Method of characterizing rheological properties of fluid compositions

Abstract

The invention relates to the technical field of rheology, and particularly discloses a method for representing rheological properties of a fluid composition, the method comprises the following steps: pre-treating the fluid composition under a predetermined shear condition, the shear condition comprising M-dimensional controllable variables, and M being an integer greater than or equal to 2; performing a rheological test on the sheared fluid composition under a predetermined test condition to obtain rheological index data; obtaining an M-dimensional data matrix formed by at least four pieces of rheological index data to characterize the rheological properties of the fluid composition; wherein each piece of rheological index data corresponds to one shearing condition, one-dimensional N pieces of data in the M-dimensional data matrix correspond to N different shearing conditions, and the N different shearing conditions are formed by combining N different variable values of one-dimensional controllable variables and one variable value of each of other-dimensional controllable variables. According to the technical scheme, tiny differences in the fluid composition can be characterized.

Description

Technical Field

[0001] This disclosure generally relates to the field of rheology, and more specifically, to a method for characterizing the rheological properties of fluid compositions. Background Technology

[0002] Rheology is the study of the flow and deformation of matter. Thixotropy is a specific rheological behavior, referring to the property of a material to exhibit a decrease in viscosity over time under shear stress, followed by a gradual recovery of viscosity over time after the shear stress is removed. Modern rheometers and viscometers are essential tools for measuring the rheological properties of materials. These instruments can apply controlled shear rates or shear stresses to sample materials and measure their response, providing valuable data on viscosity, elasticity, and viscoelasticity. Advanced rheometers typically include software that allows for precise control of shear conditions and the collection of comprehensive datasets. This is crucial for understanding the behavior of sample materials under different application conditions.

[0003] For fluid compositions, such as liquid personal care products and food products, the study of rheological properties plays a crucial role in their development and optimization. For example, high-end creams and lotions can be easily applied during rubbing or brushing and return to a more viscous state after application. Understanding and controlling these properties allows formulators to create products that meet specific performance standards, such as durability, smooth application, smudge resistance, or flowability.

[0004] The inventors found that current thixotropic / rheological detection methods have limited capabilities in characterizing some complex fluid compositions, failing to adequately distinguish between different fluid compositions and failing to obtain meaningful rheological data to interpret the rheological properties of these fluid compositions. Summary of the Invention

[0005] To address the problems in the related art, embodiments of this disclosure provide a method for characterizing the rheological properties of a fluid composition.

[0006] According to one aspect of the present invention, an embodiment of this disclosure provides a method for characterizing the rheological properties of a fluid composition, comprising:

[0007] The fluid composition is pretreated under predetermined shear conditions, wherein the shear conditions include M controllable variables, where M is an integer greater than or equal to 2;

[0008] For the fluid composition after shearing, rheological tests are performed under predetermined test conditions to obtain rheological index data;

[0009] An M-dimensional data matrix formed by acquiring at least four rheological index data is used to characterize the rheological properties of the fluid composition;

[0010] Each rheological index data corresponds to a shearing condition. The one-dimensional N data points in the M-dimensional data matrix correspond to N different shearing conditions. The N different shearing conditions are formed by combining N different variable values ​​of the one-dimensional controllable variable and one variable value of each of the other dimension controllable variables.

[0011] In one possible implementation, the N different variable values ​​of a controllable variable in the N different shearing conditions are sorted in descending or ascending order, and the rheological index data in the M-dimensional data matrix are sorted in the order of the corresponding controllable variables.

[0012] In one possible implementation, the shearing conditions include at least two of the following controllable variables: temperature, humidity, shear rate, shear duration, water evaporation parameter, salinity, magnetic field parameter, electric field parameter, tensile displacement, tensile force, pressure, radial oscillation shear parameter, axial oscillation shear parameter, neutron radiation parameter, X-ray radiation parameter, ultraviolet radiation parameter, visible light radiation parameter, and amount of chemical reagent added.

[0013] In one possible implementation, when the fluid composition is a personal care product, the shear conditions include shear rate and shear duration.

[0014] In one possible implementation, when the fluid composition is a food-grade fluid composition, the shear conditions include electric field parameters and shear rate.

[0015] In one possible implementation, when the fluid composition is a personal care product containing a material with photocatalytic properties, the shear conditions also include ultraviolet radiation and temperature.

[0016] In one possible implementation, when the fluid composition is a personal care product to be used above a predetermined temperature, the shear condition further includes temperature.

[0017] In one possible implementation, when the fluid composition is a fluid composition from the oil and gas sector, the shear conditions include temperature, pressure, and radiation parameters.

[0018] In one possible implementation, when the fluid composition is a personal care product, the shear conditions include shear duration, shear rate, and electrolyte concentration.

[0019] In one possible implementation, the step of performing rheological testing on the sheared fluid composition under predetermined test conditions to obtain rheological index data includes:

[0020] Timing begins after the fluid composition has been pretreated under predetermined shear conditions. After a predetermined duration, rheological tests are performed under predetermined test conditions to obtain rheological index data.

[0021] In one possible implementation, the predetermined duration ranges from 0 to 10 seconds.

[0022] In one possible implementation, the step of performing rheological testing under predetermined test conditions to obtain rheological index data includes:

[0023] The fluid composition was sheared at a preset shear rate for a preset shear duration, and the rheological parameters were measured.

[0024] In one possible implementation, the preset shear rate ranges from 0.001 to 0.11 / s, and the preset shear duration ranges from 300 to 1800 s.

[0025] In one possible implementation, the measurement yields rheological index data, including:

[0026] The average viscosity measured during a portion of the preset shear duration is determined as the rheological index data, where the portion of the time begins at a predetermined moment within the preset shear duration and ends at the last moment within the preset shear duration.

[0027] In one possible implementation, the method further includes:

[0028] Based on the correspondence between the data values ​​and color values ​​of the predetermined rheological index data, the M-dimensional data matrix is ​​converted into an M-dimensional color grid;

[0029] The M-dimensional color grid is interpolated using a predetermined interpolation method to convert the M-dimensional color grid into an M-dimensional pseudo-color image.

[0030] In one possible implementation, the method further includes:

[0031] Calculate the texture conversion index T using the following formula:

[0032] T = 1 - (S) min / S max );

[0033] Wherein, the S min S is the minimum value among the at least four rheological index data. max It is the maximum value among the at least four rheological index data.

[0034] In one possible implementation, the method further includes:

[0035] Calculate the texture conversion index T using the following formula:

[0036] T = 1 - (S) 结束 / S 开始 );

[0037] Wherein, the S 开始 For the rheological index data obtained from the test under the first shear condition, the S 结束 For the rheological index data obtained under the last shearing condition, the variable values ​​of the M-dimensional controllable variables in the first shearing condition are all the minimum values ​​among the variable values ​​of the controllable variables in this dimension, and the variable values ​​of the M-dimensional controllable variables in the last shearing condition are all the maximum values ​​among the variable values ​​of the controllable variables in this dimension.

[0038] In one possible implementation, when M is greater than or equal to 3, the M-dimensional pseudo-color image includes one or more three-dimensional pseudo-color images, and the method further includes:

[0039] For a given 3D color image, determine the corresponding 3D controllable variable of the 3D pseudo-color image;

[0040] Select any two controllable variables from the three-dimensional controllable variables;

[0041] Extract the two-dimensional pseudo-color images corresponding to the two selected controllable variables from the three-dimensional color image.

[0042] In one possible implementation, the predetermined interpolation method includes any one of the following: bicubic, bilinear, spline, nearest neighbor, Kriging, polynomial, centroid, radial Bass function, thin plate spline, piecewise linear, Fourier, etc.

[0043] According to the technical solution provided in this disclosure, the shearing process of the fluid composition can be simulated by setting variable values ​​of two or more controllable variables. After simulating shearing, rheological tests are performed under predetermined test conditions to obtain rheological index data. In this way, index data that can characterize the structural changes of the material under shear and the immediate structural recovery after shearing can be obtained. By conducting multi-dimensional shear condition test analysis on the fluid composition, the rich textural transformations exhibited by the fluid composition during use can be fully described. The rheological index data measured using this method can capture the subtle textural changes of the fluid composition under different usage conditions, and can also effectively distinguish between different fluid compositions with slight differences in rheological properties.

[0044] Furthermore, the data matrix formed by the rheological index data can be visualized, allowing for a more intuitive observation of the texture transformation process of the fluid composition during use.

[0045] The texture conversion index can also be calculated to make comparisons between fluid compositions.

[0046] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0047] Other features, objects, and advantages of this disclosure will become more apparent from the following detailed description of non-limiting embodiments, taken in conjunction with the accompanying drawings. In the drawings:

[0048] Figure 1 A flowchart illustrating a method for characterizing the rheological properties of a fluid composition according to an embodiment of this disclosure is shown.

