A method and apparatus for catalyst preparation based on chaotic perturbation

Abstract

The application discloses a catalyst preparation method and device based on chaotic disturbance, and relates to the field of metallurgical furnace gas reaction material preparation. The method comprises the following steps: preparing a metal salt solution system; adding a precipitant into the metal salt solution system for co-precipitation to obtain a catalyst precursor precipitate; performing aging treatment on the catalyst precursor precipitate to obtain catalyst precursor particles; performing drying treatment on the catalyst precursor particles to obtain dry precursor particles; and performing calcination treatment on the dry precursor particles to obtain catalyst particles. The chaotic process parameters obtained based on the chaotic disturbance method are used for regulation and control in the co-precipitation, aging, drying and calcination processes. The catalyst preparation method can promote the formation of a multi-stage pore structure in the particles and improve the catalyst performance.

Description

Technical Field

[0001] This application relates to the field of metallurgical furnace gas reaction material preparation, and in particular to a method and apparatus for preparing a catalyst based on chaotic perturbation. Background Technology

[0002] High-efficiency purification and resource utilization of metallurgical furnace gas is a key technological path to achieve energy conservation and emission reduction in the metallurgical industry. This technology uses catalysts to perform targeted catalytic conversion of carbon monoxide, hydrogen, tar, and various pollutants in the furnace gas, achieving the removal of harmful components and the recovery and utilization of valuable components. It has significant application prospects in reducing carbon emissions in metallurgical processes, improving the efficiency of secondary energy utilization, and reducing air pollutant emissions. As the core functional material in the catalytic conversion process of metallurgical furnace gas, the catalytic activity, selectivity, and operational stability of the catalyst largely determine the overall technological level of furnace gas purification efficiency and resource utilization.

[0003] Existing research indicates that catalyst performance is closely related to its microstructure, including the spatial dispersion of active components, hierarchical porous structure, and crystal phase structure. Among these, hierarchical porous structures and high active dispersion can significantly increase reactant migration rates and reaction interface area, thereby improving catalyst reaction efficiency and cycle stability. Therefore, controlling the microstructure of catalysts to enhance their overall performance has become an important direction in reactive materials research.

[0004] Currently, catalyst preparation methods mainly include mechanical mixing, impregnation, chemical coprecipitation, and sol-gel methods. These methods typically control the material composition and phase structure by adjusting process parameters such as solution concentration, pH value, precipitation temperature, and calcination temperature. However, in traditional preparation processes, these parameters are mostly controlled in a steady-state or monotonically changing manner, resulting in a homogeneous nucleation and growth process within the system and a relatively regular internal structure of the product particles. Given the complex composition, high dust content, and large tar content of metallurgical furnace gases, this traditional homogeneous structure has significant limitations: on the one hand, it is difficult to construct interconnected macropore-mesopore-micropore hierarchical channels within the particles, limiting the diffusion efficiency of reactants within the catalyst and making it difficult for large tar molecules to contact the active sites on the inner surface; on the other hand, improper control of local supersaturation can easily lead to the enrichment or agglomeration of active components on the outer surface of the particles, accelerating sintering and wear under high-temperature, dusty atmospheres, thus restricting the overall activity and operational stability of the catalyst.

[0005] In recent years, nonlinear dynamics studies have shown that chaotic perturbations possess high sensitivity, nonlinearity, and a wide spectral density, offering potential advantages in enhancing mass transfer and promoting multi-scale structure formation. If chaotic perturbations can be introduced into the material preparation process, and mass transfer and structural evolution during precipitation reactions, particle formation, and heat treatment are nonlinearly controlled, it is expected to achieve precise control of catalyst microstructure, thereby improving the material's reactivity and cycle stability. However, current technologies lack methods for introducing chaotic perturbations into catalyst preparation to regulate its microstructure. Therefore, developing a preparation method that utilizes chaotic perturbations to control catalyst microstructure is of great significance for improving catalyst performance and expanding its applications. Summary of the Invention

[0006] The purpose of this application is to provide a method and apparatus for preparing catalysts based on chaotic perturbations. This method utilizes chaotic perturbations to regulate the microstructure of the catalyst during preparation, promoting the formation of a hierarchical porous structure within the catalyst particles and improving catalyst performance. To achieve the above objective, this application provides the following solution: In a first aspect, this application provides a method for preparing a catalyst based on chaotic perturbation, comprising: Preparation of metal salt solution system; A precipitant is added to the metal salt solution system for co-precipitation to obtain a catalyst precursor precipitate. The co-precipitation process is controlled by chaotic co-precipitation process parameters obtained based on a chaotic perturbation method. The chaotic co-precipitation process parameters include the precipitant addition rate and the chaotic stirring speed. The catalyst precursor precipitate is aged to obtain catalyst precursor particles. The aging process is controlled by chaotic aging process parameters obtained based on the chaotic perturbation method. The chaotic aging process parameters include chaotic aging temperature and chaotic aging pH value. The catalyst precursor particles are dried to obtain dried precursor particles. The drying process is controlled by chaotic drying process parameters obtained based on the chaotic perturbation method. The chaotic drying process parameters include chaotic drying temperature. The dried precursor particles are calcined to obtain catalyst particles. The calcination process is controlled by chaotic calcination process parameters obtained by the chaotic perturbation method. The chaotic calcination process parameters include chaotic calcination temperature and chaotic calcination heating rate.

