Process optimization method and system for converting forestry and agricultural residues into nitrogen-doped porous carbon

Abstract

The invention discloses a process optimization method and system for converting forestry and agricultural residues into nitrogen-doped porous carbon. The method comprises the following steps: firstly, determining components, structural characterization, ORR dynamic performance and battery performance data of target nitrogen-doped porous carbon and a historical sample, and calculating the similarity between the target and the historical sample; according to different manufacturing methods, the nitrogen-doped porous carbon with high similarity is divided into four classes, and the proportion of each class in different manufacturing methods is determined. Then, the drying degree and hardness of the agricultural waste in the existing and historical manufacturing methods are analyzed, and the similarity between the existing agricultural waste and the waste in the historical sample is calculated; and calculating matching coefficients according to the similarity of the wastes and the proportions of various manufacturing methods, and finally selecting the manufacturing method with the maximum matching coefficient as an optimal scheme. According to the method, through systematic evaluation and optimization, the efficiency of the process of converting the agricultural and forestry wastes into the efficient nitrogen-doped porous carbon is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of agricultural and forestry waste conversion, and more specifically, to a process optimization method and system for converting agricultural and forestry waste into nitrogen-doped porous carbon. Background Art

[0002] The technology of converting agricultural and forestry waste into nitrogen-doped porous carbon has received widespread attention in recent years, especially in the fields of energy, environmental protection, catalysis, supercapacitors and batteries. Nitrogen-doped porous carbon materials have excellent conductivity, large specific surface area, rich pore structure and good electrochemical properties, especially in catalysis and energy storage materials.

[0003] Agricultural and forestry wastes (such as straw, wood chips, rice husks, fruit cores, etc.) are potential carbon sources and can be prepared into nitrogen-doped porous carbon through appropriate conversion techniques. The basic steps of this process include pretreatment of agricultural and forestry wastes, introduction of nitrogen sources, carbonization treatment, and post-treatment.

[0004] The existing technology is unable to select a suitable production method efficiently and accurately, and usually only selects the production method based on simple similarity matching, which easily leads to a waste of resources.

[0005] In view of the above problems, the present invention proposes a solution. Summary of the invention

[0006] In order to overcome the above-mentioned defects of the prior art, the process optimization method and system for converting agricultural and forestry waste into nitrogen-doped porous carbon in the embodiments of the present invention are provided to solve the problems raised in the above-mentioned background technology.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] Step S1: Determine the target nitrogen-doped porous carbon and the historical nitrogen-doped porous carbon composition and structural characterization, ORR kinetic performance analysis data, and battery performance analysis data, and calculate the similarity between the target nitrogen-doped porous carbon and the historical nitrogen-doped porous carbon by cosine similarity; screen out a batch of nitrogen-doped porous carbons with high similarity;

[0009] Step S2: classifying a batch of nitrogen-doped porous carbons with high similarity screened out into four different types of manufacturing methods according to different manufacturing methods, and determining the proportion of each manufacturing method to which the nitrogen-doped porous carbons with high similarity belong;

[0010] Step S3: Determine the degree of dryness and hardness of agricultural waste in existing and historical production methods, and calculate the similarity between existing agricultural waste and agricultural waste in historical production methods;

[0011] Step S4: Calculate the matching coefficient based on the weighted sum of the similarity between the existing agricultural waste and various historical production methods and the proportion of production methods to which each similarity-high nitrogen-doped porous carbon belongs, and the production method with the largest matching coefficient is selected as the preferred production method.

[0012] In a preferred embodiment, in step S1, the target and historical nitrogen-doped porous carbon composition and structural characterization, ORR kinetic performance analysis data, and battery kinetic energy analysis data are normalized, and the historical nitrogen-doped porous carbon composition and structural characterization, ORR kinetic performance analysis data, and battery kinetic energy analysis data are feature vectorized to construct the following vector t i =(x i1 ,x i2 ,.......,x in ); x im represents the value of the mth feature of the i-th nitrogen-doped porous carbon; construct a feature vector for the target nitrogen-doped porous carbon: x = (y1, y2,......., y m ).

