Synthetic method of high bio-based waterborne polyurethane resin

Abstract

The invention relates to the technical field of material synthesis, and discloses a high bio-based waterborne polyurethane resin synthesis method which comprises the following steps: determining a green synthesis protocol corresponding to key synthesis equipment, and setting a bio-based conversion threshold value corresponding to the key synthesis equipment; calculating the biological carbon chain continuation degree and the isocyano group allowance in the bio-based raw material polycondensation reaction process, and setting a process compensation coefficient corresponding to a bio-based conversion threshold value; analyzing the chemical bonding degree corresponding to the raw material components of the bio-based raw material, analyzing the hard segment microcell form of the bio-based raw material in the resin emulsion, and evaluating the resin structure stability index of the raw material components; calculating the colloid stability of the bio-based raw material under a preset storage condition, generating a process regulation and control instruction of the synthesis process, and performing synthesis treatment on the high bio-based waterborne polyurethane resin by utilizing the bio-based raw material to obtain a synthesis result. According to the invention, the synthesis efficiency of the bio-based waterborne polyurethane resin can be improved.

Description

Technical Field

[0001] The invention relates to a method for synthesizing a high-biobased waterborne polyurethane resin, and belongs to the field of material synthesis. Background Art

[0002] Waterborne polyurethane resins are widely used in many fields such as coatings, adhesives, and leather finishing agents. With the continuous enhancement of environmental awareness and the popularization of the concept of sustainable development, high-biobased waterborne polyurethane resins have attracted more and more attention due to their renewable sources and environmental friendliness. The market demand for them is showing a rapid growth trend. At present, traditional waterborne polyurethane resin synthesis methods are mainly based on petroleum-based raw materials. Not only do they face problems such as limited raw material resources and large price fluctuations, but they may also produce a large number of environmentally unfriendly by-products during the synthesis process. Although there are some synthesis methods for bio-based waterborne polyurethane resins, most of them have defects such as low bio-based content, complex synthesis process, and unstable product performance. Existing synthesis methods often make it difficult to accurately control the reaction process. During the synthesis process, the control of reaction conditions mainly depends on the experience of the operator, and the reaction parameters are adjusted by regularly sampling and testing the reaction products. This method is inefficient, and due to the time interval problem of detection, it is difficult to track the reaction progress in real time. Once the reaction deviates, it is difficult to correct it in time, resulting in uneven product quality, which makes it difficult to meet the growing market demand for high-quality and highly bio-based waterborne polyurethane resins. Therefore, a method that can effectively improve the synthesis efficiency of bio-based waterborne polyurethane resins is needed. Summary of the Invention

[0003] The present invention provides a method and system for synthesizing a high-biobased waterborne polyurethane resin, the main purpose of which is to improve the synthesis efficiency of the biobased waterborne polyurethane resin.

[0004] To achieve the above objectives, the present invention provides a method for synthesizing a highly bio-based waterborne polyurethane resin, comprising: Obtaining bio-based raw materials and a synthesis process for a high-biobased waterborne polyurethane resin, querying key synthesis equipment in the synthesis process, determining a green synthesis protocol corresponding to the key synthesis equipment, and setting a bio-based conversion threshold corresponding to the key synthesis equipment based on the green synthesis protocol; collecting in real time the thermal gradient parameter value, catalytic activity index, and phase separation characteristic value of the bio-based raw material during the polycondensation reaction process, calculating the biocarbon chain extension and isocyanate group residue during the polycondensation reaction process of the bio-based raw material based on the thermal gradient parameter value, the catalytic activity index, and the phase separation characteristic value, and setting a process compensation coefficient corresponding to the bio-based conversion threshold based on the biocarbon chain extension and the isocyanate group residue; Monitoring the particle size distribution and molecular weight distribution of the bio-based raw material in the resin emulsion of the polycondensation reaction, analyzing the chemical bonding degree corresponding to the raw material components of the bio-based raw material based on the particle size distribution and the molecular weight distribution, analyzing the hard segment micro-domain morphology of the bio-based raw material in the resin emulsion, and evaluating the resin structural stability index of the raw material components based on the chemical bonding degree and the hard segment micro-domain morphology; Recording electrokinetic potential records and organic release trajectories of the bio-based raw material during the polycondensation reaction, and calculating the colloidal stability of the bio-based raw material under preset storage conditions based on the electrokinetic potential records and the organic release trajectories; In combination with the process compensation coefficient, the resin structural stability index and the colloid uniform stability, a process control instruction of the synthesis process is generated. Based on the process control instruction, the bio-based raw material is used to perform a synthesis process of a high-bio-based waterborne polyurethane resin to obtain a synthesis result.

[0005] Optionally, determining the green synthesis protocol corresponding to the key synthesis equipment includes: Query the environmental compliance documents of the key synthetic equipment, perform multi-source data analysis on the environmental compliance documents, and obtain preliminary stipulations; Performing conflict resolution on the preliminary terms of the agreement to obtain standard terms of the agreement; The standard specification clauses are subjected to specification classification processing to obtain the green synthesis specification corresponding to the key synthesis equipment.

[0006] Optionally, setting the bio-based conversion threshold corresponding to the key synthesis equipment based on the green synthesis protocol includes: Performing specification semantic analysis on the green synthesis specification to obtain synthesis specification semantics; Extracting key specification semantics from the composite specification semantics, and calculating semantic correlation coefficients between the key specification semantics; extracting, from the synthetic specification semantics, specification constraints related to bio-based conversion based on the semantic association coefficient; Extracting key parameter indicators from the specification constraints and collecting equipment performance data and historical process data of the key synthesis equipment; Combining the equipment performance data with the historical process data, setting indicator parameter thresholds corresponding to the key parameter indicators; Based on the indicator parameter threshold, the bio-based conversion threshold corresponding to the key synthesis equipment is set.

[0007] Optionally, the calculation of the biocarbon chain extension and the isocyanate group remainder during the polycondensation reaction of the bio-based raw material by combining the thermal gradient parameter value, the catalytic activity index, and the phase separation characteristic value includes: Performing data synchronization and alignment processing on the thermal gradient parameter value, the catalytic activity index, and the phase separation characteristic value to obtain synchronous reaction time series data; Extracting reaction kinetic characteristics from the synchronous reaction time series data, and constructing a reaction characteristic matrix of the bio-based raw material based on the reaction kinetic characteristics; Calculating the biocarbon chain extension degree during the polycondensation reaction of the bio-based raw material based on the reaction characteristic matrix; The raw material spectrum data of the bio-based raw material during the polycondensation reaction is collected, and the isocyanate group residue of the bio-based raw material during the polycondensation reaction is calculated by combining the biological carbon chain extension and the raw material spectrum data.

[0008] Optionally, the step of calculating the biocarbon chain extension degree of the bio-based raw material polycondensation reaction process in combination with the reaction characteristic matrix includes: The biocarbon chain extension degree of the bio-based raw material polycondensation reaction process is calculated by the following formula: Where A represents the degree of extension of the biocarbon chain during the polycondensation reaction of bio-based raw materials. represents the standard degree of polymerization, represents the temperature contribution coefficient, represents the reaction rate constant at time t in the reaction characteristic matrix, represents the phase separation starting time, represents the end time of phase separation, Represents the thermal gradient of the reaction feature matrix at time t, represents the delay gain coefficient, represents the phase separation triggering time in the reaction characteristic matrix, Represents the total reaction time.

[0009] Optionally, the calculation of the isocyanate residue in the polycondensation reaction of the bio-based raw material by combining the bio-carbon chain extension and the raw material spectral data includes: performing noise reduction processing on the raw material spectrum data to obtain noise-reduced raw material spectrum data; performing baseline correction processing on the noise-reduced raw material spectral data to obtain corrected raw material spectral data; Extracting characteristic spectral peaks from the corrected raw material spectral data, and calculating characteristic peak intensities corresponding to the characteristic spectral peaks; The isocyanate residue in the polycondensation reaction of the bio-based raw material is calculated based on the bio-carbon chain extension and the characteristic peak intensity.

