A method for analyzing and evaluating the anti-degradation performance of plastics based on the fitting derivative method of high-solid anaerobic biodegradation test results

Abstract

The present invention relates to a method for analyzing and evaluating the degradation resistance of plastics based on a fitting and derivative method of high-solid anaerobic biodegradation test results. The method comprises: conducting a high-solid anaerobic biodegradation test on the plastic to obtain the test results; plotting a scatter plot of biodegradation rate versus time; selecting segments from the scatter plot and performing curve fitting using a function that is at least fifth-order continuously differentiable, selecting the curve fitting result with the best fit for subsequent analysis and calculation; and obtaining the time corresponding to when the third and / or fourth derivatives of the curve are zero and the fourth and / or fifth derivatives of the curve are negative, and / or the second derivative of the curve at that time as the output of the method. The method can quantitatively describe the critical point of transition between chemical degradation involving non-microbial participation and biodegradation involving microorganisms in the early and middle stages of the high-solid anaerobic biodegradation test, and can be used to quantitatively evaluate the hydrolysis resistance or hydrolysis resistance of plastics of different types, processes, formulations, and batches.

Description

Technical Field

[0001] The invention belongs to the technical field of polymer material analysis, and in particular relates to a method for evaluating the anti-degradation performance of plastics, and also relates to a system, equipment and medium thereof adopting the method. Background Art

[0002] The invention and use of plastics have greatly facilitated people's lives, but at the same time have also caused serious environmental pollution. Biodegradable polymer materials represented by polylactic acid and polybutylene adipate terephthalate are committed to solving the problem of plastic / microplastic pollution. In addition, in the engineering field, high-performance polymer materials represented by polyamide are also increasingly widely used. However, most of the above materials are hydrolyzable, that is, they meet the necessary conditions for hydrolysis. For example, the ester bond (-COO-) in polyester materials and the amide bond (-CO-NH-) in polyamide materials can undergo hydrolysis in the presence of water and catalysts, resulting in a significant decrease in the molecular weight of the polymer and a rapid deterioration of the material properties. Therefore, scientifically and reliably characterizing and evaluating the hydrolysis resistance or hydrolysis resistance of plastics is an important means to ensure the large-scale promotion and application of such plastics, and is of great significance.

[0003] At present, some characterization and analysis techniques have been developed to evaluate properties related to plastic degradation. For example, visual observation, weight loss weighing, mechanical property evaluation, molecular weight evaluation, melt index evaluation, etc. can reflect the degree of degradation of the tested plastic at a certain moment to a certain extent, but each has its own defects. For example, the visual observation method requires a high time cost to make the sample achieve visible degradation, and the results are somewhat subjective; the weight loss weighing method cannot measure short-term degradation fluctuations and cannot reflect the impact of rapid changes in process parameters on the degradation rate of plastics; the mechanical property evaluation method cannot be used to test plastics that are broken during the degradation process; the molecular weight evaluation method requires the use of advanced chromatographic instruments to separate and characterize polymer chains of different molecular weights during the degradation process, which places high demands on testing instruments and testers; the melt index evaluation method measures the comprehensive properties of a mixture of degraded and undegraded polymers. In particular, the effect of a small amount of degraded polymers on the overall melt index in the early stages of degradation may be lower than the accidental error of the method, and accurate results cannot be obtained. As is known in the art, these prior art testing and evaluation methods are often destructive to the samples being tested. Consequently, they require numerous parallel sample tests to determine temporal trends in relevant properties. These methods place high demands on the samples, personnel, equipment, and environment used for testing, and exhibit poor test repeatability. Furthermore, these methods are generally insensitive to initial or minor degradation of plastics, and are unable to accurately and accurately reflect the degradation resistance (e.g., hydrolysis resistance) of the tested plastic.

[0004] Therefore, there is still a need to develop characterization and analytical methods for evaluating the degradation properties of plastics that can achieve a simple test and analysis process without relying on a large number of parallel sample tests. More ideally, the method should be able to sensitively and accurately reflect the hydrolysis resistance or hydrolysis resistance of plastics.

[0005] The present inventors unexpectedly discovered that by analyzing the results of high-solid anaerobic biodegradation tests that characterize plastics known in the art, the critical transition time point (i.e., critical point) in the early, middle, or early stages of the test, which transitions from a chemical degradation process involving no microorganisms (i.e., the hysteresis stage) to a biochemical process involving microorganisms (i.e., the biodegradation stage), can be obtained. The numerical value of this critical point reflects the precise information on the length of time or speed required for the plastic to decompose to a molecular weight level that can be digested and absorbed by microorganisms under anaerobic digestion conditions. This can address the deficiencies of the above-mentioned prior art and can further serve as an indicator parameter for evaluating the hydrolysis resistance or hydrolysis resistance of plastics. Summary of the Invention

[0006] One object of the present invention is to overcome at least one shortcoming of the prior art, and in particular to provide a method for evaluating the anti-degradation performance of plastics. The method analyzes the results of the high-solid anaerobic biodegradation test of plastics based on the curve fitting derivation method. The method can quantitatively describe the critical point of transition between chemical degradation involving non-microbial participation (mainly hydrolysis reaction) and biological decomposition behavior involving microorganisms in the early, middle or early stages of the high-solid anaerobic biodegradation test of plastics, thereby being used to evaluate the anti-hydrolysis or hydrolysis resistance of plastics (especially hydrolyzable plastics such as polyesters and polyamides) of different types, processes, formulas, and batches.

[0007] According to one aspect of the present invention, a method for analyzing and evaluating the anti-degradation performance of plastics based on the fitting derivative method of high-solid anaerobic biodegradation test results is provided, characterized in that it includes the following steps:

[0008] (1) conducting a high-solid anaerobic biodegradation test on plastics and obtaining the results of the test;

[0009] The test is carried out under high solids anaerobic digestion conditions, and the biodegradation rate or relative biodegradation rate (%) of the plastic at each time point t is recorded as D t ;

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

[0011] (a)D t a scatter plot of the points against 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] wherein 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 continuous data points of each segment to obtain curve fitting functions for each region;

[0015] The fitting function of the jth region is denoted as y j =f j (t)|t∈[t A,j ,t B,j ],

[0016] The size or number of continuous data points in the jth region is recorded as m j , and m j ≥7, t A,j is the starting time point of the jth region, t B,j is the end time point of the j-th region, and wherein the continuously differentiable function is selected from at least a fifth-order differentiable function, particularly preferably from at least a sixth-order differentiable function, for example, a seventh-order, eighth-order or ninth-order differentiable function;

[0017] (4) Obtaining a curve fitting result with the best fitting degree from the curve fitting function of step (3),

[0018] Each y is calculated by the following equation 1 j Calculate the adjusted coefficient of determination separately, namely

[0019]

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

[0021] From the various The maximum value is selected from the above equations, and the curve fitting function corresponding to the maximum value is limited to the curve fitting result with the best fitting degree, which is recorded 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 The fourth-order derivative y″″ and the fifth-order derivative y″″′ are obtained, and the time t corresponding to y″″=0 and y″″′<0 is obtained. c , where t c is a real number solution and satisfies t A,opt ≤t c ≤t B,opt , optionally, when there are at least 2 t that meet the above conditions c Solution, then take the minimum solution,

[0024] Optionally, additionally calculate y opt The third-order derivative y″′ and the fourth-order derivative y″″ are obtained, and the time t corresponding to y″′=0 and y″″<0 is obtained. m , where t m is a real number solution and satisfies t A,opt ≤t n ≤t B,opt , and t m ≥t c , optionally, when there are at least 2 t that meet the above conditions m Solution, then take the minimum solution,

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

[0026] (6) Output the evaluation results,

[0027] The evaluation results include the t obtained in step (5) c and preferably additionally comprises t m , optionally further comprising 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 adopts the method of the present invention.

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

[0030] processor; and

[0031] a memory for storing executable instructions;

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

[0033] According to yet another aspect of the present invention, a computer-readable storage medium is provided, characterized in that the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described above is implemented. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0035] Figure 2 The figure is a scatter plot of the relative biodegradation rate of Example 2 versus time.

