Preparation method of stretch-resistant antibacterial film material

Abstract

The invention relates to the technical field of preparation of thin film materials, in particular to a preparation method of a tensile antibacterial thin film material, which improves the performance and adaptability of the material, reduces the research and development cost and shortens the research and development time. The method comprises the following steps: acquiring target application scene information of a thin film material; performing feature extraction on the target application scene information, and performing quantitative combination on the extracted features to obtain a target performance feature vector and an application target environment feature set of the thin film material; inputting the application target environment feature set into a preset environment influence performance evaluation model to obtain an environment action coefficient set influencing target performance; based on the environmental action coefficient set, performing application correction on the target performance feature vector to obtain a corrected performance feature vector; and inputting the corrected performance feature vector into a preset thin film material preparation scheme space for contrast matching to obtain an optimal thin film material preparation scheme corresponding to the target application scene information.

Description

Technical Field

[0001] The invention relates to the technical field of film material preparation, and in particular to a method for preparing a stretch-resistant antibacterial film material. Background Art

[0002] With the rapid development of materials science, film materials are increasingly used in food packaging, medical devices, sanitary products and other fields. Among them, tensile and antibacterial film materials have become the preferred materials for many high-end application scenarios due to their excellent mechanical and antibacterial properties.

[0003] The performance of thin film materials in different application environments (such as high temperature, high humidity, acid-base environment, etc.) may vary significantly. Existing methods often ignore the impact of environmental factors on material properties when determining the composition of thin film materials. They only rely on experience or simple performance tests and lack in-depth analysis of the target application scenarios, resulting in performance degradation or failure of the prepared thin film materials in actual applications. Summary of the invention

[0004] In order to solve the above technical problems, the present invention provides a method for preparing a stretch-resistant antibacterial film material, which improves the performance and adaptability of the material and reduces the research and development cost and time.

[0005] In a first aspect, the present invention provides a method for preparing a stretch-resistant antibacterial film material, the method comprising: Obtain target application scenario information of thin film materials; Extracting features from the target application scenario information, and quantifying and combining the extracted features to obtain a target performance feature vector of the thin film material and a target application environment feature set; Inputting the application target environment feature set into a preset environmental impact performance evaluation model to obtain an environmental effect coefficient set that affects target performance; Based on the environmental effect coefficient set, applying correction to the target performance characteristic vector to obtain a corrected performance characteristic vector; Inputting the modified performance characteristic vector into a preset thin film material preparation solution space for comparison and matching, and obtaining an optimal thin film material preparation solution corresponding to the target application scenario information; According to the optimal film material preparation plan, the preparation operation of the stretch-resistant antibacterial film material is performed.

[0006] Furthermore, the target performance feature vector includes a tensile strength target feature, an antibacterial performance target feature, and a transparency target feature; and the application target environment feature set includes a temperature feature, a humidity feature, and an ultraviolet radiation intensity feature.

[0007] Furthermore, the environmental effect coefficient set includes the environmental effect coefficient corresponding to each target performance feature in the target performance feature vector.

[0008] Furthermore, the method for constructing the environmental impact performance assessment model includes: Collect experimental data on the performance of thin film materials under different environmental factors; Select machine learning models to build environmental impact performance assessment models; machine learning models include multivariate linear regression, decision tree, and neural network; Use the collected data to train the model and learn the relationship between environmental factors and performance characteristics; The model was validated by cross-validation method; Adjust and optimize the model based on the validation results; The trained environmental impact performance evaluation model is applied to the actual film material preparation process.

[0009] Furthermore, the correction performance feature vector includes a tensile strength correction feature, an antibacterial performance correction feature and a transparency correction feature.

[0010] Furthermore, the method for obtaining the best thin film material preparation solution corresponding to the target application scenario information includes: Input the corrected performance characteristic vector into the preset thin film material preparation plan space as a basis for comparison and matching; In the preset thin film material preparation plan space, search for a preparation plan that matches the modified performance feature vector based on the feasibility, cost-effectiveness, and production efficiency of the plan; After comparison and matching, the thin film material preparation plan that best matches the target application scenario information will be selected as the best plan.

[0011] Furthermore, the preparation process of the stretch-resistant antibacterial film material includes: Select polymer matrix, additives, antimicrobial agents and auxiliary components based on the best film material preparation plan; Mix the components uniformly according to the predetermined ratio; The mixed material is heated by an extruder to be molten, and the molten material is made into a film; Cool the formed film to keep the required shape and size; Carry out surface treatment on the formed film, and cut and roll the film; After the preparation is completed, the finished film is subjected to a comprehensive quality inspection; Qualified film products are packaged and stored in a clean environment.

