Multi-channel multi-phase rapid high-throughput formula screening method

Abstract

The invention discloses a multi-channel multi-phase rapid high-throughput formula screening method, which relates to the technical field of formula screening, and comprises the following steps: preparing reagents of different substance phases needing to be formulated, adding different reagents into each channel of a multi-phase reactor according to a preset formula ratio, after the reagents are added, mixing and stirring operations are performed; a multi-phase reactor is used for simulating a complex environment related to a plurality of different substance phases in an experiment; the method comprises the following steps: acquiring multiple items of data information, including static setting stability information and dynamic information, when the multiphase reactor simulates a plurality of different substance phase complex environments, and processing and comprehensively analyzing the static setting stability information and the dynamic information when the multiphase reactor simulates the plurality of different substance phase complex environments. By establishing a dynamic anomaly monitoring mechanism, the multiphase reactor simulates a plurality of complex environments with different substance phases for real-time monitoring, so that the system can detect the abnormal hidden danger condition of the multiphase reactor in time in the experiment process.

Description

Technical Field

[0001] The present invention relates to the technical field of experimental formula screening, and in particular to a multi-channel multi-phase rapid high-throughput formula screening method. Background Art

[0002] The multi-channel multi-phase rapid high-throughput formulation screening system is a highly advanced experimental platform designed to accelerate the research and development process of new materials or new drugs in the fields of chemistry and biology. The system has the ability to operate in multiple channels and can perform multiple experiments at the same time, making the experimental process more efficient. Its multi-phase characteristics mean that it can handle complex experimental conditions involving different states of matter, including solids, liquids and gases. At the same time, the high-throughput design of the system enables it to quickly process a large number of samples, thereby generating rich data in a short time.

[0003] In practical applications, this system is often used for formulation screening, that is, to find the optimal formulation or experimental conditions by trying different ingredients and conditions. Its fast and high-throughput characteristics enable scientists and researchers to evaluate a large number of possibilities in a shorter time, accelerating the discovery and optimization of new products or new drugs. The integration of automation technology further improves the consistency and repeatability of experiments and reduces the possibility of human error.

[0004] This system is particularly important in drug development because it can help scientists quickly explore complex chemical spaces and find compounds with ideal properties. In addition, this system has a wide range of applications in materials science, food industry and other fields, providing scientists with a powerful tool to cope with complex and large experimental design and data analysis challenges. By integrating multi-channel, multi-phase, high-speed and high-throughput features, this formulation screening system is pushing the frontier of experimental science and opening up new possibilities for innovation and discovery.

[0005] Multiphase reactors are usually used for formula screening in multi-channel multiphase rapid high-throughput formula screening systems. The main function of a multiphase reactor is to simulate the complex environment involving multiple different material phases (such as solids, liquids, and gases) in the experiment. Such a reactor allows different phase reactions in multiple channels to be carried out simultaneously in the same system, thereby achieving a more realistic simulation of complex chemical processes. Its design enables scientists to explore multiple reaction conditions in one experiment, improve experimental efficiency, and quickly screen out the optimal formula or conditions. The key advantage of a multiphase reactor is that it provides a more realistic and complex reaction environment that is adapted to the various material states that exist in practical applications. This enables the formula screening system to more comprehensively evaluate the interactions between different phases and provide a more accurate and reliable data basis for formula optimization. Through the application of multiphase reactors, scientists can better understand the reaction characteristics of multi-component formulas under complex conditions and accelerate the discovery and optimization process of new materials and new drugs.

[0006] The prior art has the following deficiencies:

[0007] If the multiphase reactor in the multi-channel multiphase rapid high-throughput formulation screening system has anomalies during the simulation experiment, involving a complex environment of multiple different material phases, the anomaly may cause the multiphase reactor to be unable to accurately simulate the actual reaction conditions, resulting in distortion of the experimental data. Since the goal of formulation screening is to find the optimal conditions, any inaccurate simulation of the experimental environment will cause the obtained data to be unreliable, thereby misleading scientists' judgment. Secondly, since the anomaly of the multiphase reactor may lead to inaccurate experimental conditions, scientists may make formulation optimization decisions based on erroneous data, which may cause the selected formulation to fail in actual application or fail to meet the expected performance, thereby wasting a lot of time and resources.

[0008] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0009] The purpose of the present invention is to provide a multi-channel multi-phase rapid high-throughput formula screening method. By establishing a dynamic abnormality monitoring mechanism, a multiphase reactor is simulated to monitor the complex environment of multiple different material phases in real time, so that the system can detect abnormal hidden dangers of the multiphase reactor in time during the experiment, and then take corresponding measures. The implementation of this mechanism plays a vital role in improving the reliability of experimental data. Scientists can trust the experimental results more and avoid making misleading judgments based on erroneous data, thereby providing a more reliable basis for scientific research. This is of great significance for research in fields such as formula optimization, ensuring the accuracy and scientificity of scientific research work, so as to solve the problems in the above-mentioned background technology.

[0010] In order to achieve the above object, the present invention provides the following technical solution: a multi-channel multi-phase rapid high-throughput formulation screening method, comprising the following steps:

[0011] Prepare reagents of different material phases that need to be formulated, add different reagents into various channels of the multiphase reactor according to a predetermined formula ratio, and perform mixing and stirring operations after the reagents are added;

[0012] Through multiphase reactor simulation experiments involving multiple different material phases in the complex environment;

[0013] Acquire multiple data information when a multiphase reactor simulates a complex environment of multiple different material phases, including static setting stability information and dynamic information, process and comprehensively analyze the static setting stability information and dynamic information when a multiphase reactor simulates a complex environment of multiple different material phases, establish a dynamic abnormal monitoring mechanism, and dynamically monitor the situation when a multiphase reactor simulates a complex environment of multiple different material phases;

[0014] When it is monitored that the multiphase reactor simulates a complex environment with multiple different material phases and has abnormal hidden dangers, the multiphase reactor simulation will be stopped and the corresponding experimental data will be discarded. At the same time, the abnormal hidden dangers will be further judged and different early warning prompts will be issued.

[0015] Preferably, the static setting stability information of the multiphase reactor when simulating a complex environment with multiple different material phases includes the pH value information, pressure control information and temperature control information of the multiphase reactor. The system parameter setting deviation coefficient is comprehensively generated by comparing and analyzing the real-time pH value, real-time pressure value and real-time temperature value in the multiphase reactor with the preset pH value, preset pressure value and preset temperature value set by the system; the dynamic information of the multiphase reactor when simulating a complex environment with multiple different material phases includes liquid phase flow rate distribution information and control command transmission frequency information. The liquid phase flow rate distribution difference coefficient is generated by processing the liquid phase flow rate distribution information, and the control command transmission frequency anomaly concealment coefficient is generated by processing the control command transmission frequency information.

