Method and system for measuring electrophoresis mobility and zeta potential

Abstract

The invention relates to the technical field of optical detection, in particular to a method and system for measuring electrophoresis mobility and zeta potential, and the method comprises the steps: collecting a multi-source signal in real time, the multi-source signal comprising an electric field signal, a scattered light signal and an environmental parameter; the scattered light frequency of the scattered light signals is extracted, two paths of orthogonal reference signals are generated, and whether frequency drift occurs or not is judged; when frequency drift occurs, the phases and the frequencies of the two paths of orthogonal reference signals are adjusted, and the two paths of synchronous orthogonal reference signals are output; extracting a phase signal of the scattered light signal; performing real-time cross-correlation calculation on the phase signal and the electric field signal, outputting a cross-correlation function, extracting features, and outputting an average phase; the electrophoresis mobility and the zeta potential are output; and generating a feedback report. The method has the effect of accurately acquiring information of small electrophoresis mobility in a non-aqueous phase system or a high-conductivity suspension so as to obtain zeta potential.

Description

Technical Field

[0001] The present application relates to the field of optical detection technology, and specifically to a method and system for measuring electrophoretic mobility and zeta potential. Background Art

[0002] Electrophoretic light scattering (ELS) is one of the leading methods for characterizing the zeta potential of nanoparticles. This method involves applying an electric field to surface-charged nanoparticles suspended in a solution. This causes them to undergo directional electrophoretic motion and velocity along the field, inducing a Doppler effect in the scattered light, resulting in a shift in the scattered light's frequency. The frequency shift is then extracted by analyzing the spectrum to determine the particle's electrophoretic mobility. Finally, theoretical models (such as the Henry function) are used to derive the zeta potential.

[0003] The core technology of electrophoretic light scattering (ELS) is to calculate the Doppler shift of scattered light. However, when nanoparticles are in non-aqueous phases or highly conductive suspensions, their electrophoretic mobility is very low, resulting in a very small Doppler shift. In these cases, increasing the electric field strength and extending the measurement time are necessary to obtain a good electrophoretic spectrum, but this introduces other problems, such as Joule heating and electrode polarization. In such cases, traditional ELS is not a suitable solution.

[0004] Therefore, improvements are needed. Summary of the Invention

[0005] In order to solve the technical problem of how to accurately obtain information on small electrophoretic mobility and thereby obtain zeta potential in non-aqueous phase systems or high conductivity suspensions, the present application provides a method and system for measuring electrophoretic mobility and zeta potential.

[0006] The first object of the invention of this application is achieved through the following technical solutions:

[0007] A method for measuring electrophoretic mobility and zeta potential, comprising:

[0008] Based on preset experimental parameters, multi-source signals are collected in real time, wherein the multi-source signals include electric field signals, scattered light signals and environmental parameters;

[0009] extracting the scattered light frequency of the scattered light signal, generating two orthogonal reference signals, and determining whether frequency drift occurs;

[0010] When frequency drift occurs, the phase and frequency of the two orthogonal reference signals are adjusted to output two synchronized orthogonal reference signals;

[0011] Extracting the phase signal of the scattered light signal based on the scattered light signal, two synchronized orthogonal reference signals, a preset low-pass filter, and a preset inverse trigonometric function operation;

[0012] Performing real-time cross-correlation calculation on the phase signal and the electric field signal, outputting a cross-correlation function and extracting features, and outputting an average phase;

[0013] Outputting electrophoretic mobility and zeta potential based on the average phase, a preset electrophoretic mobility formula, and a preset Henry model;

[0014] A feedback report is generated, wherein the feedback report includes electrophoretic mobility and zeta potential.

[0015] In a preferred embodiment, the step of collecting multi-source signals in real time based on preset experimental parameters, wherein the multi-source signals include electric field signals, scattered light signals, and environmental parameters, includes:

[0016] The electric field signal is represented by E(t), and the scattered light signal is represented by y total (t), the environmental parameters include temperature T, conductivity σ;

[0017] Where, E(t)=E sin(ω e t+φ), E, ω e and φ are the amplitude, angular frequency and initial phase of the electric field signal E(t), respectively;

[0018] in, A.ω s and are scattered light signals y total (t), the amplitude of the reference light signal, the angular frequency of the reference light signal, and the phase function of the scattered light signal.