[0012] On the other hand, the present application also provides a method system for preparing a stretch-resistant antibacterial film material, the system comprising: An information acquisition module, which acquires target application scenario information of thin film materials; A feature extraction and quantification module extracts features from the target application scenario information, and quantifies and combines the extracted features to obtain a target performance feature vector of the film material and a target application environment feature set; the target performance feature vector includes a tensile strength target feature, an antibacterial performance target feature, and a transparency target feature; the target application environment feature set includes a temperature feature, a humidity feature, and an ultraviolet irradiation intensity feature; An environmental impact performance evaluation module inputs the application target environmental feature set into a preset environmental impact performance evaluation model to obtain an environmental effect coefficient set that affects the target performance; the environmental effect coefficient set includes the environmental effect coefficient corresponding to each target performance feature in the target performance feature vector; A performance characteristic correction module, based on the environmental effect coefficient set, applies correction to the target performance characteristic vector to obtain a corrected performance characteristic vector; the corrected performance characteristic vector includes a tensile strength correction characteristic, an antibacterial performance correction characteristic and a transparency correction characteristic; A preparation scheme matching module, which inputs the modified performance characteristic vector into a preset thin film material preparation scheme space for comparison and matching, and obtains an optimal thin film material preparation scheme corresponding to the target application scenario information; The preparation operation execution module executes the preparation operation of the anti-stretching antibacterial film material according to the optimal film material preparation plan.

[0013] In a third aspect, the present application provides an electronic device, comprising a bus, a transceiver, a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the transceiver, the memory, and the processor are connected via the bus, and the computer program, when executed by the processor, implements the steps of any one of the above methods.

[0014] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps in any one of the above-mentioned methods when executed by a processor.

[0015] Compared with the prior art, the present invention has the following beneficial effects: the method first obtains the target application scenario information of the thin film material, ensuring that the prepared thin film material can be directly designed and optimized for specific application requirements; greatly improving the adaptability and performance of the thin film material in practical applications; By combining the feature extraction and quantification of the target application scenario information, this method not only considers the basic performance characteristics of the thin film material, but also deeply analyzes the impact of the application target environment characteristics on the material performance; so that the prepared thin film material can maintain stable performance in different application environments; By using the preset environmental impact performance evaluation model, the environmental effect coefficient set that affects the target performance can be calculated, and the target performance characteristic vector can be corrected based on these coefficients; ensuring that the prepared film material can meet the performance requirements in the actual application environment and avoiding the problem of performance degradation or failure; The method can quickly find the best preparation scheme corresponding to the target application scenario information by comparing and matching the preset film material preparation scheme space; greatly improve the preparation efficiency of the film material and shorten the preparation cycle; perform the preparation operation based on the best film material preparation scheme, which can greatly improve the accuracy of the preparation operation, thereby ensuring that the prepared film material has excellent mechanical properties and antibacterial properties; In summary, the above method provides a more scientific and efficient method to prepare stretch-resistant antibacterial film materials, while significantly improving the performance and adaptability of the materials and reducing R&D costs and time. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is a flow chart of the present invention; Figure 2 It is a flow chart of the preparation process of the stretch-resistant antibacterial film material; Figure 3 The present invention is a structural diagram of a method for preparing a tensile-resistant antibacterial film material. DETAILED DESCRIPTION

[0017] In the description of this application, those skilled in the art should know that this application can be implemented as a method, an apparatus, an electronic device, and a computer-readable storage medium. Therefore, this application can be specifically implemented in the following forms: complete hardware, complete software (including firmware, resident software, microcode, etc.), a combination of hardware and software. In addition, in some embodiments, this application can also be implemented in the form of a computer program product in one or more computer-readable storage media, and the computer-readable storage medium contains computer program code.

[0018] The above-mentioned computer-readable storage medium may adopt any combination of one or more computer-readable storage media. Computer-readable storage media include: electrical, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or devices, or any combination of the above. More specific examples of computer-readable storage media include: portable computer disks, hard disks, random access memories, read-only memories, erasable programmable read-only memories, flash memories, optical fibers, optical disc read-only memories, optical storage devices, magnetic storage devices, or any combination of the above. In the present application, computer-readable storage media can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device, or device.

[0019] The acquisition, storage, use, and processing of data in the technical solution of this application comply with the relevant provisions of national laws.

[0020] The present application describes the provided methods, devices, and electronic devices through flowcharts and / or block diagrams.