[0049] Figure 2A A schematic diagram of the raw data measured by the rheometer provided in Example 1 of this disclosure is shown;

[0050] Figure 2B This illustration shows a schematic diagram of the visualization process of rheological index data provided in Example 1 of this disclosure;

[0051] Figure 3 This illustration shows a schematic diagram of the visualization process of rheological index data provided in Example 2 of this disclosure;

[0052] Figure 4A A schematic diagram of the raw data measured by the rheometer provided in Example 3 of this disclosure is shown;

[0053] Figure 4B This illustration shows a schematic diagram of the visualization process of rheological index data provided in Example 3 of this disclosure;

[0054] Figure 5A A schematic diagram of the raw data measured by the rheometer provided in Example 4 of this disclosure is shown;

[0055] Figure 5B This illustration shows a schematic diagram of the visualization process of rheological index data provided in Example 4 of this disclosure;

[0056] Figure 6A A schematic diagram of the color grid for rheological index data conversion provided in Example 5 of this disclosure is shown;

[0057] Figure 6B A schematic diagram of the stacked three-dimensional color grid provided in Example 5 of this disclosure is shown;

[0058] Figure 7A This diagram illustrates data from a test method provided by the prior art.

[0059] Figure 7B This diagram illustrates data from a test method provided by the prior art.

[0060] Figure 8 This diagram illustrates data from a test method provided by the prior art.

[0061] Figure 9A A schematic diagram of the raw data measured by the rheometer provided in Example 6 of this disclosure is shown;

[0062] Figure 9B A schematic diagram illustrating the visualization process of rheological index data provided in Example 6 of this disclosure is shown. Detailed Implementation

[0063] In the following, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings to enable those skilled in the art to readily implement them. Furthermore, for clarity, portions unrelated to the description of exemplary embodiments have been omitted from the drawings.

[0064] In this disclosure, it should be understood that terms such as “comprising” or “having” are intended to indicate the presence of features, figures, steps, behaviors, components, parts or combinations thereof disclosed in this specification, and are not intended to exclude the possibility of the presence or addition of one or more other features, figures, steps, behaviors, components, parts or combinations thereof.

[0065] It should also be noted that, unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other. This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0066] Definitions:

[0067] Fluid compositions: including non-Newtonian fluid compositions and Newtonian fluid compositions. Fluids in which the shear stress at any point is linearly related to the shear deformation rate are called Newtonian fluids. Examples include water, most pure liquids such as alcohol, light oils, and low-molecular-weight compound solutions. Fluids that do not meet the criteria for Newtonian fluids are called non-Newtonian fluids. Examples include petroleum, toothpaste, lotion, face cream, shampoo, concentrated solutions and suspensions of polymers.

[0068] Personal care products: These include various care products designed to beautify, preserve, or alter an individual's appearance. They may include facial care products such as facial cleansers, makeup removers, lotions, creams, cosmetics, makeup, loose powder, etc.; body care products such as hand soap, shampoo, sunscreen, hair removal cream, body lotion, hand cream, antifreeze cream, etc.; and oral care products such as toothpaste, oral hygiene solutions, etc.

[0069] Shear conditions: refer to the shear conditions when a fluid composition is pretreated before rheological testing. These shear conditions include at least two controllable variables, which can be any relevant variables that can cause a change in the texture of the fluid composition. For example, shear duration, shear rate, shear temperature, shear strain, radiation parameters, ambient pressure, tensile force, changes in electrolyte concentration, magnetic field strength, electric field strength, etc.

[0070] Figure 1 A flowchart illustrating a method for characterizing the rheological properties of a fluid composition according to an embodiment of this disclosure is shown. Figure 1 As shown, the method includes the following steps S101-S103:

[0071] In step S101, the fluid composition is pretreated under predetermined shear conditions, wherein the shear conditions include M controllable variables, where M is an integer greater than or equal to 2;

[0072] In step S102, for the sheared fluid composition, a rheological test is performed under predetermined test conditions to obtain rheological index data;

[0073] In step S103, an M-dimensional data matrix is ​​obtained to form at least four rheological index data to characterize the rheological properties of the fluid composition.

[0074] In one possible implementation, the characterization method provided in this embodiment is mainly used to characterize the rheological properties of a fluid composition, which can be a fluid composition in various fields such as personal care products, oil and gas, and food, and can be a liquid, colloid, semi-solid, or other non-solid composition.

[0075] In one possible implementation, the controllable variable in the shear condition can be any relevant variable that can cause a textural change in the fluid composition. The shear condition includes M-dimensional controllable variables; different values ​​of these controllable variables can constitute different shear conditions. The fluid composition can be pretreated using a rheometer under a predetermined shear condition, and then immediately subjected to rheological testing under predetermined test conditions to obtain rheological index data measured by the rheometer, thus characterizing the material properties of the fluid composition due to the applied shear impact. By setting predetermined shear conditions to simulate the use of the fluid composition, the rheological index data obtained from subsequent rheological tests can characterize the textural changes of the fluid composition during use and its immediate textural recovery after use. This rheological index data can be any data capable of characterizing the structural changes of the fluid composition under shear and the structural recovery after shear removal.

[0076] In one possible implementation, an M-dimensional data matrix formed by at least four rheological index data can be used to characterize the rheological properties of the fluid composition. Each shear condition corresponds to a rheological index data obtained from the test. The one-dimensional N data in the M-dimensional data matrix correspond to N different shear conditions. The N different shear conditions are formed by combining N different variable values ​​of one-dimensional controllable variable and one variable value of each of the other dimension controllable variables.

[0077] For example, the shearing condition can be an M=2 dimensional controllable variable. Let these two controllable variables be denoted as controllable variable 1 and controllable variable 2. A variable value of controllable variable 1 and a variable value of controllable variable 2 can form a shearing condition. Assuming that controllable variable 1 has a different variable value and controllable variable 2 has b different variable values ​​(a and b are both integers greater than or equal to 2), then a×b shearing conditions can be formed. By iterating through these a×b shearing conditions, a×b rheological index data can be obtained. These a×b rheological index data can form an M=2 dimensional data matrix. This M=2 dimensional data matrix is ​​a matrix of size a×b. The a×b M=2 dimensional data matrix can be shown in Table 1 below:

[0078] y1 yb x1 S1 ...... Sb ...... ...... ...... ...... Xa Sb(a-1)+1 ...... Sa×b

[0079] Table 1

[0080] As shown in Table 1 above, controllable variable 1 has a different variable values ​​x1...xa, and controllable variable 2 has b different variable values ​​y1...yb. The different combinations of variable values ​​of these two dimensions of controllable variables can obtain a×b different shearing conditions as shown in Table 1. Following the order in Table 1, after shearing the fluid composition under shearing conditions x1 and y1, a rheological index data S1 can be obtained by performing a rheological test on the sheared fluid composition under predetermined conditions. Continuing to shear the fluid composition under shearing conditions x1 and y2, a rheological index data S2 can be obtained by performing a rheological test on the sheared fluid composition under predetermined conditions. In this way, the rheological index data S1...Sb in the first row of Table 1 are obtained. Then, the shearing conditions are changed to obtain the rheological index data in the second row of Table 1. By traversing row by row, a×b rheological index data S1...Sa×b can be obtained, which are presented as a two-dimensional data matrix as shown in Table 1. In this two-dimensional data matrix, a column or a row of data is a one-dimensional data item. For the first column of one-dimensional data, there are N = a shearing conditions corresponding to the N = a data points in this one-dimensional data. These N = a shearing conditions are formed by combining N = a different variable values ​​x1...xa of controllable variable 1 and a variable value y1 of controllable variable 2. For the first row of one-dimensional data, there are N = b shearing conditions corresponding to the N = b data points in this one-dimensional data. These N = b shearing conditions are formed by combining N = b different variable values ​​y1...yb of controllable variable 2 and a variable value x1 of controllable variable 1.

[0081] Alternatively, for example, the shearing condition could be M = 3 controllable variables. Let these three controllable variables be denoted as controllable variable 1, controllable variable 2, and controllable variable 3. A value of controllable variable 1, a value of controllable variable 2, and a value of controllable variable 3 can form a shearing condition. Assuming controllable variable 1 has e different values, controllable variable 2 has d different values, and controllable variable 3 has f different values ​​(e, d, and f are all integers greater than or equal to 2), these can be combined to form... Given e×d×f shear conditions, after shearing the fluid composition under one of these conditions, a rheological index can be obtained by performing rheological testing using a rheometer. By iterating through these e×d×f shear conditions, e×d×f rheological index data can be obtained. These e×d×f rheological index data can form an M=3-dimensional data matrix. This M=3-dimensional data matrix is ​​a three-dimensional matrix of size e×d×f. The M=3-dimensional data matrix of size e×d×f can be shown in Table 2 below:

[0082]

[0083] Table 2

[0084] As shown in Table 2 above, controllable variable 1 has e different variable values ​​x1……xe, controllable variable 2 has d different variable values ​​y1……yd, and controllable variable 3 has f different variable values ​​z1……zf. The different combinations of variable values ​​of these three dimensions of controllable variables can obtain e×d×f different shearing conditions as shown in Table 2, and then e×d×f rheological index data S1……Se×d×f can be tested and obtained, which are presented as the three-dimensional data matrix shown in Table 2. A column of data in Table 2 represents a one-dimensional data item in the three-dimensional data matrix. For the first column of one-dimensional data, there are N = e shearing conditions corresponding to the N = e data points. These N = e shearing conditions are formed by combining N = e different variable values ​​x1...xe of controllable variable 1 with a variable value y1 of controllable variable 2 and a variable value z1 of controllable variable 3. In a row of data in Table 2, the data corresponding to the same variable value of controllable variable 3 represents a one-dimensional data item in the three-dimensional data matrix. For the one-dimensional data (S1...Sd) corresponding to z1 in the first row of Table 2, there are N = d shearing conditions corresponding to the N = d data points. These N = d shearing conditions include combinations of a variable value x1 of controllable variable 1 and a variable value z1 of controllable variable 3 with N = d different variable values ​​y1...yd of controllable variable 2.

