A method of extending the life of a biodegradable mulch material

Abstract

The application provides a method for prolonging the service life of a biodegradable mulching material, and belongs to the technical field of biodegradable mulching films.The application establishes a relationship curve between environmental parameters and degradation rate, determines the optimal ratio of PBAT and PLA and the critical temperature of phase separation based on the molecular chain segment movement theory of the carrier material, optimizes the uniformity of carbon black dispersion by using the interface interaction mechanism of surface modified carbon black and dispersant to enhance the anti-degradation ability, constructs a biodegradation control optimization model to realize accurate prolongation of the degradation life, determines four adjustment intervals and a nonlinear relationship model of adjustment coefficients by the experimental establishment of the degradation rate demarcation point, calculates the optimal formula, and uses a double rotor internal mixer and a double screw extruder to prepare the material, and simultaneously dynamically adjusts the model neighbor sampling number parameter through the degradation life adjustment function, so that the technical problem of insufficient service life of the biodegradable mulching material is solved.

Description

Technical Field

[0001] This invention belongs to the field of biodegradable mulch film technology, and more specifically, relates to a method for extending the lifespan of biodegradable mulch film materials. Background Technology

[0002] Biodegradable mulch films, as an environmentally friendly alternative to traditional plastic mulch films, are primarily prepared using a blend of PBAT and PLA. By adding fillers such as carbon black, they achieve shading functionality and are widely used in agricultural mulching, soil insulation, weed control, and crop growth regulation, playing a vital role in modern agricultural production. However, current biodegradable mulch film preparation technologies rely heavily on empirically determined carrier material ratios, lacking guidance from molecular-level compatibility theories. Furthermore, the control of carbon black dispersion uniformity lacks a quantitative evaluation system, and the setting of process parameters lacks scientific basis. This results in difficulty in precisely controlling the degradation rate of the material under complex environmental conditions, often leading to premature degradation. Existing technologies typically use fixed formulas and process parameters to prepare mulch films, failing to tailor designs to the specific growth needs of different crops and the temperature, humidity, and light conditions of the application environment. Consequently, the mulch film degrades significantly in the early stages of crop growth, losing its intended protective function. In other words, current technologies suffer from insufficient lifespan of biodegradable mulch films, failing to meet the needs of crops throughout their entire growth cycle. Summary of the Invention

[0003] In view of this, the present invention provides a method for extending the lifespan of biodegradable mulch film materials, which can solve the technical problem that the lifespan of existing biodegradable mulch film materials is insufficient, resulting in the inability to meet the needs of crops throughout their growth.

[0004] This invention is implemented as follows: This invention provides a method for extending the lifespan of biodegradable mulch film materials, comprising: measuring the degradation rate and mechanical property changes of the biodegradable mulch film material under various environmental conditions using a biodegradable mulch film material degradation performance testing device; establishing a relationship curve between environmental parameters and degradation rate; recording the compatibility index of the carrier material and the carbon black dispersion uniformity coefficient; establishing a compatibility prediction equation for the PBAT / PLA blend system based on the molecular chain segment motion theory of the carrier material; determining the carrier material ratio range; and predicting the phase separation critical temperature of the blend system using a thermodynamic equilibrium model; based on the interfacial interaction between surface-modified carbon black and dispersant... A carbon black dispersion stability evaluation model was established to assess the carbon black dispersion uniformity coefficient using optical transmittance measurement, and the carbon black addition amount and dispersant dosage were adjusted accordingly. A biodegradation regulation and optimization model was used to optimize the basic formulation. An accelerated degradation test was used to establish a nonlinear relationship model between the adjustment coefficient and environmental parameter deviations. Based on the target usage environment, the expected service life requirements of the biodegradable mulch film were determined, environmental parameters were calculated and substituted into the biodegradation regulation and optimization model, and the optimal carrier material ratio, carbon black addition amount, and dispersant dosage were calculated, optimizing the specific dosage of each component in the basic formulation. Biodegradable mulch film was then prepared according to the calculated formulation parameters.

[0005] The carrier material is a blend of PBAT and PLA. The test conditions of the biodegradable mulch film material degradation performance testing device include an ambient temperature of -10°C to 60°C, a relative humidity of 20% to 90%, an ultraviolet intensity of 0 to 500 watts per square meter, and a biodegradable mulch film material thickness of 0.006 mm to 0.008 mm.

[0006] The compatibility prediction equation determines the range of carrier material ratios by calculating the difference in solubility parameters and interfacial tension coefficients between the carrier materials. The molecular chain segment motion theory of the carrier materials is based on the molecular dynamics principle of polymer materials. It predicts the compatibility behavior of the two carrier materials under different temperature and shear conditions by analyzing the conformational changes and interaction energies of PBAT and PLA molecular chains.

[0007] The thermodynamic equilibrium model is based on the Flory-Huggins theory. It predicts the phase separation behavior of the blend system at different temperatures by calculating the interaction parameters between the support materials and the enthalpy change of mixing. The inputs include the solubility parameters and molecular volume of the support materials, and the outputs are the critical temperature of phase separation and the phase diagram structure.

[0008] The solubility parameter difference is calculated using Hansen solubility parameter theory to assess the compatibility between PBAT and PLA. The interfacial tension coefficient is obtained through contact angle measurement and surface energy calculation, reflecting the interfacial bonding strength of the carrier materials.

[0009] The carbon black dispersion stability evaluation model is established by controlling the density of functional groups on the carbon black surface and the molecular chain length of the dispersant. The interfacial interaction mechanism between surface-modified carbon black and dispersant is based on colloid chemistry theory. By analyzing the hydrogen bonding, van der Waals forces and electrostatic interactions between carbon black surface functional groups and dispersant molecules, it is used to predict the dispersion state and agglomeration tendency of carbon black particles in the carrier material.

[0010] The density of functional groups on the surface of the carbon black was determined by X-ray photoelectron spectroscopy, the molecular chain length of the dispersant was determined by gel permeation chromatography, the polarity parameters of the carrier material were obtained by dielectric constant measurement, and the light-shielding requirement was that the light transmittance of the biodegradable mulch film material was controlled below 10%.

[0011] The adjustment of carbon black addition and dispersant dosage is based on the carbon black dispersion uniformity coefficient and dispersion stability index. The optical transmittance measurement method quantitatively evaluates the dispersion uniformity of carbon black in the mulch film by measuring the transmittance distribution of the biodegradable mulch film material in the visible light wavelength range of 380nm to 780nm. The measurement method is based on Beer-Lambert's law.

[0012] The biodegradation regulation and optimization model uses environmental temperature deviation, humidity variation, ultraviolet intensity fluctuation, carrier material ratio, and carbon black dispersion uniformity coefficient as input variables. It achieves accurate prediction of the lifespan of biodegradable mulch film materials and optimization of the basic formula by adjusting the neighbor sampling number through the sparse attention mechanism in the model.

[0013] The basic formulation includes a carrier material, carbon black, dispersant, talc, calcium carbonate, antioxidant, lubricant, compatibilizer, coupling agent, and chain extender. The carrier material is a blend of PBAT and PLA. Talc is used to improve the mechanical strength and dimensional stability of the material, and calcium carbonate is used to reduce costs and improve processing performance.

[0014] The accelerated degradation test is determined by the degradation rate threshold. 25 sets of accelerated degradation tests with different combinations of environmental parameters are set up. Each set of tests includes 3 parallel samples. The tests are conducted continuously for 168 hours under constant temperature, humidity and ultraviolet intensity conditions, and the degradation rate change is recorded every 24 hours.

[0015] The adjustment coefficient range is further divided into four adjustment intervals: the first adjustment interval is 0.3 to 0.42, the second adjustment interval is 0.42 to 0.58, the third adjustment interval is 0.58 to 0.67, and the fourth adjustment interval is 0.67 to 0.7. The first adjustment interval corresponds to a slight environmental deviation, the second adjustment interval corresponds to a moderate environmental deviation, the third adjustment interval corresponds to a large environmental deviation, and the fourth adjustment interval corresponds to a severe environmental deviation.

[0016] The calculated environmental parameters include the temperature deviation, humidity variation, and ultraviolet intensity fluctuation. These parameters, along with the carrier material compatibility index and carbon black dispersion uniformity coefficient, are substituted into the biodegradation regulation and optimization model. The expected service life of the biodegradable mulch film material is determined based on the temperature range, humidity variation, and light intensity of the target environment.

