A magnetic nanotemperature measurement method, device, electronic device, and storage medium based on particle size distribution correction.

Abstract

This application provides a magnetic nanoscale temperature measurement method, device, electronic device, and storage medium based on particle size distribution correction, relating to the field of nanomaterials technology. The method includes: acquiring the electron paramagnetic resonance (EPR) spectrum of magnetic nanoparticles in a target environment, as the target EPR spectrum; extracting the positive and negative peak amplitudes, resonance magnetic field, and peak-to-peak width from the target EPR spectrum, as the target positive and negative peak amplitudes, target resonance magnetic field, and target peak-to-peak width; and calculating the temperature corresponding to the target positive and negative peak amplitudes, target resonance magnetic field, and target peak-to-peak width based on a pre-constructed temperature measurement model, as the temperature of the target environment. The temperature measurement model characterizes the relationship between temperature and the positive and negative peak amplitudes, resonance magnetic field, and peak-to-peak width of the EPR spectrum of the magnetic nanoparticles. The temperature measurement model is constructed based on the particle size distribution of the magnetic nanoparticles. Using this embodiment can improve the accuracy of magnetic nanoscale temperature measurement.

Description

Technical Field

[0001] This application relates to the field of nanomaterials technology, and in particular to a magnetic nanotemperature measurement method, device, electronic device, and storage medium based on particle size distribution correction. Background Technology

[0002] In the fields of life sciences and precision medicine, achieving non-invasive, high-precision temperature distribution imaging at the living cell scale is of great significance for revealing the mechanisms of cellular metabolic energy changes, guiding targeted drug delivery, and tumor hyperthermia. In recent years, magnetic nanoparticle (MNP)-based magnetic thermometry (MRTM) has been regarded as a highly promising cell-level temperature measurement solution due to its excellent tissue penetration and biocompatibility.

[0003] However, existing magnetic nanoparticle thermometry techniques assume that the magnetic nanoparticles used are an ideal monodisperse system, meaning all particles have the same particle size. In reality, due to limitations in current material synthesis and separation processes, magnetic nanoparticles exhibit a certain degree of polydispersity in particle size. Particles of different sizes have different temperature responses, so the temperature obtained may correspond to the temperatures of multiple particle sizes, meaning a unique temperature solution cannot be obtained, thus compromising the accuracy of temperature measurement. Summary of the Invention

[0004] The purpose of this application is to provide a magnetic nanotemperature measurement method, device, electronic device, and storage medium based on particle size distribution correction, so as to improve the accuracy of magnetic nanotemperature measurement. The specific technical solution is as follows:

[0005] A first aspect of this application provides a magnetic nanothermometric method based on particle size distribution correction, the method comprising:

[0006] Obtain the electron paramagnetic resonance (EPR) spectral lines of magnetic nanoparticles in the target environment, and use them as the target EPR spectral lines;

[0007] The positive and negative peak amplitudes, resonance magnetic fields, and peak-to-peak widths are extracted from the target electron paramagnetic resonance spectral lines and used as the target positive and negative peak amplitudes, target resonance magnetic fields, and target peak-to-peak widths.

[0008] Based on a pre-built temperature measurement model, the temperatures corresponding to the target positive and negative peak amplitudes, the target resonant magnetic field, and the target peak-to-peak width are calculated and used as the temperature of the target environment. The temperature measurement model is used to characterize the relationship between temperature and the positive and negative peak amplitudes, resonant magnetic field, and peak-to-peak width of the electron paramagnetic resonance spectrum.

[0009] In one possible implementation, the temperature measurement model is pre-constructed by means of:

[0010] Electron paramagnetic resonance (EPR) lines of magnetic nanoparticles at different temperatures were obtained and used as EPR lines at each temperature.

[0011] The resonant magnetic field and peak-to-peak width are extracted from the electron paramagnetic resonance spectral lines at each temperature, and are used as the resonant magnetic field and peak-to-peak width at each temperature. The resonant magnetic field and peak-to-peak width are affected by the particle size distribution of the magnetic nanoparticles.

[0012] By fitting the electron paramagnetic resonance spectral lines, the resonant magnetic field, and the peak-to-peak width at each of the specified temperatures, a temperature measurement model is obtained.

[0013] In one possible implementation, the expression for the temperature measurement model is:

[0014]

[0015] in, For resonant magnetic fields, Peak-to-peak width, A and B are the amplitudes of the positive and negative peaks of the target electron paramagnetic resonance spectrum, respectively, and η is the polydispersity compensation coefficient for particle size distribution. Temperature information predicted by a monodisperse model.

[0016] In one possible implementation, extracting the resonant magnetic field from the target electron paramagnetic resonance spectral line includes:

[0017] The magnetic field strength at which the signal intensity is 0 is determined from the target electron paramagnetic resonance spectral line and is taken as the resonant magnetic field.

