CN117174899B

CN117174899B - Preparation method of carbon fluoride anode material

Info

Publication number: CN117174899B
Application number: CN202311442502.5A
Authority: CN
Inventors: 杨恩东; 丁佳佳; 许检红; 邵国柱
Original assignee: Nantong Jianghai Energy Storage Technology Co ltd
Current assignee: Nantong Jianghai Energy Storage Technology Co ltd
Priority date: 2023-11-01
Filing date: 2023-11-01
Publication date: 2024-01-26
Anticipated expiration: 2043-11-01
Also published as: CN117174899A

Abstract

The invention provides a preparation method of a carbon fluoride anode material, which relates to the technical field of batteries and comprises the following steps: reading a preparation process of the fluorocarbon cathode material, positioning modification process points, searching and calling an initial modification scheme set, building a optimizing space to generate a self-adaptive optimizing model, optimizing and testing single modification preparation schemes with high capacity, low cost and industrialization as optimizing constraint, determining a plurality of single modification schemes, performing subsequent process association influence analysis of mapping modification process nodes, determining a collaborative modification scheme, combining a performance prediction model, predicting material preparation energy efficiency based on the collaborative modification scheme, performing compensation analysis, determining a compensation modification scheme, and performing process preparation of the fluorocarbon cathode material. The invention solves the technical problems of poor effect and low efficiency of the traditional method caused by the fact that the traditional method usually needs a large number of experiments and repeated attempts to find the optimal modification scheme and can not fully meet the requirements.

Description

Preparation method of carbon fluoride anode material

Technical Field

The invention relates to the technical field of batteries, in particular to a preparation method of a fluorocarbon anode material.

Background

Carbon fluoride cathode materials commonly used in lithium ion batteries and other energy storage devices are prepared, and these cathode materials play an important role in storing and releasing electrical energy in the battery. In the battery technology, the performance of the cathode material has great influence on the capacity, charge-discharge efficiency, cycle life and other key performance indexes of the battery, so that the preparation of the high-performance carbon fluoride cathode material is very important. However, the conventional preparation method faces some technical problems, on one hand, the preparation of the conventional fluorocarbon cathode material generally involves a complex modification process, and multiple attempts and optimization are required at different modification procedure points, which makes the preparation process time-consuming, labor-consuming and costly; on the other hand, searching for the best modification scheme generally requires a large number of experiments and repeated attempts, and may not fully meet the requirements of high capacity, low cost, industrialization and the like, which results in the problems of poor effect and low efficiency of the conventional method.

Therefore, the preparation method of the carbon fluoride cathode material needs to solve the technical problems to realize higher efficiency, lower cost and more industrialization, and meet the requirements in performance.

Disclosure of Invention

The preparation method aims at solving the problems that the preparation of the traditional carbon fluoride cathode material generally involves a complex modification process, and multiple attempts and optimization are needed at different modification process points, so that the preparation process is time-consuming, labor-consuming and high in cost; and searching for the optimal modification scheme generally requires a large number of experiments and repeated attempts, and may not fully meet the requirements of high capacity, low cost, industrialization and the like, so that the traditional method has the technical problems of poor effect and low efficiency.

In view of the above, the present application provides a method for preparing a fluorocarbon cathode material.

In a first aspect of the disclosure, a method for preparing a carbon fluoride cathode material is provided, the method comprising: reading a preparation process of the carbon fluoride anode material, and positioning a modification procedure point, wherein the modification procedure point is marked with a node anode modification standard; aiming at the modification procedure point, searching and calling an initial modification scheme set by combining with the industrial Internet of things; setting up a optimizing space by taking the modification procedure point as an axial direction, and generating a self-adaptive optimizing model; carrying out single modification preparation scheme optimization and test detection based on the initial modification scheme set by combining the self-adaptive optimization model with high capacity, low cost and industrialization as optimization constraint, and determining a plurality of single modification schemes corresponding to the modification procedure points; performing a subsequent process association impact analysis mapping the modification process nodes for the plurality of single modification schemes to determine a collaborative modification scheme; combining a performance prediction model, predicting the material preparation energy efficiency based on the collaborative modification scheme, performing compensation analysis, and determining a compensation modification scheme; and based on the compensation modification scheme, performing process preparation of the carbon fluoride cathode material.

In another aspect of the present disclosure, there is provided a carbon fluoride cathode material preparation system for use in the above method, the system comprising: the working procedure point positioning module is used for reading the preparation process of the fluorocarbon anode material and positioning the modification working procedure point, and the modification working procedure point is marked with a node anode modification standard; the initial scheme calling module is used for calling an initial modification scheme set aiming at the modification procedure point by combining with the industrial Internet of things retrieval; the optimizing model generating module is used for axially building an optimizing space by taking the modification procedure point as an axial direction to generate a self-adaptive optimizing model; the scheme optimizing module is used for optimizing and detecting a single modification preparation scheme based on the initial modification scheme set by combining the self-adaptive optimizing model with high capacity, low cost and industrialization as optimizing constraint, and determining a plurality of single modification schemes corresponding to the modification procedure points; the association analysis module is used for executing subsequent procedure association influence analysis of the mapping modification procedure nodes aiming at the plurality of single modification schemes and determining a collaborative modification scheme; the compensation analysis module is used for predicting the material preparation energy efficiency based on the collaborative modification scheme and carrying out compensation analysis to determine a compensation modification scheme by combining with a performance prediction model; and the process preparation module is used for carrying out process preparation of the carbon fluoride anode material based on the compensation modification scheme.