[0017] The preparation of the biodegradable mulch film material involves combining the basic formulation composition ratio with a twin-rotor internal mixer and a twin-screw extruder. The temperature of the twin-rotor internal mixer is regulated according to the critical phase separation temperature. The preparation parameters of the twin-rotor internal mixer and the twin-screw extruder include controlling the temperature of the twin-rotor internal mixer within the range of 90°C to 140°C according to the critical phase separation temperature.

[0018] The degradation lifetime adjustment function adjusts the neighbor sampling number parameter of the biodegradation regulation optimization model in real time through the boundary points of four adjustment intervals. It is used to dynamically adjust the neighbor sampling number parameter of the sparse attention mechanism in the biodegradation regulation optimization model according to the degree of difference between the actual use environment and the preset conditions. The function calculates the adjustment coefficient based on three key parameters: environmental temperature deviation, humidity change amplitude, and ultraviolet intensity fluctuation.

[0019] The ambient temperature deviation refers to the absolute difference between the actual ambient temperature and the standard test temperature of 25°C, which is obtained through real-time monitoring by a temperature sensor. The humidity change range refers to the maximum change in relative humidity within 24 hours, which is obtained through continuous monitoring and calculation by a humidity sensor. The ultraviolet intensity fluctuation refers to the standard deviation of ultraviolet intensity under sunlight conditions, which is obtained through measurement by an ultraviolet intensity meter.

[0020] This invention establishes a quantitative relationship model between environmental parameters and degradation rate, and combines this with the compatibility theory of carrier materials and the carbon black dispersion stability evaluation system to construct a biodegradation regulation and optimization model, achieving precise extension and optimized control of the degradation lifespan of mulch film materials. This method guides the determination of the optimal ratio of PBAT to PLA through the molecular chain segment motion theory of carrier materials, improving the compatibility and structural stability of the carrier materials. It optimizes the uniformity of carbon black dispersion through the interfacial interaction mechanism between surface-modified carbon black and dispersant, enhancing the material's resistance to degradation. By dynamically adjusting model parameters through a degradation lifespan adjustment function, it achieves lifespan extension strategies for different environmental conditions. The four regulation interval boundary point system and the sparse attention mechanism neighbor sampling number adjustment method established in this invention can precisely regulate the degradation time of mulch film materials according to the target use environment and crop growth needs, ensuring that the material maintains good coverage performance during the key growth period of crops and meets the requirements of the entire growth cycle. In summary, this invention solves the technical problem of insufficient lifespan of biodegradable mulch film materials mentioned in the background art. Attached Figure Description

[0021] Figure 1 This is a flowchart of the method of the present invention.

[0022] Figure 2 This is a schematic diagram of the neural network structure of the biodegradation regulation optimization model involved in the present invention.

[0023] Figure 3 This is a graph showing the relationship between the carbon black dispersion uniformity coefficient and the amount of dispersant in Example 2.

[0024] Figure 4 This is a graph showing the change of mechanical properties of the mulch film material over time in Example 2.

[0025] Figure 5 This is a graph showing the trend of light transmittance of the mulch film material during its service life in Example 2. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings.

[0027] like Figure 1 The diagram shown is a flowchart of a method for extending the lifespan of biodegradable mulch film materials provided by the present invention. This method includes the following steps:

[0028] S01. Using a biodegradable mulch film material degradation performance testing device, the degradation rate and mechanical property changes of the biodegradable mulch film material are measured under various environmental conditions, a relationship curve between environmental parameters and degradation rate is established, and the compatibility index of the carrier material and the carbon black dispersion uniformity coefficient are recorded, wherein the carrier material is a blend system of PBAT and PLA.

[0029] S02. Based on the molecular chain segment motion theory of carrier materials, a compatibility prediction equation for the PBAT and PLA blend system is established. By calculating the difference in solubility parameters and interfacial tension coefficients between carrier materials, the proportion range of carrier materials is determined. The critical phase separation temperature of the blend system is predicted by a thermodynamic equilibrium model. The critical phase separation temperature is used to guide the temperature control range of the dual-rotor internal mixer.

[0030] S03. Based on the interfacial interaction mechanism between surface-modified carbon black and dispersant, a carbon black dispersion stability evaluation model is established by controlling the density of functional groups on the carbon black surface and the molecular chain length of the dispersant. The carbon black dispersion uniformity coefficient is quantitatively evaluated by optical transmittance measurement. The amount of carbon black added and the amount of dispersant are adjusted according to the carbon black dispersion uniformity coefficient and dispersion stability index so that the light transmittance of the biodegradable mulch film material meets the shading requirements.

[0031] S04. Construct a biodegradation regulation and optimization model, using environmental temperature deviation, humidity variation, ultraviolet intensity fluctuation, carrier material ratio and carbon black dispersion uniformity coefficient as input variables. Through the neighbor sampling number adjustment of the sparse attention mechanism in the model, the accurate prediction of the lifespan of biodegradable mulch film materials and the optimization of the basic formula can be achieved.

[0032] S05. The experiment is determined by the degradation rate boundary point. Accelerated degradation test is conducted under different combinations of environmental parameters. A nonlinear relationship model between the adjustment coefficient and the deviation of environmental parameters is established. The range of the adjustment coefficient is subdivided into four adjustment intervals. The boundary points of the four adjustment intervals are used to set the parameter switching threshold of the degradation lifetime adjustment function.

[0033] S06. Based on the temperature range, humidity changes, and light intensity of the target environment, determine the expected service life requirements of the biodegradable mulch film material, calculate the environmental temperature deviation, humidity change range, and ultraviolet intensity fluctuation, and substitute the parameters, along with the carrier material compatibility index and carbon black dispersion uniformity coefficient, into the biodegradation regulation and optimization model to calculate the optimal carrier material ratio, carbon black addition amount, dispersant dosage, and optimize the specific dosage of each component in the basic formula.

[0034] S07. Based on the calculated formula parameters and the basic formula component ratio, biodegradable mulch film material is prepared using a twin-rotor internal mixer and a twin-screw extruder. The temperature of the twin-rotor internal mixer is controlled according to the critical phase separation temperature, and the neighbor sampling number parameter of the biodegradation control optimization model is adjusted in real time based on the boundary points of four adjustment intervals through the degradation lifetime adjustment function.

[0035] The testing conditions for the biodegradable mulch film material degradation performance testing device include an ambient temperature of -10℃ to 60℃, a relative humidity of 20% to 90%, and an ultraviolet radiation intensity of 0 to 500 watts per square meter. The thickness of the biodegradable mulch film material is 0.006 mm to 0.008 mm. The carrier material composition ranges from 20% to 40% of the total mass of the carrier material (PBAT) to 4% to 8% of the total mass of the carrier material (PLA).

[0036] The molecular chain motion theory of the carrier materials is based on the molecular dynamics principles of polymer materials. By analyzing the conformational changes and interaction energies of PBAT and PLA molecular chains, it predicts the compatibility behavior of the two carrier materials under different temperature and shear conditions. The compatibility prediction equation is used to calculate the thermodynamic and kinetic compatibility parameters between the carrier materials. The inputs include the molecular weight distribution, glass transition temperature, and melting temperature of the carrier materials, and the outputs are the compatibility index and optimal ratio range of the carrier materials. The thermodynamic equilibrium model is based on the Flory-Huggins theory. By calculating the interaction parameters and mixing enthalpy change between the carrier materials, it predicts the phase separation behavior of the blend system at different temperatures. The inputs include the solubility parameters and molecular volume of the carrier materials, and the outputs are the critical phase separation temperature and phase diagram structure. The solubility parameter difference is calculated using Hansen solubility parameter theory and is used to evaluate the compatibility between PBAT and PLA. The interfacial tension coefficient is obtained through contact angle measurement and surface energy calculation, reflecting the interfacial bonding strength of the carrier materials.

[0037] The interfacial interaction mechanism between surface-modified carbon black and dispersant is based on colloid chemistry theory. A carbon black dispersion stability evaluation model is established by analyzing the hydrogen bonding, van der Waals forces, and electrostatic interactions between carbon black surface functional groups and dispersant molecules. The carbon black addition amount is 30 to 50 parts, and the dispersant addition amount is 1 to 5 parts. This carbon black dispersion stability evaluation model is used to predict the dispersion state and agglomeration tendency of carbon black particles in the carrier material. The inputs include the carbon black surface functional group density, the dispersant molecular chain length, and the polarity parameters of the carrier material. The outputs are the carbon black dispersion uniformity coefficient and the dispersion stability index. The carbon black surface functional group density is determined by X-ray photoelectron spectroscopy, the dispersant molecular chain length is determined by gel permeation chromatography, and the polarity parameters of the carrier material are obtained by dielectric constant measurement. The light-shielding requirement is that the light transmittance of the biodegradable mulch film material is controlled below 10%.

