Method for improving performance of antibacterial nano material in kitchen knife

Abstract

The invention relates to the technical field of material performance analysis, and discloses a method for improving the performance of an antibacterial nano-material in a kitchen knife, which comprises the following steps: detecting environmental resident bacterial strains and bacterial flora density of the kitchen knife in a storage environment, and determining the antibacterial nano-material corresponding to the kitchen knife; performing synthesis treatment on the cutter base material and the antibacterial nano material to obtain a synthetic material, analyzing the chemical stability corresponding to the synthetic material, and analyzing the physical stability corresponding to the synthetic material; evaluating the efficiency attenuation of the synthetic material in the storage environment; calculating the sterilization efficiency gradient of the antibacterial nano material; the optimal antibacterial material in the antibacterial nano materials is screened out, a performance improvement scheme corresponding to the kitchen knife is generated, performance improvement processing on the kitchen knife is executed, and an improvement result is obtained. The invention mainly aims to solve the problem of low performance improvement efficiency of the antibacterial nano material in the kitchen knife.

Description

Technical Field

[0001] The invention relates to a method for improving the performance of antibacterial nano materials in kitchen knives, belonging to the technical field of material performance analysis. Background Art

[0002] Against the backdrop of the continuous development of modern materials science and kitchenware manufacturing, kitchen knives, as key tools in the cooking process, have increasingly stringent performance requirements. As people continue to pay more attention to food safety and hygiene, antibacterial function has become one of the important performance indicators of kitchen knives. In order to effectively improve the comprehensive performance of kitchen knives, especially their antibacterial properties, and ensure their long-term stability and reliability in the complex environment of the kitchen, the application of antibacterial nanomaterials in kitchen knives has received increasing attention.

[0003] The existing application method of antibacterial nanomaterials in kitchen knives is mostly to simply add or coat the antibacterial nanomaterials on the surface of the knife. First, the required antibacterial performance level of the knife is determined, and the corresponding antibacterial nanomaterials, such as silver nanomaterials, zinc oxide nanomaterials, etc., are selected. The antibacterial nanomaterials are attached to the knife substrate through physical mixing or chemical coating processes. During the coating process, the coating thickness, uniformity and other parameters are controlled. For example, when using a spraying process, the pressure and distance of the spray gun are adjusted to ensure the uniform distribution of the antibacterial nanomaterials on the knife surface. The coated knife is then cured to better combine the antibacterial nanomaterials with the knife substrate. However, this traditional method mainly determines the process parameters based on past experience, lacks in-depth analysis of the actual use environment in the kitchen and the interaction between the knife substrate and the antibacterial nanomaterials, and has poor adaptability to various chemical substances, humidity, temperature changes and other factors in different kitchen environments, which leads to limited performance improvement effects of antibacterial nanomaterials in kitchen knives, such as insufficient antibacterial persistence, easily affected chemical stability, and insufficient bonding strength with the knife substrate, which leads to low efficiency in improving the performance of antibacterial nanomaterials in kitchen knives. Summary of the invention

[0004] The present invention provides a method for improving the performance of antibacterial nano materials in kitchen knives, the main purpose of which is to solve the problem of low efficiency in improving the performance of antibacterial nano materials in kitchen knives.

[0005] To achieve the above object, the present invention provides a method for improving the performance of antibacterial nanomaterials in kitchen knives, comprising: Obtaining the kitchen knives to be upgraded and the corresponding knife base materials, detecting the resident bacterial species and bacterial flora density of the kitchen knives in the storage environment, and determining the antibacterial nanomaterials corresponding to the kitchen knives based on the resident bacterial species; Performing a synthesis process on the tool base material and the antibacterial nanomaterial to obtain a synthetic material, analyzing the chemical stability of the synthetic material, and analyzing the physical stability of the synthetic material; Collecting storage environment parameters under the storage environment, querying the adaptation environment parameters corresponding to the synthetic material, and evaluating the performance attenuation of the synthetic material under the storage environment by combining the storage environment parameters and the adaptation environment parameters; In combination with the bacterial flora density and the resident bacterial species in the environment, antibacterial test conditions corresponding to the antibacterial nanomaterial are set; based on the antibacterial test conditions, an antibacterial test experiment on the antibacterial nanomaterial is performed; sterilization record data during the antibacterial test experiment is collected; and based on the sterilization record data, a sterilization efficiency gradient of the antibacterial nanomaterial is calculated; The chemical stability, the physical stability, the efficacy attenuation and the bactericidal efficacy gradient are taken as input data and input into a pre-trained comprehensive performance evaluation model. The comprehensive performance evaluation model is used to screen out the optimal antibacterial material among the antibacterial nanomaterials. Based on the optimal antibacterial material, a performance improvement plan corresponding to the kitchen knife is generated. Based on the performance improvement plan, a performance improvement process for the kitchen knife is executed to obtain an improvement result.

[0006] Optionally, analyzing the chemical stability of the synthetic material includes: Sampling the synthetic material to obtain a synthetic material sample; Performing acid and alkali soaking treatment on the synthetic material sample, and recording chemical structure change data and sample element dissolution data corresponding to the synthetic material sample; Performing data optimization processing on the chemical structure change data and the sample element dissolution data respectively to obtain target structure change data and target element dissolution data; Calculate the chemical stability coefficient corresponding to the synthetic material sample by combining the target structure change data and the target element dissolution data; According to the chemical stability coefficient, the chemical stability corresponding to the synthetic material is analyzed.

[0007] Optionally, the combining the target structure change data and the target element dissolution data to calculate the chemical stability coefficient corresponding to the synthetic material sample includes: Calculating the structural change rate corresponding to the synthetic material sample according to the target structural change data; Calculating the element dissolution rate corresponding to the synthetic material sample according to the target element dissolution data; Combining the structural change rate and the element dissolution rate, the chemical stability coefficient corresponding to the synthetic material sample is calculated by the following formula: ; Among them, A represents the chemical stability coefficient corresponding to the synthetic material sample, represents the rate of structural change, Indicates the element dissolution rate.

[0008] Optionally, analyzing the physical stability of the synthetic material includes: measuring the particle size distribution of the synthetic material to obtain initial particle size distribution data; Calculating the initial average particle size of the synthetic material according to the initial particle size distribution data; Using a preset dynamic light scattering technology to perform scattering processing on the synthetic material to obtain agglomerated particle size distribution data; Calculating the average agglomerated particle size of the synthetic material after scattering according to the agglomerated particle size distribution data; Calculate the material agglomeration index corresponding to the synthetic material by combining the agglomerated average particle size and the initial average particle size; According to the material agglomeration index, the physical stability of the synthetic material is analyzed.