One or more technical solutions provided in the present application have at least the following technical effects or advantages:

by establishing the self-adaptive optimizing model, the method realizes automatic searching and determination of the optimal modification scheme in the preparation process, thereby reducing the test times and cost in the preparation process and improving the efficiency; by introducing optimization constraints such as high capacity, low cost, industrialization and the like, the generated modification scheme is ensured to meet the actual application requirements, so that the cost is reduced under the condition of not sacrificing the performance; by executing the subsequent procedure association influence analysis, the synergistic effect of a plurality of single modification schemes is determined, so that the material performance is improved; by combining the performance prediction model, the preparation energy efficiency of the material based on the synergistic modification scheme can be predicted, and necessary compensation analysis is performed, which is helpful for more accurately preparing the high-performance material. In general, the method solves the problems of complexity and efficiency in the preparation of the traditional fluorocarbon cathode material through the steps of self-adaptive optimizing, optimizing constraint, cooperative modification, performance prediction and the like, so that the preparation process is more efficient and lower in cost, the industrialized requirement can be met, and the material performance is improved.

The foregoing description is only an overview of the technical solutions of the present application, and may be implemented according to the content of the specification in order to make the technical means of the present application more clearly understood, and in order to make the above-mentioned and other objects, features and advantages of the present application more clearly understood, the following detailed description of the present application will be given.

Drawings

Fig. 1 is a schematic flow chart of a method for preparing a carbon fluoride cathode material according to an embodiment of the present application;

fig. 2 is a schematic structural diagram of a preparation system of a fluorocarbon cathode material according to an embodiment of the present application.

Reference numerals illustrate: the system comprises a process point positioning module 10, an initial scheme calling module 20, a optimizing model generating module 30, a scheme optimizing module 40, a correlation analysis module 50, a compensation analysis module 60 and a process preparation module 70.

Detailed Description

The preparation method of the fluorocarbon cathode material solves the problems that the preparation of the traditional fluorocarbon cathode material generally involves a complex modification process, and multiple attempts and optimization are needed at different modification process points, so that the preparation process is time-consuming, labor-consuming and high in cost; and searching for the optimal modification scheme generally requires a large number of experiments and repeated attempts, and may not fully meet the requirements of high capacity, low cost, industrialization and the like, so that the traditional method has the technical problems of poor effect and low efficiency.

Having described the basic principles of the present application, various non-limiting embodiments of the present application will now be described in detail with reference to the accompanying drawings.

Example 1

As shown in fig. 1, an embodiment of the present application provides a method for preparing a fluorocarbon cathode material, the method comprising:

reading a preparation process of the carbon fluoride anode material, and positioning a modification procedure point, wherein the modification procedure point is marked with a node anode modification standard;

the preparation process information of the carbon fluoride cathode material is obtained from the existing preparation process file or database, wherein the preparation process information comprises the formula, the preparation steps, the preparation parameters and the like of raw materials, after the process information is read, the application record of the lithium carbon fluoride battery is called, the tracing is carried out according to the battery performance defects, the steps in the preparation process are determined to be optimized to improve the performance of the material, and the determined steps are the modification process points, and the modification process points are the process intervals. Positive electrode modification criteria, such as desired performance metrics, quality criteria, safety requirements, etc., are established for each process point based on the defect scale, which helps ensure that the modification process meets specific requirements.

In this way, a clear framework is established so that subsequent work can be purposefully improved for each modification process point to meet specific performance requirements and constraints.

Further, reading the preparation process of the carbon fluoride cathode material, positioning the modification procedure point, and comprising the following steps:

calling application records of the lithium fluorocarbon battery based on a preparation process of the carbon fluoride cathode material, and determining the performance defect of the battery;

screening target performance defects based on the cathode material based on the battery performance defects, tracing, and determining process nodes mapped to a preparation process of the carbon fluoride cathode material as the modification process points, wherein the modification process points are process intervals;

and determining a modification direction and a modification quantity value based on the defect scale of the target performance defect, and carrying out mapping identification of the modification process node.

Information about lithium fluorocarbon battery application records is retrieved from existing carbon fluoride cathode material preparation processes, wherein the records comprise materials of battery components, preparation processes, assembly methods, test data and the like, and the test data comprise charging and discharging data, temperature, current, voltage, cycle times and the like of the battery. The called battery application records are analyzed, and the defects of battery performance, including problems of capacity attenuation, service life, energy density and the like, are particularly focused on, so that the battery performance defects are obtained.

By analyzing the properties and characteristics of the battery performance defects, the target performance defects directly related to the positive electrode material, namely the performance defects caused by aiming at the positive electrode material, are screened out. According to the selected target performance defects, the root causes of the defects, including factors in the process, are traced back, the root causes of the target performance defects are mapped to specific process nodes of the preparation process of the fluorocarbon cathode material, which processes influence the occurrence of the performance defects in the preparation process are determined, the association between the target performance defects and the specific process nodes of the preparation process of the fluorocarbon cathode material is determined based on tracing results, the process nodes are identified and serve as modification process points, the modification process points are process intervals, and the process nodes are the key points of subsequent modification schemes so as to try to solve the target performance defects.