[0038] Among them, the optical transmittance measurement method quantitatively evaluates the uniformity of carbon black dispersion in the mulch film by measuring the transmittance distribution of the biodegradable mulch film material in the visible light wavelength range of 380nm to 780nm. The measurement method is based on Beer-Lambert's law and calculates the carbon black dispersion uniformity coefficient by analyzing the spatial variation coefficient and spectral characteristics of the transmittance. The carbon black dispersion uniformity coefficient is used to evaluate the degree of dispersion of carbon black in the carrier material.

[0039] The basic formulation includes 20 to 40 parts of carrier material, 30 to 50 parts of carbon black, 1 to 5 parts of dispersant, 0 to 20 parts of talc, 0 to 20 parts of calcium carbonate, 1 to 3 parts of antioxidant, 0.2 to 0.6 parts of lubricant, 2 to 4 parts of compatibilizer, 0.5 to 2 parts of coupling agent, and 0 to 0.2 parts of chain extender. This basic formulation represents the basic component ratio range for biodegradable mulch film materials. The carrier material is a blend of PBAT and PLA. Talc is used to improve the mechanical strength and dimensional stability of the material. Calcium carbonate is used to reduce costs and improve processing performance. Antioxidant is used to prevent oxidative degradation of the material during processing and use. Lubricant is used to improve processing fluidity. Compatibilizer is used to improve the compatibility between carrier materials. Coupling agent is used to improve the interfacial bonding between inorganic fillers and the organic matrix. Chain extender is used to adjust molecular weight and improve mechanical properties.

[0040] The degradation rate cutoff point determination experiment involved setting up 25 accelerated degradation tests with different combinations of environmental parameters. Each test included three parallel samples, and the tests were conducted continuously for 168 hours under constant temperature, humidity, and UV intensity conditions. The degradation rate change was recorded every 24 hours, and a nonlinear relationship model between the adjustment coefficient and the deviation of environmental parameters was established. The cutoff point position was obtained by fitting the model using the least squares method. The four adjustment intervals are: the first adjustment interval (0.3 to 0.42), the second adjustment interval (0.42 to 0.58), the third adjustment interval (0.58 to 0.67), and the fourth adjustment interval (0.67 to 0.7). The first adjustment interval (0.3 to 0.42) corresponds to a slight environmental deviation state, the second adjustment interval (0.42 to 0.58) corresponds to a moderate environmental deviation state, the third adjustment interval (0.58 to 0.67) corresponds to a large environmental deviation state, and the fourth adjustment interval (0.67 to 0.7) corresponds to a severe environmental deviation state.

[0041] The preparation parameters of the twin-rotor internal mixer and the twin-screw extruder include: the temperature of the twin-rotor internal mixer is controlled within the range of 90°C to 140°C based on the critical phase separation temperature; the temperature of the twin-screw extruder is controlled within the range of 90°C to 150°C; the speed of the twin-rotor main unit is 45Hz; the speed of the twin-screw main unit is 35Hz; the air volume is 20Hz; and the pelletizing frequency is 12Hz. When the critical phase separation temperature is below 100°C, the temperature of the twin-rotor internal mixer is set to 90°C to 105°C; when the critical phase separation temperature is between 100°C and 125°C, the temperature of the twin-rotor internal mixer is set to 105°C to 125°C; and when the critical phase separation temperature is above 125°C, the temperature of the twin-rotor internal mixer is set to 125°C to 140°C. The basic formula component ratio is precisely adjusted within the above range based on the output results of the biodegradation regulation and optimization model. The degradation lifetime adjustment function is used to dynamically adjust the neighbor sampling number parameter of the sparse attention mechanism in the biodegradation regulation optimization model according to the degree of difference between the actual use environment and the preset conditions. The function calculates the adjustment coefficient based on three key parameters: ambient temperature deviation, humidity change amplitude, and ultraviolet intensity fluctuation. When the adjustment coefficient is in the range of 0 to 0.3, the basic neighbor sampling number of 8 is used for model inference. When the adjustment coefficient is in the first adjustment interval of 0.3 to 0.42, the neighbor sampling number is adjusted to 10. When the adjustment coefficient is in the second adjustment interval of 0.42 to 0.58, the neighbor sampling number is adjusted to 12. When the adjustment coefficient is in the third adjustment interval of 0.58 to 0.67, the neighbor sampling number is adjusted to 15. When the adjustment coefficient is in the fourth adjustment interval of 0.67 to 0.7, the neighbor sampling number is adjusted to 18 and a multi-scale feature fusion mechanism is enabled to adjust the information propagation parameter of the biodegradation regulation optimization model. When the adjustment coefficient exceeds 0.7, the neighbor sampling number is adjusted to 20 and a global attention mechanism is enabled.

[0042] Among them, the ambient temperature deviation refers to the absolute difference between the actual ambient temperature and the standard test temperature of 25℃, obtained through real-time monitoring by a temperature sensor, and is used to quantify the impact of temperature conditions on the degradation rate. The humidity variation amplitude refers to the maximum change in relative humidity over 24 hours, calculated through continuous monitoring by a humidity sensor, reflecting the impact of humidity fluctuations on material stability. The ultraviolet intensity fluctuation refers to the standard deviation of ultraviolet intensity under sunlight conditions, obtained through measurement by an ultraviolet intensity meter, assessing the promoting effect of light changes on material degradation. These key parameters are used to quantify the complexity and intensity of environmental conditions, providing a scientific basis for the dynamic adjustment of model parameters. The multi-scale feature fusion mechanism improves the model's adaptability to complex environmental conditions by integrating environmental parameter change information at different time scales. The global attention mechanism establishes global environmental parameter correlations to achieve accurate prediction of degradation behavior under extreme environmental conditions.

[0043] The specific implementation methods of the above steps are described in detail below.

[0044] The specific implementation of step S01 is as follows: First, under test conditions of ambient temperature -10℃ to 60℃, relative humidity 20% to 90%, and ultraviolet intensity 0 to 500 watts per square meter, multi-point tests are conducted on mulch film samples with thicknesses ranging from 0.006 mm to 0.008 mm using a biodegradable mulch film material degradation performance testing device. The degradation rate and changes in mechanical properties are measured using the weight loss method and tensile strength change method, respectively. A curve relating environmental parameters to the degradation rate is established by fitting using the least squares method. Simultaneously, the compatibility index of the carrier material and the carbon black dispersion uniformity coefficient are determined using X-ray photoelectron spectroscopy and gel permeation chromatography. The compatibility index of the carrier material is obtained by calculating the interaction energy between PBAT and PLA molecular chain segments, and the value typically ranges from 0.6 to 0.9. The purpose of this step is to establish a basic database of material properties and environmental conditions, providing data support for subsequent model building.

[0045] The specific implementation of step S02 involves analyzing the conformational changes of PBAT and PLA molecular chains based on the molecular dynamics principles of polymer materials and the molecular chain segment motion theory of carrier materials. The difference in solubility parameters between the carrier materials is calculated using the Hansen solubility parameter theory; a difference less than 4 indicates good compatibility. The interfacial tension coefficient is obtained through contact angle measurement and surface energy calculation, and a thermodynamic equilibrium model is established based on the Flory-Huggins theory to predict the critical phase separation temperature of the blend system. The compatibility prediction equation uses the molecular weight distribution, glass transition temperature, and melting temperature of the carrier materials as input parameters, and outputs the compatibility index and optimal ratio range of the carrier materials. When the compatibility index is higher than 0.7, a ratio range of 20%-40% of the total mass of PBAT and 4%-8% of the total mass of PLA is determined. This step guides the scientific ratio of carrier materials through theoretical calculations, ensuring the thermodynamic stability of the blend system.

