Green ecological leather based on physical-biological synergistic decomposition and intelligent preparation method thereof

Abstract

The invention discloses green ecological leather based on physical-biological synergistic decomposition. The leather is prepared from the following components: polylactic acid, polyhydroxyalkanoate, bamboo fibers, modified natural rubber, vegetable wax, nano silicon, bio-based enzyme and plant-based glycerol. The ecological leather which is tough and has good biodegradability is formed through combination of the adopted formula, the combination of polylactic acid and polyhydroxyalkanoate ensures the degradation rate in the natural environment while providing the mechanical strength, and the formula realizes faster degradation under different environmental conditions by adding PHA and bio-based enzyme, so that the ecological leather is more environment-friendly. Compared with the prior art, the plant fiber-modified natural rubber composite material has the advantages that the degradation performance is more remarkable in a humid environment or a microorganism-rich environment, and the plant fiber and the modified natural rubber are combined, so that the mechanical strength and durability are enhanced, and the environmental protection property and comfort of the material are ensured.

Description

Technical Field

[0001] This invention belongs to the field of green eco-leather preparation based on physical-biological synergistic decomposition, specifically involving a green eco-leather based on physical-biological synergistic decomposition and its intelligent preparation method. Background Technology

[0002] Green eco-leather based on physical-biological co-degradation is a new type of environmentally friendly material designed to replace traditional animal and synthetic leather. Its core concept is to minimize negative environmental impact during the production and degradation processes by combining physical and biotechnological methods. The preparation of this leather material may employ physical methods to improve its properties while using biotechnology to promote degradation. This ensures that the material can be easily biodegraded in nature after use, reducing environmental pollution. This type of leather typically uses renewable and biodegradable raw materials, such as plant fibers, fungi, or other natural polymers, which are degraded during the growth process... Green eco-leather has a relatively small environmental burden and can safely return to nature after use. It employs low-energy, low-chemical-input production processes to reduce resource consumption and environmental pollution, emphasizing water conservation and chemical waste treatment during production. Green eco-leather can be widely used in clothing, footwear, bags, furniture, and many other fields, and is receiving increasing attention, especially from brands that prioritize sustainable development. With consumers' growing environmental awareness and increasing demand for sustainable products, green eco-leather based on physical-biological co-decomposition has a broad market prospect, and many brands are actively exploring and developing this emerging material to meet the new era's environmentally friendly consumption trends.

[0003] However, as a new type of environmentally friendly material, green eco-leather based on physical-biological co-decomposition has many advantages, but it also has some defects and challenges. Although it is designed to be biodegradable, its actual degradation performance may vary depending on temperature, humidity, microbial population and environmental conditions. Under some conditions, eco-leather may take a long time to be completely decomposed, affecting its final environmental protection effect. Summary of the Invention

[0004] The purpose of this invention is to provide a green eco-leather based on physical-biological co-degradation and its preparation method. The formulation combination forms an eco-leather that is both tough and has good biodegradability. The combination of polylactic acid and polyhydroxyalkanoate provides mechanical strength while ensuring the degradation rate in natural environments. By adding PHA and bio-based enzymes, the formulation achieves faster degradation under different environmental conditions, especially in humid or microbial-rich environments, where the degradation performance will be more significant. Combining plant fibers and modified natural rubber not only enhances mechanical strength and durability but also ensures the environmental friendliness and comfort of the material.

[0005] The technical solution adopted by this invention to solve its technical problem is: A green eco-leather based on physical-biological co-decomposition, the leather being composed of the following components: polylactic acid, polyhydroxyalkanoate, bamboo fiber, modified natural rubber, plant wax, nano-silicon, bio-based enzymes, and plant-based glycerin.

[0006] A smart preparation method for green eco-leather based on physical-biological co-decomposition includes the following steps: It uses environmentally friendly materials with patented formulas and undergoes source certification, and utilizes smart sensors to detect the physical and chemical properties of each raw material; A software platform is established, and the proportions and desired properties of each ingredient in the formula are input. The system automatically calculates the required mass of the ingredients and uses a continuous mixer or high-shear mixing equipment to mix the materials according to the instructions of the intelligent control system. Based on the product design mold, and after 3D printing or CNC machining, temperature-controlled injection molding, hot pressing or extrusion molding processes are adopted, combined with an intelligent temperature control system to automatically adjust the temperature and pressure; After molding, the leather surface is coated with plant wax, which is applied evenly using intelligent spraying technology, and then surface strengthening is performed using nano-silicon. Under temperature, humidity, and pH conditions, the dosage of bio-based enzymes is optimized through an intelligent monitoring system to promote the material's post-degradation performance. Throughout the production process, IoT technology is used to monitor the temperature, humidity and other parameters of the mixture in real time, and to test the mechanical properties and biodegradability of the final product.

[0007] As a preferred option, environmentally friendly materials with patented formulas are used, and source certification is conducted. The method of using smart sensors to detect the physical and chemical properties of each raw material is as follows: Standards for the adoption of environmentally friendly materials are established, including the renewability, biodegradability, and relevant certifications of the materials. The qualifications, production processes, environmental policies, and historical reputation of suppliers are evaluated and on-site inspections are conducted. By taking samples from suppliers and conducting additional laboratory tests, the physical and chemical properties of the materials are processed and analyzed, including but not limited to mechanical strength, temperature resistance, and water resistance. Temperature, humidity, pH and spectral sensors are used to monitor environmental conditions and material properties in real time. The sensors are connected to the central control system through Internet of Things (IoT) technology. During the storage and processing of raw materials, intelligent sensors continuously collect data on environmental conditions and material properties, and transmit the data to the central system in real time. Data analysis software is used to process the real-time data and compare it with set standards to form an automated quality monitoring system. Different thresholds are set according to material standards. When the test data exceeds the set range, the system immediately issues an alarm and prompts relevant personnel to conduct an inspection. The system automatically generates a test report and generates information on the status of the raw materials.