[0013] In a preferred embodiment, the historical and target nitrogen-doped porous carbons are determined to construct feature vectors and the cosine similarity is used to calculate the similarity between the target nitrogen-doped porous carbon and the historical nitrogen-doped porous carbon:

[0014]

[0015] In a preferred embodiment, the similarity between the target nitrogen-doped porous carbon and the historical nitrogen-doped porous carbon is determined, and compared with a similarity threshold preset by the system, and the nitrogen-doped porous carbon having a value greater than the threshold preset by the system is screened out.

[0016] In a preferred embodiment, in step S2, nitrogen-doped porous carbon greater than a system preset threshold is determined, and the production methods of nitrogen-doped porous carbon greater than the system preset threshold are divided into these four different categories of production methods according to the order of pyrolysis and doping of the production methods of nitrogen-doped porous carbon greater than the system preset threshold and the different pyrolysis methods. After the division is completed, the proportion of production methods of nitrogen-doped porous carbon with high similarity is recorded.

[0017] In a preferred embodiment, in step S3, the degree of dryness and hardness of agricultural waste in existing and historical production methods are determined, and the similarity between existing agricultural waste and agricultural waste in historical production methods is calculated by cosine similarity.

[0018] In a preferred embodiment, in step S4, the similarity between existing agricultural waste and agricultural waste in various historical production methods and the proportion of production methods to which each nitrogen-doped porous carbon with high similarity belongs are determined, and the matching coefficient is calculated by weighted calculation: T=αXS+βZB; wherein XS represents the similarity between existing agricultural waste and agricultural waste in various historical production methods, and ZB represents the proportion of production methods to which each nitrogen-doped porous carbon with high similarity belongs; T represents the matching coefficient, and α and β are system-set weight values.

[0019] In a preferred embodiment, the matching coefficients of the various production methods are determined, and the production method with the largest matching coefficient is selected and output as the preferred production method.

[0020] In a preferred embodiment, it includes: an information collection module, a feature matching module, a recommendation module, and a storage module;

[0021] The information acquisition module is used to obtain component and structural characterization, ORR kinetic performance analysis data, battery performance analysis data, and the degree of dryness and hardness of agricultural waste in various existing and historical production methods; transmit the component and structural characterization, ORR kinetic performance analysis data, and battery performance analysis data to the feature matching module, and transmit the degree of dryness and hardness of agricultural waste in various existing and historical production methods to the recommendation module;

[0022] The feature matching module finds the nitrogen-doped porous carbon individual that is most similar to the new nitrogen-doped porous carbon based on the composition and structure characterization, ORR kinetic performance analysis data, and battery performance analysis data; and transmits the most similar nitrogen-doped porous carbon individual to the recommendation module;

[0023] The recommendation module is used to classify similar nitrogen-doped porous carbon individuals into different production methods, and determine the proportion of different types of production methods in all production methods; calculate the similarity between existing agricultural waste and historical agricultural waste according to the degree of dryness and hardness of agricultural waste in existing and historical production methods; determine the proportion of different types of production methods in all production methods and the similarity between existing agricultural waste and historical agricultural waste to calculate the matching coefficient, and output the production method with the largest matching coefficient;

[0024] The storage module is used to store all data during the system processing.

[0025] Technical effects and advantages of the present invention:

[0026] Providing efficient and accurate production methods improves the utilization rate of agricultural waste and avoids the waste of resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0028] Figure 1 A schematic flow chart of a process optimization method for converting agricultural and forestry waste into nitrogen-doped porous carbon according to the present invention;

[0029] Figure 2 A schematic diagram of the structure of a process optimization system for converting agricultural and forestry waste into nitrogen-doped porous carbon according to the present invention;

[0030] Figure 3 A schematic diagram of a process optimization method for converting agricultural and forestry waste into nitrogen-doped porous carbon and a system for first doping and then pyrolysis production of the carbon;