Detailed scale measurements are made for each target performance defect, including quantitative performance metrics such as percent capacity loss, number of cycles, internal resistance values, etc., which are used to quantify the extent of the defect. Determining a modification direction based on the measurement of the defect scale, the modification direction referring to which specific measures need to be taken to improve or repair the defect, for example, if the capacity loss is large, the modification direction involves increasing the capacity of the material or reducing the capacity loss; the amount of modification for each modification direction is determined, which refers to the specific degree of change or adjustment that needs to be made at the modification process node to achieve the modification direction.

Each modification process node is identified based on the determined modification direction and modification magnitude to indicate which modification direction and modification magnitude adjustments are required, which will help guide subsequent modification work.

Aiming at the modification procedure point, searching and calling an initial modification scheme set by combining with the industrial Internet of things;

real-time data and information related to the modification process points, including sensor data, production process monitoring data, material performance data and the like, are collected by utilizing the industrial Internet of things technology, and the industrial Internet of things can provide real-time and large-scale data, so that the change and the performance in the process can be known. After the industrial internet of things data is obtained, historical modification schemes are invoked, including past modification attempts, historical data, experimental results, and the like, which are methods and strategies that have been attempted to improve material preparation. And integrating data by combining industrial Internet of things data and historical modification schemes, analyzing the change and performance data in the process and the effect of the previous modification schemes, determining which schemes are helpful for improving the process points, and screening the modification schemes with positive effects to form an initial modification scheme set.

The purpose of this step is to provide targeted preliminary protocols and suggestions for optimizing specific modification process points, with the help of real-time data and past experience, and to provide data support for further optimizing these modification protocols subsequently.

Further, in addition to invoking the initial modification scheme set in combination with the industrial internet of things retrieval, the method further comprises the following steps:

determining doping atoms based on electrochemical performance impact, wherein the doping atoms include heteroatoms and modifying atoms;

analyzing the ratio distribution influence of the hetero atoms, and determining the hetero atom critical distribution ratio of the modified cathode material, wherein the hetero atom critical distribution ratio corresponds to the hetero atoms one by one;

analyzing the ratio distribution influence of the modified atoms, and determining the critical distribution ratio of the modified atoms of the modified anode material by taking the structural stability requirement as a reference;

a doping initial modification scheme is determined based on the heteroatom critical distribution ratio and the modified atom critical distribution ratio.

The electrochemical properties of the raw materials, including performance assessment in terms of electrode reaction kinetics, conductivity, ion diffusion properties, etc., are analyzed by experimental or computational methods to define target performance parameters, i.e., electrochemical properties that are desired to be improved by doping, including higher capacity, better charge-discharge efficiency, longer cycle life, etc. Identifying doping atoms, including heteroatoms and modifying atoms, based on electrochemical properties, wherein a heteroatom is an atom that negatively affects electrochemical properties, such as oxygen, nitrogen, and the like; the modifying atom is an atom that can improve the structural stability of the material, such as cobalt (Co) and the like.

Analysis of the effect of each doping atom on electrochemical performance by theoretical calculations, experimental studies, or literature reviews, etc., determines which doping atoms have the potential to improve the target performance parameters based on the analysis results, e.g., if the goal is to increase the capacity of the cell, increasing the proportion of those modifying atoms that positively affect the capacity, and decreasing those heteroatoms that negatively affect the capacity.

Specifically, the modification amount of each heteroatom, i.e., the proportion to be incorporated into the material, is determined, which involves determining the doping concentration or doping ratio, introducing selected heteroatoms into the material, including physical mixing, chemical reaction, deposition or ion implantation, and the like, performing experimental verification to obtain electrochemical properties of the positive electrode material at different heteroatom ratios, such as capacity, cycle life, energy density, and the like, and determining the degree of influence of different ratios on the properties by analysis. Based on the analysis result of the ratio distribution influence, the critical distribution ratio of the hetero atoms of each hetero atom is determined, which means that the optimal distribution ratio of the hetero atoms in the positive electrode material is realized to reduce the influence on the electrochemical performance to the greatest extent and reduce or avoid causing material defects. The critical distribution ratio of each heteroatom to the corresponding heteroatom is one-to-one, so that the doping proportion of each heteroatom is accurately controlled in the subsequent modification procedure, and the expected performance improvement is realized.

And analyzing the ratio distribution influence of the modified atoms by the same method, and then establishing an influence trend curve based on the modified atoms by taking the ratio distribution as a horizontal axis and the structural stability and the fixation loudness of the modified atoms as a vertical axis, wherein the modified atoms comprise at least one kind, the structural stability requirement is taken as a benchmark, the modification cost and the modification difficulty are taken as constraints, and the critical distribution ratio of the modified atoms is marked in the influence trend curve.

Determining the ideal distribution proportion of each heteroatom in the positive electrode material according to the determined heteroatom critical distribution ratio; and determining the ideal distribution proportion of each modified atom according to the determined critical distribution ratio of the modified atoms. The critical distribution ratio of the hetero atoms and the modified atoms is comprehensively analyzed, and the doping amounts of different atoms are weighed to realize the optimal performance improvement, so that a final doping initial modification scheme is determined, wherein the specific process comprises the specific process of doping procedures, including when and how to dope various atoms and the proportion of various atoms in the preparation process, so that the stability and consistency of the doping process are ensured.