[0085] Of course, in addition to the cases of M=2 or M=3 in the above examples, the number of controllable variables M in the shear condition can also be 4, 5, 6, etc. When M is 4, a four-dimensional data matrix can be obtained to characterize the rheological properties of the fluid composition. This four-dimensional data matrix can be represented by multiple three-dimensional data matrices, which will not be illustrated here.

[0086] In one possible implementation, in order to better present the data, for the N different shearing conditions corresponding to the N data in the M-dimensional data matrix, the N different variable values ​​of a controllable variable in the N different shearing conditions can be sorted in descending or ascending order. At the same time, the rheological index data in the M-dimensional data matrix are sorted in the order of the corresponding controllable variables.

[0087] Taking Table 1 above as an example, controllable variable 1 corresponds to *a* different variable values, from smallest to largest (x1…xa), and controllable variable 2 corresponds to *b* different variable values, from smallest to largest (y1…yb). Thus, the order of the rheological index data in the resulting two-dimensional data matrix is ​​shown in Table 1. From left to right, the controllable variable 2 corresponding to the rheological index data gradually increases, and from top to bottom, the controllable variable 1 corresponding to the rheological index data gradually increases. This sorted M-dimensional data matrix allows researchers to more clearly understand the changes in the rheological properties of the fluid composition under the gradual changes of the corresponding controllable variables.

[0088] In one possible implementation, the shearing conditions include at least two of the following parameters: temperature, humidity, shear rate, shear duration, water evaporation parameters, salinity, magnetic field parameters (e.g., magnetic field strength), electric field parameters (e.g., electric field strength), tensile displacement, tensile force, pressure, radial oscillation shear parameters (e.g., oscillation period, amplitude), axial oscillation shear parameters, neutron radiation parameters (e.g., radiation intensity), X-ray radiation parameters, ultraviolet radiation parameters, visible light radiation parameters, and the amount of chemical reagents added (e.g., electrolyte concentration).

[0089] In this embodiment, based on the material properties of the fluid composition or the application protocol of the fluid composition, two or more parameters can be selected from the above parameters as two or more dimensions to map the rheological properties of the fluid composition when it is used.

[0090] Of course, the control variables in this shearing condition are not limited to the parameters mentioned above, and will not be listed one by one here.

[0091] In one possible implementation, the shearing condition may include controllable variables in two dimensions of the parameters described above.

[0092] In one possible implementation, when the fluid composition is a personal care product, the two-dimensional controllable variables are shear rate and shear duration.

[0093] Here, the controllable variables of shear rate and shear duration are the most typical adjustment parameters affecting the structural transformation of personal care products. Therefore, by controlling the changes in the values ​​of these two controllable variables, the usage behavior of ordinary users can be simulated. For example, by applying different shear rates and different shear durations, the consumer's application action can be imitated. Thus, after shearing the fluid composition under shear conditions, the rheological index data obtained by rheological testing using a rheometer can well characterize the structural changes of the personal care product fluid composition during use and its immediate structural recovery after use. In the data matrix formed by the shear conditions created by these two controllable variables, as the values ​​of these two controllable variables increase from left to right and from top to bottom, respectively, the amount of shear experienced by the personal care product increases with the shearing motion of the rheometer.

[0094] In one possible implementation, when the fluid composition is a food-grade fluid composition, the two-dimensional controllable variables are the electric field parameter and the shear rate.

[0095] Here, research has revealed that electrorheology (ER) can improve food processing. For example, ER technology can be used to process healthier and more delicious chocolate. By combining ER with high shear rates, the processability of chocolate can be explored under conditions close to maximum random blockage density, overcoming historical limitations in low-fat chocolate production. The inventors discovered that the performance of chocolate samples can be characterized by testing rheological parameters such as viscosity after shearing under different shear rates and electric field combinations. This allows for the construction of viscosity profiles for chocolate processed under these conditions, leading to the production of more delicious chocolate. Since these tests can be easily performed using a rheometer, there is no longer a need to build expensive equipment for experimental production purposes.

[0096] In one possible implementation, when the fluid composition is a personal care product containing a material with photocatalytic properties, the shear conditions may include ultraviolet radiation and temperature in addition to shear rate and shear duration.

[0097] In the personal care industry, some products containing materials with photocatalytic properties can degrade upon exposure to UV (ultraviolet) light. For example, TiO2 (titanium dioxide) is commonly used in personal care products for skin tone correction or sun protection; however, TiO2 is a photocatalyst when exposed to UV light, including UV rays from sunlight. TiO2 can absorb UV light and generate electron-hole pairs. These electrons and holes can migrate to the surface of TiO2 particles, where they can react with water and oxygen to form reactive oxygen species (ROS), such as hydroxyl radicals and superoxide anions. These ROS are highly reactive and can cause oxidative damage. While generally considered safe if properly formulated, it is advisable for personal care formulators to test the interaction between formulations containing photocatalytic materials and UV exposure and high temperatures to simulate sun exposure when personal care products are applied to the skin. During testing, shear conditions constructed with varying shear rates and durations, UV doses, and temperatures can be applied to the skin surface model. The modulus of the skin surface model is monitored and extracted as a rheological index, as viscosity cannot be measured for non-flowing samples. However, if only the formulation sample is tested instead of the skin surface model, viscosity can be measured as a rheological index, as in other examples. This method can be used to evaluate the safety and stability of new raw materials containing photocatalytically active materials or new sunscreen personal care products.

[0098] In one possible implementation, when the fluid composition is a personal care product to be used above a predetermined temperature, the shear conditions are shear rate and temperature.

[0099] Here, some personal care products are not sensitive to shear duration, but their application involves heating processes. For example, shampoos are typically used in the high-temperature environment of a shower, and UV protection products are typically used under sunlight exposure. In this case, shear rate and temperature can be chosen as two dimensions to map the rheological properties of these personal care products that need to be used above a predetermined temperature. Of course, in other possible implementations, some personal care products are sensitive to shear duration and also involve heating processes during use. In this case, the shear condition can also be shear rate, shear duration, and temperature.

[0100] In one possible implementation, the shearing condition may include parameters from the three dimensions mentioned above.

[0101] In one possible implementation, when the fluid composition is a fluid composition from the oil and gas sector, the three-dimensional controllable variables are temperature, pressure, and radiation parameters.

[0102] In the field of enhanced oil recovery (EOR), polymer and / or surfactant injection is commonly used to alter the environment within oil-bearing rocks / sand layers in an effort to develop polymer / surfactant mixtures resistant to subsurface conditions. Typically, in deep reservoirs, temperature and pressure increase with depth, and radiation levels can increase due to the presence of various naturally occurring radioactive materials (NORMs) in the crust, some of the most common including uranium, thorium, and their decay products such as radium and radon. Temperature, pressure, and radiation can adversely affect the performance of polymers / surfactants. Therefore, using the methods provided in this disclosure, the effects of different temperatures, pressures, and radiation can be studied in a controlled laboratory environment to understand the rheological behavior of polymer / surfactant mixtures under subsurface conditions, without the need for costly field testing in actual production environments.

[0103] In one possible implementation, when the fluid composition is a personal care product, the three-dimensional controllable variables are shear duration, shear rate, and electrolyte concentration.

[0104] Here, personal care products mix with electrolytes such as sweat from the user's skin during use, so shear rate, shear duration, and electrolyte concentration can be selected as three dimensions to map the rheological properties of personal care products during use.

[0105] In one possible implementation, the step of performing rheological testing on the sheared fluid composition under predetermined test conditions to obtain rheological index data includes:

[0106] Timing begins after the fluid composition has been pretreated under predetermined shear conditions. After a predetermined duration, rheological tests are performed under predetermined test conditions to obtain rheological index data.

[0107] In this embodiment, since the test provided by this disclosure is mainly to identify the properties of the fluid composition immediately after the shear deformation step, the timing can start from the end of the pretreatment of the fluid composition under predetermined shear conditions, and the rheological test needs to be performed immediately after a very short predetermined time, the value of which ranges from 0 to 10 seconds.