[0009] Optionally, combining the storage environment parameter and the adaptation environment parameter to evaluate the performance decay of the synthetic material in the storage environment includes: Based on the storage environment parameters, the associated environment parameters in the adaptation environment parameters are screened out; Standardizing the associated environment parameter and the stored environment parameter respectively to obtain a first standard environment parameter and a second standard environment parameter; Calculating the environmental deviation of the synthetic material under the storage environment by combining the first standard environmental parameter and the second standard environmental parameter; Determining, according to the environmental deviation, a potential failure risk of the synthetic material in the storage environment; Based on the potential failure risk, the performance degradation of the synthetic material under the storage environment is evaluated.

[0010] Optionally, the combining the first standard environmental parameter and the second standard environmental parameter to calculate the environmental deviation of the synthetic material under the storage environment includes: Identifying an environmental parameter index corresponding to the first standard environmental parameter, and calculating an index importance corresponding to the environmental parameter index according to the first standard environmental parameter; In combination with the indicator importance, the first standard environmental parameter and the second standard environmental parameter, the environmental deviation of the synthetic material in the storage environment is calculated by the following formula: ; Where B represents the environmental deviation of the synthetic material under the storage environment, represents the index importance of the i-th index in the environmental parameter index, Indicates the parameter of the ath indicator in the environmental parameter index in the first standard parameter. It indicates the parameter corresponding to the ath indicator in the environmental parameter index in the second standard environmental parameter, a indicates the serial number of the environmental parameter index, and r indicates the number corresponding to the environmental parameter index. Represents the maximum value function between the first standard parameter and the second standard parameter.

[0011] Optionally, calculating the indicator importance corresponding to the environmental parameter indicator according to the first standard environmental parameter includes: Calculating the parameter covariance of the first standard environmental parameter, and constructing a covariance matrix corresponding to the environmental parameter index according to the parameter covariance; Based on the covariance matrix, determining the indicator eigenvalue corresponding to the environmental parameter indicator; Based on the indicator characteristic value, calculating the indicator contribution rate corresponding to the environmental parameter indicator; According to the indicator contribution rate, the indicator importance corresponding to the environmental parameter indicator is determined.

[0012] Optionally, the calculating the bactericidal efficacy gradient of the antibacterial nanomaterial based on the bactericidal record data comprises: Identifying the recording time point corresponding to the sterilization record data, and determining the initial bacterial count of the antibacterial nanomaterial and the surviving bacterial count corresponding to the recording time point from the sterilization record data; Combining the initial bacterial count and the surviving bacterial count, the material sterilization rate of the antibacterial nanomaterial at each time point is calculated by the following formula: ; in, It represents the sterilization rate of antibacterial nanomaterials at each time point, represents the initial bacterial count, It indicates the number of surviving bacteria at the recording time point b; The bactericidal efficiency gradient of the antibacterial nanomaterial is calculated based on the bactericidal rate of the material and the recorded time point.

[0013] Optionally, the step of calculating the bactericidal efficiency gradient of the antibacterial nanomaterial by combining the material bactericidal rate and the recorded time point comprises: Calculating the average sterilization period of the antibacterial nanomaterial according to the recorded time points; Combined with the average sterilization cycle, the recorded time point and the sterilization rate of the material, the sterilization efficiency gradient of the antibacterial nanomaterial is calculated by the following formula: ; Where M represents the bactericidal efficiency gradient of antibacterial nanomaterials, Indicates the sterilization rate of the material corresponding to the recording time point d, Indicates the dth time point in the recorded time points, represents the average sterilization cycle, d represents the sequence of recorded time points, and q represents the number of recorded time points.

[0014] Optionally, the chemical stability, the physical stability, the efficacy attenuation and the bactericidal efficacy gradient are input as input data to a pre-trained comprehensive performance evaluation model, and the optimal antibacterial material among the antibacterial nanomaterials is screened out using the comprehensive performance evaluation model, including: The weight functions in the comprehensive performance evaluation model are used to calculate the weights corresponding to the chemical stability, the physical stability, the efficacy decay and the bactericidal efficacy gradient, respectively, to obtain a weight collection; Using the scoring function in the comprehensive performance evaluation model, the chemical stability, the physical stability, the efficacy decay and the bactericidal efficacy gradient are scored respectively to obtain a score collection; Combining the weight collection and the score collection, and using the vector fusion layer in the comprehensive performance evaluation model to construct a comprehensive feature vector of the chemical stability, the physical stability, the efficacy decay and the bactericidal efficacy gradient; Based on the comprehensive feature vector, the optimal antibacterial material among the antibacterial nanomaterials is screened out.

[0015] A system for improving the performance of antimicrobial nanomaterials in kitchen knives, the system comprising: A material determination module is used to obtain the kitchen knives to be upgraded and their corresponding knife base materials, detect the resident bacterial species and bacterial flora density of the kitchen knives in the storage environment, and determine the antibacterial nanomaterials corresponding to the kitchen knives based on the resident bacterial species; A stability analysis module, used for synthesizing the tool base material and the antibacterial nanomaterial to obtain a synthetic material, analyzing the chemical stability of the synthetic material, and analyzing the physical stability of the synthetic material; An efficiency decay evaluation module, used for collecting storage environment parameters under the storage environment, querying the adaptation environment parameters corresponding to the synthetic material, and evaluating the efficiency decay of the synthetic material under the storage environment by combining the storage environment parameters and the adaptation environment parameters; a bactericidal efficacy gradient calculation module, for setting the antibacterial test conditions corresponding to the antibacterial nanomaterial in combination with the bacterial flora density and the resident bacterial species in the environment, performing an antibacterial test experiment on the antibacterial nanomaterial based on the antibacterial test conditions, collecting bactericidal record data during the antibacterial test experiment, and calculating the bactericidal efficacy gradient of the antibacterial nanomaterial based on the bactericidal record data; The performance improvement processing module is used to input the chemical stability, the physical stability, the efficacy attenuation and the bactericidal efficacy gradient as input data into a pre-trained comprehensive performance evaluation model, use the comprehensive performance evaluation model to screen out the optimal antibacterial material among the antibacterial nanomaterials, generate a performance improvement plan corresponding to the kitchen knife based on the optimal antibacterial material, and perform performance improvement processing on the kitchen knife based on the performance improvement plan to obtain an improvement result.