[0021] It should be understood that each box in the flowchart and / or block diagram and the combination of boxes in the flowchart and / or block diagram can be implemented by computer-readable program instructions. These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer or other programmable data processing device to produce a machine, and these computer-readable program instructions are executed by a computer or other programmable data processing device to produce a device that implements the functions / operations specified by the boxes in the flowchart and / or block diagram.

[0022] These computer-readable program instructions may also be stored in a computer-readable storage medium that enables a computer or other programmable data processing device to work in a specific manner. In this way, the instructions stored in the computer-readable storage medium produce an instruction device product including functions / operations specified in the blocks in the flowchart and / or block diagram.

[0023] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device, so that a series of operational steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby enabling the instructions executed on the computer or other programmable data processing apparatus to provide a process for implementing the functions / operations specified in the blocks in the flowchart and / or block diagram.

[0024] The present application is described below in conjunction with the drawings in the present application.

[0025] Embodiment 1: Figure 1 to Figure 2 As shown, a method for preparing a stretch-resistant antibacterial film material of the present invention specifically comprises the following steps: S1. Obtain target application scenario information of thin film materials; First of all, it is necessary to clarify the specific application areas of thin film materials, including: Food packaging: The material is required to have good barrier properties, antibacterial properties, transparency and mechanical strength; Medical devices: Materials are required to have biocompatibility, antibacterial properties, chemical corrosion resistance, and a certain mechanical strength; Hygiene products: materials are required to be soft, antibacterial, absorbent and durable; For each identified application area, further detailed usage conditions and environmental parameters are collected; including: Temperature range: whether the material will be used in high or low temperature environments; Humidity conditions: whether there will be high humidity or humid environment effects; Chemical environment: whether it will be exposed to acid, alkali or other chemicals; Lighting conditions: UV exposure intensity, especially for materials used outdoors; Physical stress: mechanical effects such as stretching, compression, friction, etc. that the material may face; Biological environment: Is there a risk of microbial contamination and what level of antimicrobial protection is required? The collected information will be organized and classified according to application scenarios, environmental conditions, performance requirements and regulatory standards. The information will be evaluated based on its importance and urgency to determine which information has a decisive impact on the design and preparation of thin film materials. As market research deepens and customer needs change, relevant information will be updated and tracked in a timely manner to ensure that the prepared thin film materials always meet market demand.

[0026] In this step, by clarifying the specific application areas, we can accurately understand the special needs of each field; this precise positioning will help to design materials that are more in line with actual needs in the future; collecting detailed usage conditions and environmental parameters allows the design of materials to be optimized based on specific environmental factors; not only does it improve the stability of the material in the expected environment, but it also enhances its durability and reliability; understanding and complying with relevant laws, regulations and technical standards ensures the legality and market access qualifications of the final product, and reduces potential legal risks and market entry barriers; combining market research and customer demand analysis can ensure that product development is always user-centric, responds to changes in market demand in a timely manner, and maintains product competitiveness and market adaptability; the collected information is used according to application scenarios, environmental conditions, performance requirements and legal requirements. Classify and organize regulations and standards, and evaluate their importance and urgency, which provides a solid data foundation for subsequent technological research and development, making the decision-making process more scientific and reasonable; with the development of market trends and the evolution of customer needs, timely update and track relevant information to ensure that the prepared film materials can continue to evolve to meet the latest market needs and technical challenges; through in-depth analysis of target application scenario information, some factors that may lead to failure can be avoided in the design stage, thereby reducing unnecessary experiments and trial and error costs, and improving research and development efficiency; S1 step provides a solid foundation for the preparation of stretch-resistant antibacterial film materials through systematic and refined information collection and analysis, ensuring that the material can be optimized for specific application scenarios from the beginning of the design, so as to show excellent performance and reliability in practical applications.

