Method and system for detecting the strongest rayleigh acoustic streaming in a pinned microdroplet

Abstract

This invention discloses a method and system for detecting the strongest Rayleigh acoustic current in immobilized microdroplets. Specifically, it involves: calculating the acoustic current suppression coefficient through experimental quantitative testing to establish a quantitative mapping relationship between acoustic current intensity and droplet contact angle; utilizing an electrowetting structure composed of interdigitated electrodes, a dielectric layer, and a hydrophobic layer to actively regulate the droplet contact angle through an applied voltage; and dynamically adjusting the applied voltage in real time by monitoring the droplet vibration amplitude, particle velocity, and contact angle through a collaborative control program to maintain the acoustic current intensity at its strongest. This invention also provides a detection system for implementing the above method, including an indium tin oxide transparent interdigitated electrode substrate, a lead zirconate titanate piezoelectric transducer, a laser Doppler vibrometer, a microscope, and a collaborative control module. This invention can maximize and dynamically maintain the Rayleigh acoustic current intensity in immobilized microdroplets, significantly accelerating the solid-liquid interface mass transfer process, and is applicable to biochemical analysis fields such as rapid immunoassay and biological particle mixing.

Description

Technical Field

[0001] This invention relates to the field of interdisciplinary technology of acoustohydrodynamics and microfluidic chips, and in particular to a method and system for detecting the strongest Rayleigh acoustic flow in immobilized microdroplets. Background Technology

[0002] Acoustic streaming refers to the steady-state flow phenomenon that occurs when sound waves propagate in a fluid, transferring pseudo-momentum to the fluid through nonlinear effects. Based on different generation mechanisms, acoustic streaming is mainly divided into two categories: Eckart streaming, driven by the viscous attenuation of high-frequency sound waves in the fluid bulk phase; and Rayleigh streaming, driven by ultrasonic shearing near the fluid boundary. Rayleigh streaming exhibits boundary slip velocity, reaching an asymptotic value within a few micrometers of the solid-liquid interface, thus effectively eliminating the hydrodynamic boundary layer at the solid-liquid interface.

[0003] In the field of biosensing and biochemical analysis, sessile droplets, as an important form of microreactor, have attracted much attention due to their extremely low reagent consumption and batch processing capabilities. However, microdroplet detection based on surface biosensors faces an inherent contradiction between detection speed and reagent consumption: the mass transfer process of analytes diffusing from the droplet bulk phase to the sensor surface is usually the slowest step, while the concentration boundary layer formed at the solid-liquid interface severely hinders the analyte from reaching the sensor surface. Rayleigh acoustic flow, by generating boundary slip velocity, can effectively disrupt the hydrodynamic boundary layer at the solid-liquid interface, significantly accelerating the mass transfer process of analytes to the sensor surface. A 2023 study used Rayleigh acoustic flow to reduce the SARS-CoV-2 antibody immunoassay time from 20 minutes to 40 seconds, achieving a 30-fold acceleration, while the reagent consumption was only 2.5% to 5% of that of traditional 96-well plate detection. Furthermore, Rayleigh acoustic flow exhibits excellent biocompatibility and insensitivity to fluid composition and viscosity in complex biofluids such as blood, plasma, serum, saliva, and urine, making it valuable in biological applications such as biological particle mixing, rapid immunoassay, DNA hybridization detection, and surface plasmon resonance (SPR) detection.

[0004] In existing technologies, the quantitative characterization schemes for Rayleigh acoustic flow mainly include the following two categories:

[0005] The first category comprises direct flow velocity measurement schemes based on particle image velocimetry (PIV) and laser Doppler velocimetry (LDV). PIV, a classic method for measuring acoustic flow velocity, acquires spatially resolved velocity fields through pulsed laser illumination and imaging. In 1989, PIV was first reported for measuring acoustic flow velocity in circular tubes, pioneering the experimental quantitative characterization of acoustic flow. In 2005, research utilized LDV to simultaneously measure acoustic flow velocity and acoustic vibration velocity in standing wave fields, and developed a signal processing algorithm considering the influence of temperature gradients. In 2023, researchers combined LDV with generalized defocused particle tracking (GDPT) technology, achieving experimental reconstruction of the Rayleigh acoustic flow velocity field in fixed microdroplets by measuring the vibration amplitude of the droplet surface and the three-dimensional trajectory of internal fluorescent tracer particles. However, such schemes mainly provide transient or time-averaged spatial distribution information of acoustic flow velocity, but have not yet established a quantitative relationship between acoustic flow intensity and droplet geometry (such as contact angle, contact line diameter, etc.), and cannot directly guide the acquisition of optimal acoustic flow state.