[0019] In a preferred embodiment, the steps of extracting the scattered light frequency of the scattered light signal, generating two orthogonal reference signals, and determining whether frequency drift occurs include:

[0020] The two orthogonal reference signals include parallel reference signals y || and vertical reference signal y ⊥ (t);

[0021] Among them, y || (t) = sin(ω r t)、 ω r is the angular frequency of the two orthogonal reference signals;

[0022] The scattered light signal y total (t) and the parallel reference signal y || , vertical reference signal y ⊥ (t) performs multiplication processing and outputs a first modulated signal X(t) and a second modulated signal Y(t);

[0023] in,

[0024] When phase-locked operation is performed, ω s =ω r ,at this time

[0025]

[0026] In a preferred embodiment, the step of extracting the phase signal of the scattered light signal based on the scattered light signal, two synchronized orthogonal reference signals, a preset low-pass filter, and a preset inverse trigonometric function operation includes:

[0027] Based on the preset low-pass filter, X(t), Y(t), the first low-frequency signal X(t) is output ‘ : and the second low-frequency signal Y(t) ’ :

[0028] Based on the preset inverse trigonometric function operation, the first low-frequency signal X(t) ‘ and the second low-frequency signal Y(t) ’ , output phase signal

[0029] In a preferred embodiment, the steps of performing real-time cross-correlation calculation on the phase signal and the electric field signal, outputting a cross-correlation function and extracting features, and outputting an average phase include:

[0030] The phase signal Perform cross-correlation operation with the electric field signal E(t) and output the cross-correlation function R Eφ (τ), extract the cross-correlation function R Eφ The peak value P of (τ) i (i=1,2,…,N), valley value V j (j=1,2,…,M);

[0031] Based on preset formula Peak P i (i=1,2,…,N), valley value V j (j=1,2,…,M), output average phase

[0032] In a preferred embodiment, the step of outputting electrophoretic mobility and zeta potential based on the average phase, a preset electrophoretic mobility formula, and a preset Henry model includes:

[0033] Based on a preset electrophoretic mobility formula Outputs the electrophoretic mobility μ, where λ0, n, and θ are the wavelength, medium refractive index, and scattering angle, respectively.

[0034] Based on the preset Henry model, the zeta potential ζ is output: Among them, η, ε and F (kr) represent the viscosity coefficient, dielectric constant and Henry function respectively.

[0035] The second object of the invention of this application is achieved through the following technical solutions:

[0036] A system for measuring electrophoretic mobility and zeta potential, comprising:

[0037] Acquisition module: Based on preset experimental parameters, real-time acquisition of multi-source signals, including electric field signals, scattered light signals and environmental parameters;

[0038] A judgment module is configured to extract the scattered light frequency of the scattered light signal, generate two orthogonal reference signals, and judge whether frequency drift occurs;

[0039] Adjustment module: When frequency drift occurs, adjust the phase and frequency of the two orthogonal reference signals and output two synchronized orthogonal reference signals;

[0040] Extraction module: extracts the phase signal of the scattered light signal based on the scattered light signal, two synchronized orthogonal reference signals, preset low-pass filtering and preset inverse trigonometric function operations;

[0041] Calculation module: performs real-time cross-correlation calculation on the phase signal and the electric field signal, outputs a cross-correlation function and extracts features, and outputs an average phase;

[0042] Output module: outputs electrophoretic mobility and zeta potential based on the average phase, a preset electrophoretic mobility formula, and a preset Henry model;

[0043] Generation module: Generates a feedback report, which includes electrophoretic mobility and zeta potential.

[0044] The third object of the invention of this application is achieved through the following technical solutions:

[0045] A computer device comprises a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above-mentioned method for measuring electrophoretic mobility and zeta potential are implemented.

[0046] The fourth invention objective of this application is achieved through the following technical solutions:

[0047] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the above-mentioned method for measuring electrophoretic mobility and zeta potential.