[0027] S2. Extracting features from the target application scenario information, and quantifying and combining the extracted features to obtain a target performance feature vector and an application target environment feature set of the film material; the target performance feature vector includes a tensile strength target feature, an antibacterial performance target feature, and a transparency target feature; the application target environment feature set includes a temperature feature, a humidity feature, and an ultraviolet irradiation intensity feature; The method for extracting features from the target application scenario information comprises: Tensile strength target feature: According to the requirements for the mechanical strength of film materials in application scenarios, tensile strength is extracted as a key performance feature; Antimicrobial performance target feature: For scenarios that require antimicrobial functions, such as medical devices and sanitary products, antimicrobial performance is extracted as another key feature; Transparency target feature: Transparency is an important feature for application scenarios that need to display internal items or maintain visual clarity. When extracting transparency features, it is necessary to consider the transmittance of the material under different light conditions; Temperature characteristics: Extract temperature characteristics according to the temperature range in the application scenario; high or low temperature environment may affect the mechanical properties and chemical stability of film materials; Humidity characteristics: Humidity is a key factor affecting the hygroscopicity, air permeability and barrier properties of film materials. When extracting humidity characteristics, the humidity variation range in the application scenario needs to be considered; UV radiation intensity characteristics: For applications exposed to sunlight, UV radiation intensity is an environmental factor that cannot be ignored; it affects the light stability and aging rate of film materials; The method of quantitatively combining the extracted features includes: Standard test methods are used to quantitatively evaluate target performance characteristics such as tensile strength, antimicrobial performance, and transparency; a universal material testing machine is used to measure tensile strength, the inhibition zone method or shaking flask method is used to determine antimicrobial performance, and a light transmittance meter is used to measure transparency; Collect temperature, humidity, and UV radiation intensity data in the application scenario through environmental monitoring equipment or historical data, and perform statistical analysis to determine the typical values ​​and variation ranges of these environmental factors; The quantified target performance feature vector is combined with the application target environment feature set to form a comprehensive feature dataset.

[0028] In this step, by extracting the key performance characteristics in specific application scenarios, the actual needs of users and the market can be accurately captured; this helps to ensure that the various performance indicators of the film materials meet or exceed the expected application requirements in the subsequent design process; environmental characteristics such as temperature, humidity, and ultraviolet radiation intensity are extracted and quantified, so that the design of the material can be optimized based on specific environmental factors; and the performance degradation problem caused by environmental changes can be foreseen and solved in advance, thereby enhancing the reliability and durability of the material; standard test methods are used to quantitatively evaluate the target performance characteristics, and environmental monitoring equipment is used to collect and analyze environmental data, providing solid data support for material selection and formulation adjustment; the data-based decision-making process is more objective and reliable, reducing the uncertainty caused by subjective judgment; through systematic feature extraction and The combination of quantification can quickly screen out the key factors that affect material performance, thereby avoiding unnecessary experiments and trial and error processes; it not only speeds up the research and development speed, but also reduces development costs; the quantified target performance feature vector is combined with the application target environment feature set to form a comprehensive feature data set; it ensures that the final material has excellent performance in many aspects such as mechanical properties, antibacterial properties, optical properties, etc., and is suitable for the requirements of high-end application scenarios; with the accumulation of more data and changes in market demand, the feature extraction and quantification methods can be continuously updated and improved to keep the system up to date and always provide the best solution; through meticulous feature extraction and quantification, risk points that may lead to performance failure can be identified and avoided in the design stage, thereby improving the stability of the material in actual use and reducing the cost of subsequent maintenance and replacement.

[0029] S3, inputting the application target environment feature set into a preset environmental impact performance evaluation model to obtain an environmental effect coefficient set affecting the target performance; the environmental effect coefficient set includes the environmental effect coefficient corresponding to each target performance feature in the target performance feature vector; Taking the application target environment feature set as input data; preprocessing the application target environment feature set to ensure its accuracy and consistency so as to facilitate accurate prediction by the model; After inputting the application target environmental feature set into the preset environmental impact performance evaluation model, the model calculates the specific impact coefficient of each environmental factor on the target performance characteristics of the film material based on its internal algorithm and historical data in the database; the impact coefficient reflects the degree of change that may occur in the performance of the film material under different environmental conditions; After the model calculation, a set of environmental action coefficients corresponding to each target performance characteristic is generated, namely, the environmental action coefficient set; each coefficient in the environmental action coefficient set represents the degree of influence of the corresponding environmental factor on the specific performance characteristic; The method for constructing the environmental impact performance assessment model comprises: Collect experimental data on the performance of film materials under different environmental factors; these data should cover different types of film materials, various environmental factors and corresponding performance parameters; Extract key environmental and performance characteristics from the collected data; quantify the extracted characteristics to ensure that they can be input into the model in numerical form; According to the characteristics of the data and the complexity of the problem, a machine learning model is selected to build an environmental impact performance assessment model; machine learning models include multivariate linear regression, decision tree and neural network; Use the collected data to train the model so that it can learn the complex relationships between environmental factors and performance characteristics; The model was validated by cross-validation method to evaluate its prediction performance; Adjust and optimize the model based on the validation results to improve its accuracy and generalization ability; Apply the trained environmental impact performance evaluation model to the actual film material preparation process; input the model according to the environmental characteristics of the target application scenario and predict the corresponding environmental effect coefficient set; With the emergence of new materials, new processes and new application scenarios, new experimental data are continuously collected and the model is updated and optimized to ensure that the model can always accurately reflect the impact of environmental factors on the performance of thin film materials.

