A method for analyzing and evaluating the anti-degradation properties of plastics based on the fitting and derivative method of aerobic biodegradation test results under controlled composting conditions.

Abstract

This invention relates to a method for analyzing and evaluating the anti-degradation performance of plastics based on the fitting and derivative method of aerobic biodegradation test results under controlled composting conditions. The method includes: obtaining the results of the aerobic biodegradation test of plastics under controlled composting conditions; plotting a scatter plot of the decomposition rate relative to time; selecting a segment from the scatter plot and fitting it to a curve using a continuously differentiable function to obtain the curve fitting result with the best fit for subsequent steps; determining the time corresponding to when the third and / or fourth derivatives of the curve are zero and when the fourth and / or fifth derivatives of the curve are negative, and / or the value of the second derivative of the curve at that time as the output of the method. This method can quantitatively describe the critical point of transition between non-microbial chemical degradation and microbial biodegradation behavior in the early and middle stages of aerobic biodegradation tests of plastics under controlled composting conditions. It can be used to quantitatively evaluate the quality of the anti-hydrolysis performance of plastics of different types, processes, formulations, and batches.

Description

Technical Field

[0001] This invention belongs to the field of polymer material analysis technology, specifically relating to a method for evaluating the anti-degradation properties of plastics, and also to a system, equipment and medium for using the method. Background Technology

[0002] The invention and use of plastics have greatly facilitated people's lives, but have also caused serious environmental pollution. Biodegradable polymers, represented by polylactic acid (PLA) and polybutylene terephthalate (PET), are working to solve the problem of plastic / microplastic pollution. Furthermore, in the engineering field, high-performance polymers, represented by polyamides, are increasingly widely used. However, many of these materials are hydrolyzable, meaning they meet the necessary conditions for hydrolysis. For example, the ester bonds (-COO-) in polyester materials and the amide bonds (-CO-NH-) in polyamide materials can undergo hydrolysis in the presence of water and catalysts, leading to a significant decrease in the molecular weight of the polymer and rapid deterioration of material properties. Therefore, the scientific and reliable characterization and evaluation of the hydrolysis resistance of plastics is a crucial means to ensure the large-scale application of these plastics and is of great significance.

[0003] Several characterization and analysis techniques have been developed to evaluate properties related to plastic degradation. For example, visual observation, loss-in-weight measurement, mechanical property evaluation, molecular weight evaluation, and melt flow index (MFI) methods can reflect the degree of degradation of the tested plastic at a certain point in time, but each has its limitations. For instance, visual observation requires significant time to achieve visible degradation and the results are somewhat subjective; loss-in-weight measurement cannot measure short-term degradation fluctuations and cannot reflect the impact of rapid changes in process parameters on the degradation rate; mechanical property evaluation cannot be used to test plastics broken during degradation; molecular weight evaluation requires advanced chromatographic instruments to separate and characterize polymer chains of different molecular weights during degradation, placing high demands on the instruments and personnel; and the MFI method measures the overall properties of a mixture of degraded and undegraded polymers, but the impact of a small amount of degraded polymers on the overall MFI may be less than the method's random error in the early stages of degradation, making accurate results difficult to obtain. As is known in the art, the existing testing and evaluation methods are typically additionally destructive to the samples being tested, thus requiring numerous parallel sample tests to obtain the trends in relevant properties over time. This places high demands on the samples, personnel, equipment, and environment, and results in poor test repeatability. Furthermore, these methods are generally insensitive to the initial or minor degradation behavior of plastics on the material surface, and cannot sensitively and accurately reflect the degradation resistance (e.g., hydrolysis resistance or hydrolysis tolerance) of the plastic test material.

[0004] Therefore, there is still a need to develop characterization and analytical methods for evaluating properties related to plastic degradation, enabling simple testing and analysis processes that do not rely on a large number of parallel sample tests. Ideally, such methods should be able to sensitively and accurately reflect the hydrolysis resistance or hydrolysis tolerance of plastics.

[0005] The inventors have unexpectedly discovered that by analyzing the results of aerobic biodegradation tests of plastics known in the art under controlled composting conditions, the critical transition time point (i.e., the critical point) at which the non-microbial chemical degradation process (i.e., the lag phase) transforms into a microbial biochemical process (i.e., the biodegradation phase) in the early to mid-stages or initial stages of the test can be obtained. The magnitude of this critical point reflects the precise information on the time or speed required for the plastic to decompose to a molecular weight level that can be digested and absorbed by microorganisms under aerobic controlled composting conditions. This can overcome the shortcomings of the prior art and can be further used as an indicator parameter for evaluating the hydrolysis resistance or hydrolysis tolerance of plastics. Summary of the Invention

[0006] One object of the present invention is to overcome at least one of the shortcomings of the prior art, and in particular to provide a method for evaluating the degradation resistance of plastics. The method is based on curve fitting and differentiation to analyze the results of aerobic biodegradation tests of plastics under controlled composting conditions. The method can quantitatively describe the critical point of transition between non-microbial chemical degradation (mainly hydrolysis) and microbial biodegradation behavior of plastics in the early, middle or initial stages of the aerobic biodegradation test. Therefore, it can be used to evaluate the quality of hydrolysis resistance or hydrolysis tolerance of different types, processes, formulations and batches of plastics (especially hydrolyzable plastics such as polyester and polyamide).

[0007] According to one aspect of the present invention, a method for analyzing and evaluating the anti-degradation properties of plastics based on the fitting derivative method of aerobic biodegradation test results under controlled composting conditions is provided, characterized in that it includes the following steps:

[0008] (1) Conduct an aerobic biodegradation experiment on plastics under controlled composting conditions and obtain the results of the experiment.

[0009] Wherein, the biodegradability or relative biodegradability (%) of the plastic at each time point t is denoted as D. t ;

[0010] (2) Draw a scatter plot selected from the following.

[0011] (a)D t A scatter plot relative to t, or

[0012] (b) D t Preprocessing Then draw the preprocessed... Scatter plot relative to t;

[0013] (3) Perform curve fitting on the scatter plot in step (2).

[0014] Specifically, all possible segments containing at least 7 consecutive data points are selected from the scatter plot, and a continuously differentiable function is used to perform curve fitting on the consecutive data points of each segment to obtain a curve fitting function for each region.

[0015] Let the fitting function of the j-th region be denoted as y. j =f j (t)|t∈[t A,j ,t B,j ],

[0016] Here, the size or number of consecutive data points in the j-th region is denoted as m. j , and m j ≥7, t A,j Let t be the starting time point of the j-th region. B,j The end time point of the j-th region, and the continuously differentiable function is selected from functions that are differentiable to at least the fifth order, particularly preferably functions that are differentiable to at least the sixth order, such as functions that are differentiable to the seventh, eighth or ninth order.

[0017] (4) Obtain the curve fitting result with the best fit from the curve fitting function in step (3).

[0018] Apply the following equation 1 to each y j Calculate the adjusted coefficient of determination separately.

[0019]

[0020] in, The coefficient of determination of the curve fitting function for each of the aforementioned segments; m j As defined in step (3); k is the number of free parameters in the fitted function; m j -k>0; the exponent q is 2.0 to 7.0, and

[0021] From the various The maximum value is selected from the set, and the curve fitting function corresponding to the maximum value is constrained to be the curve fitting result with the best fit, denoted as y. opt =f opt (t)|t∈[t A,opt ,t B,opt ];

[0022] (5) Analyze the curve fitting results of the best fit in step (4).

[0023] Calculate y opt By taking the fourth derivative y″″ and the fifth derivative y″″′, we can obtain the time t corresponding to y″″ = 0 and y″″′ < 0. c , where t c The solution is a real number and satisfies t A,opt ≤t c ≤t B,opt Optionally, when there are at least two t values ​​that satisfy the above conditions... c If the solution is the minimum value, then the solution with the minimum value is taken.

[0024] Optionally, calculate y separately. opt By taking the third derivative y″′ and the fourth derivative y″″, we can obtain the time t corresponding to y″′=0 and y″″<0. m , where t m The solution is a real number and satisfies t A,opt ≤t m ≤t B,opt , and t m ≥t c Optionally, when there are at least two t values ​​that satisfy the above conditions... m If the solution is the minimum value, then the solution with the minimum value is taken.

[0025] And optionally, calculate y opt The second derivative y″ is obtained by taking y″ at time t. c The value of time y″ c , and / or get y″ in t m The value of time y″ m ;and

[0026] (6) Output the evaluation results.

[0027] The evaluation results mentioned above include t obtained in step (5). c And preferably additionally includes t m Optionally also includes y″ c and / or y″ m .

[0028] According to another aspect of the present invention, a system for evaluating the degradation resistance of plastics is provided, characterized in that the system employs the method of the present invention.

[0029] According to another aspect of the present invention, a computer device is provided, characterized in that it comprises:

[0030] processor; and

[0031] Memory, used to store executable instructions;

[0032] The processor is configured to read from the memory and execute the executable instructions to implement the method described above.

[0033] According to another aspect of the present invention, a computer-readable storage medium is provided, characterized in that it stores a computer program that, when executed by a processor, causes the method described above to be implemented. Attached Figure Description

[0034] Figure 1 This is a scatter plot of the biodegradation rate versus time for Example 1.

[0035] Figure 2 This is a scatter plot of the biodegradation rate versus time for Example 2.

[0036] Figure 3 This is a scatter plot of the biodegradation rate versus time for Example 3.

[0037] Figure 4 This is a scatter plot of the biodegradation rate versus time for Example 4.

[0038] Figure 5 This is a scatter plot of the relative biodegradation rate versus time for Example 10. Detailed Implementation

[0039] The invention is described in more detail in the following paragraphs. Unless explicitly stated otherwise, each aspect described may be combined with any other aspect or combination thereof. In particular, any feature indicated as preferred may be combined with any other feature indicated as preferred.