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

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

[0038] Figure 5 : is a scatter plot of the relative biodegradation rate of Example 6 versus time.

[0039] Figure 6 : is a scatter plot of the biodegradation rate of Example 9 versus time. DETAILED DESCRIPTION

[0040] The present invention is described in more detail in the following paragraphs. Unless explicitly stated otherwise, each aspect of description may be combined with any other one or more aspects. In particular, any feature indicated as preferred may be combined with any other one or more features indicated as preferred.

[0041] The recitation of numerical endpoints includes all numbers and fractions within the corresponding range, as well as the recited endpoints. It should be noted that in specifying any range of numerical values, any particular upper value can be associated with any particular lower value.

[0042] All references cited in this specification are hereby incorporated by reference in their entirety.

[0043] In the context of the present invention, unless otherwise defined, all terms used in the present invention, including technical and scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which the present invention belongs.

[0044] As used herein, the terms "comprising" and "consisting of" are synonymous with "including" or "containing" and are inclusive or open-ended and do not exclude additional, unrecited ingredients, components, or process steps.

[0045] The term "degradation" or "decomposition" as used herein refers to the significant change in the chemical structure of a plastic under specific environmental conditions, resulting in the loss of certain properties. It can be any process that can result in a decrease in the molecular weight of a polymer or the conversion of a long-chain structure into a shorter-chain low-molecular substance.

[0046] There are three main possible ways of degradation of plastics, depending on the process that occurs, namely biodegradation, chemical degradation and physicochemical degradation.

[0047] As used herein, the term "biodegradation" refers to the process by which plastics, acting as a nutrient source for microbial life, are digested and absorbed by organisms such as bacteria, fungi, and certain algae, transforming them into simpler compounds and ultimately into small molecules such as methane, carbon dioxide, and water. For example, the degradation of biodegradable plastics relies on biological processes that utilize the carbon-containing substances present in the plastics as a nutrient source for microorganisms.

[0048] As used herein, the term "chemical degradation" refers to the process by which plastics degrade through oxidative degradation, photodegradation, or hydrolysis, including oxidatively degradable plastics, photodegradable plastics, and hydrolytically degradable plastics. Specifically, chemical degradation in the present invention refers to the degradation process before plastics can be digested and absorbed by organisms. As known to those skilled in the art, the high-solid anaerobic biodegradation test of the present invention is conducted under anaerobic, aqueous conditions in the dark or low light, and therefore the chemical degradation involved is primarily hydrolytic degradation.

[0049] As used herein, the term "physicochemical degradation" refers to the process by which plastics degrade under the influence of physical fields such as heat, electric fields, and stress. Specifically, physicochemical degradation in this context refers to the degradation of plastics before they can be digested and absorbed by organisms. As known to those skilled in the art, the high-solid anaerobic biodegradation test described herein is conducted under anaerobic, aqueous conditions in darkness or low light at suitable temperatures, thus minimizing the physicochemical degradation effects involved.

[0050] It is known in the art that the degradation rate of plastics is affected by numerous factors, including environmental factors such as temperature, humidity, pH, chemical media, and light exposure, as well as factors inherent to the plastic itself, such as the polymer's primary, secondary, and tertiary structures, molecular weight and distribution, as well as composition, interfacial structure, physical morphology, porosity, and impurities. One objective of the present invention is to demonstrate the comprehensive anti-degradation properties of plastics through the methods of the present invention.

[0051] As used herein, the term "high-solid anaerobic biodegradation test" refers to a test for determining the ultimate anaerobic biodegradability of plastics under high-solid anaerobic digestion conditions or high-solid composting conditions according to methods known in the art, typically employing a method for analyzing and measuring the amount of biogas released. By observing the temporal trend of the biodegradation rate or relative biodegradation rate, it can be found that the initial degradation stage has zero or even negative decomposition rates, which is referred to as the "hysteresis phase." Related research has found (Handbook of Biodegradable Polymers, Edited by Abraham J. Domb, Joseph Kost and David M. Wiseman, published in 1997 by CRC Press, pp. 451-453) that, during the hysteresis phase, plastics, under the influence of factors such as water, temperature, pH, and chemical substances, can undergo chemical degradation (such as hydrolysis, oxidative degradation, and photodegradation) prior to biodegradation, resulting in changes in their chemical structure. For example, before anaerobic biodegradation begins, polylactic acid first needs to undergo a hydrolysis reaction to break ester bonds and reduce its molecular weight (Synthetic Biodegradable and Biobased Polymers, 2024, Volume 293, ISBN: 978-3-031-45861-3, edited by Andreas Künkel, Glauco Battagliarin, Malte Winnacker, Bernhard Rieger, Geoffrey Coates, 2024, p74-75). When the molecular weight drops to a certain threshold, such as below 10 kDa, its oligomers or monomers become water-soluble and can be digested and absorbed by microorganisms (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 anaerobic microorganisms, its oligomers or monomers can be further broken down into small molecules until they are ultimately decomposed into carbon dioxide, methane, and water.

[0052] As is known in the art, in this high-solids anaerobic biodegradation test, the cumulative biogas production (methane and carbon dioxide) is calculated by continuously monitoring and periodically measuring the production of biogas (methane and carbon dioxide) in the test and blank containers. The biodegradation rate is the ratio of the actual biogas release of the plastic test material to the measured or calculated total organic carbon content of the material. It is known to those skilled in the art that the high-solid anaerobic biodegradation test of plastic test materials can be carried out according to the following standards: GB / T 33797 "Plastics—Determination of the ultimate anaerobic biodegradation under high-solids anaerobic-digestion conditions—Method by analysis of released biogas", ISO 15985, ASTM D5511 "Standard Test Method for Determining Anaerobic Biodegradation of Plastic Materials Under High-Solids Anaerobic-Digestion Conditions", EN ISO 15985, BS EN ISO 15985, DIN EN ISO 15985 or KS TISO 15985.

[0053] The "biodegradation rate" used in the present invention can be determined according to methods known in the art. For example, the biodegradation rate of the plastic test material can be calculated according to the following equation in GB / T 33797:

[0054]

[0055] Among them, m C,g is the amount of carbon released from the digester gas, in grams (g), m C,i is the initial carbon content of the test material, in grams (g). The same equation applies to the biodegradation rate of the reference material.

[0056] The "relative biodegradability" used in the present 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 are the plastic and the reference material at each time point {t i |i=1,2,3,...,p}Biodegradation rate (%).

[0059] The term "digestion vessel" as used herein refers to a vessel known in the art for use in high-solid anaerobic biodegradation tests. The digestion vessel can typically comprise a tightly connected glass container or Erlenmeyer flask to prevent gas loss. The digestion vessel can include a container containing a test material, a container containing a reference material, or a blank container.

[0060] The term "plastic" as used herein refers to all types of plastics generally known in the art, in particular plastics that can be used in high-solid anaerobic biodegradation tests, such as plastics that can be used in high-solid anaerobic biodegradation tests according to the seven standards mentioned above. Such plastics may include, but are not limited to, all polymer compounds containing chemical bonds such as ester bonds, anhydride bonds (-RCOOOC-), orthoester bonds (-OCOR'R"OR-), carbonate bonds (-ROCOO-), phosphate bonds (-OPOR'OOR-), ketal bonds (-OCR'R"OR-), acetal bonds (-OCHR'OR-), imino-carbonate bonds (-ROCNHO-), peptide bonds / amide bonds (-CONH-), and / or phosphazene bonds (-RR'P=N-) in the polymer main chain or side chain skeleton structure.

[0061] The term "critical point" or "critical transition time point" as used herein refers to the critical state of transition from a chemical degradation process (such as hydrolytic degradation, etc.) in which no microorganisms participate to a biochemical process (biodegradation stage) in which microorganisms participate. The critical point is defined in the present invention as the time at which the chemical degradation process (such as hydrolytic degradation, etc.) in which the chemical degradation process (such as biodegradation, etc.) in which the chemical degradation process (such as hydrolytic degradation, etc.) participates is the critical state of transition from a chemical degradation process (such as hydrolytic degradation, etc.) in which no microorganisms participate c or t m .

