodynamics as the particle trajectory data.

[0055] S4. Calculate various observables based on the particle trajectory data to characterize the inhomogeneity of the gel.

[0056] Calculate various observables to characterize the inhomogeneity of the gel according to the principles of statistical thermodynamics and the Einstein - Stokes relationship. Different ranges of mean square displacement statistics result in different scales of inhomogeneity characterized by the calculated non - Gaussian factors:

[0057]

[0058] Equation (1) represents first statistically calculating the mean square displacement of a single particle and then taking the number average of the mean square displacements of all particles, which can only characterize the inhomogeneity of the medium within the trajectory of a single particle;

[0059]

[0060] Equation (2) represents first statistically calculating the mean square displacement of all particles in a single field of view and then taking the number average of the mean square displacements between different fields of view, which characterizes the inhomogeneity of the medium within a single field of view;

[0061] <Δx 2 (Δt)>| mp =∫ 所有视场所有粒子的位移 Δx 2 p(Δx)d(Δx) (3)

[0062] Equation (3) represents statistically calculating the mean square displacement of all particles in all fields of view, which characterizes the inhomogeneity exceeding the scale of one field of view.

[0063] The above method will be explained in detail below in combination with sodium alginate gel.

[0064] Sodium alginate is a natural polysaccharide extracted from brown algae, and its molecular structure is composed of two stereoisomers, mannuronic acid and guluronic acid. Sodium alginate can react with divalent metal ions such as calcium, copper, and zinc to form gels. When these metal ions are directly added to the sodium alginate solution, gels will be formed immediately, and the formed gels are very inhomogeneous, affecting their performance. The method of calcium ion slow release can be used to synthesize relatively homogeneous gels. Since sodium alginate is non - toxic and harmless and the gelation conditions are relatively mild, it has been widely used in the fields of food and medicine, etc.

[0065] In a specific embodiment, taking the cross - linking of sodium alginate and calcium ions as an example, it specifically includes the following steps:

[0066] (1) Preparation of sodium alginate gel

[0067] Sodium alginate was added to ultrapure water with a conductivity of 18.2MΩ·cm, and then the glass bottle containing the solution and the magnet was placed on a magnetic stirrer, fully stirred at room temperature (500rpm~600rpm) for about 1h, and then placed at room temperature for 24h to obtain a sodium alginate solution with a mass fraction of 1wt%. Calcium-ethylenediaminetetraacetic acid solution, D-glucono-1,5-lactone, and 0.5μm probe particles were added to the sodium alginate solution respectively, and the prepolymer was injected into a homemade glass chamber, sealed with vacuum silicone grease, and placed in a metal bath at 25℃ for 24h to allow the prepolymer to completely react and form a gel. The principle of gel formation is that D-glucono-1,5-lactone will slowly hydrolyze, the pH value of the solution will decrease, and calcium ions will be released from the complex to cross-link with sodium alginate. When the pH is less than 4, it can be considered that the calcium ions are completely released, and finally a sodium alginate gel cross-linked with calcium ions is obtained.

[0068] (2) Conducting microrheological experiments on gels based on multiple fields of view

[0069] Place the sample on the microrheometer, focus with a 60× phase contrast oil objective, set the temperature control chamber to 30°C, set the parameters of the high-speed camera to 2000 frames, a frame rate of 50fps, an exposure time of 0.01s, and the pixels of each frame are 2560px×2160px. Use a high-speed camera to shoot a video of the thermal motion of the particles under a microscope, and change the field of view of the fluorescence microscope until a sufficient number of particles are captured.

[0070] (3) Particle positioning, connection, labeling, statistics and calculation of inhomogeneity

[0071] Before positioning the probe particles, image preprocessing is performed. The first frame of the image is called out to determine the pixel diameter of the particle. The average background noise of the image is calculated using gate integration. The background noise of the video is then subtracted and the pixel diameter of the particle is re-determined. All particles on each frame are located and their coordinate positions (i, j) are memorized. The radius pixels of the particle movement are given according to the random walk probability, and the coordinate positions of all particles in each frame under the same field of view are found. The coordinates are connected to obtain the trajectory coordinate sequence of the particle, and the variable k is used to mark which field of view the particle belongs to. First, the trajectory coordinate sequence of the particles in each field of view is read one by one. At this time, the total number of particles N = ∑n1+n2+…+n k According to the principles of statistical thermodynamics and the Stokes-Einstein relationship, the mean square displacement, viscoelastic spectrum, non-Gaussian factor, etc. of the probe particle are calculated.

[0072] The method of the present invention is further described below through several specific embodiments.