[0040] The list of numerical endpoints includes all numbers and fractions within the corresponding range, along with the listed endpoints. It should be noted that when specifying any range of numerical values, any particular upper limit can be associated with any particular lower limit.

[0041] All references cited in this specification are incorporated herein by reference in their entirety.

[0042] In the context of this invention, unless otherwise specified, all terms used herein, including technical and scientific terms, shall have the meaning commonly understood by one of ordinary skill in the art to which this invention pertains.

[0043] The terms “comprising” and “consisting of” as used herein are synonymous with “including” or “containing” and are open-ended and do not exclude additional, unlisted ingredients, components or process steps.

[0044] The term “degradation” or “decomposition” as used in this article refers to the significant change in the chemical structure of plastics under specific environmental conditions, resulting in the loss of certain properties. It can be any process that can lead to a decrease in the molecular weight of polymers or the transformation of long-chain structures into shorter-chain low-molecular-weight substances.

[0045] Based on the process that occurs, there are three main possible degradation modes of plastics: biodegradation, chemical degradation, and physicochemical degradation.

[0046] As used in this article, "biodegradation" refers to the process by which plastics, as a nutrient source for microbial life activities, are digested and absorbed by organisms such as bacteria, fungi, and certain algae, transformed into simpler compounds, and ultimately converted into small molecules such as methane, carbon dioxide, and water. For example, the degradation of biodegradable plastics depends on biological processes that use the carbon-containing substances present in the plastic as a nutrient source for microorganisms.

[0047] As used herein, the term "chemical degradation" refers to the process by which plastics degrade through oxidative degradation, photodegradation, or hydrolysis, including oxidative degradation, photodegradation, and hydrolytic degradation. Specifically, the chemical degradation of plastics in this invention refers to the degradation process before the plastic can be digested and absorbed by organisms. As is known to those skilled in the art, the aerobic biodegradation experiments of this invention under controlled composting conditions were conducted under specified temperature, oxygen concentration, humidity, and dark or low light conditions; therefore, the chemical degradation involved is primarily hydrolytic degradation.

[0048] As used herein, the term "physicochemical degradation" refers to the process by which plastics degrade under the influence of physical fields such as thermal fields, electric fields, and stress fields. Specifically, the physicochemical degradation of the present invention refers to the degradation process of plastics before they can be digested and absorbed by organisms. As is known to those skilled in the art, the aerobic biodegradation experiments of the present invention under controlled composting conditions were conducted in darkness or low light conditions, therefore the physicochemical degradation effects involved are relatively weak.

[0049] It is known in the art that the degradation rate of plastics is influenced by numerous factors, including environmental factors such as temperature, humidity, pH, chemical media, and light irradiation, as well as intrinsic plastic factors such as the primary, secondary, and tertiary structures of the polymer, molecular weight and its distribution, composition, interfacial structure, physical morphology, porosity, and impurities. One object of this invention is to enable the method of this invention to exhibit comprehensive anti-degradation properties of plastics.

[0050] The term "aerobic biodegradation test under controlled composting conditions" as used in this article refers to determining the final aerobic biodegradability and degree of disintegration of plastic materials as organic compounds under controlled composting conditions by measuring the amount of carbon dioxide emitted, according to methods known in the art. Observing the trend of its biodegradability or relative biodegradability over time reveals a zero or even negative decomposition rate in the early stages of degradation; this early stage is referred to as the "lag phase." Related research (Handbook of Biodegradable Polymer, Edited by Abraham J. Domb, Joseph Kost and David M. Wiseman, published in 1997 by CRC Press, pp. 451-453) shows that in the lag phase, under the influence of factors such as water, temperature, pH, and chemicals, plastics undergo changes in chemical structure through non-microbial chemical degradation (such as hydrolysis, oxidative degradation, and photodegradation) before biodegradation. For example, before aerobic biodegradation begins, polylactic acid (PLA) first needs to break ester bonds and reduce its molecular weight through hydrolysis (Hamad, Kotiba, et al. Properties and medical applications of polylactic acid: A review. Express polymer letters, 2015, 9(5): 435-455). When the molecular weight is lower than a certain threshold, such as below 10 kDa, its oligomers or monomers become water-soluble and can be digested and absorbed by microorganisms or cells (Lunt, J. Large-scale production, properties and commercial applications of polylactic acid polymers. Polymer Degradation and Stability, 1998, 59: 145-152). In the biochemical process involving aerobic microorganisms, its oligomers or monomers can be further decomposed into smaller molecules until they are finally decomposed into carbon dioxide and water.

[0051] As is known in the art, in aerobic biodegradation experiments under controlled composting conditions, the cumulative release of carbon dioxide gas is calculated by continuously monitoring and periodically measuring the carbon dioxide production in test and blank containers. The ratio of the actual amount of carbon dioxide gas released by the plastic test material in the experiment to the theoretical amount of carbon dioxide that the material can produce is called the biodegradation rate. Those skilled in the art know that aerobic biodegradability tests of plastic test materials under controlled composting conditions can be performed according to the test procedures in the following standards: GB / T 19277.1 "Determination of the ultimate aerobic biodegradability of plastic materials under controlled composting conditions—Method by analysis of evolved carbon dioxide—Part 1: General method", or GB / T 19277.2 "Determination of the ultimate aerobic biodegradability of plastic materials under controlled composting conditions—Method by analysis of evolved carbon dioxide—Part 2: Gravimetric measurement of carbon dioxide emitted in a laboratory-scale test", or ISO 14855-1, or ISO 14855-2, or ASTM D5929 "Standard Test Method for Determining Biodegradability of Materials Exposed to Source-Separated Organic Municipal Solid Waste Mesophilic Composting Conditions by RespirometryOr ASTM D5338 "Standard Test Method for Determining Aerobic Biodegradation of Plastic Materials Under Controlled Composting Conditions, Incorporating Thermophilic Temperatures", or EN ISO 14855-1, or EN ISO 14855-2, or BS EN ISO 14855-1, or BS EN ISO 14855-2, or DIN EN ISO 14855-1, or DIN EN ISO 14855-2, or KS T ISO 20200 "Plastics – Determination of the degree of disintegration of plastic materials under simulated composting conditions in a laboratory-scale test", or UNE-EN 14995 "Plastics – Evaluation of compostability – Test scheme". and specifications (Test protocols and specifications for assessing the compostability of plastics), or AS5810 "Biodegradable plastics—Biodegradable plastics suitable for home composting".

[0052] The "biodegradability" used in this invention can be determined according to methods known in the art. For example, the biodegradability of the plastic test material can be calculated according to the following equation in GB / T19277.1.

[0053]

[0054] (CO2) T The cumulative amount of carbon dioxide (CO2) released from the compost container containing the test material. B ThCO2 represents the average cumulative amount of carbon dioxide released from the blank container, while ThCO2 represents the theoretical carbon dioxide release from the test material. The same equation applies to the biodegradability of the reference material.

[0055] The aerobic biodegradation test of the present invention under controlled composting conditions can be carried out in a container or indoors, in darkness or low light, without any vapors that would affect microbial growth.

[0056] The "relative biodegradability" used in this invention can be determined according to methods known in the art. For example, the relative biodegradability of the plastic test material can be further obtained according to the following equation:

[0057]

[0058] in, and These are the plastic and the reference material at each time point {t}. i Biodegradation rate (%) of |i=1,2,3,...,p}.

[0059] As used herein, the term "digestion container / composting container" refers to any container known in the art for conducting aerobic biodegradation experiments under controlled composting conditions. The digestion container typically comprises a tightly sealed glass container or a vessel made of other materials that do not affect composting efficiency to prevent gas loss. The container may include a container containing test material, a container containing reference material, or a blank container. The container may be connected to an air system and a carbon dioxide measurement system.

[0060] As used herein, the term "plastic" refers to all types of plastics generally known in the art, particularly those suitable for aerobic biodegradation testing under controlled composting conditions, such as those that can be tested under controlled composting conditions according to the 15 criteria described above. This plastic may include, but is not limited to, all polymers whose main or branched backbone contains chemical bonds such as ester bonds, anhydride bonds (-RCOOOC-), orthoester bonds (-OCOR'R”OR-), carbonate bonds (-ROCOO-), phosphate ester bonds (-OPOR'OOR-), ketal bonds (-OCR'R”OR-), acetal bonds (-OCHR'OR-), imino-carbonate bonds (-ROCNHO-), peptide / amide bonds (-CONH-), and / or phosphazene bonds (-RR'P=N-).

[0061] As used herein, the term "critical point" or "critical transition time point" refers to the critical state at which a non-microbial chemical degradation process (such as hydrolytic degradation, oxidative degradation, etc.) transitions to a microbial biochemical process (biodegradation stage). In this invention, this critical point is defined as the time point obtained by the method of this invention. c or tm .

[0062] The term "determinance" or "R" used in this article 2 "R" is a statistical indicator known to those skilled in the art for judging the correlation between the fitted curve and the selected data points. 2 The definition is as follows:

[0063]

[0064] In this paper, TSS stands for Total Sum of Squares, SSE stands for Sum of Squared Errors, and y i The measured or smoothed values ​​are the data points from the biodegradation test data set for the selected fitting region. y i The arithmetic mean, The regression values ​​are calculated by fitting the selected set of biodegradation test data points in the fitting region to a curve.

[0065] The terms "adjusted coefficient of determination" or "Adj.R" used in this article 2 "" refers to the "coefficient of determination" or "R²". 2 Based on this, an adjustment coefficient is introduced. This can penalize and amplify the error level of an object fitted to an excessively small set of data points. For example, Adj.R 2 It can be defined as follows:

[0066]

[0067] Among them, R 2 q is the coefficient of determination of the curve fitting function for the selected data point set; m is the size of the data point set; k is the number of free parameters in the fitting function; mk>0; the power exponent q is 2.0 to 7.0.