[0008] As a preferred option, a software platform is established where the proportions and desired properties of each ingredient in the formula are input. The system automatically calculates the required mass of each ingredient and uses a continuous mixer or high-shear mixing equipment to mix the materials according to the instructions of the intelligent control system. The software platform is designed with functional modules. Users can input the names, proportions, physical and chemical properties of each component into the platform. The system will automatically calculate the actual mass of each component based on the input proportions and the required total amount, and generate a formula report that includes a list of materials, component proportions, and total weight information. The integrated control algorithm uses PID control to monitor and adjust the temperature and speed during the mixing process, and connects to the stirring equipment via an API interface for data transmission and real-time monitoring. Users input the name, proportion, and property requirements of each component into the software platform. The system calculates the required mass of the component in real time based on the input information and displays the calculation results. If the generated calculation results differ significantly from the actual situation, the user can intervene to make corrections. The platform records and continuously updates the corrected data. The user confirms the calculation results and adjusts the formula ratio according to the needs. The software generates a detailed formula report to guide the material preparation. Based on the formula report, the user prepares the required raw materials and conducts quality testing to ensure compliance with standards. In the intelligent control system, the operating parameters of the continuous mixer or high-shear mixing equipment are set, including mixing speed, time, and temperature. The system monitors the current equipment status in real time, starts the mixing equipment, and the intelligent control system automatically controls the operation of the equipment. During the mixing process, temperature, humidity, and viscosity are monitored in real time by sensors. If the real-time feedback data deviates from the set value, the system will automatically adjust. After the mixing is completed, the uniformity and characteristics of the mixture are analyzed by built-in sensors or by sampling, and a test report is generated, recording the parameters and results of the mixing process.

[0009] As a preferred option, the mold is designed according to the product specifications, and then 3D printed or CNC machined. Temperature-controlled injection molding, hot pressing, or extrusion molding processes are used, combined with an intelligent temperature control system to automatically adjust temperature and pressure. Based on the shape, size, and functional requirements of the final leather product, mold design is carried out using CAD software, taking into account the leather's flexibility, thickness, and compatibility with subsequent processes. 3D printing technology is used to manufacture mold prototypes. The printing material is a high-temperature and pressure resistant polymer material. For molds with higher strength and precision, CNC machine tools are used for cutting and machining of metal or hard materials. The mixed environmentally friendly materials are injected into the mold. The temperature and pressure of the injection molding machine are precisely controlled by the intelligent temperature control system. The material is shaped inside the mold by heating the mold and applying pressure. The intelligent temperature control system dynamically adjusts the heating temperature and pressure according to the material characteristics. The mixed materials are continuously extruded through an extruder to form continuous leather sheets. During the extrusion process, an intelligent temperature control system monitors the temperature and extrusion speed of the extruder. The system integrates thermocouples and pressure sensors to collect temperature and pressure data of molds and materials in real time. The data is transmitted to the central control platform through Internet of Things technology. Combined with preset process parameters, the system automatically adjusts the operating status of heating elements or hydraulic systems. Machine learning algorithms are used to optimize temperature control parameters and dynamically adjust them according to the thermal properties of different materials.

[0010] As a preferred option, the amount of plant wax coating, the spraying path, and the nozzle movement speed are precisely controlled by the sensors and control system of the automated spraying equipment to achieve the target coating thickness and uniformity. The spraying environment and equipment parameters are monitored in real time through an Internet of Things sensor network, and the spraying pressure is dynamically adjusted using a PID control algorithm to ensure stable coating quality. By controlling the concentration, application volume, and application process parameters of the nano-silicon dispersion, a uniform reinforcing layer is formed on the leather surface using nano-silicon, and the surface hardness improvement effect is predicted and controlled based on the coverage of nanoparticles.

[0011] Preferably, the temperature, humidity, and pH of the enzyme treatment environment are monitored in real time using IoT sensors; Based on leather quality, target degradation rate, enzyme activity, and environmental parameters, the optimal amount of bio-based enzymes is dynamically calculated using a built-in algorithm model. A PID control algorithm is used to dynamically adjust the enzyme dosing strategy based on the deviation between the real-time monitored degradation process and the target value. The optimal temperature, humidity, and pH range for maintaining enzyme activity is determined through experiments or models, and used as the target for the control system.

[0012] Preferably, the temperature, humidity, and pH parameters of the mixture are collected in real time and expressed in a quantitative manner through an IoT sensor network deployed on the production line. The PID control algorithm is used to automatically adjust the process parameters of the production equipment based on the error between the real-time parameters and the target value. By using machine learning or response surface methodology, historical production data can be analyzed to continuously optimize the best combination of temperature, humidity, and pH. The final product is tested for tensile strength, tear strength, elongation and softness, and a weighted scoring model is used to evaluate its comprehensive mechanical properties. Biodegradation tests were conducted under simulated or real environmental conditions. The degradation rate was calculated by monitoring mass loss. Based on a first-order kinetic model, combined with environmental factors such as temperature, humidity, and pH, the degradation behavior of the material was evaluated and predicted.

[0013] Another technical problem to be solved by the present invention is to provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it realizes a green ecological leather based on physical-biological co-decomposition and its intelligent preparation method as described above.

[0014] Another technical problem to be solved by the present invention is to provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a green eco-leather based on physical-biological co-decomposition and its intelligent preparation method.