[0046] The specific implementation of step S03 involves analyzing the interfacial interaction mechanism between surface-modified carbon black and dispersant based on colloidal chemistry theory. A carbon black dispersion stability evaluation model is established by analyzing the hydrogen bonding, van der Waals forces, and electrostatic interactions between carbon black surface functional groups and dispersant molecules. X-ray photoelectron spectroscopy is used to determine the density of carbon black surface functional groups, gel permeation chromatography is used to determine the dispersant molecular chain length, and the polarity parameters of the carrier material are obtained using dielectric constant measurement. Based on Beer-Lambert's law, optical transmittance is measured in the visible light wavelength range of 380 nm to 780 nm, and the carbon black dispersion uniformity coefficient is calculated by analyzing the spatial variation coefficient and spectral characteristics of the transmittance. Based on the carbon black dispersion uniformity coefficient and dispersion stability index, the amount of carbon black added is adjusted to within the range of 30 to 50 parts, and the amount of dispersant is adjusted to within the range of 1 to 5 parts, so that the light transmittance of the biodegradable mulch film material is controlled below 10% to meet the shading requirements. The core of this step is to achieve uniform distribution of carbon black in the carrier material through quantitative dispersibility evaluation.

[0047] The specific implementation of step S04 involves constructing a deep learning-based biodegradation regulation and optimization model, using environmental temperature deviation, humidity variation, ultraviolet intensity fluctuation, carrier material ratio, and carbon black dispersion uniformity coefficient as input variables. The model employs a graph neural network architecture, utilizing a sparse attention mechanism to extract features and perform correlation analysis on the input variables. Through a dynamic adjustment mechanism of neighbor sampling numbers, the model can adaptively adjust computational complexity according to the complexity of environmental conditions, achieving accurate prediction of the lifespan of the biodegradable mulch film material. The model also outputs optimized parameters for the basic formulation, including specific values ​​for key components such as the carrier material ratio, carbon black addition amount, and dispersant dosage. This step utilizes artificial intelligence technology to achieve intelligent optimization of the material formulation, improving prediction accuracy and optimization efficiency.

[0048] The specific implementation of step S05 involves setting up 25 sets of accelerated degradation tests with different combinations of environmental parameters. Each test set includes 3 parallel samples, and the tests are conducted continuously for 168 hours under constant temperature, humidity, and UV intensity conditions. The degradation rate change is recorded every 24 hours, and a nonlinear relationship model between the adjustment coefficient and the environmental parameter deviation is established using the least squares method. The adjustment coefficient range is subdivided into four adjustment intervals: the first interval (0.3 to 0.42) corresponds to a slight environmental deviation state; the second interval (0.42 to 0.58) corresponds to a moderate environmental deviation state; the third interval (0.58 to 0.67) corresponds to a large environmental deviation state; and the fourth interval (0.67 to 0.7) corresponds to a severe environmental deviation state. The boundary points of each adjustment interval are determined through statistical analysis and used to set the parameter switching threshold of the degradation lifetime adjustment function. This step establishes a mapping relationship between environmental conditions and model parameters through a large amount of experimental data, providing a scientific basis for the adaptive adjustment of the model.

[0049] The specific implementation of step S06 involves monitoring the ambient temperature deviation, humidity variation, and UV intensity fluctuation in real time using temperature sensors, humidity sensors, and UV intensity meters, based on the actual conditions of the target usage environment. The ambient temperature deviation is calculated as the absolute difference between the actual usage ambient temperature and the standard test temperature of 25°C. The humidity variation is the maximum change in relative humidity over 24 hours, and the UV intensity fluctuation is the standard deviation of UV intensity under sunlight conditions. These environmental parameters, along with the carrier material compatibility index and carbon black dispersion uniformity coefficient, are substituted into the biodegradation regulation and optimization model. The model calculates the optimal carrier material ratio, carbon black addition amount, dispersant dosage, and other formulation parameters. This step achieves a precise mapping from environmental conditions to material formulation, ensuring that the prepared mulch film material has the expected service life under certain environmental conditions.

[0050] The specific implementation of step S07 is as follows: based on the formula parameters calculated in step S06, and combined with the basic formula component ratio, precise adjustments are made within a specified range. A twin-rotor internal mixer is used for melt blending. The temperature is controlled within the range of 90℃ to 140℃ according to the critical phase separation temperature. When the critical phase separation temperature is below 100℃, it is set to 90℃ to 105℃; when the critical phase separation temperature is between 100℃ and 125℃, it is set to 105℃ to 125℃; and when the critical phase separation temperature is above 125℃, it is set to 125℃ to 140℃. The twin-screw extruder temperature is controlled between 90℃ and 150℃, the twin-rotor main unit speed is 45Hz, the twin-screw main unit speed is 35Hz, the air volume is 20Hz, and the pelletizing frequency is 12Hz. The degradation lifetime adjustment function adjusts the neighbor sampling number parameter of the biodegradation regulation optimization model in real time according to the boundary points of four adjustment intervals. When the adjustment coefficient belongs to different intervals, neighbor sampling numbers of 8, 10, 12, 15, 18, and 20 are used respectively. Under severe environmental deviation conditions, a multi-scale feature fusion mechanism and a global attention mechanism are activated. This step, through precise process control and intelligent parameter adjustment, ensures that the final prepared biodegradable mulch film material has the expected performance and lifetime.

[0051] The biodegradation regulation and optimization model employs a deep learning architecture based on graph neural networks, primarily consisting of an input layer, a feature extraction layer, a sparse attention layer, a prediction layer, and an output layer. The input layer receives five key variables: ambient temperature deviation, humidity variation, UV intensity fluctuation, carrier material ratio, and carbon black dispersion uniformity coefficient. The feature extraction layer uses a multilayer perceptron structure to perform nonlinear transformations and feature representation learning on the input variables. The sparse attention layer uses a graph convolutional neural network to analyze the correlations between variables, dynamically adjusting computational complexity using a neighbor sampling mechanism, and adaptively selecting the number of neighbor nodes based on the complexity of environmental conditions. The prediction layer uses a residual network structure, combined with a multi-scale feature fusion mechanism to process environmental parameter changes at different time scales. The output layer generates material lifetime prediction results and formulation optimization parameters.

[0052] The establishment of the training dataset is divided into four stages: data collection, data preprocessing, feature engineering, and data augmentation. The data collection stage obtains basic data through material degradation experiments under different environmental conditions, including environmental parameters such as temperature, humidity, and UV intensity, as well as corresponding material degradation rates and changes in mechanical properties. The data preprocessing stage cleans, denoises, and standardizes the raw data, removing outliers and missing values. The feature engineering stage constructs combined and time-series features of environmental parameters, using principal component analysis to reduce data dimensionality. The data augmentation stage expands the dataset size using interpolation and Monte Carlo methods to improve the model's generalization ability. The final training dataset contains 10,000 sample data sets, covering various combinations of environmental conditions and material formulation parameters.

[0053] The reason why the biodegradation regulation and optimization model is suitable for solving the technical problem of this invention is that traditional material formulation design mainly relies on experience and trial and error methods, which cannot accurately predict the degradation behavior of materials under different environmental conditions. Existing mathematical models, such as the Arrhenius equation, can describe the influence of temperature on the degradation rate, but cannot comprehensively consider the synergistic effects of multiple environmental factors. Another existing technology is a prediction model based on regression analysis, which can handle multivariate problems, but has limited fitting ability for nonlinear relationships. The biodegradation regulation and optimization model of this invention can capture the complex nonlinear relationships between environmental parameters through a graph neural network architecture, achieve focused attention on key factors through a sparse attention mechanism, and improve the adaptability to time-varying environmental conditions through a multi-scale feature fusion mechanism. Compared with traditional methods, this model can simultaneously achieve accurate prediction of material lifetime and intelligent optimization of formulation parameters, significantly improving the efficiency and accuracy of material design. The model's adaptive adjustment mechanism enables it to dynamically adjust the calculation strategy according to actual environmental conditions, optimizing computational efficiency while ensuring prediction accuracy, providing strong technical support for the industrial application of biodegradable mulch film materials.

[0054] The first key technical concept of this invention is a compatibility prediction and proportion optimization technique based on the molecular chain segment motion theory of carrier materials. Compared with traditional experimental proportioning methods, this technique predicts the compatibility behavior of PBAT and PLA at the molecular level through Hansen solubility parameter theory and Flory-Huggins theory, enabling accurate determination of the optimal proportion range before material preparation. Traditional methods require extensive experimental trial and error to find a suitable proportion, while this technique directly guides proportioning design through theoretical calculations, significantly reducing the number of experiments and development cycle. The core advantage of this technology lies in combining the molecular dynamics principles of polymer materials with practical engineering applications, achieving accurate prediction from microscopic molecular structure to macroscopic material properties.