[0018] In one possible implementation, extracting peak-to-peak widths from the target electron paramagnetic resonance spectral line includes:

[0019] The magnetic field corresponding to the peak and the magnetic field corresponding to the trough are determined from the target electron paramagnetic resonance spectral line and are respectively used as the peak magnetic field and the trough magnetic field;

[0020] The difference between the peak magnetic field and the trough magnetic field is calculated as the peak-to-peak width.

[0021] A second aspect of this application provides a magnetic nanotemperature measuring device based on particle size distribution correction, the device comprising:

[0022] The acquisition module is used to acquire the electron paramagnetic resonance spectral lines of magnetic nanoparticles in the target environment, which are then used as the target electron paramagnetic resonance spectral lines.

[0023] The extraction module is used to extract the positive and negative peak amplitudes, resonance magnetic field and peak-to-peak width from the target electron paramagnetic resonance spectral line, as the target positive and negative peak amplitudes, target resonance magnetic field and target peak-to-peak width;

[0024] The calculation module is used to calculate the temperature corresponding to the target positive and negative peak amplitudes, the target resonant magnetic field, and the target peak-to-peak width based on a pre-constructed temperature measurement model, which is used as the temperature of the target environment. The temperature measurement model is used to characterize the relationship between temperature and the positive and negative peak amplitudes, resonant magnetic field, and peak-to-peak width of the electron paramagnetic resonance spectrum. The temperature measurement model is constructed based on the particle size distribution of the magnetic nanoparticles.

[0025] In one possible implementation, the temperature measurement model is pre-constructed by means of:

[0026] Electron paramagnetic resonance (EPR) lines of magnetic nanoparticles at different temperatures were obtained and used as EPR lines at each temperature.

[0027] The resonant magnetic field and peak-to-peak width are extracted from the electron paramagnetic resonance spectral lines at each temperature, and are used as the resonant magnetic field and peak-to-peak width at each temperature. The resonant magnetic field and peak-to-peak width are affected by the particle size distribution of the magnetic nanoparticles.

[0028] By fitting the electron paramagnetic resonance spectral lines, the resonant magnetic field, and the peak-to-peak width at each of the specified temperatures, a temperature measurement model is obtained.

[0029] In one possible implementation, the expression for the temperature measurement model is:

[0030]

[0031] in, For resonant magnetic fields, Peak-to-peak width, Where A is the symmetry factor, B is the amplitude of the positive and negative peaks of the target electron paramagnetic resonance spectrum, respectively, and η is the polydispersity compensation coefficient for particle size distribution. Temperature information predicted by a monodisperse model.

[0032] In one possible implementation, the extraction module is specifically used for:

[0033] The magnetic field strength at which the signal intensity is 0 is determined from the target electron paramagnetic resonance spectral line and is taken as the resonant magnetic field.

[0034] In one possible implementation, the extraction module is specifically used for:

[0035] The magnetic field corresponding to the peak and the magnetic field corresponding to the trough are determined from the target electron paramagnetic resonance spectral line and are respectively used as the peak magnetic field and the trough magnetic field;

[0036] The difference between the peak magnetic field and the trough magnetic field is calculated as the peak-to-peak width.

[0037] This application also provides an electronic device, including a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0038] Memory, used to store computer programs;

[0039] When the processor executes the program stored in the memory, it implements any of the steps of the magnetic nanotemperature measurement method based on particle size distribution correction described above.

[0040] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the magnetic nanotemperature measurement method based on particle size distribution correction described above.

[0041] This application also provides a computer program product containing instructions that, when run on a computer, cause the computer to execute any of the above-described magnetic nanotemperature measurement methods based on particle size distribution correction.

[0042] Beneficial effects of the embodiments in this application:

[0043] This application provides a magnetic nanoparticle temperature measurement method, device, electronic device, and storage medium based on particle size distribution correction. After acquiring the electron paramagnetic resonance (EPR) spectrum of magnetic nanoparticles in the target environment, the positive and negative peak amplitudes, resonance magnetic field, and peak-to-peak widths of the EPR spectrum are extracted. These values ​​are then input into a pre-constructed temperature measurement model. Since this temperature measurement model characterizes the relationship between temperature and the EPR spectrum's positive and negative peak amplitudes, resonance magnetic field, and peak-to-peak widths, and since both the resonance magnetic field and peak-to-peak widths are related to the particle size distribution of the magnetic nanoparticles, the temperature measurement model can automatically correct the influence of particle size on temperature based on the measured resonance magnetic field and peak-to-peak widths, thereby improving the accuracy of magnetic nanoparticle temperature measurement.

[0044] Of course, implementing any product or method of this application does not necessarily require achieving all of the advantages described above at the same time. Attached Figure Description

[0045] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other embodiments can be obtained based on these drawings.