[0010] Optionally, analyzing the chemical bonding degree corresponding to the raw material components of the bio-based raw material by combining the particle size distribution map and the molecular weight distribution map includes: Performing multi-peak fitting analysis on the particle size distribution spectrum to obtain particle size distribution characteristics; Performing segmented integration processing on the molecular weight distribution graph to obtain polymer content; analyzing potential coupling mechanisms of the particle size distribution characteristics and the polymer content to chemical bonding of the bio-based feedstock; assigning bonding contributions of the particle size distribution characteristics and the polymer content based on the potential coupling mechanism to obtain a first contribution and a second contribution; Calculating bonding potential values corresponding to raw material components of the bio-based raw material based on the particle size distribution characteristics, the polymer content, the first contribution, and the second contribution; Based on the bonding potential value, the chemical bonding degree corresponding to the raw material components of the bio-based raw material is analyzed.

[0011] Optionally, the analyzing the hard segment microdomain morphology of the bio-based raw material in the resin emulsion includes: Performing transmission electron microscope imaging on the resin emulsion to obtain an original transmission electron microscope image; Performing enhancement processing on the original transmission electron microscope image to obtain an enhanced transmission electron microscope image; performing thresholding processing on the enhanced electron microscope image to obtain a threshold electron microscope image; Optimizing the morphology in the threshold electron microscope image to obtain an electron microscope wheel morphology image; The hard segment micro-domain features of the electron microscope morphology optimization image are extracted, and based on the hard segment micro-domain features, the hard segment micro-domain morphology of the bio-based raw material in the resin emulsion is analyzed.

[0012] Optionally, the calculating the colloidal stability of the bio-based raw material by combining the electrokinetic potential record and the organic escape trajectory includes: performing anomaly removal processing on the electrokinetic potential record to obtain a smooth potential recording curve; extracting escape trajectory points from the organic escape trajectory, and performing fitting processing on the escape trajectory points to obtain fitting trajectory points; constructing an organic release profile of the bio-based raw material based on the fitted trajectory points; Calculating the organic release intensity of the bio-based raw material based on the organic release profile; Calculating the potential change rate corresponding to the bio-based raw material based on the smoothed potential recording curve; Calculating the instability risk coefficient of the bio-based raw material based on the organic release intensity and the potential change rate; Based on the instability risk coefficient, the colloidal stability of the bio-based raw material is calculated.

[0013] Optionally, the calculating of the instability risk coefficient of the bio-based raw material by combining the organic release intensity and the potential change rate includes: The instability risk coefficient of the bio-based raw material is calculated by the following formula: in, represents the instability risk factor of bio-based raw materials, represents the rate of change of potential, represents the extreme value of the rate of change of potential, Indicates the organic release intensity, Indicates the extreme value of organic release intensity.

[0014] In order to solve the above problems, the present invention also provides a high bio-based waterborne polyurethane resin synthesis system, the system comprising: A bio-based conversion threshold setting module is used to obtain bio-based raw materials and synthesis processes of high-bio-based waterborne polyurethane resins, query key synthesis equipment in the synthesis process, determine the green synthesis protocol corresponding to the key synthesis equipment, and set the bio-based conversion threshold corresponding to the key synthesis equipment based on the green synthesis protocol; a process compensation coefficient setting module for collecting, in real time, the thermal gradient parameter value, the catalytic activity index, and the phase separation characteristic value of the bio-based raw material during the polycondensation reaction, calculating the biocarbon chain extension and the isocyanate group residue during the polycondensation reaction of the bio-based raw material based on the thermal gradient parameter value, the catalytic activity index, and the phase separation characteristic value, and setting the process compensation coefficient corresponding to the bio-based conversion threshold based on the biocarbon chain extension and the isocyanate group residue; a resin structural stability index evaluation module, configured to monitor the particle size distribution and molecular weight distribution of the bio-based raw material in the resin emulsion of the polycondensation reaction, analyze the chemical bonding degree corresponding to the raw material components of the bio-based raw material in combination with the particle size distribution and the molecular weight distribution, analyze the hard segment micro-domain morphology of the bio-based raw material in the resin emulsion, and evaluate the resin structural stability index of the raw material components in combination with the chemical bonding degree and the hard segment micro-domain morphology; a colloid stability calculation module, configured to record the electrokinetic potential record and organic release trajectory of the bio-based raw material during the polycondensation reaction, and calculate the colloid stability of the bio-based raw material by combining the electrokinetic potential record and the organic release trajectory; A synthesis processing module is used to generate process control instructions for the synthesis process by combining the process compensation coefficient, the resin structural stability index and the colloid stability. Based on the process control instructions, the synthesis process of the high-biobased waterborne polyurethane resin is performed using the bio-based raw materials to obtain a synthesis result.

[0015] Compared with the problem described in the background technology, the present invention can obtain the relevant equipment of the important synthesis in the synthesis process by querying the key synthesis equipment in the synthesis process, determine the green synthesis protocol corresponding to the key synthesis equipment, and then obtain a series of synthesis specifications and criteria for the key synthesis equipment, thereby providing an important basis for the subsequent setting of the bio-based conversion threshold corresponding to the key synthesis equipment. Furthermore, the present invention calculates the bio-carbon chain extension degree and isocyanate group residue in the condensation reaction process of the bio-based raw material by combining the thermal gradient parameter value, the catalytic activity index and the phase separation characteristic value, and can evaluate the stability of the reaction path and the raw material utilization rate, thereby accurately adjusting the process compensation coefficient to optimize the bio-based conversion efficiency, and providing an important basis for the subsequent setting of the process compensation coefficient corresponding to the bio-based conversion threshold. The present invention analyzes the bio-based conversion by combining the particle size distribution map and the molecular weight distribution map. The chemical bonding degree corresponding to the raw material components of the bio-based raw material can be used to understand the microscopic characteristics corresponding to the bio-based raw material, providing a basis for the subsequent evaluation of the resin stability index of the raw material components. Furthermore, the present invention calculates the colloid stability of the bio-based raw material by combining the electrokinetic potential recording and the organic escape trajectory, and the colloid stability can be used to understand the colloid stability of the bio-based raw material during the polycondensation reaction and storage. Furthermore, the present invention generates process control instructions for the synthesis process by combining the process compensation coefficient, the resin stability index and the colloid stability, which can comprehensively consider the characteristics of the bio-based raw material and the actual situation of the synthesis process, significantly improving the scientificity and accuracy of the process control instructions, and based on the process control instructions, the bio-based raw material is used to perform the synthesis process of the high-bio-based waterborne polyurethane resin, thereby ensuring the efficiency of the synthesis process and improving the quality of the synthesis result of the high-bio-based waterborne polyurethane resin. Therefore, the high-bio-based waterborne polyurethane resin synthesis method and system provided by the embodiment of the present invention can improve the efficiency of the synthesis of bio-based waterborne polyurethane resin. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A schematic flow chart of a method for synthesizing a highly bio-based waterborne polyurethane resin according to one embodiment of the present invention; Figure 2 A schematic diagram of a module for implementing the method for synthesizing a highly bio-based waterborne polyurethane resin according to an embodiment of the present invention.

[0017] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0018] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0019] The embodiments of the present application provide a method for synthesizing a highly bio-based waterborne polyurethane resin. The method can be executed by at least one of electronic devices, such as a server or terminal, that can be configured to execute the method provided in the embodiments of the present application. In other words, the method can be executed by software or hardware installed on a terminal or server device. The server can include, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster.

[0020] Example 1: Reference Figure 1 FIG. 1 is a flow chart of a method for synthesizing a highly bio-based waterborne polyurethane resin according to an embodiment of the present invention. In this embodiment, the method for synthesizing a highly bio-based waterborne polyurethane resin comprises: S1. Obtain bio-based raw materials and a synthesis process for a high-biobased waterborne polyurethane resin, query key synthesis equipment in the synthesis process, determine a green synthesis protocol corresponding to the key synthesis equipment, and set a bio-based conversion threshold corresponding to the key synthesis equipment based on the green synthesis protocol.