[0031] Figure 4 This is a schematic diagram of the process optimization method for converting agricultural and forestry waste into nitrogen-doped porous carbon and the system's pyrolysis followed by doping production method of the present invention. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0033] The present invention first determines the target nitrogen-doped porous carbon and the historical nitrogen-doped porous carbon composition and structural characterization, ORR kinetic performance analysis data, and battery performance analysis data, and calculates the similarity between the target nitrogen-doped porous carbon and the historical nitrogen-doped porous carbon; then screens out a batch of nitrogen-doped porous carbons with high similarity; divides the screened batch of nitrogen-doped porous carbons with high similarity into four different production methods according to different production methods, and determines the proportion of production methods to which each nitrogen-doped porous carbon with high similarity belongs. Determine the degree of dryness and hardness of agricultural waste in the existing and historical production methods to calculate the similarity between the existing agricultural waste and the agricultural waste in the historical production methods; calculate the matching coefficient based on the weighted sum of the similarity between the existing agricultural waste and the agricultural waste in the historical production methods and the proportion of production methods to which each nitrogen-doped porous carbon with high similarity belongs, and the one with the largest matching coefficient is output as the preferred production method.

[0034] Example 1

[0035] The present invention provides Figure 1 The process optimization method for converting agricultural and forestry waste into nitrogen-doped porous carbon includes the following steps:

[0036] Step S1: Determine the target nitrogen-doped porous carbon and the historical nitrogen-doped porous carbon composition and structural characterization, ORR kinetic performance analysis data, and battery performance analysis data, calculate the similarity between the target nitrogen-doped porous carbon and the historical nitrogen-doped porous carbon; and select a batch of nitrogen-doped porous carbons with high similarity;

[0037] Step S2: classifying a batch of nitrogen-doped porous carbons with high similarity screened out into four different types of manufacturing methods according to different manufacturing methods, and determining the proportion of each manufacturing method to which the nitrogen-doped porous carbons with high similarity belong;

[0038] Step S3: Determine the degree of dryness and hardness of agricultural waste in existing and historical production methods, and calculate the similarity between existing agricultural waste and agricultural waste in historical production methods;

[0039] Step S4: Calculate the matching coefficient based on the weighted sum of the similarity between the existing agricultural waste and various historical production methods and the proportion of production methods to which each similarity-high nitrogen-doped porous carbon belongs, and the production method with the largest matching coefficient is selected as the preferred production method.

[0040] In step S1, the composition and structure characterization includes: structure characterization: scanning and transmission electron microscope tests to observe the microscopic morphology of the material, nitrogen isothermal physical adsorption and desorption tests to analyze the material's specific surface area, pore melting and pore size distribution and other pore structure parameters, and Raman spectroscopy to characterize the surface defects of the carbon surface;

[0041] Elemental composition and active site analysis data: X-ray photoelectron spectroscopy measures the chemical and electronic states of each element on the material surface, analyzes the doping situation of the material, and electron microscopy spectroscopy and TEM mapping observe the element distribution on the material surface.

[0042] ORR kinetic performance analysis data:

[0043] Preparation of working electrode: Ultrasonic disperse a certain mass of material into a mixed solution containing water, alcohol and Nafion, and obtain a catalyst slurry of a certain proportion after uniform dispersion. Take a certain volume of catalyst slurry and drop it on the glassy carbon electrode. Rotate and dry it at room temperature. The properties of the working electrode can be optimized by changing the ratio of catalyst / water / alcohol / Nafion and the volume of drop coating.

[0044] Half-cell (three-electrode) test apparatus assembly: three-electrode system (working electrode, Hg / HgO and Ag / AgCl-reference electrodes, carbon rod counter electrode), electrochemical workstation and rotating disk / ring-disk electrode apparatus.

[0045] Catalyst ORR performance test: Cyclic voltammetry or linear sweep voltammetry is used to test the potential and current density of ORR, chronoamperometry is used to test the stability and anti-poisoning performance of ORR, electrochemical impedance spectroscopy is used to analyze the mass transfer efficiency of ORR, and the number of electron transfers in the ORR process is calculated and analyzed based on the Koutecky-Levich equation and double potential (RRDE) test.

[0046] Battery performance analysis data include: zinc-air fuel cell performance analysis data, proton exchange membrane fuel cell (PEMFC) performance analysis data.

[0047] Zinc-air fuel cell performance analysis data:

[0048] Battery preparation: The zinc-air single cell consists of a zinc plate anode, an air cathode and three polymethyl methacrylate plates. First, the air cathode needs to be prepared. The sample is first dispersed in a mixed dispersion containing deionized water, isopropanol and Nafion to obtain ink, which is then coated on hydrophobic carbon paper and dried. The carbon paper, nickel foam (current collector) and a waterproof and breathable membrane are pressed to obtain the air cathode.