[0062] The term "coefficient of determination" or "R 2 " is a statistical indicator known to those skilled in the art for determining the correlation between the fitted curve and the selected data points. 2 is defined as follows:

[0063]

[0064] In this paper, TSS is the total sum of squares, SSE is the sum of squared errors, and y iis the measured value or smoothed value of the biodegradation test data point set in the selected fitting area, y i The arithmetic mean of The regression value is obtained by corresponding calculation after curve fitting of the biodegradation test data point set in the selected fitting area.

[0065] The term "Adjusted Coefficient of Determination" or "Adj.R" is used in this paper. 2 ” refers to the “coefficient of determination” or “R 2 "Introducing adjustment coefficient based on It can penalize the error level of the object fitting with a too small set of data points. For example, Adj.R 2 It can be defined as follows:

[0066]

[0067] Among them, R 2 is the coefficient of determination of the curve fitting function of 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; and the power exponent q is 2.0 to 7.0.

[0068] As used herein, the term "free parameter" refers to the number of parameters in a fitting function that can vary independently without affecting the basic structure or constraints of the function. For example, if the fitting function is a polynomial, the number of free parameters of the function is equal to the polynomial order + 1. For example, a seventh-order polynomial has an order of 7, and thus a total of 8 free parameters.

[0069] As used herein, the term "best fit" refers to the curve fitting function or result having the highest correlation with the data points being fitted. In particular, in the present invention, when the "adjusted coefficient of determination" is maximized, the corresponding curve fitting function can be the curve fitting result with the best fit.

[0070] The plastic test material used in the present invention may be in the form of a film, granules, powder, or a simple shape (e.g., dumbbell shape) known in the art for high-solid anaerobic biodegradation tests, preferably in the form of granules or powder, more preferably in the form of granules, such as plastic masterbatch. Generally, the maximum surface area of ​​each test material should not exceed 4 cm 2 , wherein if the size of the test material element exceeds the maximum surface area, the size may be reduced to meet the requirement. For example, the test material may be in the form of particles having a diameter of about 1 cm or less, such as particles having 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 less.

[0071] The term "preprocessing" used in the present invention refers to a data preprocessing method generally known in the art for data reprocessing, and its main tasks generally include data cleaning, data integration, data conversion, data reduction, etc. Common data preprocessing methods include denoising, missing value processing, outlier processing, and baseline correction processing. The term "smoothing" used in the present invention refers to a data preprocessing method known in the art to eliminate noise in the data and thus highlight the trend in the data. Those skilled in the art can perform smoothing by methods known in the art, such as moving average smoothing (MA), Savitzky-Golay smoothing (also known as convolution smoothing), Whittaker smoothing, etc. In addition to methods based on smoothing denoising, those skilled in the art can also perform data preprocessing by methods known in the art such as modeling denoising (such as Wiener Filtering, deep learning, etc.) or decomposition denoising (such as Fourier Transform, Wavelet Transform, Variational Mode Decomposition, etc.) to eliminate noise in the data and thus highlight the trend in the data.

[0072] According to one aspect of the present invention, a method for analyzing and evaluating the anti-degradation performance of plastics based on the fitting derivative method of high-solid anaerobic biodegradation test results is provided, characterized in that it includes the following steps:

[0073] (1) conducting a high-solid anaerobic biodegradation test on the plastic and obtaining the test results, which include the biodegradation rate or relative biodegradation rate at each time point;

[0074] (2) draw a scatter plot of the decomposition rate of step (1) versus time;

[0075] (3) selecting a plurality of segments containing at least 7 consecutive data points from the scatter plot of step (2), performing curve fitting on each of the segments using a function that is at least fifth-order continuously differentiable, and obtaining respective curve fitting functions;

[0076] (4) selecting a function with the best fitting degree from the curve fitting functions of step (3) as a curve fitting result; and

[0077] (5) Obtain the time corresponding to when the third-order derivative of the curve fitting result of step (4) is zero and the fourth-order derivative is negative, and / or the time corresponding to when the fourth-order derivative of the curve fitting result is zero and the fifth-order derivative is negative, and / or the second-order 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 performance of plastics based on the fitting derivative method of high-solid anaerobic biodegradation test results is provided, characterized in that it includes the following steps:

[0079] (1) conducting a high-solid anaerobic biodegradation test on plastics and obtaining the results of the test;

[0080] The test is carried out under high solids anaerobic digestion conditions, and the biodegradation rate or relative biodegradation rate (%) of the plastic at each time point t is recorded as D y ;

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

[0082] (a)D t a scatter plot of the points against 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] wherein 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 continuous data points of each segment to obtain curve fitting functions for each region;

[0086] The fitting function of the jth region is denoted as y j =f j (t)|t∈[t A,j ,t B,j ],

[0087] The size or number of continuous data points in the jth region is recorded as m j , and m j ≥7, t A,j is the starting time point of the jth region, t B,j is the end time point of the j-th region, and wherein the continuously differentiable function is selected from at least a fifth-order differentiable function, particularly preferably from at least a sixth-order differentiable function, for example, a seventh-order, eighth-order or ninth-order differentiable function;

[0088] (4) Obtaining a curve fitting result with the best fitting degree from the curve fitting function of step (3),

[0089] Each y is calculated by the following equation 1 jCalculate the adjusted coefficient of determination separately, namely

[0090]

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

[0092] From the various The maximum value is selected from the above equations, and the curve fitting function corresponding to the maximum value is limited to the curve fitting result with the best fitting degree, which is recorded 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 The fourth-order derivative y″″ and the fifth-order derivative y″″′ are obtained, and the time t corresponding to y″″=0 and y″″′<0 is obtained. c , where t c is a real number solution and satisfies t A,opt ≤t c ≤t B,opt , optionally, when there are at least 2 t that meet the above conditions c Solution, then take the minimum solution,

[0095] Optionally, additionally calculate y opt The third-order derivative y″′ and the fourth-order derivative y″″ are obtained, and the time t corresponding to y″′=0 and y″″<0 is obtained. m , where t m is a real number solution and satisfies t A,opt ≤t m ≤t B,opt , and t m ≥t c , optionally, when there are at least 2 t that meet the above conditions m Solution, then take the minimum solution,

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

[0097] (6) Output the evaluation results,

[0098] The evaluation results include the t obtained in step (5) c and preferably additionally comprises t m , optionally further comprising y″ c and / or y″ m .

[0099] In step (1) of the method of the present invention, the high-solids anaerobic biodegradation test of the plastic can be conducted according to any method known in the art, and the test results can be obtained, including the biodegradation rate or relative biodegradation rate of the plastic at each time point t. In step (1) of the method of the present invention, the validity of the results of the high-solids anaerobic biodegradation test obtained can be evaluated according to methods known in the art, for example, according to the method required by standard GB / T 33797.

[0100] According to the method of the present invention, the high-solid anaerobic biodegradation test in step (1) can be carried out under conditions of constant high temperature and darkness or weak light, and the constant high 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 high-solid anaerobic biodegradation test can be carried out under conditions of constant temperature of 52°C±2°C and darkness or weak light.

[0101] According to the method of the present invention, the time described 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 method known in the art. Typically, the moving average smoothing method can be a symmetric window moving average smoothing method or an asymmetric 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 converted into t Smoothing is the decomposition rate after preprocessing

[0104] 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 rate in the smoothing window; g is the size of the left smoothing window and does not include the data point i; h is the size of the right smoothing window and does not include the data point i; g or h are independently 0, 1, 2, 3 or a larger integer, where g and h are not 0 at the same time; u is the number of D in the smoothing window. t Position; D u is D at position u within the smoothing window t In a preferred embodiment of the present invention, in Equation 2, g=h=1. In a preferred embodiment of the present invention, in Equation 2, g≠0 and h=0, preferably, g=5 and h=0.