[0048] In summary, this application includes at least one of the following beneficial technical effects:

[0049] First, using preset experimental parameters, the system collects multiple signals, including electric field signals, scattered light signals, and environmental parameters, in real time, ensuring comprehensive and accurate data. Next, the scattered light signal is used to extract the scattered light frequency and generate two orthogonal reference signals. By monitoring and adjusting the phase and frequency of these two signals in real time, frequency drift is effectively addressed, ensuring signal stability and reliability. In the phase signal extraction stage, the scattered light signal, along with two synchronized orthogonal reference signals, a preset low-pass filter, and inverse trigonometric functions are combined to accurately extract the phase of the scattered light signal. Subsequently, a real-time cross-correlation calculation is performed between the phase signal and the electric field signal, outputting not only the cross-correlation function but also extracting features and calculating the average phase. Based on the average phase, the preset electrophoretic mobility formula, and the Henry model, the system ultimately outputs the electrophoretic mobility and zeta potential, achieving precise measurement of the sample's electrophoretic properties. Finally, a feedback report is generated, detailing key information such as electrophoretic mobility and zeta potential, providing strong support for experimental analysis and application. This method not only improves the accuracy and efficiency of electrophoretic mobility and zeta potential measurements, but also has strong anti-interference ability and real-time performance. It is suitable for various complex experimental environments and provides strong technical support for research and applications in related fields. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 This is a schematic diagram of the technical principle of an embodiment of a method for measuring electrophoretic mobility and zeta potential of the present application;

[0051] Figure 2 This is a graph showing experimental results when the electrophoresis voltage is 12 V in an embodiment of a method for measuring electrophoretic mobility and zeta potential of the present application;

[0052] Figure 3 This is a graph of zeta potential results in an embodiment of a method for measuring electrophoretic mobility and zeta potential of the present application;

[0053] Figure 4 This is a principle block diagram of a computer device of the present application. DETAILED DESCRIPTION

[0054] The following is combined with Figure 1-4 This application is described in further detail.

[0055] In one embodiment, if Figure 1 As shown, the present application discloses a method for measuring electrophoretic mobility and zeta potential, which specifically includes the following steps:

[0056] S10: Based on preset experimental parameters, multi-source signals are collected in real time, where the multi-source signals include electric field signals, scattered light signals, and environmental parameters;

[0057] S20: extracting the scattered light frequency of the scattered light signal, generating two orthogonal reference signals, and determining whether frequency drift occurs;

[0058] S30: When frequency drift occurs, adjust the phase and frequency of the two orthogonal reference signals and output the two synchronized orthogonal reference signals;

[0059] S40: extracting a phase signal of the scattered light signal based on the scattered light signal, two synchronized orthogonal reference signals, a preset low-pass filter, and a preset inverse trigonometric function operation;

[0060] S50: performing real-time cross-correlation calculation on the phase signal and the electric field signal, outputting a cross-correlation function and extracting features, and outputting an average phase;

[0061] S60: Outputting electrophoretic mobility and zeta potential based on the average phase, a preset electrophoretic mobility formula, and a preset Henry model;

[0062] S70: Generate a feedback report, wherein the feedback report includes electrophoretic mobility and zeta potential.

[0063] In this embodiment, the electrophoretic mobility and zeta potential measurement method, based on advanced signal processing and data analysis technologies, achieves high-precision, real-time measurement. First, by presetting experimental parameters, the system collects multiple sources of signals, including electric field signals, scattered light signals, and environmental parameters, in real time, ensuring the comprehensiveness and accuracy of the data. Next, the scattered light signal is used to extract the scattered light frequency and generate two orthogonal reference signals. By real-time monitoring and adjusting the phase and frequency of these two signals, the frequency drift problem is effectively addressed, ensuring signal stability and reliability. In the phase signal extraction stage, the phase signal of the scattered light signal is accurately extracted by combining the scattered light signal, two synchronized orthogonal reference signals, preset low-pass filtering, and inverse trigonometric function operations. Subsequently, the phase signal and electric field signal are cross-correlated in real time, not only outputting the cross-correlation function, but also extracting features and calculating the average phase. Based on the average phase, the preset electrophoretic mobility formula, and the Henry model, the system ultimately outputs the electrophoretic mobility and zeta potential, achieving accurate measurement of the sample's electrophoretic properties. Finally, the generated feedback report contains detailed information on key factors such as electrophoretic mobility and zeta potential, providing strong support for experimental analysis and application. This method not only improves the accuracy and efficiency of electrophoretic mobility and zeta potential measurements, but also exhibits strong anti-interference capabilities and real-time performance, making it suitable for a variety of complex experimental environments and providing strong technical support for research and application in related fields.