[0021] By querying the key synthesis equipment in the synthesis process, the present invention can obtain the relevant equipment of the important synthesis in the synthesis process, determine the green synthesis regulations corresponding to the key synthesis equipment, and then obtain a series of synthesis specifications and criteria for the key synthesis equipment, thereby providing an important basis for the subsequent setting of the bio-based conversion threshold corresponding to the key synthesis equipment. It should be explained that high bio-based water-based polyurethane resin is a kind of raw material mainly derived from renewable biological resources, prepared by a specific polymerization process, with water as the dispersion medium, and has excellent film-forming, wear resistance, flexibility and other properties of polyurethane resin, while being environmentally friendly and low in VOC (volatile organic compound). The bio-based raw materials refer to chemical raw materials derived from renewable biomass (such as vegetable oil, cellulose, etc.); the key synthesis equipment is the core device for the preparation of high-biobased waterborne polyurethane resin, such as bio-based prepolymer reactor, water-based emulsification equipment, vacuum dehydration device and low-temperature drying system; the green synthesis protocol is the environmental protection standards and technical specifications that must be followed in the operation of the equipment, including raw material utilization requirements, energy consumption restrictions, waste emission standards, etc.; further, the query of key synthesis equipment in the synthesis process can be achieved through process flow chart analysis.

[0022] In detail, the determining of the green synthesis protocol corresponding to the key synthesis equipment includes: Query the environmental compliance documents of the key synthetic equipment, perform multi-source data analysis on the environmental compliance documents, and obtain preliminary stipulations; Performing conflict resolution on the preliminary terms of the agreement to obtain standard terms of the agreement; The standard specification clauses are subjected to specification classification processing to obtain the green synthesis specification corresponding to the key synthesis equipment.

[0023] It should be explained that the equipment environmental compliance document is a normative document that the key synthetic equipment must follow in the design, manufacturing, use and other links to ensure compliance with environmental protection requirements; the preliminary regulations are the specific provisions related to equipment environmental protection that are preliminarily drafted in the equipment environmental compliance document; the standard regulations are the regulations that are finalized as equipment environmental implementation standards after the conflict resolution in the preliminary regulations, adjustment, optimization, and unified specifications.

[0024] Furthermore, the environmental compliance documents of the key synthetic equipment can be queried through the industry database provided by the equipment manufacturer, and the multi-source data of the environmental compliance documents of the equipment can be parsed through natural language processing technology to obtain preliminary regulations. The numerical contradictions of the cross-document clauses can be logically checked (for example, the "lower limit of bio-based content" in different documents is 55% and 60% respectively, and the stricter 60% is taken as the final constraint) to resolve conflicts in the preliminary regulations and obtain standard regulations. A grading system can be constructed based on indicators such as the degree of environmental impact and resource utilization efficiency to grade the standard regulations and obtain green synthesis regulations corresponding to the key synthetic equipment.

[0025] The present invention sets the bio-based conversion threshold corresponding to the key synthesis equipment based on the green synthesis protocol, which can quantitatively evaluate the utilization efficiency and environmental friendliness of bio-based raw materials in the synthesis process, thereby providing data support for optimizing the sustainability of the synthesis process. It should be explained that the bio-based conversion threshold is the core parameter for measuring the effective conversion rate of bio-based raw materials in the synthesis process of the equipment.

[0026] Specifically, the bio-based conversion threshold corresponding to the key synthesis equipment is set based on the green synthesis protocol, including: Performing specification semantic analysis on the green synthesis specification to obtain synthesis specification semantics; Extracting key specification semantics from the composite specification semantics, and calculating semantic correlation coefficients between the key specification semantics; extracting, from the synthetic specification semantics, specification constraints related to bio-based conversion based on the semantic association coefficient; Extracting key parameter indicators from the specification constraints and collecting equipment performance data and historical process data of the key synthesis equipment; Combining the equipment performance data with the historical process data, setting indicator parameter thresholds corresponding to the key parameter indicators; Based on the indicator parameter threshold, the bio-based conversion threshold corresponding to the key synthesis equipment is set.

[0027] It should be explained that the synthesis protocol semantics is the meaning of the green synthesis protocol expressed in a specific language; the key protocol semantics is the part of the meaning in the synthesis protocol semantics that plays a core and key role in the synthesis process; the semantic association coefficient represents the quantitative value of the degree of association between the key protocol semantics; the protocol constraints are the restrictions and prescriptive conditions related to bio-based conversion extracted from the synthesis protocol semantics; the key parameter indicators are specific quantitative indicators in the protocol constraints used to measure and define key aspects of bio-based conversion; the equipment performance data and the historical process data are respectively the performance data of the key synthesis equipment during operation and the data accumulated during the past process execution; the indicator parameter threshold is the numerical limit corresponding to the key parameter indicator for judging whether the equipment operation and bio-based conversion status meet the requirements.

[0028] Furthermore, the green synthesis specification can be subjected to specification semantic analysis using a semantic parsing method to obtain synthesis specification semantics; key specification semantics in the synthesis specification semantics can be extracted using a TF-IDF algorithm; semantic correlation coefficients between the key specification semantics can be calculated using a semantic similarity algorithm; the semantic correlation coefficient is compared with a preset correlation coefficient, and when the semantic correlation coefficient is greater than the preset correlation coefficient, specification constraints related to bio-based conversion are extracted from the synthesis specification semantics; key parameter indicators in the specification constraints can be extracted using domain knowledge-driven rule matching, and equipment performance data and historical process data of the key synthesis equipment can be collected in real time through equipment sensors and retrieved from a historical database; based on the equipment performance data and the historical process data, indicator parameter thresholds corresponding to the key parameter indicators can be set using statistical analysis and machine learning algorithms, such as using regression analysis to evaluate the correlation between parameters to set an initial threshold value, and then using a clustering algorithm to fine-tune the threshold based on data distribution characteristics to ensure that the threshold matches the equipment performance and process reality; based on the indicator parameter threshold, a bio-based conversion threshold corresponding to the key synthesis equipment can be set, such as dynamically adjusting the bio-based conversion threshold based on the degree to which the key parameter indicator deviates from the threshold and the weight of its impact on bio-based conversion.

[0029] S2. Real-time collection of thermal gradient parameter values, catalytic activity indices, and phase separation characteristic values of the bio-based raw materials during the polycondensation reaction process; combining the thermal gradient parameter values, the catalytic activity indices, and the phase separation characteristic values to calculate the bio-carbon chain extension and the isocyanate group remainder during the polycondensation reaction of the bio-based raw materials; and setting a process compensation coefficient corresponding to the bio-based conversion threshold value based on the bio-carbon chain extension and the isocyanate group remainder.

[0030] The present invention calculates the biocarbon chain extension and isocyanate residue in the bio-based raw material polycondensation reaction process by combining the thermal gradient parameter value, the catalytic activity index and the phase separation characteristic value, and can evaluate the stability of the reaction path and the raw material utilization rate, thereby accurately adjusting the process compensation coefficient to optimize the bio-based conversion efficiency, and providing an important basis for the subsequent setting of the process compensation coefficient corresponding to the bio-based conversion threshold. It should be explained that the thermal gradient parameter value is a quantitative indicator of the uneven temperature distribution in the reaction system; the catalytic activity index is a real-time performance parameter of the catalyst during the reaction process (such as conversion rate per unit time, deactivation rate); the phase The separation characteristic value is the dynamic characteristic of the interfacial behavior of the two phases (such as the polymer phase and the solvent phase) in the system (such as the critical time of phase separation and the interfacial tension); the biocarbon chain extension is a quantitative indicator that characterizes the carbon chain growth efficiency during the polymerization of bio-based monomers (such as the standard deviation of the polymerization degree); the isocyanate group residue is the concentration of isocyanate groups that do not participate in the reaction, reflecting the degree of side reactions in the condensation reaction; further, the real-time collection of the thermal gradient parameter value, catalytic activity index and phase separation characteristic value of the bio-based raw material during the condensation reaction can be achieved through instruments such as high-precision temperature sensors, catalytic activity detectors based on spectral analysis technology, and optical phase separation monitoring probes.