[0055] The second key technological approach is a carbon black dispersion stability evaluation and control technique based on colloid chemistry theory. Traditional carbon black dispersion mainly relies on empirical adjustments of dispersant dosage and mixing process parameters, making it difficult to achieve uniform dispersion of carbon black in carrier materials. This technique, by analyzing the interfacial interaction mechanism between carbon black surface functional groups and dispersant molecules, establishes a quantitative dispersion stability evaluation model, capable of accurately predicting the dispersion state and agglomeration tendency of carbon black particles. Combined with quantitative evaluation methods using optical transmittance measurement, this technique achieves precise control of carbon black dispersion uniformity, ensuring stable light-shielding performance of the mulch film material.

[0056] The third key technological approach is a biodegradation regulation and optimization model and an adaptive parameter adjustment mechanism based on graph neural networks. Existing material performance prediction models often employ linear regression or simple nonlinear fitting methods, which cannot effectively handle the complex coupling relationships between multiple environmental factors. This technology uses a graph neural network architecture to capture the nonlinear correlations between environmental parameters, achieves focused attention on key factors through a sparse attention mechanism, and improves adaptability to time-varying environmental conditions through a multi-scale feature fusion mechanism. The adaptive parameter adjustment mechanism dynamically adjusts the model's calculation strategy according to the complexity of environmental conditions, optimizing computational efficiency while ensuring prediction accuracy.

[0057] The fourth key technological approach is a degradation lifetime adjustment function and a zoned control strategy based on real-time monitoring of environmental parameters. Traditional material lifetime prediction is usually based on standard environmental conditions and cannot adapt to the dynamic changes in actual use environments. This technology establishes a mapping relationship between environmental parameters and model adjustment coefficients by real-time monitoring of environmental temperature deviations, humidity variations, and ultraviolet intensity fluctuations. The adjustment coefficient range is divided into four zones corresponding to different environmental deviation states, thus realizing the dynamic adjustment of model parameters.

[0058] The synergistic effect of these four key technological approaches forms a complete technological system, providing a systematic solution from the theoretical foundation of materials design to the entire process of engineering implementation. Carrier material compatibility prediction technology provides theoretical guidance for the design of the material system; carbon black dispersion control technology ensures the uniform distribution of functional components in the material; the biodegradation regulation and optimization model enables accurate prediction of material performance and intelligent optimization of formulations; and the environmental adaptive adjustment mechanism allows the material to adapt to the complex changes in the actual use environment. Compared with traditional empirical design methods, this technological system achieves a technological leap from qualitative to quantitative, from static to dynamic, and from empirical to intelligent, significantly improving the design efficiency and performance of biodegradable mulch film materials, and providing strong technical support for the industrial application of the materials.

[0059] It should be noted that this invention also solves the following technical problem: the problem of poor compatibility of carrier materials leading to unstable material structure and easy degradation. In the traditional preparation process of PBAT and PLA blends, the two materials have significant differences in molecular structure and polarity. Compatibility assessment lacks theoretical guidance, often resulting in phase separation. The resulting microscopic defects become weak points in degradation, accelerating the overall degradation process of the material. This invention establishes a theory of molecular chain segment motion and a compatibility prediction equation for carrier materials. Combined with the Hansen solubility parameter theory, it quantitatively calculates the difference in solubility parameters and the interfacial tension coefficient, achieving accurate assessment and optimization of the compatibility of carrier materials. Based on the Flory-Huggins thermodynamic equilibrium model, it predicts the critical temperature for phase separation and guides processing temperature control, ensuring good compatibility of the carrier material at the molecular level, eliminating structural defects, and significantly improving the overall stability and anti-degradation ability of the material.

[0060] The technical problem of accelerated local degradation caused by uneven carbon black dispersion. In existing technologies, carbon black easily agglomerates in carrier materials, forming an unevenly dispersed microstructure. Agglomeration areas become stress concentration points and degradation initiation points, leading to preferential degradation in these areas and shortening the overall service life. This invention establishes a carbon black dispersion stability evaluation model based on colloid chemistry theory, deeply analyzes the hydrogen bonding, van der Waals forces, and electrostatic interaction mechanisms between carbon black surface functional groups and dispersant molecules, and achieves uniform dispersion of carbon black in carrier materials by precisely controlling the density of carbon black surface functional groups and the chain length of dispersant molecules. Combined with a quantitative evaluation system established by optical transmittance measurement, it ensures precise control of the carbon black dispersion uniformity coefficient, eliminates local agglomeration, forms a uniform and stable microstructure, effectively avoids the problem of accelerated local degradation, and extends the overall service life of the material.

[0061] Specifically, the principle of this invention is as follows: The fundamental reason why this invention can solve the problem of insufficient lifespan of biodegradable mulch film materials lies in the establishment of a systematic theoretical system and precise control mechanism for lifespan extension. First, through in-depth analysis of the conformational changes and interaction energies of PBAT and PLA molecular chains using the molecular chain segment motion theory of carrier materials, and by combining the Flory-Huggins thermodynamic equilibrium model to accurately calculate the critical phase separation temperature, this provides molecular-level theoretical guidance for optimizing the carrier material ratio, significantly improving the compatibility and structural stability of the blend system and slowing down the degradation process. Second, based on the colloid chemistry theory, a carbon black dispersion stability evaluation model is established. By quantitatively controlling the density of functional groups on the carbon black surface and the length of the dispersant molecular chains, uniform dispersion of carbon black in the carrier material is achieved, forming a stable network structure that effectively prevents the penetration and diffusion of degradation factors, enhancing the material's resistance to degradation. Third, the biodegradation regulation and optimization model uses a sparse attention mechanism to handle multidimensional environmental parameters. By establishing a nonlinear relationship between environmental temperature deviation, humidity variation, and ultraviolet intensity fluctuation and the degradation rate, accurate prediction of degradation behavior under different environmental conditions is achieved, providing a scientific basis for lifespan extension. Finally, the degradation life adjustment function is set based on the boundary points of four adjustment intervals. It can dynamically adjust the model parameters and formulation composition according to the target life requirements and environmental conditions, and realize the full coverage life extension control under conditions of slight to severe environmental deviations, ensuring that the mulch film material can meet the full growth needs of different crops.

[0062] The following provides a specific embodiment 1 of the present invention, and the specific implementation of each step in this embodiment 1 is described in detail below.

[0063] The specific implementation of step S01 is to use a biodegradable mulch film material degradation performance testing device to conduct tests under various environmental conditions, and establish a relationship curve between environmental parameters and degradation rate, which is specifically expressed as follows:

[0064]

[0065] In the formula, R d The degradation rate is expressed in mg / (cm³). 2 ·d); T is the ambient temperature, in °C; H is the relative humidity, in %; U is the ultraviolet radiation intensity, in W / m². 2 k1 is the material constant, with units of mg / (cm³). 2 ·d·℃ {a_1}·％ {a_2}·(W / m 2)^{a_3}), with a value range of 0.02 to 0.08; a1, a2, and a3 are environmental sensitivity indices, all dimensionless parameters, with values ​​ranging from 0.8 to 1.2, 0.5 to 0.8, and 0.3 to 0.6, respectively; ε1 is the error term, with units of mg / (cm³). 2 •d), ranging from 0.1 to 0.3. The carbon black dispersion uniformity coefficient is determined based on the optical transmittance assessment according to the Beer-Lambert law, specifically expressed as follows:

[0066]

[0067] In the formula, D carbon σ is the carbon black dispersion uniformity coefficient, dimensionless; thrans The standard deviation of transmittance is dimensionless. The average transmittance is dimensionless; n is the number of measurement points; T i Let be the transmittance at the i-th measurement point, which is dimensionless. The compatibility index of the carrier material is calculated as follows:

[0068]

[0069] In the formula, C comp δ is the compatibility index of the carrier material, dimensionless; PBAT and δ PLA These are the solubility parameters for PBAT and PLA, respectively, in MPa^{1 / 2}; γ interface This refers to the interfacial tension coefficient, with units of mJ / m. 2 R is the gas constant, with a value of 8.314 J / (mol·K); T abs This refers to absolute temperature, expressed in Kelvin (K). Parameters are obtained as follows: T, H, and U are acquired through real-time monitoring using sensors; δ... PBAT and δ PLA γ was obtained through theoretical calculations based on the Hansen solubility parameter. interface The values ​​were obtained through contact angle measurement and surface energy calculation; a1, a2, and a3 were obtained by fitting experimental data using the least squares method; T i The measurements were obtained using a visible spectrophotometer in the wavelength range of 380 nm to 780 nm.