[0007] A precipitant is added to the metal salt solution system to perform co-precipitation, resulting in a catalyst precursor precipitate. The co-precipitation process is controlled using chaotic co-precipitation process parameters obtained based on a chaotic perturbation method, specifically including: The co-precipitation process is divided into multiple precipitation control time periods by equal time intervals; Based on a preset first initial chaotic mapping value and a chaotic mapping model, the chaotic mapping value for each sedimentation control time period is obtained respectively; the chaotic mapping model includes at least one of Logistic mapping, Tent mapping or Chebyshev mapping; The chaotic precipitant addition rate for each precipitation control period is determined based on the chaotic mapping value and the preset precipitant baseline addition rate for each precipitation control period. The chaotic stirring speed for each sedimentation control time period is determined based on the chaotic mapping value and the preset benchmark stirring speed for each sedimentation control time period. During each precipitation control period, a precipitant is added to the metal salt solution system at the chaotic precipitant addition rate corresponding to each precipitation control period, and the mixture is stirred according to the chaotic stirring speed corresponding to each precipitation control period. After the co-precipitation process is completed, the catalyst precursor precipitate is obtained.

[0008] The formula for calculating the addition rate of the chaotic precipitant is: ; The formula for calculating the chaotic stirring speed is: ; in, x i For the first i The chaotic mapping value of a sedimentation control period. v i For the first i The rate of addition of the precipitant during a specific precipitation control period. v 0 The preset precipitant addition rate, n i For the first i The chaotic stirring speed during the sedimentation control period. n 0 This is the preset baseline stirring speed.

[0009] The catalyst precursor precipitate is aged to obtain catalyst precursor particles. The aging process is controlled using chaotic aging process parameters obtained based on a chaotic perturbation method, specifically including: The aging process is divided into equal time intervals to obtain multiple aging control time periods; Based on the preset second initial chaotic mapping value and chaotic mapping model, the chaotic mapping value for each aging control time period is obtained respectively; The chaotic aging temperature for each aging control period is determined based on the chaotic mapping value and the preset baseline aging temperature for each aging control period. The chaotic aging pH value for each aging control period is determined based on the chaotic mapping value and the preset reference pH value for each aging control period. During each aging control period, the catalyst precursor precipitate is aged using the chaotic aging temperature and chaotic aging pH value corresponding to each aging control period. After the aging process is completed, the catalyst precursor particles are obtained.

[0010] The formula for calculating the chaotic aging temperature is: ; The formula for calculating the pH value during chaotic aging is: ; in, y i For the first i The chaotic mapping value of a time period under aging control. T i For the first i The chaotic aging temperature for a specific aging period. T 0 The preset baseline aging temperature, k This is the aging temperature adjustment coefficient. q i For the first i The pH value of chaotic aging during a specific aging control period. q 0 This is the preset reference pH value.

[0011] The catalyst precursor particles are dried to obtain dried precursor particles. The drying process is controlled using chaotic drying process parameters obtained based on a chaotic perturbation method, specifically including: The drying process is divided into multiple drying control time periods by equal time intervals; Based on the preset third chaotic mapping value and chaotic mapping model, the chaotic mapping value for each drying control time period is obtained respectively; The chaotic drying temperature for each drying control period is determined based on the chaotic mapping value and the preset baseline drying temperature for each drying control period. During each drying control period, the catalyst precursor particles are dried using the chaotic drying temperature corresponding to each drying control period. After the drying process is completed, the dried precursor particles are obtained.

[0012] The formula for calculating the chaotic drying temperature is: ; in, z i For the first i Chaotic mapping values ​​for a drying control periodT d,i For the first i Chaotic drying temperature for a controlled drying period T d The preset reference drying temperature, α This is the drying temperature adjustment coefficient.

[0013] The dried precursor particles are calcined to obtain catalyst particles. The calcination process is controlled using chaotic calcination process parameters obtained based on a chaotic perturbation method, specifically including: The calcination process is divided into multiple calcination control time periods by equal time intervals. Based on the preset fourth chaotic mapping value and chaotic mapping model, the chaotic mapping value for each calcination control time period is obtained respectively. The chaotic calcination temperature for each calcination control time period is determined based on the chaotic mapping value and the preset benchmark calcination temperature for each calcination control time period. The chaotic calcination heating rate for each calcination control time period is determined based on the chaotic mapping value and the preset reference heating rate for each calcination control time period. During each calcination control period, the dried precursor particles are calcined using the chaotic calcination temperature and the chaotic calcination heating rate corresponding to each calcination control period. After the calcination process is completed, the catalyst particles are obtained.

[0014] The formula for calculating the chaotic calcination temperature is as follows: ; The formula for calculating the heating rate of chaotic calcination is: ; in, o i For the first i Chaotic mapping values ​​for a calcination control time period T c,i For the first i The chaotic calcination temperature during a specific calcination control period. T c The preset reference calcination temperature, β This is the calcination temperature adjustment coefficient. For the first i Chaotic mapping values ​​for a calcination control time period For the first i The chaotic calcination heating rate during a calcination control period The preset baseline calcination heating rate, This is the coefficient for adjusting the calcination heating rate.