[0030] In this step, the preset environmental impact performance evaluation model can accurately transform the application target environmental feature set into the environmental action coefficient set that affects the target performance; the environmental action coefficient set accurately reflects the degree of change that may occur in the performance of the film material under different environmental conditions, and provides a scientific basis for the subsequent preparation of the film material; after understanding the specific impact of environmental factors on the performance of the film material, the preparation plan can be adjusted more specifically to meet the needs of specific application scenarios; not only the preparation efficiency of the film material is improved, but also the performance of the final product is ensured to meet expectations; by accurately predicting the impact of the environment on the performance of the film material, unnecessary repeated experiments and material waste can be avoided; at the same time, the optimized preparation plan may involve less resource consumption and lower costs, thereby improving the overall economic benefits. economic benefits; in the process of constructing the environmental impact performance evaluation model, the accuracy and generalization ability of the model are ensured by collecting a large amount of experimental data, selecting a suitable machine learning model, and performing cross-validation; this means that the model can be applied to more types of thin film materials, more complex environmental factors, and a wider range of application scenarios; with the continuous emergence of new materials, new processes, and new application scenarios, the environmental impact performance evaluation model also needs to be continuously updated and optimized; it helps to promote the continuous development of thin film material preparation technology and provide better and more reliable thin film material solutions for more fields; this step introduces the environmental impact performance evaluation model to achieve accurate prediction and targeted adjustment of the impact of environmental factors on thin film material performance, thereby improving the efficiency and accuracy of thin film material preparation and reducing costs.

[0031] S4. Based on the environmental action coefficient set, applying correction to the target performance feature vector to obtain a corrected performance feature vector; the corrected performance feature vector includes a tensile strength correction feature, an antibacterial performance correction feature, and a transparency correction feature; The target performance feature vectors of the film material have been extracted and quantified based on the target application scenario information, including the tensile strength target feature, the antibacterial performance target feature, and the transparency target feature; For each feature in the target performance feature vector, multiply it by the corresponding environmental effect coefficient to obtain a correction value of the feature under the target application environment conditions; The target performance feature vector is corrected according to the calculated correction value to obtain a tensile strength correction feature, an antibacterial performance correction feature, and a transparency correction feature; The tensile strength correction feature, antibacterial performance correction feature and transparency correction feature that have been corrected and calculated are combined to form a corrected performance feature vector; the corrected performance feature vector reflects the performance characteristics that the film material should have under the environmental conditions of the target application scenario; When making correction calculations, it is necessary to ensure the accuracy and reliability of the environmental effect coefficient; The correction process also needs to consider the interactions and synergies between different environmental factors to avoid over-correction or under-correction.

[0032] In this step, by correcting the environmental effect coefficient of the target performance characteristic vector, the actual performance of the film material in a specific application scenario can be predicted more accurately, making the prediction result closer to the actual application situation; according to the information of the target application scenario, the key performance characteristics of the film material such as tensile strength, antibacterial performance and transparency are modified in a targeted manner to ensure the applicability and performance advantages of the material in a specific environment; it helps material scientists and engineers to better select and optimize materials to meet specific application requirements; by correcting the performance characteristic vector, the performance characteristics that the film material should have under specific environmental conditions can be quickly determined, thereby providing strong support for the design and development of the material; it helps to shorten the material research and development and application cycle and improve R&D efficiency; in the correction process, the accuracy and reliability of the environmental action coefficient are emphasized, and the interaction and synergistic effect between different environmental factors are considered; it is helpful to have a more comprehensive and in-depth understanding of the impact of environmental factors on material properties, so as to formulate a more scientific and reasonable material performance optimization strategy; the implementation of this step not only improves the accuracy and pertinence of thin film material performance prediction, but also promotes the research and development of materials science in related fields through in-depth analysis and quantification of environmental factors, and provides a theoretical basis and technical support for the development and application of new materials; this step corrects the target performance characteristic vector through the environmental action coefficient, which effectively improves the accuracy and pertinence of thin film material performance prediction.