[0049] Battery performance test: test the potential difference between the anode and cathode, i.e. the open circuit voltage of the battery; test the polarization curve of the battery by linear sweep voltammetry; record the cathode and anode potentials of the battery and calculate the limiting current density and output power of the battery; test the long-term working stability of the battery by constant potential / constant current.

[0050] Proton exchange membrane fuel cell (PEMFC) performance analysis data:

[0051] Membrane electrode production: The membrane electrode (MEA) is composed of a bipolar plate (current collecting plate) and a metal heating plate. First, the MEA needs to be prepared. The sample is first mixed with isopropanol, water and Nafion to form a catalyst ink. Then the ink is sprayed on the gas diffusion layer with a spray gun and dried to obtain a catalytic layer. The gas diffusion layer coated with the catalytic layer is then hot-pressed with the PEM to obtain the MEA.

[0052] Battery performance test: test the potential difference between the anode and cathode, i.e. the open circuit voltage of the battery; test the polarization curve of the battery by linear sweep voltammetry; record the cathode and anode potentials of the battery and calculate the limiting current density and output power of the battery; test the long-term working stability of the battery by constant potential / constant current.

[0053] In a three-electrode system, various electrochemical methods are used to determine the oxygen reduction potential and limiting current density of nitrogen-doped porous carbon electrocatalytic ORR, study the stability and anti-poisoning performance of the catalyst electrocatalytic ORR, analyze the electron transfer between metal oxide nanoparticle catalysts and carriers, study the ORR kinetics, calculate the ORR electron transfer number, etc. Fuel cell performance: assemble a fuel cell single cell system, test the cell's limiting power density and overpotential, and study the stability of the catalyst electrocatalytic ORR in a fuel cell cell and its environmental tolerance; composition and structure characterization: through modern instrumental analysis technology, characterize the macro and micro structures of the products, including the morphology, specific surface area, pore size distribution, carbonization degree and metal oxide phase of the products, the formation process of nitrogen-doped porous carbon, characterize the carbon surface defects and the chemical and electronic states of each element, etc.

[0054] The target and historical nitrogen-doped porous carbon composition and structural characterization, ORR kinetic performance analysis data, and battery kinetic energy analysis data were normalized. Specifically, the following formula was used to normalize the data R i Normalized to the range [0,1]: Where R′ i is the normalized value, R min and R max The data R i The minimum and maximum values ​​of .

[0055] The composition and structural characterization of historical nitrogen-doped porous carbon, ORR kinetic performance analysis data, and battery kinetic energy analysis data are quantized to construct the following vector t i =(x i1 ,x i2 ,.......,x in ); where x im represents the value of the mth feature of the i-th nitrogen-doped porous carbon;

[0056] Construct a feature vector for the target nitrogen-doped porous carbon: x = (y1, y2, ..., y m );

[0057] Use cosine similarity to calculate the similarity between the target nitrogen-doped porous carbon and the historical nitrogen-doped porous carbon: Where k is the feature index, which ranges from 1 to m, traversing all features, so that the cosine similarity formula can calculate the similarity between multi-dimensional feature vectors.

[0058] The calculated similarity between the target nitrogen-doped porous carbon and the historical nitrogen-doped porous carbon is compared with the similarity threshold preset by the system, and the nitrogen-doped porous carbon with a value greater than the preset threshold is taken as an alternative. Different nitrogen-doped porous carbons correspond to different manufacturing methods.

[0059] In step S2, four different production methods are divided according to the different production process of the alternative solutions.

[0060] The following are two methods of making by pyrolysis first and then doping, such as Figure 3 As shown:

[0061] Step A1: Pre-treatment of agricultural and forestry waste:

[0062] Collection of agricultural and forestry waste: First, rice and wheat straw were selected as representatives for research, and then expanded to other agricultural and forestry wastes.

[0063] Cleaning and drying of agricultural and forestry waste: After washing away the ash and dirt on the surface of the agricultural and forestry waste, place it in a vacuum drying oven to dry overnight.

