A method for magnetic field assisted organic molecule magnetic regulation

Abstract

The present application relates to the technical field of magnetic regulation, in particular to a kind of organic molecule magnetic regulation method based on magnetic field auxiliary, comprising the following steps, obtain magnetic response data, analyze trajectory displacement difference, construct response input weight, revise magnetic focusing coordinates, rearrange response sequence, identify magnetic control mapping path, classify organic molecule magnetic response behavior, output magnetic control archive node path set.In the present application, by analyzing the speed variation characteristics of magnetic response, the speed direction angle is accurately calculated, the fine correspondence between excitation frequency and response direction trajectory is realized, the deviation between magnetic moment direction and response path is effectively identified, the spatial position of magnetic response center and the feedback rhythm change trend are accurately corrected, the control input weight distribution and path node sequence are dynamically adjusted, the fine classification and archive management of magnetic response behavior are realized, the stability and precision of magnetic state regulation are significantly improved, and the control condition dependency dispersion, response data disconnection and feedback adjustment lag are effectively avoided.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of magnetic regulation, in particular to a magnetic regulation method for organic molecules based on magnetic field assistance. BACKGROUND

[0002] The technical field of magnetic regulation includes a strategy method system for regulating the response behavior of magnetic substances in information processing and functional control, aiming to realize dynamic management and selective control of magnetic parameters in materials, systems or modules through programmed or signal control means, and specifically relates to magnetic data expression methods, magnetic field action sequence generation, magnetic state feedback identification, control flow design and other elements, and is applied to organic electronic systems, Internet of Things node control, spin logic operation flow, intelligent material response management, wherein the magnetic regulation method for organic molecules based on magnetic field assistance refers to a control method for programmatically regulating the magnetic state of an organic molecule system by defining control parameters and logic conditions using a magnetic field as an external driving signal, which covers establishing a magnetic response model for a target organic molecule system, setting magnetic field input parameters, mapping relationships of molecular states, and triggering condition mechanisms to call specific control instruction logic to schedule external magnetic field control units for completion, including magnetic field input parameter setting methods, state discrimination condition logic, molecular response mapping rule definition, and regulation flow execution sequence setting.

[0003] In the magnetic field control process of the traditional organic molecule magnetic regulation technology, the speed direction change and trajectory difference characteristics of the magnetic response are not deeply considered, resulting in insufficient spatial position calibration of the magnetic response center, unbalanced feedback rhythm that cannot be accurately identified, deviation of the magnetic moment direction from the actual control path, insufficient accuracy and stability of dynamic management, and difficulty in guaranteeing the accuracy of response behavior classification, which is prone to position and state regulation errors in complex magnetic control scenarios. SUMMARY

[0004] The purpose of the application is to solve the shortcomings in the prior art and propose a magnetic regulation method for organic molecules based on magnetic field assistance.

[0005] In order to achieve the above-mentioned purpose, the application adopts the following technical scheme: a magnetic regulation method for organic molecules based on magnetic field assistance, comprising the following steps:

[0006] S1: Obtain magnetic response data, analyze the magnetic response speed change in the molecular response process under multi-frequency magnetic field pulse excitation, calculate the speed direction angle at consecutive time points, establish the corresponding trajectory of excitation frequency and direction change, and generate response trajectory distribution information;

[0007] S2: using the response trajectory distribution information, comparing the sequence difference of the current response path and the standard path, analyzing the displacement of the response point arrangement, adjusting the input priority level, constructing the control intensity matching coefficient, and outputting the response input weight configuration;

[0008] S3: using the response input weight configuration, analyzing the position change of the response center and the path end point in the direction, judging the direction deviation characteristics of the current response center of gravity, combining the feedback response time information of the corresponding period, correcting the magnetic focusing center coordinates, and outputting the focusing coordinate correction result;

[0009] S4: according to the focusing coordinate correction result, screening the time feedback record of each response node in the magnetic control period, calculating the response time interval difference between each pair of adjacent nodes, judging the change trend of feedback rhythm, screening the rhythm imbalance segment, rearranging the current path structure through the response rhythm stability degree, and generating the response sequence reconstruction result.

[0010] As a further scheme of the application, the response trajectory distribution information includes excitation frequency, direction change trajectory, speed direction angle trend, the response input weight configuration specifically is response path offset position, control state level parameter, control intensity matching factor, the focusing coordinate correction result specifically refers to response center space coordinates, path end point extension position, feedback time reference node, and the response sequence reconstruction result includes time interval difference group, path rhythm stability label and rearranged response sequence number.

[0011] As a further scheme of the application, the response trajectory distribution information acquisition step specifically includes:

[0012] S111: acquiring magnetic response data, analyzing the magnetic field pulse excitation signal sequence under multiple frequency conditions, recording the magnetic response speed change data in each excitation period, calculating the speed change direction angle between consecutive time points, and generating a frequency-related speed angle set;

[0013] S112: calling the frequency-related speed angle set, grouping the speed direction change data under multiple frequency conditions, analyzing the change trend of each frequency segment, calculating the response trend strength, and obtaining a frequency distribution trend parameter set;

[0014] S113: based on the frequency distribution trend parameter set, analyzing the relationship between excitation frequency and direction change path, judging the co-occurrence characteristics of direction jump and excitation change, establishing the corresponding trajectory of excitation frequency and direction change, and obtaining the response trajectory distribution information.