[0068] As used in this paper, the term "free parameters" refers to the number of parameters in a fitted function that can vary independently without affecting the function's basic structure or constraints. For example, when the fitted function is a polynomial function, the number of free parameters is equal to the polynomial order plus one. Taking a seventh-order polynomial as an example, its order is 7, so its number of free parameters is 8.

[0069] The term "best fit" as used in this paper refers to the curve function or result that has the highest correlation with the data points being fitted. Specifically, in this invention, when the "adjusted coefficient of determination" is at its maximum, the corresponding curve fitting function can be considered the curve fitting result with the best fit.

[0070] The plastic test material used in this invention may be in forms known in the art for aerobic biodegradation tests under controlled composting conditions, added in solid form, typically including films, granules, powders, or simple shapes (e.g., dumbbell shapes), preferably in granule or powder form, more preferably in granule form, such as plastic masterbatch. Generally, the maximum surface area of ​​each piece of said plastic test material should not exceed 4 cm². 2 If the size of the test material exceeds the maximum surface area mentioned above, its size can be reduced to meet the requirements. For example, the test material can be in the form of particles with a diameter of about 1 cm or less, such as particles with a diameter of less than about 9 mm, less than about 8 mm, less than about 7 mm, less than about 6 mm, less than about 5 mm, less than about 4 mm, less than about 3 mm, less than about 2 mm or smaller.

[0071] The term "preprocessing" used in this invention refers to data reprocessing using methods commonly known in the art, the main tasks of which typically include data cleaning, data integration, data transformation, and data reduction. Commonly used data preprocessing methods include noise reduction, missing value handling, outlier handling, and baseline correction. The term "smoothing" used in this invention refers to data preprocessing methods known in the art to eliminate noise in the data and thus highlight trends. Those skilled in the art can perform smoothing using methods known in the art, such as moving average (MA), Savitzky-Golay smoothing (also known as convolutional smoothing), and Whittaker smoothing. In addition to smoothing-based denoising methods, those skilled in the art can also perform data preprocessing using methods known in the art, such as modeling-based denoising (e.g., Wiener filtering, deep learning) or decomposition-based denoising (e.g., Fourier transform, wavelet transform, variational mode decomposition), to eliminate noise in the data and thus highlight trends.

[0072] According to one aspect of the present invention, a method for analyzing and evaluating the anti-degradation properties of plastics based on the fitting derivative method of aerobic biodegradation test results under controlled composting conditions is provided, characterized in that it includes the following steps:

[0073] (1) Conduct an aerobic biodegradation test of plastics under controlled composting conditions and obtain the results of the test, including the biodegradation rate or relative biodegradation rate at each time point.

[0074] (2) Draw a scatter plot of the decomposition rate of step (1) relative to time;

[0075] (3) Select multiple segments containing at least 7 consecutive data points from the scatter plot in step (2), and use a function that is at least fifth-order continuously differentiable to perform curve fitting on each segment, and obtain their respective curve fitting functions.

[0076] (4) Select the function with the best fit from the curve fitting functions in step (3) as the curve fitting result; and

[0077] (5) Obtain the time corresponding to the third derivative of the curve fitting result in step (4) being zero and the fourth derivative being negative, and / or the time corresponding to the fourth derivative of the curve fitting result being zero and the fifth derivative being negative, and / or the second derivative value of the curve corresponding to the time, as the output evaluation result.

[0078] According to another aspect of the present invention, a method for analyzing and evaluating the anti-degradation properties of plastics based on the fitting derivative method of aerobic biodegradation test results under controlled composting conditions is provided, characterized by comprising the following steps:

[0079] (1) Conduct an aerobic biodegradation experiment on plastics under controlled composting conditions and obtain the results of the experiment.

[0080] Wherein, the biodegradability or relative biodegradability (%) of the plastic at each time point t is denoted as D. t ;

[0081] (2) Draw a scatter plot selected from the following.

[0082] (a)D t A scatter plot relative to t, or

[0083] (b) D t Preprocessing Then draw the preprocessed... Scatter plot relative to t;

[0084] (3) Perform curve fitting on the scatter plot in step (2).

[0085] Specifically, all possible segments containing at least 7 consecutive data points are selected from the scatter plot, and a continuously differentiable function is used to perform curve fitting on the consecutive data points of each segment to obtain a curve fitting function for each region.

[0086] Let the fitting function of the j-th region be denoted as y. j =f j (t)|t∈[t A,j ,tB,j ],

[0087] Here, the size or number of consecutive data points in the j-th region is denoted as m. j , and m j ≥7, t A,j Let t be the starting time point of the j-th region. B,j The end time point of the j-th region, and the continuously differentiable function is selected from functions that are differentiable to at least the fifth order, particularly preferably functions that are differentiable to at least the sixth order, such as functions that are differentiable to the seventh, eighth or ninth order.

[0088] (4) Obtain the curve fitting result with the best fit from the curve fitting function in step (3).

[0089] Apply the following equation 1 to each y j Calculate the adjusted coefficient of determination separately.

[0090]

[0091] in, The coefficient of determination of the curve fitting function for each of the aforementioned segments; m j As defined in step (3); k is the number of free parameters in the fitted function; m j -k>0; the exponent q is 2.0 to 7.0, and

[0092] From the various The maximum value is selected from the set, and the curve fitting function corresponding to the maximum value is constrained to be the curve fitting result with the best fit, denoted as y. opt =f opt (t)|t∈[t A,opt ,t B,opt ];

[0093] (5) Analyze the curve fitting results of the best fit in step (4).

[0094] Calculate y opt By taking the fourth derivative y″″ and the fifth derivative y″″′, we can obtain the time t corresponding to y″″ = 0 and y″″′ < 0. c , where t c The solution is a real number and satisfies t A,opt ≤t c ≤t B,opt Optionally, when there are at least two t values ​​that satisfy the above conditions... c If the solution is the minimum value, then the solution with the minimum value is taken.

[0095] Optionally, calculate y separately. optBy taking the third derivative y″′ and the fourth derivative y″″, we can obtain the time t corresponding to y″′=0 and y″″<0. m , where t m The solution is a real number and satisfies t A,opt ≤t m ≤t B,opt , and t m ≥t c Optionally, when there are at least two t values ​​that satisfy the above conditions... m If the solution is the minimum value, then the solution with the minimum value is taken.

[0096] And optionally, calculate y opt The second derivative y″ is obtained by taking y″ at time t. c The value of time y″ c , and / or get y″ in t m The value of time y″ m ;and

[0097] (6) Output the evaluation results.

[0098] The evaluation results mentioned above include t obtained in step (5). c And preferably additionally includes t m Optionally also includes y″ c and / or y″ m .

[0099] In step (1) of the method of the present invention, the aerobic biodegradation test of the plastic under controlled composting conditions can be conducted according to any method known in the art, and the results of the test can be obtained, including the biodegradation rate or relative biodegradation rate of the plastic at each time point t. The validity of the results of the aerobic biodegradation test under controlled composting conditions obtained in step (1) of the method of the present invention can be evaluated according to methods known in the art, for example, according to the methods required in standards GB / T 19277.1 or GB / T 19277.2.

[0100] According to the method of the present invention, the aerobic biodegradation test in step (1) can be carried out under constant temperature and dark or low light conditions, wherein the constant temperature can be at least 45°C, at least 46°C, at least 47°C, at least 48°C, at least 49°C, at least 50°C, at least 51°C, at least 52°C, at least 53°C, at least 54°C, at least 55°C, at least 56°C, at least 57°C, at least 58°C, at least 59°C, at least 60°C, or higher. Preferably, the aerobic biodegradation test can be carried out under constant temperature of 58°C ± 2°C and dark or low light conditions.

[0101] According to the method of the present invention, the time mentioned in step (1) can be in minutes (m), hours (h), or days (d). In some preferred embodiments, the time is in days (d).

[0102] According to the method of the present invention, the preprocessing in step (2) can be any data preprocessing method known in the art, such as smoothing. In one embodiment of the present invention, the smoothing can be a moving average smoothing known in the art. Typically, the moving average smoothing method can be a symmetrical window moving average smoothing method or an asymmetrical window moving average smoothing method.

[0103] In one embodiment of the present invention, in step (2) of the method of the present invention, D can be expressed by the following equation 2. t Smoothing process is the pre-processed decomposition rate.

[0104]

[0105] Where i is the position of the smoothed data point; p is the total number of time points of the decomposition rate before preprocessing; for The i-th preprocessed decomposition ratio in the equation; g is the size of the left smoothing window excluding data point i; h is the size of the right smoothing window excluding data point i; g or h is independently an integer of 0, 1, 2, 3 or larger, where g and h are not both 0; u is the value of each D within the smoothing window. t Location; D u D is at position u within the smooth window. t In a preferred embodiment of the invention, in Equation 2, g = h = 1. In a preferred embodiment of the invention, in Equation 2, g ≠ 0 and h = 0; preferably, g = 5 and h = 0.

[0106] According to the method of the present invention, the scale of continuous data points in step (3), i.e., the number m j It can be at least 8, at least 9 or at least 10, preferably at least 15, particularly preferably at least 20, and still more preferably at least 30 or at least 60.

[0107] According to the method of the present invention, in step (3) t A,j It may be at least the 6th, 12th, 18th, 24th, 30th, 36th, 42nd or 48th hour, or at least the 3rd, 4th, 5th, 6th, 7th, 8th, 9th, 10th, 15th or 20th day, or at least the 30th, 40th, 50th, 60th, 70th or 80th day.

[0108] According to the method of the present invention, in step (3) t A,jIt can be at most the 12th or 24th hour, or at most the 3rd, 6th, 10th, 15th, 30th, 60th or 90th day.