[0016] Preferably, the logic for obtaining the system parameter setting deviation coefficient is as follows:

[0017] In the time window G, the real-time pH value, real-time pressure value, and real-time temperature value are obtained when the multiphase reactor simulates a complex environment with multiple different material phases, and the real-time pH value, real-time pressure value, and real-time temperature value are respectively used in time series by function f pH (t), f 压力 (t), f 温度 (t) indicates;

[0018] The real-time pH value, real-time pressure value, and real-time temperature value obtained in the time window G when the multiphase reactor simulates a complex environment of multiple different material phases are compared and analyzed with the preset pH value, preset pressure value, and preset temperature value set by the system, and the system parameter setting deviation coefficient is calculated. The calculation expression is: In the formula, Indicates the system parameter setting deviation coefficient, YS pH Indicates the preset pH value, YS 压力 Indicates the preset pressure value, YS 温度 Indicates the preset temperature value, t 1 , t 2 Respectively represent the start and end time of the time window G.

[0019] Preferably, the logic for obtaining the liquid phase flow velocity distribution difference coefficient is as follows:

[0020] Obtain the real-time liquid phase flow rate values ​​at different positions at the same time when the multiphase reactor simulates a complex environment with multiple different material phases, and calibrate the real-time liquid phase flow rate as ξ 流速 y , y represents the number of the real-time liquid phase flow rate values ​​at different positions at the same time when the multiphase reactor simulates a complex environment of multiple different material phases, x=1, 2, 3, 4, ..., h, h is a positive integer;

[0021] Calculate the standard deviation of the liquid phase flow rate value through a plurality of real-time liquid phase flow rate values ​​obtained at the same time by the multiphase reactor;

[0022] In the time window G, the standard deviation of the liquid phase flow rate value at different times when the multiphase reactor simulates a complex environment with multiple different material phases is obtained, and the obtained standard deviation of the liquid phase flow rate value is used to establish a data set. Then, the standard deviation of the liquid phase flow rate value in the data set is sorted in order, and the largest standard deviation of the liquid phase flow rate value is screened out, and the largest standard deviation of the liquid phase flow rate value is calibrated as ξ 流速 max ;

[0023] The maximum standard deviation of the liquid flow rate in the data set is ξ 流速 max Calculate the liquid phase flow velocity distribution difference coefficient, the calculation expression is: In the formula, ξ 流速 η Represents the liquid phase flow velocity distribution difference coefficient.

[0024] Preferably, the logic of obtaining the control command transmission frequency anomaly concealment coefficient is as follows:

[0025] Obtain the optimal control command transmission frequency range for the control system to send adjustment instructions to the multiphase reactor when the multiphase reactor simulates a complex environment with multiple different material phases, and calibrate the optimal control command transmission frequency range as φ 控制 ,in ~φ 控制 max ;

[0026] In the time window G, the actual control command transmission frequency of the control system sending adjustment instructions to the multiphase reactor at different time periods when the multiphase reactor simulates a complex environment with multiple different material phases is obtained, and the actual control command transmission frequency is calibrated as φ 控制 v, v represents the number of the actual control command transmission frequency of the control system sending the adjustment command to the multiphase reactor at different time periods when the multiphase reactor simulates a complex environment with multiple different material phases, v = 1, 2, 3, 4, ..., k, k is a positive integer;

[0027] Calculate the control command transmission frequency anomaly concealment coefficient, the calculation expression is: In the formula, φ 控制 μ represents the control command transmission frequency anomaly concealment coefficient, φ 控制 v′ represents the actual control command transmission frequency that is not in the optimal control command transmission frequency range obtained within the time window G when the multiphase reactor simulates a complex environment with multiple different material phases, v′ represents the number of the actual control command transmission frequency that is not in the optimal control command transmission frequency range obtained within the time window G when the multiphase reactor simulates a complex environment with multiple different material phases, v′=1, 2, 3, 4, ..., ', ' is a positive integer, and '≤, k represents the total number of actual control command transmission frequencies obtained within the time window G when the multiphase reactor simulates a complex environment with multiple different material phases.

[0028] Preferably, the system parameter setting deviation coefficient generated by the processed static setting stability information and dynamic information when the multiphase reactor simulates a complex environment of multiple different material phases is obtained. Liquid phase velocity distribution difference coefficient ξ 流速 η And the control command transmission frequency anomaly concealment coefficient φ 控制 μ Then, set the system parameter deviation coefficient Liquid phase velocity distribution difference coefficient ξ 流速 η And the control command transmission frequency anomaly concealment coefficient φ 控制 μ Establish data analysis model and generate simulation index MN θ , by simulating the index MN θ Dynamically monitor the multiphase reactor when simulating a complex environment with multiple different material phases.

[0029] Preferably, when a multiphase reactor simulates a complex environment with multiple different material phases, the larger the system parameter setting deviation coefficient generated in the time window G, the larger the liquid phase flow rate distribution difference coefficient, and the larger the control command transmission frequency anomaly concealment coefficient, that is, when a multiphase reactor simulates a complex environment with multiple different material phases, the simulation index MN generated in the time window G is greater. θThe larger the performance value, the greater the risk that the multiphase reactor cannot accurately simulate the actual reaction conditions and cause the experimental data to be distorted. Conversely, the smaller the risk that the multiphase reactor cannot accurately simulate the actual reaction conditions and cause the experimental data to be distorted.

[0030] Preferably, the simulation index generated in the time window G when the multiphase reactor simulates a complex environment of multiple different material phases is compared and analyzed with a preset simulation index reference threshold, and a dynamic abnormal monitoring mechanism is established to dynamically monitor the situation when the multiphase reactor simulates a complex environment of multiple different material phases. The specific logic is as follows:

[0031] If the simulation index is less than or equal to the simulation index reference threshold, a first signal is generated. When the multiphase reactor simulates a complex environment of multiple different material phases, when the first signal is generated, it indicates that the multiphase reactor can efficiently simulate the complex environment of multiple different material phases, and the simulation continues through the multiphase reactor;

[0032] If the simulation index is greater than the simulation index reference threshold, a second signal is generated. When the second signal is generated when the multiphase reactor simulates a complex environment of multiple different material phases, it indicates that the simulation has failed.