[0108] In one possible implementation, the step of performing rheological testing under predetermined test conditions to obtain rheological index data includes:

[0109] The fluid composition was sheared at a preset shear rate for a preset shear duration, and the rheological parameters were measured.

[0110] In this embodiment, the preset shear rate during rheological testing needs to be very low to ensure that the fluid composition can complete an instantaneous recovery. Its value ranges from 0.001 to 0.11 / s. The preset shear duration needs to allow the fluid composition to complete the instantaneous recovery and reach the measurement platform. After the fluid composition reaches the measurement platform, the rheological properties of the fluid composition to be measured have reached a steady state. The value range of the preset shear duration is 300-1800s.

[0111] In one possible implementation, the measurement yields rheological index data, including:

[0112] The average viscosity measured during a portion of the preset shear duration is determined as the rheological index data, where the portion of the time begins at a predetermined moment within the preset shear duration and ends at the last moment within the preset shear duration.

[0113] In this embodiment, rheological testing is used to generate a rheological index data to represent the properties of the fluid composition, the final shear viscosity, and the final yield stress. The rheological index data can be selected based on direct observation or by model fitting. Preferably, the rheological index data can be viscosity. In other embodiments, if viscosity cannot be tested, modulus (such as shear modulus, Young's modulus, compression modulus) can be used as the rheological index data.

[0114] In this embodiment, during rheological testing, the fluid composition can be sheared at a preset shear rate for a preset shear duration, and the viscosity of the fluid composition within the preset shear duration can be monitored. The average viscosity for a portion of the preset shear duration is used as the measured rheological index data. This portion of the time starts from a predetermined moment within the preset shear duration and ends at the last moment within the preset shear duration. For example, the average viscosity from the middle moment within the preset shear duration to the last moment within the preset shear duration, i.e., the latter half of the preset shear duration, can be used as the measured rheological index data.

[0115] In one possible implementation, the method further includes:

[0116] Based on the correspondence between the data values ​​and color values ​​of the predetermined rheological index data, the M-dimensional data matrix is ​​converted into an M-dimensional color grid;

[0117] The M-dimensional color grid is interpolated using an interpolation method to convert it into an M-dimensional pseudo-color image.

[0118] In this embodiment, in order to see the test results more intuitively, the texture transformation represented by the M-dimensional data matrix can be visualized. Since the M-dimensional data matrix is ​​a two-dimensional or multi-dimensional matrix containing at least four rheological index data, it is usually not feasible to assign values ​​to the texture transformation based on numerical comparison when visualizing the M-dimensional data matrix. Moreover, the texture transformation is based on the change of the M-dimensional controllable variables. Therefore, a pseudo-color image can be used to better visualize the texture transformation process.

[0119] In this implementation, when visualizing the M-dimensional data matrix, the correspondence between the data values ​​and color values ​​of the rheological index data can be defined first. For example, the data range of the rheological index data corresponding to color value 1 can be defined as (S... 11 S 12 The data range of the rheological index data corresponding to color value 2 is (S 12 S 13Alternatively, color scales can be defined, using the colors at both ends of the scale to represent the maximum and minimum values ​​of the rheological index data. The defined color value range corresponds to the entire data range of the rheological index data, which can exceed or include the range of rheological index data values ​​in the aforementioned M-dimensional data matrix. By querying the correspondence between the data values ​​and color values ​​of the predetermined rheological index data, the color value corresponding to each rheological index data in the M-dimensional data matrix can be determined. The M-dimensional data matrix is ​​then converted into an M-dimensional color grid, where the color value of each color grid represents a rheological index data. Then, by using an interpolation method to interpolate the M-dimensional color grid, it can be converted into an M-dimensional pseudo-color image.

[0120] In this embodiment, after converting the data in the M-dimensional data matrix into an M-dimensional pseudo-color image, the M-dimensional pseudo-color image can be displayed to consumers. For example, the M-dimensional pseudo-color image corresponding to the product can be displayed in the relevant product introduction section of the product website or shopping platform so that consumers can understand the specific details of the product.

[0121] In one possible implementation, the above-described interpolation method may include any one of the following: bicubic, bilinear, spline, nearest neighbor, Kriging, polynomial, centroid, radial Bass function, thin plate spline, piecewise linear, Fourier, etc.

[0122] This embodiment can convert an M-dimensional data matrix into an M-dimensional pseudo-color image, thus simplifying complex M-dimensional rheological index data into a single M-dimensional pseudo-color image, making it easy to identify the texture transformation process of the fluid composition during use.

[0123] In one possible implementation, when M is greater than or equal to 3, the M-dimensional pseudo-color image includes one or more three-dimensional pseudo-color images, and the method further includes:

[0124] For a given 3D color image, determine the corresponding 3D controllable variable of the 3D pseudo-color image;

[0125] Select any two controllable variables from the three-dimensional controllable variables;

[0126] Extract the two-dimensional pseudo-color images corresponding to the two selected controllable variables from the three-dimensional color image.

[0127] In this implementation, when M equals 3, a third dimension can be added to the two-dimensional pseudo-color image using a stacking technique to obtain a three-dimensional pseudo-color image. When M is greater than or equal to 4, two or more three-dimensional pseudo-color images can be used to represent a four-dimensional data matrix.

[0128] In this implementation, assuming M=3, a three-dimensional color image is obtained. The three-dimensional controllable variables corresponding to this three-dimensional pseudo-color image are determined to be controllable variable 1, controllable variable 2, and controllable variable 3. Any two controllable variables, such as controllable variable 1 and controllable variable 2, are selected from these three-dimensional controllable variables. Two-dimensional pseudo-color images corresponding to these two controllable variables (controllable variable 1 and controllable variable 2) can be extracted from the three two-dimensional pseudo-color images of the three-dimensional color image. Thus, even though the combination of these two controllable variables is not specifically tested during the data generation stage, the two-dimensional pseudo-color images corresponding to these two controllable variables can still be obtained from the high-dimensional color image, achieving compatibility between high-dimensional testing and two-dimensional testing.

[0129] In one possible implementation, the method further includes:

[0130] Calculate the texture conversion index T using the following formula:

[0131] T = 1 - (S) min / S max );

[0132] Wherein, the S min S is the minimum value among the at least four rheological index data. max It is the maximum value among the at least four rheological index data.

[0133] In this implementation, in some scenarios, especially in production environments, dozens of samples can be generated, resulting in pseudo-color images corresponding to these samples. This situation requires a more refined metric to provide a comparison of these transformed pseudo-color images. Therefore, this implementation proposes a new parameter to further simplify the changes in the pseudo-color image to a single parameter, namely the texture transformation index T.

[0134] In this embodiment, T = 1 - (S) min / S max The texture transformation index T represents the reduction in rheological index data from the start of the first shear condition to the end of the last shear condition during the analytical testing process. Specifically, when using shear rate and shear duration as shear conditions, T can represent the logical structure change resulting from the shear energy input during personal care product application. Through calculation, the parameter T can be used to represent the degree of texture change, accompanied by a pseudo-color plot.

[0135] In other embodiments, the texture transformation index T can also be calculated using the following formula: T = 1 - (S 结束 / S 初始 ), where S 初始 It is the rheological index data obtained from the test under the first shear condition (i.e., the maximum value among at least four rheological index data), S 结束It is the rheological index data obtained under the last shearing condition (the minimum value among at least four rheological index data). In the first shearing condition, the variable values ​​of the M-dimensional controllable variables are all the minimum values ​​among the variable values ​​of the controllable variables in this dimension. As the test proceeds, the variable values ​​of the M-dimensional controllable variables gradually increase. In the last shearing condition, the variable values ​​of the M-dimensional controllable variables are all the maximum values ​​among the variable values ​​of the controllable variables in this dimension.

[0136] In other possible implementations, when M is greater than or equal to 3, the number of dimensions used in calculating T can be reduced. For example, any two controllable variables in the multidimensional data can be selected, and the rheological index data corresponding to all shear conditions with changes in the variable values ​​of the controllable variables in the selected two dimensions and fixed variable values ​​in the other dimensions can be obtained. Then, T = 1 - (S) can be calculated. min / S max At this time, S min S is the minimum value among the rheological index data corresponding to all shear conditions. max This is the maximum value among the rheological index data corresponding to all shear conditions.

[0137] The method for characterizing the rheological properties of fluid compositions disclosed herein can effectively characterize the rich textural changes exhibited by the fluid composition during use, effectively capture the subtle textural differences of the fluid composition under different usage conditions, and distinguish the textural differences between different fluid compositions. In contrast, traditional methods cannot effectively characterize many fluid compositions. Several examples and comparative examples are used to illustrate this below.

[0138] Example 1:

[0139] The fluid composition to be tested is personal care product 1. The shear conditions include two-dimensional controllable variables: shear duration and shear rate. Each dimension of the controllable variable has three different values. Under three different combinations of shear rates and three different shear durations, a total of 3×3 = 9 different shear histories were experienced, ultimately generating a two-dimensional 3×3 data matrix. Bicubic interpolation was used for visualization. In this example, the two-dimensional controllable variables are controlled to simulate the behavior of a typical user. The user's motion of applying the personal care product is simulated by applying different shear rates multiplied by different shear durations.