[0046] Figure 1 A schematic diagram of a magnetic nanotemperature measurement method based on particle size distribution correction provided in an embodiment of this application;

[0047] Figure 2 A schematic diagram illustrating the construction of a temperature measurement model provided in an embodiment of this application;

[0048] Figure 3a Example diagrams of EPR spectra of magnetic nanoparticles with different particle size dispersions provided in embodiments of this application;

[0049] Figure 3b Example diagram showing the trend of resonant magnetic field variation with particle size dispersion provided in the embodiments of this application;

[0050] Figure 3c Example graph showing the peak-to-peak width variation with particle size dispersity in embodiments of this application;

[0051] Figure 4 A flowchart for constructing an EPR response model provided in this application embodiment;

[0052] Figure 5 A flowchart for constructing a temperature measurement model provided in this application embodiment;

[0053] Figure 6 A comparative example diagram showing the temperature measurement errors of the temperature measurement model and the monodisperse model provided in the embodiments of this application;

[0054] Figure 7 A schematic diagram of the structure of the magnetic nanotemperature measuring device based on particle size distribution correction provided in the embodiments of this application;

[0055] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0056] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art based on this application are within the scope of protection of this application.

[0057] To improve the accuracy of magnetic nanometer temperature measurement, this application provides a magnetic nanometer temperature measurement method based on particle size distribution correction, applicable to electronic devices, which can be servers or terminal devices, both of which are reasonable. In practical applications, the terminal device can be a smartphone, laptop, desktop computer, etc.

[0058] First, let's introduce the technical terms used in the embodiments of this application:

[0059] Electron paramagnetic resonance (EPR) is a spectroscopic technique specifically used to detect and study unpaired electrons and their surrounding structure in matter. It is typically achieved using an electron paramagnetic resonance spectrometer. The signal spectrum detected by an electron paramagnetic resonance spectrometer, reflecting the transitions of unpaired electrons in a sample as they absorb microwave energy in an applied magnetic field, is called the EPR spectrum.

[0060] The magnetic nanotemperature measurement method based on particle size distribution correction provided in the embodiments of this application will be described below with reference to the accompanying drawings. Figure 1 As shown in the embodiments of this application, the magnetic nanoscale thermometry method based on particle size distribution correction includes the following steps: Step S101, obtaining the electron paramagnetic resonance (EPR) spectrum of magnetic nanoparticles in the target environment as the target EPR spectrum; Step S102, extracting the positive and negative peak amplitudes, resonance magnetic field, and peak-to-peak width from the target EPR spectrum as the target positive and negative peak amplitudes, target resonance magnetic field, and target peak-to-peak width; Step S103, calculating the temperature corresponding to the target positive and negative peak amplitudes, target resonance magnetic field, and target peak-to-peak width based on a pre-constructed temperature measurement model as the temperature of the target environment; wherein, the temperature measurement model is used to characterize the relationship between temperature and the positive and negative peak amplitudes, resonance magnetic field, and peak-to-peak width of the EPR spectrum, and the temperature measurement model is constructed based on the particle size distribution of magnetic nanoparticles. In this embodiment of the application, after obtaining the electron paramagnetic resonance (EPR) spectrum of magnetic nanoparticles in the target environment, the amplitudes of the positive and negative peaks, the resonance magnetic field, and the peak-to-peak width of the EPR spectrum are extracted. These values ​​are then input into a pre-constructed temperature measurement model. Since this temperature measurement model is used to characterize the relationship between temperature and the amplitudes of the positive and negative peaks, the resonance magnetic field, and the peak-to-peak width of the EPR spectrum, and since the resonance magnetic field and peak-to-peak width are both related to the particle size distribution of the magnetic nanoparticles, the temperature measurement model can automatically correct the influence of particle size on temperature based on the measured resonance magnetic field and peak-to-peak width during temperature measurement, thereby improving the accuracy of magnetic nanoparticle temperature measurement.

[0061] The following is a detailed explanation of steps S101-S103:

[0062] In step S101 of this embodiment, the magnetic nanoparticles can be ferrite nanoparticles, magnetic metal nanoparticles, or other paramagnetic nanoparticles; this embodiment does not limit the types of nanoparticles. The target environment refers to the environment in which the paramagnetic magnetic nanoparticles are located and the temperature needs to be measured. For example, assuming the temperature within tumor tissue A needs to be measured, the magnetic nanoparticles are targeted into tumor tissue A, and tumor tissue A is the target environment.

[0063] In this embodiment, the electron paramagnetic resonance (EPR) spectral lines of magnetic nanoparticles in the target environment refer to the EPR spectral lines obtained by measuring the target environment using an EPR spectrometer when the magnetic nanoparticles are placed in the target environment. The EPR spectral lines obtained in this embodiment can be automatically output to the electronic device after the EPR spectrometer measures the EPR spectral lines, or they can be obtained by the electronic device sending a data request to the EPR spectrometer, which then returns the data to the electronic device after completing the measurement, or they can be obtained from data pre-stored in the electronic device; all of these are possible.