[0105] According to the method of the present invention, the scale of the continuous data points in step (3) is the number m j It may be at least 8, at least 9 or at least 10, preferably at least 15, particularly preferably at least 20, still more preferably at least 30 or at least 60.

[0106] According to the method of the present invention, in step (3) A,j It can 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.

[0107] According to the method of the present invention, in step (3) A,j It may be up to the 12th or 24th hour, or up to the 3rd, 6th, 10th, 15th, 30th, 60th or 90th day.

[0108] According to the method of the present invention, in step (3) B,j It may 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.

[0109] According to the method of the present invention, in step (3), the above range of t can be selected according to actual needs such as degradation conditions, material type and / or shape 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.

[0110] According to the method of the present invention, the continuously differentiable function in step (3) can be selected from the continuously differentiable function selected from at least fifth-order differentiable functions, preferably selected from at least sixth-order differentiable functions, more preferably selected from at least seventh-order differentiable functions, for example, seventh-order, eighth-order or ninth-order differentiable functions. In one embodiment of the present invention, the continuously differentiable function in step (3) can be selected from polynomial functions, Boltzmann functions or Bezier curves, preferably polynomial functions. 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.

[0111] 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 quintic polynomial function or a higher-order polynomial function, more preferably a 6th, 7th, 8th or 9th-order polynomial. Particularly preferably, the continuously differentiable function in step (3) may be a 7th-order polynomial function.

[0112] In the method of the present invention, "a" related to a continuously differentiable function refers to the same type of differentiable functions 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-order polynomial function with different coefficients.

[0113] In one embodiment, in step (4), is the coefficient of determination of the curve fitting function of each segment, specifically, m j -k>0;D tj is the biodegradation rate of the jth segment (i.e. D t ); is the D of the jth segment t The arithmetic mean of D tj The arithmetic mean of is the D of the jth segment t The regression value calculated after curve fitting in step (3).

[0114] In a preferred embodiment of the present invention, a scatter plot of the biodegradation rate of the plastic relative to t is drawn in step (2), wherein the biodegradation rate of the plastic is a smoothed biodegradation rate And in step (4) is based on The coefficient of determination of the curve fitting function obtained from the scatter plot relative to t, specifically, m j -k>0; is the smoothed biodegradation rate of the jth segment (i.e. ); For the jth segment The arithmetic mean of The arithmetic mean of For the jth segment The regression value calculated after curve fitting in step (3).

[0115] According to the method of the present invention, in step (4), the coefficient of determination can be adjusted by To analyze the fitting of the curve obtained in step (3), the coefficient of determination R 2 An adjustment factor can be introduced based on The error level of the fitting solution of the data point set that is too small is penalized and amplified, where m j -k>0;m j is the size or number of continuous data points contained in the jth segment, and m j ≥7; k is the number of free parameters in the fitting function; q is the power index in the adjustment coefficient. The maximum error analysis optimization method can obtain a continuous differentiable function with a moderate data point set size and can describe the biodegradation test data related to the biodegradation critical point region as completely and accurately as possible, such as a polynomial fitting function. The maximization principle can avoid the problem of selecting a fitting solution with too small a data set for curve fitting analysis.

[0116] 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 the following equation 3:

[0117] y=a n ×t n +a n-1 ×t n-1 +...+a2×t 2 +a1×t+a0 Equation 3

[0118] Where n is the order of the polynomial function, a0 to a n are the coefficients of the orders of the polynomial function, then in the adjusted coefficient of determination in step (4), the number k of free parameters in the fitting 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.

[0119] 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 mj It may 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, further 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.

[0120] In some embodiments of the present invention, the power exponent q in the adjustment coefficient may be 2.0 to 7.0.

[0121] In some embodiments of the present invention, the continuously differentiable function in step (3) of the method may be a fifth-order polynomial function. Preferably, the adjusted coefficient of determination of the fifth-order polynomial function in step (4) is The power exponent q in step (3) 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) may be a quintic polynomial function, and the coefficient of determination adjusted in step (4) may be The power exponent q in may be from 5.0 to 7.0, typically 5.0.

[0122] In a preferred embodiment of the present invention, the continuously differentiable function in step (3) of the method may be a sixth-order polynomial function. Preferably, the adjusted coefficient of determination of the sixth-order polynomial function in step (4) is The power exponent q in 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-order polynomial function, and the coefficient of determination adjusted in step (4) is The power exponent q in can be from 3.0 to 6.5, typically 4.6.

[0123] In a preferred embodiment of the present invention, the continuously differentiable function in step (3) of the method may be a seventh-order polynomial function. Preferably, the adjusted coefficient of determination of the seventh-order polynomial function in step (4) is The power exponent q in is 2.5 to 6.0, preferably 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-order polynomial function, and the coefficient of determination adjusted in step (4) is The power exponent q in can be from 2.5 to 6.0, typically 4.3.

[0124] In a preferred embodiment of the present invention, the continuously differentiable function in step (3) of the method may be an octave polynomial function, and preferably, the adjusted coefficient of determination of the octave polynomial function in step (4) is The power exponent q in is 2.0 to 5.5, preferably 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 octave polynomial function, and the coefficient of determination adjusted in step (4) is The power exponent q in can be from 2.0 to 5.5, typically 4.1.

[0125] In a preferred embodiment of the present invention, the continuously differentiable function in step (3) of the method may be a ninth-order polynomial function. Preferably, the adjusted coefficient of determination of the ninth-order polynomial function in step (4) is The power exponent q in is 2.0 to 5.5, preferably 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-order polynomial function, and the coefficient of determination adjusted in step (4) is The power exponent q in can be from 2.0 to 5.5, typically 3.9.

[0126] According to the method of the present invention, the y calculated in step (5) opt The third-order derivatives y″′, y opt The fourth-order derivative y″″ and y opt The second-order derivative y″ can be independently solved numerically or analytically.

[0127] In some embodiments of the present invention, in step (5), t is calculated c and / or t m If there is no real number solution or an unreasonable solution in the process, you can return to step (4) and select Select the next largest value from the equation, use the curve fitting function corresponding to the value as the new curve fitting result, and obtain its corresponding t according to step (5). c and / or t m . And so on, until we get t that meets the conditions c and / or t m The evaluation results are output.

[0128] Specifically, in step (5), t is calculated c and / or t mIf there is no real number solution or an unreasonable solution in the process, you can return to step (4) and select The second largest value is selected, and the curve fitting function corresponding to the second largest value is used as the new curve fitting result, and the corresponding t is obtained according to step (5). c and / or t m . It is still impossible to calculate t from the curve fitting function corresponding to the second largest value c and / or t m In the case of , you can return to step (4) again and select The third largest value is selected, and the curve fitting function corresponding to the third largest value is used as the new curve fitting result, and its corresponding t is obtained according to step (5). c and / or t m . And so on, until we get t that meets the conditions c and / or t m It should be noted that when calculating t according to the method of the present invention, c and t m When both are used as evaluation results, the same curve fitting results should be used to calculate t in any case. c and t m both.

[0129] In some embodiments of the present invention, the biodegradation rate or relative biodegradation rate D is obtained in step (1) of the method. t The maximum value may 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%.

[0130] In some embodiments of the present invention, the biodegradation rate or relative biodegradation rate D is obtained in step (1) of the method. t The maximum value may 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%.

[0131] In some embodiments of the present invention, the minimum value of t at each time point in step (1) of the method may be the 0th hour or the 0th day, and the maximum value of t at each time point may 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 in the hysteresis stage over time (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 in the biodegradation stage increasing over time.

[0132] According to another aspect of the present invention, a system for evaluating the degradation resistance of plastics is provided, characterized in that the system adopts the method of the present invention.

[0133] According to yet another aspect of the present invention, there is provided a computer device, characterized in that it comprises:

[0134] processor; and

[0135] a memory for storing executable instructions;

[0136] The processor is configured to read and execute the executable instructions from the memory to implement the method described above.

[0137] According to yet another aspect of the present invention, a computer-readable storage medium is provided, characterized in that the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described above is implemented.