[0033] Preferably, when it is monitored that the multiphase reactor simulates a complex environment with multiple different material phases and has abnormal hidden dangers, the multiphase reactor simulation is stopped, and the corresponding experimental data are discarded, and at the same time, several simulation indexes subsequently generated when the multiphase reactor simulates a complex environment with multiple different material phases are obtained to establish an analysis set;

[0034] The simulated index mean and simulated index discrete value generated by several simulated indexes in the analysis set are calculated, and the simulated index mean and simulated index discrete value are compared and analyzed with the preset simulated index reference threshold and discrete value reference threshold respectively. The results of the comparison and analysis are as follows:

[0035] If the simulation index mean is less than or equal to the simulation index reference threshold and the simulation index discrete value is less than or equal to the discrete value reference threshold, a first-level warning signal is generated. When a multiphase reactor simulates a complex environment of multiple different material phases and generates a first-level warning signal, an accidental warning prompt is issued;

[0036] If the simulation index mean value is less than or equal to the simulation index reference threshold and the simulation index discrete value is less than or equal to the discrete value reference threshold, a secondary warning signal is generated. When a multiphase reactor simulates a complex environment of multiple different material phases and generates a secondary warning signal, an abnormal warning prompt is issued to alert relevant experimental personnel.

[0037] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0038] The present invention establishes a dynamic abnormal monitoring mechanism to simulate a complex environment of multiple different material phases in a multiphase reactor for real-time monitoring, so that the system can detect abnormal hidden dangers of the multiphase reactor in a timely manner during the experiment, and then take corresponding measures. The implementation of this mechanism plays a vital role in improving the reliability of experimental data. Scientists can trust the experimental results more and avoid making misleading judgments based on erroneous data, thereby providing a more reliable basis for scientific research. This is of great significance for research in the fields of formulation optimization and ensures the accuracy and scientificity of scientific research work.

[0039] The present invention introduces a real-time abnormal monitoring mechanism, which can detect problems in the early stage of the experiment, stop the simulation in time and discard the experimental data, so as to avoid long-term experiments under wrong conditions. This helps scientists to interrupt the simulation experiment in time to avoid wasting time and resources, and take further troubleshooting and repair measures when necessary, thereby improving the efficiency and operability of the experiment;

[0040] The present invention generates a first-level warning signal and a second-level warning signal, so that the present invention has the ability to distinguish between accidental anomalies and systematic anomalies. When the simulation index mean is less than or equal to the simulation index reference threshold and the simulation index discrete value is less than or equal to the discrete value reference threshold, a first-level warning signal is generated, indicating that there may be a sudden and accidental abnormal hidden danger. At this time, the system will stop the simulation experiment and discard the data, but the scientist can conduct the simulation experiment again. When the first-level warning conditions are not met, a second-level warning signal is generated, indicating that there may be a systematic abnormality and it is necessary to stop the simulation experiment and conduct equipment maintenance. Such differentiated processing helps scientists to judge abnormal conditions more accurately and improve their ability to respond to abnormal situations. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0042] Figure 1 The present invention is a method flow chart of a multi-channel multi-phase rapid high-throughput formulation screening method. DETAILED DESCRIPTION

[0043] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these example embodiments are provided so that the description of the present disclosure will be more comprehensive and complete, and the concept of the example embodiments will be fully conveyed to those skilled in the art.

[0044] The present invention provides Figure 1 A multi-channel multi-phase rapid high-throughput formulation screening method is shown, comprising the following steps:

[0045] Before the experiment begins, prepare the reagents of the different material phases required for formulation;

[0046] Reagents for the different material phases of a formulation may include liquids, solids, and gases, and these reagents usually represent the different components of the formulation.

[0047] Adding different reagents into various channels of the multiphase reactor according to a predetermined formula ratio, and performing mixing and stirring operations after the reagents are added;

[0048] The liquid handling system is used to add different liquid reagents to each channel of the multiphase reactor according to a predetermined formula ratio, which may involve liquid pumps, valves and other equipment to accurately control the amount of liquid added; for the addition of solid reagents, the system can use an automated solid powder handling system, which usually includes a solid reagent supply device, a weighing system and a conveying device, which can predetermine the type and quality of solid reagents required in each channel. The system will accurately add the corresponding amount of solid reagents to each channel, ensuring the accuracy and controllability of the formula. Such an automated solid handling system can efficiently process multiple channels, greatly improving the consistency and repeatability of the experiment; for the addition of gas reagents, the system can use a precise gas control system, which includes a gas supply system, a flow control device and a gas transmission pipeline. The gas type and flow rate required for each channel can be set through a preset program. The system will accurately control the amount of gas added, which ensures the accurate ratio of gas reagents in different channels and simulates the required gas phase reaction conditions in the experiment. The precision of this gas control system helps to achieve high-throughput formula screening while ensuring the controllability and safety of the experiment;

[0049] Mixing and stirring operations can be achieved by equipment such as stirrers and mixers.

[0050] Through multiphase reactor simulation experiments involving multiple different material phases in the complex environment;

[0051] The simulation experiment involves a complex environment with multiple different material phases, which may include liquid, gas and solid phase reactions, making the system closer to actual application scenarios.

[0052] Acquire multiple data information when a multiphase reactor simulates a complex environment of multiple different material phases, including static setting stability information and dynamic information, process and comprehensively analyze the static setting stability information and dynamic information when a multiphase reactor simulates a complex environment of multiple different material phases, establish a dynamic abnormal monitoring mechanism, and dynamically monitor the situation when a multiphase reactor simulates a complex environment of multiple different material phases;

[0053] The static setting stability information of the multiphase reactor when simulating a complex environment of multiple different material phases includes the pH value information, pressure control information and temperature control information of the multiphase reactor. The system parameter setting deviation coefficient is comprehensively generated by comparing and analyzing the real-time pH value, real-time pressure value and real-time temperature value in the multiphase reactor with the preset pH value, preset pressure value and preset temperature value set by the system.

[0054] When simulating a complex environment with multiple different material phases through a multiphase reactor, a large deviation between the real-time pH value and the preset pH value set by the system may cause the multiphase reactor to be unable to accurately simulate the actual reaction conditions, thereby causing distortion of the experimental data. The specific reasons are as follows:

[0055] Influence on reaction kinetics: pH value is a key parameter in many reactions and plays an important role in catalyst activity, reaction rate, etc. If there is a large deviation between the real-time pH value and the preset pH value, the kinetic behavior of the reaction may change, resulting in experimental results that are inconsistent with expectations.

[0056] Influence on reaction selectivity: In some multiphase reactions, specific pH conditions may be critical to selectivity. If the real-time pH value deviates from the preset value, it may lead to the occurrence of side reactions or the reduction of the selectivity of the main reaction, thus affecting the accuracy of the experimental results.

[0057] Impact on reaction equilibrium: pH value also has an important impact on the equilibrium of reactions involving acid-base neutralization. Real-time pH values ​​with large deviations may cause imbalance in the reaction equilibrium, affect the distribution of the final products of the reaction, and thus affect the interpretation of the experimental results.