[0064] In step S102 of this embodiment, the electron paramagnetic resonance (EPR) spectral line typically exhibits one positive peak and one negative peak. The amplitudes of the positive and negative peaks refer to the amplitudes of the positive and negative peaks of the EPR spectral line, respectively. The resonance magnetic field is the external magnetic field strength value corresponding to the zero-crossing point of the EPR spectral line. The peak-to-peak width is the distance between the positive and negative peaks on the EPR spectral line. In this embodiment, the positive and negative peak amplitudes, resonance magnetic field, and peak-to-peak width are extracted from the target EPR spectral line. This can be achieved through spectral peak detection and measurement, machine learning, or other methods. This embodiment does not limit these methods.

[0065] In step S103 of this embodiment, the temperature measurement model is a multivariate regression model. The inputs to this model are the positive and negative peak amplitudes, the resonant magnetic field, and the peak-to-peak width, and the output is temperature. This model describes the quantitative functional relationship between the positive and negative peak amplitudes, the resonant magnetic field, and the peak-to-peak width and temperature. The temperature measurement model is pre-fitted based on the positive and negative peak amplitudes, the resonant magnetic field, and the peak-to-peak width extracted from EPR curves under different parameters. The specific construction process of the temperature measurement model in this application will be described below.

[0066] In one possible implementation, such as Figure 2As shown, the temperature measurement model is pre-constructed in the following manner: Step S201, obtaining the electron paramagnetic resonance (EPR) spectra of magnetic nanoparticles at different temperatures as the EPR spectra at each temperature; Step S202, extracting the resonance magnetic field and peak-to-peak width from the EPR spectra at each temperature as the resonance magnetic field and peak-to-peak width at each temperature, wherein the resonance magnetic field and peak-to-peak width are affected by the particle size distribution of the magnetic nanoparticles; Step S203, fitting the EPR spectra, resonance magnetic field, and peak-to-peak width at each temperature to obtain the temperature measurement model. Using this embodiment, since the magnetic nanoparticles used in actual temperature measurement have a certain particle size distribution, fitting the resonance magnetic field and peak-to-peak width in the EPR spectra at different temperatures can quantify the influence of the particle size distribution of the magnetic nanoparticles on the temperature. The temperature measurement model constructed in this way can reduce the temperature difference caused by the influence of the magnetic nanoparticle particle size on the temperature during temperature measurement.

[0067] The EPR spectra of magnetic nanoparticles at different temperatures obtained in step S201 of this embodiment can be either EPR spectra of magnetic nanoparticles at different temperatures measured by an electron paramagnetic resonance spectrometer, or EPR spectra of magnetic nanoparticles at different temperatures simulated using a pre-built EPR response model. The construction process of the EPR response model is described below and will not be repeated here.

[0068] It is understandable that, when the EPR spectral lines are measured by an electron paramagnetic resonance spectrometer, the EPR spectral lines of magnetic nanoparticles at different temperatures refer to the measurements obtained by placing the magnetic nanoparticles in a variable-temperature device and using an electron paramagnetic resonance spectrometer at different temperatures.

[0069] For example, suppose the EPR spectra of magnetic nanoparticles obtained at different temperatures are as follows: Figure 3a As shown, from Figure 3a It can be seen that as the particle size distribution (as shown in the figure) increases... As the field increases, the EPR spectral lines of the magnetic nanoparticles broaden and shift towards higher fields. For example... Figure 3b As shown, the EPR resonant magnetic field increases with the increase of the particle size dispersion of magnetic nanoparticles, and the increasing trend is also increasing. Figure 3c As shown, the peak-to-peak width of the EPR spectrum increases with the increase of the particle size dispersion of magnetic nanoparticles. In other words, the influence of the particle size distribution of magnetic nanoparticles on temperature is specifically manifested in the amplitude of the positive and negative peaks, the resonant magnetic field, and the peak-to-peak width of the EPR spectrum. Therefore, it is necessary to establish the relationship between the true temperature that takes into account the particle size distribution and the amplitude of the positive and negative peaks, the resonant magnetic field, and the peak-to-peak width of the electron paramagnetic resonance spectrum.

[0070] In this embodiment, step S202, which extracts the resonant magnetic field and peak-to-peak width, is the same as step S102 described above, and will not be repeated here.

[0071] After extracting the resonance magnetic field and peak-to-peak width in the EPR spectrum at each temperature in step S202 of this embodiment, the resonance magnetic field and peak-to-peak width at each temperature can be obtained. The positive and negative peak amplitudes, resonance magnetic field and peak-to-peak width at each temperature can be represented by a data list or by other forms.