[0015] Secondly, this application provides a catalyst preparation apparatus based on chaotic perturbation, comprising: The process parameter calculation module is used to calculate the process parameters for chaotic coprecipitation, chaotic aging, chaotic drying, and chaotic calcination. The chaotic coprecipitation process parameters include the precipitant addition rate and the chaotic stirring speed; the chaotic aging process parameters include the chaotic aging temperature and the chaotic aging pH value; the chaotic drying process parameters include the chaotic drying temperature; and the chaotic calcination process parameters include the chaotic calcination temperature and the chaotic calcination heating rate. The control module, connected to the process parameter calculation module, is used to generate a first feed pump control signal based on the precipitant addition rate, a second feed pump control signal based on the chaotic aging pH value, a stirring motor control signal based on the chaotic stirring speed, a first heating device control signal based on the chaotic aging temperature, a second heating device control signal based on the chaotic drying temperature, a third heating device control signal based on the chaotic calcination temperature, and a fourth heating device control signal based on the chaotic calcination heating rate. A feed pump, connected to the control module and the reaction device, is used to add reaction materials to the reaction device according to the first feed pump control signal and the second feed pump control signal; A stirring motor, connected to the control module and the reaction device, is used to stir the solution in the reaction device according to the stirring motor control signal; A heating device, connected to the control module and the reaction device, is used to heat the reaction device according to a first heating device control signal, a second heating device control signal, a third heating device control signal, and a fourth heating device control signal; A reaction apparatus used for catalyst preparation.

[0016] According to the specific embodiments provided in this application, the following technical effects are disclosed: This application provides a method and apparatus for catalyst preparation based on chaotic perturbation. The method includes: preparing a metal salt solution system; adding a precipitant to the metal salt solution system for co-precipitation to obtain a catalyst precursor precipitate; aging the catalyst precursor precipitate to obtain catalyst precursor particles; drying the catalyst precursor particles to obtain dried precursor particles; and calcining the dried precursor particles to obtain catalyst particles. Chaotic process parameters obtained based on chaotic perturbation are used to control the co-precipitation, aging, drying, and calcination processes. This application introduces chaotic perturbation into the catalyst preparation process to dynamically control key steps such as co-precipitation, aging, drying, and calcination, causing the nucleation, growth, and structural evolution processes in the reaction system to exhibit nonlinear changes. This promotes the formation of a hierarchical porous structure within the particles, significantly increasing the specific surface area and the number of reaction interfaces of the catalyst, thereby improving catalyst performance. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of the steps in a catalyst preparation method based on chaotic perturbation in one embodiment of this application.

[0019] Figure 2 This is a schematic diagram of a catalyst preparation device based on chaotic perturbation in one embodiment of this application.

[0020] Figure 3 This is a schematic diagram of another catalyst preparation device based on chaotic perturbation in one embodiment of this application.

[0021] Figure 4 The image provided is a scanning electron microscope (SEM) image of the surface morphology before and after chaotic perturbation control in one embodiment of the application.

[0022] Figure label: Appendix Figure 2 In the middle: 1-chaotic mapping calculation module, 2-process parameter calculation module, 3-control module, 4-feed pump, 5-stirring motor, 6-heating device, and 7-reaction device.

[0023] Appendix Figure 3 In the middle: 1-raw material solution storage tank, 2-precipitant storage tank, 3-feeding pump, 4-reaction vessel, 5-stirring motor, 6-temperature sensor, 7-filtration device, 8-drying device, 9-muffle furnace and 10-catalyst particulate material.

[0024] Appendix Figure 4 In the middle: (a) - Surface morphology of the catalyst before chaotic perturbation regulation, (b) - Surface morphology of the catalyst after chaotic perturbation regulation. Detailed Implementation

[0025] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0026] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0027] To address the limitations of existing catalysts in treating metallurgical furnace gases containing dust, tar, and complex poisons (such as sulfur and chlorine), including limited microstructure control, easy pore blockage, and agglomeration and deactivation of active components due to high-temperature atmospheres, this invention provides a catalyst preparation method based on chaotic perturbation. By introducing nonlinear chaotic perturbation during catalyst formation, the nucleation, growth, and structural evolution processes of the material are dynamically controlled, thereby constructing a catalyst with a hierarchical porous structure and highly dispersed active components, improving its catalytic activity, resistance to carbon deposition, and long-term operational stability.

[0028] like Figure 1 As shown in the embodiments of this application, a catalyst preparation method based on chaotic perturbation is provided, including: a raw material solution preparation step S1, a chaotic perturbation co-precipitation step S2, a chaotic perturbation aging step S3, a chaotic perturbation drying step S4, and a chaotic perturbation calcination step S5. Specifically, as follows: S1, Obtain the active metal salt raw material and precursor raw material required for catalyst preparation; Dissolve the active metal salt raw material and the precursor raw material in a solvent according to a set ratio to form a metal salt precursor solution; Stir or disperse the metal salt precursor solution to make the active metal salt raw material and the precursor raw material uniformly distributed in the solution, thereby obtaining a uniform metal salt solution system for subsequent precipitation reaction.

[0029] S2, a precipitant is added to the metal salt solution system for co-precipitation to obtain a catalyst precursor precipitate. The co-precipitation process is controlled using chaotic co-precipitation process parameters obtained based on a chaotic perturbation method. These parameters include the precipitant addition rate and the chaotic stirring speed. A chaotic control sequence is generated through chaotic mapping, and the precipitant addition rate and the stirring speed of the reaction system are dynamically adjusted according to this sequence. This allows the co-precipitation reaction to proceed under nonlinear perturbation conditions, thereby generating the catalyst precursor precipitate and achieving a nonlinear precipitation formation process for the catalyst precursor.

[0030] S3, the catalyst precursor precipitate is aged to obtain catalyst precursor particles. The aging process is controlled using chaotic aging process parameters obtained based on a chaotic perturbation method. These chaotic aging process parameters include chaotic aging temperature and chaotic aging pH value. By aging the catalyst precursor precipitate and controlling the temperature and pH conditions during the aging process through chaotic mapping, the precipitate particles undergo structural rearrangement and particle growth in a nonlinear environment, thereby forming catalyst precursor particles with stable structural characteristics.