[0064] like Figure 1 As shown, step S10 includes:

[0065] S101: The electric field signal is represented by E(t), and the scattered light signal is represented by y total (t), the environmental parameters include temperature T, conductivity σ;

[0066] S102: Where, E(t)=E sin(ω e t+φ), E, ω e and φ are the amplitude, angular frequency and initial phase of the electric field signal E(t), respectively;

[0067] S103: Among them, A.ω s and are scattered light signals y total (t), the amplitude of the reference light signal, the angular frequency of the reference light signal, and the phase function of the scattered light signal.

[0068] In this embodiment, step S10 lays a solid data foundation for the entire electrophoretic mobility and zeta potential measurement method. Specifically, step S101 clarifies the types of multi-source signals collected, including the electric field signal E(t), the scattered light signal y total(t) and environmental parameters (such as temperature T, conductivity σ) are captured in real time and accurately. The comprehensive collection of these parameters ensures the effectiveness and reliability of subsequent analysis. Furthermore, S102 and S103 steps mathematically model the electric field signal and scattered light signal. The electric field signal is expressed as E(t) = E sin(ω e t+φ), where E, ω e and φ represent the amplitude, angular frequency, and initial phase of the electric field signal E(t), respectively. This representation facilitates subsequent signal processing and analysis. Similarly, the scattered light signal is represented as Among them, A, ω s and are scattered light signals y total (t), the amplitude of the reference light signal, and the phase function of the scattered light signal. This representation not only reveals the essential characteristics of the scattered light signal, but also provides a theoretical basis for the extraction of the phase signal. Through this precise signal representation and acquisition, this method can ensure that the detection of frequency drift, extraction of phase signals, cross-correlation calculations, and output of electrophoretic mobility and zeta potential in subsequent steps are highly accurate and stable. Ultimately, the generated feedback report will include these key measurement results, providing intuitive and effective data support. In summary, step S10 provides reliable data support for the entire measurement process through precise signal acquisition and representation, thereby ensuring the efficiency and accuracy of this method in electrophoretic mobility and zeta potential measurements.

[0069] like Figure 1 As shown, step S20 includes:

[0070] S201: The two orthogonal reference signals include parallel reference signals y || and vertical reference signal y ⊥ (t);

[0071] S202: Among them, y || (t) = sin(ω r t)、 ω r is the angular frequency of the two orthogonal reference signals;

[0072] S203: The scattered light signal y total (t) and the parallel reference signal y || , vertical reference signal y ⊥ (t) performs multiplication processing and outputs a first modulated signal X(t) and a second modulated signal Y(t);

[0073] S204: Among them,

[0074] S205: When performing phase-locked operation, ω s =ω r ,at this time

[0075] In this embodiment, in step S20, this embodiment uses advanced signal processing technology to ensure the accuracy and stability of the phase extraction of the scattered light signal. First, two orthogonal reference signals are generated - parallel reference signals y || and vertical reference signal y ⊥ (t), the two signals have the same angular frequency ω r , ensuring the synchronization of signal processing. Then, by transforming the scattered light signal y total (t) and the parallel reference signal y || and vertical reference signal y ⊥ (t) is multiplied to obtain the first modulated signal X(t): This step utilizes the principle of signal modulation to convert the phase information of the scattered light signal into a processable modulation signal, laying the foundation for subsequent phase extraction. In the phase-locked operation, the angular frequency of the reference signal is adjusted so that ω s =ω r , ensuring the accuracy of phase extraction. This phase-locking technology effectively improves the anti-interference capability of signal processing and ensures the stable output of phase information. In summary, step S20 achieves precise extraction of the phase of the scattered light signal by generating an orthogonal reference signal, performing signal modulation, and performing phase-locking operations. This process not only improves the accuracy of phase measurement but also enhances the stability and anti-interference capability of the system, providing reliable data support for subsequent electrophoretic mobility and zeta potential calculations.