[0058] Influencing solubility: In some reactions, solubility may change due to the influence of pH. If there is a large difference between the real-time pH value and the preset value, it may cause the solubility of the reactants or products to change, thus affecting the progress and results of the reaction.

[0059] Impact on catalyst activity: Changes in pH may affect the activity of catalysts, especially in catalytic reactions. Deviations between the real-time pH value and the preset value may cause changes in the performance of the catalyst, thereby affecting the reaction rate and selectivity.

[0060] When simulating a complex environment with multiple different material phases through a multiphase reactor, a large deviation between the real-time pressure value and the preset pressure value set by the system may cause the multiphase reactor to be unable to accurately simulate the actual reaction conditions, thereby causing distortion of the experimental data. The specific reasons are as follows:

[0061] Impact on reaction rate: Pressure is one of the key parameters for controlling the gas phase in multiphase reactions. A large deviation between the real-time pressure value and the preset pressure value may cause a change in the concentration of the gas phase, thereby affecting the reaction rate. This will make the experimental data inconsistent with the kinetics under actual reaction conditions.

[0062] Impact on reaction equilibrium: In multiphase reactions involving gas and liquid interactions, changes in pressure may cause a shift in the reaction equilibrium. If the real-time pressure value does not match the preset value, the reaction equilibrium may be affected, resulting in changes in product distribution, thus distorting the experimental results.

[0063] Influence on phase state: Changes in pressure may affect the phase state of different phases of matter in the reaction system. In multiphase reactions, changes in phase state may have an important impact on the progress and results of the reaction. Large pressure deviations may lead to abnormal changes in phase state, thereby affecting the reliability of experimental data.

[0064] Influence on solubility: In gas-liquid phase reactions, changes in pressure may affect the solubility of the gas in the liquid. If the real-time pressure value differs greatly from the preset value, it may cause excessive dissolution or escape of the gas, thus affecting the reaction and the interpretation of the experimental results.

[0065] Impact on the safety of the reactor: A large deviation between the real-time pressure value and the preset pressure value may cause the reactor to operate in an unsafe pressure range, increasing the risk of accidents. In order to ensure the safety of the experiment, it is necessary to ensure that the real-time monitoring and control of the pressure is consistent with the preset value set by the system.

[0066] When simulating a complex environment with multiple different material phases through a multiphase reactor, a large deviation between the real-time temperature value and the preset temperature value set by the system may cause the multiphase reactor to be unable to accurately simulate the actual reaction conditions, thereby causing distortion of the experimental data. The specific reasons are as follows:

[0067] Influence on reaction rate: Temperature is one of the key factors affecting reaction rate. Large real-time temperature deviation may cause the reaction rate to be inconsistent with the rate under actual reaction conditions, affecting the accuracy of experimental data.

[0068] Influence on reaction selectivity: Temperature has an important influence on the selectivity of some multiphase reactions. The deviation between the real-time temperature value and the preset value may cause different reaction pathways to be activated, affecting the selectivity of the reaction and the product distribution.

[0069] Affecting phase equilibrium: In multiphase reactions, temperature changes may cause the phase equilibrium position to shift. If the real-time temperature does not match the preset temperature, the phase equilibrium may be affected, which in turn affects the consistency of the experimental results.

[0070] Effect on solubility: Temperature changes may affect the solubility of substances in the reaction system, especially in multiphase reactions involving gas and liquid interactions. Large temperature deviations may lead to changes in solubility, affecting the reaction and product formation.

[0071] Influence on reaction kinetic parameters: Temperature changes will affect the kinetic parameters of the reaction, such as activation energy, etc. The deviation between the real-time temperature and the preset temperature may lead to inconsistency between the kinetic parameters under experimental conditions and those under preset conditions, thus affecting the interpretation and analysis of the data.

[0072] Therefore, the real-time pH value and the preset pH value set by the system when the multiphase reactor simulates a complex environment with multiple different material phases are monitored, the real-time pressure value and the preset pressure value set by the system when the multiphase reactor simulates a complex environment with multiple different material phases are monitored, and the real-time temperature value and the preset temperature value set by the system when the multiphase reactor simulates a complex environment with multiple different material phases are monitored. It can be perceived that the large deviation between the real-time pH value and the preset pH value set by the system, the large deviation between the real-time pressure value and the preset pressure value set by the system, and the large deviation between the real-time temperature value and the preset temperature value set by the system may cause the multiphase reactor to be unable to accurately simulate the actual reaction conditions, resulting in hidden dangers of distortion of experimental data.

[0073] The logic for obtaining the system parameter setting deviation coefficient is as follows:

[0074] In the time window G, the real-time pH value, real-time pressure value, and real-time temperature value are obtained when the multiphase reactor simulates a complex environment with multiple different material phases, and the real-time pH value, real-time pressure value, and real-time temperature value are respectively used in time series by function f pH (t), f 压力 (t), f 温度 (t) indicates;

[0075] It should be noted that a dedicated pH electrode is used to be inserted into the reactor, and the pH value of the reaction system is obtained in real time by detecting the hydrogen ion concentration. The signal of the pH electrode can be connected to a pH meter or a data acquisition system for real-time monitoring and recording. A pressure sensor is installed in the reactor to obtain the pressure value in real time by measuring the pressure change of the gas phase. The output signal of the sensor can be connected to the data acquisition system to achieve real-time monitoring and recording. A temperature sensor is installed in the reactor to directly measure the temperature of the reaction system. The output signal of the sensor is connected to a thermometer or a data acquisition system to achieve real-time temperature monitoring and recording.

[0076] The real-time pH value, real-time pressure value, and real-time temperature value obtained in the time window G when the multiphase reactor simulates a complex environment of multiple different material phases are compared and analyzed with the preset pH value, preset pressure value, and preset temperature value set by the system, and the system parameter setting deviation coefficient is calculated. The calculation expression is: In the formula, Indicates the system parameter setting deviation coefficient, YS pH Indicates the preset pH value, YS 压力 Indicates the preset pressure value, YS 温度 Indicates the preset temperature value, t 1 , t 2 Respectively represent the start and end time of the time window G;

[0077] It can be seen from the calculation expression of the system parameter setting deviation coefficient that when the multiphase reactor simulates a complex environment with multiple different material phases, the larger the performance value of the system parameter setting deviation coefficient generated within the time window G, the greater the potential risk that the multiphase reactor cannot accurately simulate the actual reaction conditions and cause distortion of the experimental data; conversely, the smaller the potential risk that the multiphase reactor cannot accurately simulate the actual reaction conditions and cause distortion of the experimental data.

[0078] The dynamic information of a multiphase reactor when simulating a complex environment of multiple different material phases includes liquid phase flow rate distribution information and control command transmission frequency information. The liquid phase flow rate distribution difference coefficient is generated by processing the liquid phase flow rate distribution information, and the control command transmission frequency anomaly concealment coefficient is generated by processing the control command transmission frequency information.