[0109] According to the method of the present invention, in step (3) t B,j It can be at least 24, at least 36 or at least 48 hours, or at least 3, at least 6 or at least 10 days, preferably at least 15 days, more preferably at least 30 days, particularly preferably at least 60 days, still more preferably at least 90 days, or even at least 120 days.

[0110] According to the method of the present invention, in step (3), the above-mentioned range of t can be optionally selected according to actual needs, such as degradation conditions, material type and / or morphological size. A,j and t B,j To avoid or reduce t c and / or t m Not in t A,j To t B,j The occurrence of incomprehensible situations within the section.

[0111] According to the method of the present invention, the continuously differentiable function in step (3) can be selected from functions that are at least fifth-order differentiable, preferably at least sixth-order differentiable, more preferably at least seventh-order differentiable, for example, seventh-, eighth-, or ninth-order differentiable functions. In one embodiment of the present invention, the continuously differentiable function in step (3) can be selected from a polynomial function, a Boltzmann function, or a Bézier curve, preferably a polynomial function. In some embodiments, the continuously differentiable function can be a polynomial function or a Boltzmann function. In a preferred embodiment, the continuously differentiable function can be a polynomial function.

[0112] In some preferred embodiments of the present invention, the continuously differentiable function in step (3) of the method may be a polynomial function, such as a fifth-order polynomial function or a higher-order polynomial function, more preferably a sixth-order, seventh-order, eighth-order, or ninth-order polynomial. Particularly preferably, the continuously differentiable function in step (3) may be a seventh-order polynomial function.

[0113] In the method of the present invention, "a" in relation to a continuously differentiable function refers to a function of the same type that is differentiable of the same order, wherein the coefficients, i.e., the free parameters, may be different. For example, a continuously differentiable function may be a seventh-degree polynomial function with different coefficients.

[0114] In one implementation, in step (4), The coefficient of determination of the curve fitting function for each of the aforementioned segments, specifically, m j -k>0; D tjThe biodegradation rate of the j-th segment (i.e., D) t ); D for segment j t The arithmetic mean, i.e., D tj The arithmetic mean; D for segment j t The regression value is calculated after curve fitting in step (3).

[0115] In a preferred embodiment of the invention, in step (2), a scatter plot of the biodegradability of the plastic relative to t is plotted, wherein the biodegradability of the plastic is a smoothed biodegradability rate. And in step (4) Based on The coefficient of determination of the curve fitting function obtained relative to the scatter plot of t, specifically, m j -k>0; The smooth biodegradation rate of the j-th segment (i.e. ); For the j-th segment The arithmetic mean, i.e. The arithmetic mean; For the j-th segment The regression value is calculated after curve fitting in step (3).

[0116] According to the method of the present invention, in step (4), the adjustment of the coefficient of determination can be achieved. To analyze the goodness of fit of the curve obtained in step (3), its coefficient of determination R 2 An adjustment coefficient can be introduced based on this. The error level of the fitting scheme for a data point set that is too small is penalized and amplified, where m j -k>0; m j Let m be the size or number of consecutive data points contained in the j-th segment, and m j ≥7; k is the number of free parameters in the fitted function; q is the power exponent in the adjustment coefficient. Based on the present invention The error-maximizing optimization method can obtain a continuously differentiable function, such as a polynomial fitting function, that provides a data point set of moderate size and can describe the biodegradation experimental data involving the biodegradation critical point region as completely and accurately as possible. The method of this invention adjusts the coefficient of determination... The principle of maximization can avoid the problem of choosing a fitting scheme with an excessively small dataset for curve fitting analysis.

[0117] In some preferred embodiments of the present invention, when the continuously differentiable function in step (3) of the method is a polynomial function, for example, the form of the polynomial function can be as shown in Equation 3 below.

[0118] y = a n ×t n +a n-1 ×t n-1 +...+a2×t 2 Equation 3: +a1×t+a0

[0119] Where n is the order of the polynomial function, and a0 to a n If the coefficients of each term of the polynomial function are given, then in the adjustment of the coefficients of determination in step (4), the number of free parameters k in the fitted function is equal to the number of parameters, i.e., coefficients, of the polynomial function. That is, when the continuously differentiable function in step (3) of the method is a polynomial function, k is equal to the order of the polynomial function + 1, i.e., k = n + 1.

[0120] In some embodiments of the present invention, when the continuously differentiable function in step (3) of the method is a polynomial function, the scale of the continuous data points in step (3), i.e., the number m, is... j It can be at least the order of the polynomial function + 2, preferably at least the order of the polynomial function + 3, more preferably at least the order of the polynomial function + 4, even more preferably at least the order of the polynomial function + 5, even more preferably at least the order of the polynomial function + 10, still more preferably at least the order of the polynomial function + 15, most preferably at least the order of the polynomial function + 20, or greater.

[0121] In some embodiments of the present invention, the power exponent q in the adjustment coefficient may be 2.0 to 7.0.

[0122] In one embodiment of the present invention, the continuously differentiable function in step (3) of the method can be a fifth-degree polynomial function. Preferably, the coefficient of determination of the fifth-degree polynomial function in step (4) is adjusted. The power exponent q in the equation is 4.0 to 7.0, preferably 5.0 to 7.0, for example 4.0, 4.5, 5.0, 5.5, 6.0, 6.5, or 7.0. In a preferred embodiment, the continuously differentiable function in step (3) can be a fifth-degree polynomial function, and the coefficient of determination in step (4) is adjusted. The power exponent q in the equation can be between 5.0 and 7.0, but is usually 5.0.

[0123] In a preferred embodiment of the present invention, the continuously differentiable function in step (3) of the method can be a sixth-degree polynomial function. Preferably, the coefficient of determination of the sixth-degree polynomial function in step (4) is adjusted. The power exponent q in the function is 3.0 to 6.5, preferably 3.6 to 5.6, for example 4.0, 4.2, 4.4, 4.6, 4.8, 5.0, or 5.2. In a particularly preferred embodiment, the continuously differentiable function in step (3) may be a sixth-degree polynomial function, and the coefficient of determination in step (4) is adjusted. The power exponent q in the equation can range from 3.0 to 6.5, but is typically 4.6.

[0124] In a preferred embodiment of the present invention, the continuously differentiable function in step (3) of the method can be a seventh-degree polynomial function. Preferably, the coefficient of determination of the seventh-degree polynomial function in step (4) is adjusted. The power exponent q in the function is from 2.5 to 6.0, preferably from 3.3 to 5.3, for example 3.7, 3.9, 4.1, 4.3, 4.5, 4.7, or 4.9. In a particularly preferred embodiment, the continuously differentiable function in step (3) may be a seventh-degree polynomial function, and the coefficient of determination in step (4) is adjusted. The power exponent q in the equation can range from 2.5 to 6.0, but is typically 4.3.

[0125] In a preferred embodiment of the present invention, the continuously differentiable function in step (3) of the method can be an eighth-degree polynomial function. Preferably, the coefficient of determination of the eighth-degree polynomial function in step (4) is adjusted. The power exponent q in the function is from 2.0 to 5.5, preferably from 3.1 to 5.1, for example 3.5, 3.7, 3.9, 4.1, 4.3, 4.5, or 4.7. In a particularly preferred embodiment, the continuously differentiable function in step (3) may be an eighth-degree polynomial function, and the coefficient of determination in step (4) is adjusted. The power exponent q in the equation can range from 2.0 to 5.5, but is typically 4.1.

[0126] In a preferred embodiment of the present invention, the continuously differentiable function in step (3) of the method can be a ninth-degree polynomial function. Preferably, the coefficient of determination of the ninth-degree polynomial function in step (4) is adjusted. The power exponent q in the equation is from 2.0 to 5.5, preferably from 2.9 to 5.9, for example 3.3, 3.5, 3.7, 3.9, 4.1, 4.3, or 4.5. In a particularly preferred embodiment, the continuously differentiable function in step (3) may be a ninth-degree polynomial function, and the coefficient of determination in step (4) is adjusted. The power exponent q in the equation can range from 2.0 to 5.5, but is typically 3.9.

[0127] According to the method of the present invention, y calculated in step (5) opt The third derivatives y″′ and y opt The fourth derivatives y″″ and y opt The second derivative y″ can be either a numerical solution or an analytical solution independently.

[0128] In some embodiments of the present invention, t is calculated in step (5). c and / or t m If no real solution or an unreasonable solution is found during the process, the process can be returned to step (4) to find the solution from each of the following steps. Select the next largest value from the set, take the curve fitting function corresponding to this value as the new curve fitting result, and obtain its corresponding t according to step (5). c and / or t m This process continues until a value t that satisfies the condition is obtained. c and / or t m The evaluation result is used as the output.

[0129] Specifically, in step (5), t is calculated. c and / or t m If no real solution or an unreasonable solution is found during the process, the process can be returned to step (4) to find the solution from each of the following steps. Select the second largest value, take the curve fitting function corresponding to the second largest value as the new curve fitting result, and obtain its corresponding t according to step (5). c and / or t m Since t still cannot be calculated from the curve fitting function corresponding to the second largest value. c and / or t m In this case, we can return to step (4) and retrieve the results from each step. Select the third largest value, take the curve fitting function corresponding to the third largest value as the new curve fitting result, and obtain its corresponding t according to step (5). c and / or t m This process continues until a value t that satisfies the condition is obtained. c and / or t m The evaluation result is output. It should be noted that when t is calculated according to the method of the present invention... c and t m When both are used as evaluation results, the same curve fitting result should be used to calculate t in all cases. c and t m both.

[0130] In some embodiments of the present invention, step (1) of the method yields the biodegradability or relative biodegradability D. t The maximum value can be less than 10%, less than 9%, less than 8%, less than 7%, less than 10%, less than 9%, less than 8%, less than 7%, less than 6%, less than 5%, less than 4.5%, less than 4%, less than 3.5%, less than 3%, less than 2.5%, less than 2%, or less than 1.5%.