[0072] In step S203 of this embodiment, when fitting the electron paramagnetic resonance (EPR) spectral lines, resonance magnetic fields, and peak-to-peak widths at various temperatures, the least squares method or other algorithms can be used. This embodiment does not limit the fitting method. When fitting the EPR spectral lines, resonance magnetic fields, and peak-to-peak widths at various temperatures, the EPR spectral lines, resonance magnetic fields, and peak-to-peak widths at all temperatures can be used, or the EPR spectral lines, resonance magnetic fields, and peak-to-peak widths at some temperatures can be used. The EPR spectral lines, resonance magnetic fields, and peak-to-peak widths at the remaining temperatures are then used to verify the fitted temperature measurement model.

[0073] In one possible implementation, the expression for the temperature measurement model is:

[0074]

[0075] in, For the target resonant magnetic field, For the target peak-to-peak width, A and B are the amplitudes of the positive and negative peaks of the target electron paramagnetic resonance spectrum, respectively, and η is the polydispersity compensation coefficient for particle size distribution. This is the temperature information predicted by the monodisperse model. Using this embodiment, after measuring the target EPR spectrum and extracting the target positive and negative peak amplitudes, the target resonant magnetic field, and the target peak-to-peak width, the temperature of the target environment can be calculated quickly and accurately, improving the efficiency of magnetic nanothermometry.

[0076] In this embodiment, the monodisperse model refers to a theoretical model constructed under the assumption that all magnetic nanoparticles have the same particle size, used to characterize the relationship between ideal temperature, resonant magnetic field, and peak-to-peak width. By inputting the target resonant magnetic field and target peak-to-peak width into the monodisperse model, the ideal temperature information under the condition that the magnetic nanoparticles have the same particle size can be predicted. Based on this ideal temperature information, the ideal temperature can be derived, which ignores the influence of the magnetic nanoparticle particle size. The specific expression of the temperature information predicted by the monodisperse model is described below and will not be repeated here.

[0077] In this embodiment, the particle size distribution polydispersity compensation coefficient can be preset based on experience and requirements, or it can be obtained during the fitting of the temperature measurement model. This application embodiment does not limit this.

[0078] The specific process of extracting the resonant magnetic field and peak-to-peak width through spectral peak detection and measurement is explained below.

[0079] In one possible implementation, extracting the resonant magnetic field from the target electron paramagnetic resonance (EPR) spectral line includes: determining the magnetic field strength at which the signal intensity is 0 in the target EPR spectral line, and using this as the resonant magnetic field. Using this embodiment, the resonant magnetic field can be quickly determined by identifying the magnetic field strength at which the signal intensity is 0 in the EPR spectral line.

[0080] In one possible implementation, extracting peak-to-peak widths from the target electron paramagnetic resonance (EPR) spectral lines includes: determining the magnetic fields corresponding to the peaks and troughs in the target EPR spectral lines, respectively, as the peak magnetic field and trough magnetic field; and calculating the difference between the peak magnetic field and the trough magnetic field as the peak-to-peak width. Using this embodiment, by determining the magnetic fields corresponding to the peaks and troughs in the EPR spectral lines, the peak-to-peak widths can be determined quickly and accurately.

[0081] In one possible implementation, step S201, obtaining the electron paramagnetic resonance (EPR) spectra of magnetic nanoparticles at different temperatures, includes: obtaining the EPR spectra of magnetic nanoparticles at different temperatures output by a pre-constructed EPR response model, or obtaining the EPR spectra of magnetic nanoparticles at different temperatures measured by an EPR spectrometer. Using this embodiment, the EPR spectra of magnetic nanoparticles at different temperatures can be obtained through experimental or simulation methods, thereby enabling the construction of a temperature measurement model capable of accurate temperature measurement based on the EPR spectra.

[0082] In one possible implementation, such as Figure 4 As shown, the EPR response model is constructed as follows: Step S401, obtaining the particle size distribution characteristics of magnetic nanoparticles; Step S402, using the particle size distribution characteristics to correct the single-particle theoretical spectral line model to obtain the EPR response model. In this embodiment, the particle size distribution characteristics of magnetic nanoparticles are used to correct the single-particle theoretical spectral line model, enabling the obtained EPR response model to simulate the spectral lines of real magnetic nanoparticles at different temperatures. This allows the EPR spectral lines output by the EPR response model at different temperatures to accurately reflect the influence of particle size distribution on temperature.

[0083] In this embodiment, the particle size distribution of the magnetic nanoparticles is obtained through dynamic light scattering and electron microscopy techniques such as scanning electron microscopy and transmission electron microscopy, or other methods. The particle size distribution characteristics of magnetic nanoparticles typically exhibit a log-normal distribution, meaning the particle size distribution characteristics are represented by a magnetic nanoparticle distribution model, the expression of which is:

[0084]

[0085] in, and For logarithmic distribution parameters, , E(D) is the expected value of the magnetic nanoparticle size, Var(D) is the variance of the magnetic nanoparticle size, and D is the magnetic nanoparticle size.