[0138] Example

[0139] In order to further understand the present invention, the 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, rather than limiting the claims of the present invention. Any other changes, modifications, substitutions, combinations, and simplifications that do not deviate from the spirit and principles of the present invention should be considered as equivalent replacement methods and are included in the scope of protection of the present invention.

[0140] The materials and test instruments used in the high-solid anaerobic biodegradation tests in Examples 1 to 9 are shown below:

[0141] -Testing instrument: Bioprocess Control Sweden AB's Gas Endeavour biodegradation test system;

[0142] -Plastic: All are polyester plastics, specifically poly (L-lactic acid) resin (PLA, CAS: 26100-51-6, molecular formula (C3H4O2) n ), the dosage is 7.5g, in the form of particles with a diameter of about 3mm, wherein the melting point of poly (L-lactic acid) resin 1# is 160.0℃, the melt index is 17.1g / 10min (190℃, 2.16kg), the molecular weight distribution index is 1.65, the glass transition temperature (T g ) is 58.7℃ and the density is 1.25g / cm 3 , lactide content is 0.33%, the melting point of poly (L-lactic acid) resin 2# is 174.6℃, the melt index is 4.9g / 10min (190℃, 2.16kg), the molecular weight distribution index is 1.58, the glass transition temperature (T g ) is 59.9℃ and the density is 1.25g / cm 3 , lactide content is 0.11%, the melting point of poly (L-lactic acid) resin 3# 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 g ) is 60.8℃ and the density is 1.25g / cm 3 , lactide content is 0.20%, the melting point of poly (L-lactic acid) resin 4# is 171.6℃, the melt index is 3.8g / 10min (190℃, 2.16kg), the molecular weight distribution index is 1.67, the glass transition temperature (T g ) is 60.9℃ and the density is 1.25g / cm 3 , lactide content is 0.15%, and the performance index test method of the above poly (L-lactic acid) resin is carried out in accordance with the national standard GB / T29284-2024 "Polylactic Acid"; the amount of polyhydroxyalkanoate resin (PHA) is 7.5g, in the form of particles with a diameter of about 3mm, specifically BP350 poly-3-hydroxybutyric acid-3-hydroxyhexanoate (PHBH, molecular formula (C4H6O2) from Beijing Lanjing Microbiology Technology Co., Ltd. x (C6H 10 O2) y ) resin;

[0143] -Inoculum: All were anaerobic high-solid sludge from Bipu Instrument (Zhejiang) Co., Ltd., with a dosage of 500g;

[0144] - Reference material: cellulose powder (α-cellulose powder, CAS: 9004-34-6, particle size ≤ 25 μm) from Shanghai Aladdin Biochemical Technology Co., Ltd.

[0145] -Digestion vessel: 1L Schott blue cap glass reagent bottle.

[0146] Example 1

[0147] Poly(L-lactic acid) resin 1# was tested for high-solids anaerobic biodegradation in accordance with GB / T 33797, "Determination of the ultimate anaerobic biodegradability of plastics under high-solids composting conditions using analytical methods for the determination of biogas release." α-cellulose powder was used as the reference material. The test was conducted at a temperature of 52°C ± 2°C and low light conditions. The cumulative biogas release within each digestion container was recorded on a daily basis, and the biodegradation rate of the test material was calculated.

[0148] To plot the biodegradation rate against time, see Figure 1 After smoothing the biodegradation rate by asymmetric window moving average with a left 5 and right 0 scale, all regions in the scatter plot containing at least 9 consecutive data points were enumerated, and a seventh-order polynomial was used to fit the curve of each region, and the corresponding adjusted coefficient of determination was calculated. The power exponent q is 4.3. After calculation, we have found that The largest area corresponds to the data point set from day 11 to day 33, and the corresponding curve fitting function is:

[0149] y opt =–3.4211171238889×10 -10 ×t 7 +5.34258705146005×10 -8 ×t 6 –3.4824961417425×10 -6 ×t 5 +1.22215405698812×10 -4 ×t 4 –2.47796175659958×10 -3 ×t 3 +2.89775114342309×10 -2 ×t 2 –0.181490828647322×t+0.469979894503608

[0150] Calculate the real number solution of the fourth-order derivative of the above function y″″=0, and the solution is t c =15.73, and its fifth-order derivative y″″′=–2.611×10 -5 <0|t=t c , and 11≤t c ≤33, get the evaluation result t c=15.73d.

[0151] In addition, calculate the real number solution of the third-order derivative y″′=0 of the above function, and get t m =20.33, and its fourth-order derivative y″″=–2.813×10 -5 <0|t=t m , and 11≤t m ≤33 and t m ≥t c , get the evaluation result t m =20.33d.

[0152] Example 2

[0153] Poly(L-lactic acid) resin No. 2 was tested for high-solids anaerobic biodegradation according to ISO 15985, "Plastics—Determination of the ultimate anaerobic biodegradation under high-solids anaerobic-digestion conditions—Method by analysis of released biogas." α-cellulose powder was used as the reference material. The test was conducted at 52°C ± 2°C under low light conditions. The cumulative biogas release within each digestion vessel was recorded on a daily basis, and the relative biodegradation rate of the test material was calculated.

[0154] To plot the relative biodegradation rates against time, see Figure 2 After the relative biodegradability was smoothed by a 5-left and 0-right asymmetric window moving average, all regions in the scatter plot containing at least 9 consecutive data points were enumerated, and a seventh-order polynomial was used to fit the curve of each region, and the corresponding adjusted coefficient of determination was calculated. The power exponent q is 4.3. After calculation, we have found that The largest region corresponds to the data point set from day 12 to day 34, and the corresponding curve fitting function is:

[0155] y opt =1.06450910417923×10 -10 ×t 7 –1.81910210770126×10 -8 ×t 6 +1.29287849524046×10 -6 ×t 5 –4.95290092107914×10 -5 ×t 4+1.10787506207289×10 -3 ×t 3 –1.45018041379454×10 -2 ×t 2 +0.102780392908991×t–0.303776582768672

[0156] Calculate the real number solution of the fourth-order derivative of the above function y″″=0, and the solution is t c =23.75, and its fifth-order derivative y″″′=–4.607×10 -6 <0|t=t c , and 12≤t c ≤34, get the evaluation result t c =23.75d.

[0157] In addition, calculate the real number solution of the third-order derivative y″′=0 of the above function, and get t m =28.11, and its fourth-order derivative y″″=–1.606×10 -5 <0|t=t m , and 12≤t m ≤34 and t m ≥t c , get the evaluation result t m =28.11d.

[0158] Example 3

[0159] According to ISO 15985 "Plastics—Determination of the ultimate anaerobic biodegradation under high-solids anaerobic-digestion conditions—Method by analysis of released biogas", poly (L-lactic acid) resin 3# was tested for high-solids anaerobic biodegradation. α-cellulose powder was used as the reference material. The test was conducted at a temperature of 52°C ± 2°C under low light conditions. The cumulative biogas release in each digestion container was counted and recorded in units of days (d), and the biodegradation rate D of the test material was calculated. t .

[0160] To plot the biodegradation rate against time, see Figure 3 . D tAfter smoothing with an asymmetric window moving average 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 the curve of each region, and the corresponding adjusted coefficient of determination was calculated. The power exponent q is 4.3. After calculation, we have found that The largest region corresponds to the data point set from day 12 to day 34, and the corresponding curve fitting function is:

[0161] y opt =1.70080406707207×10 -11 ×t 7 –3.25068469377051×10 -9 ×t 6 +2.5918745767733×10 -7 ×t 5 –1.10803657255771×10 -5 ×t 4 +2.73243469473893×10 -4 ×t 3 –3.85947351162713×10 -3 ×t 2 +2.87623967775815×10 -2 ×t–8.89449681172927×10 -2

[0162] Calculate the real number solution of the fourth-order derivative of the above function y″″=0, and the solution is t c =29.44, and its fifth-order derivative y″″′=–6.536×10 -7 <0|t=t c , and 12≤t c ≤34, get the evaluation result t c =29.44d.