[0070] The specific implementation of step S02 is to establish a compatibility prediction equation for the PBAT / PLA blend system based on the molecular chain segment motion theory of the carrier material, as specifically expressed below:

[0071]

[0072] In the formula, χ is the Flory-Huggins interaction parameter, which is dimensionless; V m Reference molar volume, unit: cm³3 / mol; δ d δ p δ h These represent the solubility parameter components corresponding to dispersing force, polar force, and hydrogen bonding force, respectively, in MPa^{1 / 2}; the superscripts PBAT and PLA indicate the parameters of the corresponding materials. The detailed calculation of the interfacial tension coefficient is as follows:

[0073]

[0074] In the formula, γ PBAT and γ PLA The surface tensions of PBAT and PLA are respectively, in mJ / m. 2 ;θ contact The contact angle is expressed in degrees. The critical temperature for phase separation is calculated as follows:

[0075]

[0076] In the formula, T critical φ is the critical temperature for phase separation, expressed in Kelvin (K). PBAT and φ PLA N represents the volume fractions of PBAT and PLA, respectively, dimensionless; PBAT and N PLA These are the degree of aggregation for PBAT and PLA, respectively, and are dimensionless. The parameter is obtained as follows: V m Obtained through density measurement and molecular weight calculation; δ d δ p δ h φ was obtained by calculation using the group contribution method. PBAT and φ PLA Obtained based on mass ratio and density; N PBAT and N PLA γ was obtained by gel permeation chromatography. PBAT and γ PLA Obtained by surface tension meter measurement; θ contact The angle was obtained by measuring the contact angle with a contact angle meter.

[0077] The specific implementation of step S03 is as follows: a carbon black dispersion stability evaluation model is established based on the interfacial interaction mechanism between surface-modified carbon black and dispersant. The calculation of the carbon black dispersion uniformity coefficient is expressed as follows:

[0078]

[0079] In the formula, D uniformity σ is the carbon black dispersion uniformity coefficient, dimensionless; T is the standard deviation of transmittance, which is dimensionless; α is the average transmittance, dimensionless; α is the interfacial interaction intensity coefficient, in nm. 2 / each, with a value ranging from 0.5 to 1.2; ρ functional The density of functional groups on the surface of carbon black is expressed in units per nm. 2 L dispersant The length of the dispersant molecular chain is expressed in nm. The dispersion stability index is calculated as follows:

[0080]

[0081] In the formula, S stability E is the dispersion stability index, dimensionless. interaction The interaction energy between a single functional group and the dispersant is expressed in J; kJ. B T is the Boltzmann constant, with a value of 1.38 × 10^{-23} J / K; proc Processing temperature, in K; d particle The average particle size of carbon black is given in nm. Transmittance is calculated based on the Beer-Lambert law, as follows:

[0082] T transmittance =exp(-ε·C carbon ·d film );

[0083] In the formula, T transmittance Transmittance is dimensionless; ε is the molar absorptivity of carbon black, in L / (mol·cm); C carbon This refers to the carbon black concentration, expressed in mol / L; d film This refers to the thickness of the plastic film, in cm. The parameter is obtained using: σ T and Obtained through optical transmittance measurement; ρ functional Determined by X-ray photoelectron spectroscopy analysis; L dispersant The method was used for determination by gel permeation chromatography; ε was obtained by calibration using a UV-Vis spectrophotometer; E interaction Obtained through molecular dynamics simulations; d particle The results were obtained by dynamic light scattering method.

[0084] The specific implementation of step S04 is the same as described above, and will not be repeated in detail here.

[0085] The specific implementation of step S05 is to establish a nonlinear relationship model between the adjustment coefficient and the deviation of environmental parameters by determining the degradation rate threshold, as shown below:

[0086] β=w1·ΔT norm +w2·ΔH norm +w3·ΔUnorm +w4·(·ΔT norm ) 2 +w5·(ΔH norm ) 2 +w6·(ΔU norm ) 2 +ε2;

[0087] In the formula, β is the adjustment coefficient, which is dimensionless; ΔT norm , ΔU norm ΔU norm εa represents the standardized deviations of temperature, humidity, and UV intensity, all dimensionless; w1 to w6 are regression coefficients, all dimensionless, with values ​​ranging from 0.2 to 0.5, 0.1 to 0.4, 0.15 to 0.45, 0.05 to 0.15, 0.02 to 0.12, and 0.08 to 0.25, respectively; ε2 is the error term, dimensionless, ranging from 0.05 to 0.15. The standardized deviation is calculated as follows:

[0088]

[0089] In the formula, T actual This refers to the actual ambient temperature, in °C; T standard The standard test temperature is 25℃; T range Temperature testing range: 70℃; ΔH 24h The humidity change over 24 hours is expressed in percentage (%). range Humidity test range: 70%; σ U The standard deviation of ultraviolet radiation intensity is expressed in W / m². 2 U range UV intensity testing range: 500W / m 2 The location of the dividing point was determined using statistical analysis methods, as shown below:

[0090]

[0091] In the formula, B i β represents the position of the i-th boundary point, which is dimensionless; j Let J be the adjustment coefficient for the j-th group of experiments; The average value of the adjustment coefficient; k i The coefficients for the dividing points are k1 = -0.5, k2 = 0, k3 = 0.5, and k4 = 1.0. The parameters are obtained as follows: T actual ΔH 24h σ U Obtained through continuous monitoring by sensors; w1 to w6 were obtained by fitting 25 sets of accelerated degradation test data using the least squares method; β j The value was calculated by recording the degradation rate change every 24 hours during a continuous 168-hour test.

[0092] The specific implementation method of step S06 is the same as described above, and will not be repeated in detail here.

[0093] The specific implementation of step S07 is to use a degradation lifetime adjustment function to adjust the neighbor sampling number parameter of the biodegradation regulation optimization model in real time. The degradation lifetime adjustment function is expressed as follows:

[0094]

[0095] In the formula, N sampling N represents the number of neighbor samples. base The number of basic neighbor samples, with a value of 8; β is the floor function; γ is a special adjustment factor with a value of 10; I(·) is an indicator function, where I(β>0.67) = 1 when β>0.67, and 0 otherwise. The parameters are obtained as follows: β is calculated according to the formula in step S05; N base γ and γ are preset parameter values.

[0096] It should be noted that the formula for the relationship between environmental parameters and degradation rate is... Based on the Arrhenius equation and multifactor regression theory, a power function formula is used to describe the nonlinear effects of temperature, humidity, and UV intensity on the degradation rate. Compared to traditional single-factor linear models, this formula can more accurately predict material degradation behavior under complex environmental conditions, significantly improving the accuracy of lifetime prediction and providing reliable data support for material formulation optimization. (Carbon black dispersion uniformity coefficient formula) Through the standard deviation term The degree of dispersion of quantified transmittance distribution enables a precise quantitative assessment of the dispersion state of carbon black compared to traditional visual observation methods.

[0097] Formula for calculating the compatibility index of carrier materials It combines Hansen's solubility parameter theory and interfacial thermodynamics theory, where the exponential term exp(-γ) interface / (R·T abs This formula describes the temperature-dependent effect of interfacial energy on compatibility. Compared with traditional qualitative assessment methods, this formula enables quantitative prediction of compatibility, avoids a large number of trial and error experiments, and significantly shortens the material development cycle.

[0098] Formula for calculating Flory-Huggins interaction parameters Based on the thermodynamic theory of polymer solutions, the weighted terms and Reflecting the weighting difference between polar interactions and hydrogen bonding interactions relative to dispersion forces, this formula can more accurately predict the compatibility of blend systems compared to the simplified solubility parameter difference method, providing theoretical guidance for the proportioning of carrier materials. Interfacial tension coefficient calculation formula.

[0099] Based on Young's equations and geometric mean theory, where the geometric mean term It reflects the intensity of the interaction between the two phases and can more accurately reflect the essence of the interface interaction compared to the simple arithmetic mean method.

[0100] Formula for calculating critical phase separation temperature Based on the thermodynamic equilibrium theory, the denominator φ PBAT ·φ PLA ·(1 / N PBAT +1 / N PLA Taking into account the effects of component concentration and molecular weight on phase separation, this formula can scientifically determine the processing temperature range compared to empirical temperature setting methods, thus avoiding the deterioration of material properties caused by phase separation.

[0101] Formula for calculating the dispersion uniformity coefficient of carbon black Based on the colloidal stability theory and optical transmission theory, the exponential term exp(-α·ρ) functional ·L dispersant This formula describes the exponentially enhancing effect of surface modification on dispersion stability. Compared to traditional visual observation methods, this formula provides a quantitative assessment of dispersion uniformity, ensuring the stability of the shading performance of the mulch film material. Dispersion Stability Index Formula Through energy ratio The competition between interaction energy and thermal disturbance kinetic energy is quantified, and compared with static dispersion evaluation methods, it can predict dispersion stability under dynamic processing conditions.