[0031] In detail, the calculation of the biocarbon chain extension and the isocyanate group residue during the polycondensation reaction of the bio-based raw material by combining the thermal gradient parameter value, the catalytic activity index, and the phase separation characteristic value includes: Performing data synchronization and alignment processing on the thermal gradient parameter value, the catalytic activity index, and the phase separation characteristic value to obtain synchronous reaction time series data; Extracting reaction kinetic characteristics from the synchronous reaction time series data, and constructing a reaction characteristic matrix of the bio-based raw material based on the reaction kinetic characteristics; Calculating the biocarbon chain extension degree during the polycondensation reaction of the bio-based raw material based on the reaction characteristic matrix; The raw material spectrum data of the bio-based raw material during the polycondensation reaction is collected, and the isocyanate group residue of the bio-based raw material during the polycondensation reaction is calculated by combining the biological carbon chain extension and the raw material spectrum data.

[0032] It should be explained that the synchronous reaction time series data is a data set obtained by arranging and integrating the thermal gradient parameter values, the catalytic activity index and the phase separation characteristic values after data synchronization and alignment processing, and accurately reflecting the changes of various parameters at the same time point; the reaction kinetic characteristics are characteristic parameters related to the dynamic changes of the reaction, such as the condensation reaction rate, reaction direction, reaction activation energy, etc. of the bio-based raw materials in the synchronous reaction time series data; the reaction characteristic matrix is constructed based on the reaction kinetic characteristics, and is a matrix-form data structure used to comprehensively and systematically describe the key reaction kinetic characteristics of the bio-based raw materials in the condensation reaction and their mutual relationships; the raw material spectral data is spectral data obtained in real time by spectral detection means during the condensation reaction of the bio-based raw materials, which can reflect information such as the molecular structure of the raw materials and chemical bond changes.

[0033] Furthermore, the thermal gradient parameter value, the catalytic activity index and the phase separation characteristic value can be synchronized and aligned with each other through timestamp matching and interpolation algorithms to obtain synchronized reaction time series data; the reaction kinetic characteristics in the synchronized reaction time series data can be extracted by combining feature extraction algorithms with domain knowledge; based on the reaction kinetic characteristics, the reaction characteristic matrix of the bio-based raw material can be constructed through matrix construction rules and data conversion operations; the raw material spectral data of the bio-based raw material during the polycondensation reaction can be collected through a high-resolution spectrometer and a real-time data transmission module.

[0034] Furthermore, as an optional embodiment of the present invention, the calculation of the biocarbon chain extension degree of the bio-based raw material polycondensation reaction process in combination with the reaction characteristic matrix includes: The biocarbon chain extension degree of the bio-based raw material polycondensation reaction process is calculated by the following formula: Where A represents the degree of extension of the biocarbon chain during the polycondensation reaction of bio-based raw materials. represents the standard degree of polymerization, represents the temperature contribution coefficient, represents the reaction rate constant at time t in the reaction characteristic matrix, represents the phase separation starting time, represents the end time of phase separation, Represents the thermal gradient of the reaction feature matrix at time t, represents the delay gain coefficient, represents the phase separation triggering time in the reaction characteristic matrix, Represents the total reaction time.

[0035] It should be explained that the standard degree of polymerization is a benchmark in the absence of any dynamic factors (such as temperature changes or catalytic activity), and is a value obtained through experimental determination under standard conditions. The temperature contribution coefficient reflects the contribution of the synergistic effect of temperature gradient and reaction rate to chain growth, and is obtained by fitting experimental data. The delay gain coefficient is the influence of the ratio of phase separation time to total reaction time on the degree of polymerization. By fixing other reaction conditions and only adjusting the amount of phase separation inhibitor / promoter added in the experimental design, the experimental data is calculated by the partial least squares regression method to obtain the delay gain coefficient. The total reaction time can be obtained by summing the phase separation trigger time.

[0036] Furthermore, as an optional embodiment of the present invention, the calculation of the isocyanate residue in the polycondensation reaction of the bio-based raw material by combining the bio-carbon chain extension and the raw material spectral data includes: performing noise reduction processing on the raw material spectrum data to obtain noise-reduced raw material spectrum data; performing baseline correction processing on the noise-reduced raw material spectral data to obtain corrected raw material spectral data; Extracting characteristic spectral peaks from the corrected raw material spectral data, and calculating characteristic peak intensities corresponding to the characteristic spectral peaks; The isocyanate residue in the polycondensation reaction of the bio-based raw material is calculated based on the bio-carbon chain extension and the characteristic peak intensity.

[0037] It should be explained that the de-noised raw material spectral data is the raw material spectral data after being processed to remove noise interference, reducing the influence of random fluctuations and outliers in the data, making the spectral data smoother and more accurate; the corrected raw material spectral data is the data obtained after the de-noised raw material spectral data eliminates the influence of spectral baseline drift, tilt, etc.; the spectral characteristic peak is the wavelength position of the corrected raw material spectral data that can characterize the characteristics of specific chemical bonds, functional groups or molecular vibrations in the molecular structure of bio-based raw materials; the characteristic peak intensity is the intensity value of the spectral signal corresponding to the spectral characteristic peak at the wavelength position of the characteristic peak.

[0038] Furthermore, the raw material spectral data can be subjected to noise reduction processing by a wavelet transform algorithm to obtain noise-reduced raw material spectral data; the noise-reduced raw material spectral data can be subjected to baseline correction processing by a polynomial fitting algorithm to obtain corrected raw material spectral data; the spectral characteristic peaks in the corrected raw material spectral data can be extracted by a derivative spectroscopy method combined with a peak-finding algorithm; the characteristic peak intensity corresponding to the spectral characteristic peak can be calculated by an integral method or by directly reading the peak height value; the step of calculating the isocyanate group residue in the polycondensation reaction process of the bio-based raw material by combining the bio-carbon chain extension degree and the characteristic peak intensity is as follows: determining the bio-carbon chain extension degree , the qualitative relationship between the characteristic peak intensity and the isocyanate residue. By consulting relevant literature, studying past experimental data or analyzing based on chemical principles, the influence trend of the increase or decrease of the biological carbon chain extension and the change of the characteristic peak intensity on the isocyanate residue is clarified, and a semi-quantitative relationship between the three is established. Based on a series of standard samples with known isocyanate residues, their biological carbon chain extension and characteristic peak intensity are measured, and the corresponding relationship curves or tables are drawn. For bio-based raw materials in actual polycondensation reactions, their biological carbon chain extension and characteristic peak intensity are measured, and then the corresponding isocyanate residue is estimated by looking up or interpolating in the established relationship curves or tables.

[0039] The present invention sets the process compensation coefficient corresponding to the bio-based conversion threshold by combining the bio-carbon chain extension degree and the isocyanate group residue, thereby accurately regulating the conversion process of bio-based raw materials in the polycondensation reaction, flexibly optimizing process parameters according to real-time reaction conditions, ensuring stable production of bio-based waterborne polyurethane resins, and improving product quality and bio-based raw material utilization. It should be explained that the process compensation coefficient corresponding to the bio-based conversion threshold is used to adjust the reaction process parameters in real time according to the bio-carbon chain extension degree and the isocyanate group residue. Furthermore, in combination with the bio-carbon chain extension degree and the isocyanate group residue, the step of setting the process compensation coefficient corresponding to the bio-based conversion threshold is as follows: standardizing the bio-carbon chain extension degree and isocyanate group residue data to eliminate dimensionality effects, such as expressing the bio-carbon chain extension degree as The isocyanate residue is expressed as the ratio relative to the theoretical maximum extension degree and the isocyanate residue is expressed as the ratio relative to the initial amount. Based on a large number of previous experiments and theoretical analysis, the weights of the influence of the bio-carbon chain extension degree and the isocyanate residue on the bio-based conversion are determined. For example, if the bio-carbon chain extension degree has a more significant impact on the bio-based conversion, it can be given a higher weight, such as 0.6, and the isocyanate residue weight is set to 0.4. The process compensation coefficient calculation formula is set, such as process compensation coefficient = standardized value of bio-carbon chain extension degree × 0.6 + standardized value of isocyanate residue × 0.4. When the bio-carbon chain extension degree is high and the isocyanate residue is reasonable, the calculated process compensation coefficient can be used to moderately increase the reaction temperature or extend the reaction time, etc., to promote bio-based conversion; conversely, if the bio-carbon chain extension degree is low or the isocyanate residue is abnormal, the coefficient adjustment direction is opposite.