[0076] like Figure 1 As shown, step S40 includes:

[0077] S401: Based on the preset low-pass filter, X(t), Y(t), output the first low-frequency signal X(t) ‘ : and the second low-frequency signal Y(t) ’ :

[0078] S402: Based on the preset inverse trigonometric function operation, the first low-frequency signal X(t) ‘ and the second low-frequency signal Y(t) ’ , output phase signal

[0079] In this embodiment, the signal processing process is further deepened to ensure that phase information can be accurately extracted from complex signals. First, the first modulated signal X(t) and the second modulated signal Y(t) are processed by a preset low-pass filter to filter out high-frequency noise and interference, thereby obtaining the first low-frequency signal X(t). ‘ : and the second low-frequency signal Y(t) ’ : This step effectively improves the signal quality and creates favorable conditions for subsequent phase extraction. Then, the first low-frequency signal X(t) is calculated using the preset inverse trigonometric function. ‘ and the second low-frequency signal Y(t) ’ After further processing, the phase signal is finally output The preset inverse trigonometric function operation accurately converts the amplitude of the low-frequency signal into the corresponding phase value, thereby achieving precise extraction of phase information. In summary, step S40 successfully extracts the phase signal from the scattered light signal through low-pass filtering and the preset inverse trigonometric function operation. This process not only improves the accuracy of phase measurement but also enhances the stability and anti-interference capability of signal processing. Ultimately, the precise phase signal provides reliable data support for subsequent electrophoretic mobility and zeta potential calculations, further enhancing the effectiveness and accuracy of the entire measurement method.

[0080] like Figure 1 As shown, step S50 includes:

[0081] S501: The phase signal Perform cross-correlation operation with the electric field signal E(t) and output the cross-correlation function R Eφ (τ), extract the cross-correlation function R Eφ The peak value P of (τ) i (i=1,2,…,N), valley value V j (j=1,2,…,M);

[0082] S502: Based on the preset formula Peak P i (i=1,2,…,N), valley value V j (j=1,2,…,M), output average phase

[0083] In this embodiment, in step S50, this embodiment uses the key technology of cross-correlation operation to further accurately process the phase signal. First, the phase signal is extracted Perform cross-correlation operation with the electric field signal E(t) to obtain the cross-correlation function REφ (τ). The cross-correlation operation can effectively reveal the phase relationship between the two signals. By analyzing the peak value P of the cross-correlation function i and valley value V j , we can deeply understand the phase difference and synchronization between signals. Then, based on the preset formula and the extracted peak P i and valley value V j , calculate the average phase This step utilizes the characteristic information of the cross-correlation function and further refines the average phase value through a mathematical model, thus providing more accurate phase data for subsequent electrophoretic mobility and zeta potential calculations. In summary, step S50 successfully achieves high-precision processing of phase and electric field signals through cross-correlation calculations and feature extraction. This process not only improves the accuracy of phase measurement but also enhances the stability and reliability of data processing. Ultimately, the precise average phase value lays a solid foundation for the accurate calculation of electrophoretic mobility and zeta potential, further enhancing the effectiveness and practicality of the entire measurement method.

[0084] like Figure 1 As shown, step S60 includes:

[0085] S601: Based on the preset electrophoretic mobility formula Outputs the electrophoretic mobility μ, where λ0, n, and θ are the wavelength, medium refractive index, and scattering angle, respectively.

[0086] S602: Based on the preset Henry model, output zeta potential ζ: Among them, η, ε and F (kr) represent the viscosity coefficient, dielectric constant and Henry function respectively.