[0131] In some embodiments of the present invention, step (1) of the method yields the biodegradability or relative biodegradability D. t The maximum value can be at least 1%, at least 1.5%, at least 2%, at least 2.5%, at least 3%, at least 3.5%, at least 4%, at least 4.5%, at least 5%, at least 6%, at least 7%, at least 8%, at least 9%, or at least 10%.

[0132] In some embodiments of the present invention, the minimum value of each time point t in step (1) of the method can be the 0th hour or the 0th day, and the maximum value of each time point t can be at least the 48th hour, the 3rd, 4th, 5th, 10th, 15th, 20th, 25th, 30th, 35th, 45th, 60th or 90th day, as long as the scatter plot in the corresponding step (2) of the method can reflect the trend of the biodegradation rate or relative biodegradation rate changing with time in the lag phase (that is, it can be found that there is a zero decomposition rate or even a negative decomposition rate in the early stage of degradation) and the trend of the biodegradation rate or relative biodegradation rate increasing with time in the biodegradation phase.

[0133] According to another aspect of the present invention, a system for evaluating the degradation resistance of plastics is provided, characterized in that the system employs the method of the present invention.

[0134] According to another aspect of the present invention, a computer device is provided, characterized in that it comprises:

[0135] processor; and

[0136] Memory, used to store executable instructions;

[0137] The processor is configured to read from the memory and execute the executable instructions to implement the method described above.

[0138] According to another aspect of the present invention, a computer-readable storage medium is provided, characterized in that it stores a computer program that, when executed by a processor, causes the method described above to be implemented.

[0139] Example

[0140] To further understand the present invention, preferred embodiments of the present invention are described below in conjunction with examples. However, it should be understood that these descriptions are only for further illustrating the features and advantages of the present invention, and not for limiting the claims of the present invention. Any changes, modifications, substitutions, combinations, or simplifications made without departing from the spirit and principle of the present invention should be considered equivalent substitutions and are included within the protection scope of the present invention.

[0141] The following shows the materials and testing instruments used in the aerobic biodegradation experiments under controlled composting conditions in Examples 1 to 11:

[0142] - Testing instrument: Bioprocess Control Gas Endeavour biodegradation testing system manufactured by Bioprocess Control Sweden AB;

[0143] - Plastics: All are polyester plastics, specifically poly(L-lactic acid) resin (PLA, CAS: 26100-51-6, molecular formula (C3H4O2)). n The dosage was 7.5g, in the form of particles with a diameter of approximately 3mm. The poly(L-lactic acid) resin #1 had a melting point of 174.6℃, a melt index of 4.9g / 10min (190℃, 2.16kg), a molecular weight distribution index of 1.65, and a glass transition temperature (T0). g The temperature was 58.7℃ and the density was 1.25 g / cm³. 3 The content of lactide is 0.33%, the melting point of poly(L-lactic acid) resin 2# is 177.3℃, the melt index is 4.6g / 10min (190℃, 2.16kg), the molecular weight distribution index is 1.62, and the glass transition temperature (T) is... g The temperature is 60.8℃ and the density is 1.25 g / cm³. 3 The content of lactide is 0.20%, and the melting point of poly(L-lactic acid) resin #3 is 160.0℃, the melt index is 17.1g / 10min (190℃, 2.16kg), the molecular weight distribution index is 1.58, and the glass transition temperature (T) is... g The temperature was 59.9℃ and the density was 1.25 g / cm³. 3 The content of lactide is 0.11%. The test methods for the performance indicators of the above poly(L-lactic acid) resin are in accordance with the national standard GB / T 29284-2024 "Polylactic Acid"; the modified polylactic acid resin is used in a dosage of 7.5g, in the form of particles with a diameter of approximately 3mm, including those from Zhejiang Hisun Biomaterials Co., Ltd. Type 181 modified polylactic acid resin.

[0144] -Inoculum: All were aerobic compost from Bipu Instruments (Zhejiang) Co., Ltd., and the amount used was 500g;

[0145] - Reference material: Cellulose powder (α-cellulose powder, CAS: 9004-34-6, particle size ≤25μm) from Shanghai Aladdin Biochemical Technology Co., Ltd.

[0146] - Digestion container: 1L Schott blue cap glass reagent bottle.

[0147] Example 1

[0148] According to GB / T 19277.1 "Determination of the final aerobic biodegradability of materials under controlled composting conditions—Method for determining the release of carbon dioxide—Part 1: General Method", an aerobic biodegradation test was conducted on poly(L-lactic acid) resin 1# under controlled composting conditions, using α-cellulose powder as a reference material. The test was conducted under weak light conditions at a temperature of 58℃±2℃. The cumulative carbon dioxide gas release in each digester was recorded on a daily basis (d), and the biodegradation rate of the test material was calculated.

[0149] To plot the biodegradation rate relative to time, see [reference]. Figure 1 The study exhaustively enumerated all regions in the scatter plot containing at least nine consecutive data points, fitted curves to each region using a seventh-order polynomial, and calculated the corresponding adjusted coefficient of determination. The power exponent q is 4.3. This was calculated to be... The largest region corresponds to the data point set from day 2 to day 42, and its corresponding curve fitting function is:

[0150] y opt =–2.22483321746615×10 -11 ×t 7 +3.49921656327096×10 -9 ×t 6 –2.03282902465231×10 -7 ×t 5 +5.17125289554367×10 -6 ×t 4 –4.78818761596649×10 -5 ×t 3 +8.29194633109149×10 -5 ×t 2 –5.05774357023876×10 -3 ×t+2.4372002915553×10 -2

[0151] Calculate the numerical solution of the fourth derivative y″″ = 0 of the above function, and obtain t. c =8.00, and its fifth derivative y″″′ = –7.824 × 10 -6 <0|t=t c and 2≤t c ≤42, the evaluation result t is obtained. c =8.00d.

[0152] In addition, the numerical solution of the third derivative y″′=0 of the above function is calculated, and t is obtained. m =15.50, and its fourth derivative y″″ = –2.094 × 10 -5 <0|t=t m and 2≤t m ≤42 and t m ≥t c The evaluation result t was obtained. m =15.50d.

[0153] Example 2

[0154] An aerobic biodegradability test was conducted on poly(L-lactic acid) resin #2 according to ISO 14855-1 "Determination of the ultimate aerobic biodegradability of plastic materials under controlled composting conditions - Method by analysis of evolved carbon dioxide - Part 1: General method". α-cellulose powder was used as a reference material, and the test was conducted under low-light conditions at a temperature of 58℃±2℃. The cumulative carbon dioxide gas release in each digestion container was recorded daily, and the biodegradability rate of the test material was calculated.

[0155] To plot the biodegradation rate relative to time, see [reference]. Figure 2 The study exhaustively enumerated all regions in the scatter plot containing at least nine consecutive data points, fitted curves to each region using a seventh-order polynomial, and calculated the corresponding adjusted coefficient of determination. The power exponent q is 4.3. This was calculated to be... The largest region corresponds to the data point set from day 2 to day 43, and the corresponding curve fitting function is:

[0156] y opt = –1.31414836271717 × 10 -10×t 7 +1.9883622665005×10 -8 ×t 6 –1.19097923793376×10 -6 ×t 5 +3.57824185692077×10 -5 ×t 4 –5.61979273799354×10 -4 ×t 3 +4.43019536100526×10 -3 ×t 2 –1.72691823101215×10 -2 ×t+1.59750691563909×10 -2

[0157] Calculate the numerical solution of the fourth derivative y″″ = 0 of the above function, and obtain t. c =11.24, and its fifth derivative y″″′ = –2.385 × 10 -5 <0|t=t c and 2≤t c ≤43, the evaluation result t is obtained. c =11.24d.

[0158] In addition, the numerical solution of the third derivative y″′=0 of the above function is calculated, and t is obtained. m =16.85, and its fourth derivative y″″ = –4.513 × 10 -5 <0|t=t m and 2≤t m ≤43 and t m ≥t c The evaluation result t was obtained. m =16.85d.

[0159] Example 3

[0160] An aerobic biodegradability test was conducted on poly(L-lactic acid) resin #3 according to ISO 14855-1 "Determination of the ultimate aerobic biodegradability of plastic materials under controlled composting conditions - Method by analysis of evolved carbon dioxide - Part 1: General method". α-cellulose powder was used as a reference material, and the test was conducted under low-light conditions at a temperature of 58℃±2℃. The cumulative carbon dioxide gas release in each digestion container was recorded daily, and the biodegradability rate of the test material was calculated.

[0161] To plot the biodegradation rate relative to time, see [reference]. Figure 3 The study exhaustively enumerated all regions in the scatter plot containing at least nine consecutive data points, fitted curves to each region using a seventh-order polynomial, and calculated the corresponding adjusted coefficient of determination. The power exponent q is 4.3. This was calculated to be... The largest region corresponds to the data point set from day 0 to day 42, and the corresponding curve fitting function is:

[0162] y opt =–3.5959282934999×10 -11 ×t 7 +2.9984520756262×10 -9 ×t 6 +1.64139843166322×10 -8 ×t 5 –8.22860759207612×10 -6 ×t 4 +2.83611124872035×10 -4 ×t 3 –3.32507447042611×10 -3 ×t 2 +1.61898207300958×10 -2 ×t–4.18749380483645×10 -3

[0163] Calculate the real solution of the fourth derivative y″″ = 0 of the above function, and obtain t. c = -10.34, however, the t c<0, meaning it is not within the range of day 0 to day 42 of the data point set, in other words, in Calculate t when taking the maximum value c An unreasonable solution was found during the process.