[0102] formula for calculating light transmittance T transmittance =exp(-ε·C carbon ·d film Based on Beer-Lambert's law, the effect of carbon black concentration and thickness on light transmittance is described by an exponential decay function. Compared with empirical adjustment methods, this formula can accurately control the shading effect of the mulch film and meet the functional requirements of agricultural applications.

[0103] The nonlinear relationship model between the adjustment coefficient and the deviation of environmental parameters is β=w1·ΔT. norm +w2·ΔH norm +w3·ΔU norm +w4·(ΔT norm ) 2+w5·(ΔH norm ) 2 +w6·(ΔU norm ) 2 +ε2 is based on multiple regression theory, where the quadratic term (ΔT) norm ) 2 、(ΔH norm ) 2 、(ΔU norm ) 2 This model captures the nonlinear effect of environmental parameter deviations on the system response. Compared to linear regression models, it better fits nonlinear relationships, improving the accuracy of environmental adaptability assessment. (Breakpoint calculation formula) Through the mean term and standard deviation The linear combination of the data determines the location of the dividing point, which can better reflect the statistical distribution characteristics of the data compared with the equal interval division method.

[0104] Degradation lifetime adjustment function Based on piecewise function theory, the floor function A mapping from continuously adjusted coefficients to discrete sample numbers was implemented. The indicator function I (β>0.67) triggers additional computational resource allocation under extreme environmental conditions. Compared to the continuously adjusted method, this function avoids frequent parameter changes, improving model stability and computational efficiency while ensuring adaptability to different environmental conditions. Standardized deviation formula set. Normalization eliminates the dimensional differences between different environmental parameters, enabling comparison and weight allocation of various environmental factors within the same numerical range. Compared to directly using raw data, this method can more fairly assess the relative importance of each environmental factor, providing a scientific basis for adjusting model parameters.

[0105] Further explanation is needed regarding the biodegradation regulation and optimization model in this embodiment, which employs a deep learning architecture based on graph neural networks. This architecture consists of a five-layer network: an input layer, a feature extraction layer, a sparse attention layer, a prediction layer, and an output layer. The input layer receives five key variables: ambient temperature deviation, humidity variation, ultraviolet intensity fluctuation, carrier material ratio, and carbon black dispersion uniformity coefficient. These variables are standardized and normalized using a data preprocessing module to establish a 512-dimensional multidimensional feature vector representation, ensuring effective fusion of variables with different dimensions. The feature extraction layer uses a three-layer multilayer perceptron structure, with each layer containing 256 neurons. It performs deep feature transformation and representation learning on the input variables using the ReLU nonlinear activation function, employs batch normalization to avoid overfitting, and uses residual connections to maintain gradient propagation stability, effectively extracting potential correlation patterns and nonlinear mapping relationships between variables. The sparse attention layer is the core component of the model. It constructs a graph of relationships between variables using a graph convolutional neural network, enabling in-depth analysis of complex correlations between variables. An adaptive neighbor sampling mechanism dynamically adjusts the number of computation nodes based on the complexity of environmental conditions. When environmental deviations are small, 8 neighbor nodes are used for local computation. As environmental complexity increases, the number of nodes is gradually expanded to 20, and a global attention mechanism is enabled. This significantly optimizes computational efficiency and model convergence speed while maintaining prediction accuracy. The prediction layer employs a deep residual network structure containing four residual blocks. Each residual block integrates a multi-scale feature fusion mechanism, which can integrate environmental parameter changes at three different time scales: short-term, medium-term, and long-term. Skip connection technology effectively avoids the gradient vanishing and gradient exploding problems during deep network training. Simultaneously, an attention weight allocation mechanism is introduced to automatically adjust feature weights based on the influence of different environmental parameters on degradation behavior. The output layer generates material lifetime prediction results and formulation optimization parameters through two parallel fully connected neural network branches. The lifetime prediction branch outputs the expected number of days of use and the confidence interval, while the formulation optimization branch outputs the precise values ​​of key parameters such as the optimal ratio of carrier materials, the amount of carbon black added, and the amount of dispersant. This enables accurate prediction of degradation behavior under different environmental conditions and intelligent optimization design of the formulation.

[0106] To better understand and implement this invention, the following is an example 2 of a specific application scenario: A technical team needs to develop biodegradable mulch film materials for an agricultural base in a certain region. The region has special environmental conditions, with large temperature differences between day and night, high ultraviolet intensity, and drastic humidity changes. Traditional mulch film materials degrade too quickly under these conditions and cannot meet the requirements of the crop growth cycle.

[0107] First, the technical team conducted detailed parameter tests on the target usage environment. Through seven consecutive days of environmental monitoring, they found that the daytime temperature in the area could reach 35℃, while the nighttime temperature dropped to 8℃. Relative humidity varied between 30% and 75%, and ultraviolet radiation intensity could reach a maximum of 420W / m². 2 Based on this data, the technical team calculated that the ambient temperature deviation was 10℃, the humidity variation was 45%, and the standard deviation of ultraviolet intensity fluctuation was 85W / m. 2 After standardization, the standardized values ​​for temperature deviation were 0.143, humidity deviation were 0.643, and UV intensity deviation were 0.170.

[0108] Next, the technical team selected PBAT and PLA as carrier materials for compatibility analysis. Using Hansen solubility parameter theory, the solubility parameter of PBAT was calculated to be... The difference between the two is This indicates good compatibility potential. The surface tension of PBAT was measured to be 42.5 mJ / m² via contact angle measurement. 2 The surface tension of PLA is 37.8 mJ / m. 2 With a contact angle of 68 degrees, the calculated interfacial tension coefficient is 8.2 mJ / m. 2 Based on this, the optimal ratio of PBAT to PLA was determined to be 50:10, with a carrier material compatibility index of 0.76.

[0109] The technical team used the Flory-Huggins theory to calculate the interaction parameters, obtaining an interaction parameter of 0.28 at 25℃. Further calculations revealed the critical phase separation temperature to be 115℃. This result guides the setting of the temperature control range for the dual-rotor internal mixer between 105℃ and 125℃, ensuring that phase separation does not occur during the blending process.

[0110] In the design of the carbon black dispersion system, the technical team selected surface-modified carbon black as the light-shielding component. X-ray photoelectron spectroscopy analysis determined the functional group density on the carbon black surface to be 2.8 groups / nm. 2 The selected dispersant has a molecular chain length of 15 nm. For example... Figure 3 As shown, under different carbon black addition amounts, the dispersion uniformity coefficient first increases and then decreases with the change of dispersant dosage. Tests were conducted using optical transmittance measurement in the wavelength range of 380nm to 780nm. When the carbon black addition amount was 42 parts and the dispersant dosage was 3.2 parts, the dispersion uniformity coefficient reached its maximum value of 0.89. At this point, the light transmittance of the mulch film was 6.8%, meeting the shading requirements.

[0111] The technical team established 25 sets of accelerated degradation tests with different combinations of environmental parameters, each set containing 3 parallel samples, and tested continuously for 168 hours under constant conditions. As shown in Table 1, the degradation rate test results under different environmental conditions showed a clear environmental dependence.

[0112] Table 1 Degradation rate test data under different environmental conditions

[0113] Test group Temperature (°C) humidity(%) <![CDATA[Ultraviolet intensity (W / m 2 )]]> <![CDATA[Degradation rate (mg / (cm 2 ·d))]]> 1 25 50 200 0.42 2 35 30 420 0.78 3 15 75 150 0.31 4 40 60 380 0.89 5 20 40 280 0.55 6 30 65 350 0.71 7 10 80 100 0.28 8 45 35 450 0.95

[0114] By fitting the experimental data using the least squares method, the technical team obtained the regression coefficients of the nonlinear relationship model between the adjustment coefficient and the deviation of environmental parameters: the coefficients of the linear terms were 0.34, 0.28, and 0.31, and the coefficients of the quadratic terms were 0.09, 0.06, and 0.12. Based on the environmental parameters of the plateau region, the adjustment coefficient was calculated to be 0.62, which falls within the third adjustment interval, corresponding to a relatively large environmental deviation.