[0086] In this embodiment, the single-particle theoretical spectral line model refers to the theoretical expression used to describe the EPR signal generated by a magnetic nanoparticle in an external magnetic field under given external magnetic field, temperature, and particle size conditions. In one possible implementation, the single-particle theoretical spectral line model can be expressed as follows:

[0087]

[0088] in, , , Let V be the saturation magnetization of the particle, and V be the volume. is the Boltzmann constant.

[0089] In one possible implementation, the EPR response model is obtained by modifying the single-particle theoretical spectral line model using the particle size distribution characteristics of magnetic nanoparticles. It can be expressed by the following formula:

[0090]

[0091] Where H is the external magnetic field and T is the temperature. These are single-particle theoretical spectral lines.

[0092] In one possible implementation, a non-uniform broadening factor can be introduced to correct the single-particle theoretical spectral line model. In this embodiment, step S402, which uses particle size distribution characteristics to correct the single-particle theoretical spectral line model to obtain an EPR response model, includes: correcting the single-particle theoretical spectral line model using particle size distribution characteristics to obtain a first EPR response model; and correcting the first EPR response model based on a non-uniform broadening factor to obtain an EPR response model. By introducing a non-uniform broadening factor in this embodiment, the constructed EPR response model more accurately simulates the EPR spectral line shape of actual polydisperse magnetic nanoparticle samples.

[0093] In one possible implementation, the non-uniform broadening factor The expression is:

[0094]

[0095] In one possible implementation, the expression for the EPR response model obtained by correcting for particle size distribution characteristics and non-uniform widening factors is as follows:

[0096] .

[0097] In one possible implementation, the temperature information predicted by the monodisperse model above can be expressed as:

[0098]

[0099] in, The original external magnetic field, , These represent the magnetic nanoparticles' magnetic resistance and demagnetization, respectively, where K is the effective anisotropy constant and γ is the gyromagnetic ratio. This is the paramagnetic relaxation time.

[0100] See Figure 5 In one possible implementation, the process of constructing the temperature measurement model provided in this application may include the following steps:

[0101] Step S501: Construct a magnetic nanoparticle distribution model;

[0102] Step S502: Construct an EPR response model based on particle size distribution.

[0103] Step S503: Extract the resonant magnetic field and peak-to-peak width;

[0104] Step S504: Construct a temperature measurement model based on particle size distribution.

[0105] Step S501 is equivalent to step S401 above, step S502 is equivalent to step S402 above, step S503 is equivalent to step S402 above, and step S505 is equivalent to step S403 above.

[0106] As can be seen from the above, the temperature measurement model provided in this application takes into account the influence of particle size distribution on temperature during measurement, and therefore predicts a more accurate temperature than the monodisperse model. Figure 6 As shown in the figure, the vertical axis represents the root mean square error between the measured temperature and the actual temperature. It can be seen from the figure that the temperature error of the monodisperse model (i.e., the uncorrected model in the figure) increases sharply under high dispersion. That is, the increase of particle size dispersion will seriously affect the temperature measurement accuracy of the model. The temperature measurement model in this application (i.e., the particle size distribution corrected model in the figure) is a temperature measurement model based on particle size distribution correction, which can reduce the temperature error caused by the influence of particle size distribution on temperature.

[0107] A second aspect of this application provides a magnetic nanometer temperature measuring device based on particle size distribution correction, such as... Figure 7 As shown, the device includes:

[0108] The acquisition module 701 is used to acquire the electron paramagnetic resonance spectral lines of magnetic nanoparticles in the target environment, and use them as the target electron paramagnetic resonance spectral lines.

[0109] Extraction module 702 is used to extract the positive and negative peak amplitudes, resonance magnetic field and peak-to-peak width from the target electron paramagnetic resonance spectral lines, as the target positive and negative peak amplitudes, target resonance magnetic field and target peak-to-peak width;

[0110] The calculation module 703 is used to calculate the temperature corresponding to the target positive and negative peak amplitudes, the target resonant magnetic field, and the target peak-to-peak width based on a pre-built temperature measurement model, which is used as the temperature of the target environment. The temperature measurement model is used to characterize the relationship between temperature and the positive and negative peak amplitudes, resonant magnetic field, and peak-to-peak width of the electron paramagnetic resonance spectrum. The temperature measurement model is constructed based on the particle size distribution of magnetic nanoparticles.

[0111] In this embodiment of the application, after obtaining the electron paramagnetic resonance (EPR) spectrum of magnetic nanoparticles in the target environment, the amplitudes of the positive and negative peaks, the resonance magnetic field, and the peak-to-peak width of the EPR spectrum are extracted. These values ​​are then input into a pre-constructed temperature measurement model. Since this temperature measurement model is used to characterize the relationship between temperature and the amplitudes of the positive and negative peaks, the resonance magnetic field, and the peak-to-peak width of the EPR spectrum, and since the resonance magnetic field and peak-to-peak width are both related to the particle size distribution of the magnetic nanoparticles, the temperature measurement model can automatically correct the influence of particle size on temperature based on the measured resonance magnetic field and peak-to-peak width during temperature measurement, thereby improving the accuracy of magnetic nanoparticle temperature measurement.