Further, determining a modified atomic critical distribution ratio of the modified cathode material includes:

Establishing an influence trend curve based on modified atoms by taking ratio distribution as a horizontal axis and modified atom structure stability as a vertical axis, wherein the modified atoms comprise at least one kind;

marking the critical distribution ratio of the modified atoms in the influence trend curve by taking the structural stability requirement as a reference;

wherein, carry out the modification analysis based on the modified atom number, still include:

if the modified atoms are one type, curve nodes based on the structural stability requirement are positioned, and the ratio distribution is identified as the critical distribution ratio of the modified atoms;

and if the number of the modified atoms is multiple, carrying out modification balanced distribution by taking the modification cost and the modification difficulty as constraints and combining the influence trend curve, and determining the critical distribution ratio of the modified atoms.

And verifying the influence degree of each modified atomic ratio distribution on the structural stability of the cathode material through laboratory tests or simulation calculation, wherein the influence degree comprises calculation and analysis on the aspects of the crystal structure, the electronic structure and the like of modified atoms.

And connecting the structural stability influence degree of the modified atoms corresponding to different ratios of each modified atom through data visualization software by taking the structural stability influence degree of the modified atoms under different ratio distribution as a vertical axis value and taking the ratio distribution as a horizontal axis value, drawing an influence trend curve, wherein one modified atom corresponds to one curve, and drawing a plurality of influence trend curves correspondingly if a plurality of modified atoms exist.

By plotting the trend curve, the change trend of the structural stability of the modified atoms under different ratio distribution can be determined, which is helpful for understanding the influence degree of the modified atoms under different ratios and provides reference for the final modification scheme.

According to the requirement of the structural stability of the battery, the required structural stability standard comprising the required crystal structural stability, electronic structural stability and the like is determined, the change of the modified atomic structural stability fixing loudness under different ratios in the curve is analyzed by using the established influence trend curve, the point corresponding to the structural stability requirement on the curve is particularly focused, for example, a straight line parallel to a transverse axis is drawn by a value of a vertical coordinate corresponding to the structural stability requirement, the point intersected with the straight line on the curve is extracted, and the corresponding ratio distribution, namely the modified atomic critical distribution ratio, is determined, which is the key doping ratio meeting the structural stability requirement.

If the modifying atom includes only one kind, the corresponding node can be found directly on the curve based on the structural stability requirement to determine the ratio distribution as the critical distribution ratio of the modifying atom, for example, drawing a straight line parallel to the horizontal axis with the value of the ordinate corresponding to the structural stability requirement, extracting the point on the curve intersecting the straight line, and determining the corresponding ratio distribution, i.e., the critical distribution ratio of the modifying atom, which is the critical doping ratio satisfying the structural stability requirement.

If the modifying atoms include a plurality of modifying atoms, evaluation of modifying costs and modifying difficulties for each modifying atom, including raw material costs, complexity of production process, equipment requirements, etc., are taken into consideration to limit the number and distribution of modifying atoms.

And determining nodes within the structural stability requirement range by using an influence trend curve, wherein the nodes represent the performances of different ratio distribution under the structural stability requirement, determining the modification cost and modification difficulty corresponding to the distribution proportion of each modified atom by using a mathematical model, experimental verification and other methods, screening the determined performances of different ratio distribution with the aim of minimizing the modification cost and the modification difficulty, determining the distribution proportion of the final modified atom so as to meet the structural stability requirement, and taking the distribution proportion as the critical distribution proportion of the modified atom by considering the constraint of the cost and the difficulty.

Setting up a optimizing space by taking the modification procedure point as an axial direction, and generating a self-adaptive optimizing model;

the key stage centered on the modification process point is selected, and a multi-dimensional optimizing space is established on the basis of the modification process point, wherein the space contains various possible modification schemes, and each dimension represents a potential modification variable or parameter, such as an atomic doping ratio and the like, and the parameters can be adjusted to influence the performance of the material. For each dimension, based on actual conditions, historical data, experimental results and the like, a possible parameter range is determined, namely, in which range each parameter can be changed, so that the optimizing space is ensured to contain a practical and feasible modification scheme.

The self-adaptive optimizing model is a model constructed based on an optimizing algorithm, and the task of the model is to help determine an optimal modification scheme so as to optimize parameters of the preparation process. Specifically, data about existing modification schemes and experimental results are collected, the data comprise performance data under different parameter combinations, a proper optimizing algorithm is selected, the algorithm comprises a genetic algorithm, particle swarm optimization, simulated annealing, gradient descent and the like, the algorithm is used for searching an optimal modification scheme in an optimizing space, the collected data and a determined optimizing algorithm are used for training, an adaptive optimizing model is built, the basis of the obtained adaptive optimizing model is the optimizing algorithm, the optimizing algorithm is used for helping to determine the optimal modification scheme, and the efficiency of a preparation process is improved, so that the requirements of specific applications are met.

Carrying out single modification preparation scheme optimization and test detection based on the initial modification scheme set by combining the self-adaptive optimization model with high capacity, low cost and industrialization as optimization constraint, and determining a plurality of single modification schemes corresponding to the modification procedure points;

the constraints of optimizing are well defined, these conditions include high capacity, i.e. materials requiring high energy storage capacity to be produced; low cost, i.e. the modification scheme is required not to increase the excessive production cost; and industrialization, i.e. modification schemes need to be adapted to large-scale industrial production.