[0031] S4, the catalyst precursor particles are dried to obtain dried precursor particles. The drying process is controlled using chaotic drying process parameters obtained based on a chaotic perturbation method; the chaotic drying process parameters include chaotic drying temperature. The catalyst precursor particles are dried, and the temperature change during the drying process is controlled by chaotic mapping, causing the solvent inside the particles to gradually evaporate and promoting the formation of internal pore structures under nonlinear thermal perturbation conditions.

[0032] S5, the dried precursor particles are calcined to obtain catalyst particles. The calcination process is controlled using chaotic calcination process parameters obtained based on a chaotic perturbation method. These chaotic calcination process parameters include chaotic calcination temperature and chaotic calcination heating rate. The dried catalyst precursor particles are calcined, and the temperature and heating rate during the calcination process are controlled by chaotic mapping, causing the precursor particles to undergo a phase transformation and form a stable structure under a nonlinear thermal environment, thereby obtaining the catalyst material.

[0033] In step S1, optionally, the active metal salt raw material includes at least one of the following: iron salt, copper salt, nickel salt, manganese salt, or cobalt salt. For sulfur-containing metallurgical furnace gas, an iron-based or molybdenum-based system is preferred; for high-temperature furnace gas rich in tar, a nickel-based system is preferred.

[0034] Optionally, the active metal salt raw material specifically includes at least one of the following: ferric nitrate, copper nitrate, nickel nitrate, manganese nitrate, or cobalt nitrate.

[0035] Optionally, the carrier precursor raw material includes at least one of the following: alumina precursor, silicon dioxide precursor, zirconium oxide precursor or titanium oxide precursor.

[0036] Optionally, the solvent includes water or a mixture of water and an organic solvent. Optionally, the stirring or dispersion treatment includes at least one of mechanical stirring, magnetic stirring, or ultrasonic dispersion.

[0037] Step S2 involves adding a precipitant to the metal salt solution system for co-precipitation to obtain a catalyst precursor precipitate. The co-precipitation process is controlled using chaotic co-precipitation process parameters obtained based on a chaotic perturbation method, specifically including: The co-precipitation process is divided into equal time intervals to obtain multiple precipitation control time periods.

[0038] Based on the preset initial chaotic mapping value and chaotic mapping model, the chaotic mapping value for each sedimentation control time period is obtained.

[0039] The chaotic precipitant addition rate for each precipitation control period is determined based on the chaotic mapping value and the preset precipitant baseline addition rate for each precipitation control period.

[0040] The chaotic stirring speed for each sedimentation control time period is determined based on the chaotic mapping value and the preset benchmark stirring speed for each sedimentation control time period.

[0041] During each precipitation control period, a precipitant is added to the metal salt solution system at the chaotic precipitant addition rate corresponding to each precipitation control period, and the mixture is stirred according to the chaotic stirring speed corresponding to each precipitation control period. After the co-precipitation process is completed, the catalyst precursor precipitate is obtained.

[0042] In step S2, optionally, the precipitant includes at least one of the following: sodium hydroxide solution, ammonia water, or sodium carbonate solution.

[0043] Optionally, the chaotic precipitant addition rate is determined by the following relationship: chaotic precipitant addition rate = baseline addition rate × chaotic mapping value.

[0044] Optionally, the chaotic stirring speed is determined by the following relationship: chaotic stirring speed = reference stirring speed × chaotic mapping value.

[0045] Optionally, the chaotic mapping model includes at least one or a combination of the following: Logistic mapping, Tent mapping, or Chebyshev mapping.

[0046] In step S2, preferably, the formula for calculating the addition rate of the chaotic precipitant is: ; The formula for calculating the chaotic stirring speed is: ; in, x i For the first i The chaotic mapping value of a sedimentation control period. v i For the first i The rate of addition of the precipitant during a specific precipitation control period. v 0 The preset precipitant addition rate, n i For the first i The chaotic stirring speed during the sedimentation control period. n 0 This is the preset baseline stirring speed.

[0047] Step S3 involves aging the catalyst precursor precipitate to obtain catalyst precursor particles. The aging process is controlled using chaotic aging process parameters obtained based on a chaotic perturbation method. Specifically, this includes: The aging process is divided into equal time intervals to obtain multiple aging control time periods.

[0048] Based on the preset second initial chaotic mapping value and chaotic mapping model, the chaotic mapping value for each aging control time period is obtained.

[0049] The chaotic aging temperature for each aging control period is determined based on the chaotic mapping value and the preset baseline aging temperature for each aging control period.

[0050] The chaotic aging pH value for each aging control period is determined based on the chaotic mapping value and the preset reference pH value for each aging control period.

[0051] During each aging control period, the catalyst precursor precipitate is aged using the chaotic aging temperature and chaotic aging pH value corresponding to each aging control period. After the aging process is completed, the catalyst precursor particles are obtained.

[0052] In step S3, preferably, the formula for calculating the chaotic aging temperature is: .

[0053] The formula for calculating the pH value during chaotic aging is: .

[0054] in, y i For the first i The chaotic mapping value of a time period under aging control. T iFor the first i The chaotic aging temperature for a specific aging period. T 0 The preset baseline aging temperature, k This is the aging temperature adjustment coefficient. q i For the first i The pH value of chaotic aging during a specific aging control period. q 0 This is the preset reference pH value.

[0055] In step S3, optionally, the chaotic aging temperature is determined by the following relationship: chaotic aging temperature = reference aging temperature × chaotic mapping value.

[0056] Optionally, the chaotic aging pH value is determined by the following relationship: chaotic aging pH value = reference pH value × chaotic mapping value.

[0057] Optionally, the aging process can be carried out over a period of 1 to 24 hours.

[0058] Optionally, the aging temperature range is 40°C to 120°C.