[0006] Option 2: Acoustic Flow Control Based on Shape-Optimized Channels. In 2020, a study proposed a quantitative characterization method for the acoustic flow suppression coefficient in shape-optimized channels through theoretical analysis and numerical simulation. This method systematically explored the influence of channel geometry on acoustic flow intensity and provided a quantitative theoretical value for the acoustic flow suppression coefficient. While this research provides an important theoretical foundation for the quantitative characterization of acoustic flow fields, its research object is limited to acoustic flow phenomena within microchannels, and the proposed complex curved channel structure presents significant challenges in actual fabrication, lacking experimental verification.

[0007] A comprehensive analysis of existing technologies reveals the following technical problems in this field:

[0008] (1) There is a lack of quantitative characterization methods for Rayleigh acoustic flow intensity in fixed microdroplet systems. Although existing PIV / LDV measurement schemes can obtain the spatial distribution of acoustic flow velocity, a quantitative mapping relationship between acoustic flow intensity and droplet geometric parameters (contact angle, contact line, volume, etc.) has not yet been established. Although existing studies have proposed quantitative characterization methods for acoustic flow suppression coefficients, their research objects are limited to microchannel systems and cannot be directly applied to fixed microdroplets.

[0009] (2) Existing acoustic flow control schemes are difficult to achieve quantitative optimization in fixed microdroplets. Although the existing proposed shape optimization channel schemes provide quantitative simulation values ​​of acoustic flow suppression coefficients, their geometric optimization ideas based on hard-walled microchannels cannot be directly transferred to fixed microdroplet systems. Moreover, the complex three-dimensional curved channel structure has extremely high requirements for microfabrication technology and is difficult to achieve through conventional soft lithography or micromachining, thus lacking experimental feasibility.

[0010] (3) There is a lack of technical approaches to actively control the droplet shape using electrical methods to quantitatively optimize the acoustic flow intensity. The contact angle and shape of immobilized microdroplets are usually passively determined by the substrate surface properties and the fluid physicochemical properties. Existing technologies have not yet achieved real-time and reversible control of the droplet contact angle through external electrical signals (such as dielectric wetting, electrochemical modulation, etc.), thereby actively seeking and maintaining the strongest Rayleigh acoustic flow state.

[0011] (4) Current biological applications of acoustic flow excitation lack resonance optimization and real-time feedback mechanisms. Studies have shown that droplet evaporation causes changes in volume and contact angle over time, which in turn alters the acoustic resonance frequency, making it difficult to maintain the strongest acoustic flow state continuously with fixed-frequency excitation. Current technologies have not established a real-time feedback control mechanism between droplet shape, resonance frequency, and acoustic flow intensity, making it impossible to quantitatively explore and dynamically maintain the strongest Rayleigh acoustic flow state.

[0012] Therefore, there is an urgent need to study a method that can quantitatively detect the strongest Rayleigh acoustic flow in immobilized microdroplets. By establishing a quantitative relationship between acoustic flow intensity and droplet shape, and combining electrical methods to actively control the droplet contact angle, the Rayleigh acoustic flow intensity in immobilized microdroplets can be maximized, thereby providing technical support for applications such as rapid biological detection and efficient mixing of biological particles. Summary of the Invention

[0013] The purpose of this invention is to provide a method and system for detecting the strongest Rayleigh acoustic flow in immobilized microdroplets, which quantitatively explores and dynamically maintains the strongest Rayleigh acoustic flow state by actively controlling the shape of the immobilized microdroplets.

[0014] The technical solution to achieve the objective of this invention is: a method for detecting the strongest Rayleigh acoustic flux in immobilized microdroplets, comprising the following steps:

[0015] Step 1: Quantitatively measure and calculate the acoustic flow in the immobilized microdroplets using experimental methods, including: measuring the second-order steady-state acoustic velocity using cell tracing methods. The vibration amplitude of the fixed microdroplets was measured using a laser Doppler vibrometer, and the vibration amplitude was then substituted into a multiphysics simulation to obtain the acoustic energy density through numerical calculation. Furthermore, based on the acoustic energy density Calculate the acoustic velocity According to the second-order steady-state acoustic velocity and the acoustic velocity Calculate the acoustic flow suppression coefficient ;

[0016] Step 2: Actively control the contact angle of droplets by combining electrical control methods, including: fabricating interdigital electrodes on a transparent electrode substrate and coating them with dielectric and hydrophobic layers in sequence; changing the interfacial tension between the immobilized microdroplets and the solid surface by applying an external voltage, thereby actively controlling the contact angle of the immobilized microdroplets.