[0112] In one possible implementation, the temperature measurement model is pre-built in the following manner:

[0113] Electron paramagnetic resonance (EPR) lines of magnetic nanoparticles at different temperatures were obtained and used as EPR lines at each temperature.

[0114] The resonant magnetic field and peak-to-peak width were extracted from the electron paramagnetic resonance spectral lines at various temperatures and used as the resonant magnetic field and peak-to-peak width at each temperature. The resonant magnetic field and peak-to-peak width are affected by the particle size distribution of the magnetic nanoparticles.

[0115] By fitting the electron paramagnetic resonance spectrum, the resonance magnetic field, and the peak-to-peak width at each temperature, a temperature measurement model is obtained.

[0116] In one possible implementation, the expression for the temperature measurement model is:

[0117]

[0118] in, For resonant magnetic fields, Peak-to-peak width, Let A be the symmetry factor, and B be the amplitudes of the positive and negative peaks of the target electron paramagnetic resonance spectrum, respectively. Let η be the polydispersity compensation coefficient for the particle size distribution. Temperature information predicted by a monodisperse model.

[0119] In one possible implementation, the extraction module is specifically used for:

[0120] The magnetic field strength at which the signal intensity is 0 is determined from the target electron paramagnetic resonance spectral line and is taken as the resonance magnetic field.

[0121] In one possible implementation, the extraction module is specifically used for:

[0122] The magnetic fields corresponding to the peaks and troughs of the target electron paramagnetic resonance spectral lines are determined and used as the peak magnetic field and trough magnetic field, respectively.

[0123] Calculate the difference between the peak magnetic field and the trough magnetic field, which is used as the peak-to-peak width.

[0124] This application also provides an electronic device, such as... Figure 8 As shown, it includes a processor 801, a communication interface 802, a memory 803, and a communication bus 804, wherein the processor 801, the communication interface 802, and the memory 803 communicate with each other through the communication bus 804.

[0125] Memory 803 is used to store computer programs;

[0126] When processor 801 executes a program stored in memory 803, it performs the following steps:

[0127] Obtain the electron paramagnetic resonance (EPR) spectral lines of magnetic nanoparticles in the target environment, and use them as the target EPR spectral lines;

[0128] The positive and negative peak amplitudes, resonance magnetic fields, and peak-to-peak widths are extracted from the target electron paramagnetic resonance spectral lines and used as the target positive and negative peak amplitudes, target resonance magnetic fields, and target peak-to-peak widths.

[0129] Based on a pre-constructed temperature measurement model, the temperatures corresponding to the target positive and negative peak amplitudes, the target resonant magnetic field, and the target peak-to-peak width are calculated and used as the temperature of the target environment. The temperature measurement model is used to characterize the relationship between temperature and the positive and negative peak amplitudes, resonant magnetic field, and peak-to-peak width of the electron paramagnetic resonance spectrum. The temperature measurement model is constructed based on the particle size distribution of magnetic nanoparticles.

[0130] The communication bus mentioned in the above electronic devices can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in the diagram, but this does not indicate that there is only one bus or one type of bus.

[0131] The communication interface is used for communication between the aforementioned electronic devices and other devices.

[0132] The memory may include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0133] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0134] In another embodiment provided in this application, a computer-readable storage medium is also provided, which stores a computer program that, when executed by a processor, implements the steps of any of the above-described magnetic nanotemperature measurement methods based on particle size distribution correction.

[0135] In another embodiment provided in this application, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to execute any of the magnetic nanotemperature measurement methods based on particle size distribution correction in the above embodiments.

[0136] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially as a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. 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. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. 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 integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid state disk (SSD)).

[0137] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0138] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the apparatus embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0139] The above description is merely a preferred embodiment of this application and is not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application are included within the scope of protection of this application.

Claims

1. A magnetic nanothermometry method based on particle size distribution correction, characterized in that, The method includes: Obtain the electron paramagnetic resonance (EPR) spectral lines of magnetic nanoparticles in the target environment, and use them as the target EPR spectral lines; The positive and negative peak amplitudes, resonance magnetic fields, and peak-to-peak widths are extracted from the target electron paramagnetic resonance spectral lines and used as the target positive and negative peak amplitudes, target resonance magnetic fields, and target peak-to-peak widths. Based on a pre-constructed temperature measurement model, the temperatures corresponding to the target positive and negative peak amplitudes, the target resonant magnetic field, and the target peak-to-peak width are calculated and used as the temperature of the target environment. The temperature measurement model is used to characterize the relationship between temperature and the positive and negative peak amplitudes, resonant magnetic field, and peak-to-peak width of the electron paramagnetic resonance spectrum. The temperature measurement model is constructed based on the particle size distribution of the magnetic nanoparticles.