[0015] As a further scheme of the application, the response input weight configuration acquisition step specifically includes:

[0016] S211: Obtain the response trajectory distribution information, compare the position sequence difference between the current response path sequence of the molecule and the standard path template, analyze the arrangement displacement of each response point, and generate a response offset displacement parameter group;

[0017] S212: According to the response offset displacement parameter group, identify the sequence offset direction of each response point, call the corresponding control state sequence, match the offset direction and the control state sequence, calculate the sequence offset matching coefficient, combine the arrangement displacement data and the state sequence order, and generate a matching coefficient data set;

[0018] S213: According to the matching coefficient data set, adjust the input priority level, construct the control intensity matching coefficient by combining the offset displacement and the priority level, and establish the response input weight configuration.

[0019] As a further scheme of the present application, the acquisition of the focus coordinate correction result is specifically:

[0020] S311: Use the response input weight configuration to identify the response center coordinate point in the magnetic control period, combine the spatial position coordinates of the last response node in the same period, analyze the change of the response center and the path end point in the spatial direction, and generate the center end point direction change amount;

[0021] S312: According to the center end point direction change amount, judge the direction offset characteristics of the current response gravity center, combine the response direction extension trajectory, calculate the gravity center direction offset trend amount, analyze the spatial displacement trend of the path end point, and generate the gravity center direction offset trend amount;

[0022] S313: Use the gravity center direction offset trend amount to combine the feedback response time information of the corresponding period to perform spatial correction on the magnetic focusing center coordinate, and obtain the focus coordinate correction result.

[0023] As a further scheme of the present application, the acquisition of the response sequence reconstruction result is specifically:

[0024] S411: According to the focus coordinate correction result, screen the time feedback record of each response node in the magnetic control period, calculate the response time interval difference between each pair of adjacent nodes, and generate a time interval difference value group;

[0025] S412: Call the time interval difference value group, judge the feedback rhythm change trend by analyzing the fluctuation change of the time interval, screen the rhythm imbalance segment, identify the unstable area of the path, and obtain the rhythm fluctuation identification result;

[0026] S413: Through the rhythm fluctuation identification result, rearrange the current path structure according to the response rhythm stability degree, adjust the response node sequence, and obtain the response sequence reconstruction result.

[0027] As a further scheme of the present application, the method further comprises:

[0028] S5: calling the response sequence reconstruction result, locating the corresponding response state node according to each item of magnetic field input information in the control sequence, identifying the mapping path of the input control sequence and the effective response state by analyzing the direction change in the control input and the angle difference between the magnetic moment directions in the response process, classifying the organic magnetic response behavior, and outputting the magnetic control archiving node path set;

[0029] The magnetic control archiving node path set is specifically the control input direction, the response node coordinate, and the angle matching path number.

[0030] As a further scheme of the present application, the acquisition step of the magnetic control archiving node path set is specifically:

[0031] S511: calling the response sequence reconstruction result, locating the corresponding response state node according to each item of magnetic field input information in the control sequence, and generating a control response node positioning set;

[0032] S512: calling the control response node positioning set, analyzing the direction change in the control input sequence, combining the angle difference between the magnetic moment directions in the response process, identifying the mapping path of the input control sequence and the effective response state, and obtaining a control response mapping path set;

[0033] S513: according to the control response mapping path set, analyzing the mapping path, classifying the organic magnetic response behavior, and outputting the magnetic control archiving node path set.

[0034] Compared with the prior art, the present application has the following advantages and positive effects:

[0035] In the present application, by analyzing the magnetic response speed change characteristics, the speed direction angle is accurately calculated, the fine correspondence between the excitation frequency and the response direction trajectory is realized, the deviation between the magnetic moment direction and the response path is effectively identified, the spatial position of the magnetic response center and the feedback rhythm change trend are accurately corrected, the control input weight distribution and the path node sequence are dynamically adjusted, the fine classification and archiving management of the magnetic response behavior are realized, the stability and precision of the magnetic state regulation are significantly improved, and the control condition dependency dispersion, response data disconnection, and feedback adjustment lag are effectively avoided. BRIEF DESCRIPTION OF DRAWINGS

[0036] Figure 1 It is a main step schematic diagram of the present application;

[0037] Figure 2 It is a response trajectory distribution information acquisition flowchart of the present application;

[0038] Figure 3A response input weight configuration acquisition flowchart for the application;

[0039] Figure 4 A focus coordinate correction result acquisition flowchart for the application;

[0040] Figure 5 A response sequence reconstruction result acquisition flowchart for the application;

[0041] Figure 6 A magnetic control archiving node path set acquisition flowchart for the application. DETAILED DESCRIPTION

[0042] In order to make the objects, technical solutions and advantages of the application clearer, the application will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the application and do not limit the application.

[0043] In the description of the application, it should be understood that the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer" and the like indicate the orientation or positional relationship shown in the drawings, and are only used to facilitate the description of the application and simplify the description, and do not indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the application. In addition, in the description of the application, the meaning of "a plurality of" is two or more, unless otherwise explicitly and specifically limited.