[0087] In this embodiment, the preset electrophoretic mobility formula is combined The system calculates the electrophoretic mobility and zeta potential accurately based on the preset Henry model. Using known parameters such as wavelength λ0, medium refractive index n, and scattering angle θ, the electrophoretic mobility μ is calculated. This calculation process is based on electrophoresis theory, ensuring that the electrophoretic mobility result accurately reflects the migration characteristics of the sample under the action of an electric field. Then, in step S602, the system further calculates the zeta potential based on the preset Henry model. This model takes into account the viscosity coefficient η, dielectric constant ε, and Henry function F (kr)Factors such as zeta potential were used to calculate the key parameter zeta potential through complex mathematical calculations. Zeta potential is an important indicator for measuring the surface charge of particles and is of great significance for understanding the surface properties and electrophoretic behavior of samples. In summary, step S60 successfully achieved the output of electrophoretic mobility and zeta potential through precise formula calculations and model application. This process not only improved the accuracy of the measurement results, but also enhanced the scientific nature and reliability of the method. Ultimately, the generated electrophoretic mobility and zeta potential data provided strong support for experimental analysis and application, demonstrating the advanced nature and practicality of this embodiment in measuring electrophoretic properties.

[0088] like Figure 2 As shown in the figure, when the electrophoresis voltage is 12V, (a) is the phase signal result, (b) is the cross-correlation function result, and the small squares and small circles represent the peak points and valley points of the curve respectively. Figure 3 In (a), the peaks and valleys of the phase signal function are not obvious, and no theoretical periodic signal is formed, which will lead to a large error between the extracted electrophoretic mobility and the true value. On the contrary, after the correlation processing, that is, Figure 3 The peaks and troughs of the cross-correlation function curve in (b) are clearly distinguished, and its periodicity is significantly enhanced, which is more conducive to extracting accurate electrophoretic mobility and then obtaining more accurate zeta potential values.

[0089] like Figure 3 As shown in the figure, (a) is the zeta potential obtained from the phase signal, (b) is the zeta potential obtained from the cross-correlation function, and (c) is the experimental error. It can be seen that the zeta potential obtained after cross-correlation processing is closer to the true value and has a lower error.

[0090] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0091] In one embodiment, a system for measuring electrophoretic mobility and zeta potential is provided. The system for measuring electrophoretic mobility and zeta potential corresponds to the method for measuring electrophoretic mobility and zeta potential in the above embodiment. The system for measuring electrophoretic mobility and zeta potential includes:

[0092] Acquisition module: Based on preset experimental parameters, real-time acquisition of multi-source signals, including electric field signals, scattered light signals and environmental parameters;

[0093] A judgment module is configured to extract the scattered light frequency of the scattered light signal, generate two orthogonal reference signals, and judge whether frequency drift occurs;

[0094] Adjustment module: When frequency drift occurs, adjust the phase and frequency of the two orthogonal reference signals and output two synchronized orthogonal reference signals;

[0095] Extraction module: extracts the phase signal of the scattered light signal based on the scattered light signal, two synchronized orthogonal reference signals, preset low-pass filtering and preset inverse trigonometric function operations;

[0096] Calculation module: performs real-time cross-correlation calculation on the phase signal and the electric field signal, outputs a cross-correlation function and extracts features, and outputs an average phase;

[0097] Output module: outputs electrophoretic mobility and zeta potential based on the average phase, a preset electrophoretic mobility formula, and a preset Henry model;

[0098] Generation module: Generates a feedback report, which includes electrophoretic mobility and zeta potential.

[0099] Optionally, also include:

[0100] The first module includes: the electric field signal is represented by E(t), the scattered light signal is represented by y total (t), the environmental parameters include temperature T, conductivity σ;

[0101] The first calculation module: Where E(t) = E sin(ω e t+φ), E, ω e and φ are the amplitude, angular frequency and initial phase of the electric field signal E(t), respectively;

[0102] Second calculation module: wherein, A.ω s and are scattered light signals y total (t), the amplitude of the reference light signal, the angular frequency of the reference light signal, and the phase function of the scattered light signal.