[0059] Optionally, the chaotic mapping model includes at least one or a combination of the following: Logistic mapping, Tent mapping, or Chebyshev mapping.

[0060] Step S4 involves drying the catalyst precursor particles to obtain dried precursor particles. The drying process is controlled using chaotic drying process parameters obtained based on a chaotic perturbation method. Specifically, this includes: The drying process is divided into equal time intervals to obtain multiple drying control time periods.

[0061] Based on the preset third chaotic mapping value and chaotic mapping model, the chaotic mapping value for each drying control time period is obtained.

[0062] The chaotic drying temperature for each drying control period is determined based on the chaotic mapping value and the preset baseline drying temperature for each drying control period.

[0063] During each drying control period, the catalyst precursor particles are dried using the chaotic drying temperature corresponding to each drying control period. After the drying process is completed, the dried precursor particles are obtained.

[0064] In step S4, preferably, the formula for calculating the chaotic drying temperature is: .

[0065] in, z iFor the first i Chaotic mapping values ​​for a drying control period T d,i For the first i Chaotic drying temperature for a controlled drying period T d The preset reference drying temperature, α This is the drying temperature adjustment coefficient.

[0066] In step S4, optionally, the chaotic drying temperature is determined by the following relationship: chaotic drying temperature = reference drying temperature × chaotic mapping value.

[0067] Optionally, the temperature range for the drying process is 60°C to 150°C.

[0068] Optionally, the drying process can be performed for 2 to 24 hours.

[0069] Optionally, the drying method includes at least one of the following: forced air drying, vacuum drying, or microwave drying.

[0070] Optionally, the chaotic mapping model includes at least one or a combination of the following: Logistic mapping, Tent mapping, or Chebyshev mapping.

[0071] Step S5 involves calcining the dried precursor particles to obtain catalyst particles. The calcination process is controlled using chaotic calcination process parameters obtained based on a chaotic perturbation method. Specifically, this includes: The calcination process is divided into equal time intervals to obtain multiple calcination control time periods.

[0072] Based on the preset fourth chaotic mapping value and chaotic mapping model, the chaotic mapping value for each calcination control time period is obtained.

[0073] The chaotic calcination temperature for each calcination control period is determined based on the chaotic mapping value and the preset benchmark calcination temperature for each calcination control period.

[0074] The chaotic calcination heating rate for each calcination control time period is determined based on the chaotic mapping value and the preset baseline heating rate for each calcination control time period.

[0075] During each calcination control period, the dried precursor particles are calcined using the chaotic calcination temperature and the chaotic calcination heating rate corresponding to each calcination control period. After the calcination process is completed, the catalyst particles are obtained.

[0076] In step S5, preferably, the formula for calculating the chaotic calcination temperature is: .

[0077] The formula for calculating the heating rate of chaotic calcination is: ; in, o i For the first i Chaotic mapping values ​​for a calcination control time period T c,i For the first i The chaotic calcination temperature during a specific calcination control period. T c The preset reference calcination temperature, β This is the calcination temperature adjustment coefficient. For the first i Chaotic mapping values ​​for a calcination control time period For the first i The chaotic calcination heating rate during a calcination control period The preset baseline calcination heating rate, This is the coefficient for adjusting the calcination heating rate.

[0078] In step S5, optionally, the chaotic calcination temperature is determined by the following relationship: chaotic calcination temperature = reference calcination temperature × chaotic mapping value.

[0079] Optionally, the chaotic heating rate is determined by the following relationship: chaotic heating rate = reference heating rate × chaotic mapping value.

[0080] Optionally, the calcination treatment temperature range is 500°C to 1000°C.

[0081] Optionally, the calcination treatment time ranges from 2 hours to 10 hours.

[0082] Optionally, the calcination atmosphere includes at least one of the following: an air atmosphere, an oxygen atmosphere, or an inert atmosphere.

[0083] Optionally, the chaotic mapping model includes at least one or a combination of the following: Logistic mapping, Tent mapping, or Chebyshev mapping.

[0084] like Figure 2 As shown, based on the same inventive concept, this application also provides a catalyst preparation apparatus based on chaotic perturbation, comprising: Process parameter calculation module 2 is used to calculate the process parameters of chaotic coprecipitation, chaotic aging, chaotic drying, and chaotic calcination. The chaotic coprecipitation process parameters include the precipitant addition rate and the chaotic stirring speed; the chaotic aging process parameters include the chaotic aging temperature and the chaotic aging pH value; the chaotic drying process parameters include the chaotic drying temperature; and the chaotic calcination process parameters include the chaotic calcination temperature and the chaotic calcination heating rate.

[0085] Control module 3, connected to the process parameter calculation module, is used to generate a first feed pump control signal based on the precipitant addition rate, a second feed pump control signal based on the chaotic aging pH value, a stirring motor control signal based on the chaotic stirring speed, a first heating device control signal based on the chaotic aging temperature, a second heating device control signal based on the chaotic drying temperature, a third heating device control signal based on the chaotic calcination temperature, and a fourth heating device control signal based on the chaotic calcination heating rate.

[0086] Feed pump 4 is connected to the control module and the reaction device, and is used to add reaction materials to the reaction device according to the first feed pump control signal and the second feed pump control signal.

[0087] The stirring motor 5 is connected to the control module and the reaction device, and is used to stir the solution in the reaction device according to the stirring motor control signal.

[0088] Heating device 6 is connected to the control module and the reaction device, and is used to heat the reaction device according to the first heating device control signal, the second heating device control signal, the third heating device control signal and the fourth heating device control signal.

[0089] Reaction apparatus 7 is used for catalyst preparation.