[0140] Here, three different shear rates were used: 201 / s, 2001 / s, and 20001 / s; three different shear durations were used: 10s, 30s, and 60s. The specific test procedure is as follows:

[0141] In the first step, a shearing step is performed, applying a first shear rate of 20 L / s for 10 seconds. Then, a rheological testing step is performed, measuring the shear stress of personal care product 1 at a shear rate of 0.1 L / s for 600 seconds. Next, a shearing step is performed again, applying a shear rate of 20 L / s for 30 seconds, followed by another rheological testing step measuring the shear stress of product 1 at a shear rate of 0.1 L / s for 600 seconds. Finally, a shearing step is performed again, applying a shear rate of 20 L / s for 60 seconds, followed by another rheological testing step measuring the shear stress at a rate of 0.1 L / s for 600 seconds. During each shearing step (20 L / s), viscosity is not used for analysis, and shear stress is collected in each rheological testing step. Thus, viscosity is calculated from the shear stress collected in the measurement steps. In this example, the average viscosity value of the last 300 seconds of each rheological testing step can be used as rheological index data to represent the yield strength of personal care product 1 after shearing. The second and third steps follow the same method as the first step, except that the shearing rate during the shearing step is increased to the second shearing rate of 2001 / s and the third shearing rate of 20001 / s, respectively.

[0142] The raw data measured by the rheometer during the above tests are as follows: Figure 2A As shown, Figure 2A The horizontal axis represents time, and the vertical axis represents viscosity. Blue data represents viscosity measured in the first step at a shear rate of 201 L / s for shearing times of 10 s, 30 s, and 60 s. Green data represents viscosity measured in the second step at a shear rate of 2001 L / s for shearing times of 10 s, 30 s, and 60 s. Red data represents viscosity measured in the second step at a shear rate of 20001 L / s for shearing times of 10 s, 30 s, and 60 s. Based on this, the annual average value of the rheological index data after 300 s following each rheological test step can be calculated, resulting in a 3×3 data matrix. This 3×3 data matrix is ​​a direct result of rheological testing under two-dimensional controllable variables; therefore, this 3×3 two-dimensional data matrix can be listed in the following table:

[0143] 201 / s 2001 / s 20001 / s 10s 294 251 201 30s 281 206 147 60s 245 173 78

[0144] Table 3

[0145] When visualizing the above 2D data matrix, a color scale of divergence type is defined: dark red represents the maximum viscosity of 500 cP, dark blue represents the minimum viscosity of 0 cP, and white represents the average value of 250 cP. Figure 2B As shown, color stops are displayed on the right side of the graph. The data matrix can be converted to... Figure 2BThe color grid shown in the middle left image is transformed by performing bicubic interpolation on the original data in the data matrix. Figure 2B The pseudo-color image shown in the middle right figure.

[0146] Simultaneously, the texture transformation index T = 1 - (S) corresponding to this pseudo-color image was calculated. min / S max ) = 1 - (78 / 294) = 73%.

[0147] During the testing process, the parameters of the transition and degree of change from high viscosity to low viscosity of personal care product 1 were consistent with the texture assessment of trained experts. Thus, the viscosity of the test can well capture the subtle changes in the rheological properties of personal care product 1 during different user experiences.

[0148] It's important to note that when testing with multiple shear condition combinations, multiple tests of certain control variables (especially shear duration) can be performed consecutively. For example, one control variable can be fixed, and multiple tests with different shear durations can be performed consecutively, such as... Figure 2A As shown, multiple tests with a fixed shear rate of 201 / s and shear durations of 10s, 30s, and 60s were conducted consecutively in time. Of course, in other examples, each test could be conducted completely independently of the others. Through methods such as... Figure 2A The tests shown can be performed consecutively or individually to form an M-dimensional data matrix.

[0149] Example 2:

[0150] The fluid composition to be tested is personal care product 2. The shear conditions include two-dimensional controllable variables: shear duration and shear rate. Unlike Example 1, this example has three shear rates and five shear durations. Under the three different combinations of shear rates and five different shear durations, a total of 3 × 5 = 15 different shear histories were experienced, ultimately generating a two-dimensional 3 × 5 data matrix. Spline interpolation was used for visualization. In this example, the number of variable values ​​for the two dimensions of controllable variables is different.

[0151] Here, three different shear rates were used: 201 L / s, 2001 L / s, and 2000 L / s; and three different shear durations were used: 10 s, 40 s, 160 s, 460 s, and 1060 s. The specific test procedure was the same as in Example 1, except that the shear rate and shear duration values ​​were different, and the number of shear cycles was different. The rheological index data (i.e., average viscosity) obtained in this way forms a 3×5 data matrix as shown in the table below:

[0152] 201 / s 2001 / s 20001 / s 10s 2214 1 921 2012 40s 2106 1 763 1 896 1 60s 1956 1 598 1 693 460s 1 858 1460 1456 1060s 1780 1 335 1212

[0153] Table 4

[0154] When visualizing the 2D data matrix shown in Table 4, color stops are defined, such as... Figure 3 The diagram shows the maximum viscosity (2220 cP) represented by orange and the minimum viscosity (1200 cP) represented by purple. The color scale is shown below. Figure 3 The right side. The data matrix can be converted to Figure 3 The color grid shown in the middle left image is transformed by spline interpolation of the original data in the data matrix. Figure 3 The pseudo-color image shown in the middle right figure.

[0155] Simultaneously, the texture transformation index T = 1 - (S) corresponding to this pseudo-color image was calculated. min / S max ) = 1 - (1212 / 2214) = 45%.

[0156] Please note that polymer solutions generally exhibit shear-thinning properties, therefore, under prolonged shearing or at higher shear strengths (shear rates), viscosity is expected to decrease. In Example 1 and... Figure 2B In Table 3, the response of personal care product 1 follows the expected behavior, i.e., from the top left to the bottom right, the viscosity of personal care product 1 gradually decreases with increasing energy input (i.e., increasing shear rate and shear time). However, for personal care product 2, it can be noted that the viscosity of personal care product 2 increases as the shear rate changes from 200 L / s to 2000 L / s at shear durations of 10 s, 40 s, and 160 s, and decreases as the shear rate changes from 200 L / s to 2000 L / s at shear durations of 460 s and 1060 s.

[0157] based on Figure 3 As shown in the left image, in this uninterpolated color grid, one can already see... Figure 3 The rectangular area in the left figure shows some unusual changes in the texture of personal care product 2. Notable anomalies (thickening) in personal care product 2 at low shear times within a higher shear rate (shear rate = 2000 L / s) can be observed. Figure 3 In the right figure, after interpolation, the thickening phenomenon is more pronounced and covers a wider range of shear rates and shear times, such as... Figure 3 The area defined by the dashed circle in the right figure is shown. Effectively, the interpolated pseudo-color image helps improve the sensitivity of the test without increasing the complexity of the experimental procedure.

[0158] This is a unique characteristic compared to personal care product 1 and general personal care products and aqueous solutions of personal care product ingredients. This characteristic is of great significance for the research and development of personal care products and the consumer experience when using the product. In summary, some special physicochemical phenomena in aqueous solutions of personal care products or personal care product ingredients can only be detected using the test methods described in the present disclosure. That is, this example can demonstrate that the method provided in this disclosure can accurately capture special textural changes in fluid compositions.

[0159] Please also note that if the shear time in the shear conditions of Example 2 above is only 10s, 40s, and 160s, then the 3×3 data matrix formed by the measured rheological index data (i.e., average viscosity) is shown in Table 4.1 below:

[0160] 201 / s 2001 / s 20001 / s 10s 2214 1 921 2012 40s 2106 1 763 1 896 1 60s 1956 1 598 1 693

[0161] Table 4.1

[0162] At this point, if the formula T = 1 - (S) is used... min / S max The texture transformation index T can be calculated as T = 1 - (1693 / 2214) = 0.23; if the formula T = 1 - (S 结束 / S 开始 The texture conversion index T can be calculated as T = 1 - (1598 / 2214) = 0.28. This shows a difference between the two calculated texture conversion indices, a difference caused by the unique properties of this personal care product 2.

[0163] For general samples, the rheological data obtained during measurement are always negatively correlated with their shear history (i.e., shear thinning), or the viscosity or modulus always decreases during temperature increases. For these materials, the two formulas mentioned above will yield equivalent texture transition indices. However, in some special materials, such as the personal care product 2 described in Example 2, under certain experimental conditions, T = 1 - (S 结束 / S 开始 This more intuitively reflects the texture transformation properties of these special personal care products or material systems.

[0164] Example 3:

[0165] The fluid composition to be tested is the same as that in Example 1, namely personal care product 1, and the shear conditions are also the same as those in Example 1. However, the shear rate in the rheological test step is reduced from 0.11 / s in Example 1 to 0.051 / s, to show that for the method provided in this disclosure, the rheological test can be performed under different predetermined conditions (different from the shear rate of 0.11 / s in Example 1).