[0103] Optionally, also include:

[0104] The second module includes: the two orthogonal reference signals include parallel reference signals y || and vertical reference signal y ⊥ (t);

[0105] The third calculation module: where y || (t) = sin(ω r t)、 ω r is the angular frequency of the two orthogonal reference signals;

[0106] The first output module: the scattered light signal y total (t) and the parallel reference signal y || , vertical reference signal y ⊥ (t) performs multiplication processing and outputs a first modulated signal X(t) and a second modulated signal Y(t);

[0107] The fourth calculation module: wherein,

[0108] The fifth calculation module: When performing phase-locked operation, ω s =ω r ,at this time

[0109]

[0110] Optionally, also include:

[0111] Second output module: Based on the preset low-pass filter, X(t), Y(t), output the first low-frequency signal X(t) ‘ : and the second low-frequency signal Y(t) ’ :

[0112] The third output module: based on the preset inverse trigonometric function operation and the first low-frequency signal X(t) ‘

[0113] and the second low-frequency signal Y(t) ’ , output phase signal

[0114] Optionally, also include:

[0115] The fourth output module: the phase signal Perform cross-correlation operation with the electric field signal E(t) and output the cross-correlation function R Eφ (τ), extract the cross-correlation function R Eφ The peak value P of (τ) i (i=1,2,…,N), valley value V j (j=1,2,…,M);

[0116] The sixth calculation module: based on the preset formula Peak P i (i=1,2,…,N), valley value V j (j=1,2,…,M), output average phase

[0117] Optionally, also include:

[0118] The fifth output module: based on the preset electrophoretic mobility formula Outputs the electrophoretic mobility μ, where λ0, n, and θ are the wavelength, medium refractive index, and scattering angle, respectively.

[0119] The sixth output module: Based on the preset Henry model, outputs the zeta potential ζ: Among them, η, ε and F (kr) represent the viscosity coefficient, dielectric constant and Henry function respectively.

[0120] The specific definition of a system for measuring electrophoretic mobility and zeta potential can be found in the definition of a method for measuring electrophoretic mobility and zeta potential described above and will not be repeated here. The various modules in the above-mentioned system for measuring electrophoretic mobility and zeta potential can be implemented in whole or in part through software, hardware, or a combination thereof. The above-mentioned modules can be embedded in or independent of a processor in a computer device in hardware form, or can be stored in a memory in a computer device in software form, so that the processor can call and execute the operations corresponding to the above modules.

[0121] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 4 As shown. The computer device includes a processor, a memory, a network interface and a database connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store electrophoretic mobility and zeta potential. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a method for measuring electrophoretic mobility and zeta potential is implemented.

[0122] In one embodiment, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, a method for measuring electrophoretic mobility and zeta potential is implemented.

[0123] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, a method for measuring electrophoretic mobility and zeta potential is provided.

[0124] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0125] Those skilled in the art will clearly understand that for the sake of convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

Claims

1. A method for measuring electrophoretic mobility and zeta potential, characterized in that: include: Based on preset experimental parameters, multi-source signals are collected in real time, wherein the multi-source signals include electric field signals, scattered light signals and environmental parameters; extracting the scattered light frequency of the scattered light signal, generating two orthogonal reference signals, and determining whether frequency drift occurs; When frequency drift occurs, the phase and frequency of the two orthogonal reference signals are adjusted to output two synchronized orthogonal reference signals; Extracting the phase signal of the scattered light signal based on the scattered light signal, two synchronized orthogonal reference signals, a preset low-pass filter, and a preset inverse trigonometric function operation; Performing real-time cross-correlation calculation on the phase signal and the electric field signal, outputting a cross-correlation function and extracting features, and outputting an average phase; Outputting electrophoretic mobility and zeta potential based on the average phase, a preset electrophoretic mobility formula, and a preset Henry model; A feedback report is generated, wherein the feedback report includes electrophoretic mobility and zeta potential.