[0044] Please refer to Figure 1 The application provides a technical solution: a method for magnetic regulation of organic molecules based on magnetic field assistance, comprising the following steps:

[0045] S1: Obtain magnetic response data, analyze the change of magnetic response speed in the response process of the molecules under multi-frequency magnetic field pulse excitation, calculate the included angle of the speed direction at consecutive time points, establish the corresponding trajectory of excitation frequency and direction change, and generate response trajectory distribution information;

[0046] S2: Using the response trajectory distribution information, comparing the sequence difference between the current response path and the standard path, analyzing the displacement of the response point arrangement, adjusting the input priority level in combination with the control state sequence, constructing the control intensity matching coefficient, and outputting the response input weight configuration;

[0047] S3: Using the response input weight configuration, analyzing the position change of the response center and the end point of the path in the direction, judging the direction deviation characteristics of the current response center of gravity, combining the feedback response time information of the corresponding period, correcting the magnetic focus center coordinates, and outputting the focus coordinate correction result;

[0048] S4: According to the focus coordinate correction result, screen the time feedback record of each response node in the magnetic control period, calculate the response time interval difference between each pair of adjacent nodes, judge the feedback rhythm change trend, screen the rhythm imbalance segment, rearrange the current path structure through the response rhythm stability degree, and generate the response sequence reconstruction result;

[0049] S5: Call the response sequence reconstruction result, locate the corresponding response state node according to each item of magnetic field input information in the control sequence, identify the mapping path of input control sequence and effective response state by analyzing the direction change in control input and the angle difference between magnetic moment directions in response process, classify the organic magnetic response behavior, and output the magnetic control archiving node path set.

[0050] The response trajectory distribution information includes excitation frequency, direction change trajectory, and speed direction angle trend. The response input weight configuration specifically refers to response path offset position, control state level parameter, and control intensity matching factor. The focus coordinate correction result specifically refers to response center spatial coordinates, path end point extension position, and feedback time reference node. The response sequence reconstruction result includes time interval difference group, path rhythm stability label, and rearranged response sequence number. The magnetic control archiving node path set specifically refers to control input direction, response node coordinates, and angle matching path number.

[0051] Please refer to Figure 2 , the acquisition steps of the response trajectory distribution information are as follows:

[0052] S111: Obtain magnetic response data, analyze magnetic field pulse excitation signal sequence under multiple frequency conditions, record magnetic response speed change data in each excitation period, calculate the speed change direction angle between consecutive time points, and generate a frequency-related speed angle set;

[0053] First, determine the frequency range of the magnetic field pulse excitation signal. For example, the experimental frequency conditions are 、 、 、 and a total of 5 groups. The duration of the magnetic field pulse under each frequency is , and the sampling interval is set to . Taking an actual implementation as an example, in the magnetic response experiment, an organic magnetic molecular material (such as a metal porphyrin molecular material) is selected, and its magnetic response speed change data is recorded under different frequency magnetic field excitation. Assuming that when the frequency is , the molecular response speed change data is shown in Table 1.

[0054] Table 1 Magnetic response speed change data table

[0055]

[0056] As shown in Table 1, according to the response speed data, the speed direction included angle between consecutive time points is calculated in sequence, specifically: taking the time number and as an example, the speed vector of the second time point , the speed vector of the first time point , the speed direction included angle between the two points is , and the actual value is calculated by bringing it in , and the included angle values of all consecutive points are calculated in sequence, and the speed included angle set under each frequency condition is obtained through the above process, that is, the frequency correlation speed included angle set is obtained.

[0057] S112: Call the frequency correlation speed included angle set, group the speed direction change data under multiple frequency conditions, analyze the change trend of each frequency band, and use the formula:

[0058] ; ;

[0059] Calculate the response trend strength to obtain the frequency distribution trend parameter set;

[0060] , wherein is the response trend strength under frequency regulation, is the speed direction included angle normalized value of the th response time point, which is obtained by comparing the original included angle with the theoretical maximum included angle, is the arithmetic mean of the speed direction included angle normalized value in all response sampling periods, which is obtained by averaging the normalized values of each period, is the speed increment normalized value in the th response period, which is obtained by comparing the speed increment in this period with the maximum speed increment in this period, is the excitation frequency density normalized value in the th period, which is obtained by comparing the excitation frequency in this period with the maximum excitation frequency in all periods, is the normalized sampling frequency of the system minimum unit, which is obtained by normalizing the minimum sampling frequency set by the system, is the total number of response sampling periods, is the response sampling period number;

[0061] By extracting the speed direction included angle of the th response time point , first, the actual included angle is divided by the theoretical maximum included angle , for example, the first included angle value , and the normalized processing obtains Then, calculate the arithmetic mean of all the normalized angle values. For example, assume the arithmetic mean of 100 normalized angle values. Simultaneously, the response speed increment within each cycle... Normalization is performed, specifically taking the velocity increment of the second cycle as an example. Let's assume the velocity increment for this cycle is... The maximum speed increment is Then the normalized value of the velocity increment ; for periodic excitation frequency Normalization is performed using periodic frequency. For example, assuming the highest frequency of the experiment Then the normalized value of frequency density System minimum sampling frequency Set as sampling frequency Normalized value Then, substitute the normalized parameters above into the formula:

[0062] ;

[0063] The specific calculations are as follows:

[0064] Pick Sometimes, , , Substitute into the formula to calculate:

[0065] ;

[0066] For all The calculation is performed sequentially for each sampling point, assuming the final summation result is... ,and Then substitute it into the calculation:

[0067] ;

[0068] The response trend intensity is a comprehensive dimensionless value characterizing the coordinated characteristics of directional fluctuations and velocity changes in the response process of an organic molecular system under magnetic field-assisted excitation. It reflects the strength of non-uniform response segments or abrupt change segments exhibited under different excitation frequencies and magnetic response behaviors. A larger response trend intensity value indicates that the magnetic response behavior exhibits more obvious directional fluctuations and velocity jumps within the observed period; a smaller value indicates a more stable response with limited variation. This parameter is used in various application scenarios such as magnetic control strategy adjustment, focusing response anomaly screening, or automatic optimization of magnetic response devices, enabling real-time feedback and strategy support for the dynamic behavior of the magnetic field control system. The results show that the calculated response trend intensity of the frequency distribution trend parameter set is... Its range is generally within The formula is verified and determined by multiple sets of experimental data. The formula obtains a precise description of the magnetic response trend by the speed angle and the speed increment, and can accurately depict the response characteristics of organic molecules under different frequencies.