[0040] S3. Monitor the particle size distribution and molecular weight distribution of the bio-based raw material in the resin emulsion of the polycondensation reaction, analyze the chemical bonding degree corresponding to the raw material components of the bio-based raw material based on the particle size distribution and the molecular weight distribution, analyze the hard segment micro-domain morphology of the bio-based raw material, and evaluate the resin structure stability index of the raw material components based on the chemical bonding degree and the hard segment micro-domain morphology.

[0041] The present invention analyzes the chemical bonding degree corresponding to the raw material components of the bio-based raw material by combining the particle size distribution map and the molecular weight distribution map, so as to understand the microscopic characteristics corresponding to the bio-based raw material and provide a basis for the subsequent evaluation of the resin stability index of the raw material components. It should be explained that the resin emulsion is a stable system with water as the continuous phase and polymer particles dispersed therein, which is formed by the bio-based raw material through polymerization reaction and dispersion in the polycondensation reaction; the particle size distribution map and the molecular weight distribution map are respectively visualization charts of the polymer particle size distribution and the polymer molecular weight distribution of the bio-based raw material in the resin emulsion of the polycondensation reaction; the chemical bonding degree is the degree of tightness of the chemical bond connection between the raw material components of the bio-based raw material. Furthermore, the monitoring of the particle size distribution map and the molecular weight distribution map of the bio-based raw material in the resin emulsion of the polycondensation reaction can be achieved by a laser particle size analyzer and a gel permeation chromatograph.

[0042] In detail, the analyzing the chemical bonding degree corresponding to the raw material components of the bio-based raw material by combining the particle size distribution map and the molecular weight distribution map includes: Performing multi-peak fitting analysis on the particle size distribution spectrum to obtain particle size distribution characteristics; Performing segmented integration processing on the molecular weight distribution graph to obtain polymer content; analyzing potential coupling mechanisms of the particle size distribution characteristics and the polymer content to chemical bonding of the bio-based feedstock; assigning bonding contributions of the particle size distribution characteristics and the polymer content based on the potential coupling mechanism to obtain a first contribution and a second contribution; Calculating bonding potential values corresponding to raw material components of the bio-based raw material based on the particle size distribution characteristics, the polymer content, the first contribution, and the second contribution; Based on the bonding potential value, the chemical bonding degree corresponding to the raw material components of the bio-based raw material is analyzed.

[0043] It should be explained that the particle size distribution characteristics are characteristic parameters obtained by multi-peak fitting analysis of the particle size distribution graph, which can reflect the distribution state of particles of different particle sizes in the emulsion, the proportion of each particle size interval, etc.; the polymer content is the relative content of polymers in different molecular weight intervals obtained by segmented integration processing in the molecular weight distribution graph; the potential coupling mechanism is the inherent, interrelated and mutually influential mode and principle of action of the particle size distribution characteristics and the polymer content on the chemical bonding of the bio-based raw material; the first contribution and the second contribution are respectively allocated to the particle size distribution characteristics and the polymer content based on the potential coupling mechanism to measure the bonding contribution of each of them to the chemical bonding process of the bio-based raw material; the bonding potential value indicates the potential ability of the raw material components of the bio-based raw material to theoretically form chemical bonds under the current particle size distribution characteristics and polymer content.

[0044] Furthermore, the particle size distribution spectrum can be subjected to multi-peak fitting analysis by the built-in multi-peak fitting algorithm in professional data analysis software (such as Origin, Matlab, etc.) to obtain the particle size distribution characteristics; the molecular weight distribution diagram can be subjected to segmented integration processing by customizing the integral interval in the data analysis software and applying the integral operation algorithm to obtain the polymer content; the potential coupling mechanism of the particle size distribution characteristics and the polymer content on the chemical bonding of the bio-based raw materials can be analyzed through in-depth theoretical research (such as chemical kinetics, intermolecular force theory, etc.); based on the potential coupling mechanism, the correlation between the particle size distribution characteristics, polymer content and chemical bonding degree under different experimental conditions can be compared and analyzed. , using a statistical analysis method to allocate the bonding contribution of the particle size distribution characteristics and the polymer content to obtain a first contribution and a second contribution; multiplying the particle size distribution characteristics and the polymer content with the corresponding first contribution and second contribution respectively, and then obtaining a bonding potential value corresponding to the raw material component of the bio-based raw material; based on the bonding potential value, by comparing with standard sample data with known chemical bonding degrees, establishing a mapping relationship between the two to analyze the chemical bonding degrees corresponding to the raw material components of the bio-based raw material, such as dividing the bonding potential value into multiple intervals, comparing the corresponding chemical bonding degree ranges falling into each interval in the standard sample data, and judging the level of the chemical bonding degree of the bio-based raw material accordingly.

[0045] By analyzing the hard segment micro-domain morphology of the bio-based raw material in the resin emulsion, the present invention can understand the internal microstructural characteristics of the bio-based raw material and provide the accuracy of the subsequent evaluation of the resin stability index of the raw material components. It should be explained that the hard segment micro-domain morphology is the morphological structure of the microscopic region formed by the aggregation of hard segment molecular segments in the bio-based raw material, including the distribution state, size, shape and other characteristics of the hard segment.

[0046] In detail, the analysis of the hard segment micro-domain morphology of the bio-based raw material in the resin emulsion includes: Performing transmission electron microscope imaging on the resin emulsion to obtain an original transmission electron microscope image; Performing enhancement processing on the original transmission electron microscope image to obtain an enhanced transmission electron microscope image; performing thresholding processing on the enhanced electron microscope image to obtain a threshold electron microscope image; Optimizing the morphology in the threshold electron microscope image to obtain an electron microscope wheel morphology image; The hard segment micro-domain features of the electron microscope morphology optimization image are extracted, and based on the hard segment micro-domain features, the hard segment micro-domain morphology of the bio-based raw material in the resin emulsion is analyzed.

[0047] It should be explained that the original transmission electron microscope image is the initial image directly reflecting the internal microstructure of the resin emulsion obtained through transmission electron microscope imaging processing; the enhanced electron microscope image is the image after the original transmission electron microscope image enhances the contrast between the hard segment micro-region and the background and highlights the details; the threshold electron microscope image is the binary image after the enhanced electron microscope image is divided into black and white parts representing the hard segment micro-region and the background based on the pixel grayscale value; the electron microscope morphology optimized image is the image after the threshold electron microscope image removes isolated noise points, fills holes, and smoothes contour edges to make the hard segment micro-region morphology clearer and more complete; the hard segment micro-region characteristics are the dimensional parameters such as area, perimeter, major axis and minor axis length measured by the electron microscope morphology optimized image, as well as the shape characteristics described by indicators such as shape factor, as well as the statistical information such as the number and distribution of hard segment micro-regions in different regions.