[0090] In one embodiment of this application, the catalyst preparation apparatus based on chaotic perturbation further includes a chaotic mapping calculation module 1 for generating chaotic mapping values.

[0091] As a preferred implementation, the equipment operating status parameters are acquired within the current process control time period, and a PID control algorithm is used to ensure that the actual operating parameters of the reaction equipment are consistent with the calculated chaotic process control parameters, thereby achieving precise control of the catalyst preparation process.

[0092] like Figure 3As shown, this application provides another catalyst preparation device based on chaotic perturbation. The raw material solution storage tank 1 and the precipitant storage tank 2 are respectively connected to the reaction vessel 4 through pipelines. The precipitant storage tank 2 is controlled by the feed pump 3 to control the precipitant addition rate. The reaction vessel 4 is equipped with a stirring device and connected to the stirring motor 5 to realize the stirring and mixing of the reaction system. The temperature sensor 6 is used to monitor the reaction temperature in real time. The output end of the reaction vessel 4 is connected in sequence to the filter device 7, the drying device 8 and the muffle furnace 9 to complete the filtration, drying and calcination treatment of the catalyst precursor, thereby obtaining the catalyst particulate material 10.

[0093] This application uses Fe2O3 / Al2O3 catalyst material as an example for specific illustration. This method is applied to the preparation method of catalyst microstructure controlled by chaotic perturbation described in Example 1, and includes the following steps: Step 10: Preparation of raw material solution; Weigh a certain amount of ferric nitrate (Fe(NO3)3). 9H2O) and aluminum nitrate (Al(NO3)3) Fe (9H₂O) is used as the active metal salt and carrier precursor, and mixed according to a set molar ratio. In this embodiment, the molar ratio of Fe to Al is 60:40. The metal salt is dissolved in deionized water and mechanically stirred to ensure complete dissolution, forming a homogeneous and stable metal salt precursor solution.

[0094] In this embodiment, the total concentration of the metal salt solution is 1 mol / L-2 mol / L. The solution is kept homogeneous by continuous stirring to serve as the raw material solution for the subsequent coprecipitation reaction.

[0095] Step 20: Chaotic perturbation coprecipitation; A precipitant is added to the metal salt precursor solution obtained in step 10 to carry out a coprecipitation reaction. The precipitant is ammonia or sodium carbonate solution.

[0096] During the co-precipitation process, chaotic sequence values ​​are generated using a chaotic mapping model. The addition rate of the precipitant and the stirring speed of the reaction system are dynamically controlled by the chaotic sequence value, so that the precipitation reaction is carried out under nonlinear perturbation conditions.

[0097] Specifically, the precipitant addition rate is determined by the following relationship: .

[0098] in: This represents the rate at which the precipitant is added during the current time period. As a reference addition rate; This is a chaotic mapping value.

[0099] Meanwhile, the stirring speed of the reaction system is determined by the following relationship: .

[0100] in: This represents the stirring speed for the current time period. The reference stirring speed is [value].

[0101] By using the aforementioned chaotic perturbation control method, the nucleation and particle growth processes in the reaction system are carried out under nonlinear conditions, thereby obtaining catalyst precursor precipitates with more uniform particle size distribution.

[0102] Step 30: Chaotic perturbation aging: The precipitate obtained in step 20 is aged to promote particle structure stability and crystal structure rearrangement.

[0103] In this embodiment, the aging process is carried out at a temperature of 60-80℃ for 3-6 hours. During the aging process, the aging temperature is controlled over time using chaotic mapping, and the relationship is as follows: .

[0104] in: This refers to the aging temperature for the current time period. The reference aging temperature; This is the temperature regulation coefficient; This is a chaotic mapping value.

[0105] .

[0106] in: The pH value for aging during the current time period; The pH value is used as a reference for aging. This represents the chaotic mapping value. The chaotic precipitation temperature and chaotic aging pH disturbances promote the rearrangement of the internal structure of the particles, resulting in a more stable microstructure in the catalyst precursor.

[0107] Step 40: Drying treatment; The catalyst precursor precipitate obtained in step 30 is filtered and washed to remove residual ionic impurities, and then dried. In this embodiment, the drying temperature is 100℃-120℃, and the drying time is 10-12 hours. During the drying process, the slight fluctuation of the drying temperature can be controlled by chaotic mapping, allowing the internal moisture of the particles to gradually evaporate, thereby promoting the formation of a porous structure.

[0108] Step 50: Chaotic perturbation calcination; The dried catalyst precursor particles are placed in a muffle furnace for calcination. In this embodiment, the calcination temperature is 800℃-900℃, and the holding time is 3-4 hours.

[0109] During the calcination process, a chaotic temperature control sequence is generated using a chaotic mapping model. This sequence is then used to dynamically regulate the heating rate and stage temperatures, enabling the precursor particles to undergo a phase transformation under a nonlinear thermal environment. This chaotic perturbation-based calcination method promotes uniform grain growth and the formation of catalyst materials with hierarchical porous structures.

[0110] After the above steps, Fe2O3 / Al2O3 catalyst particles are obtained.

[0111] The obtained catalyst particles have good structural stability and high oxygen transfer capacity, making them suitable for combustion and hydrogen production processes.

[0112] Further explanation: In this embodiment, the chaotic sequence It is generated through one or a combination of Logistic, Tent, and Chebyshev chaotic mappings, where the basic form of Logistic is: .

[0113] in: The values ​​are from a chaotic mapping sequence. For chaotic process control parameters, when The system is in a chaotic state.

[0114] The control sequence generated by the above chaotic mapping is used to dynamically regulate key process parameters such as feeding, stirring, and temperature in the catalyst preparation process, thereby achieving nonlinear regulation of the material microstructure formation process.