[0115] The technical team constructed a biodegradation regulation and optimization model. This model adopts a graph neural network architecture, and the input layer receives five key variables: ambient temperature deviation, humidity variation, ultraviolet intensity fluctuation, carrier material ratio, and carbon black dispersion uniformity coefficient. Based on the calculation results with an adjustment coefficient of 0.62, the number of neighbor samples in the model was adjusted to 15, and a multi-scale feature fusion mechanism was enabled to adapt to the complex plateau environmental conditions.

[0116] After training, the model outputs optimized formulation parameters for the environmental conditions of the plateau region. As shown in Table 2, the optimized basic formulation composition ratio can achieve the expected service life under the target environment.

[0117] Table 2. Optimized Basic Formula Component Allocation Ratio

[0118] Component Name Dosage (per serving) Functions PBAT 35 carrier material PLA 7 carrier material Surface modified carbon black 42 Light-blocking components dispersant 3.2 Dispersion stability talcum powder 12 Mechanical strengthening <![CDATA[CaCO3]]> 8 Cost control antioxidants 2.1 Antioxidant lubricant 0.4 Processing aids compatibilizer 3.5 Interface improvements Coupling agent 1.2 Interface integration

[0119] The technical team prepared the materials according to the optimized formula, using a twin-rotor internal mixer at 115°C for melt blending with a main motor speed of 45Hz. The mixture was then extruded using a twin-screw extruder at 120°C with a main motor speed of 35Hz, an airflow rate of 20Hz, and a pelletizing frequency of 12Hz. During the preparation process, the degradation lifetime adjustment function adjusted the model parameters in real time according to environmental conditions to ensure the stability of product performance.

[0120] The prepared biodegradable mulch film material had a thickness of 0.007 mm and underwent a 6-month field trial in a high-altitude environment. Figure 4As shown, the mechanical properties of the mulch film material change curve over time indicate that the tensile strength remains above 15 MPa in the first 3 months, meeting the coverage requirements during the crop growth period. It begins to degrade slowly in the 4th month, and the tensile strength drops below 5 MPa at the end of the 6th month, achieving the expected degradation time control.

[0121] Environmental monitoring data during the experiment showed that the mulch film material can adapt to the complex environmental changes in plateau regions. For example... Figure 5 As shown, the light transmittance remained below 8% throughout the entire service life, effectively blocking strong ultraviolet radiation and providing a good growth environment for crop roots. Meanwhile, the carbon black dispersion uniformity on the mulch film surface remained stable during use, with no obvious agglomeration.

[0122] This invention represents a significant technological advancement over traditional empirical methods for designing mulch films. Traditional methods rely primarily on trial and error and empirical adjustments, failing to accurately predict material degradation behavior under complex environmental conditions and often requiring numerous repeated experiments to find a suitable formulation. This invention, by establishing a quantitative model of the relationship between environmental parameters and degradation rates, achieves a precise mapping from environmental conditions to material performance, significantly reducing development cycles and testing costs. Traditional compatibility assessments mainly employ qualitative observation and simple physical tests, making it difficult to accurately predict the thermodynamic stability of blended systems. This invention, based on molecular dynamics theory and thermodynamic principles, achieves scientific prediction of compatibility and formulation optimization through quantitative calculations of solubility and interaction parameters. Regarding carbon black dispersion control, traditional methods rely mainly on visual observation and empirical adjustments, failing to achieve precise control of dispersion uniformity. This invention, through optical transmittance measurement and colloidal stability theory, establishes a quantitative evaluation system for dispersion uniformity, ensuring the stability of the mulch film's shading performance. Most importantly, the biodegradation regulation and optimization model constructed in this invention possesses environmental adaptability, dynamically adjusting material formulations and process parameters according to changes in the actual usage environment—a technological breakthrough impossible with traditional static design methods.

[0123] It should be noted that the variables involved in this invention are explained in detail in Table 3 below.

[0124] Table 3. Variable Explanation Table

[0125]

[0126]

[0127] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for extending the lifespan of biodegradable mulch film materials, characterized in that, Includes the following steps: S01. Using a biodegradable mulch film material degradation performance testing device, the degradation rate and mechanical property changes of the biodegradable mulch film material are measured under various environmental conditions, a relationship curve between environmental parameters and degradation rate is established, and the compatibility index of the carrier material and the carbon black dispersion uniformity coefficient are recorded, wherein the carrier material is a blend system of PBAT and PLA. S02. Based on the molecular chain segment motion theory of carrier materials, a compatibility prediction equation for the PBAT and PLA blend system is established. By calculating the difference in solubility parameters and interfacial tension coefficients between carrier materials, the proportion range of carrier materials is determined. The critical phase separation temperature of the blend system is predicted by a thermodynamic equilibrium model. The critical phase separation temperature is used to guide the temperature control range of the dual-rotor internal mixer. S03. Based on the interfacial interaction mechanism between surface-modified carbon black and dispersant, a carbon black dispersion stability evaluation model is established by controlling the density of functional groups on the carbon black surface and the molecular chain length of the dispersant. The carbon black dispersion uniformity coefficient is quantitatively evaluated by optical transmittance measurement. The amount of carbon black added and the amount of dispersant are adjusted according to the carbon black dispersion uniformity coefficient and dispersion stability index so that the light transmittance of the biodegradable mulch film material meets the shading requirements. S04. Construct a biodegradation regulation and optimization model, using environmental temperature deviation, humidity variation, ultraviolet intensity fluctuation, carrier material compatibility index and carbon black dispersion uniformity coefficient as input variables. Through the neighbor sampling number adjustment of the sparse attention mechanism in the model, the lifespan of biodegradable mulch film materials can be accurately predicted and the basic formula optimized. S05. The experiment is determined by the degradation rate boundary point. Accelerated degradation test is conducted under different combinations of environmental parameters. A nonlinear relationship model between the adjustment coefficient and the deviation of environmental parameters is established. The range of the adjustment coefficient is subdivided into four adjustment intervals. The boundary points of the four adjustment intervals are used to set the parameter switching threshold of the degradation lifetime adjustment function. S06. Based on the temperature range, humidity changes, and light intensity of the target environment, determine the expected service life requirements of the biodegradable mulch film material, calculate the environmental temperature deviation, humidity change range, and ultraviolet intensity fluctuation, and substitute them together with the carrier material compatibility index and carbon black dispersion uniformity coefficient into the biodegradation regulation and optimization model to calculate the optimal carrier material ratio, carbon black addition amount, dispersant dosage, and optimize the specific dosage of each component in the basic formula. S07. Based on the calculated formula parameters and the basic formula component ratio, biodegradable mulch film material is prepared using a twin-rotor internal mixer and a twin-screw extruder. The temperature of the twin-rotor internal mixer is controlled according to the critical phase separation temperature, and the neighbor sampling number parameter of the biodegradation control optimization model is adjusted in real time based on the boundary points of four adjustment intervals through the degradation lifetime adjustment function.

2. The method for extending the lifespan of biodegradable mulch film materials according to claim 1, characterized in that, The thermodynamic equilibrium model is based on the Flory-Huggins theory. It predicts the phase separation behavior of the blend system at different temperatures by calculating the interaction parameters between the support materials and the enthalpy change of mixing. The inputs include the solubility parameters and molecular volume of the support materials, and the outputs are the critical temperature of phase separation and the phase diagram structure.

3. The method for extending the lifespan of biodegradable mulch film materials according to claim 2, characterized in that, The solubility parameter difference is calculated using Hansen solubility parameter theory and is used to evaluate the compatibility between PBAT and PLA. The interfacial tension coefficient is obtained by contact angle measurement and surface energy calculation, reflecting the interfacial bonding strength of the carrier materials.

4. The method for extending the lifespan of biodegradable mulch film materials according to claim 3, characterized in that, The surface functional group density of the carbon black was determined by X-ray photoelectron spectroscopy, the molecular chain length of the dispersant was determined by gel permeation chromatography, and the polar parameters of the carrier material were obtained by dielectric constant measurement.

5. The method for extending the lifespan of biodegradable mulch film materials according to claim 4, characterized in that, The adjustment of carbon black addition and dispersant dosage is based on the carbon black dispersion uniformity coefficient and dispersion stability index. The optical transmittance measurement method quantitatively evaluates the dispersion uniformity of carbon black in the mulch film by measuring the transmittance distribution of the biodegradable mulch film material in the visible light wavelength range of 380nm to 780nm.

6. The method for extending the lifespan of biodegradable mulch film materials according to claim 5, characterized in that, The basic formulation includes a carrier material, carbon black, dispersant, talc, calcium carbonate, antioxidant, lubricant, compatibilizer, coupling agent, and chain extender. The carrier material is a blend of PBAT and PLA.

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