[0163] In addition, calculate the real number solution of the third-order derivative y″′=0 of the above function, and get t m There is no real solution, that is, Calculate t when taking the maximum value m In the process, unreasonable solutions appeared.

[0164] Therefore, from various The second largest value is selected, and the corresponding data point set is from the 10th to the 34th day. The corresponding curve fitting function is:

[0165] y opt =–1.43985605655084×10-11 ×t 7 +1.89641779297856×10 -9 ×t 6 –9.59560126862662×10 -8 ×t 5 +2.27796374394314×10 -6 ×t 4 –2.22441242170291×10 -5 ×t 3 –1.97857065014693×10 -5 ×t 2 +1.64946712453103×10 -3 ×t–8.75312952464576×10 -3

[0166] Calculate the real number solution of the fourth-order derivative of the above function y″″=0, and the solution is t c =8.02, however, the t c <10, that is, not within the range of the 10th to 34th day of the data point set, that is, Calculate t when taking the second largest value c In the process, unreasonable solutions appeared.

[0167] Therefore, from various The third largest value is selected, and the corresponding data point set is from the 11th to the 34th day. The corresponding curve fitting function is:

[0168] y opt =–6.26294802104488×10 -12 ×t 7 +5.82787948725758×10 -10 ×t 6 –6.81903028319136×10 -9 ×t 5 –1.01236582251139×10 -6 ×t 4 +4.90122592387045×10 -5 ×t 3 –9.23870393288964×10 -4 ×t 2 +7.86409811578337×10 -3 ×t–2.65878224639102×10 -2

[0169] Calculate the real number solution of the fourth-order derivative of the above function y″″=0, and the solution is t c =–8.31, however, the t c <11, that is, not within the range of the 11th to 34th day of the data point set, that is, Calculate t when taking the third largest c In the process, unreasonable solutions appeared.

[0170] Therefore, from various The fourth largest value is selected, and the corresponding data point set is from the 13th to the 34th day. The corresponding curve fitting function is:

[0171] y opt =2.13111968088386×10 -11 ×t 7 –3.97368772623481×10 -9 ×t 6 +3.10464729097939×10 -7 ×t 5 –1.30686782530207×10 -5 ×t 4 +3.18729986348971×10 -4 ×t 3 –4.47292156777153×10 -3 ×t 2 +3.32751396700088×10 -2 ×t–0.102905803171419

[0172] Calculate the real number solution of the fourth-order derivative of the above function y″″=0, and the solution is t c =29.63, and its fifth-order derivative y″″′=–3.673×10 -7 <0|t=t c , and 13≤y c ≤34, get the evaluation result t c =29.63d.

[0173] In addition, calculate the real number solution of the third-order derivative y″′=0 of the above function, and get t m There is no real solution, that is, Calculate t when taking the fourth largest m In the process, unreasonable solutions appeared.

[0174] Therefore, from various The fifth largest value is selected, and the corresponding data point set is from the 14th to the 34th day. The corresponding curve fitting function is:

[0175] y opt =5.56126918522546×10 -11 ×t 7 –9.84820912174588×10 -9 ×t 6 +7.35968678286115×10 -7 ×t 5 –2.99545253992654×10 -5 ×t 4 +7.14989021533172×10 -4 ×t 3 –9.9685360518877×10 -3 ×t 2 +7.49603798371409×10 -2 ×t–0.236253155808885

[0176] Calculate the real number solution of the fourth-order derivative of the above function y″″=0, and the solution is t c =27.71, and its fifth-order derivative y″″′=–5.583×10 -7 <0|t=t c , and 14≤t c ≤34, get the evaluation result t c =27.71d.

[0177] In addition, calculate the real number solution of the third-order derivative y″′=0 of the above function, and get t m There is no real solution, that is, Calculate t when taking the fifth largest m In the process, unreasonable solutions appeared.

[0178] Therefore, from various The sixth largest value is selected, and its corresponding data point set is from the 8th to the 34th day. The corresponding curve fitting function is:

[0179] y opt =–3.83190100901317×10 -11 ×t 7 +5.66527024540093×10 -9 ×t 6 –3.44733142440552×10 -7 ×t 5 +1.11796357202363×10 -5 ×t 4–2.08361107413735×10 -4 ×t 3 +2.24971348858112×10 -3 ×t 2 –1.32684944067332×10 -2 ×t+3.19628821427325×10 -2

[0180] Calculate the real number solution of the fourth-order derivative of the above function y″″=0, and the solution is t c =14.19, and its fifth-order derivative y″″′=–2.933×10 -6 <0|t=t c , and 8≤t c ≤34, get the evaluation result t c =14.19d.

[0181] In addition, calculate the real number solution of the third-order derivative y″′=0 of the above function, and get t m =17.38, and its fourth-order derivative y″″=–3.588×10 -6 <0|t=t m , and 8≤t m ≤34 and t m ≥t c , get the evaluation result t m =17.38d.

[0182] Example 4

[0183] According to ISO 15985 "Plastics—Determination of the ultimate anaerobic biodegradation under high-solids anaerobic-digestion conditions—Method by analysis of released biogas", poly (L-lactic acid) resin 4# was tested for high-solids anaerobic biodegradation. α-cellulose powder was used as the reference material. The test was conducted at a temperature of 52°C ± 2°C under low light conditions. The cumulative biogas release in each digestion container was counted and recorded in units of days (d), and the biodegradation rate D of the test material was calculated. t .

[0184] To plot the biodegradation rate against time, see Figure 4 . D tAfter smoothing with an asymmetric window moving average 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 the curve of each region, and the corresponding adjusted coefficient of determination was calculated. The power exponent q is 4.3. After calculation, we have found that The largest region corresponds to the data point set from day 10 to day 34, and the corresponding curve fitting function is:

[0185] y opt =–5.77594231422511×10 -11 ×t 7 +8.64260355513909×10 -9 ×t 6 –5.37461077354915×10 -7 ×t 5 +1.80615201282556×10 -5 ×t 4 –3.53834951570575×10 -4 ×t 3 +4.05141891362169×10 -3 ×t 2 –2.54589291423585×10 -2 ×t+6.64370472559309×10 -2

[0186] Calculate the real number solution of the fourth-order derivative of the above function y″″=0, and the solution is t c =15.72, and its fifth-order derivative y″″′=–2.643×10 -6 <0|t=t c , and 10≤t c ≤34, get the evaluation result t c =15.72d.

[0187] In addition, calculate the real number solution of the third-order derivative y″′=0 of the above function, and get t m =31.76, and its fourth-order derivative y″″=–3.076×10 -5 <0|t=t m , and 10≤t m ≤34 and t m ≥t c , get the evaluation result t m =31.76d.

[0188] Example 5

[0189] The scatter plot of Example 2 was curve fitted. After the relative biodegradability was smoothed using a symmetrical window moving average with a window size of 3, all regions in the scatter plot containing at least 10 consecutive data points were enumerated. An eighth-order polynomial was used to curve fit each region, and the corresponding adjusted coefficient of determination was calculated. The power exponent q is 4.1. After calculation, we have found that The largest region corresponds to the data point set from day 7 to day 33, and the corresponding curve fitting function is:

[0190] y opt =2.69900954175677×10 -11 ×t 8 –4.3288008408457×10 -9 ×t 7 +2.94247511638288×10 -7 ×t 6 –1.10472023685665×10 -5 ×t 5 +2.50004363658776×10 -4 ×t 4 –3.48135115792691×10 -3 ×t 3 +2.90195107860245×10 -2 ×t 2 –0.132021081043973×t+0.25062238801605

[0191] Calculate the real number solution of the fourth-order derivative of the above function y″″=0, and the solution is t c =12.07, and its fifth-order derivative y″″′=–3.879×10 -5 <0|t=t c , and 7≤t c ≤33, get the evaluation result t c =12.07d.