[0069] S113: Based on the frequency distribution trend parameter set, analyze the relationship between the excitation frequency and the direction change path, judge the co-occurrence characteristics of direction jump and excitation change, establish the corresponding trajectory of excitation frequency and direction change, and obtain response trajectory distribution information;

[0070] Take the response trend intensity obtained in paragraph 2 For example, first determine the analysis range of excitation frequency and direction change path, that is, select As the obvious co-occurrence interval between When analyzing the response path, the above frequency Corresponding data is called first to identify the direction jump position in the response process, that is, when the change of the speed direction angle normalized value between two consecutive time points exceeds the threshold value, it is defined as a direction jump, and the threshold value is set to be the angle normalized value For example, the speed direction angle normalized values between time points 15 and 16 are And The difference is Exceeds the threshold value Therefore, it is determined that this is a direction jump point; secondly, through the periodic characteristics of the excitation frequency, the change of the corresponding magnetic field pulse excitation signal between And Record the corresponding excitation frequency jump data, compare the jump positions of the excitation frequency and the speed direction jump position, judge the co-occurrence between the two, and record the corresponding trajectory of the excitation frequency and the direction change, to obtain the response trajectory distribution information with actual data.

[0071] Please refer to Figure 3 The response input weight configuration acquisition step is specifically:

[0072] S211: Obtain response trajectory distribution information, compare the position sequence difference between the current response path sequence of the molecule and the standard path template, analyze the arrangement displacement of each response point, and generate a response offset displacement parameter group;

[0073] First, a set of actual magnetic response path sequences and standard path templates are selected. The positions of each response point within the sequence are compared one by one. Assuming the measured molecule has a total of 10 response points under the influence of a magnetic field, the standard path template numbers are sequentially increasing integers from 1 to 10, and the actual measured response point sequence is: [1,3,2,4,5,7,6,8,9,10]. This sequence represents the control state number of the response molecule under the actual influence of an external magnetic field. By calling the corresponding position number of the standard template one by one, taking position 2 of the actual response sequence (response point state number 3) as an example, the corresponding position number of the standard template is 2. The numerical difference is calculated by subtracting the values, thus obtaining the displacement difference of that response point. That is, the position is shifted one unit in the positive direction, and the same process is performed on the remaining response points one by one to obtain the displacement value data of each response point relative to the standard template, as shown in Table 2.

[0074] Table 2 Data on Displacement Difference at Response Points

[0075]

[0076] As shown in Table 2, the position of each response point is calculated by the numerical difference between the actual response state number and the standard state number, and the offset displacement of each response point is obtained to form a response offset displacement parameter group.

[0077] S212: Based on the response offset displacement parameter group, identify the sequential offset direction of each response point, call the corresponding control state sequence, and match the offset direction with the control state sequence using the formula:

[0078] ;

[0079] Calculate the sequence offset matching coefficients, and combine the displacement data with the state sequence order to generate a matching coefficient dataset;

[0080] in, For sequential offset matching coefficients, For the first The current control state number of each response point is obtained through the response point control command number. For the first Displacement of each response point The sign function value, if If positive, take 1; if negative, take -1; if zero, take 0. For the first Each standard state sequence reference state number is determined by the standard path template number. For the first The displacement of each response point relative to the standard path. This represents the total number of response points. The index number of the response point;

[0081] First, call the displacement difference parameter of the response point ( The direction is determined one by one, and the sign of the displacement difference is determined by the displacement difference of the second response point. For example, because it is a positive value, the sign function... The calculation result is 1, the displacement difference of the 3rd response point. Then the sign function The value is -1, and so on. The control state sequence is called to perform a sequence matching process, and the actual response state sequence number is ( ) sequentially with the standard state number ( Numerical calculations are performed using the results of the offset displacement sign function, taking the second response point as an example, the response state number... Standard state number The sign function value is 1. Substituting this into the formula, the calculation is as follows:

[0082] ;

[0083] First, calculate the absolute value of the numerator, taking the second response point as an example:

[0084] ;

[0085] Calculate separately for all response points, such as response point number 3:

[0086] ;

[0087] The sum of the results from all 10 response points is:

[0088] .

[0089] Next, calculate the square root operation of the second term in the numerator, taking the second response point as an example:

[0090] ;

[0091] The sum of all response points is calculated cumulatively. For example, the sum of all point displacements calculated by taking the square root of the total displacement is 6.656.

[0092] Next, calculate the denominator, taking response point number 2 as an example:

[0093] ;

[0094] Calculate each response point individually, and the total sum of the cumulative denominators is 4.