[0048] Furthermore, the resin emulsion can be subjected to transmission electron microscopy imaging processing by a transmission electron microscope to obtain an original transmission electron microscopy image; the original transmission electron microscopy image can be enhanced by a histogram equalization method to obtain an enhanced transmission electron microscopy image; the enhanced transmission electron microscopy image can be thresholded by the Otsu method to obtain a threshold electron microscopy image; the morphology in the threshold electron microscopy image can be optimized by morphological operations such as corrosion, expansion, opening operation, closing operation, etc. to obtain an electron microscope wheel morphological image; the hard segment micro-region features of the electron microscope morphological optimization image can be extracted by image analysis software; based on the hard segment micro-region features, the hard segment micro-region morphology of the bio-based raw material in the resin emulsion is analyzed; for example, the size of the hard segment micro-region is judged based on its area and perimeter data, and the shape factor is combined to analyze whether the micro-region is approximately circular, elliptical or irregular, and then the number and distribution of hard segment micro-regions in different regions are used to infer whether it is uniformly dispersed or locally aggregated in the resin emulsion.

[0049] The present invention evaluates the resin structural stability index of the raw material component by combining the chemical bonding degree and the hard segment micro-domain morphology, thereby accurately understanding the structural stability of the bio-based raw material in the resin system, and providing key data support for optimizing the raw material formula and improving the production process. It should be explained that the resin structural stability index is a stability measurement value of the raw material component in the resin system. Furthermore, the resin structural stability index of the raw material component is evaluated in combination with the chemical bonding degree and the hard segment micro-domain morphology. The tightness of the intermolecular bonding is judged based on the chemical bonding degree, and the structural regularity is determined with reference to the hard segment micro-domain morphology. The two are intuitively correlated to comprehensively judge the resin structural stability index.

[0050] S4. Recording the electrokinetic potential and organic release trajectory of the bio-based raw material during the polycondensation reaction, and calculating the colloidal stability of the bio-based raw material based on the electrokinetic potential and organic release trajectory.

[0051] The present invention calculates the colloid uniformity of the bio-based raw material by combining the electrokinetic potential record and the organic escape trajectory. The colloid uniformity can be used to understand the colloid stability of the bio-based raw material during the polycondensation reaction and storage. It should be explained that the electrokinetic potential record and the organic escape trajectory are respectively the data on the change of the potential of the bio-based raw material over time in the polycondensation reaction and the information such as the movement path and time nodes of the escaped organic molecules. The colloid uniformity indicates the stability of the bio-based raw material during the polycondensation reaction and storage. Furthermore, the electrokinetic potential record and the organic escape trajectory record of the bio-based raw material in the polycondensation reaction can be achieved by an electrochemical workstation and a gas chromatography-mass spectrometer.

[0052] In detail, the calculation of the colloidal stability of the bio-based raw material by combining the electrokinetic potential record and the organic escape trajectory includes: performing anomaly removal processing on the electrokinetic potential record to obtain a smooth potential recording curve; extracting escape trajectory points from the organic escape trajectory, and performing fitting processing on the escape trajectory points to obtain fitting trajectory points; constructing an organic release profile of the bio-based raw material based on the fitted trajectory points; Calculating the organic release intensity of the bio-based raw material based on the organic release profile; Calculating the potential change rate corresponding to the bio-based raw material based on the smoothed potential recording curve; Calculating the instability risk coefficient of the bio-based raw material based on the organic release intensity and the potential change rate; Based on the instability risk coefficient, the colloidal stability of the bio-based raw material is calculated.

[0053] It should be explained that the smoothed potential recording curve is a curve reflecting the trend of potential change over time obtained by removing abnormal fluctuations and noise interference from the electrokinetic potential recording; The escape trajectory points are a series of discrete position information points in the organic escape trajectory, used to describe the escape path of the organic molecule; the fitted trajectory points are new points obtained by processing the escape trajectory points using a suitable mathematical fitting algorithm. The curve formed by these points can more smoothly and reasonably fit the escape trajectory of the organic molecule, reducing the impact of data fluctuations; the organic release profile is a visualization chart constructed based on the escape trajectory of the organic molecule and related information during the polycondensation reaction of the bio-based raw material. It intuitively displays the release path, speed, distribution and other characteristics of the organic components in the bio-based raw material in different dimensions (such as time, spatial position, etc.); The organic release intensity indicates the amount or concentration of organic molecules released per unit time or per unit space during the polycondensation reaction of the bio-based raw material, and is used to measure the severity of the release of organic components in the bio-based raw material. The potential change rate indicates how quickly the electrokinetic potential of the bio-based raw material changes with time during the polycondensation reaction, and reflects the rate of change in the surface charge distribution of particles in the raw material system. The instability risk coefficient is a quantitative indicator of the possibility that the colloidal system of the bio-based raw material will undergo unstable changes (such as coagulation, stratification, etc.) under preset storage conditions or during the reaction process. A higher value indicates that the colloidal system of the bio-based raw material is more likely to lose stability.

[0054] Furthermore, the electrokinetic potential record can be processed for anomaly removal by a mean filtering method to obtain a smooth potential recording curve; the escape trajectory points in the organic escape trajectory can be extracted by image recognition technology; the escape trajectory points can be fitted by a polynomial fitting method to obtain fitting trajectory points; based on the fitting trajectory points, the organic release spectrum of the bio-based raw material can be constructed by a visual software tool; the organic release spectrum can be integrated and the integral value obtained is the organic release intensity of the bio-based raw material; the potential change rate corresponding to the bio-based raw material can be calculated by calculating the ratio of the potential difference between adjacent time points of the smooth potential recording curve to the time interval; based on the instability risk coefficient, the colloid stability of the bio-based raw material is calculated, and the colloid stability = 1-the instability risk coefficient.

[0055] Furthermore, as an optional embodiment of the present invention, the calculation of the instability risk coefficient of the bio-based raw material by combining the organic release intensity and the potential change rate includes: The instability risk coefficient of the bio-based raw material is calculated by the following formula: in, represents the instability risk factor of bio-based raw materials, represents the rate of change of potential, represents the extreme value of the rate of change of potential, Indicates the organic release intensity, Indicates the extreme value of organic release intensity.

[0056] It should be explained that the extreme value of organic release intensity is the maximum release intensity in historical data. It is the absolute value of the maximum potential change rate in the historical data.

[0057] S5. Generate process control instructions for the synthesis process based on the process compensation coefficient, the resin structural stability index, and the colloid uniformity. Based on the process control instructions, perform a synthesis process of a high-biobased waterborne polyurethane resin using the bio-based raw materials to obtain a synthesis result.

[0058] The present invention generates process control instructions for the synthesis process by combining the process compensation coefficient, resin structural stability index and colloid uniformity, which can comprehensively consider the characteristics of bio-based raw materials and the actual situation of the synthesis process, significantly improve the scientificity and accuracy of the process control instructions, and based on the process control instructions, utilize the bio-based raw materials to perform the synthesis treatment of high-biobased water-based polyurethane resin, thereby ensuring the efficiency of the synthesis process and improving the quality of the synthesis results of high-biobased water-based polyurethane resin. It should be explained that the process control instructions are a specific adjustment and control method for the synthesis process of high-biobased water-based polyurethane resin. Furthermore, the generation steps of the process control instructions for the synthesis process are: assuming that the process compensation coefficient is high, the resin structural stability index is high, If the colloid stability is within the ideal range (indicating that the current synthesis process, raw material structural stability and colloid stability are all good), maintain the existing synthesis process parameters, including reaction temperature, pressure, raw material ratio, stirring speed, etc., and continue to pretreat the raw materials according to the established process, such as purifying and drying the bio-based raw materials, to ensure the stability of the raw material quality. Continue to maintain routine maintenance and inspection of the reaction equipment to ensure the normal operation of the equipment and prevent the synthesis effect from being affected by equipment failure. At the same time, appropriately reduce the monitoring frequency of the synthesis process, but still need to regularly collect data during the reaction process, such as the pH value and viscosity of the reaction liquid, to confirm the smooth progress of the synthesis. Establish a simple recording mechanism to record key information during the synthesis process for subsequent traceability and analysis.