[0164] Therefore, from various The second largest value is selected, corresponding to the data set from day 0 to day 43. The corresponding curve fitting function is:

[0165] y opt =–7.18008925086128×10 -11 ×t 7 +7.95459645858276×10 -9 ×t 6 –2.5235783572402×10 -7 ×t 5 –1.00410326543275×10 -6 ×t 4 +1.83692370488336×10 -4 ×t 3 –2.71993765571635×10 -3 ×t 2 +1.46448947806362×10 -2 ×t+2.64176580789852×10 -4

[0166] Calculate the real solution of the fourth derivative y″″ = 0 of the above function, and obtain t. c = -0.74, however, the t c <0, meaning it is not within the range of day 0 to day 43 of the data point set, in other words, in Calculate t when taking the second largest value. c An unreasonable solution was found during the process.

[0167] Therefore, from various The third largest value is selected, and its corresponding data point set is from day 1 to day 42. The corresponding curve fitting function is:

[0168] y opt =–3.49506937392479×10 -11 ×t 7 +2.75626102692637×10 -9 ×t 6 +3.69752844248873×10 -8 ×t 5–9.06507989006697×10 -6 ×t 4 +3.0129555216914×10 -4 ×t 3 –3.57410792686069×10 -3 ×t 2 +1.72615307029147×10 -2 ×t–1.90474672447274×10 -3

[0169] Calculate the real solution of the fourth derivative y″″ = 0 of the above function, and obtain t. c = -14.11, however, the t c <1, meaning it is not within the range of day 1 to day 42 of the data point set, in other words, in Calculate t when taking the third largest value. c An unreasonable solution was found during the process.

[0170] Therefore, from various The fourth largest value is selected, corresponding to the data set from day 1 to day 43. The corresponding curve fitting function is:

[0171] y opt = –7.4126940976463 × 10 -11 ×t 7 +8.33234678340413×10 -9 ×t 6 –2.77022327655295×10 -7 ×t 5 –1.77411171833121×10 -7 ×t 4 +1.68658915087824×10 -4 ×t 3 –2.57637032006149×10 -3 ×t 2 +1.40128728940951×10 -2 ×t+1.16005524278218×10 -3

[0172] Calculate the real solution of the fourth derivative y″″ = 0 of the above function, and obtain t. c = -0.13, however, the t c <1, meaning it is not within the range of day 1 to day 43 of the data point set, in other words, in Calculate t when taking the fourth time cAn unreasonable solution was found during the process.

[0173] Therefore, from various The fifth largest value is selected, and its corresponding data point set is from day 2 to day 42. The corresponding curve fitting function is:

[0174] y opt = –4.90476620209193 × 10 -11 ×t 7 +5.03902984840981×10 -9 ×t 6 –1.12483568245987×10 -7 ×t 5 –4.00015471712182×10 -6 ×t 4 +2.06968740032992×10 -4 ×t 3 –2.63162431021857×10 -3 ×t 2 +1.27453367584566×10 -2 ×t+5.68266612575028×10 -3

[0175] Calculate the real solution of the fourth derivative y″″ = 0 of the above function, and obtain t. c = -4.34, however, the t c <2, meaning it is not within the range of day 2 to day 42 of the data point set, in other words, in Calculate t when taking the fifth time. c An unreasonable solution was found during the process.

[0176] Therefore, from various The sixth largest value is selected, corresponding to the data set from day 2 to day 43. The corresponding curve fitting function is:

[0177] y opt = –9.30009110505888 × 10 -11 ×t 7 +1.14591343651394×10 -8 ×t 6 –4.86429015996485×10 -7 ×t 5 +7.07993736973606×10 -6 ×t 4 +3.04838731246372×10-5 ×t 3 –1.16571339459982×10 -3 ×t 2 +7.11267255276953×10 -3 ×t+1.29723122871096×10 -2

[0178] Calculate the numerical solution of the fourth derivative y″″ = 0 of the above function, and obtain t. c =3.91, and its fifth derivative y″″′ = –2.968 × 10 -5 <0|t=t c and 2≤t c ≤43, the evaluation result t is obtained. c =3.91d.

[0179] In addition, the numerical solution of the third derivative y″′=0 of the above function is calculated, and t is obtained. m =11.87, and its fourth derivative y″″ = –7.239 × 10 -5 <0|t=t m and 2≤t m ≤43 and t m ≥t c The evaluation result t was obtained. m =11.87d.

[0180] Example 4

[0181] According to ISO 14855-1 "Determination of the ultimate aerobic biodegradability of plastic materials under controlled composting conditions - Method by analysis of evolved carbon dioxide - Part 1: General method", the samples from Zhejiang Hisun Biomaterials Co., Ltd. were analyzed. Aerobic biodegradation tests were conducted on modified polylactic acid resin of type 181, using α-cellulose powder as a reference material, under weak light conditions at a temperature of 58℃±2℃. The cumulative carbon dioxide gas release in each digestion container was recorded on a daily basis (d), and the biodegradation rate of the test material was calculated.

[0182] To plot the biodegradation rate relative to time, see [reference]. Figure 4The study exhaustively enumerated all regions in the scatter plot containing at least nine consecutive data points, fitted curves to each region using a seventh-order polynomial, and calculated the corresponding adjusted coefficient of determination. The power exponent q is 4.3. This was calculated to be... The largest region corresponds to the data point set from day 3 to day 41, and the corresponding curve fitting function is:

[0183] y opt =–2.53972582084636×10 -10 ×t 7 +3.76231120340404×10 -8 ×t 6 –2.21582739640101×10 -6 ×t 5 +6.57825442591369×10 -5 ×t 4 –1.03466020869181×10 -3 ×t 3 +8.62538068756277×10 -3 ×t 2 –4.00425470608963×10 -2 ×t+6.93840584917279×10 -2

[0184] Calculate the numerical solution of the fourth derivative y″″ = 0 of the above function, and obtain t. c =11.20, and its fifth derivative y″″′ = –4.279 × 10 -5 <0|t=t c and 3≤t c ≤41, the evaluation result t is obtained. c =11.20d.

[0185] In addition, the numerical solution of the third derivative y″′=0 of the above function is calculated, and t is obtained. m =16.18, and its fourth derivative y″″ = –8.133 × 10 -5 <0|t=t m and 3≤t m ≤41 and t m ≥t c The evaluation result t was obtained. m =16.18d.

[0186] Example 5

[0187] Curve fitting was performed on the scatter plot of Example 1. All regions in the scatter plot containing at least 11 consecutive data points were exhaustively enumerated, and curve fitting was performed on each region using a ninth-order polynomial. The corresponding adjustment coefficient of determination was then calculated. The power exponent q is 3.9. This was calculated to be... The largest region corresponds to the data point set from day 2 to day 42, and the corresponding curve fitting function is:

[0188] y opt =–1.31902670959225×10 -13 ×t 9 +3.15657922619443×10 -11 ×t 8 –3.16386857859078×10 -9 ×t 7 +1.73280816436763×10 -7 ×t 6 –5.64556611756845×10 -6 ×t 5 +1.11077917362539×10 -4 ×t 4 –1.27590129894226×10 -3 ×t 3 +8.05220061984835×10 -3 ×t 2 –3.0382839784887×10 -2 ×t+5.30204443633206×10 -2

[0189] Calculate the numerical solution of the fourth derivative y″″ = 0 of the above function, and obtain t. c =9.15, and its fifth derivative y″″′ = –5.491 × 10 -5 <0|t=t c and 2≤t c ≤42, the evaluation result t is obtained. c =9.15d.

[0190] In addition, the numerical solution of the third derivative y″′=0 of the above function is calculated, and t is obtained. m =14.20, and its fourth derivative y″″ = –5.934 × 10 -5 <0|t=t m and 2≤t m ≤42 and t m ≥t c The evaluation result t was obtained.m =14.20d.

[0191] Example 6

[0192] Curve fitting was performed on the scatter plot of Example 2. All regions in the scatter plot containing at least 11 consecutive data points were exhaustively enumerated, and curve fitting was performed on each region using a ninth-order polynomial. The corresponding adjustment coefficient of determination was then calculated. The power exponent q is 3.9. This was calculated to be... The largest region corresponds to the data point set from day 1 to day 45, and the corresponding curve fitting function is:

[0193] y opt =5.73162454592436×10 -13 ×t 9 –1.17472461668288×10 -10 ×t 8 +1.00673682953582×10 -8 ×t 7 –4.68373606265947×10 -7 ×t 6 +1.28651664715183×10 -5 ×t 5 –2.13124401414326×10 -4 ×t 4 +2.10029946087793×10 -3 ×t 3 –1.17541456475382×10 -2 ×t 2 +3.18361112167389×10 -2 ×t–3.83800520889604×10 -2

[0194] Calculate the numerical solution of the fourth derivative y″″ = 0 of the above function, and obtain t. c =14.15, and its fifth derivative y″″′ = –3.749 × 10 -5 <0|t=t c and 1≤t c ≤45, the evaluation result t is obtained. c =14.15d.

[0195] In addition, the numerical solution of the third derivative y″′=0 of the above function is calculated, and t is obtained. m =18.27, and its fourth derivative y″″ = –8.060 × 10 -5<0|t=t m and 1≤t m ≤45 and t m ≥t c The evaluation result t was obtained. m =18.27d.