[0166] Here, three different shear rates were used: 201 / s, 2001 / s, and 20001 / s; three different shear durations were used: 10s, 30s, and 60s. The specific test procedure is as follows:

[0167] In the first step, a shearing step is performed, applying a first shear rate of 20 lb / s for 10 seconds. Then, a rheological test step is performed, measuring the shear stress of personal care product 1 at a shear rate of 0.05 lb / s for 600 seconds. Next, a shearing step is performed again, applying a shear rate of 20 lb / s for 30 seconds, followed by another rheological test step measuring the shear stress of product 1 at a shear rate of 0.05 lb / s for 600 seconds. This process is repeated, applying a shearing step at 20 lb / s for 60 seconds, followed by another rheological test step measuring the shear stress at a shear rate of 0.05 lb / s for 600 seconds. During each shearing step (20 lb / s), viscosity is not used for analysis, and shear stress is collected in each rheological test step. Thus, viscosity is calculated from the shear stress collected in the measurement steps. In this example, the average viscosity value of the last 300 seconds of each rheological test step can be used as rheological index data to represent the yield strength of personal care product 1 after shearing. The second and third steps follow the same method as the first step, except that the shear rate in the shear condition is increased to 2001 / s and 20001 / s, respectively.

[0168] The raw data from the rheometer during the above tests are as follows: Figure 4A As shown, Figure 4A The horizontal axis represents time, and the vertical axis represents viscosity. Blue data represents the viscosity measured in the first step at a shear rate of 201 L / s for shearing times of 10 s, 30 s, and 60 s. Green data represents the viscosity measured in the second step at a shear rate of 2001 L / s for shearing times of 10 s, 30 s, and 60 s. Red data represents the viscosity measured in the second step at a shear rate of 20001 L / s for shearing times of 10 s, 30 s, and 60 s. The measured rheological data (i.e., average viscosity) can be tabulated in a 3×3 matrix, as shown in the table below:

[0169] 201 / s 2001 / s 20001 / s 10s 412 349 277 30s 388 282 209 60s 339 238 111

[0170] Table 5

[0171] When visualizing the 2D data matrix shown in Representation 5 above, a color scale of divergence type is defined: dark red represents the maximum viscosity of 500 cP, dark blue represents the minimum viscosity of 0 cP, and white represents the average viscosity of 250 cP. The color scale is displayed as follows: Figure 4BThe right side. The data matrix can be converted to Figure 4B The color grid shown in the middle left image is transformed by performing bicubic interpolation on the original data in the data matrix. Figure 4B The pseudo-color image shown in the middle right figure.

[0172] Because the shear rate (0.051 / s) used to measure the average viscosity above is different from the shear rate (0.11 / s) in Example 1, the value of the average viscosity is different. Nevertheless, the texture change pattern of personal care product 1 remains unchanged.

[0173] Simultaneously, the texture transformation index T = 1 - (S) corresponding to this pseudo-color image was calculated. min / S max ) = 1 - (111 / 412) = 73%.

[0174] In Example 3, the parameters regarding the transition from high to low viscosity of personal care product 1, as well as the degree of change, were consistent with the textural assessments performed by trained experts. Furthermore, although the testing protocols for Examples 1 and 3 differed somewhat (the shear rate in the rheological testing steps decreased from 0.11 / s in Example 1 to 0.051 / s in Example 3), the calculated textural transition index T was consistent (both were 73%). This indicates that when following the same experimental protocol for the same sample, using either shear rate for rheological testing to determine the average viscosity will yield valid comparative analytical results.

[0175] Example 4:

[0176] The fluid composition to be tested was personal care product 3. Shear conditions included two-dimensional controllable variables: shear duration and shear rate. With two shear rates and three shear durations, a total of 2 × 3 = 6 different shear histories were experienced under the combination of two different shear rates and three different shear durations, ultimately generating a two-dimensional 2 × 3 data matrix. Bicubic interpolation was used for visualization. In this example, a very small shear rate of 0.011 / s was used during testing to demonstrate that rheological parameters (such as average viscosity) could be measured under different predetermined conditions.

[0177] Here, two different shear rates were used: 201 / s and 2001 / s. Three different shear durations were used: 10s, 30s, and 120s. The specific test procedure is as follows:

[0178] In the first step, a shearing step is performed, applying a first shear rate of 201 / s for 10 seconds, followed by a rheological test step measuring the shear stress of the personal care product 3 at a shear rate of 0.01 1 / s for 600 seconds. Then, a further shearing step is performed, applying a shear rate of 201 / s to the personal care product 3 for 30 seconds, followed by another rheological test step measuring the shear stress of the product 3 at a shear rate of 0.01 1 / s for 600 seconds. This is repeated, applying a shearing step to the personal care product 3 at a shear rate of 201 / s for 60 seconds, followed by another rheological test step measuring the shear stress at a shear rate of 0.01 1 / s for 600 seconds. The second step follows the same method as the first step, except that the shear rate in the shearing condition is increased to 2001 / s. In each shearing step (201 / s and 2001 / s), viscosity is not used for analysis, and shear stress is collected in each measurement step. Thus, rheological index data are collected from the measurement steps. In this example, the average viscosity value of the last 300 seconds of each measurement step (i.e., the measurement at a shear rate of 0.051 / s) can be used as rheological index data to represent the yield strength of the personal care product 3 after shearing.

[0179] The raw data from the rheometer during the above tests are as follows: Figure 5A As shown, Figure 5A The horizontal axis represents time, and the vertical axis represents viscosity. The blue data represents the viscosity measured in the first step at a shear rate of 201 L / s and shear times of 10 s, 30 s, and 120 s. The green data represents the viscosity measured in the second step at a shear rate of 2001 L / s and shear times of 10 s, 30 s, and 120 s. The measured rheological parameters (i.e., average viscosity) are shown in the 2×3 matrix in the table below.

[0180]

[0181]

[0182] Table 6

[0183] When visualizing the 2D data matrix shown in Table 6 above, grayscale color scales are used. Black represents the maximum viscosity (35000 cP), and white represents the minimum viscosity (20000 cP). The color scales are displayed on the right side of the graph. The data matrix can be converted to... Figure 5B The color grid shown in the middle left image is transformed by performing bicubic interpolation on the original data in the data matrix. Figure 5B The pseudo-color image shown in the middle right figure.

[0184] Example 5:

[0185] The fluid composition to be tested was personal care product 4, and the shear conditions included three-dimensional controllable variables: shear duration, shear rate, and electrolyte concentration. In this example, the effectiveness of the method for generating the three-dimensional data matrix was demonstrated using a high-dimensional approach. Personal care product 4, which it represents, is a polymer solution and is relatively sensitive to the effects of electrolytes. Although two-dimensional controllable variables are sufficient to show the transformation process of personal care product 4, its sensitivity to electrolytes requires a third-dimensional controllable variable for characterization and visualization.

[0186] Here, in this three-dimensional controllable variable, the shear rate has three different values: 121 l / s, 144 l / s, and 201 6 l / s; the shear duration has three different values: 10 s, 30 s, and 120 s; and the electrolyte concentration has three different values: 2%, 4%, and 8%. The specific test procedure is as follows:

[0187] In the first step, a shearing step is first performed, applying a first shear rate of 121 l / s to the personal care product 4 with an electrolyte concentration of 2% for 10 seconds. Then, a rheological test step is performed, measuring the shear stress of the personal care product 4 at a shear rate of 0.01 l / s for 600 seconds. Next, a shearing step is performed again, applying a shearing step at a rate of 121 l / s to the personal care product 4 with an electrolyte concentration of 2% for 30 seconds. Then, a rheological test step is performed, measuring the shear stress of the personal care product 4 at a shear rate of 0.01 l / s for 600 seconds. Finally, a shearing step is performed again, applying a shearing step at a rate of 121 l / s to the personal care product 4 with an electrolyte concentration of 2% for 120 seconds. Then, a rheological test step is performed, measuring the shear stress at a rate of 0.01 l / s for 600 seconds. The second step follows the same method as the first step, except that the shear rate in the shear condition is increased to 1441 / s. In the third step, the shear rate is increased to 20161 / s. Since there is a third controllable variable in this example—electrolyte concentration—the first to third steps will be repeated for personal care products 4 with electrolyte concentrations of 4% and 8%, respectively. A total of 27 shear conditions will be checked to achieve an output of 27 average viscosities, which are the average viscosity values ​​from the last 300 seconds of the shear stress measurement.