[0015] The beneficial effects of this invention are: Utilizing patented, environmentally friendly materials, source certification ensures the sustainability and low environmental impact of raw materials, reducing reliance on animal resources and chemicals in traditional leather production. Optimized bio-based enzyme dosage promotes post-production degradation, meeting biodegradability standards such as ASTM D6400 or EN 13432, thus mitigating long-term environmental pollution risks. Real-time monitoring of parameters such as temperature, humidity, and pH using IoT technology ensures stable production processes, reduces human intervention, and improves consistency and efficiency. A software platform automatically calculates the quality of formula components, precisely controlling material mixing ratios using continuous mixers or high-shear mixing equipment, enhancing production accuracy and repeatability. Mechanical performance testing ensures excellent strength, toughness, and softness, meeting the demands of high-quality leather applications. Plant wax coatings and nano-silicon reinforcement enhance the leather's surface abrasion resistance, water resistance, and tactile feel while maintaining environmental friendliness. Intelligent sensors detect the physical and chemical properties of raw materials. The system ensures stable raw material quality and reduces production risks caused by raw material differences. An intelligent monitoring system dynamically adjusts the dosage of bio-based enzymes and process parameters, optimizing degradation performance while avoiding over-degradation, ensuring a balance between product lifespan and degradation performance. Intelligent formula calculation, mixing, molding, and surface treatment reduce manual operations and labor costs. Continuous production and intelligent control shorten the production cycle, increasing output and resource utilization. Combining physical molding processes and bio-based enzyme degradation technology breaks through the technical bottlenecks of traditional leather production, achieving a balance between environmental protection and performance. Nano-silicon surface strengthening treatment enhances product durability while maintaining biodegradability, demonstrating the technology's forward-thinking nature. Attached Figure Description

[0016] Figure 1 This is a flowchart of the present invention. Detailed Implementation

[0017] The principles and features of the present invention are described below. The examples given are for illustrative purposes only and are not intended to limit the scope of the invention. The invention is described more specifically by way of example in the following paragraphs. The advantages and features of the invention will become clearer from the following description and claims.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items. Example

[0019] The technical solution adopted by this invention to solve its technical problem is: A green eco-leather based on physical-biological co-decomposition, the leather being composed of the following components: polylactic acid, polyhydroxyalkanoate, bamboo fiber, modified natural rubber, plant wax, nano-silicon, bio-based enzymes, and plant-based glycerin.

[0020] Polylactic acid (PLA) and polyhydroxyalkanoates (PHA) are biodegradable bio-based polymers that meet degradation standards such as ASTM D6400 or EN13432, reducing long-term environmental pollution. Bamboo fiber, modified natural rubber, plant waxes, and plant-based glycerin are all derived from renewable resources, reducing reliance on petrochemical raw materials and animal leather, thus lowering the carbon footprint. Bamboo fiber enhances the tensile strength and toughness of leather, while modified natural rubber provides elasticity and softness, giving leather both strength and a comfortable feel, suitable for footwear, apparel, and home furnishings. Plant waxes provide waterproof and stain-resistant surface protection, while nano-silicon further enhances abrasion resistance and anti-aging properties, extending product lifespan. All ingredients are bio-based or natural materials, avoiding harmful chemicals such as chromium salts used in traditional leather tanning, reducing health risks to humans and the environment. Bamboo fiber and vegetable-based glycerin are relatively inexpensive raw materials, and the production technologies for polylactic acid (PLA) and polyhydroxyalkanoates (PHA) are becoming increasingly mature, reducing overall production costs. Green eco-leather meets consumers' demand for environmentally friendly and sustainable products, aligns with global green consumption trends, and enhances brand appeal. PLA provides physical structural stability, bio-based enzymes promote degradation, and nano-silicon enhances surface properties, achieving a balance between performance and environmental protection. PLA and PHA have good thermoplasticity, making them suitable for injection molding, hot pressing, or extrusion molding. Bamboo fiber and modified natural rubber are easy to mix, adapting to intelligent production processes. Component selection supports low-energy production, reducing wastewater and exhaust emissions, and meeting green manufacturing requirements.

[0021] See Figure 1 As shown, a smart preparation method for green eco-leather based on physical-biological co-decomposition includes the following steps: It uses environmentally friendly materials with patented formulas and undergoes source certification, and utilizes smart sensors to detect the physical and chemical properties of each raw material; A software platform is established, and the proportions and desired properties of each ingredient in the formula are input. The system automatically calculates the required mass of the ingredients and uses a continuous mixer or high-shear mixing equipment to mix the materials according to the instructions of the intelligent control system. Based on the product design mold, and after 3D printing or CNC machining, temperature-controlled injection molding, hot pressing or extrusion molding processes are adopted, combined with an intelligent temperature control system to automatically adjust the temperature and pressure; After molding, the leather surface is coated with plant wax, which is applied evenly using intelligent spraying technology, and then surface strengthening is performed using nano-silicon. Under temperature, humidity, and pH conditions, the dosage of bio-based enzymes is optimized through an intelligent monitoring system to promote the material's post-degradation performance. Throughout the production process, IoT technology is used to monitor the temperature, humidity and other parameters of the mixture in real time, and to test the mechanical properties and biodegradability of the final product.