[0073] Example 1

[0074] Weigh 0.0505 g of sodium alginate powder and add it to a glass bottle equipped with a magnetic stir bar. Use a pipette to measure 5 ml of ultrapure water and add it to the bottle. Stir at a speed of 600 rpm on a magnetic stirrer at room temperature for about 1 h, and then let it stand for 24 h to obtain a 1 wt% sodium alginate solution. Weigh 0.5000 g of the 1 wt% sodium alginate solution, and successively add 150 μl of a calcium-ethylenediaminetetraacetic acid solution with a concentration of 5.048×10 -2 mol / L, 200 μl of a D-glucono-1,5-lactone solution with a concentration of 0.1136 mol / L, 150 μl of ultrapure water, and 10 μl of a polystyrene probe particle suspension (diameter 0.2 μm). After stirring for 15 min, inject the mixture into a glass chamber and seal it with vacuum silicone grease. Then, place the glass chamber in a metal bath at 25 °C for 24 h to allow it to fully react to form a gel.

[0075] Place the sample on a microrheometer. Set the temperature of the temperature control chamber to 30 °C, use a 60× phase contrast oil immersion objective lens to focus, select the probe particles in the middle layer, set the duration of the high-speed camera to 2000 frames, the frame rate to 49.65 fps, the exposure time to 0.01 s, and the pixel size to 2560 px×2160 px. After stabilizing for 5 min, take a video. Change the field of view of the fluorescence microscope and stand still for 1 min until enough particles are captured.

[0076] Read the video file. First, perform image preprocessing. Call up the first frame image, set the pixel diameter of the particles to be 14, use gate integration to calculate the background noise of the image to be 300, subtract the background noise, and re-determine the pixel diameter of the particles to be 12. Locate all the particles on each frame and remember their coordinate positions (i, j). According to the random walk probability, give the maximum pixel radius of particle movement as 50, and use k to mark which field of view it belongs to. Read the trajectory coordinate sequence of the particles in each field of view one by one. At this time, the total number of particles N = ∑n1 + n2 + … + n k . Calculate the mean square displacement of the particles in different ranges:

[0077]

[0078]

[0079] <Δx 2 (Δt)>| mp =∫ 所有视场所有粒子的位移 Δx 2 p(Δx)d(Δx)

[0080] Then calculate the viscoelastic spectrum and non-Gaussian factor of the gel.

[0081] The obtained mean square displacement is almost a straight line with a slope of 0, indicating that sodium alginate has gelled and the particles can hardly perform Brownian motion; dynamic modulus: at 11 rad / s, the storage modulus is 98.86 Pa and the loss modulus is 21.07 Pa; at 5.5 rad / s, the storage modulus is 90.48 Pa and the loss modulus is 14.67 Pa; at 0.6 rad / s, the storage modulus is 78.32 Pa and the loss modulus is 8.10 Pa. The kinetic inhomogeneity of the gel, the non-Gaussian factor α2 of a single particle: 0.5 - 1.0; the non-Gaussian factor α2 of a single field of view: 5.0 - 10; the non-Gaussian factor of multiple particles: 7 - 15. The larger the non-Gaussian factor, the greater the degree of inhomogeneity of the gel.

[0082] Example 2

[0083] Weigh 0.0505 g of sodium alginate powder and add it to a glass bottle equipped with a magnetic stirrer. Use a pipette to measure 5 ml of ultrapure water and add it to the bottle. Stir at a speed of 600 rpm on a magnetic stirrer at room temperature for about 1 h, and then let it stand for 24 h to obtain a 1 wt% sodium alginate solution. Weigh 0.5000 g of the 1 wt% sodium alginate solution, and successively add 85 μl of a calcium-ethylenediaminetetraacetic acid solution with a concentration of 5.048×10 -2 mol / L, 200 μl of a D-glucono-1,5-lactone solution with a concentration of 0.0644 mol / L, 215 μl of ultrapure water, and 10 μl of a polystyrene probe particle suspension (diameter 0.2 μm). After stirring for 15 min, inject the mixture into a glass chamber and seal it with vacuum silicone grease. Then place the glass chamber in a metal bath at 25 °C for 24 h to allow it to react completely to form a gel.

[0084] Place the sample on a microrheometer. Set the temperature of the temperature control chamber to 30 °C. Use a 60× phase contrast oil immersion objective lens to focus. Select the probe particles in the middle layer. Set the duration of the high-speed camera to 2000 frames, the frame rate to 49.65 fps, the exposure time to 0.01 s, and the pixel size to 2560 px×2160 px. After stabilizing for 5 min, take a video. Change the field of view of the fluorescence microscope and stand still for 1 min until enough particles are captured.