[0115] Furthermore, the chaotic perturbation preparation method described in this invention is not only applicable to Fe2O3 / Al2O3 catalyst materials, but can also be applied to the preparation process of active metal oxide catalyst materials such as CuO, NiO, and MnO.

[0116] This application obtains the chaotic mapping value corresponding to the current process control time period and calculates the chaotic process control parameters corresponding to the current process control time period by combining it with the set process reference parameters. Based on the chaotic process control parameters, key process parameters in the catalyst preparation process are dynamically adjusted. By continuously updating the chaotic process control parameters throughout the preparation process, nonlinear dynamic adjustment of reaction conditions is achieved, thereby inducing the formation of a complex mass transfer and nucleation environment in the reaction system and promoting the optimized control of the catalyst microstructure. This application can effectively improve the uniformity of catalyst particle structure, enhance the catalyst's reactivity and cycle stability, and provide a new technical approach for the controllable preparation of reaction catalyst materials.

[0117] like Figure 4As shown, this application provides scanning electron microscopy (SEM) results of the catalyst surface morphology before and after chaotic perturbation regulation. Comparing the catalyst surface morphology before (a) and after (b) chaotic perturbation regulation, it can be seen that the catalyst before regulation exhibits a dense, blocky or spherical aggregate with a rough particle surface, scarce internal pores, and a low specific surface area. However, the catalyst after chaotic perturbation regulation as described in this application shows a significant reconstruction of its particle morphology, with a noticeably smoothed surface and the formation of interconnected and uniformly distributed hierarchical channels. This morphological difference directly leads to a more than 15% increase in reaction efficiency and a significant increase in mesopore volume after chaotic perturbation regulation compared to before, confirming the directional construction and regulation effect of chaotic perturbation on the hierarchical porous structure.

[0118] According to the specific embodiments provided in this application, the following technical effects are disclosed: (1) The present application provides a method for regulating the microstructure of a catalyst by introducing chaotic perturbation during the catalyst preparation process to dynamically regulate key steps such as coprecipitation, aging, drying and calcination, so that the nucleation, growth and structural evolution processes in the reaction system exhibit nonlinear changes, thereby promoting the formation of a multi-level porous structure inside the particles and significantly increasing the specific surface area and the number of reaction interfaces of the catalyst.

[0119] (2) The method for regulating the microstructure of a catalyst by chaotic perturbation provided in this application can be used in gasification and methanol processes, and especially in the high-value conversion of metallurgical furnace gas and energy catalysis.

[0120] (3) The method for regulating the microstructure of a catalyst by chaotic perturbation provided in this application can be applied to the preparation of catalytic materials, oxygen storage materials and porous functional materials by changing the active metal components, support materials or reaction system parameters.

[0121] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0122] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0123] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0124] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0125] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for preparing a catalyst based on chaotic perturbation, characterized in that, The catalyst preparation method based on chaotic perturbation includes: Preparation of metal salt solution system; A precipitant is added to the metal salt solution system for co-precipitation to obtain a catalyst precursor precipitate. The co-precipitation process is controlled by chaotic co-precipitation process parameters obtained based on a chaotic perturbation method. The chaotic co-precipitation process parameters include the precipitant addition rate and the chaotic stirring speed. The catalyst precursor precipitate is aged to obtain catalyst precursor particles. The aging process is controlled by chaotic aging process parameters obtained based on the chaotic perturbation method. The chaotic aging process parameters include chaotic aging temperature and chaotic aging pH value. The catalyst precursor particles are dried to obtain dried precursor particles. The drying process is controlled by chaotic drying process parameters obtained based on the chaotic perturbation method. The chaotic drying process parameters include chaotic drying temperature. The dried precursor particles are calcined to obtain catalyst particles. The calcination process is controlled by chaotic calcination process parameters obtained by the chaotic perturbation method. The chaotic calcination process parameters include chaotic calcination temperature and chaotic calcination heating rate.

2. The catalyst preparation method based on chaotic perturbation according to claim 1, characterized in that, A precipitant is added to the metal salt solution system to perform co-precipitation, resulting in a catalyst precursor precipitate. The co-precipitation process is controlled using chaotic co-precipitation process parameters obtained based on a chaotic perturbation method, specifically including: The co-precipitation process is divided into multiple precipitation control time periods by equal time intervals; Based on a preset first initial chaotic mapping value and a chaotic mapping model, the chaotic mapping value for each sedimentation control time period is obtained respectively; the chaotic mapping model includes at least one of Logistic mapping, Tent mapping or Chebyshev mapping; The chaotic precipitant addition rate for each precipitation control period is determined based on the chaotic mapping value and the preset precipitant baseline addition rate for each precipitation control period. The chaotic stirring speed for each sedimentation control time period is determined based on the chaotic mapping value and the preset benchmark stirring speed for each sedimentation control time period. During each precipitation control period, a precipitant is added to the metal salt solution system at the chaotic precipitant addition rate corresponding to each precipitation control period, and the mixture is stirred according to the chaotic stirring speed corresponding to each precipitation control period. After the co-precipitation process is completed, the catalyst precursor precipitate is obtained.

3. The catalyst preparation method based on chaotic perturbation according to claim 2, characterized in that, The formula for calculating the addition rate of the chaotic precipitant is: ; The formula for calculating the chaotic stirring speed is: ; in, x i For the first i The chaotic mapping value of a sedimentation control period. v i For the first i The rate of addition of the precipitant during a specific precipitation control period. v 0 The preset precipitant addition rate, n i For the first i The chaotic stirring speed during the sedimentation control period. n 0 This is the preset baseline stirring speed.

4. The catalyst preparation method based on chaotic perturbation according to claim 1, characterized in that, The catalyst precursor precipitate is aged to obtain catalyst precursor particles. The aging process is controlled using chaotic aging process parameters obtained based on a chaotic perturbation method, specifically including: The aging process is divided into equal time intervals to obtain multiple aging control time periods; Based on the preset second initial chaotic mapping value and chaotic mapping model, the chaotic mapping value for each aging control time period is obtained respectively; The chaotic aging temperature for each aging control period is determined based on the chaotic mapping value and the preset baseline aging temperature for each aging control period. The chaotic aging pH value for each aging control period is determined based on the chaotic mapping value and the preset reference pH value for each aging control period. During each aging control period, the catalyst precursor precipitate is aged using the chaotic aging temperature and chaotic aging pH value corresponding to each aging control period. After the aging process is completed, the catalyst precursor particles are obtained.

5. The catalyst preparation method based on chaotic perturbation according to claim 4, characterized in that, The formula for calculating the chaotic aging temperature is: ; The formula for calculating the pH value during chaotic aging is: ; in, y i For the first i The chaotic mapping value of a time period under aging control. T i For the first i The chaotic aging temperature for a specific aging period. T 0 The preset baseline aging temperature, k This is the aging temperature adjustment coefficient. q i For the first i The pH value of chaotic aging during a specific aging control period. q 0 This is the preset reference pH value.

6. The catalyst preparation method based on chaotic perturbation according to claim 1, characterized in that, The catalyst precursor particles are dried to obtain dried precursor particles. The drying process is controlled using chaotic drying process parameters obtained based on a chaotic perturbation method, specifically including: The drying process is divided into multiple drying control time periods by equal time intervals; Based on the preset third chaotic mapping value and chaotic mapping model, the chaotic mapping value for each drying control time period is obtained respectively; The chaotic drying temperature for each drying control period is determined based on the chaotic mapping value and the preset baseline drying temperature for each drying control period. During each drying control period, the catalyst precursor particles are dried using the chaotic drying temperature corresponding to each drying control period. After the drying process is completed, the dried precursor particles are obtained.

7. The catalyst preparation method based on chaotic perturbation according to claim 6, characterized in that, The formula for calculating the chaotic drying temperature is: ; in, z i For the first i Chaotic mapping values ​​for a drying control period T d,i For the first i Chaotic drying temperature for a controlled drying period T d The preset reference drying temperature, α This is the drying temperature adjustment coefficient.

8. The catalyst preparation method based on chaotic perturbation according to claim 1, characterized in that, The dried precursor particles are calcined to obtain catalyst particles. The calcination process is controlled using chaotic calcination process parameters obtained based on a chaotic perturbation method, specifically including: The calcination process is divided into multiple calcination control time periods by equal time intervals. Based on the preset fourth chaotic mapping value and chaotic mapping model, the chaotic mapping value for each calcination control time period is obtained respectively. The chaotic calcination temperature for each calcination control time period is determined based on the chaotic mapping value and the preset benchmark calcination temperature for each calcination control time period. The chaotic calcination heating rate for each calcination control time period is determined based on the chaotic mapping value and the preset reference heating rate for each calcination control time period. During each calcination control period, the dried precursor particles are calcined using the chaotic calcination temperature and the chaotic calcination heating rate corresponding to each calcination control period. After the calcination process is completed, the catalyst particles are obtained.

9. The catalyst preparation method based on chaotic perturbation according to claim 8, characterized in that, The formula for calculating the chaotic calcination temperature is as follows: ; The formula for calculating the heating rate of chaotic calcination is: ; in, o i For the first i Chaotic mapping values ​​for a calcination control time period T c,i For the first i The chaotic calcination temperature during a specific calcination control period. T c The preset reference calcination temperature, β This is the calcination temperature adjustment coefficient. For the first i Chaotic mapping values ​​for a calcination control time period For the first i The chaotic calcination heating rate during a calcination control period The preset baseline calcination heating rate, This is the coefficient for adjusting the calcination heating rate.

10. A catalyst preparation apparatus based on chaotic perturbation, characterized in that, The catalyst preparation apparatus based on chaotic perturbation includes: The process parameter calculation module is used to calculate the process parameters for chaotic coprecipitation, chaotic aging, chaotic drying, and chaotic calcination. The chaotic coprecipitation process parameters include the precipitant addition rate and the chaotic stirring speed; the chaotic aging process parameters include the chaotic aging temperature and the chaotic aging pH value; the chaotic drying process parameters include the chaotic drying temperature; and the chaotic calcination process parameters include the chaotic calcination temperature and the chaotic calcination heating rate. The control module, connected to the process parameter calculation module, is used to generate a first feed pump control signal based on the precipitant addition rate, a second feed pump control signal based on the chaotic aging pH value, a stirring motor control signal based on the chaotic stirring speed, a first heating device control signal based on the chaotic aging temperature, a second heating device control signal based on the chaotic drying temperature, a third heating device control signal based on the chaotic calcination temperature, and a fourth heating device control signal based on the chaotic calcination heating rate. A feed pump, connected to the control module and the reaction device, is used to add reaction materials to the reaction device according to the first feed pump control signal and the second feed pump control signal; A stirring motor, connected to the control module and the reaction device, is used to stir the solution in the reaction device according to the stirring motor control signal; A heating device, connected to the control module and the reaction device, is used to heat the reaction device according to a first heating device control signal, a second heating device control signal, a third heating device control signal, and a fourth heating device control signal; A reaction apparatus used for catalyst preparation.

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