[0022] By inputting the formula ratio and target characteristics into the software platform, the system automatically calculates the required raw material quality, reducing human error and improving formula consistency. A continuous mixer or high-shear mixing equipment, combined with an intelligent control system, precisely controls the mixing uniformity. An intelligent temperature control system automatically adjusts the temperature and pressure of injection molding, hot pressing, or extrusion molding, optimizing production efficiency and ensuring product consistency. Using environmentally friendly materials with patented formulas, and with source certification ensuring raw material traceability and sustainability, reduces dependence on non-renewable resources. Intelligent spraying technology ensures a uniform plant wax coating, improving waterproof and stain-resistant properties. Nano-silicon enhances surface wear resistance and anti-aging properties, extending product lifespan. 3D printing... The printing or CNC machining molds support diverse product designs, meeting the personalized needs of fashion, automotive interiors, furniture, and other fields. Through IoT technology, parameters such as temperature, humidity, and pressure of the mixture and production environment are collected in real time, dynamically adjusting process conditions to reduce production defects. The software platform records and analyzes production data, supporting process optimization and quality traceability, improving production repeatability and transparency. The intelligently prepared green and eco-friendly leather conforms to global environmental protection trends, attracting consumers who value sustainable development and enhancing brand market competitiveness. It integrates cutting-edge technologies such as IoT, smart sensors, 3D printing, and bio-based enzymes, reflecting the innovative combination of intelligent manufacturing and materials science.

[0023] The method involves using environmentally friendly materials with patented formulas, undergoing source certification, and utilizing smart sensors to detect the physical and chemical properties of each raw material. Standards for the adoption of environmentally friendly materials are established, including the renewability, biodegradability, and relevant certifications of the materials. The qualifications, production processes, environmental policies, and historical reputation of suppliers are evaluated and on-site inspections are conducted. By taking samples from suppliers and conducting additional laboratory tests, the physical and chemical properties of the materials are processed and analyzed, including but not limited to mechanical strength, temperature resistance, and water resistance. Temperature, humidity, pH and spectral sensors are used to monitor environmental conditions and material properties in real time. The sensors are connected to the central control system through Internet of Things (IoT) technology. During the storage and processing of raw materials, intelligent sensors continuously collect data on environmental conditions and material properties, and transmit the data to the central system in real time. Data analysis software is used to process the real-time data and compare it with set standards to form an automated quality monitoring system. Different thresholds are set according to material standards. When the test data exceeds the set range, the system immediately issues an alarm and prompts relevant personnel to conduct an inspection. The system automatically generates a test report and generates information on the status of the raw materials.

[0024] By establishing requirements for renewability, biodegradability, and related certifications, we ensure the selection of environmentally friendly materials, guaranteeing their green attributes from the source. Through qualification reviews, production process assessments, environmental policy verification, and historical reputation checks, we select reliable suppliers, reducing supply chain risks and ensuring raw material stability and compliance. Temperature toy technology connects temperature, humidity, pH, and spectral sensors to a central control system, collecting environmental and material data in real time. Data analysis software compares this data with set standards, forming an automated quality monitoring system that reduces manual intervention, improves efficiency, and automatically alarms and generates reports when data exceeds certain limits, prompting inspections and quickly identifying problematic raw materials to reduce production defects. Through source certification and stringent environmental standards, we prioritize renewable and biodegradable materials, reducing reliance on non-renewable resources and lowering our carbon footprint. The Internet of Things and data analysis software enable automated monitoring, reducing manual inspection costs and improving production efficiency. Real-time alarm and report generation mechanisms promptly identify problems, reducing production interruptions and waste losses due to substandard raw materials, thus lowering production costs. Strict environmental material certification and intelligent testing processes align with global sustainable development trends, enhancing the product's competitiveness in the environmental market.

[0025] The software platform is established by inputting the proportions and desired properties of each ingredient in the formula. The system automatically calculates the required mass of each ingredient and uses a continuous mixer or high-shear mixing equipment to mix the materials according to the instructions of the intelligent control system. The software platform is designed with functional modules. Users can input the names, proportions, physical and chemical properties of each component into the platform. The system will automatically calculate the actual mass of each component based on the input proportions and the required total amount, and generate a formula report that includes a list of materials, component proportions, and total weight information. The integrated control algorithm uses PID control to monitor and adjust the temperature and speed during the mixing process, and connects to the stirring equipment via an API interface for data transmission and real-time monitoring. Users input the name, proportion, and property requirements of each component into the software platform. The system calculates the required mass of the component in real time based on the input information and displays the calculation results. If the generated calculation results differ significantly from the actual situation, the user can intervene to make corrections. The platform records and continuously updates the corrected data. The user confirms the calculation results and adjusts the formula ratio according to the needs. The software generates a detailed formula report to guide the material preparation. Based on the formula report, the user prepares the required raw materials and conducts quality testing to ensure compliance with standards. In the intelligent control system, the operating parameters of the continuous mixer or high-shear mixing equipment are set, including mixing speed, time, and temperature. The system monitors the current equipment status in real time, starts the mixing equipment, and the intelligent control system automatically controls the operation of the equipment. During the mixing process, temperature, humidity, and viscosity are monitored in real time by sensors. If the real-time feedback data deviates from the set value, the system will automatically adjust. After the mixing is completed, the uniformity and characteristics of the mixture are analyzed by built-in sensors or by sampling, and a test report is generated, recording the parameters and results of the mixing process.

[0026] The software platform automatically calculates the mass of each component based on the user-input ingredient name, proportion, and characteristics, generating a formula report and reducing human calculation errors. The system records user-corrected data and updates the algorithm, improving the accuracy of subsequent calculations and adapting to different production scenarios. Through PID control algorithms and API interfaces, it monitors and adjusts the parameters of continuous mixers or high-shear mixing equipment in real time to ensure stable mixing processes and reduce manual intervention. Sensors provide real-time feedback on the mixing status; if the data deviates from the set value, the system automatically adjusts the equipment parameters to ensure mixing quality. After mixing, the uniformity and characteristics of the mixture are verified through built-in sensors or sampling analysis, generating a test report to ensure product compliance with standards. Precise formula calculation and real-time adjustment reduce raw material waste and optimize resource utilization. Automated formula generation and equipment control shorten preparation and mixing time, improving production efficiency. Accurate calculation of raw material usage avoids overuse, reducing environmental impact. The software platform supports rapid formula adjustments to adapt to market changes. By recording and analyzing historical data, it optimizes formulas and processes, enhancing product quality and brand competitiveness.

[0027] Based on the product design mold, and after 3D printing or CNC machining, temperature-controlled injection molding, hot pressing, or extrusion molding processes are used, combined with an intelligent temperature control system to automatically adjust the temperature and pressure. Based on the shape, size, and functional requirements of the final leather product, mold design is carried out using CAD software, taking into account the leather's flexibility, thickness, and compatibility with subsequent processes. 3D printing technology is used to manufacture mold prototypes. The printing material is a high-temperature and pressure resistant polymer material. For molds with higher strength and precision, CNC machine tools are used for cutting and machining of metal or hard materials. The mixed environmentally friendly materials are injected into the mold. The temperature and pressure of the injection molding machine are precisely controlled by the intelligent temperature control system. The material is shaped inside the mold by heating the mold and applying pressure. The intelligent temperature control system dynamically adjusts the heating temperature and pressure according to the material characteristics. The mixed materials are continuously extruded through an extruder to form continuous leather sheets. During the extrusion process, an intelligent temperature control system monitors the temperature and extrusion speed of the extruder. The system integrates thermocouples and pressure sensors to collect temperature and pressure data of molds and materials in real time. The data is transmitted to the central control platform through Internet of Things technology. Combined with preset process parameters, the system automatically adjusts the operating status of heating elements or hydraulic systems. Machine learning algorithms are used to optimize temperature control parameters and dynamically adjust them according to the thermal properties of different materials.

[0028] Molds are designed using CAD software based on the shape, size, flexibility, and thickness of the leather product, taking into account material properties and compatibility with subsequent processes to ensure the molds meet complex geometric and functional requirements. 3D printing technology uses high-temperature and pressure-resistant polymer materials to rapidly manufacture mold prototypes, shortening the development cycle and making it suitable for small-batch testing or rapid iteration. An intelligent temperature control system monitors the temperature and pressure of the injection molding machine, hot press, or extruder in real time using thermocouples and pressure sensors, dynamically adjusting heating elements or hydraulic systems to ensure the material is formed within the optimal process window. The extrusion process, monitored by the intelligent temperature control system, generates continuous leather sheets suitable for mass production. This system reduces downtime; it dynamically adjusts temperature and pressure based on the thermal properties of environmentally friendly materials to minimize material degradation or defects; it analyzes historical data using machine learning algorithms to optimize temperature control parameters, improving product quality and process stability; 3D-printed molds reduce initial development costs and are suitable for small-batch or customized production; CNC machining meets high-strength requirements, extends mold life, and reduces long-term costs; the solution is compatible with environmentally friendly materials, reduces material waste and energy consumption through precise temperature control, and supports rapid mold adjustments through CAD design and 3D printing to meet personalized market demands. By recording and analyzing process parameters, it continuously improves production processes and enhances market responsiveness.

[0029] After molding, the leather surface is coated with a plant wax coating using intelligent spraying technology for uniform application, and then surface strengthening is achieved using nano-silicon. Automated spraying equipment is used, and the spraying amount, spraying speed, and spraying path are precisely controlled through sensors and a control system. The coating thickness control formula is as follows: in, This refers to the coating thickness. The volumetric flow rate of the plant wax during the spraying process; The concentration of plant wax; The density of plant wax; This refers to the area to be coated. Uniformity is controlled by the nozzle movement speed and spraying pressure of the spraying equipment, as shown in the formula: in, For coating uniformity; For spraying mass flow rate; This refers to the nozzle movement speed; This refers to the spray width; The environmental and spraying parameters during the spraying process are monitored in real time using IoT sensors, and dynamically adjusted using a PID control algorithm. The formula is as follows: in, This is the adjustment amount for the spraying pressure; This represents the error between the actual coating thickness and the target thickness. , , These are the proportional, integral, and derivative control coefficients; The nano-silicon dispersion is applied to the surface of a plant wax coating by spraying or dip coating. The high specific surface area and chemical stability of nanoparticles strengthen the surface. The formula for calculating the quality of the nano-silicon coating is as follows: in, The quality of the nano-silicon coating; The concentration of the nano-silicon dispersion; The volume of the nano-silicon dispersion for spraying or dipping; The density of the nano-silicon dispersion; Surface hardness is estimated by the coverage of nano-silicon particles, using the following formula: in, To enhance the surface hardness; The original hardness of the substrate; The coverage of nano-silicon particles on the surface; This is the hardness enhancement factor; By controlling the spraying speed and particle concentration, a uniform distribution of nano-silicon on the surface is ensured, as shown in the formula: in, The distribution density of nano-silicon particles; The total number of nano-silicon particles sprayed; The surface area of ​​the leather.

[0030] By employing automated spraying equipment and a precise sensor control system, combined with coating thickness control and uniformity formulas, the plant wax coating can be precisely applied, ensuring consistent and uniform coating thickness and avoiding uneven thickness or missed areas that may occur with traditional manual spraying. This significantly improves the aesthetics and consistency of the leather surface. Real-time monitoring of environmental parameters using IoT sensors, combined with a PID control algorithm, dynamically adjusts spraying pressure and path, ensuring a stable and efficient spraying process, reducing material waste, and improving production efficiency. Applying a nano-silicon dispersion leverages the high specific surface area and chemical stability of nano-silicon particles to significantly enhance the abrasion resistance and durability of the leather surface. Controlling spraying speed and particle concentration ensures uniform distribution of nano-silicon particles on the leather surface, enhancing the stability of surface strengthening effects, avoiding localized performance differences, and improving overall protective performance. Plant wax, as a natural material, is environmentally friendly and sustainable; combined with intelligent spraying technology, it reduces material waste and labor costs. This solution, through precise mathematical models and automation technology, is applicable to various leather types and application scenarios, allowing for flexible parameter adjustments to meet different hardness, thickness, and appearance requirements, demonstrating high adaptability and market competitiveness.

[0031] The method for optimizing the dosage of bio-based enzymes under temperature, humidity, and pH conditions to promote the later-stage degradation performance of materials using an intelligent monitoring system is as follows: IoT sensors are used to monitor temperature, humidity, and pH levels in real time. Combined with a control algorithm, the enzyme dosage is dynamically adjusted to achieve the desired degradation effect. The formula for calculating the enzyme dosage is as follows: in, This refers to the dosage of bio-based enzymes; For the quality of leather materials; The target degradation rate is determined based on product design requirements; This refers to enzyme activity; This is the enzyme efficiency coefficient; This refers to the degradation reaction time; The biodegradation rate is affected by temperature, humidity, and pH, and is described by a modified Arrhenius equation: in, The degradation rate; Forecast factor; It is the activation energy; It is the gas constant; Absolute temperature; Humidity is an influencing factor; pH value is a factor that affects pH. Real-time data is collected through an intelligent monitoring system, and the enzyme dosage is adjusted using a PID control algorithm. The formula is as follows: in, This is an adjustment for the amount of enzyme added; This represents the error between the actual degradation rate and the target degradation rate. , , These are the proportional, integral, and derivative control coefficients; The optimal ranges for temperature, humidity, and pH were determined experimentally or through models, using the following formulas: in, To optimize the objective function; , , The optimal temperature, humidity, and pH value for enzyme activity; , , These are the weighting coefficients.

[0032] By utilizing an enzyme dosage calculation formula and combining it with IoT sensors to monitor temperature, humidity, and pH in real time, the system ensures that the dosage of bio-based enzymes is precisely matched to the quality of leather materials and the target degradation rate, avoiding over- or under-dosing, significantly improving degradation efficiency and reducing enzyme usage costs. A modified Arrhenius equation describes the effects of temperature, humidity, and pH on the degradation rate, and a PID control algorithm is used to adjust the enzyme dosage in real time to adapt to environmental changes, ensuring a stable and efficient degradation process and reducing resource waste. The objective function is optimized by determining the optimal range for temperature, humidity, and pH through experiments or models, ensuring that the enzyme exerts maximum activity under optimal conditions and adapts to different environments. The production environment is improved, enhancing the reliability and consistency of degradation performance. Bio-based enzymes, as green degradation agents, combined with intelligent monitoring and control technology, can efficiently promote the biodegradation of leather materials, reducing environmental pollution from chemical treatments, meeting the requirements of sustainable development, reducing waste disposal difficulties, and improving the eco-friendliness of leather products. The combination of intelligent monitoring systems and automated control algorithms reduces human intervention, improves the automation level of the production process, and lowers operating costs. This solution, through flexible parameter adjustment and real-time monitoring, is applicable to various leather materials and degradation scenarios, and its degradation performance can be customized according to product design requirements, demonstrating high market adaptability and application value.

[0033] Throughout the production process, IoT technology is used to monitor the temperature, humidity, and other parameters of the mixture in real time, and the final product is tested for mechanical and biodegradability properties. The Internet of Things (IoT) technology is used to monitor the temperature, humidity, and pH values ​​of mixtures during the production process in real time. The IoT system collects data through sensors and uses control algorithms to adjust production conditions. The formula is as follows: in, For time The environmental parameter vector at that location; , , For real-time monitoring of temperature, humidity, and pH value; The PID control algorithm is used to adjust the process parameters to approach the target value. The formula is: in, To control the output; The error between the target parameter and the actual parameter; , , These are the proportional, integral, and derivative control coefficients; IoT systems optimize production parameters using machine learning or response surface methodology, as shown in the formula: in, To optimize the objective function; , , For optimal temperature, humidity, and pH; , , These are the weighting coefficients; Mechanical property testing is used to evaluate the strength, toughness, and durability of eco-friendly leather. Common tests include tensile strength, tear strength, and softness. Tensile strength reflects the material's ability to withstand tensile forces, and the calculation formula is: in, Tensile strength; This represents the maximum tensile force. The cross-sectional area of ​​the sample; The formula for calculating elongation is: in, Elongation; This represents the length change at tensile fracture. This is the initial length; Tear strength reflects a material's resistance to tearing, and the formula for calculating it is: in, Tear strength; For tearing force; The thickness of the sample; Softness is measured using a rigidity modulus or a softness tester, and the calculation formula is as follows: in, For softness; It is the stiffness coefficient; The comprehensive mechanical properties are evaluated using a weighted scoring model, and the calculation formula is as follows: in, The overall score is based on mechanical properties. , , , These are the weighting coefficients for each performance metric; Biodegradability testing evaluates the degradation ability of eco-friendly leather in natural environments or under specific conditions. The degradation rate is calculated through mass loss, using the following formula: in, Degradation rate; The initial mass; For time The remaining mass after; The degradation rate is affected by temperature, humidity, and pH, and is described using a first-order kinetic model. in, For material quality; This is the degradation rate constant; The environmental factor function integrates the effects of temperature, humidity, and pH: Forecast factor; It is the activation energy; It is the gas constant; Absolute temperature; , For humidity and pH value; , , These are the parameters for the experimental fitting.

[0034] By utilizing IoT sensors to collect environmental parameter vectors and combining them with PID control algorithms and optimization objective functions, real-time dynamic adjustments to production conditions are achieved. This ensures that temperature, humidity, and pH values ​​are maintained within optimal ranges, improving production process stability and reducing the impact of parameter fluctuations on product quality. Through mechanical performance testing and a comprehensive weighted scoring model, the strength, toughness, durability, and softness of the eco-leather are comprehensively evaluated, ensuring the product meets diverse application needs and enhances market competitiveness. Biodegradability testing uses mass loss calculations and a first-order kinetic model to accurately assess the material's degradation capacity under different environmental conditions, ensuring efficient degradation of the eco-leather in the natural environment, reducing environmental pollution, and meeting sustainable development requirements. IoT technology combined with machine learning or response surface methodology optimizes production parameters, significantly reducing human intervention and improving the automation level of the production process. This solution reduces the use of chemicals and waste generation by precisely controlling production conditions and optimizing degradation performance, enhancing the environmental attributes of eco-leather. Through flexible parameter optimization and comprehensive performance testing, this solution is applicable to the production of different types of eco-leather and various application scenarios.

[0035] This embodiment also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it realizes the green eco-leather based on physical-biological co-decomposition and its intelligent preparation method as described above.

[0036] This embodiment also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements a green eco-leather based on physical-biological co-decomposition and its intelligent preparation method as described above.

[0037] In raw material testing, infrared spectroscopy sensors and ultrasonic sensors are used to detect the density and moisture content of environmentally friendly materials. The test data is processed by support vector machine algorithm to optimize the screening accuracy of raw materials, and the screening pass rate is over 98%. The plant wax coating uses a mixture of palm wax and beeswax in a 3:1 ratio, with a coating thickness controlled at 10-15μm and a spraying temperature set at 60℃. Nano-silicon is uniformly dispersed in the coating after being modified by a silane coupling agent, improving surface wear resistance by up to 30%. The IoT system adopts a mesh network topology, with sensor data collected at a frequency of 1Hz and transmitted to edge computing nodes via the MQTT protocol. Data fusion uses a Kalman filter algorithm to reduce temperature monitoring error to ±0.5℃.

[0038] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0039] Those skilled in the art will understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above.

[0040] The above embodiments of the present invention are not intended to limit the scope of protection of the present invention. The implementation of the present invention is not limited thereto. All other modifications, substitutions or alterations made to the above structure of the present invention based on the above content of the present invention, in accordance with ordinary technical knowledge and common practice in the field, without departing from the basic technical idea of ​​the present invention, shall fall within the scope of protection of the present invention.

Claims

1. A green eco-leather based on physical-biological co-decomposition, characterized in that, The leather is composed of the following components: polylactic acid, polyhydroxyalkanoate, bamboo fiber, modified natural rubber, plant wax, nano-silicon, bio-based enzymes, and plant-based glycerin.

2. A smart preparation method for green eco-leather based on physical-biological co-decomposition, characterized in that, Includes the following steps: It uses environmentally friendly materials with patented formulas and undergoes source certification, and utilizes smart sensors to detect the physical and chemical properties of each raw material; A software platform is established, and the proportions and desired properties of each ingredient in the formula are input. The system automatically calculates the required mass of the ingredients and uses a continuous mixer or high-shear mixing equipment to mix the materials according to the instructions of the intelligent control system. Based on the product design mold, and after 3D printing or CNC machining, temperature-controlled injection molding, hot pressing or extrusion molding processes are adopted, combined with an intelligent temperature control system to automatically adjust the temperature and pressure; After molding, the leather surface is coated with plant wax, which is applied evenly using intelligent spraying technology, and then surface strengthening is performed using nano-silicon. Under temperature, humidity, and pH conditions, the dosage of bio-based enzymes is optimized through an intelligent monitoring system to promote the material's post-degradation performance. Throughout the production process, IoT technology is used to monitor the temperature, humidity and other parameters of the mixture in real time, and to test the mechanical properties and biodegradability of the final product.

3. The intelligent preparation method for green eco-leather based on physical-biological co-decomposition according to claim 2, characterized in that, The method involves using environmentally friendly materials with patented formulas, undergoing source certification, and utilizing smart sensors to detect the physical and chemical properties of each raw material. Standards for the adoption of environmentally friendly materials are established, including the renewability, biodegradability, and relevant certifications of the materials. The qualifications, production processes, environmental policies, and historical reputation of suppliers are evaluated and on-site inspections are conducted. By taking samples from suppliers and conducting additional laboratory tests, the physical and chemical properties of the materials are processed and analyzed, including but not limited to mechanical strength, temperature resistance, and water resistance. Temperature, humidity, pH and spectral sensors are used to monitor environmental conditions and material properties in real time. The sensors are connected to the central control system through Internet of Things (IoT) technology. During the storage and processing of raw materials, intelligent sensors continuously collect data on environmental conditions and material properties, and transmit the data to the central system in real time. Data analysis software is used to process the real-time data and compare it with set standards to form an automated quality monitoring system. Different thresholds are set according to material standards. When the test data exceeds the set range, the system immediately issues an alarm and prompts relevant personnel to conduct an inspection. The system automatically generates a test report and generates information on the status of the raw materials.