And carrying out traversal search on the initial modification scheme set under the optimization constraint condition by utilizing the generated self-adaptive optimization model, wherein the schemes comprise combinations of different parameters, conditions or material components, specifically, initializing initial values of the parameters according to an optimization algorithm, wherein the initial values are determined based on existing data or experience knowledge, searching potential modification schemes in an optimization space by the optimization algorithm based on the initial modification scheme set so as to find a parameter combination with the maximum performance improvement, evaluating the performances of the different parameter combinations according to the existing data and target performance parameters by the algorithm, and finally determining the optimal modification scheme, namely, the parameter combination found in the optimization space can bring the maximum performance improvement. Based on the predicted results of the model, one or more most promising modification schemes are selected, and the single modification parameters are selected to determine a plurality of single modification schemes corresponding to modification procedure points, wherein each scheme represents an improvement method or condition to meet the requirements of high capacity, low cost and industrialization.

Further, the determining a plurality of single modification schemes corresponding to the modification process point includes:

Setting a optimizing mechanism of the self-adaptive optimizing model, wherein the optimizing mechanism comprises a scheme optimizing amount and an optimizing range based on scheme fitness;

setting an adaptability function based on the optimizing constraint, and carrying out configuration of the self-adaptive optimizing model by combining the optimizing mechanism;

and traversing the initial modification scheme set to execute multi-step long iteration expansion and screening constraint based on scheme fitness by combining the self-adaptive optimizing model until convergence conditions are met, and selecting an optimal modification scheme of maximum fitness mapping as the plurality of single modification schemes.

The optimizing mechanism is used for guiding the process of searching the optimal modification scheme and comprises two key aspects, namely scheme optimizing quantity and optimizing range. The solution optimizing amount is an index for evaluating the fitness of different modification solutions, and this index is a numerical value, and may be determined according to the nature of a specific problem, for example, a comprehensive score of performance parameters such as battery capacity, charge-discharge efficiency, cycle life and the like, and the objective of this index is to help determine which modification solutions have more potential to achieve optimized performance. The optimizing range defines the variation range of each parameter when searching the optimal modifying scheme, and determines the optimizing space, such as the value range of the parameters of the concentration, the reaction time, the temperature and the like of the modifying atoms, and the range can be fixed or can be dynamically adjusted according to the feedback of real-time data and a model so as to accelerate the optimizing process.

The objective of the optimizing mechanism is to guide the adaptive optimizing model according to the value of the optimizing quantity of the scheme so as to make the adaptive optimizing model concentrate on the modified scheme with higher adaptability, and by continuously evaluating and comparing the adaptability of different schemes, the adaptive optimizing model can identify which schemes are more likely to realize the best performance and focus on the schemes, which is helpful to improve the efficiency and accuracy of the searching of the modified scheme so as to meet the optimizing constraint of high capacity, low cost, industrialization and the like.

Fitness functions are used to quantify and evaluate the fitness of each modification scheme, and the design of this fitness function is based on optimization constraints to ensure that the resulting modification scheme is viable in practical applications. The fitness function can be a mathematical formula, and a fitness score is calculated according to the scheme optimizing quantity and the optimizing constraint value, and the fitness function is designed so that the fitness score is in direct proportion to the performance and the conformity of the modification scheme.

When the self-adaptive optimizing model is configured, the designed fitness function is combined with an optimizing mechanism, and the fitness function is embedded into the optimizing mechanism so as to evaluate the fitness of the modification scheme in each optimizing iteration, and along with the iteration of the model, the design of the fitness function ensures that the model searches for the modification schemes with high fitness scores in a concentrated mode so as to meet optimizing constraint.

The configuration of the self-adaptive optimizing model is completed by designing the fitness function and combining with the optimizing mechanism, and the special constraint and the special requirement are considered when the model searches the optimal modifying scheme are ensured by the self-adaptive optimizing model, so that the self-adaptive optimizing model is beneficial to generating the optimal modifying scheme meeting the requirements of high capacity, low cost, industrialization and the like.

Starting from an initial set of modification schemes, which contains a series of possible modification schemes, in each iteration, new possible modification schemes are generated by adjusting certain parameters of existing schemes or employing new modification methods, according to the current scheme, wherein a multi-step length means that parameters can be altered by a plurality of larger or smaller steps during the iteration, which helps to explore the solution space more widely.

For each newly generated modification scheme, its fitness score is calculated using the previously defined fitness function, the scheme with higher fitness is screened out from the score, and the scheme with lower fitness is discarded.

After each iteration, it is checked whether predefined convergence conditions are met, which may be that a maximum number of iterations is reached, the adaptation score changes less than a certain threshold, etc. When the convergence condition is met, the iteration process is terminated in all iterations, the modification scheme with the highest fitness score is selected as the optimal modification scheme, and the plurality of single modification schemes are obtained, wherein the schemes represent the optimal selection after the self-adaptive optimization model screening.

Performing a subsequent process association impact analysis mapping the modification process nodes for the plurality of single modification schemes to determine a collaborative modification scheme;

for the plurality of single modification schemes, firstly, defining modification process nodes related to each modification scheme, and executing subsequent process association analysis on each modification process node to determine the influence of subsequent preparation steps on the modification process node.