[0079] The liquid phase flow velocity distribution difference information refers to the change in the flow velocity of the liquid phase in space in a multiphase reactor. Since a multiphase reaction system usually includes liquid components of different material phases, the liquid phase flow velocity distribution difference information reflects the difference in flow velocity of the liquid in different areas inside the reactor. This information is crucial for understanding the miscibility and fluid dynamics behavior inside the reactor. By analyzing the flow velocity distribution differences in detail, we can understand the movement characteristics of the liquid phase in the reactor, optimize the reaction conditions, and improve the reaction efficiency.

[0080] In the multi-channel multi-phase rapid high-throughput formula screening system, the control command transmission frequency of the multiphase reactor refers to the rate at which the control system sends adjustment instructions to the actuator inside the reactor. This frequency determines the speed and accuracy of the system's adjustment of the reaction conditions. The importance of the control command transmission frequency lies in ensuring real-time monitoring and adjustment of the reaction conditions during the experiment. Through control command transmission, the system can respond to the dynamic changes of different material phases inside the reactor in real time to maintain the required experimental conditions.

[0081] When a multiphase reactor simulation experiment involves a complex environment with multiple different material phases, the large difference in liquid phase flow rate distribution may affect the accuracy and data reliability of the multiphase reactor simulation experiment. The specific reasons are as follows:

[0082] Uneven mixing: If the flow rate distribution of the liquid phase in the reactor varies greatly, the mixing effect of the reactants in different areas will be different. This may cause some areas to react slowly while other areas react quickly, making it difficult to accurately simulate the kinetic behavior of the entire reaction process.

[0083] Reaction temperature gradient generation: Uneven flow rate distribution will lead to different temperature distributions in different areas, thus forming a temperature gradient. Since the reaction rate is usually related to temperature, such a gradient may cause the reaction conditions in different areas to vary, making it impossible for the experiment to truly simulate uniform reaction conditions.

[0084] Differences in mass transfer effects: Uneven flow rates may lead to differences in the transfer rate of substances in different areas, affecting the distribution of the reaction substances in the reactor. This may lead to inconsistent product yields and distort the experimental results.

[0085] Interactions within the reactor: Interactions between regions with different flow rates may lead to local feedback effects, which in turn affect the kinetic behavior of the entire reactor. This makes the system behavior more complex and difficult to accurately predict with simple models.

[0086] Therefore, by monitoring the liquid phase flow rate distribution information when the multiphase reactor simulates a complex environment with multiple different material phases, it can be perceived that large differences in liquid phase flow rate distribution may cause the multiphase reactor to be unable to accurately simulate the actual reaction conditions, resulting in hidden dangers of distortion of experimental data.

[0087] The logic for obtaining the liquid phase flow velocity distribution difference coefficient is as follows:

[0088] Obtain the real-time liquid phase flow rate values ​​at different positions at the same time when the multiphase reactor simulates a complex environment with multiple different material phases, and calibrate the real-time liquid phase flow rate as ξ 流速 y , y represents the number of the real-time liquid phase flow rate values ​​at different positions at the same time when the multiphase reactor simulates a complex environment of multiple different material phases, x=1, 2, 3, 4, ..., h, h is a positive integer;

[0089] It should be noted that the position for obtaining the real-time liquid phase flow rate value in the multiphase reactor is not specifically limited here, but the selected positions are evenly distributed in the multiphase reactor, so as to more accurately obtain the real-time liquid phase flow rate values ​​at different positions in the multiphase reactor. Secondly, the flow rate sensors installed at different positions inside the multiphase reactor are the most direct way. These sensors can monitor the flow rate of the liquid phase in real time by measuring the speed of the fluid passing through. Sensors at different positions can provide flow rate information of different areas;

[0090] Calculate the standard deviation of the liquid phase flow rate value through a plurality of real-time liquid phase flow rate values ​​obtained at the same time by the multiphase reactor;

[0091] It should be noted that, when a multiphase reactor simulates a complex environment with multiple different material phases, the larger the standard deviation of the liquid phase flow rate value generated is, the greater the difference in the real-time liquid phase flow rate values ​​at different locations when the multiphase reactor simulates a complex environment with multiple different material phases is; conversely, the smaller the difference in the real-time liquid phase flow rate values ​​at different locations when the multiphase reactor simulates a complex environment with multiple different material phases is.

[0092] In the time window G, the standard deviation of the liquid phase flow rate value at different times when the multiphase reactor simulates a complex environment with multiple different material phases is obtained, and the obtained standard deviation of the liquid phase flow rate value is used to establish a data set. Then, the standard deviation of the liquid phase flow rate value in the data set is sorted in order, and the largest standard deviation of the liquid phase flow rate value is screened out, and the largest standard deviation of the liquid phase flow rate value is calibrated as ξ 流速 max ;

[0093] The maximum standard deviation of the liquid flow rate in the data set is ξ 流速 max Calculate the liquid phase flow velocity distribution difference coefficient, the calculation expression is: In the formula, ξ 流速 η represents the liquid phase flow velocity distribution difference coefficient;

[0094] From the calculation expression of the liquid phase flow velocity distribution difference coefficient, it can be seen that when the multiphase reactor simulates a complex environment with multiple different material phases, the larger the performance value of the liquid phase flow velocity distribution difference coefficient generated within the time window G, the greater the potential risk that the multiphase reactor cannot accurately simulate the actual reaction conditions and cause distortion of the experimental data; conversely, the smaller the potential risk that the multiphase reactor cannot accurately simulate the actual reaction conditions and cause distortion of the experimental data.

[0095] When simulating a complex environment involving multiple different material phases in a multiphase reactor, the control command transmission frequency is crucial for the multiphase reactor in a multi-channel multiphase rapid high-throughput formulation screening system. Too high or too low a frequency may cause distortion of the experimental data:

[0096] Too high a frequency: If the control command is delivered too frequently, the system will frequently adjust the reaction conditions. This can cause the system to overreact, introducing unnecessary fluctuations and noise. A fast control response may cause the system to adjust before the actual change occurs, resulting in unstable experimental conditions and ultimately affecting the accuracy of the data.

[0097] Frequency is too low: On the contrary, if the control command transmission frequency is too low, the system may not be able to respond to the actual changes inside the reactor in time. This will cause the system to be unable to maintain the required reaction conditions at certain moments, resulting in instability and inaccuracy of experimental conditions.

[0098] Loss of dynamic characteristics: Too high or too low control frequency may cause the system to lose the ability to capture the dynamic characteristics of the reaction. Some reaction processes may have fast dynamic responses and require high-frequency control commands to maintain the stability of experimental conditions. Low-frequency control may not be able to capture these rapid changes, resulting in distorted experimental results.