4. The intelligent preparation method for green eco-leather based on physical-biological co-decomposition according to claim 3, characterized in that, The software platform is established by inputting the proportions and desired properties of each ingredient in the formula. The system automatically calculates the required mass of each ingredient and uses a continuous mixer or high-shear mixing equipment to mix the materials according to the instructions of the intelligent control system. The software platform is designed with functional modules. Users can input the names, proportions, physical and chemical properties of each component into the platform. The system will automatically calculate the actual mass of each component based on the input proportions and the required total amount, and generate a formula report that includes a list of materials, component proportions, and total weight information. The integrated control algorithm uses PID control to monitor and adjust the temperature and speed during the mixing process, and connects to the stirring equipment via an API interface for data transmission and real-time monitoring. Users input the name, proportion, and property requirements of each component into the software platform. The system calculates the required mass of the component in real time based on the input information and displays the calculation results. If the generated calculation results differ significantly from the actual situation, the user can intervene to make corrections. The platform records and continuously updates the corrected data. The user confirms the calculation results and adjusts the formula ratio according to the needs. The software generates a detailed formula report to guide the material preparation. Based on the formula report, the user prepares the required raw materials and conducts quality testing to ensure compliance with standards. In the intelligent control system, the operating parameters of the continuous mixer or high-shear mixing equipment are set, including mixing speed, time, and temperature. The system monitors the current equipment status in real time, starts the mixing equipment, and the intelligent control system automatically controls the operation of the equipment. During the mixing process, temperature, humidity, and viscosity are monitored in real time by sensors. If the real-time feedback data deviates from the set value, the system will automatically adjust. After the mixing is completed, the uniformity and characteristics of the mixture are analyzed by built-in sensors or by sampling, and a test report is generated, recording the parameters and results of the mixing process.

5. The intelligent preparation method for green eco-leather based on physical-biological co-decomposition according to claim 4, characterized in that, Based on the product design mold, and after 3D printing or CNC machining, temperature-controlled injection molding, hot pressing, or extrusion molding processes are used, combined with an intelligent temperature control system to automatically adjust the temperature and pressure. Based on the shape, size, and functional requirements of the final leather product, mold design is carried out using CAD software, taking into account the leather's flexibility, thickness, and compatibility with subsequent processes. 3D printing technology is used to manufacture mold prototypes. The printing material is a high-temperature and pressure resistant polymer material. For molds with higher strength and precision, CNC machine tools are used for cutting and machining of metal or hard materials. The mixed environmentally friendly materials are injected into the mold. The temperature and pressure of the injection molding machine are precisely controlled by the intelligent temperature control system. The material is shaped inside the mold by heating the mold and applying pressure. The intelligent temperature control system dynamically adjusts the heating temperature and pressure according to the material characteristics. The mixed materials are continuously extruded through an extruder to form continuous leather sheets. During the extrusion process, an intelligent temperature control system monitors the temperature and extrusion speed of the extruder. The system integrates thermocouples and pressure sensors to collect temperature and pressure data of molds and materials in real time. The data is transmitted to the central control platform through Internet of Things technology. Combined with preset process parameters, the system automatically adjusts the operating status of heating elements or hydraulic systems. Machine learning algorithms are used to optimize temperature control parameters and dynamically adjust them according to the thermal properties of different materials.

6. The intelligent preparation method for green eco-leather based on physical-biological co-decomposition according to claim 5, characterized in that, By using sensors and control systems in automated spraying equipment, the amount of plant wax coating applied, the spraying path, and the nozzle movement speed are precisely controlled to achieve the target coating thickness and uniformity. The spraying environment and equipment parameters are monitored in real time through an Internet of Things sensor network, and the spraying pressure is dynamically adjusted using a PID control algorithm to ensure stable coating quality. By controlling the concentration, application volume, and application process parameters of the nano-silicon dispersion, a uniform reinforcing layer is formed on the leather surface using nano-silicon, and the surface hardness improvement effect is predicted and controlled based on the coverage of nanoparticles.

7. The intelligent preparation method for green eco-leather based on physical-biological co-decomposition according to claim 6, characterized in that, The temperature, humidity, and pH of the enzyme treatment environment are monitored in real time using IoT sensors. Based on leather quality, target degradation rate, enzyme activity, and environmental parameters, the optimal amount of bio-based enzymes is dynamically calculated using a built-in algorithm model. A PID control algorithm is used to dynamically adjust the enzyme dosing strategy based on the deviation between the real-time monitored degradation process and the target value. The optimal temperature, humidity, and pH range for maintaining enzyme activity is determined through experiments or models, and used as the target for the control system.

8. The intelligent preparation method for green eco-leather based on physical-biological co-decomposition according to claim 7, characterized in that, Through an IoT sensor network deployed on the production line, the temperature, humidity, and pH parameters of the mixture are collected in real time and expressed in a quantitative manner. The PID control algorithm is used to automatically adjust the process parameters of the production equipment based on the error between the real-time parameters and the target value. By using machine learning or response surface methodology, historical production data can be analyzed to continuously optimize the best combination of temperature, humidity, and pH. The final product is tested for tensile strength, tear strength, elongation and softness, and a weighted scoring model is used to evaluate its comprehensive mechanical properties. Biodegradation tests were conducted under simulated or real environmental conditions. The degradation rate was calculated by monitoring mass loss. Based on a first-order kinetic model, combined with environmental factors such as temperature, humidity, and pH, the degradation behavior of the material was evaluated and predicted.

9. An electronic device, characterized in that, The invention includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements an intelligent preparation method for green eco-leather based on physical-biological co-decomposition as described in any one of claims 2-8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements an intelligent preparation method for green eco-leather based on physical-biological co-decomposition as described in any one of claims 2-8.

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