[0095] The final result is the order offset matching coefficient:

[0096] ;

[0097] Wherein, the sequence offset matching coefficient is a dimensionless response sequence overall deviation index, used to measure the comprehensive deviation degree of the current response path and the standard template in sequence and position in the process of molecular magnetic regulation. The larger the value is, the more obvious the difference between the response point arrangement, offset direction and control state sequence number and the standard template is, and the more prominent the overall path anomaly is. During magnetic control adjustment, the input priority and excitation intensity can be dynamically adjusted according to this, and the drift risk, response anomaly or reconfiguration regulation path can be judged and warned, so as to realize automatic feedback and adaptive adjustment. The results show that the offset matching coefficient value is 4.164, which is verified by experiments. The matching coefficient Generally, the value range is 0 to 10, and the lower the value is, the higher the matching degree is. The current value is in the medium to high interval (4.0 to 6.0), indicating that further adjustment is needed. The formula realizes the quantitative analysis of the matching accuracy of the response path by the state sequence number, displacement symbol and displacement amount.

[0098] S213: According to the matching coefficient data set, adjust the input priority level, construct the control intensity matching coefficient by combining the offset displacement and priority level, and establish the response input weight configuration;

[0099] Based on the matching coefficient calculated in paragraph 2 , it is judged that the current matching coefficient value is in the interval of 4.0 to 6.0, indicating that the response path deviates from the standard path to a medium to high degree, and the input priority level needs to be adjusted. According to the interval, the priority level adjustment factor is set to 1.2, and the response offset displacement data is called one by one, for example, the displacement difference value of the second response point is 1, and the displacement difference value of the third response point is-1. The displacement absolute value and the priority level adjustment factor value are calculated by numerical multiplication, that is, the control intensity matching coefficient of the second response point is calculated, and the control intensity matching coefficient of the third response point is also

[0100] Table 3 Control intensity matching coefficient data table

[0101]

[0102] As shown in Table 3, the complete response input weight configuration data set is obtained.

[0103] Please refer to Figure 4 , the acquisition steps of the focus coordinate correction result are as follows:

[0104] S311: By configuring the response input weights, identify the coordinates of the response center within the magnetic control cycle. Combined with the spatial coordinates of the last response node in the same cycle, analyze the changes in the spatial direction between the response center and the end point of the path, and generate the change in the direction of the center and the end point.

[0105] First, the sequence of response nodes within the current magnetic control cycle is retrieved. For example, if a total of 8 response nodes are measured in this cycle, the three-dimensional coordinate position data of each response node is acquired using actual measuring equipment. The first node is used as... The second node is And so on, until the coordinates of the last node are... Call the control strength ratio coefficient of each node, for example, the first node is... The second node is The coordinates of each node are multiplied by the control strength coefficient. The weighted sum of all nodes is then divided by the sum of the control strength coefficients to obtain the coordinates of the response center. For example, in the actual calculation process: the product of the first node's position and its weight is... The product of the second node position and the weight is Calculate the product of all nodes sequentially, then sum these results vector-wise, and finally divide by the sum of all control intensity ratio coefficients. For example, if the sum of the coefficients is... The location of the response center is then calculated as follows: Using this value as the response center coordinate position, the coordinates of the last response node are further called. Then, by subtracting the coordinates of the center and the last node one dimension at a time, the change in spatial direction is obtained. This ultimately generates the change in direction of the center and end points.

[0106] S312: Based on the change in direction of the center endpoint, determine the directional shift characteristics of the current response centroid, and combine this with the response direction extension trajectory, using the formula:

[0107] ;

[0108] Calculate the trend of center of gravity offset, analyze the spatial displacement trend at the end of the path, and generate the trend of center of gravity offset.

[0109] in, This represents the trend of the center of gravity shifting in the direction of gravity. For the first The normalized spatial extension trajectory direction vector of the response node is obtained by using the first response node. The spatial trajectory direction vector of each response node is obtained by dividing the maximum magnitude of the spatial trajectory vectors of all nodes within that period. For the first normalized spatial extension trajectory direction vector of the responding node, index of the responding node, indicating the node order number in the current trajectory sequence, total number of responding nodes, obtained by counting the number of all valid responding nodes in the period;

[0110] center-end point direction change amount , first call the total number of nodes in the response period, for example, the total number of responding nodes in this period , taking the calculation of the spatial trajectory direction vector of the adjacent nodes as an example, call the position of the node and the position of the node , calculate the spatial trajectory vector , for example, the trajectory vector from node 1 to node 2 is , and the trajectory vectors between all nodes are calculated in turn. Assuming that the maximum value of the length of each vector is , then each node trajectory vector is normalized one by one, for example, the trajectory vector of the first node is , and the normalized trajectory vector is , and so on. The normalized spatial trajectory vectors of all nodes are calculated as shown in Table 4:

[0111] Table 4: Normalized trajectory vector table of nodes

[0112]

[0113] As shown in Table 4, the adjacent normalized trajectory vectors are called one by one to calculate the vector difference value, and the length of the difference vector is calculated, for example, the difference vector from node 1 to node 2 is , and the length is , then the sum of the lengths of the difference vectors between all nodes is calculated, for example, the sum is , and the dot product of the trajectory vectors between the nodes is calculated one by one, for example, the dot product of the vectors of node 1 and node 2 is , and assuming that the sum of all node dot products is , then the formula is calculated as follows:

[0114] ;

[0115] The center of gravity direction offset trend is a comprehensive index quantifying the spatial direction variation degree of the response path in the whole magnetic control period, reflects the overall turning, jumping or drifting degree of the path, the larger the value, the more discontinuous and sudden the spatial trend of the response sequence, the smaller the value, the more continuous and stable the spatial trend of the response path, and the parameter is used as the decision input of the magnetic control adjustment such as magnetic focusing correction, spatial anomaly detection and response reconstruction judgment, to realize the automatic calibration of spatial positioning and early warning of abnormal response. Generally, the value of the parameter is in the range of 0 to 2, 0 represents no direction offset, and the value closer to 2 represents a stronger offset trend. The current offset trend is moderate and weak (0.5 to 1.0). The formula accurately evaluates the center of gravity spatial direction offset trend by normalizing the spatial trajectory vector difference length and point product operation.