[0033] S5, inputting the modified performance characteristic vector into a preset thin film material preparation solution space for comparison and matching, and obtaining an optimal thin film material preparation solution corresponding to the target application scenario information; The method for obtaining the best thin film material preparation solution corresponding to the target application scenario information comprises: Input the corrected performance characteristic vector into the preset thin film material preparation plan space as a basis for comparison and matching; Searching for a preparation scheme that best matches the modified performance characteristic vector in a preset thin film material preparation scheme space; Involves comparison and evaluation of multiple preparation schemes, including consideration of factors such as feasibility, cost-effectiveness, and production efficiency; During the matching process, we use optimization algorithms, machine learning models and other technical means to improve the accuracy and efficiency of matching; After comparison and matching, the thin film material preparation scheme that best matches the target application scenario information will be selected as the best scheme; The selected solution can meet the revised performance characteristics requirements while also meeting other requirements in the actual application scenario, including cost, production efficiency, environmental protection requirements, etc.; After determining the best solution, further verification and optimization work is required; this includes verifying the feasibility of the solution through experimental testing, and making necessary adjustments and optimizations to the solution based on the test results.

[0034] In this step, by comparing and matching the corrected performance characteristic vector with the preset thin film material preparation solution space, the thin film material preparation solution that best matches the target application scenario information can be accurately selected; accurate matching ensures that the selected solution not only meets the performance requirements, but also fully considers other needs in the actual application scenario; in the matching process, the use of optimization algorithms, machine learning models and other technical means can significantly improve the accuracy and efficiency of matching; and then quickly screen out preparation solutions that meet the requirements, greatly shortening the solution selection time and improving work efficiency; this step not only considers the performance requirements of the thin film material, but also comprehensively considers the feasibility, cost-effectiveness, and production efficiency of the solution. production efficiency and other factors; comprehensive consideration ensures the feasibility and economy of the selected solution in practical application, helps to reduce production costs and improve market competitiveness; after determining the best solution, further verification and optimization work is needed; the verification and optimization process helps to discover problems and deficiencies in the solution, and make necessary adjustments and improvements to it; the continuous improvement mechanism ensures the continuous optimization and improvement of the thin film material preparation solution, and improves the quality and performance of the product; this step helps to improve the quality and performance of the product and reduce production costs through the beneficial effects of accurately matching the best solution, improving matching efficiency, comprehensively considering multiple factors, promoting solution optimization and enhancing adaptability.

[0035] S6. According to the optimal film material preparation scheme, the preparation operation of the anti-stretching antibacterial film material is performed; The preparation process of the stretch-resistant antibacterial film material includes: Select appropriate polymer matrix, additives, antimicrobial agents and necessary auxiliary ingredients based on the best preparation plan; ensure that all materials meet food safety standards or medical device-related regulatory requirements; Using a high shear mixer, the components are uniformly mixed in a predetermined ratio to ensure that the antimicrobial agent and other functional additives can be well dispersed in the polymer matrix; The mixed material is heated to an appropriate temperature through an extruder to make it molten; in this process, parameters such as temperature, pressure and screw speed need to be precisely controlled to avoid material degradation or performance changes; The molten material is made into a film by using techniques such as film blowing, casting or calendering. The thickness uniformity and surface smoothness of the film should be considered during the forming process. The formed film needs to be cooled quickly, and the rapid cooling can be achieved by air cooling or water cooling to keep the film in the required shape and dimensional stability; the cooling rate will affect the crystallinity, and thus affect the physical properties of the film; Improve mechanical properties through heat treatment, increase antibacterial effect and improve adhesion through surface treatment; perform finishing work such as cutting and winding of the film; After the preparation is completed, the finished film is subjected to comprehensive quality testing, including mechanical testing, antimicrobial efficacy evaluation, optical performance inspection, and environmental adaptability verification; Qualified film products are packaged in a clean environment and stored under appropriate conditions to prevent contamination or performance degradation until they are shipped to users.

[0036] In this step, the safety and compliance of the film product are ensured by selecting materials that meet food safety standards or medical device-related regulations based on the best preparation plan; this not only improves the market competitiveness of the product, but also meets the strict requirements of specific industries for material safety; a high-shear mixer is used to evenly mix the components to ensure good dispersion of the antimicrobial agent and other functional additives in the polymer matrix; this helps to improve the antimicrobial properties of the film and the consistency of the overall performance; precise control of parameters such as temperature, pressure, and screw speed during the extrusion process avoids material degradation or performance changes; at the same time, appropriate molding technology is used to ensure the uniformity of the film's thickness and surface smoothness, thereby improving the quality and aesthetics of the product; air cooling or water cooling is used The formed film is quickly cooled to maintain the required shape and dimensional stability; the control of the cooling rate has an important influence on the crystallinity and physical properties of the film, which helps to improve the mechanical properties and durability of the film; the mechanical properties are improved by heat treatment, and the antibacterial effect and adhesion are increased by surface treatment, which further improves the overall performance of the film; the finished film is fully quality tested, including mechanical testing, antibacterial efficacy evaluation, optical performance inspection and environmental adaptability verification, to ensure the quality and reliability of the product; it helps to improve customer trust and satisfaction; qualified film products are packaged in a clean environment and stored under suitable conditions to prevent contamination or performance degradation; and the safety and stability of the product during transportation and use are ensured.