2. The method for measuring electrophoretic mobility and zeta potential according to claim 1, wherein: The step of collecting multi-source signals in real time based on preset experimental parameters, wherein the multi-source signals include electric field signals, scattered light signals and environmental parameters, includes: The electric field signal is represented by E(t), and the scattered light signal is represented by y total (t), the environmental parameters include temperature T, conductivity σ; Where E(t)=E sin(ω e t+φ), E, ω e and φ are the amplitude, angular frequency and initial phase of the electric field signal E(t), respectively; in, A.ω s and are scattered light signals y total (t), the amplitude of the reference light signal, the angular frequency of the reference light signal, and the phase function of the scattered light signal.

3. The method for measuring electrophoretic mobility and zeta potential according to claim 1, wherein: The step of extracting the scattered light frequency of the scattered light signal, generating two orthogonal reference signals, and determining whether frequency drift occurs includes: The two orthogonal reference signals include parallel reference signals y || and vertical reference signal y ⊥ (t); Among them, y || (t) = sin(ω r t)、 ω r is the angular frequency of the two orthogonal reference signals; The scattered light signal y total (t) and the parallel reference signal y || , vertical reference signal y ⊥ (t) performs multiplication processing and outputs a first modulated signal X(t) and a second modulated signal Y(t); in, When phase-locked operation is performed, ω s =ω r ,at this time 4. The method for measuring electrophoretic mobility and zeta potential according to claim 1, wherein: The step of extracting the phase signal of the scattered light signal based on the scattered light signal, two synchronized orthogonal reference signals, a preset low-pass filter, and a preset inverse trigonometric function operation includes: Based on the preset low-pass filter, X(t), Y(t), the first low-frequency signal X(t) is output ‘ : and the second low-frequency signal Y(t) ’ : Based on the preset inverse trigonometric function operation, the first low-frequency signal X(t) ‘ and the second low-frequency signal Y(t) ’ , output phase signal 5. The method for measuring electrophoretic mobility and zeta potential according to claim 1, wherein: The step of performing real-time cross-correlation calculation on the phase signal and the electric field signal, outputting a cross-correlation function and extracting features, and outputting an average phase comprises: The phase signal Perform cross-correlation operation with the electric field signal E(t) and output the cross-correlation function R Eφ (τ), extract the cross-correlation function R Eφ The peak value P of (τ) i (i=1,2,…,N), valley value V j (j=1,2,…,M); Based on preset formula Peak P i (i=1,2,…,N), valley value V j (j=1,2,…,M), output average phase 6. The method for measuring electrophoretic mobility and zeta potential according to claim 1, wherein: The step of outputting electrophoretic mobility and zeta potential based on the average phase, a preset electrophoretic mobility formula, and a preset Henry model includes: Based on a preset electrophoretic mobility formula Outputs the electrophoretic mobility μ, where λ0, n, and θ are the wavelength, medium refractive index, and scattering angle, respectively. Based on the preset Henry model, the zeta potential ζ is output: Among them, η, ε and F (kr) represent the viscosity coefficient, dielectric constant and Henry function respectively.

7. A system for measuring electrophoretic mobility and zeta potential, characterized in that: include: Acquisition module: Based on preset experimental parameters, real-time acquisition of multi-source signals, including electric field signals, scattered light signals and environmental parameters; A judgment module is configured to extract the scattered light frequency of the scattered light signal, generate two orthogonal reference signals, and judge whether frequency drift occurs; Adjustment module: When frequency drift occurs, adjust the phase and frequency of the two orthogonal reference signals and output two synchronized orthogonal reference signals; Extraction module: extracts the phase signal of the scattered light signal based on the scattered light signal, two synchronized orthogonal reference signals, preset low-pass filtering and preset inverse trigonometric function operations; Calculation module: performs real-time cross-correlation calculation on the phase signal and the electric field signal, outputs a cross-correlation function and extracts features, and outputs an average phase; Output module: outputs electrophoretic mobility and zeta potential based on the average phase, a preset electrophoretic mobility formula, and a preset Henry model; Generation module: Generates a feedback report, which includes electrophoretic mobility and zeta potential.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the method for measuring electrophoretic mobility and zeta potential as claimed in claims 1 to 6 are implemented.

9. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the steps of the method for measuring electrophoretic mobility and zeta potential according to claims 1 to 6.

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