[0116] S313: Using the center of gravity direction offset trend, combined with the feedback response time information of the corresponding period, the spatial correction of the magnetic focusing center coordinates is performed to obtain the focusing coordinate correction result;

[0117] Based on the calculated trend , the feedback response time data of the response nodes in the current period are further called, for example, the response times of the first to eighth nodes are , the response time difference of the response nodes is calculated one by one, and the maximum difference value of the feedback response time is determined, for example, the maximum difference value in the current period is set as , and the maximum time difference value in the current period is assumed to be , which is less than the set threshold, indicating that the time difference meets the set condition, and the spatial direction variation of the response center coordinates and the last node coordinates is multiplied to adjust the value, for example, the center of gravity direction trend is multiplied by the direction variation to obtain the correction amount , and finally the correction amount is added to the original response center coordinates to obtain the center coordinates after focusing correction , and the focusing coordinate correction result is generated.

[0118] Please refer to Figure 5 , and the acquisition steps of the response sequence reconstruction result are as follows:

[0119] S411: According to the focusing coordinate correction result, the time feedback records of each response node in the magnetic control period are screened, the response time interval difference between each pair of adjacent nodes is calculated, and a time interval difference value group is generated;

[0120] Firstly, the response node time feedback record in the magnetron cycle is called, assuming that 9 response nodes are recorded in this cycle, and the feedback response time is [0.013, 0.025, 0.036, 0.049, 0.061, 0.073, 0.086, 0.098, 0.110]s, the response time value of the adjacent node is called one by one to perform numerical subtraction operation, for example, the response time interval difference between the 2nd node and the 1st node is calculated as , the response time interval difference between the 3rd node and the 2nd node is calculated as , and so on. The response time interval difference between all adjacent nodes is shown in Table 5.

[0121] Table 5 Response node time interval difference table

[0122]

[0123] As shown in Table 5, the complete time interval difference value group is obtained through the above calculation process.

[0124] S412: Call the time interval difference value group, analyze the fluctuation change of the time interval, judge the rhythm change trend, screen the rhythm imbalance segment, identify the unstable area of the path, and obtain the rhythm fluctuation identification result;

[0125] Firstly, all the response time interval difference value data in Table 5 are called, and the fluctuation amount between adjacent difference values is calculated one by one, for example, the first fluctuation amount is calculated by subtracting the second interval difference value from the first interval difference value, and the calculation result is , the third interval difference value and the second interval difference value calculate the fluctuation amount as , and so on. All the fluctuation amounts are calculated to obtain the fluctuation data as [0.001, 0.002, 0.001, 0.000, 0.001, 0.001, 0.000]s. Then, the set fluctuation threshold is called, and the fluctuation threshold is set as , each fluctuation amount is compared one by one, when the fluctuation amount is greater than the threshold, it is determined that there is a rhythm imbalance segment at this position, for example, the second fluctuation amount is higher than the threshold , it is determined that there is a rhythm imbalance segment between node 2→4, the node position corresponding to this interval is called as the unstable area of the path, and the remaining fluctuation amounts are lower than the threshold, so other areas are identified as stable areas. Finally, the rhythm fluctuation identification result is obtained as the path between nodes 2 and 4 is unstable.

[0126] S413: Through the rhythm fluctuation identification result, the response rhythm stability degree is used to rearrange the current path structure, adjust the response node order, and obtain the response sequence reconstruction result;

[0127] Firstly, the identified unstable path region, i.e. nodes 2 to 4, is called, and the original time feedback records of each node are called, respectively, node 2: , node 3: , and node 4: . Then, the feedback times of the nodes in the region are reordered, and the difference in values is determined, and the response time difference between the nodes is taken as the basis for rearrangement. For example, the interval between nodes 2 and 3 is , the interval between nodes 3 and 4 is , and it is determined that the interval between nodes 3 and 4 is greater than the interval between nodes 2 and 3. Therefore, node 4 is moved forward to the position of node 3, node 3 is moved backward to the position of node 4, and node 2 remains in the same position. The adjustment of the node order is completed, and the rearranged response sequence is [node 2: 0.025s, node 4: 0.049s, node 3: 0.036s]. Then, all nodes are called again to reconstruct the complete response sequence, and the rearranged segment is placed back in the original path position. Finally, the reconstructed complete response sequence result is obtained: [node 1: 0.013s, node 2: 0.025s, node 4: 0.049s, node 3: 0.036s, node 5: 0.061s, node 6: 0.073s, node 7: 0.086s, node 8: 0.098s, node 9: 0.110s].

[0128] Please refer to Figure 6 , the steps for obtaining the magnetically controlled archival node path set are as follows:

[0129] S511: Call the response sequence reconstruction result, and locate the corresponding response state node according to each item of magnetic field input information in the control sequence to generate a control response node positioning set.