[0017] Step 3: Investigate the relationship between the contact angle of the immobilized microdroplet and the acoustic flow intensity in the immobilized microdroplet, including: changing the excitation voltage to set the immobilized microdroplet at different contact angles, and repeating Step 1 at each contact angle to quantify the corresponding acoustic flow intensity, thereby establishing a quantitative mapping relationship between the contact angle and the acoustic flow intensity.

[0018] Step 4: Achieve coordinated control of droplet contact angle and acoustic flow intensity in droplet to dynamically maintain the strongest acoustic flow state. This includes: monitoring the vibration amplitude, particle speed and contact angle of the fixed microdroplet in real time through a coordinated control program, and adjusting the applied voltage in real time according to the quantitative mapping relationship established in Step 3, so that the acoustic flow intensity is dynamically maintained at the preset strongest state.

[0019] Furthermore, in step one, the acoustic flow suppression coefficient Calculated using the following formula:

[0020]

[0021] in, The acoustic flow suppression coefficient is... As a regulating factor, For acoustic velocity, For second-order steady-state acoustic velocity, The volume of the immobilized microdroplets; For the integration region, For volume integral variables; As a volumetric infinitesimal element, it is used in spatial regions Earn points; It is a step function.

[0022] Furthermore, in step one, the acoustic velocity Calculated using the following formula:

[0023]

[0024] in, The average acoustic energy density in the fluid, or simply acoustic energy density; For the density of the fluid, The speed at which sound waves propagate in a fluid.

[0025] Furthermore, in step one, the acoustic energy density Calculated using the following formula:

[0026]

[0027] in, For first-order sound pressure, It is the first-order speed of sound.

[0028] Furthermore, in step one, when measuring the vibration amplitude of the fixed microdroplet using a laser Doppler vibrometer, the voltage signal output by the photodetector of the laser Doppler vibrometer... Satisfy the following formula:

[0029]

[0030] in, Let be the impedance of the photodetector. The amplitude of the current density at the photodetector. The heterodyne frequency shift between the reference beam and the measurement beam, For time, Wavelength, To fix the mechanical vibration amplitude on the surface of the microdroplets, To determine the migration frequency of the immobilized microdroplet surface, For the initial phase, For the fixed phase of the reference beam, To measure the fixed phase of the beam, The imaginary unit, This indicates taking the real part.

[0031] Furthermore, when the mechanical vibration amplitude of the surface of the attached microdroplets... For values ​​greater than 100 nm, the mechanical vibration amplitude is calculated using a non-perturbation method. The non-perturbation method is based on the Jacobi-Anger expansion of the above equation:

[0032]

[0033] in, for The first-order Bessel equation, where n is an integer;

[0034] By measuring the amplitude ratios between different harmonics, the mechanical vibration amplitude of the surface of the fixed microdroplet can be obtained by substituting the ratios into the above equation. .

[0035] Furthermore, in step two:

[0036] The interdigitated electrode is an indium tin oxide transparent interdigitated electrode;

[0037] The dielectric layer is a chloroethyl pullulan dielectric layer;

[0038] The hydrophobic layer is a Teflon hydrophobic layer;

[0039] The active control of the contact angle follows the Lippmann-Young equation, which states that the contact angle decreases as the applied voltage increases.

[0040] Furthermore, the collaborative control program in step four is a Python program;

[0041] The real-time monitoring includes: acquiring the vibration amplitude of the top of the fixed microdroplet using a laser Doppler vibrometer, acquiring a side view image of the fixed microdroplet using a microscope to calculate the contact angle, and tracking the particle displacement to obtain the particle velocity.

[0042] The real-time adjustment of the applied voltage includes: when the calculated acoustic flow suppression coefficient is obtained... When the target range is deviated from the preset target range, the target contact angle is found according to the quantitative mapping relationship between the contact angle and the acoustic flow intensity established in step three, and the required voltage change is calculated, thereby controlling the applied voltage to change the current contact angle.

[0043] Furthermore, step four also includes: real-time detection of whether the contact line of the fixed microdroplet has slipped. When the contact angle is detected to exceed the range of the retreat angle or the advance angle, it is determined that the contact line has slipped. At this time, the system stops adjusting the voltage and issues an alarm to prevent the fixed microdroplet from breaking or overflowing.

[0044] A detection system for the strongest Rayleigh acoustic current in a fixed microdroplet, used to implement a method for detecting the strongest Rayleigh acoustic current in the fixed microdroplet, the system comprising:

[0045] Indium tin oxide transparent interdigitated electrode substrate is used to support immobilized microdroplets and actively control the contact angle of the immobilized microdroplets by applying voltage to the substrate;

[0046] Lead zirconate titanate piezoelectric transducers are used to provide sound source energy to excite acoustic streams.