Specifically, performance parameters are defined for evaluating the effects of the modification scheme, including battery capacity, charge-discharge efficiency, cycle life, safety, and the like. Collecting performance parameter data about each modification scheme and performance data of samples processed by subsequent steps, analyzing the data to determine the effect of subsequent steps on each modification scheme, and determining which individual modification schemes can cooperate to achieve better overall performance, e.g., selecting complementary schemes among different modification schemes to maximize performance, based on the results of the subsequent step-related effect analysis.

Experimental verification was performed for the synergistic modification schemes to ensure that they did achieve the desired performance improvement in the subsequent steps. By this procedure it is possible to determine which individual modification schemes have the best synergistic effect in the subsequent preparation steps, while ensuring that the processes do not negatively affect each other, thus achieving better overall performance.

Combining a performance prediction model, predicting the material preparation energy efficiency based on the collaborative modification scheme, performing compensation analysis, and determining a compensation modification scheme;

based on the historical data and experimental results, a performance prediction model is established, and the model can be a machine learning model, such as a neural network model, and is of a three-layer fully-connected network structure, and comprises a material analysis layer, a simulation test layer and a modification compensation layer, and is used for predicting the performance of materials, such as capacity, cycle life, energy density and the like.

Parameters and conditions of the collaborative modification scheme are input into a performance prediction model, a material performance prediction result is obtained through a material analysis layer, a discharge index measurement result is obtained through a simulation test layer, and the obtained material performance prediction result and the discharge index measurement result are analyzed to determine the influence on the material preparation energy efficiency, for example, the influence is compared with a preset standard or compared with an unmodified standard process, so that improvement or reduction of the energy efficiency of modification is known. If the synergistic modification scheme has a negative impact on the energy efficiency of the material preparation or does not meet the expected requirements, it is necessary to determine compensating modification schemes that aim to address problems or deficiencies that may be introduced by the synergistic modification scheme to ensure that the final material meets the performance and efficacy criteria.

The method realizes the energy efficiency of material preparation based on the collaborative modification scheme, and determines whether a compensation modification scheme is needed according to the performance prediction result so as to meet the required performance and efficiency requirements.

Further, predicting a material preparation energy efficiency based on the synergistic modification scheme includes:

the performance prediction model is of a three-layer fully-connected network structure and comprises a material analysis layer, a simulation test layer and a modified compensation layer;

performing material performance prediction on the collaborative modification scheme by combining the material analysis layer to determine a prediction result;

combining the simulation test layer to simulate the electrochemical environment of the carbon fluoride anode material, and performing discharge analysis and index determination to determine two prediction results;

and if any one of the one predicted result and the two predicted results does not meet the modification threshold standard, determining the compensation modification scheme by combining the modification compensation layer.

The material analysis layer is the first layer of the model and is used for receiving input material characteristics and parameters of a synergistic modification scheme, wherein the characteristics comprise chemical components, crystal structures, physical properties and the like of the material, and the layer performs preliminary analysis and processing on the input characteristics and performs material performance prediction; the simulation test layer is a second layer of the model and is responsible for receiving the processed characteristics from the material analysis layer and performing simulation, emulation or experimental test, and the simulated material of the layer can perform discharge analysis and index measurement in a specific electrochemical environment; the modified compensation layer is a third layer of the model, receives the output of the simulation test layer, wherein the output is the performance parameter obtained by simulation, and the modified compensation layer compensates the collaborative modification scheme according to the result of material performance prediction, and determines the compensation modification scheme so as to optimize the performance of the material.

The layers of the model are fully connected, the nodes in each layer are fully connected with the nodes of the previous layer, and the structure enables the model to effectively conduct modification compensation from the input material characteristics to the final performance prediction and simulation results according to the performance prediction and simulation results.

The material analysis layer is constructed based on a neural network, and the marked historical data is used as training data to train and optimize parameters of the material analysis layer, so that the material analysis layer can make accurate performance prediction by learning the relation between input characteristics and performance.

Providing a synergistic modification scheme as input to a trained material analysis layer, and predicting performance parameters of the material according to the modification atomic combination and doping proportion of the scheme by using a learned performance prediction method to obtain predicted material performance parameters, wherein the parameters represent expected performance of the material corresponding to the synergistic modification scheme and serve as a prediction result.

The simulation software is used for simulating the behavior of the carbon fluoride anode material in an electrochemical environment, including considering the factors of the battery, electrolyte, electrode materials and the like, so as to simulate the discharging process of the battery, recording relevant parameters such as current, voltage, charge state and the like, and simulating the performance change of the material in the discharging process through simulation analysis. Based on the results of the discharge analysis, various indexes of the carbon fluoride cathode material, such as discharge capacity, cycle life, electrochemical stability, etc., are determined, and these indexes provide detailed information about the material properties. And combining analysis and index measurement of the simulation test layer to obtain a predicted result related to the performance of the fluorocarbon cathode material, wherein the predicted result is used as two predicted results.