[0064] Cutting and grinding of agricultural and forestry waste: Cut, crush / grind the dried agricultural and forestry waste and store them for later use.

[0065] Step A2: Carbonization of agricultural and forestry waste:

[0066] Tube furnace pyrolysis: Under the protection of inert gas, the pre-treated agricultural and forestry waste is pyrolyzed in a vacuum tube furnace to prepare the corresponding agricultural and forestry waste biochar. The structure and properties of the biochar are optimized by adjusting the experimental parameters such as the heating rate, pyrolysis temperature and pyrolysis time.

[0067] Hydrothermal / solvothermal: A certain mass ratio of biomass and solvent is placed in a reactor and subjected to high-temperature hydrothermal / solvothermal reaction in an oven to prepare the corresponding biochar. The structure and properties of the biochar are optimized by adjusting the experimental parameters such as the heating rate, temperature, time, and the type and concentration of the solvent used.

[0068] Step A3: Carbon modification of agricultural and forestry wastes:

[0069] Activation pore making: A certain mass ratio of agricultural and forestry waste biochar / activator is fully mixed by dry ball milling / ultrasonic impregnation / hot pressing domain, etc., and then placed in a vacuum tube furnace / hydrothermal kettle for high-temperature activation to create pores inside and on the surface of the biochar. The internal pores and surface defect structure of the material are optimized by adjusting parameters such as the biochar / activator ratio, the type of activator, the heating rate, the temperature and time, and the multi-scale pore structure is designed.

[0070] Step A4: Nitrogen atom / inorganic metal nanoparticle doping:

[0071] A certain mass ratio of biochar / nitrogen-containing compound / metal compound is fully mixed by dry ball milling / ultrasonic impregnation and placed in a vacuum tube furnace / hydrothermal reactor for heteroatom doping. The distribution of the reactive active sites of the material is optimized by adjusting the ratio of nitrogen-containing compound / metal compound, the type of activator, the heating rate, the temperature and time and other parameters. Among metal oxides, manganese and cobalt oxides have higher ORR electrocatalytic activity, so the hydroxides or carbonates of manganese and cobalt are selected first, and then expanded to compounds of other metal elements.

[0072] The following are two production methods of doping first and then pyrolysis, such as Figure 4 As shown:

[0073] The specific work that needs to be done is:

[0074] Step B1: Pretreatment of agricultural and forestry waste: including chopping / grinding the agricultural and forestry waste precursor to reduce the size of biomass particles, promoting heat and mass transfer within the biomass particles, and reducing the ash and mineral content of the agricultural and forestry waste precursor by acid washing / water washing;

[0075] Step B2: Solution impregnation method: dissolve the nitrogen source in an appropriate solvent (such as water or ethanol), and then soak the agricultural and forestry waste in the nitrogen source solution. The soaking time can be adjusted according to demand, usually 1-12 hours, to ensure that the nitrogen source fully penetrates into the waste. Solid phase doping method: directly mix the solid nitrogen source (such as urea) with the agricultural and forestry waste powder, and after sufficient stirring or pressing, a uniform nitrogen source-doped sample is obtained. This method does not require a solvent, but it is necessary to ensure sufficient contact between the nitrogen source and the waste during mixing;

[0076] Step B3: The sample doped by the solution impregnation method is pyrolyzed by hydrothermal / solvothermal method, and the sample doped by the solid phase doping method is pyrolyzed by a tube furnace.

[0077] The alternative production methods are divided into four different categories according to the order of pyrolysis and doping and the different pyrolysis methods. After the division is completed, the proportion of each production method with high similarity of nitrogen-doped porous carbon is recorded.

[0078] In step S3, the degree of drying of agricultural waste and the hardness of agricultural waste in the existing and historical production methods are determined. The drying process of agricultural waste in the existing production methods is firstly carried out by weighing the mass of agricultural waste containing water; placing the sample in an oven, usually drying it at a temperature of 60°C-105°C, and taking out the sample after drying for several hours, and weighing the mass again after cooling; the degree of drying in the sample is calculated by measuring the mass difference before and after drying. The existing hardness of agricultural waste is evaluated by applying a vertical compressive force to the waste and measuring the pressure of its deformation or fracture. The agricultural waste is placed in a testing machine (such as a universal material testing machine) and a certain compressive force is applied until the material is deformed or fractured; the hardness is judged by the maximum applied pressure or deformation value. The commonly used unit of hardness is MPa.