[0085] Read the video file. First, perform image preprocessing. Call out the first frame image. Set the pixel diameter of the facility particle to 14. Use gate integration to calculate the background noise of the image as 300. Subtract the background noise and re-determine the pixel diameter of the particle to be 12. Locate all the particles on each frame and remember their coordinate positions (i, j). According to the random walk probability, give the maximum pixel radius of the particle movement as 50, and use k to mark which field of view it belongs to. Read the trajectory coordinate sequence of the particles in each field of view one by one. At this time, the total number of particles N = ∑n1 + n2 + … + n kStatistically analyze the mean square displacement of particles in different ranges:

[0086]

[0087]

[0088] <Δx 2 (Δt)>| mp =∫ 所有视场所有粒子的位移 Δx 2 p(Δx)d(Δx)

[0089] Then calculate the viscoelastic spectrum and non-Gaussian factor of the gel.

[0090] The mean square displacements of particles in different fields of view obtained vary greatly. In some positions, gelation has occurred and the particles cannot move; in other positions, the probe particles can perform random thermal motion. The dynamic inhomogeneity of the gel, the non-Gaussian factor α2 of single particles: 0.1 - 0.5; the non-Gaussian factor α2 of a single field of view: 6.3 - 23; the non-Gaussian factor of multiple particles: 11 - 98. The non-Gaussian factor of multiple particles reaches 100, which has not been reported before, indicating that the inhomogeneous scale of the gel has exceeded one field of view.

[0091] Example 3

[0092] Weigh 0.0505 g of sodium alginate powder and add it to a glass bottle equipped with a magnetic stirrer. Use a pipette to measure 5 ml of ultrapure water and add it to the bottle. Stir at a speed of 600 rpm on a magnetic stirrer at room temperature for about 1 h, and then let it stand for 24 h to obtain a 1 wt% sodium alginate solution. Weigh 0.5000 g of the 1 wt% sodium alginate solution multiple times. Taking to represent different degrees of gelation, when f takes 0.30, 0.20, 0.18, 0.17, 0.16, 0.15, 0.14, 0.10 respectively, add 150 μl, 100 μl, 90 μl, 85 μl, 80 μl, 75 μl, 70 μl, 50 μl of 5.048×10 -2 mol / L calcium-ethylenediaminetetraacetic acid solution respectively, and then add 200 μl of D-glucono-1,5-lactone solution and 10 μl of polystyrene probe particle suspension (diameter 0.2 μm). After stirring for 15 min, inject the mixture into a glass chamber and seal it with vacuum silicone grease. Then place the glass chamber in a metal bath at 25 °C for 24 h to allow it to fully react to form a gel.

[0093] Place the samples on a microrheometer respectively. Set the temperature of the temperature control chamber to 30 °C, focus with a 60× phase contrast oil immersion objective lens, select the probe particles in the middle layer, set the duration of the high-speed camera to 2000 frames, the frame rate to 49.65 fps, the exposure time to 0.01 s, and the pixel size to 2560 px × 2160 px. After stabilizing for 5 min, shoot the video. Change the field of view of the fluorescence microscope and stand still for 1 min until enough particles are captured.

[0094] Read the video file. First, perform image preprocessing, bring out the first frame image. Set the pixel diameter of the particles to be 14, calculate the background noise of the image using gate integration to be 300, subtract the background noise, and re-determine the pixel diameter of the particles to be 12. Locate all the particles on each frame and record their coordinate positions (i, j). Given the maximum pixel radius of particle movement as 50 according to the random walk probability, and mark which field of view it belongs to with k. Read the trajectory coordinate sequences of the particles in each field of view one by one. At this time, the total number of particles N = ∑n1 + n2 + … + n k . Calculate the mean square displacement of the particles in different ranges:

[0095]

[0096]

[0097] <Δx 2 (Δt)>| mp =∫ 所有视场所有粒子的位移 Δx 2 p(Δx)d(Δx)

[0098] Then calculate the viscoelastic spectrum and non-Gaussian factor of the gel.

[0099] Obtained the complete change process of inhomogeneity with time, space, and degree of gelation. For example, when the time interval is equal to 0.1 s, the non-Gaussian factors corresponding to different degrees of gelation f = 0.10, 0.14, 0.15, 0.16, 0.17, 0.18, 0.20, 0.30 are as follows: the non-Gaussian factor α2 of a single particle: 0.03, 0.02, 0.04, 0.2, 0.5, 1.0, 1.0, 0.8; the non-Gaussian factor α2 of a single field of view: 0.1, 0.2, 2.0, 5.2, 6.3, 10, 6.0, 5.6; the non-Gaussian factor α2 of multiple particles: 0.8, 1.5, 3.2, 5.7, 11, 70, 21, 15. It shows that the trend of inhomogeneity with the degree of gelation is to increase first, then decrease, and finally remain unchanged. At different degrees of gelation, some inhomogeneities gradually relax with time, and some remain unchanged. It shows that the degree of gelation and time have a very significant impact on inhomogeneity.