[0016] Compared with the problems described in the background technology, the present invention can obtain the common bacteria types and bacteria quantity statistics in the storage environment by detecting the resident bacteria species and bacterial flora density of the kitchen knife in the storage environment, thereby facilitating the subsequent determination of the antibacterial nanomaterial corresponding to the kitchen knife and the setting of the antibacterial test conditions corresponding to the antibacterial nanomaterial. The present invention can synthesize the knife base material and the antibacterial nanomaterial together by synthesizing the two materials, which is convenient for subsequent analysis and processing. By analyzing the chemical stability corresponding to the synthetic material, the tolerance of the synthetic material can be understood, and the accuracy of subsequent screening of the optimal antibacterial material can be improved. The present invention combines the storage environment parameters and the suitable According to the environmental parameters, the performance attenuation of the synthetic material under the storage environment is evaluated, and the degree of material performance degradation of the synthetic material under the storage environment can be understood, which lays an important foundation for the subsequent screening and processing of the optimal antibacterial material. The present invention performs an antibacterial test experiment on the antibacterial nanomaterial based on the antibacterial test conditions, so as to collect the evaluation index information during the antibacterial test experiment, which lays an important foundation for the subsequent calculation of the bactericidal efficiency gradient of the antibacterial nanomaterial. The present invention uses the comprehensive performance evaluation model to screen out the optimal antibacterial material in the antibacterial nanomaterial, which can accurately locate the material with high antibacterial properties, thereby improving the performance improvement efficiency of the subsequent antibacterial nanomaterial in kitchen knives. Therefore, the performance improvement method of antibacterial nanomaterials in kitchen knives proposed by the present invention improves the performance improvement efficiency of antibacterial nanomaterials in kitchen knives. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A schematic flow chart of a method for improving the performance of antibacterial nanomaterials in kitchen knives provided by an embodiment of the present invention; Figure 2 A functional module diagram of a system for improving the performance of antibacterial nanomaterials in kitchen knives provided in one embodiment of the present invention.

[0018] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings in conjunction with the embodiments. DETAILED DESCRIPTION

[0019] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0020] The embodiment of the present application provides a method for improving the performance of antibacterial nanomaterials in kitchen knives. The execution subject of the method for improving the performance of antibacterial nanomaterials in kitchen knives includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the present application. In other words, the method for improving the performance of antibacterial nanomaterials in kitchen knives can be executed by software or hardware installed in a terminal device or a server device. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc.

[0021] Embodiment 1: Reference Figure 1 FIG. 2 is a flow chart of a method for improving the performance of antibacterial nanomaterials in kitchen knives according to an embodiment of the present invention. In this embodiment, the method for improving the performance of antibacterial nanomaterials in kitchen knives includes: S1. Obtain kitchen knives to be upgraded and their corresponding knife base materials, detect the resident bacterial species and bacterial flora density of the kitchen knives in the storage environment, and determine the antibacterial nanomaterials corresponding to the kitchen knives based on the resident bacterial species.

[0022] The present invention can obtain common bacteria types and bacteria counts in the storage environment by detecting the environmental resident bacteria species and bacterial flora density of the kitchen knife in the storage environment, thereby facilitating the subsequent determination of the antibacterial nanomaterial corresponding to the kitchen knife and the setting of the antibacterial test conditions corresponding to the antibacterial nanomaterial. It should be explained that the kitchen knife is a tool used for cutting and processing food in a cooking scene, the knife base material is the basic material constituting the main structure of the kitchen knife, the environmental resident bacteria species are specific bacteria species that often exist and relatively stably inhabit and reproduce in the storage environment of the kitchen knife, the bacterial flora density is the individual number distribution of the environmental resident bacteria species per unit volume or area, and the antibacterial nanomaterial is a functional nanoscale material that can inhibit or kill the environmental resident bacteria species to ensure the hygiene and safety of the kitchen knife. Furthermore, the detection of the environmental resident bacteria species and bacterial flora density of the kitchen knife in the storage environment can be achieved by genetic detection technology, and the antibacterial nanomaterial corresponding to the kitchen knife can be determined by querying the bactericidal material corresponding to the environmental resident bacteria species from the Internet.

[0023] S2. Performing a synthesis process on the tool base material and the antibacterial nanomaterial to obtain a synthetic material, analyzing the chemical stability of the synthetic material, measuring the material particle size distribution of the synthetic material, and analyzing the physical stability of the synthetic material based on the material particle size distribution.

[0024] The present invention can synthesize the tool base material and the antibacterial nanomaterial together by performing a synthesis treatment on the two materials, which is convenient for subsequent analysis and processing. By analyzing the chemical stability corresponding to the synthetic material, the tolerance of the synthetic material can be understood, and the accuracy of subsequent screening of the optimal antibacterial material can be improved. It should be explained that the synthetic material is the material after the tool base material and the antibacterial nanomaterial are processed and synthesized together, and the chemical stability is the stability of the chemical performance corresponding to the synthetic material. Furthermore, the synthesis treatment of the tool base material and the antibacterial nanomaterial can be achieved by chemical synthesis.

[0025] In detail, the analysis of the chemical stability of the synthetic material includes: Sampling the synthetic material to obtain a synthetic material sample; Performing acid and alkali soaking treatment on the synthetic material sample, and recording chemical structure change data and sample element dissolution data corresponding to the synthetic material sample; Performing data optimization processing on the chemical structure change data and the sample element dissolution data respectively to obtain target structure change data and target element dissolution data; Calculate the chemical stability coefficient corresponding to the synthetic material sample by combining the target structure change data and the target element dissolution data; According to the chemical stability coefficient, the chemical stability corresponding to the synthetic material is analyzed.

[0026] It should be explained that the synthetic material sample is part of the material selected or prepared from the synthetic material for detection and analysis, the chemical structure change data and the sample element dissolution data are respectively data related to the chemical structure change caused by the acid-base environment during the acid-base immersion treatment of the synthetic material sample and data related to the specific quantity of elements dissolved into the immersion solution, the target structure change data and the target element dissolution data are respectively data obtained after processing the anomalies, errors and other data in the chemical structure change data and the sample element dissolution data, and the chemical stability coefficient represents the quantitative value of the stability corresponding to the synthetic material sample.

[0027] Furthermore, the synthetic material can be sampled by a cutting tool to obtain a synthetic material sample; the synthetic material sample can be subjected to acid-base immersion treatment by a soaking device equipped with precise pH and temperature control; the chemical structure change data and sample element dissolution data corresponding to the synthetic material sample can be recorded by a high-precision spectrometer and an advanced element detection instrument; the chemical structure change data and the sample element dissolution data can be optimized by a data fitting algorithm to obtain target structure change data and target element dissolution data; the chemical stability corresponding to the synthetic material can be analyzed according to the value of the chemical stability coefficient, such as the higher the chemical stability coefficient, the higher the chemical stability.

[0028] Further, as an optional embodiment of the present invention, the step of combining the target structure change data and the target element dissolution data to calculate the chemical stability coefficient corresponding to the synthetic material sample includes: Calculating the structural change rate corresponding to the synthetic material sample according to the target structural change data; Calculating the element dissolution rate corresponding to the synthetic material sample according to the target element dissolution data; Combining the structural change rate and the element dissolution rate, the chemical stability coefficient corresponding to the synthetic material sample is calculated by the following formula: ; Among them, A represents the chemical stability coefficient corresponding to the synthetic material sample, represents the rate of structural change, Indicates the element dissolution rate.

[0029] Among them, the structural change rate indicates the degree of change of the chemical structure corresponding to the synthetic material sample after acid-base immersion and other treatments (such as the breaking of chemical bonds or the proportion of new bonds formed, etc.), and the element dissolution rate indicates the percentage of the mass of a certain element corresponding to the synthetic material sample dissolved from the inside of the material into the immersion solution during the immersion process, accounting for the original mass of the element in the material. Furthermore, based on the parameters after the chemical structure change in the target structural change data and the original chemical structure parameters, a comparative analysis is performed, and according to a pre-set structural change measurement standard, such as using relevant formulas such as the chemical bond change ratio and the degree of crystal phase structure change, the structural change rate corresponding to the synthetic material sample can be calculated; based on the ratio calculation of the mass or amount of substance of the dissolved element recorded in the target element dissolution data and the original mass or amount of substance of the element in the sample, the element dissolution rate corresponding to the synthetic material sample can be calculated.

[0030] By analyzing the physical stability corresponding to the synthetic material, the present invention can understand the physical stability of the synthetic material, laying a foundation for improving the subsequent screening of the optimal antibacterial material. It should be explained that the physical stability is a description of the physical stability of the synthetic material.

[0031] In detail, the analysis of the physical stability of the synthetic material includes: measuring the particle size distribution of the synthetic material to obtain initial particle size distribution data; Calculating the initial average particle size of the synthetic material according to the initial particle size distribution data; Using a preset dynamic light scattering technology to perform scattering processing on the synthetic material to obtain agglomerated particle size distribution data; Calculating the average agglomerated particle size of the synthetic material after scattering according to the agglomerated particle size distribution data; Calculate the material agglomeration index corresponding to the synthetic material by combining the agglomerated average particle size and the initial average particle size; According to the material agglomeration index, the physical stability of the synthetic material is analyzed.

[0032] Among them, the initial particle size distribution data is the distribution of particle size when the synthetic material has not undergone changes such as agglomeration; the initial average particle size is the initial average value of all particle sizes corresponding to the synthetic material; the preset dynamic light scattering technology is a pre-set technical method that uses light scattering phenomenon and Brownian motion of particles to measure particle size and its distribution; the agglomerated particle size distribution data is the new particle size distribution caused by particle agglomeration after the synthetic material is scattering treated; the agglomerated average particle size is the average particle size of the synthetic material in the agglomerated state after scattering; the material agglomeration index is a numerical value corresponding to the synthetic material that measures the degree of particle agglomeration, which is used to evaluate physical stability.

[0033] Furthermore, the particle size distribution of the synthetic material can be measured by a laser particle size analyzer to obtain initial particle size distribution data; based on the initial particle size distribution data, the initial average particle size corresponding to the synthetic material is calculated using a weighted average method according to each particle size range and the corresponding proportion; the calculation principle of the agglomeration average particle size is the same as that of the initial average particle size, which will not be elaborated here; the ratio between the agglomeration average particle size and the initial average particle size is calculated to obtain the material agglomeration index corresponding to the synthetic material; based on the value of the material agglomeration index, the physical stability corresponding to the synthetic material is analyzed, and the larger the value of the material agglomeration index, the better the physical stability.

[0034] S3. Collect storage environment parameters under the storage environment, query the adaptation environment parameters corresponding to the synthetic material, and evaluate the performance attenuation of the synthetic material under the storage environment by combining the storage environment parameters and the adaptation environment parameters.

[0035] The present invention evaluates the performance decay of the synthetic material under the storage environment by combining the storage environment parameters and the adaptation environment parameters, so as to understand the degree of material performance degradation of the synthetic material under the storage environment, and lays an important basis for the subsequent screening and processing of the optimal antibacterial material. It should be explained that the storage environment parameters are data related to various physical and chemical factors under the storage environment, such as temperature, humidity, pH, light intensity, etc.; the adaptation environment parameters are the range settings of the ideal environmental factors corresponding to the synthetic material that can maintain good performance and optimal stability, and the performance decay is a description of the performance degradation of the synthetic material under the storage environment over time and under the influence of environmental factors; further, the collection of storage environment parameters under the storage environment can be achieved through sensors, such as temperature sensors, humidity sensors, and light intensity sensors, and the adaptation environment parameters corresponding to the synthetic material can be obtained by querying the official website of the corresponding material.

[0036] In detail, the combining the storage environment parameter and the adaptation environment parameter to evaluate the performance attenuation of the synthetic material in the storage environment includes: Based on the storage environment parameters, the associated environment parameters in the adaptation environment parameters are screened out; Standardizing the associated environment parameter and the stored environment parameter respectively to obtain a first standard environment parameter and a second standard environment parameter; Calculating the environmental deviation of the synthetic material under the storage environment by combining the first standard environmental parameter and the second standard environmental parameter; Determining, according to the environmental deviation, a potential failure risk of the synthetic material in the storage environment; Based on the potential failure risk, the performance degradation of the synthetic material under the storage environment is evaluated.

[0037] It should be explained that the associated environmental parameters are parameters in the adapted environmental parameters that correspond to the storage environmental parameters, and the first standard environmental parameters and the second standard environmental parameters are respectively data forms of unified specifications and convenient for comparative analysis formed after the associated environmental parameters and the storage environmental parameters are standardized; the environmental deviation degree indicates the degree of deviation of the synthetic material from the adapted environment in various aspects under the storage environment, and is used to quantify the differences; the potential failure risk is the possibility that the synthetic material may lose its original efficacy due to the reduction of antibacterial performance and structural changes in the storage environment due to the inconsistency between the environmental conditions and the adapted environment.

[0038] Furthermore, based on the storage environment parameters, the associated environment parameters in the adaptation environment parameters can be filtered out through a filtering function, and the filtering function is compiled by a scripting language, such as JS scripting language; the associated environment parameters and the storage environment parameters can be standardized respectively by a Z-score standardization method to obtain a first standard environment parameter and a second standard environment parameter; the environmental deviation and the failure risk level are mapped, and the potential failure risk of the synthetic material under the storage environment is determined according to the mapping result and the specific value of the environmental deviation. For example, the deviation of 0-0.3 is set as low risk, 0.3-0.6 as medium risk, and above 0.6 as high risk, and then the calculated environmental deviation is compared with these set intervals to determine the potential failure risk level of the synthetic material under the storage environment; according to the potential failure risk, the performance attenuation of the synthetic material under the storage environment is evaluated, and the performance attenuation data of materials with similar potential failure risks in past records are compared, and this is used as a reference to evaluate the performance attenuation of the synthetic material under the storage environment.

[0039] Further, as an optional embodiment of the present invention, the combining the first standard environmental parameter and the second standard environmental parameter to calculate the environmental deviation of the synthetic material under the storage environment includes: Identifying an environmental parameter index corresponding to the first standard environmental parameter, and calculating an index importance corresponding to the environmental parameter index according to the first standard environmental parameter; In combination with the indicator importance, the first standard environmental parameter and the second standard environmental parameter, the environmental deviation of the synthetic material in the storage environment is calculated by the following formula: ; Where B represents the environmental deviation of the synthetic material under the storage environment, represents the index importance of the i-th index in the environmental parameter index, Indicates the parameter of the ath indicator in the environmental parameter index in the first standard parameter. It indicates the parameter corresponding to the ath indicator in the environmental parameter index in the second standard environmental parameter, a indicates the serial number of the environmental parameter index, and r indicates the number corresponding to the environmental parameter index. Represents the maximum value function between the first standard parameter and the second standard parameter.

[0040] Among them, the environmental parameter index is the various specific factors (such as temperature, humidity, etc.) corresponding to the first standard environmental parameter for measuring the storage environment and the adaptation environment; the indicator importance represents the relative importance of each environmental parameter index in the process of evaluating the deviation of the synthetic material storage environment corresponding to the environmental parameter index. Furthermore, the identification of the environmental parameter index corresponding to the first standard environmental parameter can be achieved through OCR recognition technology.

[0041] Optionally, as an optional embodiment of the present invention, calculating the indicator importance corresponding to the environmental parameter indicator according to the first standard environmental parameter includes: Calculating the parameter covariance of the first standard environmental parameter, and constructing a covariance matrix corresponding to the environmental parameter index according to the parameter covariance; Based on the covariance matrix, determining the indicator eigenvalue corresponding to the environmental parameter indicator; Based on the indicator characteristic value, calculating the indicator contribution rate corresponding to the environmental parameter indicator; According to the indicator contribution rate, the indicator importance corresponding to the environmental parameter indicator is determined.

[0042] It should be explained that the parameter covariance is the degree of coordination of changes between different environmental parameter indicators in the first standard environmental parameters; the covariance matrix is ​​the matrix corresponding to the environmental parameter indicators containing all covariance values ​​between two indicators; the indicator eigenvalue is the numerical value corresponding to the environmental parameter indicator used to describe the size of the principal component variance determined by the covariance matrix; the indicator contribution rate represents the contribution ratio of the indicator corresponding to the environmental parameter indicator to the overall variance.

[0043] Furthermore, the parameter covariance of the first standard environmental parameter can be calculated by the covariance calculation formula, and the covariance matrix corresponding to the environmental parameter index can be constructed by a matrix function, such as a zero matrix function; the covariance matrix is ​​subjected to eigenvalue decomposition to obtain the indicator eigenvalue corresponding to the environmental parameter index; the ratio of the indicator eigenvalue corresponding to the environmental parameter index to the sum of all eigenvalues ​​is calculated to obtain the indicator contribution rate corresponding to the environmental parameter index; after normalizing the indicator contribution rate, the indicator importance corresponding to the environmental parameter index is obtained.

[0044] S4. In combination with the bacterial flora density and the resident bacterial species in the environment, antibacterial test conditions corresponding to the antibacterial nanomaterial are set; based on the antibacterial test conditions, an antibacterial test experiment on the antibacterial nanomaterial is performed; sterilization record data during the antibacterial test experiment is collected; and based on the sterilization record data, a sterilization efficiency gradient of the antibacterial nanomaterial is calculated.

[0045] The present invention performs an antibacterial test experiment on the antibacterial nanomaterial based on the antibacterial test conditions, so as to collect the evaluation index information during the antibacterial test experiment, and lays an important basis for the subsequent calculation of the bactericidal efficiency gradient of the antibacterial nanomaterial. It should be explained that the antibacterial test conditions are a general term for the specific conditions such as bacterial species, bacterial population density, test environment, test duration, etc. set for the antibacterial nanomaterial when detecting its antibacterial ability; the sterilization record data are the specific content of the antibacterial nanomaterial in the sterilization process. Furthermore, in combination with the bacterial population density and the resident bacterial species in the environment, the antibacterial nanomaterial is set to The antibacterial test conditions are as follows: the initial concentration and action time of the antibacterial nanomaterials are determined according to the density of the bacterial population. If the density of the bacterial population is large, the concentration of the material is appropriately increased and the action time is prolonged. Secondly, for the resident bacterial species in the environment, the culture medium and culture environment conditions suitable for the growth and reproduction of the species are selected, such as temperature, humidity, pH, etc., so as to construct a test condition system that can accurately reflect the antibacterial effect of the antibacterial nanomaterials on specific bacteria in the actual environment; the antibacterial test experiment of the antibacterial nanomaterials can be performed through corresponding experimental equipment, such as a sterile operating table; the collection of sterilization record data during the antibacterial test experiment can be achieved through information collection instruments, such as optical detection instruments.

[0046] In detail, the step of calculating the bactericidal efficacy gradient of the antibacterial nanomaterial based on the bactericidal record data includes: Identifying the recording time point corresponding to the sterilization record data, and determining the initial bacterial count of the antibacterial nanomaterial and the surviving bacterial count corresponding to the recording time point from the sterilization record data; Combining the initial bacterial count and the surviving bacterial count, the material sterilization rate of the antibacterial nanomaterial at each time point is calculated by the following formula: ; in, It represents the sterilization rate of antibacterial nanomaterials at each time point, represents the initial bacterial count, It indicates the number of surviving bacteria at the recording time point b; The bactericidal efficiency gradient of the antibacterial nanomaterial is calculated based on the bactericidal rate of the material and the recorded time point.

[0047] It should be explained that the initial number of bacteria is the total number of bacteria measured at the beginning of the antibacterial nanomaterial sterilization test experiment; the number of surviving bacteria is the number of surviving bacteria detected at each recorded time point after the action of the antibacterial nanomaterial; the material sterilization rate represents the proportion of bacteria that can be killed by the antibacterial nanomaterial at each time point, that is, an indicator reflecting the degree of its effect on killing bacteria at the corresponding moment. Furthermore, the recording time point corresponding to the sterilization record data can be identified by an identification tool, and the identification tool is compiled by a programming language.

[0048] Further, as an optional embodiment of the present invention, the bactericidal efficiency gradient of the antibacterial nanomaterial is calculated by combining the material sterilization rate and the recorded time point, including: Calculating the average sterilization period of the antibacterial nanomaterial according to the recorded time points; Combined with the average sterilization cycle, the recorded time point and the sterilization rate of the material, the sterilization efficiency gradient of the antibacterial nanomaterial is calculated by the following formula: ; Where M represents the bactericidal efficiency gradient of antibacterial nanomaterials, Indicates the sterilization rate of the material corresponding to the recording time point d, Indicates the dth time point in the recorded time points, represents the average sterilization cycle, d represents the sequence of recorded time points, and q represents the number of recorded time points.

[0049] Furthermore, the duration period of each time point in the recorded time points is counted, the duration periods are added up and divided by the number of time points to obtain the average sterilization period of the antibacterial nanomaterial.

[0050] S5. The chemical stability, the physical stability, the efficacy attenuation and the bactericidal efficacy gradient are used as input data and input into a pre-trained comprehensive performance evaluation model. The optimal antibacterial material among the antibacterial nanomaterials is screened out using the comprehensive performance evaluation model. Based on the optimal antibacterial material, a performance improvement plan corresponding to the kitchen knife is generated. Based on the performance improvement plan, a performance improvement process is performed on the kitchen knife to obtain an improvement result.

[0051] The present invention uses the comprehensive performance evaluation model to screen out the optimal antibacterial material among the antibacterial nanomaterials, and can accurately locate the materials with high antibacterial properties, thereby improving the performance improvement efficiency of the subsequent antibacterial nanomaterials in kitchen knives. It should be explained that the comprehensive performance evaluation model is a quantitative analysis model for comprehensively and systematically evaluating the various aspects of the performance of antibacterial nanomaterials; the optimal antibacterial material is the material among the antibacterial nanomaterials that performs most prominently in all aspects and best meets the application requirements under the measurement of the comprehensive performance evaluation model; the performance improvement plan is a specific plan and measure formulated to address the deficiencies of kitchen knives in antibacterial properties. Furthermore, based on the optimal antibacterial material, the steps of generating the corresponding performance improvement plan for the kitchen knives are: applying the optimal antibacterial material to the surface of the kitchen knife in the form of a coating, making it evenly adhered through a special process, and in the edge processing link of the knife, optimizing the heat treatment process in combination with the characteristics of the optimal antibacterial material, improving the edge hardness and wear resistance while ensuring that the antibacterial performance is not affected.

[0052] In detail, the chemical stability, the physical stability, the efficacy attenuation and the bactericidal efficacy gradient are input as input data to a pre-trained comprehensive performance evaluation model, and the optimal antibacterial material among the antibacterial nanomaterials is screened out using the comprehensive performance evaluation model, including: The weight functions in the comprehensive performance evaluation model are used to calculate the weights corresponding to the chemical stability, the physical stability, the efficacy decay and the bactericidal efficacy gradient, respectively, to obtain a weight collection; Using the scoring function in the comprehensive performance evaluation model, the chemical stability, the physical stability, the efficacy decay and the bactericidal efficacy gradient are scored respectively to obtain a score collection; Combining the weight collection and the score collection, and using the vector fusion layer in the comprehensive performance evaluation model to construct a comprehensive feature vector of the chemical stability, the physical stability, the efficacy decay and the bactericidal efficacy gradient; Based on the comprehensive feature vector, the optimal antibacterial material among the antibacterial nanomaterials is screened out.

[0053] It should be explained that the weight function is a function used in the comprehensive performance evaluation model to calculate the weights corresponding to the chemical stability, the physical stability, the efficacy decay and the bactericidal efficacy gradient, such as the weight determination function constructed by the analytic hierarchy process (AHP), the weight collection is a collection of weight values ​​corresponding to the chemical stability, the physical stability, the efficacy decay and the bactericidal efficacy gradient, the scoring function is a function used in the comprehensive performance evaluation model to score the chemical stability, the physical stability, the efficacy decay and the bactericidal efficacy gradient, such as the scoring function constructed by the fuzzy comprehensive evaluation method, and the scoring collection is the scoring values ​​corresponding to the chemical stability, the physical stability, the efficacy decay and the bactericidal efficacy gradient. The vector fusion layer is a neural layer in the comprehensive performance evaluation model for fusing the chemical stability, the physical stability, the efficacy decay and the bactericidal efficacy gradient into a feature vector, and is composed of a plurality of fully connected neurons. The comprehensive feature vector is a vector constructed by multiplying the weights corresponding to the chemical stability, the physical stability, the efficacy decay and the bactericidal efficacy gradient and the corresponding score values. Furthermore, based on the size of the vector eigenvalue of the comprehensive feature vector, the optimal antibacterial material among the antibacterial nanomaterials is screened out. The larger the eigenvalue, the better the performance under comprehensive considerations such as chemical stability, physical stability, efficacy decay and bactericidal efficacy gradient. Accordingly, the optimal antibacterial material with balance in all aspects and outstanding performance can be accurately screened out.

[0054] Compared with the problems described in the background technology, the present invention can obtain the common bacteria types and bacteria quantity statistics in the storage environment by detecting the resident bacteria species and bacterial flora density of the kitchen knife in the storage environment, thereby facilitating the subsequent determination of the antibacterial nanomaterial corresponding to the kitchen knife and the setting of the antibacterial test conditions corresponding to the antibacterial nanomaterial. The present invention can synthesize the knife base material and the antibacterial nanomaterial together by synthesizing the two materials, which is convenient for subsequent analysis and processing. By analyzing the chemical stability corresponding to the synthetic material, the tolerance of the synthetic material can be understood, and the accuracy of subsequent screening of the optimal antibacterial material can be improved. The present invention combines the storage environment parameters and the suitable According to the environmental parameters, the performance attenuation of the synthetic material under the storage environment is evaluated, and the degree of material performance degradation of the synthetic material under the storage environment can be understood, which lays an important foundation for the subsequent screening and processing of the optimal antibacterial material. The present invention performs an antibacterial test experiment on the antibacterial nanomaterial based on the antibacterial test conditions, so as to collect the evaluation index information during the antibacterial test experiment, which lays an important foundation for the subsequent calculation of the bactericidal efficiency gradient of the antibacterial nanomaterial. The present invention uses the comprehensive performance evaluation model to screen out the optimal antibacterial material in the antibacterial nanomaterial, which can accurately locate the material with high antibacterial properties, thereby improving the performance improvement efficiency of the subsequent antibacterial nanomaterial in kitchen knives. Therefore, the performance improvement method of antibacterial nanomaterials in kitchen knives proposed by the present invention improves the performance improvement efficiency of antibacterial nanomaterials in kitchen knives.

[0055] Embodiment 2: like Figure 2 , which is a functional module diagram of a system for improving the performance of antibacterial nanomaterials in kitchen knives provided by an embodiment of the present invention.

[0056] The performance improvement system 100 of an antibacterial nanomaterial in a kitchen knife of the present invention can be installed in an electronic device. According to the functions to be implemented, the performance improvement system 100 of an antibacterial nanomaterial in a kitchen knife can include a material determination module 101, a stability analysis module 102, an efficiency decay evaluation module 103, a bactericidal efficiency gradient calculation module 104 and a performance improvement processing module 105. The module of the present invention can also be called a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0057] In this embodiment, the functions of each module / unit are as follows: The material determination module 101 is used to obtain the kitchen knife to be upgraded and its corresponding knife base material, detect the resident bacterial species and bacterial flora density of the kitchen knife in the storage environment, and determine the antibacterial nanomaterial corresponding to the kitchen knife based on the resident bacterial species; The stability analysis module 102 is used to perform a synthesis process on the tool base material and the antibacterial nanomaterial to obtain a synthetic material, analyze the chemical stability of the synthetic material, and analyze the physical stability of the synthetic material; The performance decay evaluation module 103 is used to collect storage environment parameters under the storage environment, query the adaptation environment parameters corresponding to the synthetic material, and evaluate the performance decay of the synthetic material under the storage environment by combining the storage environment parameters and the adaptation environment parameters; The bactericidal efficacy gradient calculation module 104 is used to set the antibacterial test conditions corresponding to the antibacterial nanomaterial in combination with the bacterial flora density and the resident bacterial species in the environment, perform the antibacterial test experiment on the antibacterial nanomaterial based on the antibacterial test conditions, collect the bactericidal record data during the antibacterial test experiment, and calculate the bactericidal efficacy gradient of the antibacterial nanomaterial based on the bactericidal record data; The performance improvement processing module 105 is used to input the chemical stability, the physical stability, the efficacy attenuation and the bactericidal efficacy gradient as input data into a pre-trained comprehensive performance evaluation model, and use the comprehensive performance evaluation model to screen out the optimal antibacterial material among the antibacterial nanomaterials, and based on the optimal antibacterial material, generate a performance improvement plan corresponding to the kitchen knife, and based on the performance improvement plan, perform performance improvement processing on the kitchen knife to obtain an improvement result.

[0058] In detail, each module described in the system 100 for improving the performance of antibacterial nanomaterials in kitchen knives in the embodiment of the present application is used in the same manner as described above. Figure 1 The same technical means are used as described in the method for improving the performance of antibacterial nanomaterials in kitchen knives, and can produce the same technical effects, so I will not go into details here.

[0059] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0060] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A method for improving the performance of antibacterial nanomaterials in kitchen knives, characterized in that: The method comprises: Obtaining the kitchen knives to be upgraded and the corresponding knife base materials, detecting the resident bacterial species and bacterial flora density of the kitchen knives in the storage environment, and determining the antibacterial nanomaterials corresponding to the kitchen knives based on the resident bacterial species; Performing a synthesis process on the tool base material and the antibacterial nanomaterial to obtain a synthetic material, analyzing the chemical stability of the synthetic material, and analyzing the physical stability of the synthetic material; Collecting storage environment parameters under the storage environment, querying the adaptation environment parameters corresponding to the synthetic material, and evaluating the performance attenuation of the synthetic material under the storage environment by combining the storage environment parameters and the adaptation environment parameters; In combination with the bacterial flora density and the resident bacterial species in the environment, antibacterial test conditions corresponding to the antibacterial nanomaterial are set; based on the antibacterial test conditions, an antibacterial test experiment on the antibacterial nanomaterial is performed; sterilization record data during the antibacterial test experiment is collected; and based on the sterilization record data, a sterilization efficiency gradient of the antibacterial nanomaterial is calculated; The chemical stability, the physical stability, the efficacy attenuation and the bactericidal efficacy gradient are taken as input data and input into a pre-trained comprehensive performance evaluation model. The comprehensive performance evaluation model is used to screen out the optimal antibacterial material among the antibacterial nanomaterials. Based on the optimal antibacterial material, a performance improvement plan corresponding to the kitchen knife is generated. Based on the performance improvement plan, a performance improvement process for the kitchen knife is executed to obtain an improvement result.

2. The method for improving the performance of antibacterial nanomaterials in kitchen knives according to claim 1, characterized in that: The analyzing the chemical stability of the synthetic material comprises: Sampling the synthetic material to obtain a synthetic material sample; Performing acid and alkali soaking treatment on the synthetic material sample, and recording chemical structure change data and sample element dissolution data corresponding to the synthetic material sample; Performing data optimization processing on the chemical structure change data and the sample element dissolution data respectively to obtain target structure change data and target element dissolution data; Combining the target structure change data and the target element dissolution data, calculating the chemical stability coefficient corresponding to the synthetic material sample; According to the chemical stability coefficient, the chemical stability corresponding to the synthetic material is analyzed.

3. The method for improving the performance of antibacterial nanomaterials in kitchen knives according to claim 2, characterized in that: The step of combining the target structure change data and the target element dissolution data to calculate the chemical stability coefficient corresponding to the synthetic material sample includes: Calculating the structural change rate corresponding to the synthetic material sample according to the target structural change data; Calculating the element dissolution rate corresponding to the synthetic material sample according to the target element dissolution data; Combining the structural change rate and the element dissolution rate, the chemical stability coefficient corresponding to the synthetic material sample is calculated by the following formula: ； Among them, A represents the chemical stability coefficient corresponding to the synthetic material sample, represents the rate of structural change, Indicates the element dissolution rate.

4. The method for improving the performance of antibacterial nanomaterials in kitchen knives according to claim 1, characterized in that: The analyzing the physical stability of the synthetic material comprises: measuring the particle size distribution of the synthetic material to obtain initial particle size distribution data; Calculating the initial average particle size of the synthetic material according to the initial particle size distribution data; Performing scattering processing on the synthetic material using a preset dynamic light scattering technology to obtain agglomerated particle size distribution data; Calculating the average agglomerated particle size of the synthetic material after scattering according to the agglomerated particle size distribution data; Calculate the material agglomeration index corresponding to the synthetic material by combining the agglomerated average particle size and the initial average particle size; According to the material agglomeration index, the physical stability of the synthetic material is analyzed.

5. The method for improving the performance of antibacterial nanomaterials in kitchen knives according to claim 1, characterized in that: The step of combining the storage environment parameter and the adaptation environment parameter to evaluate the performance attenuation of the synthetic material under the storage environment includes: Based on the storage environment parameters, the associated environment parameters in the adaptation environment parameters are screened out; Standardizing the associated environment parameter and the stored environment parameter respectively to obtain a first standard environment parameter and a second standard environment parameter; Calculating the environmental deviation of the synthetic material under the storage environment by combining the first standard environmental parameter and the second standard environmental parameter; Determining, according to the environmental deviation, a potential failure risk of the synthetic material in the storage environment; Based on the potential failure risk, the performance degradation of the synthetic material under the storage environment is evaluated.

6. The method for improving the performance of antibacterial nanomaterials in kitchen knives according to claim 5, characterized in that: The step of calculating the environmental deviation of the synthetic material under the storage environment by combining the first standard environmental parameter and the second standard environmental parameter comprises: Identifying an environmental parameter index corresponding to the first standard environmental parameter, and calculating an index importance corresponding to the environmental parameter index according to the first standard environmental parameter; In combination with the indicator importance, the first standard environmental parameter and the second standard environmental parameter, the environmental deviation of the synthetic material in the storage environment is calculated by the following formula: ； Where B represents the environmental deviation of the synthetic material under the storage environment, represents the index importance of the i-th index in the environmental parameter index, Indicates the parameter of the ath indicator in the environmental parameter index in the first standard parameter. It indicates the parameter corresponding to the ath indicator in the environmental parameter index in the second standard environmental parameter, a indicates the serial number of the environmental parameter index, and r indicates the number corresponding to the environmental parameter index. Represents the maximum value function between the first standard parameter and the second standard parameter.

7. The method for improving the performance of antibacterial nanomaterials in kitchen knives according to claim 6, characterized in that: The step of calculating the indicator importance corresponding to the environmental parameter indicator according to the first standard environmental parameter includes: Calculating the parameter covariance of the first standard environmental parameter, and constructing a covariance matrix corresponding to the environmental parameter index according to the parameter covariance; Based on the covariance matrix, determining the indicator eigenvalue corresponding to the environmental parameter indicator; Based on the indicator characteristic value, calculating the indicator contribution rate corresponding to the environmental parameter indicator; According to the indicator contribution rate, the indicator importance corresponding to the environmental parameter indicator is determined.

8. The method for improving the performance of antibacterial nanomaterials in kitchen knives according to claim 1, characterized in that: The step of calculating the bactericidal efficacy gradient of the antibacterial nanomaterial based on the bactericidal record data comprises: Identifying the recording time point corresponding to the sterilization record data, and determining the initial bacterial count of the antibacterial nanomaterial and the surviving bacterial count corresponding to the recording time point from the sterilization record data; Combining the initial bacterial count and the surviving bacterial count, the material sterilization rate of the antibacterial nanomaterial at each time point is calculated by the following formula: ； in, It represents the sterilization rate of antibacterial nanomaterials at each time point, represents the initial bacterial count, It indicates the number of surviving bacteria at the recording time point b; The bactericidal efficiency gradient of the antibacterial nanomaterial is calculated based on the bactericidal rate of the material and the recorded time point.

9. The method for improving the performance of antibacterial nanomaterials in kitchen knives according to claim 8, characterized in that: The step of calculating the bactericidal efficiency gradient of the antibacterial nanomaterial by combining the material bactericidal rate and the recorded time point comprises: Calculating the average sterilization period of the antibacterial nanomaterial according to the recorded time points; Combined with the average sterilization cycle, the recorded time point and the sterilization rate of the material, the sterilization efficiency gradient of the antibacterial nanomaterial is calculated by the following formula: ； Where M represents the bactericidal efficiency gradient of antibacterial nanomaterials, Indicates the sterilization rate of the material corresponding to the recording time point d, Indicates the dth time point in the recorded time points, represents the average sterilization cycle, d represents the sequence of recorded time points, and q represents the number of recorded time points.

10. The method for improving the performance of antibacterial nanomaterials in kitchen knives according to claim 1, characterized in that: The chemical stability, the physical stability, the efficacy attenuation and the bactericidal efficacy gradient are input as input data to a pre-trained comprehensive performance evaluation model, and the optimal antibacterial material among the antibacterial nanomaterials is screened out using the comprehensive performance evaluation model, including: The weight functions in the comprehensive performance evaluation model are used to calculate the weights corresponding to the chemical stability, the physical stability, the efficacy decay and the bactericidal efficacy gradient, respectively, to obtain a weight collection; Using the scoring function in the comprehensive performance evaluation model, the chemical stability, the physical stability, the efficacy decay and the bactericidal efficacy gradient are scored respectively to obtain a score collection; Combining the weight collection and the score collection, and using the vector fusion layer in the comprehensive performance evaluation model to construct a comprehensive feature vector of the chemical stability, the physical stability, the efficacy decay and the bactericidal efficacy gradient; Based on the comprehensive feature vector, the optimal antibacterial material among the antibacterial nanomaterials is screened out.

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