[0099] Difficulty tracking fast reactions: Some reactions may change rapidly in a short period of time, requiring the system to be able to adjust quickly to maintain the accuracy of experimental conditions. If the frequency is too low, the system may not be able to track these fast reactions, thus affecting the authenticity of the experimental data.

[0100] Therefore, by monitoring the control command transmission frequency when the multiphase reactor simulates a complex environment with multiple different material phases, it is possible to detect the hidden danger that abnormal control command transmission frequency may cause the multiphase reactor to be unable to accurately simulate the actual reaction conditions, resulting in distortion of experimental data.

[0101] The logic of obtaining the control command transmission frequency anomaly concealment coefficient is as follows:

[0102] Obtain the optimal control command transmission frequency range for the control system to send adjustment instructions to the multiphase reactor when the multiphase reactor simulates a complex environment with multiple different material phases, and calibrate the optimal control command transmission frequency range as φ 控制 min ~φ 控制 max ;

[0103] It should be noted that the frequency scanning experiment is carried out by gradually adjusting the control command transmission frequency, recording the system response, analyzing the experimental results, finding the system's sensitivity area to frequency changes, and determining the optimal frequency range. Considering the experimental objectives and the required dynamic response characteristics, if the experiment requires rapid dynamic adjustment, a higher frequency may be required, while for relatively slowly changing experimental conditions, the frequency can be moderately lowered. Therefore, when the multiphase reactor simulates a complex environment with multiple different material phases, the optimal control command transmission frequency range for the control system to send adjustment instructions to the multiphase reactor is not specifically limited here and can be adjusted according to actual needs.

[0104] In the time window G, the actual control command transmission frequency of the control system sending adjustment instructions to the multiphase reactor at different time periods when the multiphase reactor simulates a complex environment with multiple different material phases is obtained, and the actual control command transmission frequency is calibrated as φ 控制 v , v represents the number of the actual control command transmission frequency of the control system sending the adjustment command to the multiphase reactor at different time periods when the multiphase reactor simulates a complex environment with multiple different material phases, v = 1, 2, 3, 4, ..., k, k is a positive integer;

[0105] It should be noted that the selection of the duration within a time period is not specifically limited here. The durations within several time periods can all be equal, or all be unequal, or a cross of the two. There is no specific limitation here. Secondly, real-time database systems such as InfluxDB and Prometheus can be used to store and query real-time data. By associating the real-time data of the control system with the timestamp, the actual control command transmission frequency can be analyzed.

[0106] Calculate the control command transmission frequency anomaly concealment coefficient, the calculation expression is: In the formula, φ 控制 μ represents the control command transmission frequency anomaly concealment coefficient, φ 控制 v′ represents the actual control command transmission frequency that is not in the optimal control command transmission frequency range obtained in the time window G when the multiphase reactor simulates a complex environment with multiple different material phases, v′ represents the number of the actual control command transmission frequency that is not in the optimal control command transmission frequency range obtained in the time window G when the multiphase reactor simulates a complex environment with multiple different material phases, v′=1, 2, 3, 4, ..., ', ' is a positive integer, and '≤, k represents the total number of actual control command transmission frequencies obtained in the time window G when the multiphase reactor simulates a complex environment with multiple different material phases;

[0107] From the calculation expression of the control command transmission frequency anomaly concealment coefficient, it can be seen that when the multiphase reactor simulates a complex environment with multiple different material phases, the larger the performance value of the control command transmission frequency anomaly concealment coefficient generated within the time window G, the greater the potential risk of the multiphase reactor being unable to accurately simulate the actual reaction conditions and causing distortion of the experimental data. Conversely, the smaller the potential risk of the multiphase reactor being unable to accurately simulate the actual reaction conditions and causing distortion of the experimental data.

[0108] Obtain the system parameter setting deviation coefficient generated by the processed static setting stability information and dynamic information when simulating a complex environment with multiple different material phases in a multiphase reactor Liquid phase velocity distribution difference coefficient ξ 流速 η And the control command transmission frequency anomaly concealment coefficient φ 控制 μ Then, set the system parameter deviation coefficient Liquid phase velocity distribution difference coefficient ξ 流速 η And the control command transmission frequency anomaly concealment coefficient φ 控制 μ Establish data analysis model and generate simulation index MN θ , based on the formula: Where v1, v2, and v3 are the system parameter setting deviation coefficients respectively. Liquid phase velocity distribution difference coefficient ξ 流速 η , control command transmission frequency anomaly concealment coefficient φ 控制 μ The preset proportional coefficient, and v1, v2, and v3 are all greater than 0;

[0109] It can be seen from the calculation formula that when a multiphase reactor simulates a complex environment with multiple different material phases, the larger the system parameter setting deviation coefficient generated in the time window G, the larger the liquid phase flow rate distribution difference coefficient, and the larger the control command transmission frequency anomaly concealment coefficient, that is, when a multiphase reactor simulates a complex environment with multiple different material phases, the simulation index MN generated in the time window G is θ The larger the performance value, the greater the risk that the multiphase reactor cannot accurately simulate the actual reaction conditions and cause the experimental data to be distorted. Conversely, the smaller the risk that the multiphase reactor cannot accurately simulate the actual reaction conditions and cause the experimental data to be distorted.

[0110] The simulation index generated in the time window G when the multiphase reactor simulates a complex environment with multiple different material phases is compared and analyzed with the preset simulation index reference threshold, and a dynamic abnormal monitoring mechanism is established to dynamically monitor the situation when the multiphase reactor simulates a complex environment with multiple different material phases. The specific logic is as follows:

[0111] If the simulation index is less than or equal to the simulation index reference threshold, a first signal is generated. When the multiphase reactor simulates a complex environment of multiple different material phases, when the first signal is generated, it indicates that the multiphase reactor can efficiently simulate the complex environment of multiple different material phases, and the simulation continues through the multiphase reactor;

[0112] If the simulation index is greater than the simulation index reference threshold, a second signal is generated. When a multiphase reactor generates a second signal when simulating a complex environment of multiple different material phases, it indicates that the multiphase reactor has a hidden danger of failing to accurately simulate actual reaction conditions, resulting in distortion of experimental data, indicating a simulation failure.