[0192] In addition, calculate the real number solution of the third-order derivative y″′=0 of the above function, and get t m =15.50, and its fourth-order derivative y″″=–2.168×10 -5 <0|t=t m , and 7≤t m ≤33 and t m ≥t c , get the evaluation result t m =15.50d.

[0193] Example 6

[0194] Poly(L-lactic acid) resin 3# was tested for high-solids anaerobic biodegradation according to ISO 15985, "Plastics—Determination of the ultimate anaerobic biodegradation under high-solids anaerobic-digestion conditions—Method by analysis of released biogas." α-cellulose powder was used as the reference material. The test was conducted at 52°C±2°C under low light conditions. The cumulative biogas release from each digestion vessel was recorded on a daily basis, and the relative biodegradation rate of the test material was calculated.

[0195] To plot the relative biodegradation rates against time, see Figure 5 After the relative biodegradability was smoothed by a 3-left and 0-right asymmetric window moving average, all regions in the scatter plot containing at least 8 consecutive data points were enumerated, and a sixth-order polynomial was used to fit the curve of each region, and the corresponding adjusted coefficient of determination was calculated. The power exponent q is 4.6. After calculation, we found that The largest region corresponds to the data point set from day 13 to day 34, and the corresponding curve fitting function is:

[0196] y opt =–1.43701916264522×10 -10 ×t 6 +1.4865137590509×10 -8 ×t 5 –3.86914057413983×10 -7 ×t 4 –6.33508704280439×10 -6 ×t 3 +4.77708527261054×10 -4 ×t 2 –7.89243951063975×10 -3 ×t+3.97604895982588×10 -2

[0197] Calculate the real number solution of the fourth-order derivative of the above function y″″=0, and the solution is t c =28.09, and its fifth-order derivative y″″′=–1.123×10 -6 <0|t=t c, and 13≤t c ≤34, get the evaluation result t c =28.09d.

[0198] In addition, calculate the real number solution of the third-order derivative y″′=0 of the above function, and get t m =33.95, and its fourth-order derivative y″″=–8.346×10 -6 <0|t=t m , and 13≤t m ≤34 and t m ≥t c , get the evaluation result t m =33.95d.

[0199] Example 7

[0200] Perform curve fitting on the scatter plot of Example 1. Exhaustively list all regions in the scatter plot that contain at least 9 consecutive data points, and perform curve fitting on each region using a seventh-order polynomial, and calculate the corresponding adjusted coefficient of determination. The power exponent q is 4.3. After calculation, we have found that The largest area corresponds to the data point set from the 10th to the 30th day, and the corresponding curve fitting function is:

[0201] y opt =–1.14026771433683×10 -9 ×t 7 +1.57444295137411×10 -7 ×t 6 –9.06048963589077×10 -6 ×t 5 +2.80657249975495×10 -4 ×t 4 –5.03249523416425×10 -3 ×t 3 +5.21930520391578×10 -2 ×t 2 –0.290636936956885×t+0.670856134190778

[0202] Calculate the real number solution of the fourth-order derivative of the above function y″″=0, and the solution is t c =13.92, and its fifth-order derivative y″″′=–6.591×10 -5 <0|t=t c , and 10≤t c ≤30, get the evaluation result t c=13.92d.

[0203] In addition, calculate the real number solution of the third-order derivative y″′=0 of the above function, and get t m =17.39, and its fourth-order derivative y″″=–6.811×10 -5 <0|t=t m , and 10≤t m ≤30 and t m ≥t c , get the evaluation result t m =17.39d.

[0204] Example 8

[0205] Perform curve fitting on the scatter plot of Example 2. Exhaustively list all regions in the scatter plot that contain at least 9 consecutive data points, and perform curve fitting on each region using a seventh-order polynomial, and calculate the corresponding adjusted coefficient of determination. The power exponent q is 4.3. After calculation, we have found that The largest region corresponds to the data point set from day 11 to day 32, and the corresponding curve fitting function is:

[0206] y opt =3.55837215648732×10 -10 ×t 7 –5.45720245023808×10 -8 ×t 6 +3.49705923176726×10 -6 ×t 5 –1.21251244202399×10 -4 ×t 4 +2.45803236369347×10 -3 ×t 3 –2.91360897271222×10 -2 ×t 2 +0.186704820551642×t–0.498354175016332

[0207] Calculate the real number solution of the fourth-order derivative of the above function y″″=0, and the solution is t c =21.66, and its fifth-order derivative y″″′=–1.072×10 -5 <0|t=t c , and 11≤t c ≤32, get the evaluation result t c =21.66d.

[0208] In addition, calculate the real number solution of the third-order derivative y″′=0 of the above function, and get t m =25.16, and its fourth-order derivative y″″=–2.748×10 -5 <0|t=t m , and 11≤t m ≤32 and t m ≥t c , get the evaluation result t m =25.16d.

[0209] Example 9

[0210] According to GB / T 33797 "Determination of the ultimate anaerobic biodegradability of plastics under high solid composting conditions using the method of analytical determination of released biogas", BP350 poly-3-hydroxybutyrate-3-hydroxyhexanoate (PHBH) resin (molecular formula (C4H6O2) from Beijing Lanjing Microbiology Technology Co., Ltd. was tested. x (C6H 10 O2) y ) conducted high-solid anaerobic biodegradation tests using α-cellulose powder as the reference material at a temperature of 52°C ± 2°C under low light conditions. The cumulative biogas release within each digestion vessel was recorded in hours, and the biodegradation rate of the test material was calculated.

[0211] To plot the biodegradation rate against time, see Figure 6 After smoothing the biodegradation rate by asymmetric window moving average with a left 5 and right 0 scale, all regions in the scatter plot containing at least 9 consecutive data points were enumerated, and a seventh-order polynomial was used to fit the curve of each region, and the corresponding adjusted coefficient of determination was calculated. The power exponent q is 4.3. After calculation, we have found that The largest area corresponds to the data point set from the 17th hour to the 100th hour, and the corresponding curve fitting function is:

[0212] y opt =5.08034084545242×10 -14 ×t 7 –2.18981861486183×10 -11 ×t 6 +3.84075186789846×10 -9 ×t 5 –3.52966870197372×10 -7 ×t 4 +1.82716315055882×10 -5 ×t 3–5.18446297350659×10 -4 ×t 2 +7.37416977903541×10 -3 ×t–4.09675110755131×10 -2

[0213] Calculate the real number solution of the fourth-order derivative of the above function y″″=0, and the solution is t c =60.82, and its fifth-order derivative y″″′=–2.447×10 -8 <0|t=t c , and 17≤t c ≤100, get the evaluation result t c =60.82h, or about 2.53d.

[0214] In addition, calculate the real number solution of the third-order derivative y″′=0 of the above function, and get t m =72.98, and its fourth-order derivative y″″=–2.351×10 -7 <0|t=t m , and 17≤t m ≤100 and t m ≥t c , get the evaluation result t m =72.98h, or about 3.04d.

[0215] As can be seen from Examples 1 to 9, the method of the present invention can convert the "rough" raw data reflecting the initial anaerobic degradation characteristics of the degradable plastic into an accurate mathematical function by fitting the biodegradation rate or relative biodegradation rate curve into a function that is at least 5th order differentiable and calculating and analyzing the adjusted coefficient of determination, and through this mathematical function, clearly define and calculate the evaluation results that can reflect the corresponding degradation characteristics of the degradable plastic. At the same time, it is believed that when the same continuously differentiable function is used to fit the biodegradation rate collected under the same test conditions and the optional additional identical data preprocessing process according to the method of the present invention, and the adjusted coefficient of determination with the same power exponent is used, that is, When , according to the output evaluation results such as t c or t m It can be used to compare the comprehensive anti-degradation performance of different plastics. c It can be understood as the critical moment when the outermost layer of the test material directly contacts the biodegradation test environment and begins to biodegrade (the plastic molecular weight is reduced to a level that can be digested and decomposed by microorganisms through chemical degradation). m It can be understood as the critical moment when the surface plastic of the test material begins to biodegrade. c and / or t mThe larger the value, the better the plastic's resistance to chemical degradation.