[0079] The dryness and hardness of agricultural waste in various historical production methods are obtained through historical data; the dryness and hardness of agricultural waste in various current and historical production methods are determined by calculating the similarity between the current agricultural waste and the agricultural waste in various historical production methods through cosine similarity. The calculation method is consistent with the above method.

[0080] In step S4, the similarity between existing agricultural waste and agricultural waste in various historical production methods and the proportion of production methods of nitrogen-doped porous carbon with high similarity are determined, and the matching coefficient is calculated by weighted calculation: T = αXS + βZB; wherein XS represents the similarity between existing agricultural waste and agricultural waste in various historical production methods, ZB represents the proportion of production methods of nitrogen-doped porous carbon with high similarity; T represents the matching coefficient, and α and β are weight values ​​set by the system.

[0081] The matching coefficients of the various production methods are determined, and the production method with the largest matching coefficient is selected as the preferred production method for output.

[0082] Example 2

[0083] The present invention provides Figure 2 The process optimization system for converting agricultural and forestry waste into nitrogen-doped porous carbon shown in the figure includes: an information acquisition module, a feature matching module, a recommendation module, and a storage module;

[0084] The information acquisition module is used to obtain component and structural characterization, ORR kinetic performance analysis data, battery performance analysis data, and the degree of dryness and hardness of agricultural waste in various existing and historical production methods; transmit the component and structural characterization, ORR kinetic performance analysis data, and battery performance analysis data to the feature matching module, and transmit the degree of dryness and hardness of agricultural waste in various existing and historical production methods to the recommendation module;

[0085] The feature matching module finds the nitrogen-doped porous carbon individual that is most similar to the new nitrogen-doped porous carbon based on the composition and structure characterization, ORR kinetic performance analysis data, and battery performance analysis data; and transmits the most similar nitrogen-doped porous carbon individual to the recommendation module;

[0086] The recommendation module is used to classify similar nitrogen-doped porous carbon individuals into different production methods, and determine the proportion of different types of production methods in all production methods; calculate the similarity between existing agricultural waste and historical agricultural waste according to the degree of dryness and hardness of agricultural waste in existing and historical production methods; determine the proportion of different types of production methods in all production methods and the similarity between existing agricultural waste and historical agricultural waste to calculate the matching coefficient, and output the production method with the largest matching coefficient;

[0087] The storage module is used to store all data during the system processing.

[0088] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0089] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0090] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0091] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0092] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A process optimization method for converting agricultural and forestry waste into nitrogen-doped porous carbon, characterized in that: The following steps are involved: Step S1: Determine the target nitrogen-doped porous carbon and the historical nitrogen-doped porous carbon composition and structural characterization, ORR kinetic performance analysis data, and battery performance analysis data, and calculate the similarity between the target nitrogen-doped porous carbon and the historical nitrogen-doped porous carbon by cosine similarity; screen out a batch of nitrogen-doped porous carbons with high similarity; Step S2: classifying a batch of nitrogen-doped porous carbons with high similarity screened out into four different types of manufacturing methods according to different manufacturing methods, and determining the proportion of each manufacturing method to which the nitrogen-doped porous carbons with high similarity belong; Step S3: Determine the degree of dryness and hardness of agricultural waste in existing and historical production methods, and calculate the similarity between existing agricultural waste and agricultural waste in historical production methods; Step S4: Calculate the matching coefficient based on the weighted sum of the similarity between the existing agricultural waste and various historical production methods and the proportion of production methods to which each similarity-high nitrogen-doped porous carbon belongs, and the production method with the largest matching coefficient is selected as the preferred production method.

2. The process optimization method for converting agricultural and forestry waste into nitrogen-doped porous carbon according to claim 1, characterized in that: In step S1, the target and historical nitrogen-doped porous carbon composition and structural characterization, ORR kinetic performance analysis data, and battery kinetic energy analysis data are normalized, and the historical nitrogen-doped porous carbon composition and structural characterization, ORR kinetic performance analysis data, and battery kinetic energy analysis data are feature vectorized to construct the following vector t i =(x i1 ,x i2 ,.......,x in ); x im represents the value of the mth feature of the i-th nitrogen-doped porous carbon; construct a feature vector for the target nitrogen-doped porous carbon: x = (y1, y2,......., y m ).

3. The process optimization method for converting agricultural and forestry waste into nitrogen-doped porous carbon according to claim 2, characterized in that: Determine the historical and target nitrogen-doped porous carbon to construct feature vectors and use cosine similarity to calculate the similarity between the target nitrogen-doped porous carbon and the historical nitrogen-doped porous carbon:

4. The process optimization method for converting agricultural and forestry waste into nitrogen-doped porous carbon according to claim 3, characterized in that: Determine the similarity between the target nitrogen-doped porous carbon and the historical nitrogen-doped porous carbon, compare it with the similarity threshold preset by the system, and screen out the nitrogen-doped porous carbon that is greater than the threshold preset by the system.

5. The process optimization method for converting agricultural and forestry waste into nitrogen-doped porous carbon according to claim 1, characterized in that: In step S2, nitrogen-doped porous carbon with a content greater than a system preset threshold is determined, and the production methods of nitrogen-doped porous carbon with a content greater than a system preset threshold are divided into four different categories of production methods according to the order of pyrolysis and doping of the production methods of nitrogen-doped porous carbon with a content greater than a system preset threshold and the different pyrolysis methods. After the division is completed, the proportion of production methods of nitrogen-doped porous carbon with high similarity is recorded.

6. The process optimization method for converting agricultural and forestry waste into nitrogen-doped porous carbon according to claim 1, characterized in that: In step S3, the degree of dryness and hardness of agricultural waste in existing and historical production methods are determined, and the similarity between existing agricultural waste and agricultural waste in historical production methods is calculated by cosine similarity.

7. The process optimization method for converting agricultural and forestry waste into nitrogen-doped porous carbon according to claim 1, characterized in that: In step S4, the similarity between existing agricultural waste and agricultural waste in various historical production methods and the proportion of production methods of nitrogen-doped porous carbon with high similarity are determined, and the matching coefficient is calculated by weighted calculation: T = αXS + βZB; wherein XS represents the similarity between existing agricultural waste and agricultural waste in various historical production methods, ZB represents the proportion of production methods of nitrogen-doped porous carbon with high similarity; T represents the matching coefficient, and α and β are weight values ​​set by the system.

8. The process optimization method for converting agricultural and forestry waste into nitrogen-doped porous carbon according to claim 7, characterized in that: The matching coefficients of the various production methods are determined, and the production method with the largest matching coefficient is selected as the preferred production method for output.

9. A process optimization system for converting agricultural and forestry waste into nitrogen-doped porous carbon, used to implement the process optimization method for converting agricultural and forestry waste into nitrogen-doped porous carbon as claimed in any one of claims 1 to 8, characterized in that: include: Information collection module, feature matching module, recommendation module, storage module; The information acquisition module is used to obtain component and structural characterization, ORR kinetic performance analysis data, battery performance analysis data, and the degree of dryness and hardness of agricultural waste in various existing and historical production methods; transmit the component and structural characterization, ORR kinetic performance analysis data, and battery performance analysis data to the feature matching module, and transmit the degree of dryness and hardness of agricultural waste in various existing and historical production methods to the recommendation module; The feature matching module finds the nitrogen-doped porous carbon individual that is most similar to the new nitrogen-doped porous carbon based on the composition and structure characterization, ORR kinetic performance analysis data, and battery performance analysis data; and transmits the most similar nitrogen-doped porous carbon individual to the recommendation module; The recommendation module is used to classify similar nitrogen-doped porous carbon individuals into different fabrication methods and determine the proportion of different categories of fabrication methods in all fabrication methods; Calculate the similarity between existing agricultural waste and historical agricultural waste according to the degree of dryness and hardness of agricultural waste in existing and historical production methods; determine the proportion of different types of production methods in all production methods and the matching coefficient calculated by the similarity between existing agricultural waste and historical agricultural waste, and output the production method with the largest matching coefficient; The storage module is used to store all data during the system processing.

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