2. The method according to claim 1, characterized in that, The temperature measurement model is pre-constructed in the following manner, including: Electron paramagnetic resonance (EPR) lines of magnetic nanoparticles at different temperatures were obtained and used as EPR lines at each temperature. The resonant magnetic field and peak-to-peak width are extracted from the electron paramagnetic resonance spectral lines at each temperature, and are used as the resonant magnetic field and peak-to-peak width at each temperature. The resonant magnetic field and peak-to-peak width are affected by the particle size distribution of the magnetic nanoparticles. By fitting the electron paramagnetic resonance spectral lines, the resonant magnetic field, and the peak-to-peak width at each of the specified temperatures, a temperature measurement model is obtained.

3. The method according to claim 1 or 2, characterized in that, The expression for the temperature measurement model is: ； in, For the target resonant magnetic field, For the target peak-to-peak width, A and B are the amplitudes of the positive and negative peaks of the target electron paramagnetic resonance spectrum, respectively, and η is the polydispersity compensation coefficient for particle size distribution. Temperature information predicted by a monodisperse model.

4. The method according to claim 1, characterized in that, Extracting the resonant magnetic field from the target electron paramagnetic resonance spectral line includes: The magnetic field strength at which the signal intensity is 0 is determined from the target electron paramagnetic resonance spectral line and used as the resonant magnetic field.

5. The method according to claim 1, characterized in that, Extracting peak-to-peak widths from the target electron paramagnetic resonance spectral lines includes: The magnetic fields corresponding to the peaks and the magnetic fields corresponding to the troughs of the target electron paramagnetic resonance spectral lines are determined and used as the peak magnetic field and the trough magnetic field, respectively. The difference between the peak magnetic field and the trough magnetic field is calculated as the peak-to-peak width.

6. A magnetic nanotemperature measuring device based on particle size distribution correction, characterized in that, The device includes: The acquisition module is used to acquire the electron paramagnetic resonance spectral lines of magnetic nanoparticles in the target environment, which are then used as the target electron paramagnetic resonance spectral lines. The extraction module is used to extract the positive and negative peak amplitudes, resonance magnetic field and peak-to-peak width from the target electron paramagnetic resonance spectral line, as the target positive and negative peak amplitudes, target resonance magnetic field and target peak-to-peak width; The calculation module is used to calculate the temperature corresponding to the target positive and negative peak amplitudes, the target resonant magnetic field, and the target peak-to-peak width based on a pre-constructed temperature measurement model, which is used as the temperature of the target environment. The temperature measurement model is used to characterize the relationship between temperature and the positive and negative peak amplitudes, resonant magnetic field, and peak-to-peak width of the electron paramagnetic resonance spectrum. The temperature measurement model is constructed based on the particle size distribution of the magnetic nanoparticles.

7. The apparatus according to claim 6, characterized in that, The temperature measurement model is pre-constructed in the following manner, including: Electron paramagnetic resonance (EPR) lines of magnetic nanoparticles at different temperatures were obtained and used as EPR lines at each temperature. The resonant magnetic field and peak-to-peak width are extracted from the electron paramagnetic resonance spectral lines at each temperature, and are used as the resonant magnetic field and peak-to-peak width at each temperature. The resonant magnetic field and peak-to-peak width are affected by the particle size distribution of the magnetic nanoparticles. By fitting the electron paramagnetic resonance spectral lines, the resonant magnetic field, and the peak-to-peak width at each of the specified temperatures, a temperature measurement model is obtained.

8. The apparatus according to claim 6 or 7, characterized in that, The expression for the temperature measurement model is: ； in, For resonant magnetic fields, Peak-to-peak width, Where A is the symmetry factor, B is the amplitude of the positive and negative peaks of the target electron paramagnetic resonance spectrum, respectively, and η is the polydispersity compensation coefficient for particle size distribution. Temperature information predicted by a monodisperse model; and / or The extraction module is specifically used for: The magnetic field strength at which the signal intensity is 0 is determined from the target electron paramagnetic resonance spectral line and used as the resonant magnetic field; and / or The extraction module is specifically used for: The magnetic fields corresponding to the peaks and the magnetic fields corresponding to the troughs of the target electron paramagnetic resonance spectral lines are determined and used as the peak magnetic field and the trough magnetic field, respectively. The difference between the peak magnetic field and the trough magnetic field is calculated as the peak-to-peak width.

9. An electronic device, characterized in that, It includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; A processor, when executing a program stored in memory, implements the steps of the method described in any one of claims 1-5.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the method described in any one of claims 1-5.

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