[0130] Firstly, the magnetic field input control sequence is called, for example, 7 magnetic field input information is called together, each input information contains the specific parameters of the magnetic field application direction, magnetic field strength, application duration, etc. Taking the first magnetic field input information as an example, the magnetic field application direction is set to the spatial three-dimensional vector direction (0.4, 0.7, 0.6), the magnetic field strength is 1.2 mT, and the application duration is 0.02 s. Then the spatial position and response time parameters of the nodes in the reconstructed response sequence are called in turn, and the node positioning is performed by item-by-item comparison. For example, the application duration 0.02 s of the first input magnetic field is calculated by difference value with the response time of the nodes in the response sequence one by one. The response time of node 1 is 0.013 s, and the response time of node 2 is 0.025 s. The absolute difference values |0.02-0.013|=0.007 s and |0.02-0.025|=0.005 s are calculated respectively. According to the principle of minimum absolute difference value, it is determined that node 2 is the response state node corresponding to the first input magnetic field, and the response node positioning of the first magnetic field input information is completed. Similarly, for the second magnetic field input information direction (0.5, 0.6, 0.5), strength 1.0 mT, duration 0.035 s, the time sequence of the response nodes is called one by one to calculate the difference value, and finally node 3 is positioned. The above steps are repeated until the response node positioning of all 7 input information is completed, and a complete control response node positioning set is formed.

[0131] S512: The control response node positioning set is called, the direction change in the control input sequence is analyzed, the difference of the magnetic moment direction angle in the response process is combined, the mapping path of the input control sequence and the effective response state is identified, and the control response mapping path set is obtained.

[0132] First, call the spatial direction vector of each magnetic field control input sequence, for example, the first item direction vector is (0.4, 0.7, 0.6), the second item direction vector is (0.5, 0.6, 0.5), and the angle change between adjacent direction vectors of the control input sequence is calculated in turn, for example, the vector angle calculation process is called by the dot product formula of the direction vector, taking the first and second inputs as an example, the dot product of the two vectors is calculated: 0.4×0.5+0.7×0.6+0.6×0.5=0.83, the vector module length is calculated respectively, the first item module length is (0.4²+0.7²+0.6²)^0.5=1.0, the second item module length is (0.5²+0.6²+0.5²)^0.5=0.927, and the angle calculation formula cosθ=0.83 / (1.0×0.927)=0.895 is called to calculate the angle θ=26.56°, the angle between adjacent directions of all input sequences is calculated repeatedly, and the magnetic moment direction vector of the corresponding response node is called, for example, the node 2 magnetic moment direction vector is (0.42, 0.69, 0.58), and the node 3 magnetic moment direction vector is (0.51, 0.59, 0.51), the angle change between the response node magnetic moments is calculated one by one to obtain the magnetic moment direction angle 25.50°, and then the difference between the input direction and the response magnetic moment is calculated: |26.56°-25.50°|=1.06°, the angle difference between all magnetic field inputs and the corresponding response node magnetic moment direction is analyzed one by one in this way, and then the angle difference value is set to a threshold value, the threshold value is 2°, when the difference value is lower than the threshold value, it is determined that it is an effective response state, the input and the response node are marked as an effective mapping relationship, and finally the control response mapping path set is obtained.

[0133] S513: According to the control response mapping path set, analyze the mapping path, classify the organic magnetic response behavior, and output the magnetic control archive node path set;

[0134] Firstly, the marked valid control response mapping path is called, for example, the first input and node 2 are valid mapping relationship, the second input and node 3 are valid mapping relationship, the specific parameter information of the response node in the mapping path is called one by one, including node space position, magnetic moment direction, response strength and other parameters, for example, the space position of node 2 is (1.3, 2.4, 1.2) mm, the magnetic moment direction is (0.42, 0.69, 0.58), and the response strength is 0.95, then the parameter value range of the response node is classified and divided according to the parameter value range of the response node, for example, the space position coordinate division standard is set as the basis of x, y and z directions respectively: x direction (1.0-1.5) mm, y direction (2.0-2.5) mm, z direction (1.0-1.5) mm, the magnetic moment direction angle division standard is 0-30° for the same category, and the response strength is 0.8-1.0 for strong response interval, node 2 is divided into "space range A-strong response category" filing category, and the same classification process is carried out on all the node parameters in the mapping path according to the above method, and finally the complete magnetic control filing node path set is obtained.

[0135] The above is only the preferred embodiment of the present application, and does not limit the present application in other forms. Any skilled person in the art can modify or change the above disclosed technical content to equivalent embodiments applied to other fields, but any simple modification, equivalent change and modification made according to the technical essence of the present application to the above embodiments without departing from the technical solution content of the present application still belongs to the protection scope of the present application.

Claims

1. A method for controlling the magnetic properties of organic molecules based on a magnetic field-assisted process, characterized in that, Includes the following steps: S1: Acquire magnetic response data, analyze the change in magnetic response velocity during the molecular response process under multi-frequency magnetic field pulse excitation, calculate the velocity direction angle at continuous time points, establish the corresponding trajectory of excitation frequency and direction change, and generate response trajectory distribution information; S2: Using the response trajectory distribution information, compare the sequence differences between the current response path and the standard path, analyze the displacement of the response points, adjust the input priority level in combination with the control state sequence, construct the control intensity ratio coefficient, and output the response input weight configuration. S3: Using the aforementioned response input weight configuration, analyze the positional changes of the response center and the end point of the path in the direction, determine the directional offset characteristics of the current response center of gravity, and, in conjunction with the feedback response time information of the corresponding period, correct the magnetic focusing center coordinates and output the focusing coordinate correction result. S4: Based on the focusing coordinate correction results, filter the time feedback records of each response node within the magnetic control cycle, calculate the response time interval difference between each pair of adjacent nodes, determine the trend of feedback rhythm change, filter out rhythm imbalance segments, rearrange the current path structure based on the stability of the response rhythm, and generate response sequence reconstruction results.