[0188] The measured rheological data (i.e., average viscosity) are shown in the 3×3×3 three-dimensional data matrix in the table below:

[0189]

[0190]

[0191] Table 7

[0192] When visualizing the 3D data matrix shown in Table 7 above, color scales are defined: red represents the maximum viscosity (7500 cP), and blue represents the minimum viscosity (2000 cP). The color scales are displayed on the right side of the graph. The data matrix can be converted to... Figure 6A The color grid shown in the middle left image, Figure 6A The image shows, from left to right, two-dimensional color grids of the two-dimensional data matrix when the electrolyte concentration is 2%, 4%, and 8%, respectively. These three two-dimensional color grids can be further stacked to form... Figure 6B The diagram shows a three-dimensional color grid and a visualization of the solid-line three-dimensional data matrix. From the three-dimensional plot shown in 6B, the transitions due to increased shear duration (from left to right), the effect of increased shear rate (from back to front), and the effect of increased additional electrolyte (from top to bottom) are easily observed. Of course, the original data in this data matrix can be interpolated to convert the three-dimensional color grid into a three-dimensional pseudo-color plot.

[0193] Simultaneously, the texture transformation index T = 1 - (S) corresponding to this pseudo-color image was calculated. min / S max = 1 - (2002 / 7375) = 73%. The texture conversion index T was calculated considering the effects of shear duration, shear rate, and electrolyte concentration.

[0194] Furthermore, the number of dimensions can be reduced (i.e., generating two-dimensional data from three-dimensional data). For example, texture transformations caused by shear duration and electrolyte concentration can be extracted from a three-dimensional pseudo-color image (i.e., the frontal plane of the three-dimensional pseudo-color image), even though the combination of these two controllable variables was not specifically tested during the data generation phase. Therefore, high-dimensional methods are compatible with two-dimensional methods.

[0195] Comparative Example 1:

[0196] The fluid composition to be tested is personal care product 1. The test method is based on the method described by Joyner in "Rheology of Semi-Solid Foods". This method defines thixotropy as the hysteretic behavior between two viscosity curves obtained from a linearly changing shear rate. The thixotropic area can be calculated by measuring the difference between the lower and upper curves.

[0197] Using the existing method described above, the personal care product 1 can be sheared using a linearly varying shear rate, such as... Figure 7AAs shown, the shear rate can linearly increase from 11 / s to 10001 / s, and then linearly decrease back to 11 / s. The linear increase and decrease of the shear rate takes a total of 4 minutes, with 2 minutes allocated to the linear increase and 2 minutes to the linear decrease. To demonstrate the thixotropic or textural change of personal care product 1, this process is repeated 4 times, and the data changes during the test are shown below. Figure 7A and Figure 7B As shown.

[0198] The test data is shown below. In the continuous shear cycles, the shear stress of the first cycle is the same as that of the last (4th) cycle. The thixotropic area of ​​the four cycles is as follows:

[0199] 721 Pa / s

[0200] 595Pa / s

[0201] 589Pa / s

[0202] 586Pa / s

[0203] It is evident that for personal care product 1, it is impossible to detect any meaningful textural transformation of personal care product 1. This indicates that, due to the approximate thixotropic area of ​​cycles 2 / 3 / 4, the textural transformation ceases immediately after the first cycle, a result inconsistent with expert sensory assessment; whereas, using the method of this disclosure, the average viscosity tested in Example 1, with its transition from high to low viscosity during testing and the degree of change, is consistent with the textural assessment of trained experts. This demonstrates that the method of this disclosure can characterize the rheological properties of the fluid composition and effectively capture minute textural differences in the fluid composition during use.

[0204] Furthermore, Comparative Example 1 was affected by the inertia of the sample and the equipment during rheological testing. Although advanced rheometers generally have inertia correction functions, these functions cannot always completely eliminate the influence of inertia, especially when the sample mass is large and the viscosity is low. For example, Irvin M. Krieger's article "Bingham Award Lecture-1989: The role of instrument inertia in controlled-stress rheometers," published in the *Journal of Rheology*, Vol. 34, p. 471 in 1990, recorded a case of negative viscosity measurements (as shown in Figure 4 of the article). In the technical solution described in Comparative Example 1, as... Figure 7A and Figure 7BAs shown, within the lower shear rate range during the linear decrease of shear rate, the shear stress (i.e., viscosity, based on Newton's law of viscosity) of personal care product 1 also exhibits a negative value. It is well known that the viscosity of a product cannot be negative. Therefore, negative viscosity indicates a measurement error. This situation demonstrates that the inherent limitations of the instrument have not been fully corrected for the impact on the measurement results. Such limitations cannot be overcome using existing techniques. Therefore, the thixotropic properties and textural transitions of the fluid composition obtained using existing techniques in Comparative Example 1 are affected by the inertia of the equipment and the sample. In contrast, this method uses a constant preset shear rate to perform rheological testing on the sample, thus it is unaffected by the inertia of the sample and the equipment, and can obtain better measurement results than the comparative example.

[0205] Comparative Example 2:

[0206] Compared to Example 2 above, personal care product 2 was tested using the method disclosed in existing US11456450, employing multiple shear rate tests but using only a fixed shear duration. The specific method disclosed in existing US11456450 is as follows:

[0207] The analyte is introduced into the rheometer system at shear rates of 0.11 / s -> 101 / s -> 0.11 / s -> 1001 / s -> 0.11 / s -> 10001 / s -> 0.11 / s -> 10001 / s, with a retention time of 180 seconds for each shear rate. Stability is determined by comparing the viscosity measured at the second / third 0.11 / s interval with the viscosity measured at the first 0.11 / s interval. The slurry is considered stable if the viscosity measured at 0.11 / s is within 20% of that measured at the 10.11 / s interval, and vice versa. A key requirement for this method is that the shear rate should be around 0.11 / s for the first / third / possibly all odd-numbered (measurement) steps. The duration of the third / fourth shear rate step is 180-260 seconds. The shear rate in steps 2, 4, and subsequent even-numbered steps should be increased by a factor of 10 or more per step.

[0208] Based on the description in the prior art above, such as Figure 8 As shown, the application of personal care product 2 involves six steps:

[0209] Step 1: Shear rate 0.11 / s, duration 250s;

[0210] Step 2: Shear rate 101 / s, duration 250s;

[0211] Step 3: Shear rate 0.11 / s, duration 250s;

[0212] Step 4: Shear rate 1001 / s, duration 250s;

[0213] Step 5: Shear rate 0.11 / s, duration 250s;

[0214] Step 6: Shear rate 10001 / s, duration 250s.

[0215] The measured rheological data (i.e., viscosity) are as follows: Figure 8 As shown, the viscosity of personal care product 2 appears to decrease continuously, as indicated by the viscosity data in steps one, three, and five above. Clearly, this method fails to identify the true texture transformation process of the fluid composition.

[0216] Since the prior art only changes the shear rate while always using the same duration to apply shear deformation, this method essentially captures only one dimension of the method introduced in this disclosure, thus missing important rheological information that is crucial for the development and evaluation of fluid composition formulations.

[0217] Furthermore, in manufacturing environments, it is often necessary to produce the same product under different geographical locations and manufacturing conditions. Slight differences in the rheological properties can exist between different batches of products. These batch-to-batch differences typically arise from several reasons, including but not limited to:

[0218] 1. Variations in raw materials: The composition or quality of ingredients such as oils and surfactants, especially those of natural origin, may vary slightly between batches. Even minor differences can affect the stability, texture, or appearance of the product.

[0219] 2. Equipment Wear and Maintenance: Wear and tear on manufacturing equipment can lead to differences in mixing or heating processes. For example, worn blades in a mixer may not generate the same shear force as new blades, resulting in inconsistencies.

[0220] 3. Environmental factors: Changes in humidity, temperature, and even air quality in the manufacturing environment can affect the stability and quality of the emulsion. For example, lower ambient temperatures may cause a slightly faster cooling rate, resulting in differences in viscosity or texture.

[0221] 4. Operator variability: Different ways operators handle the manufacturing process, such as slight changes in time, the order of ingredient addition, or judgments made during mixing, can introduce batch-to-batch variation.

[0222] These factors highlight the importance of rigorous quality control measures, including raw material testing, precise control of manufacturing parameters, and consistent equipment maintenance, to minimize batch-to-batch variations. While these variations may be minor, they can, in some cases, affect the texture of the final product, particularly in the high-end personal care products sector, where the highest levels of consistency are required across all manufactured products.

[0223] Existing evaluation processes are typically conducted by experienced personnel highly trained in sensory evaluation because other methods (such as typical in vitro methods) may not adequately quantify these subtle differences. Publicly available methods, however, can effectively identify batch-to-batch variations, thereby improving quality control and process engineering.

[0224] Example 6:

[0225] The fluid composition to be tested was personal care product 1a, and the testing procedure was exactly the same as in Example 1. The formulation of personal care product 1a was the same as that of personal care product 1, but the batches of raw materials used in the production of personal care product 1a were different from those of personal care product 1.