[0037] Embodiment 2: Figure 3 As shown, a method for preparing a stretch-resistant antibacterial film material of the present invention specifically includes the following modules; An information acquisition module, which acquires target application scenario information of thin film materials; A feature extraction and quantification module extracts features from the target application scenario information, and quantifies and combines the extracted features to obtain a target performance feature vector of the film material and a target application environment feature set; the target performance feature vector includes a tensile strength target feature, an antibacterial performance target feature, and a transparency target feature; the target application environment feature set includes a temperature feature, a humidity feature, and an ultraviolet irradiation intensity feature; An environmental impact performance evaluation module inputs the application target environmental feature set into a preset environmental impact performance evaluation model to obtain an environmental effect coefficient set that affects the target performance; the environmental effect coefficient set includes the environmental effect coefficient corresponding to each target performance feature in the target performance feature vector; A performance characteristic correction module, based on the environmental effect coefficient set, applies correction to the target performance characteristic vector to obtain a corrected performance characteristic vector; the corrected performance characteristic vector includes a tensile strength correction characteristic, an antibacterial performance correction characteristic and a transparency correction characteristic; A preparation scheme matching module, which inputs the modified performance characteristic vector into a preset thin film material preparation scheme space for comparison and matching, and obtains an optimal thin film material preparation scheme corresponding to the target application scenario information; The preparation operation execution module executes the preparation operation of the anti-stretching antibacterial film material according to the optimal film material preparation plan.

[0038] By introducing the environmental impact performance evaluation module, the system can consider the impact of factors such as temperature, humidity, and ultraviolet rays in the actual application environment on the performance of film materials, thereby improving the stability and reliability of the materials; The feature extraction and quantification module ensures that the key features extracted from the target application scenario information are accurately quantified into performance feature vectors and environmental feature sets, thereby improving the accuracy of subsequent analysis and matching; The combination of the performance characteristic correction module and the preparation scheme matching module enables the system to adjust the target performance characteristic vector according to the specific environmental action coefficient set and find the best preparation scheme; Traditional methods rely on experience and simple performance tests, which will lead to repeated trials to find the right material formula; this system greatly reduces the number of unnecessary experiments through an intelligent matching process, reducing R&D costs and time; the operation of the entire system is based on data collection, analysis and model prediction, ensuring that all decisions have a solid data foundation, which helps to improve the success rate of new material development; With the accumulation and feedback of more application scenario information, the environmental impact performance assessment model can be continuously updated and improved, further improving the accuracy and applicability of the system; In summary, this system provides a more scientific and efficient method to prepare stretch-resistant antibacterial film materials, while significantly improving the performance and adaptability of the materials and reducing R&D costs and time.

[0039] The various variations and specific embodiments of the method for preparing the stretch-resistant antibacterial film material in the aforementioned embodiment 1 are also applicable to the system for preparing the stretch-resistant antibacterial film material in this embodiment. Through the detailed description of the method for preparing the stretch-resistant antibacterial film material mentioned above, those skilled in the art can clearly know the implementation method of the system for preparing the stretch-resistant antibacterial film material in this embodiment, so for the sake of brevity of the specification, it will not be described in detail here.

[0040] In addition, the present application also provides an electronic device, including a bus, a transceiver, a memory, a processor, and a computer program stored in the memory and executable on the processor. The transceiver, the memory, and the processor are respectively connected via a bus. When the computer program is executed by the processor, each process of the above-mentioned method for controlling output data is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be described here.