A modification threshold criteria is determined based on previous research or application requirements, which may be a minimum value of a performance parameter, a stability requirement, or other material property related condition, for evaluating the success or failure of a modification regimen. One and two predictors are evaluated to determine if they meet the modification threshold criteria, and if one or both predictors do not meet the modification threshold criteria, indicating that the current modification scheme fails to meet the performance requirements or electrochemical conditions, further adjustments are made with the modification compensation layer based on the unsatisfied predictors, e.g., trying different combinations of modification atoms, changing doping ratios, optimizing electrochemical conditions, etc.

Again, performance predictions and simulation tests are performed using the modified compensated scheme, which helps determine if the modified threshold criteria have been met by the modified compensation. If the modified and compensated scheme still cannot meet the threshold standard, iterating for a plurality of times, and continuously adjusting and optimizing the modified scheme until the performance requirement or the electrochemical condition is met. When a modification scheme meeting the modification threshold criteria is found, the scheme is selected as the final compensating modification scheme.

Further, simulating the electrochemical environment of the carbon fluoride cathode material, performing discharge analysis and index measurement, and determining two prediction results, wherein the method comprises the following steps:

based on the electrochemical environment, taking an electrochemical reaction formula as a reference, and carrying out discharge test and synchronous monitoring of the collaborative modification scheme;

monitoring the electrochemical state of the carbon fluoride anode material based on the synergistic modification scheme, and determining the phase state and the electrical performance index of the material as a static test result;

if the material phase state and the electrical performance index meet the modification threshold standard, performing cross-time-sequence trend state analysis to determine electrochemical stability, and taking the electrochemical stability as a dynamic test result;

and determining the two prediction results based on the static test result and the dynamic test result.

Determining electrochemical environment to be subjected to discharge test, including conditions of battery composition, electrolyte, temperature and the like, wherein the conditions can reflect the situation in practical application; the electrochemical reaction formula, i.e., the chemical reactions that occur during discharge, are determined, and these reactions include charge transfer between the positive and negative electrode materials, ion diffusion, and the like.

The collaborative modification schemes are provided as inputs to an electrochemical test system, including modified atomic combinations, doping ratios, etc., and are subjected to discharge testing in a defined electrochemical environment under laboratory conditions to simulate the discharge operation of the battery, while various parameters, such as current, voltage, temperature, ion concentration, etc., are monitored during the discharge testing process, which aids in understanding the performance and behavior of the battery.

Monitoring the electrochemical state of the carbon fluoride anode material by using a proper electrochemical instrument, wherein the electrochemical state monitoring comprises measuring a charge/discharge curve, a volt-ampere characteristic curve, a cyclic volt-ampere curve and the like, and analyzing the phase change of the carbon fluoride anode material, including the structural state, specific capacity, ionic compound state and the like of the material according to electrochemical state monitoring data; based on the electrochemical state monitoring data, electrical performance indicators, such as conductivity, kinetic performance, and the like, of the carbon fluoride cathode material are determined.

The measurement results of the phase and electrical performance indexes of the material are used as static test results, and the results provide information about the static performance and the electrochemical state of the carbon fluoride cathode material.

Comparing the obtained static test result with a preset modification threshold standard, determining the threshold standard according to the previous research or application requirement, evaluating whether the modification scheme is successful or not, performing cross-time sequence analysis on the material phase and electrical property indexes meeting the modification threshold standard under the condition that the material phase and electrical property indexes meet the modification threshold standard, continuously performing periodic discharge test on the fluorocarbon cathode material at the stage, continuously monitoring the change of the electrochemical environment, recording the data obtained in the dynamic test process, including discharge capacity, cycle number, charge-discharge efficiency and the like, performing statistical analysis on the recorded data, further evaluating the performance attenuation condition of the material in the long-time use or the cyclic charge-discharge process according to the result of the data analysis, and determining the electrochemical stability. The electrochemical stability evaluation result is recorded as a dynamic test result, and the record provides information of stability and durability of the material under time sequence pushing in the actual application process.

And comprehensively analyzing the static test result and the dynamic test result, determining the performance and stability of the collaborative modification scheme under the dynamic and static state, and determining two prediction results based on the comprehensive analysis result.

And based on the compensation modification scheme, performing process preparation of the carbon fluoride cathode material.

The resulting compensation modification scheme is applied to the process of preparing the carbon fluoride cathode material, including adjusting process steps, parameters, material composition, or other necessary modifications to ensure that the desired performance and performance criteria are met.

Further, performance evaluation is performed on the carbon fluoride anode material sample prepared according to the compensation modification scheme, and the degree of coincidence between the carbon fluoride anode material sample and an expected performance index is compared, so that whether further adjustment is needed in the preparation process or not is facilitated, and the preparation process is subjected to necessary adjustment according to the performance evaluation result, so that the performance of the material is further improved, and the requirement is met.

In summary, the preparation method of the fluorocarbon cathode material provided by the embodiment of the application has the following technical effects:

1. by establishing the self-adaptive optimizing model, the method realizes automatic searching and determination of the optimal modification scheme in the preparation process, thereby reducing the test times and cost in the preparation process and improving the efficiency;

2. By introducing optimization constraints such as high capacity, low cost, industrialization and the like, the generated modification scheme is ensured to meet the actual application requirements, so that the cost is reduced under the condition of not sacrificing the performance;

3. by executing the subsequent procedure association influence analysis, the synergistic effect of a plurality of single modification schemes is determined, so that the material performance is improved;

4. by combining the performance prediction model, the preparation energy efficiency of the material based on the synergistic modification scheme can be predicted, and necessary compensation analysis is performed, which is helpful for more accurately preparing the high-performance material.