2. The method for controlling the magnetic properties of organic molecules based on a magnetic field assisted according to claim 1, characterized in that, The response trajectory distribution information includes excitation frequency, direction change trajectory, and velocity direction angle trend. The response input weight configuration specifically includes response path offset position, control state level parameter, and control intensity ratio factor. The focusing coordinate correction result specifically refers to the response center spatial coordinates, path end point extension position, and feedback time reference node. The response sequence reconstruction result includes time interval difference group, path rhythm stability label, and rearranged response sequence number.

3. The method for controlling the magnetic properties of organic molecules based on magnetic field assistance according to claim 1, characterized in that, The specific steps for obtaining the response trajectory distribution information are as follows: S111: Acquire magnetic response data, analyze magnetic field pulse excitation signal sequences under multiple frequency conditions, record magnetic response velocity change data in each excitation cycle, calculate the velocity change direction angle between consecutive time points, and generate a set of frequency-correlated velocity angles. S112: Call the frequency-related velocity angle set, group the velocity direction change data under multiple frequency conditions, analyze the change trend of each frequency band, calculate the response trend intensity, and obtain the frequency distribution trend parameter set; S113: Based on the frequency distribution trend parameter set, analyze the relationship between the excitation frequency and the direction change path, determine the co-occurrence characteristics of direction jump and excitation change, establish the corresponding trajectory of excitation frequency and direction change, and obtain response trajectory distribution information.

4. The method for controlling the magnetic properties of organic molecules based on a magnetic field assisted according to claim 3, characterized in that, The specific steps for obtaining the response input weight configuration are as follows: S211: Obtain the response trajectory distribution information, compare the positional order difference between the current molecular response path sequence and the standard path template, analyze the arrangement displacement of each response point, and generate a response offset displacement parameter set; S212: Based on the response offset displacement parameter group, identify the sequential offset direction of each response point, call the corresponding control state sequence, match the offset direction with the control state sequence, calculate the sequential offset matching coefficient, and combine the arrangement displacement data with the state sequence sequence to generate a matching coefficient dataset. S213: Based on the matching coefficient dataset, adjust the input priority level, construct the control intensity ratio coefficient by combining the offset displacement and priority level, and establish the response input weight configuration.

5. The method for controlling the magnetic properties of organic molecules based on a magnetic field assisted according to claim 4, characterized in that, The specific steps for obtaining the focusing coordinate correction result are as follows: S311: Using the aforementioned response input weight configuration, identify the response center coordinate point within the magnetic control cycle, and combine it with the spatial position coordinates of the last response node in the same cycle to analyze the changes in the spatial direction between the response center and the end point of the path, and generate the change in the direction of the center and end point. S312: Based on the change in direction of the center endpoint, determine the directional offset characteristics of the current response center of gravity, combine the response direction extension trajectory, calculate the directional offset trend of the center of gravity, analyze the spatial displacement trend of the path endpoint, and generate the directional offset trend of the center of gravity. S313: Using the aforementioned center of gravity offset trend, combined with the feedback response time information of the corresponding period, spatial correction is performed on the magnetic focusing center coordinates to obtain the focusing coordinate correction result.

6. The method for controlling the magnetic properties of organic molecules based on a magnetic field assisted according to claim 5, characterized in that, The specific steps for obtaining the response sequence reconstruction result are as follows: S411: Based on the focusing coordinate correction results, filter the time feedback records of each response node within the magnetic control cycle, calculate the response time interval difference between each pair of adjacent nodes, and generate a time interval difference value group. S412: Call the time interval difference group, analyze the fluctuation of the time interval, determine the trend of feedback rhythm change, filter out rhythm imbalance segments, identify unstable path areas, and obtain rhythm fluctuation identification results. S413: Based on the rhythm fluctuation recognition results, the current path structure is rearranged according to the stability of the response rhythm, the order of response nodes is adjusted, and the response sequence reconstruction result is obtained.

7. The method for controlling the magnetic properties of organic molecules based on a magnetic field assisted according to claim 1, characterized in that, The method further includes: S5: Call the response sequence reconstruction result, locate the corresponding response state node according to each magnetic field input information in the control sequence, identify the mapping path between the input control sequence and the effective response state by analyzing the direction change in the control input and the angle difference between the magnetic moment directions during the response process, classify the organic magnetic response behavior, and output the magnetic control archive node path set; The magnetically controlled archiving node path set specifically includes the control input direction, response node coordinates, and angle matching path number.

8. The method for controlling the magnetic properties of organic molecules based on a magnetic field assisted according to claim 7, characterized in that, The specific steps for obtaining the magnetically controlled archiving node path set are as follows: S511: Call the response sequence reconstruction result, locate the corresponding response state node according to each magnetic field input information in the control sequence, and generate a control response node location set; S512: Call the control response node location set, analyze the directional changes in the control input sequence, and combine the angle differences between magnetic moment directions during the response process to identify the mapping path between the input control sequence and the effective response state, and obtain the control response mapping path set; S513: Based on the control response mapping path set, analyze the mapping path, classify the organic magnetic response behavior, and output the magnetic control archiving node path set.

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