[0059] If the process compensation coefficient is low, the resin stability index is low, and the colloidal stability is outside the acceptable range (indicating defects in the synthesis process, unstable raw material structure, and poor colloidal stability), the synthesis process should be fully optimized immediately. Depending on the cause of the low process compensation coefficient, the reaction temperature and pressure may need to be readjusted. For example, if the low process compensation coefficient is due to a slow reaction rate, the reaction temperature can be appropriately increased, but the impact of the temperature increase on raw material and colloidal stability should be carefully evaluated to ensure that adjustments are made within a safe range. The raw material ratio should be recalculated. Based on the characteristics of the bio-based raw material and the feedback from the resin stability index, the ratio of bio-based raw materials to other additives should be optimized to enhance the resin structure stability. The stirring speed and method should be adjusted to improve the mixing uniformity of the colloidal material by changing the stirring conditions, thereby optimizing the colloidal stability. The bio-based raw materials should be subjected to more rigorous pretreatment and more advanced purification technologies should be adopted to remove impurities that may affect the synthesis and improve the raw material purity. The reaction equipment should be maintained and upgraded, and key performance indicators such as equipment sealing and heat transfer efficiency should be checked. If necessary, aging or underperforming equipment components should be replaced. Significantly increase the monitoring frequency of the synthesis process, monitor various indicators of the reaction liquid in real time, such as temperature, pressure, pH value, viscosity, solid content, etc., and establish a detailed database to record all data. Based on real-time monitoring data, adjust process parameters in a timely manner to ensure that the synthesis process always proceeds in the ideal direction. At the same time, work closely with raw material suppliers to jointly analyze raw material problems, seek higher-quality sources of bio-based raw materials or improve raw material processing methods.

[0060] In this way, process control instructions for the synthesis process are generated, and based on these instructions, the bio-based raw materials are used to carry out the synthesis of high-biobased waterborne polyurethane resin, and finally a synthesis result is obtained. During the synthesis process, the process control instructions are strictly followed, each synthesis link is accurately controlled, the reaction progress is closely monitored, and possible problems are dealt with in a timely manner to ensure the smooth completion of the synthesis work and obtain a high-biobased waterborne polyurethane resin product that meets the quality requirements.

[0061] Compared with the problem described in the background technology, the present invention can obtain the relevant equipment of the important synthesis in the synthesis process by querying the key synthesis equipment in the synthesis process, determine the green synthesis protocol corresponding to the key synthesis equipment, and then obtain a series of synthesis specifications and criteria for the key synthesis equipment, thereby providing an important basis for the subsequent setting of the bio-based conversion threshold corresponding to the key synthesis equipment. Furthermore, the present invention calculates the bio-carbon chain extension degree and isocyanate group residue in the condensation reaction process of the bio-based raw material by combining the thermal gradient parameter value, the catalytic activity index and the phase separation characteristic value, and can evaluate the stability of the reaction path and the raw material utilization rate, thereby accurately adjusting the process compensation coefficient to optimize the bio-based conversion efficiency, and providing an important basis for the subsequent setting of the process compensation coefficient corresponding to the bio-based conversion threshold. The present invention analyzes the bio-based conversion by combining the particle size distribution map and the molecular weight distribution map. The chemical bonding degree corresponding to the raw material components of the bio-based raw material can be used to understand the microscopic characteristics corresponding to the bio-based raw material, providing a basis for the subsequent evaluation of the resin stability index of the raw material components. Furthermore, the present invention calculates the colloid stability of the bio-based raw material by combining the electrokinetic potential recording and the organic escape trajectory, and the colloid stability can be used to understand the colloid stability of the bio-based raw material during the polycondensation reaction and storage. Furthermore, the present invention generates process control instructions for the synthesis process by combining the process compensation coefficient, the resin stability index and the colloid stability, which can comprehensively consider the characteristics of the bio-based raw material and the actual situation of the synthesis process, significantly improving the scientificity and accuracy of the process control instructions, and based on the process control instructions, the bio-based raw material is used to perform the synthesis process of the high-bio-based waterborne polyurethane resin, thereby ensuring the efficiency of the synthesis process and improving the quality of the synthesis result of the high-bio-based waterborne polyurethane resin. Therefore, the high-bio-based waterborne polyurethane resin synthesis method and system provided by the embodiment of the present invention can improve the efficiency of the synthesis of bio-based waterborne polyurethane resin.

[0062] Example 2: like Figure 2 The figure shows a functional module diagram of a high bio-based waterborne polyurethane resin synthesis system of the present invention.

[0063] The highly bio-based waterborne polyurethane resin synthesis system 200 described herein can be installed in an electronic device. Depending on the functionality implemented, the highly bio-based waterborne polyurethane resin synthesis system may include a bio-based conversion threshold setting module 201, a process compensation coefficient setting module 202, a resin structural stability index evaluation module 203, a colloidal stability calculation module 204, and a synthesis processing module 205. A module, also referred to as a unit, is a series of computer program segments that can be executed by an electronic device processor and perform a fixed function. These are stored in the electronic device's memory.

[0064] In the embodiment of the present invention, the functions of each module / unit are as follows: The bio-based conversion threshold setting module 201 is used to obtain bio-based raw materials and synthesis processes of high-bio-based waterborne polyurethane resin, query key synthesis equipment in the synthesis process, determine the green synthesis protocol corresponding to the key synthesis equipment, and set the bio-based conversion threshold corresponding to the key synthesis equipment based on the green synthesis protocol; The process compensation coefficient setting module 202 is used to collect the thermal gradient parameter value, catalytic activity index and phase separation characteristic value of the bio-based raw material during the polycondensation reaction in real time, calculate the biocarbon chain extension and isocyanate group residue during the polycondensation reaction of the bio-based raw material based on the thermal gradient parameter value, the catalytic activity index and the phase separation characteristic value, and set the process compensation coefficient corresponding to the bio-based conversion threshold based on the biocarbon chain extension and the isocyanate group residue; The resin structural stability index evaluation module 203 is used to monitor the particle size distribution and molecular weight distribution of the bio-based raw material in the resin emulsion of the polycondensation reaction, analyze the chemical bonding degree corresponding to the raw material components of the bio-based raw material based on the particle size distribution and the molecular weight distribution, and analyze the hard segment micro-domain morphology of the bio-based raw material in the resin emulsion, and evaluate the resin structural stability index of the raw material components based on the chemical bonding degree and the hard segment micro-domain morphology; The colloidal stability calculation module 204 is used to record the electrokinetic potential record and organic release trajectory of the bio-based raw material during the polycondensation reaction, and calculate the colloidal stability of the bio-based raw material by combining the electrokinetic potential record and the organic release trajectory; The synthesis processing module 205 is used to generate process control instructions for the synthesis process by combining the process compensation coefficient, the resin structural stability index and the colloid stability. Based on the process control instructions, the synthesis process of the high-biobased waterborne polyurethane resin is performed using the bio-based raw materials to obtain a synthesis result.

[0065] In detail, each module in the highly bio-based waterborne polyurethane resin synthesis system 200 of the embodiment of the present invention is used in the same manner as above. Figure 1 The same technical means are used as the method for synthesizing high bio-based waterborne polyurethane resin described in , and can produce the same technical effects, so they will not be repeated here.