Claims

1. A method for analyzing and evaluating the anti-degradation performance of plastics based on the fitting derivative method of high-solid anaerobic biodegradation test results, characterized in that: It includes the following steps: (1) conducting a high-solid anaerobic biodegradation test on plastics and obtaining the results of the test; The test is carried out under high solids anaerobic digestion conditions, and the biodegradation rate or relative biodegradation rate (%) of the plastic at each time point t is recorded as D t ; (2) Draw a scatter plot selected from the following: (a)D t a scatter plot of the points against 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), wherein 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 continuous data points of each segment to obtain curve fitting functions for each region; The fitting function of the jth region is denoted as y j =f j (t)|t∈[t A,j ,t B,j ], The size or number of continuous data points in the jth region is recorded as m j , and m j ≥7, t A,j is the starting time point of the jth region, t B,j is the end time point of the j-th region, and wherein the continuously differentiable function is selected from at least fifth-order differentiable functions; (4) Obtaining a curve fitting result with the best fitting degree from the curve fitting function of step (3), Each y is calculated by the following equation 1 j Calculate the adjusted coefficient of determination separately, namely in, is the coefficient of determination of the curve fitting function of each segment; m j As defined in step (3); k is the number of free parameters in the fitting function; m j -k>0; the power exponent q is 2.0 to 7.0, and From the various The maximum value is selected from the above equations, and the curve fitting function corresponding to the maximum value is limited to the curve fitting result with the best fitting degree, which is recorded 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 The fourth-order derivative y″″ and the fifth-order derivative y″″′ are obtained, and the time t corresponding to y″″=0 and y″″′<0 is obtained. c , where t c is a real number solution 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 , In step (5), t is calculated c If there is no real number solution or an unreasonable solution in the process, return to step (4) and select Select the next largest value from the equation, use the curve fitting function corresponding to the value as the new curve fitting result, and obtain its corresponding t according to step (5). c , and so on, until a t that satisfies the conditions is obtained. c The evaluation results are output.

2. The method according to claim 1, characterized in that In step (5), when there are at least two t c solution, then take the solution with the minimum value.

3. The method according to claim 2, characterized in that In step (5), additionally calculate y opt The third-order derivative y″′ and the fourth-order derivative y″″ are obtained, and the time t corresponding to y″′=0 and y″″<0 is obtained. m , where t m is a real number solution and satisfies t A,opt ≤t m ≤t B,opt , and t m ≥t c , and in step (6), wherein the evaluation result further includes t m , In step (5), t is calculated m If there is no real number solution or an unreasonable solution in the process, return to step (4) and select Select the next largest value from the equation, use the curve fitting function corresponding to the value as the new curve fitting result, and obtain its corresponding t according to step (5). c and t m , and so on, until a t that satisfies the conditions is obtained. c and t m The evaluation results are output.

4. The method according to claim 3, characterized in that In step (5), when there are at least two t m solution, then take the solution with the minimum value.

5. The method according to claim 4, characterized in that In step (5), additionally calculate y opt The second derivative y″ of t c The value of time y″ c , and / or get y″ at t m The value of time y″ m , and in step (6), wherein the evaluation result also includes 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 at least sixth-order differentiable functions.

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

8. The method according to any one of claims 1 to 7, characterized in that The high-solid anaerobic biodegradation test in step (1) is carried out at a constant temperature of 52°C ± 2°C and in darkness or low light.

9. The method according to any one of claims 1 to 7, characterized in that The time described in step (1) is in units of 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 smoothing.

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

12. The method according to claim 11, characterized in that The D in step (2) is converted into t Moving smoothing is the decomposition rate after preprocessing 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 rate in the smoothing window; g is the size of the left smoothing window and does not include the data point i; h is the size of the right smoothing window and does not include the data point i; g or h are each independently 0, 1, 2, 3 or a larger integer, where g and h are not 0 at the same time; u is the number of D in the smoothing window. t Position; D u is D at position u within the smoothing 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 In step (3), m j At least 8.

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

17. The method according to any one of claims 1 to 7, characterized in that In step (3), m j 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 For 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 For up to the 12th hour.

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

23. The method according to any one of claims 1 to 7, characterized in that In step (3), t A,j Up to 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 For 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 For 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 a polynomial function, a Boltzmann function or a Bezier curve.

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 +a1×t+a0 Equation 3 Where n is the order of the polynomial function, a0 to a n are the coefficients of the polynomial functions, The polynomial is a fifth-order, sixth-order, seventh-order, eighth-order or ninth-order polynomial function, or a higher-order polynomial function.

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

31. The method according to claim 29, wherein The scale of continuous data points in step (3) is the number m j At least the order of the polynomial function + 2.

32. The method according to claim 29, wherein The scale of continuous data points in step (3) is the number m j At least the order of the polynomial function + 10.

33. The method according to claim 29, wherein The scale of continuous data points in step (3) is the number m j At least the order of the polynomial function + 20.

34. The method according to claim 29, wherein In the adjusted 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, wherein The continuously differentiable function in step (3) is: 1) A fifth-order polynomial function, the adjusted coefficient of determination of the fifth-order polynomial function in step (4) is The power exponent q in is 4.0 to 7.0; or 2) A sixth-order polynomial function, the adjusted coefficient of determination of the sixth-order polynomial function in step (4) is The power exponent q is between 3.0 and 6.5; or 3) A seventh-order polynomial function, the adjusted coefficient of determination of the seventh-order polynomial function in step (4) is The power exponent q in is 2.5 to 6; or 4) an octave polynomial function, the adjusted coefficient of determination of the octave polynomial function in step (4) being The power exponent q is between 2.0 and 5.5; or 5) A ninth-order polynomial function, the adjusted coefficient of determination of the ninth-order polynomial function in step (4) is The power exponent q in the range is 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 fifth-order polynomial function, the adjusted coefficient of determination of the fifth-order polynomial function in step (4) is The power exponent q in is 5.0 to 7.0; or 2) A sixth-order polynomial function, the adjusted coefficient of determination of the sixth-order polynomial function in step (4) is The power exponent q is between 3.6 and 5.6; or 3) A seventh-order polynomial function, the adjusted coefficient of determination of the seventh-order polynomial function in step (4) is The power exponent q is between 3.3 and 5.3; or 4) an octave polynomial function, the adjusted coefficient of determination of the octave polynomial function in step (4) being The power exponent q is between 3.1 and 5.1; or 5) A ninth-order polynomial function, the adjusted coefficient of determination of the ninth-order polynomial function in step (4) is The power exponent q in the range is 2.9 to 5.

9.

37. The method according to claim 29, wherein The continuously differentiable function in step (3) is: 1) A fifth-order polynomial function, the adjusted coefficient of determination of the fifth-order polynomial function in step (4) is The power exponent q in is 4.0, 4.5, 5.0, 5.5, 6.0, 6.5 or 7.0; or 2) A sixth-order polynomial function, the adjusted coefficient of determination of the sixth-order polynomial function in step (4) is The power exponent q in is 4.0, 4.2, 4.4, 4.6, 4.8, 5.0 or 5.2; or 3) A seventh-order polynomial function, the adjusted coefficient of determination of the seventh-order polynomial function in step (4) is The power exponent q in is 3.7, 3.9, 4.1, 4.3, 4.5, 4.7 or 4.9; or 4) an octave polynomial function, the adjusted coefficient of determination of the octave polynomial function in step (4) being The power exponent q in is 3.5, 3.7, 3.9, 4.1, 4.3, 4.5 or 4.7; or 5) A ninth-order polynomial function, the adjusted coefficient of determination of the ninth-order polynomial function in step (4) is The power exponent q in 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 a method according to any one of the preceding claims.

39. A computer device, characterized in that: It includes: processor; and a memory for storing executable instructions; The processor is configured to read and execute the executable instructions from the memory to implement the method according to any one of claims 1 to 37.

40. A computer-readable storage medium, characterized in that The computer program is stored therein, and when the computer program is executed by a processor, the method according to any one of claims 1 to 37 is implemented.

Images