[0196] Example 7

[0197] Curve fitting was performed on the scatter plot of Example 3. All regions in the scatter plot containing at least 11 consecutive data points were exhaustively enumerated, and curve fitting was performed on each region using a ninth-order polynomial. The corresponding adjusted coefficient of determination was then calculated. The power exponent q is 3.9. This was calculated to be... The largest region corresponds to the data point set from day 0 to day 43, and the corresponding curve fitting function is:

[0198] y opt =–2.03253141701116×10 -13 ×t 9 +3.63639364249766×10 -11 ×t 8 –2.73836057508396×10 -9 ×t 7 +1.10946800405038×10 -7 ×t 6 –2.48827177964377×10 -6 ×t 5 +2.57935305595126×10 -5 ×t 4 +2.49144464576113×10 -5 ×t 3 –2.4027009676927×10 -3 ×t 2 +1.49270472208×10 -2 ×t–2.275619827647×10 -4

[0199] Calculate the numerical solution of the fourth derivative y″″ = 0 of the above function, and obtain t. c =3.23, and its fifth derivative y″″′ = –1.046 × 10 -4 <0|t=t c and 0≤t c ≤43, the evaluation result t is obtained. c =3.23d.

[0200] In addition, the numerical solution of the third derivative y″′=0 of the above function is calculated, and t is obtained. m =10.82, and its fourth derivative y″″ = –1.034 × 10 -4 <0|t=t m and 0≤t m ≤43 and t m ≥t c The evaluation result t was obtained. m =10.82d.

[0201] Example 8

[0202] Curve fitting was performed on the scatter plot of Example 4. The biodegradation rate was smoothed using a moving average with an asymmetric window size of 5 on the left and 0 on the right. All regions in the scatter plot containing at least 9 consecutive data points were enumerated, and a seventh-order polynomial was used to fit curves to each region, with the corresponding adjusted coefficient of determination calculated. The power exponent q is 4.3. This was calculated to be... The largest region corresponds to the data point set from day 8 to day 41, and the corresponding curve fitting function is:

[0203] y opt =–2.5769287835971×10 -10 ×t 7 +4.25488871943111×10 -8 ×t 6 –2.85184431054741×10 -6 ×t 5 +9.94195953264661×10 -5 ×t 4 –1.92563121420163×10 -3 ×t 3 +2.08317308296463×10 -2 ×t 2 –0.122261153002679×t+0.295607262189315

[0204] Calculate the numerical solution of the fourth derivative y″″ = 0 of the above function, and obtain t. c =14.08, and its fifth derivative y″″′ = –3.960 × 10 -5 <0|t=t c and 8≤t c ≤41, the evaluation result t is obtained. c =14.08d.

[0205] In addition, the numerical solution of the third derivative y″′=0 of the above function is calculated, and t is obtained. m =18.71, and its fourth derivative y″″ = –7.250 × 10 -5 <0|t=t m and 8≤t m ≤41 and t m ≥t c The evaluation result t was obtained. m =18.71d.

[0206] Example 9

[0207] Curve fitting was performed on the scatter plot of Example 2. The biodegradation rate was smoothed using a moving average with an asymmetric window size of 5 on the left and 0 on the right. All regions in the scatter plot containing at least 9 consecutive data points were enumerated, and a seventh-order polynomial was used to fit curves to each region, with the corresponding adjusted coefficient of determination calculated. The power exponent q is 4.3. This was calculated to be... The largest region corresponds to the data point set from day 7 to day 43, and the corresponding curve fitting function is:

[0208] y opt =–1.54973697579025×10 -10 ×t 7 +2.65288276838355×10 -8 ×t 6 –1.84389912310913×10 -6 ×t 5 +6.67838031167046×10 -5 ×t 4 –1.3447863653956×10 -3 ×t 3 +1.4938963890991×10 -2 ×t 2 –8.64165479378314×10 -2 ×t+0.192275886400494

[0209] Calculate the numerical solution of the fourth derivative y″″ = 0 of the above function, and obtain t. c =14.72, and its fifth derivative y″″′ = –2.475 × 10 -5 <0|t=t c and 7≤t c ≤43, the evaluation result t is obtained. c =14.72d.

[0210] In addition, the numerical solution of the third derivative y″′=0 of the above function is calculated, and t is obtained. m =19.87, and its fourth derivative y″″ = –4.436 × 10 -5 <0|t=t m and 7≤t m ≤43 and t m ≥t c The evaluation result t was obtained. m =19.87d.

[0211] Example 10

[0212] An aerobic biodegradability test was conducted on poly(L-lactic acid) resin #2 according to ISO 14855-1 "Determination of the ultimate aerobic biodegradability of plastic materials under controlled composting conditions - Method by analysis of evolved carbon dioxide - Part 1: General method". α-cellulose powder was used as a reference material, and the test was conducted under low-light conditions at a temperature of 58℃±2℃. The cumulative carbon dioxide gas release in each digestion container was recorded daily, and the relative biodegradability of the test material was calculated.

[0213] To plot the relative biodegradation rate against time, see [reference]. Figure 5 The biodegradation rate was smoothed by a symmetrical moving average with a window size of 3. All regions containing at least nine consecutive data points in the scatter plot were enumerated, and each region was fitted with an eighth-order polynomial, with the corresponding adjusted coefficient of determination calculated. The power exponent q is 4.1. This was calculated to be... The largest region corresponds to the data point set from day 5 to day 44, and the corresponding curve fitting function is:

[0214] y opt =1.08744054080412×10 -11 ×t 8 –2.23313309027131×10 -9 ×t 7 +1.89409483694555×10 -7 ×t 6 –8.57698250746627×10 -6 ×t 5+2.23642446024907×10 -4 ×t 4 –3.37294974365525×10 -3 ×t 3 +2.80980694262728×10 -2 ×t 2 –0.117256233421027×t+0.155604023098694

[0215] Calculate the numerical solution of the fourth derivative y″″ = 0 of the above function, and obtain t. c =11.67, and its fifth derivative y″″′ = –8.796 × 10 -5 <0|t=t c and 5≤t c ≤44, the evaluation result t is obtained. c =11.67d.

[0216] In addition, the numerical solution of the third derivative y″′=0 of the above function is calculated, and t is obtained. m =16.76, and its fourth derivative y″″ = –1.186 × 10 -4 <0|t=t m and 5≤t m ≤44 and t m ≥t c The evaluation result t was obtained. m =16.96d.

[0217] Example 11

[0218] Curve fitting was performed on the scatter plot of Example 4. All regions in the scatter plot containing at least 11 consecutive data points were exhaustively enumerated, and curve fitting was performed on each region using a ninth-order polynomial. The corresponding adjustment coefficient of determination was then calculated. The power exponent q is 3.9. This was calculated to be... The largest region corresponds to the data point set from day 7 to day 45, and the corresponding curve fitting function is:

[0219] y opt =7.93333220564456×10 -13 ×t 9 –1.69813332245602×10 -10 ×t 8 +1.54177228820223×10 -8 ×t 7 –7.7606617848566×10 -7 ×t 6+2.38084116990179×10 -5 ×t 5 –4.62533941987951×10 -4 ×t 4 +5.74258346258761×10 -3 ×t 3 –4.43585148321059×10 -2 ×t 2 +0.189852894002362×t–0.347515045877234

[0220] Calculate the numerical solution of the fourth derivative y″″ = 0 of the above function, and obtain t. c =14.27, and its fifth derivative y″″′ = –2.351 × 10 -5 <0|t=t c and 7≤t c ≤45, the evaluation result t is obtained. c =14.27d.

[0221] In addition, the numerical solution of the third derivative y″′=0 of the above function is calculated, and t is obtained. m =18.28, and its fourth derivative y″″ = –8.249 × 10 -5 <0|t=t m and 7≤t m ≤45 and t m ≥t c The evaluation result t was obtained. m =18.28d.

[0222] As can be seen from Examples 1 to 11, the method of the present invention, by fitting the biodegradability or relative biodegradability curve to a function of at least fifth order differentiability and calculating and analyzing the adjusted coefficient of determination, can transform the "coarse" raw data reflecting the initial aerobic degradation characteristics of biodegradable plastics into a precise mathematical function. This mathematical function can then be used to explicitly define and calculate the output result that reflects the corresponding degradation characteristics of the biodegradable plastic. Furthermore, it is believed that when the method according to the present invention uses the same continuously differentiable function to fit the biodegradability collected under the same test conditions, along with optionally other identical data preprocessing procedures, and employs an adjusted coefficient of determination with the same power exponent, i.e. Then, based on the output evaluation result, such as t c or t m It can be used to compare the overall degradation resistance of different plastics. Among them, t cThis can be understood as the critical moment when the outermost layer of the test material, directly in contact with the biodegradation test environment, begins to biodegrade (the molecular weight of the plastic decreases to a level that can be digested and decomposed by microorganisms through chemical degradation). m This can be understood as the critical moment when the surface plastic of the test material begins to biodegrade. It is believed that t c and / or t m The larger the value, the better the plastic's resistance to chemical degradation.

Claims

1. A method for analyzing and evaluating the anti-degradation properties of plastics based on the fitting and differentiation method of aerobic biodegradation test results under controlled composting conditions, characterized in that, It includes the following steps: (1) Conduct an aerobic biodegradation experiment on plastics under controlled composting conditions and obtain the results of the experiment. Wherein, the biodegradability or relative biodegradability (%) of the plastic at each time point t is denoted as D. t ; (2) Draw a scatter plot selected from the following. (a)D t A scatter plot relative to t, or (b) D t Preprocessing Then draw the preprocessed... Scatter plot relative to t; (3) Perform curve fitting on the scatter plot in step (2). Specifically, all possible regions containing at least 7 consecutive data points are selected from the scatter plot, and a continuously differentiable function is used to perform curve fitting on the consecutive data points of each region to obtain a curve fitting function for each region. The fitting function for the j-th region is denoted as y. j =f j (t)|t∈[t A,j ,t B,j ], Here, the size or number of consecutive data points in the j-th region is denoted as m. j , and m j ≥7, t A,j Let t be the starting time point of the j-th region. B,j Let j be the end time point of the j-th region, and the continuously differentiable function is selected from functions that are differentiable to at least the fifth order. (4) Obtain the curve fitting result with the best fit from the curve fitting function in step (3). Apply the following equation 1 to each y j Calculate the adjusted coefficient of determination, Adj, separately. in, m represents the coefficient of determination of the curve fitting function for each of the aforementioned regions. j As defined in step (3); k is the number of free parameters in the fitted function; m j -k>0; the exponent q is 2.0 to 7.0, and From the various Adj. The maximum value is selected from the set, and the curve fitting function corresponding to the maximum value is constrained to be the curve fitting result with the best fit, denoted as y. opt =f opt (t)|t∈[t A,opt ,t B,opt ]; (5) Analyze the curve fitting results of the best fit in step (4). Calculate y opt By taking the fourth derivative y″″ and the fifth derivative y″″′, we can obtain the time t corresponding to y″″ = 0 and y″″′ < 0. c , where t c The solution is a real number and satisfies t A,opt ≤t c ≤t B,opt ;and (6) Output the evaluation results. The evaluation result includes the parameter t obtained in step (5). c .