[0113] When it is monitored that there are abnormal hidden dangers in the complex environment of multiple different material phases simulated by the multiphase reactor, the multiphase reactor simulation will be stopped and the corresponding experimental data will be discarded. At the same time, the abnormal hidden dangers will be further judged and different early warning prompts will be issued;

[0114] When it is monitored that there are abnormal hidden dangers when the multiphase reactor simulates a complex environment with multiple different material phases, the multiphase reactor simulation is stopped, and the corresponding experimental data are discarded. At the same time, several simulation indexes subsequently generated when the multiphase reactor simulates a complex environment with multiple different material phases are obtained to establish an analysis set;

[0115] The simulated index mean and simulated index discrete value generated by several simulated indexes in the analysis set are calculated, and the simulated index mean and simulated index discrete value are compared and analyzed with the preset simulated index reference threshold and discrete value reference threshold respectively. The results of the comparison and analysis are as follows:

[0116] If the simulation index mean is less than or equal to the simulation index reference threshold and the simulation index discrete value is less than or equal to the discrete value reference threshold, a first-level warning signal is generated. When a multiphase reactor simulates a complex environment with multiple different material phases and generates a first-level warning signal, an accidental warning prompt is issued. When an accidental warning prompt is generated, it indicates that when the multiphase reactor simulates a complex environment with multiple different material phases, there may be only sudden and accidental abnormal hidden dangers, which is not caused by the abnormality of the multiphase reactor itself. The simulation of the multiphase reactor is stopped, and the corresponding experimental data is discarded, and the simulation experiment can be carried out again;

[0117] If the simulation index mean is not less than or equal to the simulation index reference threshold and the simulation index discrete value is not less than or equal to the discrete value reference threshold, a secondary warning signal is generated. When the multiphase reactor simulates a complex environment with multiple different material phases and generates a secondary warning signal, an abnormal warning prompt is issued to inform the relevant experimental personnel. When the abnormal warning prompt is generated, it indicates that when the multiphase reactor simulates a complex environment with multiple different material phases, it is not a sudden and accidental abnormal hidden danger, but it is very likely caused by the abnormality of the multiphase reactor itself. The simulation of the multiphase reactor is stopped, and the corresponding experimental data is discarded. The multiphase reactor needs to be repaired and troubleshooted to effectively prevent the occurrence of abnormal hidden dangers when the multiphase reactor simulates a complex environment with multiple different material phases.

[0118] The present invention establishes a dynamic abnormal monitoring mechanism to simulate a complex environment of multiple different material phases in a multiphase reactor for real-time monitoring, so that the system can detect abnormal hidden dangers of the multiphase reactor in a timely manner during the experiment, and then take corresponding measures. The implementation of this mechanism plays a vital role in improving the reliability of experimental data. Scientists can trust the experimental results more and avoid making misleading judgments based on erroneous data, thereby providing a more reliable basis for scientific research. This is of great significance for research in the fields of formulation optimization and ensures the accuracy and scientificity of scientific research work.

[0119] The present invention introduces a real-time abnormal monitoring mechanism, which can detect problems in the early stage of the experiment, stop the simulation in time and discard the experimental data, so as to avoid long-term experiments under wrong conditions. This helps scientists to interrupt the simulation experiment in time to avoid wasting time and resources, and take further troubleshooting and repair measures when necessary, thereby improving the efficiency and operability of the experiment;

[0120] The present invention generates a first-level warning signal and a second-level warning signal, so that the present invention has the ability to distinguish between accidental anomalies and systematic anomalies. When the simulation index mean is less than or equal to the simulation index reference threshold and the simulation index discrete value is less than or equal to the discrete value reference threshold, a first-level warning signal is generated, indicating that there may be a sudden and accidental abnormal hidden danger. At this time, the system will stop the simulation experiment and discard the data, but the scientist can conduct the simulation experiment again. When the first-level warning conditions are not met, a second-level warning signal is generated, indicating that there may be a systematic abnormality and it is necessary to stop the simulation experiment and conduct equipment maintenance. Such differentiated processing helps scientists to judge abnormal conditions more accurately and improve their ability to respond to abnormal situations.

[0121] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0122] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0123] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0124] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0125] In the several embodiments provided in the present application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0126] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0127] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0128] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A multi-channel multi-phase rapid high-throughput formulation screening method, characterized in that: The following steps are involved: Prepare reagents of different material phases that need to be formulated, add different reagents into various channels of the multiphase reactor according to a predetermined formula ratio, and perform mixing and stirring operations after the reagents are added; Through multiphase reactor simulation experiments involving multiple different material phases in the complex environment; Acquire multiple data information when a multiphase reactor simulates a complex environment of multiple different material phases, including static setting stability information and dynamic information, process and comprehensively analyze the static setting stability information and dynamic information when a multiphase reactor simulates a complex environment of multiple different material phases, establish a dynamic abnormal monitoring mechanism, and dynamically monitor the situation when a multiphase reactor simulates a complex environment of multiple different material phases; When it is monitored that the multiphase reactor simulates a complex environment with multiple different material phases and has abnormal hidden dangers, the multiphase reactor simulation will be stopped and the corresponding experimental data will be discarded. At the same time, the abnormal hidden dangers will be further judged and different early warning prompts will be issued.

2. A multi-channel multi-phase rapid high-throughput formulation screening method according to claim 1, characterized in that: The static setting stability information of a multiphase reactor when simulating a complex environment with multiple different material phases includes the pH value information, pressure control information and temperature control information of the multiphase reactor. The system parameter setting deviation coefficient is comprehensively generated by comparing and analyzing the real-time pH value, real-time pressure value and real-time temperature value in the multiphase reactor with the preset pH value, preset pressure value and preset temperature value set by the system; the dynamic information of a multiphase reactor when simulating a complex environment with multiple different material phases includes liquid phase flow rate distribution information and control command transmission frequency information. The liquid phase flow rate distribution difference coefficient is generated by processing the liquid phase flow rate distribution information, and the control command transmission frequency anomaly concealment coefficient is generated by processing the control command transmission frequency information.

3. A multi-channel multi-phase rapid high-throughput formulation screening method according to claim 2, characterized in that: The logic for obtaining the system parameter setting deviation coefficient is as follows: In the time window G, the real-time pH value, real-time pressure value, and real-time temperature value are obtained when the multiphase reactor simulates a complex environment with multiple different material phases, and the real-time pH value, real-time pressure value, and real-time temperature value are respectively used in time series by function f pH (t), f 压力 (t), f 温度 (t) indicates; The real-time pH value, real-time pressure value, and real-time temperature value obtained in the time window G when the multiphase reactor simulates a complex environment of multiple different material phases are compared and analyzed with the preset pH value, preset pressure value, and preset temperature value set by the system, and the system parameter setting deviation coefficient is calculated. The calculation expression is: In the formula, Indicates the system parameter setting deviation coefficient, YS pH Indicates the preset pH value, YS 压力 Indicates the preset pressure value, YS 温度 represents the preset temperature value, t1 and t2 represent the start and end time of the time window G respectively.

4. A multi-channel multi-phase rapid high-throughput formulation screening method according to claim 3, characterized in that: The logic for obtaining the liquid phase flow velocity distribution difference coefficient is as follows: Obtain the real-time liquid phase flow rate values ​​at different positions at the same time when the multiphase reactor simulates a complex environment with multiple different material phases, and calibrate the real-time liquid phase flow rate as ξ 流速 y , y represents the number of the real-time liquid phase flow rate values ​​at different positions at the same time when the multiphase reactor simulates a complex environment of multiple different material phases, x=1, 2, 3, 4, ..., h, h is a positive integer; Calculate the standard deviation of the liquid phase flow rate value through a plurality of real-time liquid phase flow rate values ​​obtained at the same time by the multiphase reactor; In the time window G, the standard deviation of the liquid phase flow rate value at different times when the multiphase reactor simulates a complex environment with multiple different material phases is obtained, and the obtained standard deviation of the liquid phase flow rate value is used to establish a data set. Then, the standard deviation of the liquid phase flow rate value in the data set is sorted in order, and the largest standard deviation of the liquid phase flow rate value is screened out, and the largest standard deviation of the liquid phase flow rate value is calibrated as ξ 流速 max ; The maximum standard deviation of the liquid flow rate in the data set is ξ 流速 max Calculate the liquid phase flow velocity distribution difference coefficient, the calculation expression is: In the formula, ξ 流速 η Represents the liquid phase flow velocity distribution difference coefficient.

5. A multi-channel multi-phase rapid high-throughput formulation screening method according to claim 4, characterized in that: The logic of obtaining the control command transmission frequency anomaly concealment coefficient is as follows: Obtain the optimal control command transmission frequency range for the control system to send adjustment instructions to the multiphase reactor when the multiphase reactor simulates a complex environment with multiple different material phases, and calibrate the optimal control command transmission frequency range as φ 控制 min ~φ 控制 max ; In the time window G, the actual control command transmission frequency of the control system sending adjustment instructions to the multiphase reactor at different time periods when the multiphase reactor simulates a complex environment with multiple different material phases is obtained, and the actual control command transmission frequency is calibrated as φ 控制 v , v represents the number of the actual control command transmission frequency of the control system sending the adjustment command to the multiphase reactor at different time periods when the multiphase reactor simulates a complex environment with multiple different material phases, v = 1, 2, 3, 4, ..., k, k is a positive integer; Calculate the control command transmission frequency anomaly concealment coefficient, the calculation expression is: In the formula, φ 控制 μ represents the control command transmission frequency anomaly concealment coefficient, φ 控制 v′ represents the actual control command transmission frequency that is not in the optimal control command transmission frequency range obtained within the time window G when the multiphase reactor simulates a complex environment with multiple different material phases, v′ represents the number of the actual control command transmission frequency that is not in the optimal control command transmission frequency range obtained within the time window G when the multiphase reactor simulates a complex environment with multiple different material phases, v′=1, 2, 3, 4, ..., ', ' is a positive integer, and '≤, k represents the total number of actual control command transmission frequencies obtained within the time window G when the multiphase reactor simulates a complex environment with multiple different material phases.

6. A multi-channel multi-phase rapid high-throughput formulation screening method according to claim 5, characterized in that: Obtain the system parameter setting deviation coefficient generated by the processed static setting stability information and dynamic information when simulating a complex environment with multiple different material phases in a multiphase reactor Liquid phase velocity distribution difference coefficient ξ 流速 η And the control command transmission frequency anomaly concealment coefficient φ 控制 μ Then, set the system parameter deviation coefficient Liquid phase velocity distribution difference coefficient ξ 流速 η And the control command transmission frequency anomaly concealment coefficient φ 控制 μ Establish data analysis model and generate simulation index MN θ , by simulating the index MN θ Dynamically monitor the multiphase reactor when simulating a complex environment with multiple different material phases.

7. A multi-channel multi-phase rapid high-throughput formulation screening method according to claim 6, characterized in that: When a multiphase reactor simulates a complex environment with multiple different material phases, the larger the system parameter setting deviation coefficient generated in the time window G, the larger the liquid phase flow velocity distribution difference coefficient, and the larger the control command transmission frequency anomaly concealment coefficient, that is, when a multiphase reactor simulates a complex environment with multiple different material phases, the simulation index MN generated in the time window G is θ The larger the performance value, the greater the risk that the multiphase reactor cannot accurately simulate the actual reaction conditions and cause the experimental data to be distorted. Conversely, the smaller the risk that the multiphase reactor cannot accurately simulate the actual reaction conditions and cause the experimental data to be distorted.

8. A multi-channel multi-phase rapid high-throughput formulation screening method according to claim 7, characterized in that: The simulation index generated in the time window G when the multiphase reactor simulates a complex environment with multiple different material phases is compared and analyzed with the preset simulation index reference threshold, and a dynamic abnormal monitoring mechanism is established to dynamically monitor the situation when the multiphase reactor simulates a complex environment with multiple different material phases. The specific logic is as follows: If the simulation index is less than or equal to the simulation index reference threshold, a first signal is generated. When the multiphase reactor simulates a complex environment of multiple different material phases, when the first signal is generated, it indicates that the multiphase reactor can efficiently simulate the complex environment of multiple different material phases, and the simulation continues through the multiphase reactor; If the simulation index is greater than the simulation index reference threshold, a second signal is generated. When the second signal is generated when the multiphase reactor simulates a complex environment of multiple different material phases, it indicates that the simulation has failed.

9. A multi-channel multi-phase rapid high-throughput formulation screening method according to claim 8, characterized in that: When it is monitored that there are abnormal hidden dangers when the multiphase reactor simulates a complex environment with multiple different material phases, the multiphase reactor simulation is stopped, and the corresponding experimental data are discarded. At the same time, several simulation indexes subsequently generated when the multiphase reactor simulates a complex environment with multiple different material phases are obtained to establish an analysis set; The simulated index mean and simulated index discrete value generated by several simulated indexes in the analysis set are calculated, and the simulated index mean and simulated index discrete value are compared and analyzed with the preset simulated index reference threshold and discrete value reference threshold respectively. The results of the comparison and analysis are as follows: If the simulation index mean is less than or equal to the simulation index reference threshold and the simulation index discrete value is less than or equal to the discrete value reference threshold, a first-level warning signal is generated. When a multiphase reactor simulates a complex environment of multiple different material phases and generates a first-level warning signal, an accidental warning prompt is issued; If the simulation index mean value is less than or equal to the simulation index reference threshold and the simulation index discrete value is less than or equal to the discrete value reference threshold, a secondary warning signal is generated. When a multiphase reactor simulates a complex environment of multiple different material phases and generates a secondary warning signal, an abnormal warning prompt is issued to alert relevant experimental personnel.

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