[0100] In summary, compared with the prior art, the present embodiment has the following advantages and beneficial effects:

[0101] 1) Based on the multi-field micro-rheology technology, without changing the particle concentration and ensuring that the rheological properties of the gel remain unchanged, the problems in micro-rheology such as few particle statistics and inability to calculate a sufficiently reliable non-Gaussian factor are solved. Combining technologies such as particle positioning, connection, labeling, and statistics, the trajectory coordinate sequences of particles in a sufficient number of fields of view can be statistically analyzed, and the calculated non-Gaussian factor is more accurate and reliable.

[0102] 2) Since the inhomogeneity of the gel varies with time and space, its inhomogeneity is multi-scale. The existing micro-rheology technologies can characterize a relatively small range of inhomogeneous scales and cannot completely and accurately characterize the multi-scale inhomogeneity of gels such as sodium alginate. The multi-field technology can characterize the inhomogeneity in a variety of scale ranges, with a larger characterization range and a wider range of gels applicable.

[0103] 3) Combining technologies such as particle positioning, connection, labeling, and statistics, the dynamic changes of inhomogeneity with time, space, and degree of gelation can be obtained, providing guidance for studying the gelation transition process and preparing uniform gels.

[0104] The present embodiment also provides a device for characterizing the inhomogeneity of a gel based on multi-field micro-rheology, including:

[0105] At least one processor;

[0106] At least one memory for storing at least one program;

[0107] When the at least one program is executed by the at least one processor, the at least one processor is caused to implement Figure 1 The method shown.

[0108] A device for characterizing the inhomogeneity of a gel based on multi-field micro-rheology in the present embodiment can execute a method for characterizing the inhomogeneity of a gel based on multi-field micro-rheology provided by an embodiment of the present invention, can execute any combination of implementation steps of the method embodiment, and has the corresponding functions and beneficial effects of the method.

[0109] The present application embodiment also discloses a computer program product or a computer program. The computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. The processor of the computer device can read the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, causing the computer device to execute Figure 1 The method shown.

[0110] In some alternative embodiments, the functions / operations recited in the block diagrams may not occur in the order presented in the operational illustrations. For example, depending on the functions / operations involved, two blocks shown in succession may actually be executed substantially simultaneously or the blocks may sometimes be executed in reverse order. Additionally, the embodiments presented and described in the flowcharts of the present invention are provided by way of example for the purpose of providing a more comprehensive understanding of the technology. The disclosed methods are not limited to the operations and logical flows presented herein. Alternative embodiments are contemplated in which the order of various operations is altered and in which sub-operations described as part of a larger operation are performed independently.

[0111] Moreover, although the present invention has been described in the context of functional modules, it should be understood that, unless otherwise stated to the contrary, one or more of the described functions and / or features may be integrated in a single physical device and / or software module, or one or more functions and / or features may be implemented in separate physical devices or software modules. It should also be understood that a detailed discussion of the actual implementation of each module is not necessary for an understanding of the present invention. Rather, given the attributes, functions, and internal relationships of the various functional modules in the devices disclosed herein, the actual implementation of the modules will be understood within the ordinary skill of an engineer. Accordingly, those of ordinary skill in the art can implement the present invention as set forth in the claims without undue experimentation. It should also be understood that the specific concepts disclosed are merely illustrative and not intended to limit the scope of the present invention, which is determined by the full scope of the appended claims and their equivalents.

[0112] If the described functions are implemented in the form of software functional units and sold or used as independent products, they may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present invention, in essence or the part that contributes to the prior art, or a part of such technical solution, may be embodied in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs.

[0113] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a definitional sequence of executable instructions for implementing logical functions, and can be embodied specifically in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device. As used in this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in connection with the instruction execution system, apparatus, or device.

[0114] More specific examples (a non-exhaustive list) of the computer-readable medium include the following: an electrical connection part (electronic device) having one or more wirings, a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the program can be printed, as the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation, or otherwise processing as appropriate, and then storing it in a computer memory.

[0115] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or a combination of the following techniques well-known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0116] In the foregoing description of this specification, the descriptions referring to the terms "one embodiment / example", "another embodiment / example", or "certain embodiments / examples", etc., mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0117] Although embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the claims and their equivalents.