[0041] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for preparing a tensile-resistant antibacterial film material, characterized in that: The method comprises: Obtain target application scenario information of thin film materials; Extracting features from the target application scenario information, and quantifying and combining the extracted features to obtain a target performance feature vector of the thin film material and a set of application target environment features; Inputting the application target environment feature set into a preset environmental impact performance evaluation model to obtain an environmental effect coefficient set that affects target performance; Based on the environmental effect coefficient set, applying correction to the target performance characteristic vector to obtain a corrected performance characteristic vector; Inputting the modified performance characteristic vector into a preset thin film material preparation solution space for comparison and matching, and obtaining an optimal thin film material preparation solution corresponding to the target application scenario information; According to the optimal film material preparation scheme, the preparation operation of the stretch-resistant antibacterial film material is performed.

2. The method for preparing the stretch-resistant antibacterial film material according to claim 1, characterized in that: The target performance feature vector includes a tensile strength target feature, an antibacterial performance target feature, and a transparency target feature; The application target environment feature set includes temperature features, humidity features, and ultraviolet radiation intensity features.

3. The method for preparing the stretch-resistant antibacterial film material according to claim 1, characterized in that: The environmental effect coefficient set includes the environmental effect coefficient corresponding to each target performance feature in the target performance feature vector.

4. The method for preparing the stretch-resistant antibacterial film material according to claim 1, characterized in that: The method for constructing the environmental impact performance assessment model comprises: Collect experimental data on the performance of thin film materials under different environmental factors; Select machine learning models to build environmental impact performance assessment models; machine learning models include multivariate linear regression, decision tree, and neural network; Use the collected data to train the model and learn the relationship between environmental factors and performance characteristics; The model was validated by cross-validation method; Adjust and optimize the model based on the validation results; The trained environmental impact performance evaluation model is applied to the actual film material preparation process.

5. The method for preparing the stretch-resistant antibacterial film material according to claim 1, characterized in that: The correction performance feature vector includes a tensile strength correction feature, an antibacterial performance correction feature and a transparency correction feature.

6. The method for preparing the stretch-resistant antibacterial film material according to claim 1, characterized in that: The method for obtaining the best thin film material preparation solution corresponding to the target application scenario information comprises: Input the corrected performance characteristic vector into the preset thin film material preparation plan space as a basis for comparison and matching; In the preset thin film material preparation plan space, search for a preparation plan that matches the modified performance feature vector based on the feasibility, cost-effectiveness, and production efficiency of the plan; After comparison and matching, the thin film material preparation plan that best matches the target application scenario information will be selected as the best plan.

7. The method for preparing the stretch-resistant antibacterial film material according to claim 1, characterized in that: The preparation process of the stretch-resistant antibacterial film material includes: Select polymer matrix, additives, antimicrobial agents and auxiliary components based on the best film material preparation plan; Mix the components uniformly according to the predetermined ratio; The mixed material is heated by an extruder to be molten, and the molten material is made into a film; Cool the formed film to keep the required shape and size; Carry out surface treatment on the formed film, and cut and roll the film; After the preparation is completed, the finished film is subjected to a comprehensive quality inspection; Qualified film products are packaged and stored in a clean environment.

8. A system for preparing a tensile-resistant antibacterial film material, characterized in that: The system comprises: An information acquisition module, which acquires target application scenario information of thin film materials; A feature extraction and quantification module extracts features from the target application scenario information, and quantifies and combines the extracted features to obtain a target performance feature vector of the film material and a target application environment feature set; the target performance feature vector includes a tensile strength target feature, an antibacterial performance target feature, and a transparency target feature; the target application environment feature set includes a temperature feature, a humidity feature, and an ultraviolet irradiation intensity feature; An environmental impact performance evaluation module inputs the application target environmental feature set into a preset environmental impact performance evaluation model to obtain an environmental effect coefficient set that affects the target performance; the environmental effect coefficient set includes the environmental effect coefficient corresponding to each target performance feature in the target performance feature vector; A performance characteristic correction module, based on the environmental effect coefficient set, applies correction to the target performance characteristic vector to obtain a corrected performance characteristic vector; the corrected performance characteristic vector includes a tensile strength correction characteristic, an antibacterial performance correction characteristic and a transparency correction characteristic; A preparation scheme matching module, which inputs the modified performance characteristic vector into a preset thin film material preparation scheme space for comparison and matching, and obtains an optimal thin film material preparation scheme corresponding to the target application scenario information; The preparation operation execution module executes the preparation operation of the anti-stretching antibacterial film material according to the optimal film material preparation plan.

9. A method for preparing a stretch-resistant antibacterial film material. An electronic device comprising a bus, a transceiver, a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the transceiver, the memory, and the processor are connected via the bus, characterized in that: When the computer program is executed by the processor, the steps in the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps in the method according to any one of claims 1 to 7 are implemented.

Images