2. The method according to claim 1, characterized in that, In step (5), when there are at least two t values ​​that satisfy the condition... c If the solution is the minimum value, then the solution with the minimum value is taken.

3. The method according to claim 1, characterized in that, In step (5), y is also calculated. opt By taking the third derivative y″′ and the fourth derivative y″″, we can obtain the time t corresponding to y″′=0 and y″″<0. m , where t m The solution is a real number and satisfies t A,opt ≤t m ≤t B,opt , and t m ≥t c And the evaluation results in step (6) further include t m .

4. The method according to claim 3, characterized in that, In step (5), when there are at least two t values ​​that satisfy the condition... m If the solution is the minimum value, then the solution with the minimum value is taken.

5. The method according to claim 3, characterized in that, In step (5), y is also calculated. opt The second derivative y″ is obtained by taking y″ at time t. c The value of time y″ c , and / or get y″ in t m The value of time y″ m Furthermore, the evaluation results in step (6) also include y″ c and / or y″ m .

6. The method according to claim 1, characterized in that, In step (3), the continuously differentiable function is selected from functions that are differentiable by at least the sixth order.

7. The method according to claim 6, characterized in that, In step (3), the continuously differentiable function is a seventh, eighth, or ninth order differentiable function.

8. The method according to any one of claims 1 to 7, characterized in that, The aerobic biodegradation experiment in step (1) was conducted under constant temperature of 58℃±2℃ and in darkness or low light conditions.

9. The method according to any one of claims 1 to 7, characterized in that, The time mentioned in step (1) is in minutes (m), hours (h) or days (d).

10. The method according to any one of claims 1 to 7, characterized in that, The preprocessing in step (2) is a smoothing process.

11. The method according to claim 10, characterized in that, The smoothing process is a moving average smoothing.

12. The method according to claim 11, characterized in that The following equation 2 will be used to convert D in step (2) t Shift smoothing is the pre-processed decomposition rate. Where i is the position of the smoothed data point; p is the total number of time points of the decomposition rate before preprocessing; for The i-th preprocessed decomposition ratio in the equation; g is the size of the left smoothing window excluding data point i; h is the size of the right smoothing window excluding data point i; g or h is independently an integer of 0, 1, 2, 3 or larger, where g and h are not both 0; u is the value of each D within the smoothing window. t Location; D u D is at position u within the smooth window. t .

13. The method according to claim 12, characterized in that, Where g = h = 1 or where g ≠ 0 and h = 0.

14. The method according to claim 12, characterized in that, Where g = 5 and h = 0.

15. The method according to any one of claims 1 to 7, characterized in that, m in step (3) j It must be at least 8.

16. The method according to any one of claims 1 to 7, characterized in that, m in step (3) j The minimum is 15.

17. The method according to any one of claims 1 to 7, characterized in that, m in step (3) j It should be at least 20.

18. The method according to any one of claims 1 to 7, characterized in that, In step (3) t A,j For at least the 6th hour.

19. The method according to any one of claims 1 to 7, characterized in that, In step (3) t A,j It must be at least the 3rd day.

20. The method according to any one of claims 1 to 7, characterized in that, In step (3) t A,j For at least the 30th day.

21. The method according to any one of claims 1 to 7, characterized in that, In step (3) t A,j It will be at most the 12th hour.

22. The method according to any one of claims 1 to 7, characterized in that, In step (3) t A,j It will be at most the 30th day.

23. The method according to any one of claims 1 to 7, characterized in that, In step (3) t A,j It will be at most the 90th day.

24. The method according to any one of claims 1 to 7, characterized in that, In step (3) t B,j For at least 48 hours.

25. The method according to any one of claims 1 to 7, characterized in that, In step (3) t B,j It must be at least 60 days.

26. The method according to any one of claims 1 to 7, characterized in that, In step (3) t B,j It must be at least 120 days.

27. The method according to any one of claims 1 to 7, characterized in that, The continuously differentiable function in step (3) is selected from polynomial functions, Boltzmann functions, or Bézier curves.

28. The method according to any one of claims 1 to 7, characterized in that, The continuously differentiable function in step (3) is a polynomial function.

29. The method according to any one of claims 1 to 7, characterized in that, The continuously differentiable function in step (3) is a polynomial function represented by the following equation 3. y = a n ×t n +a n-1 ×t n-1 +...+a2×t 2 Equation 3: +a1×t+a0 Where n is the order of the polynomial function, and a0 to a n Let be the coefficients of the terms of the polynomial function. The polynomial is a fifth, sixth, seventh, eighth, or ninth degree polynomial function, or a higher degree polynomial function.

30. The method according to claim 29, characterized in that, The polynomial is a seventh-degree polynomial function.

31. The method according to claim 29, characterized in that, The size and number of consecutive data points m in step (3) j It is at least the order of the polynomial function plus 2.

32. The method according to claim 29, characterized in that, The size and number of consecutive data points m in step (3) j It must be at least the order of the polynomial function plus 10.

33. The method according to claim 29, characterized in that, The size and number of consecutive data points m in step (3) j It must be at least the order of the polynomial function plus 20.

34. The method according to claim 29, characterized in that, In adjusting the coefficient of determination in step (4), the number of free parameters in the fitting function is equal to the order of the curve fitting function defined in step (3) + 1.

35. The method according to claim 29, characterized in that, The continuously differentiable function in step (3) is: 1) A quintic polynomial function, wherein the coefficient of determination Adj of the quintic polynomial function is adjusted in step (4). The power exponent q in the equation is between 4.0 and 7.0; or 2) A sixth-degree polynomial function, wherein the coefficient of determination Adj of the sixth-degree polynomial function is adjusted in step (4). The power exponent q in the equation is between 3.0 and 6.5; or 3) A seventh-degree polynomial function, wherein the coefficient of determination Adj of the seventh-degree polynomial function is adjusted in step (4). The power exponent q in the equation ranges from 2.5 to 6. or 4) An octet polynomial function, wherein the coefficient of determination Adj of the octet polynomial function is adjusted in step (4). The power exponent q in the equation ranges from 2.0 to 5.5; or 5) A ninth-degree polynomial function, wherein the coefficient of determination Adj of the ninth-degree polynomial function is adjusted in step (4). The power exponent q in the equation ranges from 2.0 to 5.

5.

36. The method according to claim 35, characterized in that, The continuously differentiable function in step (3) is: 1) A quintic polynomial function, wherein the coefficient of determination Adj of the quintic polynomial function is adjusted in step (4). The power exponent q in the equation is between 5.0 and 7.0; or 2) A sixth-degree polynomial function, wherein the coefficient of determination Adj of the sixth-degree polynomial function is adjusted in step (4). The power exponent q in the equation is between 3.6 and 5.6; or 3) A seventh-degree polynomial function, wherein the coefficient of determination Adj of the seventh-degree polynomial function is adjusted in step (4). The power exponent q in the equation is between 3.3 and 5.3; or 4) An octet polynomial function, wherein the coefficient of determination Adj of the octet polynomial function is adjusted in step (4). The power exponent q in the equation is between 3.1 and 5.1; or 5) A ninth-degree polynomial function, wherein the coefficient of determination Adj of the ninth-degree polynomial function is adjusted in step (4). The power exponent q in the equation ranges from 2.9 to 5.

9.

37. The method according to claim 29, characterized in that, The continuously differentiable function in step (3) is: 1) A quintic polynomial function, wherein the coefficient of determination Adj of the quintic polynomial function is adjusted in step (4). The exponent q in the equation is 4.0, 4.5, 5.0, 5.5, 6.0, 6.5, or 7.0; or 2) A sixth-degree polynomial function, wherein the coefficient of determination Adj of the sixth-degree polynomial function is adjusted in step (4). The power exponent q in the equation is 4.0, 4.2, 4.4, 4.6, 4.8, 5.0, or 5.2; or 3) A seventh-degree polynomial function, wherein the coefficient of determination Adj of the seventh-degree polynomial function is adjusted in step (4). The power exponent q in the equation is 3.7, 3.9, 4.1, 4.3, 4.5, 4.7, or 4.9; or 4) An octet polynomial function, wherein the coefficient of determination Adj of the octet polynomial function is adjusted in step (4). The power exponent q in the equation is 3.5, 3.7, 3.9, 4.1, 4.3, 4.5, or 4.7; or 5) A ninth-degree polynomial function, wherein the coefficient of determination Adj of the ninth-degree polynomial function is adjusted in step (4). The power exponent q in the equation is 3.3, 3.5, 3.7, 3.9, 4.1, 4.3, or 4.

5.

38. A system for evaluating the degradation resistance of plastics, characterized in that, The system employs the method described in any one of the preceding claims.

39. A computer device, characterized in that, It includes: processor; and Memory, used to store executable instructions; The processor is configured to read from the memory and execute the executable instructions to implement the method as described in any one of claims 1 to 37.

40. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed by a processor, causes the method according to any one of claims 1 to 37 to be implemented.

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