[0118] The above has specifically described the preferred embodiments of the present invention, but the present invention is not limited to the above embodiments. Those skilled in the art can make various equivalent deformations or substitutions without violating the spirit of the present invention, and these equivalent deformations or substitutions are all included in the scope defined by the claims of this application.

Claims

1. A method for characterizing the inhomogeneity of a gel based on multi-field micro-rheology, characterized in that, It includes the following steps: Add probe particles to the gel prepolymer solution. After subjecting the gel prepolymer solution to gelation treatment, obtain a sample; Place the sample on a microrheometer, and use a high-speed camera to capture videos of the thermal motion of particles in multiple fields of view under a fluorescence microscope; Based on the videos of particle thermal motion, locate the probe particles on the sample. After connecting the probe particles, obtain the coordinate sequence of particle trajectories in each field of view. After traversing the data of each field of view, obtain all the particle trajectory data; Calculate various observables based on the particle trajectory data to characterize the inhomogeneity of the gel; The locating of the probe particles on the sample includes: Use a locating program to identify the coordinates of the probe particles in each frame of the image, record the coordinates (i, j) of the probe particles, and use the variable k for field-of-view marking; After traversing the data of each field of view, obtaining all the particle trajectory data includes: Read the coordinate sequences of particle trajectories in each field of view one by one. At this time, the total number of particles N = ∑n1 + n2 + … + n k , and calculate the mean square displacement of the particles according to the principles of statistical thermodynamics; The ranges of mean square displacement statistics are different, and the inhomogeneity scales characterized by the calculated non-Gaussian factors are different: Equation (1) represents first statistically calculating the mean square displacement of a single particle and taking the number average of the mean square displacements of all particles, which can only characterize the inhomogeneity of the medium within the trajectory of a single particle; Equation (2) represents first statistically calculating the mean square displacement of all particles in a single field of view and taking the number average of the mean square displacements between different fields of view, which characterizes the inhomogeneity of the medium within a single field of view; <Δx 2 (Δt)>| mp =∫ 所有视场所有粒子的位移 Δx 2 p(Δx)d(Δx) (3) Equation (3) represents statistically calculating the mean square displacement of all particles in all fields of view, which characterizes the inhomogeneity exceeding the scale of one field of view; where, Δx is the displacement, Δt is the time interval, N is the total number of probe particles, p(Δx) is the probability that the displacement of the probe particle is Δx, M is the total number of fields of view, sp indicates that the statistics are for single particles, sf indicates that the statistics are for single fields of view, mp indicates that the statistics are for multiple fields of view, and <> indicates taking the average of the variables within the symbol.

2. The method for characterizing the inhomogeneity of a gel based on multi-field-of-view micro-rheology according to claim 1, wherein The concentration of the probe particles in the gel prepolymer solution is between 0.00001 wt% and 0.0001 wt%.

3. A method for characterizing the inhomogeneity of a gel based on multi-field-of-view micro-rheology according to claim 1, characterized in that, The gelation treatment of the gel prepolymer solution includes: Inject the gel prepolymer solution into a glass chamber, place the glass chamber in a thermostatic metal bath, and wait for the gel prepolymer solution to completely gel; Among them, after injecting the gel prepolymer solution into the chamber, it needs to be sealed with vacuum silicone grease and placed in a 25°C metal bath for 24 h.

4. A method for characterizing the inhomogeneity of a gel based on multi-field-of-view micro-rheology according to claim 1, characterized in that The placing of the sample on the microrheometer includes: Set the working parameters of the microrheometer, where the working parameters include temperature, number of video frames, frame rate, and exposure time; In addition, it is necessary to capture videos of the thermal motion of particles under multiple fields of view, ensure that there are at least 20 particles in each field of view, and each field of view needs to be stationary for more than 1 min before shooting to ensure that the particle motion is not affected by other factors except temperature.

5. A method for characterizing the inhomogeneity of a gel based on multi-field micro-rheology according to claim 1, characterized in that, Before locating the probe particles, the following steps are also included: Perform image preprocessing on the videos of particle thermal motion, use gate integration to calculate the average background noise of the image, and subtract the average background noise to improve the signal-to-noise ratio of the image.

6. The method for characterizing the inhomogeneity of a gel based on multi-field micro-rheology according to claim 1, wherein After connecting the probe particles to obtain the coordinate sequence of particle trajectories in each field of view, it includes: Find out and connect the coordinates of the same particle in different frames according to the random walk probability to obtain the coordinate sequence of the particle trajectory in a single field of view.

7. A device for characterizing the inhomogeneity of a gel based on multi-field micro-rheology, characterized in that, It includes: At least one processor; At least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the method according to any one of claims 1-6.

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