[0226] Personal care product 1a is based on the raw data measured by the rheometer during the above tests, as follows: Figure 9A As shown, Figure 9A The horizontal axis represents time, and the vertical axis represents viscosity. Blue data represents viscosity measured in the first step at a shear rate of 201 / s for 10s, 30s, and 60s; green data represents viscosity measured in the second step at a shear rate of 2001 / s for 10s, 30s, and 60s; and red data represents viscosity measured in the second step at a shear rate of 20001 / s for 10s, 30s, and 60s. Based on this, the annual average value 300s after each rheological test step can be calculated as the rheological index data, resulting in a 3×3 data matrix. This 3×3 data matrix is ​​a direct result of the rheological test under two-dimensional controllable variables; therefore, this 3×3 two-dimensional data matrix can be represented as shown in Table 8 below:

[0227] 201 / s 2001 / s 20001 / s 10s 368 302 224 30s 346 243 1 59 60s 295 204 77

[0228] Table 8

[0229] When visualizing the 2D data matrix shown in Table 8 above, color scales of divergence type are defined: dark red represents the maximum viscosity of 500 cP, dark blue represents the minimum viscosity of 0 cP, and white represents the average value of 250 cP. Figure 9B As shown, color stops are displayed on the right side of the graph. The data matrix can be converted to... Figure 9BThe color grid shown in the middle left image is transformed by performing bicubic interpolation on the original data in the data matrix. Figure 9B The pseudo-color image shown in the middle right figure.

[0230] Calculations show that the texture transformation index corresponding to this pseudo-color image is T = 1 - (S). min / S max ) = 1 - (77 / 368) = 78%.

[0231] By comparing this personal care product 1a with personal care product 1 in Example 1, it can be clearly seen that the texture transformation index T of the sample increased. After a detailed comparison of the data in the two-dimensional matrix, it can be seen that this phenomenon is due to certain differences in the rheological index data of the sample under lower shear rate and time conditions (left and top of the matrix), while there is almost no difference in the rheological index data under higher shear rate and time conditions (right and bottom of the matrix).

[0232] Based on the tests conducted according to this disclosure, a complete comparison of the differences between two batches of personal care product 1 and personal care product 1a was obtained. Furthermore, the test results obtained based on the tests conducted according to this disclosure can be used to make corresponding adjustments to the production of personal care products, thereby achieving better raw material control, production management, and smaller batch variations.

[0233] Trained experts assessed the differences between personal care product 1 and personal care product 1a, but because the differences between the two batches of products were very small, the expert assessment could not accurately assess the differences between the two samples. The method provided in this disclosure can capture the minute textural differences between different batches of products.

[0234] Those skilled in the art will recognize that various modifications, alterations, and combinations can be made to the above embodiments without departing from the scope of the invention, and such modifications, alterations, and combinations should be considered within the scope of the inventive concept.

[0235] Specific examples have been described in the foregoing specification. However, those skilled in the art will understand that various modifications and changes can be made without departing from the scope of the invention as set forth in the following claims. Therefore, the specification and drawings should be considered illustrative rather than restrictive, and all such modifications are intended to be included within the scope of the teachings of this invention. Furthermore, the described examples / embodiments / implementations should not be construed as mutually exclusive, but rather as potentially composable if such combinations are permitted in any way. In other words, any feature disclosed in any of the foregoing examples / embodiments / implementations may be included in any of the other foregoing examples / embodiments / implementations.

[0236] Beneficial effects, advantages, problem solutions, and any elements that may lead to or make more apparent any beneficial effects, advantages, or solutions should not be construed as key, essential, or fundamental features or elements of any or all claims. The claimed invention is defined solely by the appended claims, including any modifications made during the pending period of this application and all equivalents of these granted claims.

[0237] This abstract is provided to enable the reader to quickly determine the nature of the technical disclosure. It should be understood that the abstract is not intended to interpret or limit the scope or meaning of the claims. Furthermore, as can be seen from the foregoing detailed description, various features have been combined in various embodiments to simplify the disclosure. This approach to disclosure should not be construed as reflecting an intention that the claimed embodiments require more features than expressly recited in each claim. Rather, as reflected in the claims, the inventive subject matter may be present in all features of a single disclosed embodiment. Therefore, the claims are hereby incorporated into the detailed description, each claim being an independent claim.

[0238] The above description is merely a preferred embodiment of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features disclosed in this disclosure that have similar functions.

Claims

1. A method for characterizing the rheological properties of a fluid composition, comprising: The fluid composition is pretreated under predetermined shear conditions, wherein the shear conditions include M controllable variables, where M is an integer greater than or equal to 2; For the fluid composition after shearing, rheological tests are performed under predetermined test conditions to obtain rheological index data; An M-dimensional data matrix formed by acquiring at least four rheological index data is used to characterize the rheological properties of the fluid composition; Each rheological index data corresponds to a shearing condition. The one-dimensional N data points in the M-dimensional data matrix correspond to N different shearing conditions. The N different shearing conditions are formed by combining N different variable values ​​of the one-dimensional controllable variable and one variable value of each of the other dimension controllable variables. N is an integer greater than or equal to 2.

2. The method according to claim 1, characterized in that: The N different variable values ​​of one controllable variable in the N different shearing conditions are sorted in descending or ascending order, and the rheological index data in the M-dimensional data matrix are sorted in the order of the corresponding controllable variables.

3. The method according to claim 1, characterized in that: The shearing conditions include at least two of the following controllable variables: temperature, humidity, shear rate, shear duration, water evaporation parameter, salinity, magnetic field parameter, electric field parameter, tensile displacement, tensile force, pressure, radial oscillation shear parameter, axial oscillation shear parameter, neutron radiation parameter, X-ray radiation parameter, ultraviolet radiation parameter, visible light radiation parameter, and amount of chemical reagent added.

4. The method according to claim 3, characterized in that: When the fluid composition is a personal care product, the shear conditions include shear rate and shear duration.

5. The method according to claim 3, characterized in that: When the fluid composition is a food-grade fluid composition, the shear conditions include electric field parameters and shear rate.

6. The method according to claim 4, characterized in that: When the fluid composition is a personal care product containing a material with photocatalytic properties, the shear conditions also include ultraviolet radiation and temperature.

7. The method according to claim 4, characterized in that: When the fluid composition is a personal care product to be used above a predetermined temperature, the shear condition also includes temperature.

8. The method according to claim 3, characterized in that: When the fluid composition is a fluid composition from the oil and gas sector, the shear conditions include temperature, pressure, and radiation parameters.

9. The method according to claim 3, characterized in that: When the fluid composition is a personal care product, the shear conditions include shear duration, shear rate, and electrolyte concentration.

10. The method according to claim 1, characterized in that: The method of performing rheological tests on the sheared fluid composition under predetermined test conditions to obtain rheological index data includes: Timing begins after the fluid composition has been pretreated under predetermined shear conditions. After a predetermined duration, rheological tests are performed under predetermined test conditions to obtain rheological index data.

11. The method according to claim 10, characterized in that: The predetermined duration ranges from 0 to 10 seconds.

12. The method according to claim 1, characterized in that: The process of conducting rheological tests under predetermined test conditions to obtain rheological index data includes: The fluid composition was sheared at a preset shear rate for a preset shear duration, and the rheological parameters were measured.

13. The method according to claim 12, characterized in that: The preset shear rate ranges from 0.001 to 0.11 / s, and the preset shear duration ranges from 300 to 1800s.

14. The method according to claim 12, characterized in that: The measurements yield rheological index data, including: The average viscosity measured during a portion of the preset shear duration is determined as the rheological index data, where the portion of the time begins at a predetermined moment within the preset shear duration and ends at the last moment within the preset shear duration.

15. The method according to any one of claims 1-14, characterized in that, The method further includes: Based on the correspondence between the data values ​​and color values ​​of the predetermined rheological index data, the M-dimensional data matrix is ​​converted into an M-dimensional color grid: The M-dimensional color grid is interpolated using a predetermined interpolation method to convert the M-dimensional color grid into an M-dimensional pseudo-color image.

16. The method according to claim 15, characterized in that, The method further includes: Calculate the texture conversion index T using the following formula: T=1-(S min / S max ); Wherein, the S min S is the minimum value among the at least four rheological index data. max It is the maximum value among the at least four rheological index data.

17. The method according to claim 15, characterized in that, The method further includes: Calculate the texture conversion index T using the following formula: T=1-(S 结束 / S 开始 ); Wherein, the S 开始 For the rheological index data obtained from the test under the first shear condition, the S 结束 For the rheological index data obtained under the last shearing condition, the variable values ​​of the M-dimensional controllable variables in the first shearing condition are all the minimum values ​​among the variable values ​​of the controllable variables in this dimension, and the variable values ​​of the M-dimensional controllable variables in the last shearing condition are all the maximum values ​​among the variable values ​​of the controllable variables in this dimension.

18. The method according to claim 15, characterized in that: When M is greater than or equal to 3, the M-dimensional pseudo-color image includes one or more three-dimensional pseudo-color images, and the method further includes: For a given 3D color image, determine the corresponding 3D controllable variable of the 3D pseudo-color image; Select any two controllable variables from the three-dimensional controllable variables; Extract the two-dimensional pseudo-color images corresponding to the two selected controllable variables from the three-dimensional color image.

19. The method according to claim 15, characterized in that: The predetermined interpolation method includes any one of the following: bicubic, bilinear, spline, nearest neighbor, Kriging, polynomial, centroid, radial Bass function, thin plate spline, piecewise linear, Fourier, etc.

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