In general, the method solves the problems of complexity and efficiency in the preparation of the traditional fluorocarbon cathode material through the steps of self-adaptive optimizing, optimizing constraint, cooperative modification, performance prediction and the like, so that the preparation process is more efficient and lower in cost, the industrialized requirement can be met, and the material performance is improved.

Example two

Based on the same inventive concept as one of the methods of preparing a carbon fluoride cathode material of the foregoing embodiments, as shown in fig. 2, the present application provides a carbon fluoride cathode material preparation system including:

the working procedure point positioning module 10 is used for reading the preparation process of the fluorocarbon anode material and positioning the modification working procedure point, and the modification working procedure point is marked with a node anode modification standard;

The initial scheme calling module 20 is used for calling an initial modification scheme set according to the modification procedure point and the industrial Internet of things;

the optimizing model generating module 30 is configured to build an optimizing space with the modifying procedure point as an axial direction, and generate an adaptive optimizing model;

a solution optimizing module 40, wherein the solution optimizing module 40 is configured to perform single modification preparation solution optimizing and test detection based on the initial modification solution set in combination with the adaptive optimizing model with high capacity, low cost and industrialization as optimizing constraint, and determine a plurality of single modification solutions corresponding to the modification procedure points;

a correlation analysis module 50, wherein the correlation analysis module 50 is configured to perform a subsequent process correlation effect analysis of the mapping modification process node for the plurality of single modification schemes, and determine a collaborative modification scheme;

the compensation analysis module 60 is used for predicting the material preparation energy efficiency based on the collaborative modification scheme and carrying out compensation analysis to determine a compensation modification scheme in combination with a performance prediction model by the compensation analysis module 60;

and a process preparation module 70, wherein the process preparation module 70 is used for performing process preparation of the carbon fluoride cathode material based on the compensation modification scheme.

Further, the system also comprises a modification procedure point positioning module for executing the following operation steps:

Further, the system also includes an initial modification scheme determination module to perform the following operational steps:

Further, the system also comprises a critical distribution ratio determining module for executing the following operation steps:

Further, the system also comprises a single item modification scheme acquisition module for executing the following operation steps:

Further, the system also includes a compensation modification scheme determination module to perform the following operational steps:

Further, the system further comprises two prediction result acquisition modules for executing the following operation steps:

From the foregoing detailed description of a method for preparing a fluorocarbon cathode material, it will be apparent to those skilled in the art that a system for preparing a fluorocarbon cathode material according to this embodiment is described more simply for the device disclosed in the examples, since it corresponds to the method disclosed in the examples, and the relevant points refer to the description of the method section.

The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for preparing a carbon fluoride cathode material, the method comprising:

based on the compensation modification scheme, performing process preparation of the carbon fluoride anode material;

wherein, reading the preparation process of the fluorocarbon cathode material, positioning the modification process point, the method comprises the following steps:

measuring a defect scale based on the target performance defect, determining a modification direction and a modification quantity value, and performing mapping identification of the modification process node;

wherein the determining a plurality of individual modification schemes corresponding to the modification process points comprises:

traversing the initial modification scheme set to execute multi-step long iteration expansion and screening constraint based on scheme fitness by combining the self-adaptive optimizing model until convergence conditions are met, and selecting an optimal modification scheme of maximum fitness mapping as the plurality of single modification schemes;

Wherein the material preparation energy efficiency based on the synergistic modification scheme is predicted, the method comprising:

2. The method of claim 1, wherein in addition to invoking the initial set of modification schemes in connection with industrial internet of things retrieval, the method comprises:

3. The method of claim 2, wherein a modified atomic critical distribution ratio of the modified cathode material is determined, the method comprising:

4. The method of claim 1, characterized in that the method comprises:

5. A system for preparing a carbon fluoride cathode material, for performing a method for preparing a carbon fluoride cathode material according to any one of claims 1 to 4, comprising:

the working procedure point positioning module is used for reading the preparation process of the fluorocarbon anode material and positioning the modification working procedure point, and the modification working procedure point is marked with a node anode modification standard;

the initial scheme calling module is used for calling an initial modification scheme set aiming at the modification procedure point by combining with the industrial Internet of things retrieval;

The optimizing model generating module is used for axially building an optimizing space by taking the modification procedure point as an axial direction to generate a self-adaptive optimizing model;

the scheme optimizing module is used for optimizing and detecting a single modification preparation scheme based on the initial modification scheme set by combining the self-adaptive optimizing model with high capacity, low cost and industrialization as optimizing constraint, and determining a plurality of single modification schemes corresponding to the modification procedure points;

the association analysis module is used for executing subsequent procedure association influence analysis of the mapping modification procedure nodes aiming at the plurality of single modification schemes and determining a collaborative modification scheme;

the compensation analysis module is used for predicting the material preparation energy efficiency based on the collaborative modification scheme and carrying out compensation analysis to determine a compensation modification scheme by combining with a performance prediction model;

the process preparation module is used for performing process preparation of the carbon fluoride anode material based on the compensation modification scheme;

the process point positioning module is modified to execute the following operation steps:

the single modification scheme acquisition module is used for executing the following operation steps:

the compensation modification scheme determining module is used for executing the following operation steps: