A zinc pyridine carboxylate complex composite catalyst and preparation method thereof

Abstract

The present invention relates to the technical field of composite catalysts, and discloses a zinc pyridine carboxylate complex composite catalyst and a preparation method thereof, which is prepared by a high-temperature reaction in a high-pressure reactor using a specific zinc pyridine carboxylate complex containing different electronic group functional groups, a DMC catalyst, a polar solvent, and a non-polar solvent. Specifically, in the preparation method of the present invention, a high-pressure reactor is used to make it easier for zinc pyridine carboxylate and two metals in a bimetallic catalyst to form active sites under a high-temperature inert gas environment, thereby exerting a synergistic effect, making the selectivity and activity of the catalyst higher, and especially for two types of catalysts, the interaction between the metals can be enhanced under an inert gas atmosphere, thereby improving the structural stability of the catalyst, and the high-temperature environment is conducive to synthesizing a stable catalyst product during the synthesis process, and the intermediate that is easily decomposed at high temperature can be stabilized under the inert gas atmosphere, which is conducive to the synthesis of the composite catalyst.

Description

Technical Field

[0001] The present invention relates to the technical field of composite catalysts, and more particularly to a zinc pyridinecarboxylate complex composite catalyst and a preparation method thereof. Background Art

[0002] Carbon dioxide, as an abundant carbon resource, has garnered widespread attention in recent years, particularly in the industrial production of aliphatic polycarbonates. Polycarbonate materials, due to their high transparency, durability, and biodegradability, hold broad application prospects in the healthcare, food packaging, and automotive industries. Polypropylene carbonate (PPC), in particular, possesses carbon sequestration properties, potentially helping mitigate the greenhouse effect and plastic pollution. It also exhibits excellent ductility, oxygen barrier properties, and biocompatibility.

[0003] However, existing industrial processes for the preparation of PPC primarily utilize heterogeneous catalysis, such as ternary rare earth catalysts, zinc carboxylate catalysts, and bimetallic catalysts. However, these catalysts suffer from insufficient activity and selectivity, resulting in poor product quality, low conversion rates, and long reaction times, limiting their production and application. Key issues include: First, it is difficult to achieve both high conversion rates and high carbonate content. Low temperatures increase carbonate chain content but lower conversion rates, while high temperatures increase conversion rates but reduce carbonate chain content. Second, the production process is lengthy. Existing catalysts are inactive, leading to reaction times of up to 20 hours or even longer, increasing energy consumption and reducing production efficiency.

[0004] In view of the above problems, the development of efficient catalysts has become the key to improving the production efficiency and quality of PPC. Zinc pyridine carboxylate complex catalysts have high catalytic activity and can achieve efficient catalytic reactions under relatively mild conditions, significantly improving the conversion rate of propylene oxide. However, in the preparation process of zinc pyridine carboxylate complex catalysts, manual control of reaction conditions is usually required. The method of manually monitoring the reaction process has a low degree of intelligence, which can easily lead to some side reactions and decomposition problems of the target product, or increase energy consumption and prolong the reaction time. Specifically, due to the subjectivity and uncertainty of manual control, the reaction conditions of different batches may vary, resulting in unstable product quality and poor consistency, thereby affecting the preparation quality of zinc pyridine carboxylate complex catalysts. In addition, continuous manual monitoring requires a lot of manpower, which not only increases labor intensity and reduces preparation efficiency, but also may cause operational errors due to fatigue or negligence. Especially in cases where continuous monitoring and fine-tuning are required, manual control is difficult to achieve ideal control accuracy, which can lead to deviations in reaction conditions, thereby affecting the preparation quality of zinc pyridine carboxylate complex catalysts, increasing energy consumption and prolonging reaction time.

[0005] Therefore, an optimized preparation scheme for zinc pyridine carboxylate complex catalyst is desired. Summary of the Invention

[0006] The present invention provides a zinc pyridinecarboxylate complex composite catalyst and a preparation method thereof, which can predictively control the dropping speed of a zinc hydrochloric acid solution according to the real-time reflux temperature, thereby realizing adaptive dynamic control of the reflux reaction and the dropping process in a more intelligent manner, thereby ensuring the consistency and controllability of the reaction conditions.

[0007] In a first aspect, a method for preparing a zinc pyridinecarboxylate complex composite catalyst is provided, comprising:

[0008] Adding a zinc pyridine carboxylate complex, a double metal cyanide catalyst and a mixed solvent into a high-pressure reactor, wherein the molar ratio of the zinc pyridine carboxylate complex to the double metal cyanide catalyst is 1:1-60;

[0009] dissolving the zinc pyridinecarboxylate complex, the double metal cyanide catalyst and the mixed solvent to obtain a raw material mixed solution;

[0010] The raw material mixture is subjected to an inert gas atmosphere reaction to obtain a suspension, wherein the reaction temperature of the inert gas atmosphere reaction is 20° C.-150° C., the reaction time is 12 h-38 h; and the pressure of the inert gas atmosphere is 0.2-1 MPa;

[0011] The suspension is cooled to room temperature, and an organic solvent is added thereto for filtration and vacuum drying to obtain a zinc pyridinecarboxylate complex composite catalyst.

[0012] In one possible implementation, the mixed solvent is a mixed solvent comprising a polar solvent and a non-polar solvent, wherein the polar solvent is selected from one or more of water, acetonitrile, methanol, ethanol, acetone, isopropanol, acetic acid, and ether, and the non-polar solvent is selected from one or more of toluene, benzene, carbon tetrachloride, hexane, and dichloromethane.

[0013] In a possible implementation, the organic solvent is selected from any one or more of ethyl acetate, ethanol, methanol, and dichloromethane, and the amount of the organic solvent is 2-20 times the volume of the suspension.

[0014] In one possible implementation, the method for preparing the zinc pyridinecarboxylate complex comprises the steps of:

[0015] Dissolving the zinc source with dilute hydrochloric acid and stirring to obtain a zinc hydrochloric acid solution;

[0016] dissolving a pyridinecarboxylic acid containing an electron-withdrawing substituent group and a pyridinecarboxylic acid containing an electron-donating substituent group in deionized water to form a pyridinecarboxylic acid mixed solution;

[0017] Slowly adding the zinc hydrochloric acid solution dropwise to the pyridinecarboxylic acid mixed solution to perform a reflux reaction;

[0018] Cooling, precipitating crystals, washing, and drying to obtain a zinc pyridinecarboxylate complex intermediate containing crystal water;

[0019] The zinc pyridinecarboxylate complex intermediate is subjected to a high temperature of 110-150° C. to remove crystal water to obtain the zinc pyridinecarboxylate complex.

[0020] In one possible implementation, the zinc source is selected from any one of zinc chloride, zinc sulfate (ZnSO4), zinc chlorate [Zn(ClO3)2], zinc nitrate [Zn(NO3)2], zinc acetate [Zn(OAc)2], zinc oxide and zinc hydroxide; and the dilute hydrochloric acid refers to an aqueous solution of HCl with a pH value between 0 and 5.

[0021] In one possible implementation, the electron-withdrawing substituent group is selected from -CX3 (X=F), -CN, -F, -Cl, -Br, and -I; the pyridinecarboxylic acid containing an electron-withdrawing substituent group is selected from any one or more of 4-chloro-2,6-pyridinedicarboxylic acid, 4-bromo-2,6-pyridinedicarboxylic acid, 4-trifluoro-2,6-pyridinedicarboxylic acid, and 4-fluoro-2,6-pyridinedicarboxylic acid; the electron-donating substituent group is selected from any one or more of -O-, -NHR3, -NH2, -OH, -OR4, -R5, and -Ph, wherein R3, R4, and R5 are any alkyl groups; the pyridinecarboxylic acid containing an electron-donating substituent group is selected from any one or more of 4-methyl-2,6-pyridinedicarboxylic acid, 4-ethyl-2,6-pyridinedicarboxylic acid, 4-ethoxy-2,6-pyridinedicarboxylic acid, 4-phenyl-2,6-pyridinedicarboxylic acid, and 4-methoxy-2,6-pyridinedicarboxylic acid.

[0022] The zinc hydrochloric acid solution is slowly added dropwise to the pyridinecarboxylic acid mixed solution to perform a reflux reaction, comprising:

[0023] Obtaining a time series of reflow temperature collected by a temperature sensor;

[0024] Transmitting the time series of the reflux temperature to a dripping acceleration control center via a wireless communication module;

[0025] In the dripping acceleration control center, the time series of the reflux temperature is segmented based on a predetermined sampling period and each subsequence is data-structured to obtain a sequence of reflux temperature local time series input vectors;

[0026] In the dripping acceleration control center, each reflux temperature local time series input vector in the sequence of the reflux temperature local time series input vector is input into a reflux temperature time series feature extractor based on a bidirectional LSTM model to obtain a sequence of reflux temperature local time series implicit correlation feature vectors;

[0027] In the dripping acceleration control center, the sequence of the local temporal implicit correlation feature vectors of the reflow temperature is input into a feature message propagation network based on the spatiotemporal transfer characteristics of node potential energy to obtain a spatiotemporal attenuation propagation representation vector of the reflow temperature;

[0028] At the dripping acceleration control center, the reflux temperature spatiotemporal attenuation propagation representation vector is input into a decoder-based dripping acceleration controller to obtain a control instruction, wherein the control instruction includes a decoded recommended value of the dripping acceleration value at the next time point;

[0029] The droplet addition speed control center transmits the control instruction to the solution droplet addition control actuator to control the droplet addition speed value of the zinc hydrochloric acid solution.

[0030] In a possible implementation, the dripping acceleration control center inputs the sequence of the local temporal implicit correlation feature vectors of the reflow temperature into a feature message propagation network based on the spatiotemporal transfer characteristics of node potential energy to obtain a spatiotemporal attenuation propagation representation vector of the reflow temperature, including:

[0031] Calculating, based on the mean and standard deviation of each reflow temperature local timing implicit correlation feature vector in the sequence of the reflow temperature local timing implicit correlation feature vectors, an energy significant descriptor of each reflow temperature local timing implicit correlation feature vector to obtain a sequence of reflow temperature local timing implicit correlation feature vectors;

[0032] Extracting the timestamp of each reflow temperature local time series implicit correlation feature vector in the sequence of the reflow temperature local time series implicit correlation feature vectors to obtain a sequence of reflow temperature timestamps;

[0033] The reflow temperature local timing implicit correlation feature vector corresponding to the current time point in the sequence of the reflow temperature local timing implicit correlation feature vectors is used as the current reflow temperature local timing implicit correlation feature vector, and the reflow temperature local timing implicit correlation feature vectors corresponding to other time points are used as the historical reflow temperature local timing implicit correlation feature vectors to obtain a sequence of the current reflow temperature local timing implicit correlation feature vector and the historical reflow temperature local timing implicit correlation feature vectors;

[0034] Calculating the energy time decay factor of each historical reflow temperature local time series implicit correlation feature vector in the sequence of the historical reflow temperature local time series implicit correlation feature vectors relative to the current reflow temperature local time series implicit correlation feature vector to obtain a sequence of reflow temperature local time series energy time decay factors;

[0035] Using the sequence of the reflow temperature local timing energy significant descriptors as positive adjustment factors and the sequence of the reflow temperature local timing energy time decay factors as negative adjustment factors, the sequence of the historical reflow temperature local timing implicit correlation feature vectors is subjected to time series propagation aggregation to obtain a reflow temperature local timing history node propagation aggregation representation feature vector;

[0036] Fusing the reflow temperature local time series history node propagation aggregation representation feature vector and the current reflow temperature local time series implicit association feature vector to obtain the reflow temperature spatiotemporal attenuation propagation representation vector;

[0037] Wherein, using the sequence of the reflow temperature local time series energy significant descriptors as a positive adjustment factor and the sequence of the reflow temperature local time series energy time decay factors as a negative adjustment factor, the sequence of the historical reflow temperature local time series implicit correlation feature vectors is subjected to time series propagation aggregation to obtain the reflow temperature local time series historical node propagation aggregation representation feature vector, including: calculating the positional division of the sequence of the reflow temperature local time series energy significant descriptors and the sequence of the reflow temperature local time series energy time decay factors, using the obtained reflow temperature local time series energy weight as a weighting coefficient, calculating the positional weighted sum of the sequence of the historical reflow temperature local time series implicit correlation feature vectors to obtain the reflow temperature local time series historical node propagation aggregation representation feature vector;

[0038] Among them, the fusion of the reflow temperature local timing history node propagation aggregation representation feature vector and the current reflow temperature local timing implicit association feature vector to obtain the reflow temperature spatiotemporal attenuation propagation representation vector includes: based on the energy significant descriptor corresponding to the current reflow temperature local timing implicit association feature vector, calculating the position-weighted sum of the reflow temperature local timing history node propagation aggregation representation feature vector and the current reflow temperature local timing implicit association feature vector to obtain the reflow temperature spatiotemporal attenuation propagation representation vector.

[0039] In a possible implementation, based on the mean and standard deviation of each reflow temperature local timing implicit correlation feature vector in the sequence of the reflow temperature local timing implicit correlation feature vectors, calculating the energy significant descriptors of each reflow temperature local timing implicit correlation feature vector to obtain a sequence of reflow temperature local timing implicit correlation feature vectors includes:

[0040] Calculating the mean and standard deviation of each reflow temperature local time series implicit correlation feature vector in the sequence of the reflow temperature local time series implicit correlation feature vector to obtain a sequence of reflow temperature local means and a sequence of reflow temperature local standard deviations;

[0041] After performing positional differentiation on each corresponding group of the sequence of the reflow temperature local timing implicit correlation feature vectors and the sequence of the reflow temperature local mean value, performing fourth power modulation on each positional feature value in the obtained sequence of differential feature vectors to obtain a sequence of reflow temperature local timing modulation feature vectors;

[0042] Calculating the expected value of each reflow temperature local timing modulation characteristic vector in the sequence of reflow temperature local timing modulation characteristic vectors to obtain a sequence of reflow temperature local timing positive expected factors;

[0043] Calculating the fourth power modulation value of each local standard deviation of the reflow temperature in the sequence of local standard deviations of the reflow temperature to obtain a sequence of local timing inverse expectation factors of the reflow temperature;

[0044] Each corresponding group of reflow temperature local timing positive expected factors and reflow temperature local timing inverse expected factors in the sequence of reflow temperature local timing positive expected factors and the sequence of reflow temperature local timing inverse expected factors are divided to obtain the sequence of reflow temperature local timing energy significant descriptors.

[0045] In a possible implementation, calculating the energy time decay factor of each historical reflow temperature local time series implicit correlation feature vector in the sequence of the historical reflow temperature local time series implicit correlation feature vectors relative to the current reflow temperature local time series implicit correlation feature vector to obtain a sequence of reflow temperature local time series energy time decay factors includes:

[0046] Calculating the reflow temperature timestamp corresponding to the current reflow temperature local time series implicit correlation feature vector and the reflow temperature timestamp corresponding to each historical reflow temperature local time series implicit correlation feature vector respectively, subtracting the timestamps and rounding down the results to obtain a sequence of time span values;

[0047] After calculating the square of each time span value in the sequence of time span values, the obtained sequence of span square modulation values ​​is divided by the square of the time decay inverse scaling parameter and multiplied by the decay rate positive scaling parameter to obtain a sequence of time series span energy decay coefficients;

[0048] Taking each time-series span energy attenuation coefficient in the sequence of the time-series span energy attenuation coefficients as an exponential power, a natural exponential function value with a natural constant e as a base is calculated to obtain a sequence of the reflow temperature local time-series energy time attenuation factors.

[0049] In a second aspect, a zinc pyridinecarboxylate complex composite catalyst is provided, which is prepared by the aforementioned preparation method of the zinc pyridinecarboxylate complex composite catalyst.

[0050] Compared with the prior art, the present invention has the following beneficial effects:

[0051] (1) The method is prepared by reacting a specific zinc pyridine carboxylate complex containing different functional groups, a DMC catalyst, a polar solvent, and a non-polar solvent in a high-pressure reactor at a high temperature. Specifically, in the preparation method of the present invention, the use of a high-pressure reactor in a high-temperature inert gas environment can make it easier for the zinc pyridine carboxylate and the two metals in the bimetallic catalyst to form active sites, thereby exerting a synergistic effect, making the catalyst more selective and active. In particular, for the two types of catalysts, the interaction between the metals can be enhanced under an inert gas atmosphere, thereby improving the structural stability of the catalyst. In addition, the high-temperature environment during the synthesis process is conducive to the synthesis of stable catalyst products. At the same time, the inert gas atmosphere can stabilize intermediates that are easily decomposed at high temperatures, which is conducive to the synthesis of composite catalysts. Compared with other preparation methods, the inert gas atmosphere reaction can obtain finer catalyst particles, smaller catalyst particle size and more excellent synergistic effect, so that the catalyst has more efficient and stable catalytic performance in subsequent polymerization reactions.

[0052] (2) A specific zinc precursor is formed by selecting a zinc source treated with hydrochloric acid, and then refluxed with a mixed solution of two pyridine carboxylic acids with different electronic groups, and then dried at high temperature to obtain zinc pyridine carboxylate with two functional groups. The above unique preparation processes complement each other and are indispensable, forming a synergistic effect, so that different pyridine carboxylic acids can synthesize zinc pyridine carboxylate complexes with different functional groups. Specifically, in the preparation process of the present invention, the zinc source is first acidified to form a zinc hydrochloric acid solution. The zinc source is mostly insoluble in organic solvents, and the solubility of the zinc source in the reaction with pyridine carboxylic acid will be limited. Therefore, the zinc source is first acidified and corroded by an acidic medium to dissolve it into a soluble zinc salt, thereby improving its solubility. In addition, during the chemical etching process using dilute hydrochloric acid, a zinc salt film with a specific surface texture can be prepared. The formation of this film is more conducive to the formation of the complex in the subsequent process, which can make the catalyst have a larger specific surface area.

[0053] (3) By using different electron groups to react with zinc sources to form zinc pyridine carboxylate complexes with different electron groups, the introduction of electron-donating and electron-withdrawing groups during the synthesis of the complex can significantly change the electronic structure of the zinc pyridine carboxylate complex, forming a diverse charge distribution and energy band structure. This diversity of electronic structure can enable the complex to better combine with bimetallic catalysts, exposing more active sites on the catalyst surface. The electron-donating group can enhance the electron density of the complex, while the electron-withdrawing group can adjust the charge distribution and the reactivity of the metal center. This dual regulation enables the complex to exhibit higher activity and selectivity in the catalytic reaction. Reasonable electronic structure design can enhance the structural stability of the zinc pyridine carboxylate complex, allowing it to maintain long-term activity during the catalytic process. In addition, the introduction of electron-donating and electron-withdrawing groups helps to reduce the decomposition or deactivation of the catalyst and improve its reusability. Due to the diversity of electronic structure, the zinc pyridine carboxylate complex can achieve efficient catalytic effect under milder reaction conditions. This feature not only reduces energy consumption and production costs, but also reduces negative impacts on the environment.

[0054] (4) During the reflux reaction, the reflux temperature data is collected in real time by a temperature sensor, and the reflux temperature data is transmitted to the dripping speed control center for processing, so that the reflux temperature data can be analyzed in a time series manner by using a data processing and analysis algorithm based on artificial intelligence and deep learning in the dripping speed control center, thereby capturing and characterizing the time series dynamic information propagation characteristics of the reflux temperature, thereby using the time series information propagation semantics of the reflux temperature to predict the dripping speed value at the next time point and automatically control the dripping speed of the zinc hydrochloric acid solution. In this way, the dripping speed of the zinc hydrochloric acid solution can be predictively controlled according to the real-time reflux temperature, thereby realizing adaptive dynamic control of the reflux reaction and the dripping process in a more intelligent manner to ensure the consistency and controllability of the reaction conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] The above and other objects, features, and advantages of the present invention will become more apparent through a more detailed description of the embodiments of the present invention in conjunction with the accompanying drawings. The accompanying drawings are provided to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and are not intended to limit the present invention. In the drawings, the same reference numerals generally represent the same components or steps.

[0056] Figure 1 This is the WXRD pattern of trifluoro-ethoxy-picolinate zinc.

[0057] Figure 2 is the WXRD pattern of the bimetallic catalyst.

[0058] Figure 3is the WXRD pattern of the composite catalyst.

[0059] Figure 4 The present invention provides a schematic flow chart of a method for preparing the zinc pyridinecarboxylate complex composite catalyst according to an embodiment of the present invention.

[0060] Figure 5 The present invention provides a schematic flow chart of a method for preparing the zinc pyridinecarboxylate complex composite catalyst according to an embodiment of the present invention.

[0061] Figure 6 This is a schematic flow chart of slowly adding the zinc hydrochloric acid solution dropwise to the pyridinecarboxylic acid mixed solution to perform a reflux reaction according to an embodiment of the present invention.

[0062] Figure 7 This is a data flow diagram of slowly adding the zinc hydrochloric acid solution dropwise to the pyridinecarboxylic acid mixed solution to perform a reflux reaction according to an embodiment of the present invention. DETAILED DESCRIPTION

[0063] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts also fall within the scope of protection of the present invention.

[0064] Specifically, the present application uses the following detection method to analyze the elemental composition of the composite catalyst:

[0065] 1. Elemental analysis was used to analyze the elemental composition of the composite catalyst: the elemental analysis was performed using Vario Macro Cube-M336 equipment produced by Elementar, Germany.

[0066] 2. Catalyst WRXD spectrum and chemical bond length test method: Wide-angle X-ray diffraction (WXRD) spectrum and data are obtained by Rigaku's Ultima IV measurement.

[0067] 3. Specific Surface Area Test Method: Testing was performed using the Quantachrome Automated Gas Adsorption System (AUTOSORB-1-C), a fully automated adsorption instrument. Specific surface area was calculated using the BET technique and the N2 adsorption curve. Prior to testing, the catalyst was vacuum-treated at 200°C for one hour to prevent pore adsorption of dust or water that could affect the test results.

[0068] Average surface particle size test method: The average surface particle size is measured by a Nicomp 380 ZLS device produced by PSS, USA. Before the measurement, the solid powder is dispersed with deionized water and the suspension is broken up by ultrasonic wave.

[0069] Preparation of zinc pyridinecarboxylate complex

[0070] (1) Add 19.87 g of zinc hydroxide to 30 mL of dilute hydrochloric acid solution (pH = 3) and stir at 20°C for 1.5 h to form a zinc hydrochloric acid solution;

[0071] (2) Add 4.70 g of 4-trifluoro-2,6-pyridinedicarboxylic acid and 3.94 g of 4-ethoxy-2,6-pyridinedicarboxylic acid to 150 mL of deionized water and stir evenly at room temperature to form a pyridinecarboxylic acid mixed solution;

[0072] (3) The prepared zinc hydrochloric acid solution was added dropwise to the pyridine carboxylic acid mixed solution at a rate of 10 drops / min. After the addition was completed, the reaction solution was heated to 80°C and refluxed for 9 h. During the reflux heating process, stirring was continued at a stirring speed of 800 r / min to ensure the formation of the pyridine carboxylic acid zinc complex;

[0073] (4) After the reaction is completed, the mixture is cooled to room temperature, crystals are gradually precipitated, and the crystals are washed and dried to obtain a zinc pyridinecarboxylate complex intermediate containing crystal water;

[0074] (5) The zinc pyridine carboxylate complex intermediate is dehydrated at a high temperature of 140° C. to obtain the trifluoro-ethoxy-zinc pyridine carboxylate complex, which is retained for later use.

[0075] The zinc pyridine carboxylate complex prepared in Example 1 was subjected to elemental analysis. The elemental analysis results (%) of the trifluoro-ethoxy-zinc pyridine carboxylate complex were: C, 38.46; H, 2.62; F, 11.41; N, 5.61; O, 18.82; Zn, 13.08. The WXRD spectrum of the zinc pyridine carboxylate complex prepared in Example 1 is shown in FIG. Figure 1 As shown, for trifluoro-ethoxy-zinc pyridine carboxylate, its characteristic peaks appear at 2θ=12.7, 15.3, and 19.7°. After the interaction between the electron-withdrawing group and the electron-donating group, the characteristic peak intensity is higher and sharper, further proving that the electron-withdrawing group and the electron-donating group can improve the crystallinity of the zinc pyridine carboxylate particles. Combined with the ratio of F and O elements in the elemental analysis, it is proved that the electron-withdrawing group and the electron-donating group react well to obtain a trifluoro-ethoxy-zinc pyridine carboxylate complex, the structure of which is shown below:

[0076]

[0077] Figure 5The present invention provides a schematic flow chart of a method for preparing the zinc pyridinecarboxylate complex composite catalyst according to an embodiment of the present invention. In the preparation of the zinc pyridinecarboxylate complex composite catalyst, the method for preparing the zinc pyridinecarboxylate complex comprises the following steps: S11, dissolving a zinc source with dilute hydrochloric acid and stirring to obtain a zinc hydrochloric acid solution; S12, dissolving a pyridinecarboxylic acid containing an electron-withdrawing substituent group and a pyridinecarboxylic acid containing an electron-donating substituent group in deionized water to form a pyridinecarboxylic acid mixed solution; S13, slowly adding the zinc hydrochloric acid solution dropwise to the pyridinecarboxylic acid mixed solution for a reflux reaction; S14, cooling, precipitating crystals, washing, and drying to obtain a zinc pyridinecarboxylate complex intermediate containing crystal water; S15, removing crystal water from the zinc pyridinecarboxylate complex intermediate at a high temperature of 110 to 150°C to obtain the zinc pyridinecarboxylate complex.

[0078] Optionally, in one embodiment of the present invention, the zinc source is selected from any one of zinc chloride, zinc sulfate (ZnSO4), zinc chlorate [Zn(ClO3)2], zinc nitrate [Zn(NO3)2], zinc acetate [Zn(OAc)2], zinc oxide and zinc hydroxide; and the dilute hydrochloric acid refers to an aqueous solution of HCl with a pH value between 0 and 5.

[0079] Optionally, in one embodiment of the present invention, the electron-withdrawing substituent group is selected from -CX3 (X=F), -CN, -F, -Cl, -Br, -I; the pyridinecarboxylic acid containing an electron-withdrawing substituent group is selected from any one or more of 4-chloro-2,6-pyridinedicarboxylic acid, 4-bromo-2,6-pyridinedicarboxylic acid, 4-trifluoro-2,6-pyridinedicarboxylic acid, and 4-fluoro-2,6-pyridinedicarboxylic acid; the electron-donating substituent group is selected from any one or more of -O-, -NHR3, -NH2, -OH, -OR4, -R5, and -Ph, wherein R3, R4, and R5 are any alkyl groups; the pyridinecarboxylic acid containing an electron-donating substituent group is selected from any one or more of 4-methyl-2,6-pyridinedicarboxylic acid, 4-ethyl-2,6-pyridinedicarboxylic acid, 4-ethoxy-2,6-pyridinedicarboxylic acid, 4-phenyl-2,6-pyridinedicarboxylic acid, and 4-methoxy-2,6-pyridinedicarboxylic acid.

[0080] In particular, in the technical solution of the present invention, a specific zinc precursor is formed by selecting a zinc source treated with hydrochloric acid, and a reflux reaction is carried out with a mixed solution of pyridine carboxylic acids with two different electronic groups, and then high-temperature drying is used to obtain zinc pyridine carboxylate with two functional groups. The above unique preparation processes complement each other and are indispensable, forming a synergistic effect, so that different pyridine carboxylic acids are synthesized into zinc pyridine carboxylate complexes with different functional groups. Specifically, in the preparation process of the present invention, the zinc source is first acidified to form a zinc hydrochloric acid solution. The zinc source is mostly insoluble in organic solvents. During the reaction of the zinc source and pyridine carboxylic acid, the solubility problem will be limited. Therefore, the zinc source is first acid-treated and corroded by an acidic medium to dissolve it into a soluble zinc salt, thereby increasing its solubility. In addition, in the process of chemical etching using dilute hydrochloric acid, a zinc salt film with a specific surface texture can be prepared. The formation of this film is more conducive to the formation of the complex in the subsequent process, which can make the catalyst specific surface area larger.

[0081] Furthermore, in this scheme, zinc pyridine carboxylate complexes with different electron groups are formed by reacting with the zinc source. The introduction of electron-donating and electron-withdrawing groups during the synthesis of these complexes significantly modifies the electronic structure of the zinc pyridine carboxylate complexes, resulting in a diverse charge distribution and energy band structure. This diverse electronic structure allows the complexes to better combine with bimetallic catalysts, exposing more active sites on the catalyst surface. Electron-donating groups enhance the electron density of the complexes, while electron-withdrawing groups adjust the charge distribution and reactivity of the metal center. This dual regulation enables the complexes to exhibit higher activity and selectivity in catalytic reactions. Reasonable electronic structure design enhances the structural stability of the zinc pyridine carboxylate complexes, maintaining their activity for extended periods during the catalytic process. Furthermore, the introduction of electron-donating and electron-withdrawing groups helps reduce catalyst decomposition or deactivation, increasing their reusability. Due to their diverse electronic structures, zinc pyridine carboxylate complexes can achieve efficient catalysis under relatively mild reaction conditions. This characteristic not only reduces energy consumption and production costs, but also mitigates negative environmental impacts.

[0082] Accordingly, in the process of preparing zinc pyridine carboxylate complex, controlling the dropping rate of zinc hydrochloric acid solution is the key to ensure reaction stability and product quality. If the dropping rate is too fast, reactants can be added in a large number within a short period of time, which may cause local temperature to rise suddenly, thereby causing side reactions or causing the quality degradation of the target product. On the contrary, if the dropping rate is too slow, the reaction time may be prolonged, energy consumption may be increased, and unnecessary side reactions may be caused because the reactant residence time is too long. In addition, it is also considered that higher reflux temperature can accelerate the reaction rate, but it may also cause the increase of side reactions, or even cause the decomposition of the target product. On the contrary, although lower temperature helps to reduce side reactions, it may also cause the reaction rate to be too slow, prolonging the reaction time. Therefore, when carrying out back flow reaction, it is necessary to consider that the dropping rate of zinc hydrochloric acid solution and the timing interaction between the reflux temperature carry out the monitoring of reaction process, and dynamically adjust the dropping rate based on the reflux temperature monitored in real time, thereby avoid the reaction conditions fluctuation caused by improper dropping rate, ensure that the reaction is carried out steadily with this, and help to improve product purity and shorten the reaction time.

[0083] However, the traditional back flow reaction control method is usually to manually set a fixed rate of addition, which is then kept unchanged throughout the reaction process. This fixed rate of addition control method cannot cope with the real-time changes of conditions such as temperature during the reaction, which can cause the deviation of the reaction conditions, thereby affecting product quality. In addition, some existing schemes are to slowly drop the zinc hydrochloric acid solution into the pyridine carboxylic acid mixed solution by manual operation and monitoring to carry out back flow reaction. The manual control method not only requires a large amount of time and energy consumed by humans, but is also difficult to achieve precise adjustment, especially in the case of long-term continuous operation, which can cause some side reactions and decomposition problems of the target product, or increase energy consumption and extend reaction time.

[0084] In response to the above technical problems, the technical concept of the present invention is to monitor and collect reflux temperature data in real time through a temperature sensor during the reflux reaction process, and transmit the reflux temperature data to a droplet velocity control center for processing, so that the droplet velocity control center can use a data processing and analysis algorithm based on artificial intelligence and deep learning to perform time series analysis on the reflux temperature data, thereby capturing and characterizing the time series dynamic information propagation characteristics of the reflux temperature, thereby using the time series information propagation semantics of the reflux temperature to predict the droplet velocity value at the next time point and automatically control the droplet velocity of the zinc hydrochloric acid solution. In this way, the droplet velocity of the zinc hydrochloric acid solution can be predictively controlled according to the real-time reflux temperature, thereby realizing adaptive dynamic control of the reflux reaction and the droplet addition process in a more intelligent manner to ensure the consistency and controllability of the reaction conditions.

[0085] Figure 6This is a schematic flow chart of slowly adding the zinc hydrochloric acid solution dropwise to the pyridinecarboxylic acid mixed solution to perform a reflux reaction according to an embodiment of the present invention. Figure 7 The data flow diagram of the embodiment of the present invention is as follows: the zinc hydrochloric acid solution is slowly added to the pyridine carboxylic acid mixed solution to perform a reflux reaction. The zinc hydrochloric acid solution is slowly added to the pyridine carboxylic acid mixed solution to perform a reflux reaction, including: S131, obtaining the time series of the reflux temperature collected by the temperature sensor; S132, transmitting the time series of the reflux temperature to the dripping acceleration control center through the wireless communication module; S133, in the dripping acceleration control center, based on a predetermined sampling period, the time series of the reflux temperature is sequence-segmented and each subsequence is data-structured to obtain a sequence of reflux temperature local time series input vectors; S134, in the dripping acceleration control center, each reflux temperature local time series input vector in the sequence of the reflux temperature local time series input vector is respectively input into the reflux temperature based on the bidirectional LSTM model. A timing feature extractor is used to obtain a sequence of local timing implicitly associated feature vectors of the reflux temperature; S135, in the dripping acceleration control center, the sequence of local timing implicitly associated feature vectors of the reflux temperature is input into a feature message propagation network based on the spatiotemporal transfer characteristics of node potential energy to obtain a spatiotemporal attenuation propagation representation vector of the reflux temperature; S136, in the dripping acceleration control center, the spatiotemporal attenuation propagation representation vector of the reflux temperature is input into a dripping acceleration controller based on a decoder to obtain a control instruction, and the control instruction includes a decoded recommended value of the dripping acceleration value at the next time point; S137, the dripping acceleration control center transmits the control instruction to the solution dripping control actuator to control the dripping acceleration value of the zinc hydrochloric acid solution.

[0086] Specifically, S131 acquires a time series of reflux temperatures collected by a temperature sensor. Alternatively, in one embodiment of the present invention, acquiring a time series of reflux temperatures collected by a temperature sensor is typically performed in the following steps: First, a temperature sensor is installed in the reaction apparatus to monitor the reflux temperature in real time. The temperature sensor is then connected to a data acquisition system that records the temperature data measured by the sensor within a specific sampling period.

[0087] Specifically, in S132, the time series of the reflux temperature is transmitted to the dripping speed control center via a wireless communication module. It is worth noting that due to the mutual correlation and interaction between the reflux temperature and the dripping speed, the dripping speed control center can automatically learn and capture the temporal interaction characteristics between the reflux temperature and the dripping speed during training using deep learning technology. In actual application, the required change in the dripping speed can be inferred from the temporal characteristics of the reflux temperature, thereby achieving adaptive control of the dripping speed based on the actual change in the reflux temperature.

[0088] Specifically, in S133, the dripping acceleration control center divides the reflux temperature time series based on a predetermined sampling period and structures each subsequence into data to obtain a sequence of reflux temperature local time series input vectors. It should be understood that, considering that the reflux temperature has a time series dynamic change characteristic in the time dimension, that is, the reflux temperature changes over time, these reflux temperature time series changes may be relatively subtle and difficult to detect and capture using traditional methods. Therefore, in the technical solution of the present invention, the dripping acceleration control center divides the reflux temperature time series based on a predetermined sampling period and structures each subsequence into data to obtain a sequence of reflux temperature local time series input vectors. By dividing the continuous reflux temperature time data into multiple smaller subsequences, each subsequence represents the reflux temperature changes over a period of time. This helps to subsequently capture the reflux temperature change pattern in the short term, which is crucial for understanding the reflux temperature time series dynamic characteristics and temperature change trends during the reflux reaction. Furthermore, by structuring the time subseries data of each reflow temperature, it can be converted into a form suitable for processing by machine learning algorithms, which facilitates subsequent feature extraction and model training.

[0089] Specifically, in the dripping acceleration control center, in S134, each reflux temperature local time series input vector in the sequence of the reflux temperature local time series input vector is input into a reflux temperature time series feature extractor based on a bidirectional LSTM model to obtain a sequence of reflux temperature local time series implicit correlation feature vectors. It should be understood that in the dripping acceleration control center, each reflux temperature local time series input vector in the sequence of the reflux temperature local time series input vector is further input into a reflux temperature time series feature extractor based on a bidirectional LSTM model for feature mining to extract the local time series implicit correlation feature information of the reflux temperature in each local time period on the time dimension, thereby obtaining a sequence of reflux temperature local time series implicit correlation feature vectors.

[0090] Specifically, in S135, the sequence of implicit correlation feature vectors of the local time series of the reflux temperature is input into a feature message propagation network based on the spatiotemporal transfer characteristics of node potential energy in order to obtain a spatiotemporal attenuation propagation representation vector of the reflux temperature. It should be understood that in the reflux temperature control center, the reflux temperature time series feature extractor based on the bidirectional LSTM model has extracted the implicit correlation features of the local time series of the reflux temperature in each local time period, thereby obtaining a series of implicit correlation feature vectors of the local time series of the reflux temperature. These feature vectors contain important information about temperature changes. However, these implicit correlation feature vectors of the local time series of the reflux temperature still need to be further processed to better capture the dynamic characteristics of the reflux temperature changes and to take into account the degree of influence of the temperature at different time points on the current reaction state. In other words, since the reflux temperature has the characteristic of decaying in the time dimension, the local time series features of the reflux temperature at a distance will have less influence on the dynamic changes and characteristic expression of the reflux temperature at the current time point. Therefore, in order to better aggregate the local temporal semantics of these reflux temperatures, and thus more accurately infer the changing trend of the reflux temperature to perform predictive control of the dripping acceleration of the zinc-hydrochloric acid solution, in the technical solution of the present invention, the sequence of the local temporal implicit association feature vectors of the reflux temperature is further input into the characteristic message propagation network based on the spatiotemporal transfer characteristics of the node potential energy to obtain the spatiotemporal attenuation propagation representation vector of the reflux temperature. The characteristic message propagation network based on the spatiotemporal transfer characteristics of the node potential energy can aggregate the local temporal features of each reflux temperature through the significance and temporal attenuation characteristics of the node energy to generate the spatiotemporal attenuation propagation representation vector of the reflux temperature. In this way, the most critical information for the current reaction state and the dripping acceleration control task can be extracted from the local temporal association feature information of the reflux temperature in different time periods, and more accurate control instructions can be generated accordingly to optimize the dripping acceleration rate of the zinc-hydrochloric acid solution.

[0091] Optionally, in one embodiment of the present invention, in the dripping acceleration control center, the sequence of the reflow temperature local time series implicit correlation feature vectors is input into a characteristic message propagation network based on the spatiotemporal transfer characteristics of node potential energy to obtain a reflow temperature spatiotemporal attenuation propagation representation vector, including: based on the mean and standard deviation of each reflow temperature local time series implicit correlation feature vector in the sequence of the reflow temperature local time series implicit correlation feature vectors, calculating the energy significant descriptors of each reflow temperature local time series implicit correlation feature vector to obtain a sequence of reflow temperature local time series energy significant descriptors; extracting the timestamps of each reflow temperature local time series implicit correlation feature vector in the sequence of the reflow temperature local time series implicit correlation feature vector to obtain a sequence of reflow temperature timestamps; using the reflow temperature local time series implicit correlation feature vector corresponding to the current time point in the sequence of the reflow temperature local time series implicit correlation feature vector as the current reflow temperature local time series implicit correlation feature vector and using the reflow temperature local time series implicit correlation feature vectors corresponding to other time points as the current reflow temperature local time series implicit correlation feature vector. As the historical reflow temperature local timing implicit correlation feature vector to obtain the current reflow temperature local timing implicit correlation feature vector and the sequence of historical reflow temperature local timing implicit correlation feature vectors; calculate the energy time attenuation factor of each historical reflow temperature local timing implicit correlation feature vector in the sequence of historical reflow temperature local timing implicit correlation feature vectors relative to the current reflow temperature local timing implicit correlation feature vector to obtain the sequence of reflow temperature local timing energy time attenuation factors; use the sequence of reflow temperature local timing energy significance descriptors as positive adjustment factors and the sequence of reflow temperature local timing energy time attenuation factors as negative adjustment factors to perform time propagation aggregation on the sequence of historical reflow temperature local timing implicit correlation feature vectors to obtain the reflow temperature local timing history node propagation aggregation representation feature vector; fuse the reflow temperature local timing history node propagation aggregation representation feature vector and the current reflow temperature local timing implicit correlation feature vector to obtain the reflow temperature spatiotemporal attenuation propagation representation vector.

[0092] Optionally, in one embodiment of the present invention, the sequence of the reflow temperature local timing energy significant descriptors is used as a positive adjustment factor and the sequence of the reflow temperature local timing energy time attenuation factor is used as a reverse adjustment factor, and the sequence of the historical reflow temperature local timing implicit correlation feature vectors is subjected to timing propagation aggregation to obtain the reflow temperature local timing history node propagation aggregation representation feature vector, including: calculating the positional division of the sequence of the reflow temperature local timing energy significant descriptors and the sequence of the reflow temperature local timing energy time attenuation factor, using the obtained reflow temperature local timing energy weight as a weighting coefficient, and calculating the positional weighted sum of the sequence of the historical reflow temperature local timing implicit correlation feature vectors to obtain the reflow temperature local timing history node propagation aggregation representation feature vector.

[0093] Optionally, in one embodiment of the present invention, the reflow temperature local timing history node propagation aggregation representation feature vector and the current reflow temperature local timing implicit association feature vector are fused to obtain the reflow temperature spatiotemporal attenuation propagation representation vector, including: based on the energy significance descriptor corresponding to the current reflow temperature local timing implicit association feature vector, calculating the position-weighted sum of the reflow temperature local timing history node propagation aggregation representation feature vector and the current reflow temperature local timing implicit association feature vector to obtain the reflow temperature spatiotemporal attenuation propagation representation vector.

[0094] Optionally, in one embodiment of the present invention, based on the mean and standard deviation of each reflow temperature local time series implicit correlation feature vector in the sequence of the reflow temperature local time series implicit correlation feature vector, the energy significant descriptors of each reflow temperature local time series implicit correlation feature vector are calculated to obtain a sequence of reflow temperature local time series energy significant descriptors, including: calculating the mean and standard deviation of each reflow temperature local time series implicit correlation feature vector in the sequence of the reflow temperature local time series implicit correlation feature vector to obtain a sequence of reflow temperature local means and a sequence of reflow temperature local standard deviations; sorting the reflow temperature local time series implicit correlation feature vectors and the reflow temperature local means of each group corresponding to the sequence of the reflow temperature local time series implicit correlation feature vector and the sequence of the reflow temperature local mean by position. After the difference, each position characteristic value in the sequence of the obtained differential characteristic vectors is modulated to the fourth power to obtain a sequence of reflow temperature local timing modulation characteristic vectors; the expected value of each reflow temperature local timing modulation characteristic vector in the sequence of the reflow temperature local timing modulation characteristic vector is calculated to obtain a sequence of reflow temperature local timing positive expectation factors; the fourth power modulation value of each reflow temperature local standard deviation in the sequence of the reflow temperature local standard deviation is calculated to obtain a sequence of reflow temperature local timing inverse expectation factors; each group of corresponding reflow temperature local timing positive expectation factors and reflow temperature local timing inverse expectation factors in the sequence of the reflow temperature local timing positive expectation factors and the sequence of the reflow temperature local timing inverse expectation factors are divided to obtain a sequence of the reflow temperature local timing energy significance descriptors.

[0095] Optionally, in one embodiment of the present invention, the energy time attenuation factor of each historical reflow temperature local time series implicit correlation feature vector in the sequence of the historical reflow temperature local time series implicit correlation feature vector is calculated relative to the current reflow temperature local time series implicit correlation feature vector to obtain a sequence of reflow temperature local time series energy time attenuation factors, including: respectively calculating the reflow temperature timestamp corresponding to the current reflow temperature local time series implicit correlation feature vector and the reflow temperature timestamp corresponding to each historical reflow temperature local time series implicit correlation feature vector, subtracting them from each other and rounding them down to obtain a sequence of time span values; calculating the square of each time span value in the sequence of time span values, dividing the obtained sequence of span square modulation values ​​by the square of the time attenuation inverse scaling parameter by position and multiplying them by the attenuation rate positive scaling parameter by position to obtain a sequence of time series span energy attenuation coefficients; using each time series span energy attenuation coefficient in the sequence of time series span energy attenuation coefficients as an exponential power, calculating the natural exponential function value with the natural constant e as the base to obtain the sequence of reflow temperature local time series energy time attenuation factors.

[0096] Specifically, the sequence of the local temporal implicit correlation feature vectors of the reflow temperature is input into the feature message propagation network based on the spatiotemporal transfer characteristics of the node potential energy and processed using the following node feature message propagation formula to obtain the spatiotemporal attenuation propagation representation vector of the reflow temperature; wherein the node feature message propagation formula is:

[0097]

[0098]

[0099]

[0100]

[0101]

[0102] in, is the sequence of implicitly associated characteristic vectors of the reflow temperature local timing, and are the ( ) and The implicit correlation feature vector of the local timing of the reflow temperature, is the sequence of implicit correlation feature vectors of the reflow temperature local timing. The implicit correlation feature vector of the local timing of the reflow temperature, For the The first implicit correlation feature vector of the local timing of the reflow temperature Position feature values, For the The length of the implicit correlation feature vector of the local timing of the reflow temperature, For the The mean of the implicit correlation feature vectors of the local timing of the reflow temperature, For the The standard deviation of the implicit correlation eigenvector of the local timing of the reflow temperature, Indicates the calculation of expected value, It is The energy significant descriptor of the implicit correlation feature vector of the local timing of the reflow temperature, represents the exponential function value with the natural constant e as the base, is a positive scaling parameter that controls the decay rate, is the inverse scaling parameter that controls the time decay period, and Respectively represent and The timestamp of the implicit correlation feature vector of the reflow temperature local timing, Indicates a round-down operation. For the The energy significant descriptor of the implicit correlation feature vector of the local timing of the reflow temperature, and is the trainable weight hyperparameter, is the vector representing the spatiotemporal attenuation propagation of the reflow temperature.

[0103] Specifically, the feature message propagation network based on the spatiotemporal transfer characteristics of node potential energy first calculates the mean and standard deviation of the local temporal implicit correlation feature vectors of reflow temperature corresponding to each node in the sequence of local temporal implicit correlation feature vectors of reflow temperature to obtain an energy-significant descriptor. The energy-significant descriptor is used to quantify the energy characteristics of the local temporal implicit correlation features of reflow temperature at each node. This step helps identify which local time periods have the most significant reflow temperature changes. The energy-significant descriptor provides a basis for subsequent feature weight assignment, allowing the model to focus more on time points that have a significant impact on the reaction. Next, timestamps are extracted from the sequence of local temporal implicit correlation feature vectors of reflow temperature to assign time information to the local temporal implicit correlation feature vectors of reflow temperature corresponding to each node in this sequence. This is crucial for understanding the time dependence of the reaction process. In other words, the timestamp sequence enables the model to capture changes in the time dimension, providing essential information for temporal analysis. Then, by distinguishing the current reflux temperature local temporal implicit correlation feature vector from the historical reflux temperature local temporal implicit correlation feature vector, we can clarify the relationship between the reflux reaction state at the current time point and its past state, thereby better understanding and predicting future reaction trends. This allows us to predict and control the dripping rate at the next time point based on the temporal dynamic changes and trends of the reflux temperature. Next, we calculate the attenuation factor of the historical reflux temperature local temporal implicit correlation feature vector relative to the current reflux temperature local temporal implicit correlation feature vector. This can be used to measure the degree to which the influence of the reflux temperature local temporal implicit correlation characteristics at the historical node on the reflux temperature local temporal implicit correlation characteristics at the current node is weakened over time. The use of this attenuation factor helps the model more rationally analyze the impact of the local temporal node characteristics of the reflux temperature in each local time period on the current reflux temperature change, thereby preventing outdated information from misleading decision-making. Then, the sequence of the historical reflow temperature local temporal implicit correlation feature vectors is weightedly aggregated using the reflow temperature local temporal energy significance descriptor as a positive adjustment factor and the reflow temperature local temporal energy time attenuation factor as a negative adjustment factor. Temporal propagation aggregation strengthens the reflow temperature local temporal semantic information in the historical nodes that is related to the energy significance of the current node, while weakening the influence of the reflow temperature local temporal characteristics attenuating over time. Finally, the reflow temperature local temporal historical node propagation aggregation representation feature vector and the current reflow temperature local temporal implicit correlation feature vector are fused to generate the final reflow temperature spatiotemporal attenuation propagation representation vector. It should be understood that the fusion operation integrates historical and current node features, namely the historical reflow temperature local temporal semantic propagation information and the current reflow temperature local temporal feature information, to form a reflow temperature spatiotemporal attenuation propagation feature representation containing rich reflow temperature local temporal information.This comprehensive representation vector of the spatiotemporal attenuation propagation of the reflux temperature can better reflect the dynamic changes during the reaction process and provide a more accurate basis for the next step of dripping speed control.

[0104] Specifically, in S136, the dripping acceleration control center inputs the reflow temperature spatiotemporal attenuation propagation representation vector into a decoder-based dripping acceleration controller to obtain a control instruction. The control instruction includes a decoded recommended value for the dripping acceleration value at the next time point. In other words, decoding regression is performed using the local temporal semantic spatiotemporal attenuation propagation representation features of the reflow temperature to predict the dripping acceleration value at the next time point, thereby obtaining a decoded recommended value for the dripping acceleration value at the next time point.

[0105] Preferably, inputting the reflow temperature spatiotemporal attenuation propagation representation vector into a decoder-based drip acceleration controller to obtain a control instruction comprises:

[0106] Subtract the zero norm of the reflow temperature spatiotemporal attenuation propagation representation vector from the length of the reflow temperature spatiotemporal attenuation propagation representation vector to obtain a reflow temperature spatiotemporal attenuation propagation isolated representation value;

[0107] Calculating the logarithm of the square of the isolated representation value of the spatiotemporal attenuation propagation of the reflow temperature and the sum of the isolated representation value of the spatiotemporal attenuation propagation of the reflow temperature to obtain the spatiotemporal attenuation propagation information order value of the reflow temperature;

[0108] Calculate a power function with each eigenvalue of the reflow temperature spatiotemporal attenuation propagation representation vector as the base, the difference of the reflow temperature spatiotemporal attenuation propagation isolated representation value minus one as the exponent, and perform a dot multiplication with the reflow temperature spatiotemporal attenuation propagation information order value to obtain a reflow temperature spatiotemporal attenuation propagation leading vector;

[0109] After performing a dot product of the difference between the reflow temperature spatiotemporal attenuation propagation representation vector and the reflow temperature spatiotemporal attenuation propagation isolated representation value minus one, the dot product is performed with the inverse of the reflow temperature spatiotemporal attenuation propagation isolated representation value to obtain a reflow temperature spatiotemporal attenuation propagation field constraint vector;

[0110] Calculating an exponential function with a natural constant as the base and each eigenvalue of the reflow temperature space-time attenuation propagation field constraint vector as the exponent to obtain a reflow temperature space-time attenuation propagation field bias vector;

[0111] Performing point addition of the reflow temperature spatiotemporal attenuation propagation leading vector and the reflow temperature spatiotemporal attenuation propagation field bias vector to obtain an optimized reflow temperature spatiotemporal attenuation propagation representation vector;

[0112] The optimized reflow temperature spatiotemporal attenuation propagation representation vector is input into the decoder-based drip acceleration controller to obtain the control instruction.

[0113] Specifically, the spatiotemporal attenuation propagation of the reflow temperature is represented by a vector, for example, The optimization process is expressed as:

[0114]

[0115]

[0116] in, is the vector representing the spatiotemporal attenuation propagation of the reflow temperature, represents the length of the vector representing the spatiotemporal attenuation propagation of the reflow temperature, represents the zero norm of the eigenvector, represents the optimized endoscope detection site state-normal state cascade isolated representation value, To calculate the power function with each eigenvalue of the reflow temperature spatiotemporal attenuation propagation representation vector as the base, the difference between the optimized endoscope detection site state-normal state cascade isolated representation value minus one is the exponential value. Indicates point multiplication by position, Indicates adding by position point, represents the natural exponential function, The optimized spatiotemporal attenuation propagation vector of the reflow temperature is represented.

[0117] Here, the sequence of the local temporal implicit correlation feature vectors of the reflow temperature respectively expresses the short-range-long-range bidirectional temporal correlation characteristics of the reflow temperature in the local time domain. Therefore, when propagating the characteristic message based on the spatiotemporal transmission characteristics of the node potential energy, the energy significance difference of the timing nodes caused by the timing feature differences in each local time domain and the full-domain timing offset caused by the different spatiotemporal attenuation characteristics of each node are taken into account. It is expected to further improve the regression comprehensibility of the full-time aggregation sequence of the reflow temperature spatiotemporal attenuation propagation representation vector, thereby improving the accuracy of the control instructions obtained by the decoder-based drip acceleration controller.

[0118] Thus, for the high-dimensional feature manifold of the reflux temperature spatiotemporal attenuation propagation representation vector, the eigenvalues ​​of the feature set are used as the vector field representation of the aggregation dimension. The superposition value of the vector field of the reflux temperature spatiotemporal attenuation propagation representation vector at isolated zero positions is used as order information to fix the local position of the eigenvalues ​​of the feature set. A bias is added as a reward for the reversibility of the characteristic regression distribution field of the reflux temperature spatiotemporal attenuation propagation representation vector to achieve mapping target tracking of the regression distribution of the reflux temperature spatiotemporal attenuation propagation representation vector to the eigenvalue position, so that the feature set of the reflux temperature spatiotemporal attenuation propagation representation vector perceives the mapping migration to the aggregate distribution. By improving the understandability of the aggregate mapping regression of the reflux temperature spatiotemporal attenuation propagation representation vector, the accuracy of the control instructions obtained by the reflux temperature spatiotemporal attenuation propagation representation vector input to the decoder-based drip acceleration controller is improved. In this way, the dripping acceleration of the zinc hydrochloric acid solution can be more accurately and dynamically adjusted according to the real-time reflux temperature, avoiding fluctuations in reaction conditions caused by improper dripping acceleration and ensuring smooth reaction.

[0119] Specifically, in S137, the droplet addition speed control center transmits the control instruction to the solution droplet addition control actuator to control the droplet addition speed of the zinc-hydrochloric acid solution. It should be understood that the droplet addition speed control center transmits the control instruction to the solution droplet addition control actuator to control the droplet addition speed of the zinc-hydrochloric acid solution. In this way, predictive control of the droplet addition speed of the zinc-hydrochloric acid solution can be performed based on the real-time reflux temperature, thereby achieving adaptive dynamic control of the reflux reaction and droplet addition process in a more intelligent manner, ensuring consistency and controllability of reaction conditions.

[0120] The comparison of the effects of the traditional reflux strategy and the dynamic reflux strategy of the present application is shown in Table 1 below:

[0121] Table 1 Comparison of the effects of traditional reflux strategy and the dynamic reflux strategy of this application

[0122]

[0123] Table 1 Comparison of the effects of traditional reflux strategy and the dynamic reflux strategy of this application

[0124]

[0125] As can be seen from the data in Table 1, compared with the traditional reflux control scheme, the dynamic reflux strategy provided in this application can significantly shorten the reflux reaction time to improve reaction efficiency. In addition, for zinc pyridine carboxylate, the dynamic reflux strategy can significantly reduce its average surface particle size to improve catalyst performance.

[0126] Preparation of Double Metal Cyanide Catalyst DMC

[0127] In the technical solution of the present application, the double metal cyanide catalyst DMC is prepared using a traditional method, which can be specifically prepared according to the following steps:

[0128] Dissolve 3.6 g of K3[Co(CN)6] in 80 mL of aqueous solution to prepare a solution, and dissolve 9.6 g of ZnCl2 in a mixture of 90 mL of water and 90 mL of tert-butanol to prepare a solution. Under strong stirring, add the K3[Co(CN)6] solution dropwise to the ZnCl2 solution at a rate of 60 drops / minute. After the addition is completed, maintain strong stirring and allow the mixed solution to continue reacting for 5 hours. The resulting white suspension is washed with a mixture of 100 mL of water and 100 mL of tert-butanol under strong stirring until the potassium ion detection reagent Na3Co(NO2)6 can no longer detect K in the mixed solution. + The mixed solution was filtered and then placed in a vacuum oven at 120°C to dry overnight. The obtained DMC (Zn3[Co(CN)6]2: 1.2ZnCl2•2.5 t The solid powder of BuOH·3.2 H2O catalyst is light yellow. The WXRD spectrum of the prepared DMC catalyst is as follows Figure 2 As shown, for the bimetallic catalyst, its characteristic peaks appear at 2θ=15.79,20.35°, which is consistent with the structure Zn3[Co(CN)6]2:1.2 ZnCl2•2.5 t The characteristic peak position of BuOH·3.2 H2O is consistent with that of zinc-cobalt bimetallic catalyst.

[0129] Composite catalyst preparation

[0130] Preparation method of composite catalyst: 100 mL toluene and 10 mL ethanol were added to a stirring bar, followed by the addition of 1 mol of the trifluoro-ethoxy-pyridine carboxylic acid zinc complex and DMCZn3[Co(CN)6]2: 1.2ZnCl2•2.5 t 20 mol of BuOH·3.2H2O was placed in a high-pressure reactor, and then the high-pressure reactor was pressurized to 0.5 MPa under argon, and then ultrasonically dissolved for 30 min. After the dissolution was completed, the reaction was carried out at 80°C for 16 h.

[0131] After the reaction is completed, the mixture is cooled to room temperature, and the suspended solid is washed with 80 mL of acetone. After washing three times, the solid is filtered to obtain a white solid, which is then dried in a vacuum drying oven to obtain a trifluoro-ethoxy-pyridine carboxylic acid zinc / DMC composite catalyst. The WXRD spectrum of the obtained trifluoro-ethoxy-pyridine carboxylic acid zinc / DMC composite catalyst is shown in FIG. Figure 3As shown, the Zn(III) / DMC composite catalyst system clearly exhibits the crystallization peak characteristics of both Zn(III) and DMC catalysts. For the Zn(III) catalyst, characteristic peaks appear at 2θ = 12.7, 15.3, and 19.7°; for the DMC catalyst, characteristic peaks appear at 2θ = 15.79 and 20.35°. The WXRD curve of the Zn(III) / DMC composite catalyst shows distinct and sharp crystallization peaks for both Zn(III) and DMC, indicating complete recombination between Zn(III) and DMC, and that this recombination process has no effect on the crystallization morphology of the catalyst particles.

[0132] Based on this, in the technical solution of the present invention, a method for preparing a zinc pyridinecarboxylate complex composite catalyst is proposed. Figure 4 Schematic flow chart of the preparation method of the zinc pyridine carboxylate complex composite catalyst according to an embodiment of the present invention. Figure 4 As shown, the preparation method of the zinc pyridinecarboxylate complex composite catalyst includes: S1, adding a zinc pyridinecarboxylate complex, a double metal cyanide catalyst and a mixed solvent into a high-pressure reactor, wherein the molar ratio of the zinc pyridinecarboxylate complex to the double metal cyanide catalyst is 1:1-60; S2, dissolving the zinc pyridinecarboxylate complex, the double metal cyanide catalyst and the mixed solvent to obtain a raw material mixed liquid; S3, subjecting the raw material mixed liquid to an inert gas atmosphere reaction to obtain a suspension, wherein the reaction temperature of the inert gas atmosphere reaction is 20°C-150°C, the reaction time is 12 h-38 h; the pressure is 0.2 MPa-1 MPa; the gas used in the inert gas atmosphere reaction is high-purity nitrogen / argon; S4, cooling the suspension to room temperature, adding an organic solvent, filtering and vacuum drying to obtain the zinc pyridinecarboxylate complex composite catalyst.

[0133] Optionally, in one embodiment of the present invention, the mixed solvent is a mixed solvent comprising a polar solvent and a non-polar solvent, the polar solvent is selected from one or more of water, acetonitrile, methanol, ethanol, acetone, isopropanol, acetic acid, and ether, and the non-polar solvent is selected from one or more of toluene, benzene, carbon tetrachloride, hexane, and dichloromethane.

[0134] Optionally, in one embodiment of the present invention, the organic solvent is selected from any one or more of ethyl acetate, ethanol, methanol, and dichloromethane, and the amount of the organic solvent is 2-20 times the volume of the suspension.

[0135] The zinc pyridinecarboxylate complexes prepared in the above-mentioned Schemes 1-6 and Comparative Schemes 1-6 were used to prepare composite catalysts according to the above-mentioned synthesis method, which are respectively recorded as Application Examples 1-6 and Comparative Application Examples 1-6. Specific parameters are described in Table 2 below.

[0136] Table 2 Parameters for preparing composite catalysts in Application Examples 1-3 and Comparative Application Examples 1-3

[0137]

[0138] Table 2: Parameters for preparing composite catalysts in application examples 4-6 and comparative application examples 4-6

[0139]

[0140] As can be seen from the application examples and comparative application examples in Table 2, the zinc pyridine carboxylate complex prepared using a dynamic reflux strategy is more likely to form a synergistic effect with the bimetallic catalyst during the composite process. During the preparation of the zinc carboxylate complex, a temperature sensor is introduced to monitor and collect reflux temperature data in real time. This reflux temperature data is then transmitted to the droplet velocity control center for processing. In the droplet velocity control center, a data processing and analysis algorithm based on artificial intelligence and deep learning is used to perform time series analysis on the reflux temperature data, thereby capturing and characterizing the temporal dynamic information propagation characteristics of the reflux temperature. In this way, the temporal information propagation semantics of the reflux temperature are used to predict the droplet velocity value at the next time point and automatically control the droplet velocity of the zinc hydrochloric acid solution. In this way, predictive control of the droplet velocity of the zinc hydrochloric acid solution can be performed based on the real-time reflux temperature, thereby achieving adaptive dynamic control of the reflux reaction and droplet addition process in a more intelligent manner to ensure the consistency and controllability of the reaction conditions. The prepared zinc carboxylate complex has a smaller average surface particle size. A smaller average surface particle size generally has a higher surface energy. Surface energy is the energy generated by unsaturated bonds between atoms or molecules on the surface of a substance. The high surface energy makes zinc carboxylate particles more susceptible to adsorption, reaction, or bonding with other substances, thereby facilitating the formation of a composite catalyst with the bimetallic catalyst. Zinc carboxylate particles with a smaller average surface diameter diffuse more rapidly within the catalyst system. This facilitates faster diffusion of zinc carboxylate particles onto the surface or within the interstices of the bimetallic catalyst during the preparation of the composite catalyst, forming a uniform composite structure. This rapid diffusion also helps improve the catalytic efficiency and stability of the composite catalyst.

[0141] In summary, the smaller average surface particle size of zinc carboxylate helps it to form a composite catalyst with the bimetallic catalyst by increasing the specific surface area, improving the surface energy, enhancing the diffusion rate, strengthening the interfacial interaction, and promoting the dispersion and uniformity of the catalyst, and may improve the catalytic performance and stability of the composite catalyst.

[0142] It is worth mentioning that in the technical solution of the present invention, by containing a specific zinc pyridine carboxylate complex, DMC catalyst, polar solvent, non-polar solvent of different functional groups, high temperature reaction preparation is carried out by autoclave.Specific, in the preparation method of the present invention, autoclave is used to make the two metals in zinc pyridine carboxylate and bimetallic catalyst more easily form active sites under high temperature inert gas atmosphere environment, and then play a synergistic effect; Make the selectivity and activity of the catalyst higher, especially for two types of catalysts, can make the metals interact with each other under high pressure to be enhanced, improve the structural stability of the catalyst, and high temperature environment is conducive to the synthesis of stable catalyst products during the synthesis process, while the intermediate that is easily decomposed at high temperature can be stabilized under inert gas atmosphere conditions, which is conducive to the synthesis of composite catalysts.Compared to other preparation methods, inert gas atmosphere reaction can obtain more delicate catalyst particles, smaller catalyst particle size and more excellent synergistic effect, so that the catalyst has more efficient and stable catalytic performance in subsequent polymerization reactions.

[0143] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above and that the invention can be embodied in other specific forms without departing from the spirit or essential characteristics of the invention. Therefore, the embodiments should be considered in all respects as illustrative and non-restrictive, and the scope of the invention is defined by the appended claims, not the foregoing description, and all variations within the meaning and range of equivalents of the claims are intended to be encompassed therein. Any reference to a figure in a claim should not be construed as limiting the claim to which it relates.

[0144] In addition, it is obvious that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units recited in a device claim can also be implemented by one unit through software or hardware.

[0145] Finally, it should be noted that the above description has been provided for purposes of illustration and description. Furthermore, the above embodiments are intended only to illustrate the technical solutions of the present invention and are not intended to be limiting. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art will appreciate that the technical solutions of the present invention may be modified or replaced with equivalents without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for preparing a zinc pyridinecarboxylate complex composite catalyst, characterized in that: include: Adding a zinc pyridine carboxylate complex, a double metal cyanide catalyst and a mixed solvent into a high-pressure reaction kettle, wherein the molar ratio of the zinc pyridine carboxylate complex to the double metal cyanide catalyst is 1:5-60; Dissolving the zinc pyridine carboxylate complex, the double metal cyanide catalyst and the mixed solvent to obtain a raw material mixed solution; The raw material mixture is subjected to an inert gas atmosphere reaction to obtain a suspension, wherein the reaction temperature of the inert gas atmosphere reaction is 20° C.-150° C., the reaction time is 12 h-38 h; and the pressure of the inert gas atmosphere is 0.2-1 MPa; The suspension is cooled to room temperature, and an organic solvent is added to filter and vacuum-dry to obtain a zinc pyridinecarboxylate complex composite catalyst; The preparation method of the zinc pyridine carboxylate complex comprises the following steps: Dissolving a zinc source with dilute hydrochloric acid and stirring to obtain a zinc hydrochloric acid solution; Dissolving a pyridine carboxylic acid containing an electron-withdrawing substituent group and a pyridine carboxylic acid containing an electron-donating substituent group in deionized water to form a pyridine carboxylic acid mixed solution; Slowly adding the zinc hydrochloric acid solution dropwise to the pyridine carboxylic acid mixed solution to perform a reflux reaction; Cooling, precipitating crystals, washing, and drying to obtain a zinc pyridinecarboxylate complex intermediate containing crystal water; removing crystal water from the zinc pyridine carboxylate complex intermediate at a high temperature of 110 to 150° C. to obtain the zinc pyridine carboxylate complex; The zinc hydrochloric acid solution is slowly added dropwise to the pyridine carboxylic acid mixed solution to perform a reflux reaction, which comprises: Obtaining a time series of reflow temperature collected by a temperature sensor; Transmitting the time series of the reflux temperature to a dripping acceleration control center via a wireless communication module; In the dripping acceleration control center, the time series of the reflux temperature is segmented into a sequence based on a predetermined sampling period and each subsequence is data structured to obtain a sequence of local time series input vectors of the reflux temperature; In the dripping acceleration control center, each reflux temperature local time series input vector in the sequence of the reflux temperature local time series input vector is respectively input into a reflux temperature time series feature extractor based on a bidirectional LSTM model to obtain a sequence of reflux temperature local time series implicit correlation feature vectors; In the dripping acceleration control center, the sequence of the local temporal implicit correlation feature vectors of the reflow temperature is input into a feature message propagation network based on the spatiotemporal transfer characteristics of node potential energy to obtain a spatiotemporal attenuation propagation representation vector of the reflow temperature; In the dripping acceleration control center, the reflux temperature spatiotemporal attenuation propagation representation vector is input into a dripping acceleration controller based on a decoder to obtain a control instruction, wherein the control instruction includes a decoded recommended value of the dripping acceleration value at a next time point; The droplet acceleration control center transmits the control instruction to the solution droplet control actuator to control the droplet acceleration value of the zinc hydrochloric acid solution.

2. The method for preparing the zinc pyridinecarboxylate complex composite catalyst according to claim 1, characterized in that: The mixed solvent is a mixed solvent comprising a polar solvent and a non-polar solvent, wherein the polar solvent is selected from one or more of water, acetonitrile, methanol, ethanol, acetone, isopropanol, acetic acid, and ether, and the non-polar solvent is selected from one or more of toluene, benzene, carbon tetrachloride, hexane, and dichloromethane.

3. The method for preparing the zinc pyridinecarboxylate complex composite catalyst according to claim 1, characterized in that: The organic solvent is selected from any one or more of ethyl acetate, ethanol, methanol, and dichloromethane, and the amount of the organic solvent is 2-20 times the volume of the suspension.

4. The method for preparing the zinc pyridinecarboxylate complex composite catalyst according to claim 1, characterized in that: The zinc source is selected from any one of zinc chloride, zinc sulfate (ZnSO4), zinc chlorate [Zn(ClO3)2], zinc nitrate [Zn(NO3)2], zinc acetate [Zn(OAc)2], zinc oxide and zinc hydroxide; the dilute hydrochloric acid refers to an aqueous solution of HCl with a pH value between 0 and 5.

5. The method for preparing the zinc pyridinecarboxylate complex composite catalyst according to claim 1, characterized in that: The electron-withdrawing substituent group is selected from -CF3, -CN, -F, -Cl, -Br, and -I; the pyridinecarboxylic acid containing an electron-withdrawing substituent group is selected from any one or more of 4-chloro-2,6-pyridinedicarboxylic acid, 4-bromo-2,6-pyridinedicarboxylic acid, 4-trifluoro-2,6-pyridinedicarboxylic acid, and 4-fluoro-2,6-pyridinedicarboxylic acid; the electron-donating substituent group is selected from any one or more of -O-, -NHR3, -NH2, -OH, -OR4, -R5, and -Ph, wherein R3, R4, and R5 are any alkyl groups; the pyridinecarboxylic acid containing an electron-donating substituent group is selected from any one or more of 4-methyl-2,6-pyridinedicarboxylic acid, 4-ethyl-2,6-pyridinedicarboxylic acid, 4-ethoxy-2,6-pyridinedicarboxylic acid, 4-phenyl-2,6-pyridinedicarboxylic acid, and 4-methoxy-2,6-pyridinedicarboxylic acid.

6. The method for preparing the zinc pyridinecarboxylate complex composite catalyst according to claim 1, characterized in that: In the dripping acceleration control center, the sequence of the local temporal implicit correlation feature vectors of the reflow temperature is input into a feature message propagation network based on the spatiotemporal transfer characteristics of node potential energy to obtain a reflow temperature spatiotemporal attenuation propagation representation vector, including: Based on the mean and standard deviation of each reflow temperature local timing implicit correlation feature vector in the sequence of the reflow temperature local timing implicit correlation feature vector, calculate the energy significant descriptor of each reflow temperature local timing implicit correlation feature vector to obtain a sequence of reflow temperature local timing energy significant descriptors; Extracting the timestamp of each reflow temperature local time series implicit correlation feature vector in the sequence of the reflow temperature local time series implicit correlation feature vector to obtain a sequence of reflow temperature timestamps; The local timing implicit correlation feature vector of the reflow temperature corresponding to the current time point in the sequence of the local timing implicit correlation feature vector of the reflow temperature is used as the current local timing implicit correlation feature vector of the reflow temperature, and the local timing implicit correlation feature vectors of the reflow temperature corresponding to other time points are used as the historical local timing implicit correlation feature vectors of the reflow temperature to obtain a sequence of the current local timing implicit correlation feature vector of the reflow temperature and the historical local timing implicit correlation feature vector of the reflow temperature; Calculating the energy time decay factor of each historical reflow temperature local timing implicit correlation feature vector in the sequence of the historical reflow temperature local timing implicit correlation feature vector relative to the current reflow temperature local timing implicit correlation feature vector to obtain a sequence of reflow temperature local timing energy time decay factors; Using the sequence of the reflow temperature local timing energy significant descriptors as positive adjustment factors and the sequence of the reflow temperature local timing energy time decay factors as negative adjustment factors, the sequence of the historical reflow temperature local timing implicit correlation feature vectors is subjected to timing propagation aggregation to obtain the reflow temperature local timing historical node propagation aggregation representation feature vector; Fusion of the reflow temperature local time series historical node propagation aggregation representation feature vector and the current reflow temperature local time series implicit association feature vector to obtain the reflow temperature spatiotemporal attenuation propagation representation vector; Among them, taking the sequence of the significant descriptors of the local temporal energy of the reflow temperature as the positive adjustment factor and taking the sequence of the local temporal energy time decay factor of the reflow temperature as the negative adjustment factor, the sequence of the local temporal implicit correlation feature vectors of the historical reflow temperature is subjected to temporal propagation aggregation to obtain the local temporal historical node propagation aggregation representation feature vector of the reflow temperature, including: calculating the positional division of the sequence of the significant descriptors of the local temporal energy of the reflow temperature and the sequence of the local temporal energy time decay factor of the reflow temperature, taking the obtained local temporal energy weight of the reflow temperature as the weighting coefficient, calculating the positional weighted sum of the sequence of the local temporal implicit correlation feature vectors of the historical reflow temperature to obtain the local temporal historical node propagation aggregation representation feature vector of the reflow temperature; Among them, the reflux temperature local timing history node propagation aggregation representation feature vector and the current reflux temperature local timing implicit association feature vector are integrated to obtain the reflux temperature spatiotemporal attenuation propagation representation vector, including: based on the energy significant descriptor corresponding to the current reflux temperature local timing implicit association feature vector, the position-weighted sum of the reflux temperature local timing history node propagation aggregation representation feature vector and the current reflux temperature local timing implicit association feature vector is calculated to obtain the reflux temperature spatiotemporal attenuation propagation representation vector.

7. The method for preparing the zinc pyridinecarboxylate complex composite catalyst according to claim 6, characterized in that: Based on the mean and standard deviation of each reflow temperature local timing implicit correlation feature vector in the sequence of the reflow temperature local timing implicit correlation feature vector, calculating the energy significant descriptor of each reflow temperature local timing implicit correlation feature vector to obtain a sequence of reflow temperature local timing energy significant descriptors, including: Calculating the mean and standard deviation of each reflow temperature local time series implicit correlation feature vector in the sequence of the reflow temperature local time series implicit correlation feature vector to obtain a sequence of reflow temperature local means and a sequence of reflow temperature local standard deviations; After performing positional differentiation on each group of corresponding local timing implicitly associated feature vectors of reflow temperature and local mean values ​​of reflow temperature in the sequence of local timing implicitly associated feature vectors of reflow temperature and the sequence of local mean values ​​of reflow temperature, performing fourth power modulation on each positional feature value in the obtained sequence of differential feature vectors to obtain a sequence of local timing modulation feature vectors of reflow temperature; Calculating the expected value of each reflow temperature local timing modulation feature vector in the sequence of reflow temperature local timing modulation feature vectors to obtain a sequence of reflow temperature local timing positive expected factors; Calculating the fourth power modulation value of each local standard deviation of the reflow temperature in the sequence of local standard deviations of the reflow temperature to obtain a sequence of local timing inverse expectation factors of the reflow temperature; Each corresponding group of reflow temperature local timing positive expected factors and reflow temperature local timing negative expected factors in the sequence of reflow temperature local timing positive expected factors and the sequence of reflow temperature local timing negative expected factors are divided to obtain the sequence of reflow temperature local timing energy significant descriptors.

8. The method for preparing the zinc pyridinecarboxylate complex composite catalyst according to claim 7, characterized in that: Calculating the energy time decay factor of each historical reflow temperature local timing implicit correlation feature vector in the sequence of the historical reflow temperature local timing implicit correlation feature vector relative to the current reflow temperature local timing implicit correlation feature vector to obtain a sequence of reflow temperature local timing energy time decay factors, including: Respectively calculating the reflow temperature timestamp corresponding to the current reflow temperature local time series implicit correlation feature vector and the reflow temperature timestamp corresponding to each historical reflow temperature local time series implicit correlation feature vector, subtracting them from each other and rounding them down to obtain a sequence of time span values; After calculating the square of each time span value in the sequence of time span values, the obtained sequence of span square modulation values ​​is divided by the square of the time decay inverse scaling parameter by position and multiplied by the decay rate positive scaling parameter by position to obtain a sequence of time series span energy decay coefficients; Taking each timing span energy attenuation coefficient in the sequence of timing span energy attenuation coefficients as an exponential power, a natural exponential function value with a natural constant e as a base is calculated to obtain a sequence of the reflow temperature local timing energy time attenuation factors.

9. A zinc pyridine carboxylate complex composite catalyst, characterized in that: The catalyst is prepared by the method for preparing the zinc pyridinecarboxylate complex composite catalyst according to any one of claims 1 to 8.

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