[0066] 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 present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0067] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for synthesizing a high bio-based waterborne polyurethane resin, characterized in that: The method comprises: Obtaining bio-based raw materials and a synthesis process for a high-biobased waterborne polyurethane resin, querying key synthesis equipment in the synthesis process, determining a green synthesis protocol corresponding to the key synthesis equipment, and setting a bio-based conversion threshold corresponding to the key synthesis equipment based on the green synthesis protocol; collecting in real time the thermal gradient parameter value, catalytic activity index, and phase separation characteristic value of the bio-based raw material during the polycondensation reaction process, calculating the biocarbon chain extension and isocyanate group residue during the polycondensation reaction process of the bio-based raw material based on the thermal gradient parameter value, the catalytic activity index, and the phase separation characteristic value, and setting a process compensation coefficient corresponding to the bio-based conversion threshold based on the biocarbon chain extension and the isocyanate group residue; Monitoring the particle size distribution and molecular weight distribution of the bio-based raw material in the resin emulsion of the polycondensation reaction, analyzing the chemical bonding degree corresponding to the raw material components of the bio-based raw material based on the particle size distribution and the molecular weight distribution, analyzing the hard segment micro-domain morphology of the bio-based raw material in the resin emulsion, and evaluating the resin structural stability index of the raw material components based on the chemical bonding degree and the hard segment micro-domain morphology; Recording electrokinetic potential records and organic release trajectories of the bio-based raw material during the polycondensation reaction, and calculating the colloidal stability of the bio-based raw material under preset storage conditions based on the electrokinetic potential records and the organic release trajectories; In combination with the process compensation coefficient, the resin structural stability index and the colloid uniform stability, a process control instruction of the synthesis process is generated. Based on the process control instruction, the bio-based raw material is used to perform a synthesis process of a high-bio-based waterborne polyurethane resin to obtain a synthesis result.

2. The method for synthesizing a high bio-based waterborne polyurethane resin according to claim 1, wherein: Determining the green synthesis protocol corresponding to the key synthesis equipment includes: Query the environmental compliance documents of the key synthetic equipment, perform multi-source data analysis on the environmental compliance documents, and obtain preliminary stipulations; Performing conflict resolution on the preliminary terms of the agreement to obtain standard terms of the agreement; The standard specification clauses are subjected to specification classification processing to obtain the green synthesis specification corresponding to the key synthesis equipment.

3. The method for synthesizing a high bio-based waterborne polyurethane resin according to claim 1, wherein: The bio-based conversion threshold corresponding to the key synthesis equipment is set based on the green synthesis protocol, including: Performing specification semantic analysis on the green synthesis specification to obtain synthesis specification semantics; Extracting key specification semantics from the composite specification semantics, and calculating semantic correlation coefficients between the key specification semantics; extracting, from the synthetic specification semantics, specification constraints related to bio-based conversion based on the semantic association coefficient; Extracting key parameter indicators from the specification constraints and collecting equipment performance data and historical process data of the key synthesis equipment; Combining the equipment performance data with the historical process data, setting indicator parameter thresholds corresponding to the key parameter indicators; Based on the indicator parameter threshold, the bio-based conversion threshold corresponding to the key synthesis equipment is set.

4. The method for synthesizing a high bio-based waterborne polyurethane resin according to claim 1, wherein: The calculation of the biocarbon chain extension and the isocyanate group residue during the polycondensation reaction of the bio-based raw material by combining the thermal gradient parameter value, the catalytic activity index, and the phase separation characteristic value includes: Performing data synchronization and alignment processing on the thermal gradient parameter value, the catalytic activity index, and the phase separation characteristic value to obtain synchronous reaction time series data; Extracting reaction kinetic characteristics from the synchronous reaction time series data, and constructing a reaction characteristic matrix of the bio-based raw material based on the reaction kinetic characteristics; Calculating the biocarbon chain extension degree during the polycondensation reaction of the bio-based raw material based on the reaction characteristic matrix; The raw material spectrum data of the bio-based raw material during the polycondensation reaction is collected, and the isocyanate group residue of the bio-based raw material during the polycondensation reaction is calculated by combining the biological carbon chain extension and the raw material spectrum data.

5. The method for synthesizing a high bio-based waterborne polyurethane resin according to claim 4, wherein: The step of calculating the biocarbon chain extension degree of the bio-based raw material polycondensation reaction process in combination with the reaction characteristic matrix includes: The biocarbon chain extension degree of the bio-based raw material polycondensation reaction process is calculated by the following formula: Where A represents the degree of extension of the biocarbon chain during the polycondensation reaction of bio-based raw materials. represents the standard degree of polymerization, represents the temperature contribution coefficient, represents the reaction rate constant at time t in the reaction characteristic matrix, represents the phase separation starting time, represents the end time of phase separation, Represents the thermal gradient of the reaction feature matrix at time t, represents the delay gain coefficient, represents the phase separation triggering time in the reaction characteristic matrix, Represents the total reaction time.

6. The method for synthesizing a highly bio-based waterborne polyurethane resin according to claim 4, wherein: The method of calculating the isocyanate residue in the polycondensation reaction of the bio-based raw material by combining the bio-carbon chain extension degree and the raw material spectrum data comprises: performing noise reduction processing on the raw material spectrum data to obtain noise-reduced raw material spectrum data; performing baseline correction processing on the noise-reduced raw material spectral data to obtain corrected raw material spectral data; Extracting characteristic spectral peaks from the corrected raw material spectral data, and calculating characteristic peak intensities corresponding to the characteristic spectral peaks; The isocyanate residue in the polycondensation reaction of the bio-based raw material is calculated based on the bio-carbon chain extension and the characteristic peak intensity.

7. The method for synthesizing a highly bio-based waterborne polyurethane resin according to claim 1, wherein: The step of analyzing the chemical bonding degree corresponding to the raw material components of the bio-based raw material by combining the particle size distribution graph and the molecular weight distribution graph includes: Performing multi-peak fitting analysis on the particle size distribution spectrum to obtain particle size distribution characteristics; Performing segmented integration processing on the molecular weight distribution graph to obtain polymer content; analyzing potential coupling mechanisms of the particle size distribution characteristics and the polymer content to chemical bonding of the bio-based feedstock; assigning bonding contributions of the particle size distribution characteristics and the polymer content based on the potential coupling mechanism to obtain a first contribution and a second contribution; Calculating bonding potential values corresponding to raw material components of the bio-based raw material based on the particle size distribution characteristics, the polymer content, the first contribution, and the second contribution; Based on the bonding potential value, the chemical bonding degree corresponding to the raw material components of the bio-based raw material is analyzed.

8. The method for synthesizing a high bio-based waterborne polyurethane resin according to claim 1, wherein: The analyzing the hard segment micro-domain morphology of the bio-based raw material in the resin emulsion includes: Performing transmission electron microscope imaging on the resin emulsion to obtain an original transmission electron microscope image; Performing enhancement processing on the original transmission electron microscope image to obtain an enhanced transmission electron microscope image; performing thresholding processing on the enhanced electron microscope image to obtain a threshold electron microscope image; Optimizing the morphology in the threshold electron microscope image to obtain an electron microscope wheel morphology image; The hard segment micro-domain features of the electron microscope morphology optimization image are extracted, and based on the hard segment micro-domain features, the hard segment micro-domain morphology of the bio-based raw material in the resin emulsion is analyzed.

9. The method for synthesizing a high bio-based waterborne polyurethane resin according to claim 1, wherein: The calculating the colloidal stability of the bio-based raw material by combining the electrokinetic potential record and the organic escape trajectory includes: performing anomaly removal processing on the electrokinetic potential record to obtain a smooth potential recording curve; extracting escape trajectory points from the organic escape trajectory, and performing fitting processing on the escape trajectory points to obtain fitting trajectory points; constructing an organic release profile of the bio-based raw material based on the fitted trajectory points; Calculating the organic release intensity of the bio-based raw material based on the organic release profile; Calculating the potential change rate corresponding to the bio-based raw material based on the smoothed potential recording curve; Calculating the instability risk coefficient of the bio-based raw material based on the organic release intensity and the potential change rate; Based on the instability risk coefficient, the colloidal stability of the bio-based raw material is calculated.

10. The method for synthesizing a highly bio-based waterborne polyurethane resin according to claim 1, wherein: The calculating the instability risk coefficient of the bio-based raw material by combining the organic release intensity and the potential change rate includes: The instability risk coefficient of the bio-based raw material is calculated by the following formula: in, represents the instability risk factor of bio-based raw materials, represents the rate of change of potential, represents the extreme value of the rate of change of potential, Indicates the organic release intensity, Indicates the extreme value of organic release intensity.

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