Method and device for detecting purity of OLED intermediate material

Abstract

This invention discloses a method and apparatus for detecting the purity of OLED intermediate materials, relating to the field of materials testing. The method includes: performing multi-dimensional detection on the material to be tested to obtain multiple detection spectra; emitting a purity numerical signal when the multiple spectra meet predetermined confirmation constraints; obtaining the chemical purity value of the material to be tested using chromatography; obtaining predetermined functional targets for the OLED device and matching the target functional requirements of the material to be tested within the targets; retrieving corresponding predetermined functional indicators to detect the material to be tested to obtain functional indicator parameters; and performing quality assessment on the material to be tested in conjunction with the chemical purity value. This application solves the problems of existing intermediate material quality testing that focus only on chemical purity while neglecting functional performance, have insufficient accuracy in structural confirmation, and fail to match test results with actual application needs. It achieves the effect of balancing chemical purity and functional performance testing, improving the accuracy of structural confirmation, and ensuring that test results are accurately matched with actual application needs.

Description

Technical Field

[0001] This application relates to the field of materials testing, and in particular to a method and apparatus for detecting the purity of OLED intermediate materials. Background Technology

[0002] The purity and functional performance of OLED intermediate materials directly determine the display effect, lifespan, and stability of OLED devices, forming the core foundation for the high-quality development of the OLED industry. They are crucial for ensuring consistency in mass production and reducing production costs. Currently, the mainstream technology for quality testing of OLED intermediate materials primarily uses a single chromatographic method to determine the chemical purity, supplemented by simple infrared spectroscopy for preliminary structural confirmation. Specifically, high-performance liquid chromatography (HPLC) or gas chromatography (GC) is used to determine the content of target and impurity components in the material, calculating the chemical purity value. Then, characteristic peaks in the infrared spectrum are used to preliminarily determine whether there are any obvious structural anomalies. However, existing methods only focus on detecting the chemical purity of the material, neglecting the critical impact of the functional performance of OLED intermediate materials on devices. Furthermore, single-spectral detection is insufficient to accurately confirm the material structure, easily leading to misjudgments where chemical purity meets standards but functional performance is unqualified. It also fails to comprehensively reflect potential defects such as molecular configuration and thermal stability, resulting in a disconnect between test results and actual application requirements, making it difficult to meet the high-quality requirements of OLED devices for intermediate materials.

[0003] Currently, the quality testing of OLED intermediate materials suffers from several technical problems, including a single testing dimension, focusing only on chemical purity while neglecting functional performance, and insufficient accuracy in structural confirmation, leading to test results that cannot match the actual application requirements of devices. Summary of the Invention

[0004] This application provides a method and apparatus for detecting the purity of OLED intermediate materials. The method involves multi-dimensional detection of the OLED intermediate material to obtain corresponding detection spectra. A structure verification mechanism is used to determine whether the spectra meet predetermined verification constraints. If they do, a purity numerical signal is emitted. Based on this signal, the chemical purity value of the material is measured using chromatography. Simultaneously, the target functional requirements of the material are matched from the predetermined functional objectives of the OLED device. Corresponding predetermined functional indicators are retrieved and detected to obtain functional indicator parameters. A comprehensive evaluation mechanism combining chemical purity values ​​and functional indicator parameters is used to complete the quality assessment of the OLED intermediate material. This method solves the technical problems of existing OLED intermediate material quality detection methods, such as a single detection dimension, focusing only on chemical purity while neglecting functional performance, and insufficient accuracy in structure verification, leading to test results that cannot match the actual application requirements of the device. The method achieves the technical effect of enriching the detection dimensions, taking into account both chemical purity and functional performance detection, improving the accuracy of structure verification, and ensuring that the test results accurately match the actual application requirements of the OLED device.

[0005] This application provides a method for detecting the purity of OLED intermediate materials, comprising: performing multi-dimensional detection on the OLED intermediate material to be tested to obtain multiple detection spectra; according to a structural verification mechanism, when the multiple detection spectra reach a predetermined verification constraint, emitting a purity numerical signal; based on the purity numerical signal, obtaining the chemical purity value of the OLED intermediate material to be tested using chromatography; obtaining a predetermined functional target of the OLED device, and matching the target functional requirements of the OLED intermediate material to be tested within the predetermined functional target; retrieving the predetermined functional indicators corresponding to the target functional requirements, and detecting the predetermined functional indicators on the OLED intermediate material to be tested to obtain functional indicator parameters; and according to a comprehensive evaluation mechanism, coordinating the chemical purity value and the functional indicator parameters to perform a quality evaluation of the OLED intermediate material to be tested.

[0006] In a possible implementation, according to the structural verification mechanism, when the multiple detection spectra reach a predetermined verification constraint, a purity numerical signal is emitted, and the following processing is performed: a predetermined standard sample of the OLED intermediate material to be tested is obtained, and multiple standard spectra of the predetermined standard sample are obtained through multi-dimensional detection; the multiple standard spectra are compared with the multiple detection spectra to obtain a spectrum comparison result; an arbitrary similarity is obtained based on any comparison result in the spectrum comparison result; according to the structural verification mechanism, when the arbitrary similarity is within the similarity tolerance range, the predetermined verification constraint is reached.

[0007] In a possible implementation, the following process is performed: the predetermined standard sample is detected in a predetermined dimension, wherein the predetermined dimension includes at least a nuclear magnetic resonance spectroscopy dimension, an infrared spectroscopy dimension, and a mass spectrometry dimension.

[0008] In a possible implementation, the following process is performed: according to the structural verification mechanism, when any similarity is not within the similarity tolerance range, the OLED intermediate material to be tested is a defective product, and subsequent testing is terminated.

[0009] In a possible implementation, the following process is performed: when the OLED intermediate material to be tested is a defective product, the chemical purity value and the functional index parameters are fed back to the production process control link of the OLED intermediate material to be tested, so as to guide the optimization of process parameters including reaction temperature, reaction time, catalyst dosage or recrystallization conditions.

[0010] In possible implementations, the following processing is performed: the predetermined functional objective refers to thermal stability and / or electrochemical stability and / or optical purity.

[0011] In a possible implementation, the following process is performed: if the target functional requirement is the thermal stability function, a thermogravimetric analysis (TGA) scheme is introduced to detect the predetermined functional index of the OLED intermediate material under test at the target thermal decomposition temperature; wherein, the target thermal decomposition temperature refers to the temperature at which the mass loss of the OLED intermediate material under test reaches a predetermined percentage according to the target relationship curve; wherein, the target relationship curve refers to the relationship curve of the mass change of the OLED intermediate material under test with temperature recorded by heating the OLED intermediate material under test at a constant heating rate under inert gas protection.

[0012] In a possible implementation, the following process is performed: if the target functional requirement is the electrochemical stability function, a cyclic voltammetry scheme is introduced to detect the predetermined functional index of the OLED intermediate material to be tested, wherein the cyclic voltammetry scheme contains a preset deviation; wherein the preset deviation refers to the maximum deviation range between the measured value of the highest occupied molecular orbital energy level or the lowest unoccupied molecular orbital energy level of the OLED intermediate material to be tested and the theoretical design value.

[0013] In a possible implementation, the following process is performed: if the target functional requirement is the optical purity function, an ultraviolet-visible absorption spectroscopy scheme is introduced to detect the predetermined functional index of the OLED intermediate material to be tested, wherein the ultraviolet-visible absorption spectroscopy scheme contains preset limits; wherein the preset limits refer to the lowest value of the ratio of characteristic absorption peak intensities or fluorescence quantum yield of the OLED intermediate material to be tested at a specific wavelength.

[0014] This application also provides a purity detection device for OLED intermediate materials, comprising: a multi-dimensional detection module for performing multi-dimensional detection on the OLED intermediate material to be tested to obtain multiple detection spectra; a structure verification module for issuing a purity numerical signal when the multiple detection spectra reach a predetermined verification constraint according to a structure verification mechanism; a chemical purity numerical acquisition module for obtaining the chemical purity numerical value of the OLED intermediate material to be tested using chromatography based on the purity numerical signal; a target functional requirement matching module for obtaining a predetermined functional target of the OLED device and matching the target functional requirement of the OLED intermediate material to be tested among the predetermined functional targets; a predetermined functional index detection module for retrieving the predetermined functional index corresponding to the target functional requirement and detecting the predetermined functional index on the OLED intermediate material to be tested to obtain functional index parameters; and a quality evaluation module for performing quality evaluation on the OLED intermediate material to be tested according to a comprehensive evaluation mechanism, in conjunction with the chemical purity numerical value and the functional index parameters.

[0015] This application proposes a method and apparatus for detecting the purity of OLED intermediate materials. First, the OLED intermediate material to be tested undergoes multi-dimensional detection, yielding multiple detection spectra. Then, based on a structural verification mechanism, when the multiple detection spectra meet predetermined verification constraints, a purity numerical signal is emitted. Next, based on the purity numerical signal, the chemical purity value of the OLED intermediate material to be tested is obtained using chromatography. Then, predetermined functional targets for the OLED device are obtained, and the target functional requirements of the OLED intermediate material to be tested are matched within these predetermined functional targets. Furthermore, predetermined functional indicators corresponding to the target functional requirements are retrieved, and the OLED intermediate material to be tested is subjected to the detection of these predetermined functional indicators to obtain functional indicator parameters. Finally, based on a comprehensive evaluation mechanism, the chemical purity value and the functional indicator parameters are combined to perform a quality assessment of the OLED intermediate material to be tested. Through the above process, the method and apparatus proposed in this application achieve the technical effects of enriching detection dimensions, balancing chemical purity and functional performance detection, improving the accuracy of structural verification, and ensuring that the detection results are accurately matched with the actual application requirements of OLED devices. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings of the embodiments of the present invention will be briefly described below. Flowcharts are used in this application to illustrate the operations performed by the system according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, various steps can be processed in reverse order or simultaneously as needed. Furthermore, other operations can be added to these processes, or one or more steps can be removed from these processes.

[0017] Figure 1 This is a flowchart illustrating a method for detecting the purity of OLED intermediate materials provided in an embodiment of this application.

[0018] Figure 2 This is a schematic diagram of the structure of an OLED intermediate material purity detection device provided in an embodiment of this application.

[0019] Figure labeling: Multi-dimensional detection module 10, structure confirmation module 20, chemical purity value acquisition module 30, target functional requirement matching module 40, predetermined functional indicator detection module 50, quality assessment module 60. Detailed Implementation

[0020] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0021] This application provides a method for detecting the purity of OLED intermediate materials, such as... Figure 1 As shown, the method includes: Step S100: Perform multi-dimensional detection on the OLED intermediate material to be tested to obtain multiple detection spectra.

[0022] Specifically, a predetermined mass of the OLED intermediate material to be tested was weighed, and the same batch of weighed OLED intermediate materials was tested using three detection devices: nuclear magnetic resonance (NMR) spectroscopy, infrared spectroscopy, and mass spectrometry. The NMR spectroscopy conditions were set as follows: the sample was dissolved in deuterated chloroform and injected into a 5 mm NMR tube; proton and carbon spectra were acquired at 400 MHz, and the NMR spectrum of the sample was output. The infrared spectroscopy conditions were set as follows: using an attenuated total reflectance accessory, the sample was placed directly on the surface of a diamond crystal, and 32 scans were performed within the wavenumber range of 4000-4000, outputting the infrared spectrum of the sample. The mass spectrometry conditions were set as follows: using an electrospray ionization source in positive ion mode, with a mass scan range of 50 u to 2000 u, outputting the mass spectrum of the sample. The detection devices in the above three dimensions output corresponding detection spectra, namely the nuclear magnetic resonance spectrum, the infrared spectrum, and the mass spectrum, which serve as multiple detection spectra.

[0023] Step S200: According to the structural verification mechanism, when the multiple detection spectra reach the predetermined verification constraints, a purity numerical signal is emitted.

[0024] Specifically, the multiple detection spectra obtained in step S100 are compared with multiple standard spectra of a predetermined standard sample. The predetermined confirmation constraint is defined as follows: the spectral similarity in each of the three dimensions—NMR spectroscopy, infrared spectroscopy, and mass spectrometry—is within a preset similarity tolerance range. When the spectral similarity in all three dimensions meets the above condition, the predetermined confirmation constraint is deemed met, and a Boolean-type purity numerical signal is generated and emitted. A true value for this signal indicates that subsequent purity numerical detection steps are allowed. If the spectral similarity in any of the three dimensions—NMR spectroscopy, infrared spectroscopy, and mass spectrometry—is not within the preset similarity tolerance range, the predetermined confirmation constraint is deemed not met. In this case, a false purity numerical signal is emitted, and the subsequent detection process is terminated; steps S300, S400, S500, and S600 are not executed.

[0025] In one possible implementation, according to the structural verification mechanism, when the multiple detection spectra reach a predetermined verification constraint, a purity numerical signal is emitted. Step S200 further includes step S210, acquiring a predetermined standard sample of the OLED intermediate material to be tested, and obtaining multiple standard spectra of the predetermined standard sample through multi-dimensional detection. The predetermined standard sample is detected using predetermined dimensions, which include at least nuclear magnetic resonance (NMR) spectroscopy, infrared spectroscopy, and mass spectrometry. Specifically, a certified predetermined standard sample of the OLED intermediate material to be tested with a purity of not less than 99.9% is taken from the standard sample library, and the predetermined standard sample is detected using the same predetermined dimensions as in step S100. The predetermined dimensions include at least nuclear magnetic resonance (NMR) spectroscopy, infrared spectroscopy, and mass spectrometry. The detection conditions for the NMR spectroscopy dimension are: using deuterated chloroform as a solvent, acquiring proton and carbon spectra at a frequency of 400 MHz, and outputting the NMR spectrum of the predetermined standard sample as one of the standard spectra. The detection conditions for infrared spectroscopy are as follows: using an attenuated total reflectance accessory, scanning 32 times in the wavenumber range of 4000-400, and outputting the infrared spectrum of the predetermined standard sample as one of the standard spectra. The detection conditions for mass spectrometry are as follows: using an electrospray ionization source, positive ion mode, mass scan range of 50u~2000u, and outputting the mass spectrum of the predetermined standard sample as one of the standard spectra. The standard spectra of the above three dimensions together constitute multiple standard spectra.

[0026] Step S220: Compare the multiple standard spectra with the multiple detection spectra to obtain spectral comparison results. Specifically, compare the spectra one by one in the NMR, infrared, and mass spectrometry dimensions. For the NMR dimension, a peak position matching algorithm is used: compare the signal peaks at each chemical shift in the NMR spectrum to be tested with the corresponding signal peaks at the chemical shifts in the standard NMR spectrum, and record the chemical shift deviation of each signal peak. For the infrared dimension, a characteristic absorption peak wavenumber matching algorithm is used: compare the wavenumber values ​​of each characteristic absorption peak in the infrared spectrum to be tested with the corresponding wavenumber values ​​in the standard infrared spectrum, and record the wavenumber deviation of each characteristic absorption peak. For the mass spectrometry dimension, a mass-to-charge ratio matching algorithm is used: compare the mass-to-charge ratio values ​​of each major ion peak in the mass spectrum to be tested with the corresponding mass-to-charge ratio values ​​of the ion peaks in the standard mass spectrum, and record the mass-to-charge ratio deviation of each ion peak. After the above comparisons are completed, a spectral comparison result set is output, which contains a list of deviation records in the three dimensions.

[0027] Step S230: Obtain arbitrary similarity based on any comparison result in the spectrum comparison results. Specifically, for each dimension in the aforementioned spectrum comparison result set, calculate the similarity for that dimension. For the nuclear magnetic resonance (NMR) spectroscopy dimension, the calculation of similarity first requires determining the allowable threshold for chemical shift deviation. This allowable threshold is determined as follows: using the same instrument parameters and sample concentration as the sample to be tested, repeatedly detect the predetermined standard sample 10 times, record the chemical shift value of each signal peak, calculate the standard deviation of the chemical shift for each signal peak in the 10 detections, and multiply the largest standard deviation among all signal peaks by 3 to obtain the allowable threshold for chemical shift deviation. Then, count the total number of signal peaks in the NMR spectrum to be tested with a signal-to-noise ratio greater than 10, and record this as the total number. Record the number of signal peaks with a chemical shift deviation less than or equal to the above allowable threshold for chemical shift deviation as the matching number. Divide the matching number by the total number and multiply by 100% to obtain the NMR spectral similarity, expressed as a percentage. For the infrared spectroscopy dimension, the calculation of similarity first requires determining the allowable threshold for wavenumber deviation. The method for determining the permissible threshold is as follows: Using the same instrument parameters as the sample to be tested, the predetermined standard sample is repeatedly tested 10 times. The wavenumber of each characteristic absorption peak is recorded, and the standard deviation of the wavenumber of each characteristic absorption peak in the 10 tests is calculated. The largest standard deviation among all characteristic absorption peaks is multiplied by 3 to obtain the permissible threshold for wavenumber deviation. Then, the total number of characteristic absorption peaks with a signal-to-noise ratio greater than 3 in the infrared spectrum to be tested is counted and recorded as the total number. The signal-to-noise ratio is calculated by dividing the peak height of the characteristic absorption peak by the root mean square value of the baseline noise. The number of characteristic absorption peaks with a wavenumber deviation less than or equal to the above permissible threshold for wavenumber deviation is recorded as the matching number. The matching number is divided by the total number and then multiplied by 100% to obtain the infrared spectral similarity, expressed as a percentage. For the mass spectrometry dimension, the calculation of similarity first requires determining the permissible threshold for mass-to-charge ratio deviation and the cutoff threshold for relative abundance. The method for determining the mass-to-charge ratio deviation tolerance threshold is as follows: Using the same instrument parameters as the sample to be tested, the predetermined standard sample is repeatedly tested 10 times. The mass-to-charge ratio value of each major ion peak is recorded, and the standard deviation of the mass-to-charge ratio of each ion peak in the 10 tests is calculated. The largest standard deviation value among all ion peaks is multiplied by 3 to obtain the mass-to-charge ratio deviation tolerance threshold. The method for determining the relative abundance cutoff threshold is as follows: The predetermined standard sample is mass spectrometrically detected. The intensity value of the base peak, i.e., the peak with a relative abundance of 100%, is recorded as the reference intensity. 10% of the reference intensity is used as the relative abundance cutoff threshold, i.e., only ion peaks with an intensity greater than or equal to this cutoff threshold are counted. Then, the intensity values ​​of all ion peaks in the mass spectrum of the sample to be tested are counted. The total number of ion peaks with an intensity greater than or equal to the above relative abundance cutoff threshold is recorded as the total number. The number of ion peaks with a mass-to-charge ratio deviation less than or equal to the above mass-to-charge ratio deviation tolerance threshold is recorded as the matching number. The matching number is divided by the total number and then multiplied by 100% to obtain the mass spectrometry similarity, in percentage form.Any one of the above-mentioned nuclear magnetic resonance spectral similarity, infrared spectral similarity, and mass spectrometry similarity can be used as an arbitrary similarity output.

[0028] Step S240: According to the structural verification mechanism, when any similarity falls within the similarity tolerance interval, the predetermined verification constraint is met. Specifically, the lower and upper limits of the similarity tolerance interval are determined. The method for determining the lower limit of the similarity tolerance interval is as follows: using the same instrument parameters and sample concentration as the sample to be tested, the predetermined standard sample is repeatedly tested 10 times. For each test, the similarity of the nuclear magnetic resonance spectrum, infrared spectrum, and mass spectrometry between the test and the predetermined standard sample is calculated according to the method in step S230. The average value and standard deviation of the 10 similarity values ​​obtained from the 10 tests in each dimension are calculated respectively. The average value of the dimension minus three times the standard deviation is used as the lower limit of the similarity tolerance interval for that dimension. The upper limit of the similarity tolerance interval is fixed at 100%. The similarity of the nuclear magnetic resonance spectrum, infrared spectrum, and mass spectrometry calculated in step S230 is compared with the similarity tolerance interval of their respective dimensions. When the similarity of the nuclear magnetic resonance (NMR) spectrum is greater than or equal to its lower limit of dimension and less than or equal to 100%, the similarity of the infrared spectrum is greater than or equal to its lower limit of dimension and less than or equal to 100%, and the similarity of the mass spectrometry spectrum is greater than or equal to its lower limit of dimension and less than or equal to 100%, the predetermined confirmation constraint is considered met. At this point, a confirmation pass flag is generated, which is a Boolean value of true, allowing subsequent steps to be executed.

[0029] Step S250: According to the structural verification mechanism, when any similarity is not within the similarity tolerance range, the OLED intermediate material to be tested is a defective product, and subsequent testing is terminated. Specifically, the nuclear magnetic resonance (NMR) spectral similarity calculated in step S230 is compared with the similarity tolerance range of the NMR spectral dimension, the infrared spectral similarity is compared with the similarity tolerance range of the infrared spectral dimension, and the mass spectrometry similarity is compared with the similarity tolerance range of the mass spectrometry dimension. If the NMR spectral similarity is less than the lower limit of the similarity tolerance range of the NMR spectral dimension, or the infrared spectral similarity is less than the lower limit of the similarity tolerance range of the infrared spectral dimension, or the mass spectrometry similarity is less than the lower limit of the similarity tolerance range of the mass spectrometry dimension, then it is determined that the predetermined verification constraint has not been met. At this time, a verification failure flag is generated, which is a Boolean false flag, and the OLED intermediate material to be tested is marked as a defective product. Simultaneously, the detection system immediately stops executing all subsequent operations in steps S300, S400, S500, and S600, and outputs a detection termination report. This report includes the material code of the OLED intermediate material to be tested, the detection time, the specific values ​​of nuclear magnetic resonance spectral similarity, infrared spectral similarity, and mass spectrometry similarity, the lower limit of the similarity tolerance range for each dimension, and a description of the reason for non-compliance. The description of the reason for non-compliance specifically indicates which dimension(s) the similarity is lower than the lower limit of the corresponding dimension.

[0030] In one possible implementation, step S200 further includes step S260, whereby, when the OLED intermediate material to be tested is a non-conforming product, the chemical purity value and the functional index parameters are fed back to the production process control stage of the OLED intermediate material to be tested, to guide the optimization of process parameters including reaction temperature, reaction time, catalyst dosage, or recrystallization conditions. Specifically, this step provides two parallel implementation methods, one of which is selected for execution according to the detection requirements in practical applications. First implementation method: After determining that the OLED intermediate material to be tested is a non-conforming product in step S250, the detection system immediately terminates the entire detection process and does not execute steps S300, S400, S500, and S600. At this time, since subsequent detection is not performed, neither the chemical purity value nor the functional index parameters are obtained. Therefore, in this implementation method, no feedback operation is performed, i.e., no feedback data packet is sent to the production process control stage. This implementation method is suitable for rapid detection scenarios that only require structural confirmation screening and do not require obtaining detailed functional data of non-conforming products. The second implementation method: After determining that the OLED intermediate material to be tested is unqualified in step S250, the detection system does not terminate the detection process, but continues to execute steps S300, S400, S500, and S600 normally to fully obtain the chemical purity value and various functional index parameters. After all the above steps are completed, the feedback module of the detection system packages all the data generated in this detection process into a feedback data packet. The feedback data packet is in comma-separated value format and includes the following fields: material code, detection timestamp, chemical purity value, thermal decomposition temperature value (if detected), energy level difference value (if detected), fluorescence quantum yield value (if detected), nuclear magnetic resonance spectrum similarity, infrared spectrum similarity, mass spectrometry similarity, lower limit of the similarity tolerance interval for each dimension, and unqualified reason code. This feedback data packet is sent to the manufacturing execution system in the production process control stage via an Ethernet interface.

[0031] The Manufacturing Execution System (MES) executes corresponding process optimization instructions based on the information in the feedback data packet. If the reason for non-compliance is that the NMR spectrum similarity is lower than its tolerance limit, it indicates that the peak position of the NMR signal of the target molecule in the OLED intermediate material to be tested deviates systematically from that of the standard sample. This deviation is usually related to byproduct formation caused by reaction temperature fluctuations or incomplete reaction due to insufficient catalyst dosage. The MES determines the adjustment instructions based on the degree of deviation: the larger the absolute value of the chemical shift deviation, the more serious the molecular structure deviation, the greater the tightening of the reaction temperature fluctuation range, and the higher the proportion of catalyst dosage increase. The specific adjustment amount is obtained by querying the preset fuzzy control rule table in the MES. This rule table divides the similarity deviation into three levels: slight deviation, moderate deviation, and severe deviation, with each level corresponding to a preset adjustment step size.

[0032] If the reason for non-compliance is that the infrared spectral similarity is lower than its tolerance limit, it indicates that the wavenumber of the absorption peak of the characteristic functional group in the OLED intermediate material to be tested deviates from that of the standard sample. This deviation is usually related to improper control of recrystallization conditions leading to crystal form or solvent residue. The manufacturing execution system determines the adjustment command based on the sign and magnitude of the wavenumber deviation: if the characteristic absorption peak shifts towards lower wavenumbers, it indicates that the intermolecular forces are enhanced, and the recrystallization cooling rate needs to be reduced to improve crystal growth conditions; if the characteristic absorption peak shifts towards higher wavenumbers, it indicates the presence of solvent residue or oxidation products, and the number of recrystallizations needs to be increased to improve the purification effect. The specific adjustment amount is calculated by the proportional-integral-derivative control algorithm preset in the manufacturing execution system. This algorithm takes the wavenumber deviation value as input and outputs the adjustment value of the recrystallization cooling rate and the increase in the number of recrystallizations.

[0033] If the reason for non-compliance is that the mass spectrometry similarity is lower than its tolerance limit, it indicates that the molecular weight or fragment distribution of the OLED intermediate material to be tested deviates from that of the standard sample. This deviation is usually related to insufficient reaction time leading to incomplete conversion of the intermediate or excessive reaction time leading to the formation of degradation products. The Manufacturing Execution System (MES) determines the adjustment instructions based on the specific value of the mass-to-charge ratio deviation: if a low molecular ion peak and a high fragment ion peak are detected, it indicates degradation, and the reaction time should be shortened and the reaction temperature lowered; if a low molecular ion peak and no obvious fragment peak are detected, it indicates incomplete reaction, and the reaction time should be extended. The specific adjustment amount is obtained by matching a preset expert rule base in the MES, which stores the correspondence between different mass spectrometry deviation modes and reaction time adjustment amounts.

[0034] If the chemical purity value is low, it indicates that the content of the target component in the OLED intermediate material being tested is below the set threshold. This problem is usually related to insufficient reaction conversion or low purification and separation efficiency. The manufacturing execution system determines the adjustment command based on the ratio of the difference between the chemical purity value and the chemical purity threshold: the larger the ratio of the difference, the greater the reduction in reaction temperature and the higher the ratio of the extension in reaction time. The specific adjustment amount is calculated by a preset linear interpolation table in the manufacturing execution system. This interpolation table takes the percentage of purity deviation as input and outputs the reaction temperature adjustment value and the reaction time adjustment value.

[0035] If the thermal decomposition temperature is lower than the design value, it indicates insufficient thermal stability of the OLED intermediate material under test. This problem is usually related to imperfect crystal form due to recrystallization conditions or catalytic decomposition of residual impurities. The manufacturing execution system determines the adjustment command based on the difference between the thermal decomposition temperature and the design value: the larger the difference, the more the recrystallization cooling rate needs to be reduced to promote the formation of a more perfect crystal form. The specific adjustment amount is calculated by a pre-set proportional controller in the manufacturing execution system.

[0036] If the energy level difference exceeds the preset deviation range, it indicates that the electronic energy level of the OLED intermediate material under test does not match the theoretical design. This problem is usually related to improper catalyst dosage leading to deviations in molecular conjugation or substituent positions. The manufacturing execution system determines the adjustment command based on the direction of deviation between the measured energy level difference and the theoretical design value: if the measured energy level difference is less than the theoretical design value, it indicates insufficient molecular conjugation or a lack of electron-donating groups, requiring an increase in catalyst dosage to promote reaction completion; if the measured energy level difference is greater than the theoretical design value, it indicates excessive molecular conjugation or the introduction of electron-withdrawing groups, requiring a decrease in catalyst dosage to suppress side reactions. The specific adjustment amount is calculated by a preset incremental proportional-integral-derivative control algorithm in the manufacturing execution system. This algorithm takes the energy level difference deviation value as input and outputs the percentage adjustment of catalyst dosage.

[0037] All the above adjustment instructions are automatically calculated and sent by the manufacturing execution system based on the specific values ​​in the feedback data packet. This implementation method is suitable for scenarios that require comprehensive analysis of various indicators of non-conforming products for in-depth optimization of production processes.

[0038] Step S300: Based on the purity numerical signal, the chemical purity value of the OLED intermediate material to be tested is obtained by chromatography.

[0039] Specifically, after confirming the receipt of a true purity numerical signal, high-performance liquid chromatography (HPLC) was used to analyze the OLED intermediate material. This involved dissolving the OLED intermediate material in chromatographic-grade acetonitrile to prepare a sample solution with a concentration of 0.1 mg / mL. The HPLC column used was an octadecylsilane-bonded silica column with a length of 250 mm, an inner diameter of 4.6 mm, and a packing particle size of 5 μm. The mobile phase was a 70:30 volume ratio of acetonitrile to water, with a flow rate of 1.0 mL / min, a column temperature of 30 °C, and a detection wavelength of 254 nm. The injection volume was 10 μL. After the chromatograph output, the chemical purity was calculated using the area normalization method: the sum of the areas of all integrated peaks in the chromatogram was taken as the total peak area; the area of ​​the main peak corresponding to the target component was divided by the total peak area, and then multiplied by 100% to obtain the chemical purity value of the OLED intermediate material, expressed as a percentage.

[0040] Step S400: Obtain the predetermined functional targets of the OLED device, and match the target functional requirements of the OLED intermediate material to be tested in the predetermined functional targets. The predetermined functional targets refer to thermal stability function and / or electrochemical stability function and / or optical purity function.

[0041] Specifically, the pre-defined functional targets set during the current OLED device design phase are retrieved from the process control system database. These targets include one or more of the following: thermal stability, electrochemical stability, and optical purity. The pre-defined functional targets are determined based on the role of the OLED intermediate material under test within the target OLED device. If the material is used as the main material of the emissive layer, thermal stability and electrochemical stability are tested; if it is used as a dopant material in the emissive layer, thermal stability, electrochemical stability, and optical purity are tested; and if it is used in the electron transport layer or hole transport layer, thermal stability and electrochemical stability are tested. Then, the material code of the OLED intermediate material under test is used as the query key and matched against a material functional requirement mapping table. This mapping table pre-stores the correspondence between each OLED intermediate material code and its corresponding target functional requirement, which is also recorded as a tag representing at least one of thermal stability, electrochemical stability, or optical purity. Upon successful matching, one or more target functional requirement tags are output to indicate the type of functional indicator testing to be performed subsequently. If no corresponding record is found for the material code in the mapping table, a warning signal is issued and the testing process is terminated.

[0042] Step S500: Retrieve the predetermined functional indicators corresponding to the target functional requirements, and perform the predetermined functional indicators on the OLED intermediate material to be tested to obtain functional indicator parameters.

[0043] Specifically, based on the target functional requirement tag matched in step S400, the corresponding predetermined functional index is retrieved from the functional index parameter library. For the thermal stability functional tag, the predetermined functional index type is the target thermal decomposition temperature, and the qualification condition is that the target thermal decomposition temperature is not lower than the thermal decomposition temperature threshold. The method for determining the thermal decomposition temperature threshold is as follows: take the highest ambient temperature when the OLED intermediate material is working in the target OLED device, add a safety margin to the highest ambient temperature as the thermal decomposition temperature threshold, and ensure that the material will not undergo significant thermal decomposition within the device's operating temperature range. For the electrochemical stability functional tag, the predetermined functional index type is the energy level difference between the highest occupied molecular orbital energy level and the lowest unoccupied molecular orbital energy level, or the deviations of the highest occupied molecular orbital energy level and the lowest unoccupied molecular orbital energy level are judged separately. One of the two judgment methods is selected and pre-selected according to the functional role of the OLED intermediate material under test in the device during specific implementation. The qualification criteria are as follows: If the energy level difference criterion is used, the absolute value of the deviation between the measured value and the theoretical design value of the energy level difference shall not exceed the preset deviation range; if the separate criterion is used, the absolute values ​​of the deviation between the measured value and the theoretical design value of the highest occupied molecular orbital energy level and the absolute values ​​of the deviation between the measured value and the theoretical design value of the lowest unoccupied molecular orbital energy level shall not exceed their respective preset deviation ranges. The method for determining this preset deviation range is as follows: density functional theory calculations are performed on the theoretically designed molecular structure of the OLED intermediate material. Geometric optimization and energy level calculations are performed using the B3LYP functional and the 6-31G asterisk basis set to obtain the theoretical highest occupied molecular orbital energy level HOMO. theo And the theoretical lowest unoccupied molecular orbital energy level LUMO theo Then, the theoretical energy level difference ΔE is calculated. theo =LUMO theo -HOMO theo Regarding the method for determining energy level differences, the theoretical energy level difference ΔE is... theo 5% is set as the preset deviation range; for separate determination methods, the theoretically highest occupied molecular orbital energy level HOMO is used. theo The 2% threshold is used as the preset deviation range for the HOMO energy level, and the theoretical lowest unoccupied molecular orbital energy level LUMO is determined. theoA 2% threshold is used as the preset deviation range for the LUMO energy level. For the optical purity functional label, the predetermined functional index type is either the characteristic absorption peak intensity ratio or the fluorescence quantum yield, with one of the two methods selected in advance based on the optical properties of the OLED intermediate material to be tested. If the characteristic absorption peak intensity ratio method is used, the pass / fail condition is that the characteristic absorption peak intensity ratio of the test sample is not less than 0.95 times the characteristic absorption peak intensity ratio of the predetermined standard sample; if the fluorescence quantum yield method is used, the pass / fail condition is that the fluorescence quantum yield of the test sample is not less than the minimum fluorescence quantum yield value required for the external quantum efficiency of the OLED device to reach the design target. After retrieval, the OLED intermediate material to be tested is tested according to the corresponding detection plan in steps S510, S520, and S530, and the functional index parameters are output.

[0044] In one possible implementation, step S500 further includes step S510, whereby if the target functional requirement is the thermal stability function, a thermogravimetric analysis (TGA) scheme is introduced to detect the predetermined functional index of the OLED intermediate material under test at a target thermal decomposition temperature; wherein, the target thermal decomposition temperature refers to the temperature at which the mass loss of the OLED intermediate material under test reaches a predetermined percentage according to the target relationship curve; wherein, the target relationship curve refers to the relationship curve of the mass change of the OLED intermediate material under test with temperature recorded by heating the OLED intermediate material under test at a constant heating rate under inert gas protection.

[0045] Specifically, if a thermal stability function tag is identified from the target functional requirement tags, the thermogravimetric analysis (TGA) plan is invoked. The specific execution is as follows: A thermogravimetric analyzer is used to test the OLED intermediate material. A certain mass (e.g., 5-10 mg) of the OLED intermediate material is weighed and placed in an alumina crucible, which is then placed on the balance support of the TGA analyzer. Under inert gas protection (e.g., nitrogen protection), the OLED intermediate material is heated at a constant heating rate (e.g., 10°C per minute). The TGA analyzer records the mass change of the OLED intermediate material with temperature in real time, generating a target relationship curve. The horizontal axis of this curve represents temperature, and the vertical axis represents mass retention rate. Based on the target relationship curve, the temperature corresponding to the predetermined percentage of mass loss of the OLED intermediate material is calculated. This predetermined percentage is determined by taking the upper limit of acceptable thermal decomposition weight loss for the OLED intermediate material. Based on the OLED device packaging and operation requirements, this is typically set to 5%, meaning that when the mass loss exceeds 5%, the material has undergone significant thermal decomposition, potentially releasing gases that could lead to device failure. The specific calculation method is as follows: Read the temperature value corresponding to a mass retention rate of 100 minus the predetermined percentage from the target relationship curve. For example, when the predetermined percentage is 5%, read the temperature corresponding to a mass retention rate of 95%, and record this temperature value as the target thermal decomposition temperature. Then, compare the target thermal decomposition temperature with the thermal decomposition temperature threshold in the predetermined functional indicators retrieved in step S500. If the target thermal decomposition temperature is greater than or equal to the threshold, the functional indicator is deemed qualified; if it is lower than the threshold, it is deemed unqualified.

[0046] Step S520: If the target functional requirement is the electrochemical stability function, a cyclic voltammetry scheme is introduced to detect the predetermined functional index of the OLED intermediate material to be tested. The cyclic voltammetry scheme contains a preset deviation. The preset deviation refers to the maximum deviation range between the measured value of the highest occupied molecular orbital energy level or the lowest unoccupied molecular orbital energy level of the OLED intermediate material to be tested and the theoretical design value.

[0047] Specifically, if an electrochemical stability function label is identified from the target functional requirement label, the cyclic voltammetry plan is invoked. The specific execution is as follows: An electrochemical workstation is used to test the OLED intermediate material. The test solution is prepared by dissolving the OLED intermediate material in anhydrous acetonitrile to a concentration of 1 mmol / L, and then adding the supporting electrolyte tetrabutylammonium hexafluorophosphate to achieve a concentration of 0.1 mol / L. A three-electrode system is used: a glassy carbon electrode as the working electrode, a silver / silver ion electrode as the reference electrode, and a platinum wire electrode as the counter electrode. The three electrodes are then immersed in the test solution.

[0048] The scanning potential range of the electrochemical workstation is determined based on the theoretically calculated energy levels of the OLED intermediate material to be tested. Specifically, the method is as follows: using the theoretically highest occupied molecular orbital (HOMO) energy level... theo The starting potential is obtained by subtracting 0.5V from the corresponding potential, and the theoretical lowest unoccupied molecular orbital energy level LUMO is used. theo A termination potential of 0.5V was added to the corresponding potential. The scan rate was set to 0.1V / s, and the number of cycles was set to 3. The electrochemical workstation acquired and output the cyclic voltammetry curves.

[0049] Read the oxidation peak potential E from the cyclic voltammetry curve. ox and reduction peak potential E red The method for determining the reference electrode calibration value is as follows: ferrocene is added to the test solution, and the oxidation potential E of ferrocene is measured under test conditions identical to those of the test sample. Fc Then the reference electrode calibration value E ref =E Fc -0.69V, where 0.69V is the standard oxidation potential of ferrocene relative to a standard hydrogen electrode.

[0050] The highest occupied molecular orbital energy level (HOMO) is calculated using the following formula. meas and the lowest unoccupied molecular orbital energy level LUMO meas : HOMO meas =-4.8-(E ox -E ref ) LUMO meas =-4.8-(E red -E ref ) Here, -4.8 is a commonly used reference value for the standard hydrogen electrode potential relative to the vacuum energy level. Then, the energy level difference ΔE is calculated. meas ΔE meas =LUMO meas -HOMO meas The cyclic voltammetry scheme contains a preset deviation. The method for determining the range of this preset deviation is as follows: The theoretical highest occupied molecular orbital energy level (HOMO) calculated using density functional theory in step S500 is used as the reference value. theo Theoretically lowest unoccupied molecular orbital energy level LUMO theo And the theoretical energy level difference ΔE theo The preset deviation range is determined as follows: For the energy level difference determination method, the preset deviation range ΔE is... tol =0.05×ΔE theo That is, 5% of the theoretical energy level difference; for separate determination methods, the preset deviation range of the HOMO energy level is HOMO. tol =0.02×|HOMOtheo |, Preset deviation range of LUMO energy level LUMO tol =0.02×|LUMO theo |, which is 2% of the absolute value of the theoretical energy level.

[0051] The determination process is as follows: If the energy level difference determination method is used, calculate the absolute value ΔE of the deviation between the measured energy level difference and the theoretical energy level difference. diff =|ΔE meas -ΔE theo |. If ΔE diff ≤ΔE tol If ΔE is qualified, then the functional indicator is deemed acceptable; diff >ΔE tol If a separate judgment method is used, the absolute value of the deviation between the HOMO measured value and the theoretical value is calculated. diff =|HOMO meas -HOMO theo | Calculate the absolute value of the deviation between the measured and theoretical LUMO values. diff =|LUMO meas -LUMO theo |. If HOMO diff ≤HOMO tol And LUMO diff ≤LUMO tol If so, the function indicator is deemed qualified; if HOMO diff HOMO tol Or LUMO diff >LUMO tol If so, it is deemed unqualified.

[0052] Step S530: If the target functional requirement is the optical purity function, an ultraviolet-visible absorption spectroscopy scheme is introduced to detect the predetermined functional index of the OLED intermediate material to be tested. The ultraviolet-visible absorption spectroscopy scheme contains preset limits. The preset limits refer to the lowest value of the ratio of characteristic absorption peak intensities or fluorescence quantum yield of the OLED intermediate material to be tested at a specific wavelength.

[0053] Specifically, if an optical purity functional label is identified from the target functional requirement label, the UV-Vis absorption spectroscopy pre-program is invoked. This step provides two parallel implementation methods, one of which is pre-selected based on the optical properties of the OLED intermediate material to be tested.

[0054] The first implementation method is based on the intensity ratio of characteristic absorption peaks. An ultraviolet-visible spectrophotometer is used to detect the OLED intermediate material to be measured. The material to be measured is dissolved in chromatographic grade dichloromethane to prepare a solution with a concentration of 10 μmol / L, which is injected into a quartz cuvette. Scanning is performed within the range of 250 nm - 700 nm to obtain an ultraviolet-visible absorption spectrum. The method for determining the wavelength of the characteristic absorption peak is as follows: in the ultraviolet-visible absorption spectrum, the wavelength corresponding to the peak with the maximum absorbance and a half-peak width less than 20 nm is selected as the wavelength of the characteristic absorption peak. This implementation method provides two sub-methods for calculating the intensity ratio, which are pre-selected according to the material characteristics during specific implementation. The first sub-method: Read the intensity value at the wavelength of the characteristic absorption peak from the spectrum of the sample to be measured, and at the same time read the intensity value at the same wavelength from the spectrum of a predetermined standard sample, and calculate the ratio of the intensity value of the sample to be measured to the intensity value of the standard sample as the intensity ratio. The second sub-method: Read the intensity value at the wavelength of the characteristic absorption peak from the spectrum of the sample to be measured, and at the same time read the intensity value at another wavelength of the characteristic absorption peak, and calculate the ratio of the two as the intensity ratio. The method for determining the wavelength of the other characteristic absorption peak is as follows: in the ultraviolet-visible absorption spectrum, the wavelength corresponding to the peak with the second largest absorbance and a difference from the wavelength of the characteristic absorption peak greater than 30 nm is selected as the wavelength of the other characteristic absorption peak. The preset limit value refers to the lowest value of this intensity ratio, and its determination method is: perform the same detection on the predetermined standard sample, calculate its intensity ratio according to the selected sub-method, and take 0.95 times of this ratio as the lowest value. Compare the intensity ratio of the sample to be measured with this lowest value. If it is greater than or equal to this lowest value, it is judged as qualified; otherwise, it is judged as unqualified.

[0055] The second implementation method is based on the fluorescence quantum yield. Joint detection is performed using an ultraviolet-visible spectrophotometer and a fluorescence spectrometer. The material to be measured is dissolved in chromatographic grade dichloromethane to prepare a solution with a concentration of 10 μmol / L. The absorbance value of this solution at the excitation wavelength is measured using an ultraviolet-visible spectrophotometer. The integrated fluorescence intensity of the sample to be measured is measured using a fluorescence spectrometer at the same excitation wavelength. Quinine sulfate dissolved in 0.1 mol / L sulfuric acid solution is used as a standard reference sample, with a fluorescence quantum yield of 54.6%. Its absorbance value and integrated fluorescence intensity are measured at the same excitation wavelength. The fluorescence quantum yield of the sample to be measured is calculated according to the standard relative method. The preset limit value refers to the lowest value of the fluorescence quantum yield, and its determination method is: when taking this OLED intermediate material as the light-emitting layer material, the lowest fluorescence quantum yield value required to make the external quantum efficiency of the OLED device using this material reach the design target. Compare the fluorescence quantum yield of the sample to be measured with this lowest value. If it is greater than or equal to this lowest value, it is judged as qualified; otherwise, it is judged as unqualified.

[0056] Step S600: Based on the comprehensive evaluation mechanism, the quality of the OLED intermediate material to be tested is evaluated in conjunction with the chemical purity value and the functional index parameters.

[0057] Specifically, a comprehensive evaluation is performed based on the chemical purity value obtained in step S300 and the various qualification judgment results obtained in steps S510, S520, and S530. A preset chemical purity threshold is established. The method for determining this threshold is as follows: five OLED intermediate materials with different chemical purities are prepared, standard OLED devices are fabricated for each, and the decay lifetime is tested. The device lifetime with a purity of 99.9% is used as the benchmark. When the device lifetime decays to 90% of the benchmark lifetime, the corresponding chemical purity value is the chemical purity threshold.

[0058] First, determine if the chemical purity value is greater than or equal to the chemical purity threshold. If it is lower than the threshold, the product is directly judged as unqualified because the chemical purity does not meet the standard. If the chemical purity meets the standard, further check whether all the required functional indicators are qualified. The required functional indicators are determined by the target functional requirement label matched in step S400, and may include one or more of the following: thermal stability function, electrochemical stability function, and optical purity function. When all the required functional indicators are judged to be qualified, the overall evaluation result is qualified; if any functional indicator is judged to be unqualified, the overall evaluation result is unqualified, and the reason for non-compliance is output, specifically indicating which functional indicator did not meet the standard, along with the measured value and the threshold or range required for qualification.

[0059] This application embodiment obtains corresponding detection spectra by performing multi-dimensional detection on the OLED intermediate material under test. Based on the structural confirmation mechanism, it determines whether the spectrum meets the predetermined confirmation constraints. If it does, a purity numerical signal is issued. Based on this signal, the chemical purity value of the material is measured by chromatography. At the same time, the target functional requirements required by the material are matched from the predetermined functional targets of the OLED device. The corresponding predetermined functional indicators are retrieved and detected to obtain functional indicator parameters. Through a comprehensive evaluation mechanism combining chemical purity values ​​and functional indicator parameters, the quality evaluation of the OLED intermediate material is completed. This solves the technical problems of existing OLED intermediate material quality detection, such as the single detection dimension, focusing only on chemical purity and ignoring functional performance, insufficient accuracy of structural confirmation, and the inability of the detection results to match the actual application requirements of the device. It achieves the technical effect of enriching the detection dimensions, taking into account both chemical purity and functional performance detection, improving the accuracy of structural confirmation, and making the detection results accurately match the actual application requirements of the OLED device.

[0060] In the above text, refer to Figure 1 A method for detecting the purity of OLED intermediate materials according to embodiments of the present invention is described in detail. Next, reference will be made to... Figure 2This invention describes an apparatus for detecting the purity of OLED intermediate materials according to an embodiment of the present invention.

[0061] An OLED intermediate material purity testing device according to an embodiment of the present invention addresses the technical problems of existing OLED intermediate material quality testing, such as a single testing dimension, focusing only on chemical purity while neglecting functional performance, and insufficient accuracy in structural confirmation, resulting in test results that cannot match the actual application requirements of devices. The device achieves the technical effect of enriching testing dimensions, taking into account both chemical purity and functional performance testing, improving the accuracy of structural confirmation, and ensuring that the test results accurately match the actual application requirements of OLED devices. The OLED intermediate material purity testing device includes: a multi-dimensional testing module 10, a structural confirmation module 20, a chemical purity value acquisition module 30, a target functional requirement matching module 40, a predetermined functional index testing module 50, and a quality evaluation module 60.

[0062] The system includes a multi-dimensional detection module 10 for performing multi-dimensional detection on the OLED intermediate material to be tested, obtaining multiple detection spectra; a structure verification module 20 for issuing a purity numerical signal when the multiple detection spectra reach a predetermined verification constraint according to a structure verification mechanism; a chemical purity numerical acquisition module 30 for obtaining the chemical purity value of the OLED intermediate material to be tested using chromatography based on the purity numerical signal; a target functional requirement matching module 40 for obtaining the predetermined functional target of the OLED device and matching the target functional requirement of the OLED intermediate material to be tested among the predetermined functional targets; a predetermined functional index detection module 50 for retrieving the predetermined functional index corresponding to the target functional requirement and detecting the predetermined functional index on the OLED intermediate material to be tested to obtain functional index parameters; and a quality evaluation module 60 for performing quality evaluation on the OLED intermediate material to be tested according to a comprehensive evaluation mechanism, coordinating the chemical purity value and the functional index parameters.

[0063] The detailed description of the specific configuration of the structure verification module 20 is explained as follows: As mentioned above, according to the structure verification mechanism, when the multiple detection spectra reach the predetermined verification constraint, a purity numerical signal is emitted. The structure verification module 20 may further include: a standard spectrum acquisition unit for acquiring a predetermined standard sample of the OLED intermediate material to be tested, and obtaining multiple standard spectra of the predetermined standard sample through multi-dimensional detection; a spectrum comparison unit for comparing the multiple standard spectra with the multiple detection spectra to obtain a spectrum comparison result; a similarity calculation unit for obtaining any similarity based on any comparison result in the spectrum comparison result; and a verification constraint unit for reaching the predetermined verification constraint when the arbitrary similarity is within the similarity tolerance range, according to the structure verification mechanism.

[0064] The standard spectrum acquisition unit may further include: detecting the predetermined standard sample in a predetermined dimension, wherein the predetermined dimension includes at least a nuclear magnetic resonance spectroscopy dimension, an infrared spectroscopy dimension, and a mass spectrometry dimension.

[0065] The structure verification module 20 may further include a termination detection unit, which, according to the structure verification mechanism, determines that if any similarity is not within the similarity tolerance range, the OLED intermediate material to be tested is a defective product, and subsequent detection is terminated.

[0066] The structure verification module 20 may further include a process parameter optimization unit, which, when the OLED intermediate material to be tested is a defective product, feeds back the chemical purity value and the functional index parameters to the production process control link of the OLED intermediate material to be tested, so as to guide the optimization of process parameters including reaction temperature, reaction time, catalyst dosage or recrystallization conditions.

[0067] The specific configuration of the target functional requirement matching module 40 is described in detail below: As mentioned above, the target functional requirement matching module 40 may further include: the predetermined functional target refers to thermal stability function and / or electrochemical stability function and / or optical purity function.

[0068] The specific configuration of the predetermined functional indicator detection module 50 is described in detail below: As mentioned above, the predetermined functional indicator detection module 50 may further include: a thermogravimetric analysis (TGA) scheme introduction unit, used to introduce a TGA scheme to detect the predetermined functional indicator of the OLED intermediate material under test at a target thermal decomposition temperature if the target functional requirement is the thermal stability function; wherein, the target thermal decomposition temperature refers to the temperature corresponding to when the mass loss of the OLED intermediate material under test reaches a predetermined percentage according to the target relationship curve; wherein, the target relationship curve refers to the relationship curve of the mass change of the OLED intermediate material under test with temperature recorded when the OLED intermediate material under test is heated at a constant heating rate under inert gas protection.

[0069] The predetermined functional index detection module 50 may further include: a cyclic voltammetry scheme introduction unit for introducing a cyclic voltammetry scheme to detect the predetermined functional index of the OLED intermediate material under test if the target functional requirement is the electrochemical stability function. The cyclic voltammetry scheme contains a preset deviation. The preset deviation refers to the maximum deviation range between the measured value of the highest occupied molecular orbital energy level or the lowest unoccupied molecular orbital energy level of the OLED intermediate material under test and the theoretical design value.

[0070] The predetermined functional index detection module 50 may further include: an ultraviolet-visible absorption spectroscopy scheme introduction unit, used to introduce an ultraviolet-visible absorption spectroscopy scheme to detect the predetermined functional index of the OLED intermediate material under test if the target functional requirement is the optical purity function. The ultraviolet-visible absorption spectroscopy scheme contains preset limit values. The preset limit values ​​refer to the lowest values ​​of the ratio of characteristic absorption peak intensities or fluorescence quantum yield of the OLED intermediate material under test at a specific wavelength.

[0071] The OLED intermediate material purity detection device provided in this embodiment of the invention can execute the OLED intermediate material purity detection method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0072] Although this application makes various references to certain modules in the system according to the embodiments of this application, any number of different modules can be used and run on user terminals and / or servers. The various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy distinction between each other and are not used to limit the scope of protection of this invention.

[0073] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A method for detecting the purity of OLED intermediate materials, characterized in that, include: Multi-dimensional detection was performed on the OLED intermediate material to be tested, and multiple detection spectra were obtained; According to the structural verification mechanism, when the multiple detection spectra reach the predetermined verification constraints, a purity numerical signal is emitted. Based on the purity numerical signal, the chemical purity value of the OLED intermediate material to be tested is obtained by chromatography. Obtain the predetermined functional targets of the OLED device, and match the target functional requirements of the OLED intermediate material under test in the predetermined functional targets; The predetermined functional indicators corresponding to the target functional requirements are retrieved, and the predetermined functional indicators are detected on the OLED intermediate material to be tested to obtain the functional indicator parameters. Based on the comprehensive evaluation mechanism, the quality of the OLED intermediate material to be tested is evaluated by combining the chemical purity value with the functional index parameters.

2. The method for detecting the purity of OLED intermediate materials as described in claim 1, characterized in that, According to the structural verification mechanism, when the multiple detection spectra reach the predetermined verification constraints, a purity numerical signal is emitted, including: A predetermined standard sample of the OLED intermediate material to be tested was obtained, and multiple standard spectra of the predetermined standard sample were obtained by multi-dimensional detection. The multiple standard spectra are compared with the multiple detected spectra to obtain the spectrum comparison results; Any similarity can be obtained from any comparison result in the spectral comparison results; According to the structure verification mechanism, when any similarity is within the similarity tolerance range, the predetermined verification constraint is reached.

3. The method for detecting the purity of OLED intermediate materials as described in claim 2, characterized in that, The predetermined standard sample is detected according to predetermined dimensions, wherein the predetermined dimensions include at least nuclear magnetic resonance spectroscopy, infrared spectroscopy, and mass spectrometry.

4. The method for detecting the purity of OLED intermediate materials as described in claim 2, characterized in that, According to the structure verification mechanism, when any similarity is not within the similarity tolerance range, the OLED intermediate material to be tested is a defective product, and subsequent testing is terminated.

5. The method for detecting the purity of OLED intermediate materials as described in claim 4, characterized in that, When the OLED intermediate material to be tested is a defective product, the chemical purity value and the functional index parameters are fed back to the production process control of the OLED intermediate material to be tested, so as to guide the optimization of process parameters including reaction temperature, reaction time, catalyst dosage or recrystallization conditions.

6. The method for detecting the purity of OLED intermediate materials as described in claim 1, characterized in that, The predetermined functional objectives refer to thermal stability and / or electrochemical stability and / or optical purity.

7. The method for detecting the purity of OLED intermediate materials as described in claim 6, characterized in that, If the target functional requirement is the thermal stability function, a thermogravimetric analysis plan is introduced to detect the predetermined functional indicators of the OLED intermediate material to be tested at the target thermal decomposition temperature; The target thermal decomposition temperature refers to the temperature at which the mass loss of the OLED intermediate material under test reaches a predetermined percentage, according to the target relationship curve. The target relationship curve refers to the relationship curve of the mass of the OLED intermediate material under test as a function of temperature, recorded when the material is heated at a constant heating rate under inert gas protection.

8. The method for detecting the purity of OLED intermediate materials as described in claim 6, characterized in that, If the target functional requirement is the electrochemical stabilization function, a cyclic voltammetry scheme is introduced to detect the predetermined functional indicators of the OLED intermediate material to be tested, wherein the cyclic voltammetry scheme contains a preset deviation. The preset deviation refers to the maximum deviation range between the measured value of the highest occupied molecular orbital energy level or the lowest unoccupied molecular orbital energy level of the OLED intermediate material under test and the theoretical design value.

9. The method for detecting the purity of OLED intermediate materials as described in claim 6, characterized in that, If the target functional requirement is the optical purity function, an ultraviolet-visible absorption spectroscopy scheme is introduced to detect the predetermined functional index of the OLED intermediate material to be tested, wherein the ultraviolet-visible absorption spectroscopy scheme contains preset limit values. The preset limit refers to the lowest value of the ratio of characteristic absorption peak intensity or fluorescence quantum yield of the OLED intermediate material under test at a specific wavelength.

10. A purity detection device for OLED intermediate materials, characterized in that, The apparatus is used to implement the purity detection method for OLED intermediate materials according to any one of claims 1-9, and the apparatus comprises: The multi-dimensional detection module is used to perform multi-dimensional detection on the OLED intermediate material under test and obtain multiple detection spectra. The structure verification module is used to issue a purity numerical signal when the multiple detection spectra reach the predetermined verification constraints, according to the structure verification mechanism. A chemical purity value acquisition module is used to acquire the chemical purity value of the OLED intermediate material to be tested by using chromatography based on the purity value signal. The target functional requirement matching module is used to obtain the predetermined functional targets of the OLED device and match the target functional requirements of the OLED intermediate material to be tested among the predetermined functional targets. The predetermined functional index detection module is used to retrieve the predetermined functional index corresponding to the target functional requirement, and to detect the predetermined functional index on the OLED intermediate material to be tested, so as to obtain the functional index parameters. The quality assessment module is used to assess the quality of the OLED intermediate material to be tested by combining the chemical purity value and the functional index parameters according to the comprehensive assessment mechanism.

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