[0047] Laser Doppler vibration meter is used to measure the vibration amplitude of fixed microdroplets;

[0048] Microscopes are used to observe the velocity of particles in fixed microdroplets to obtain second-order steady-state acoustic flow rates. ;

[0049] A collaborative control module is connected to the indium tin oxide transparent interdigitated electrode substrate, the laser Doppler vibrometer, and the microscope, respectively. The collaborative control module receives vibration amplitude data measured by the laser Doppler vibrometer and particle velocity data measured by the microscope, calculates the real-time acoustic flow intensity in the fixed microdroplets, dynamically calculates the required voltage adjustment based on the comparison between the real-time acoustic flow intensity and the preset strongest acoustic flow state, and outputs a control voltage to the indium tin oxide transparent interdigitated electrode substrate to adjust the contact angle of the fixed microdroplets, thereby maintaining the strongest acoustic flow state.

[0050] Compared with the prior art, the significant advantages of this invention are:

[0051] (1) It can not only quantitatively measure the acoustic flow intensity in fixed microdroplets, but also give a quantitative relationship between droplet contact angle and acoustic flow intensity, providing a theoretical basis for active optimization;

[0052] (2) By combining the collaborative control program Python with the electrical control method, the vibration amplitude, particle velocity and contact angle are monitored in real time, and the applied voltage is dynamically adjusted to achieve the continuous dynamic maintenance of the strongest acoustic flow state in the fixed microdroplets under disturbances such as droplet evaporation;

[0053] (3) An electrowetting structure consisting of an indium tin oxide transparent interdigitated electrode, a dielectric layer and a hydrophobic layer is adopted to achieve real-time, reversible and active control of the contact angle of the fixed microdroplets, overcoming the limitations of traditional passive control.

[0054] (4) A non-perturbation method based on Jacobi-Anger expansion is proposed, which is applicable to the case where the vibration amplitude of the droplet surface is greater than 100 nm. The mechanical vibration amplitude is inverted by the harmonic amplitude ratio, which ensures the accuracy of the quantification of acoustic energy density and acoustic flow intensity.

[0055] (5) To maintain the strongest Rayleigh acoustic flow in immobilized microdroplets, a complete implementation method combining numerical quantification and dynamic control was designed, thus providing technical support for applications such as rapid biological detection and efficient mixing of biological particles. Attached Figure Description

[0056] Figure 1 A schematic diagram of the Rayleigh acoustic flow smooth quantization process.

[0057] Figure 2 This is a schematic diagram of the electrical control of the droplet contact angle.

[0058] Figure 3 A schematic diagram of the method for investigating the acoustic flow intensity in immobilized microdroplets. Detailed Implementation

[0059] This invention provides a method for detecting the strongest Rayleigh acoustic flux in immobilized microdroplets, comprising the following steps:

[0060] Step 1: Quantitatively measure and calculate the acoustic flow in the immobilized microdroplets using experimental methods, including: measuring the second-order steady-state acoustic velocity using cell tracing methods. The vibration amplitude of the fixed microdroplets was measured using a laser Doppler vibrometer, and the vibration amplitude was then substituted into a multiphysics simulation to obtain the acoustic energy density through numerical calculation. Furthermore, based on the acoustic energy density Calculate the acoustic velocity According to the second-order steady-state acoustic velocity and the acoustic velocity Calculate the acoustic flow suppression coefficient ;

[0061] Step 2: Actively control the contact angle of droplets by combining electrical control methods, including: fabricating interdigital electrodes on a transparent electrode substrate and coating them with dielectric and hydrophobic layers in sequence; changing the interfacial tension between the immobilized microdroplets and the solid surface by applying an external voltage, thereby actively controlling the contact angle of the immobilized microdroplets.

[0062] Step 3: Investigate the relationship between the contact angle of the immobilized microdroplet and the acoustic flow intensity in the immobilized microdroplet, including: changing the excitation voltage to set the immobilized microdroplet at different contact angles, and repeating Step 1 at each contact angle to quantify the corresponding acoustic flow intensity, thereby establishing a quantitative mapping relationship between the contact angle and the acoustic flow intensity.

[0063] Step 4: Achieve coordinated control of droplet contact angle and acoustic flow intensity in droplet to dynamically maintain the strongest acoustic flow state. This includes: monitoring the vibration amplitude, particle speed and contact angle of the fixed microdroplet in real time through a coordinated control program, and adjusting the applied voltage in real time according to the quantitative mapping relationship established in Step 3, so that the acoustic flow intensity is dynamically maintained at the preset strongest state.

[0064] As a specific example, in step one, the acoustic flow suppression coefficient Calculated using the following formula:

[0065] (1)

[0066] in, The acoustic flow suppression coefficient is... As a regulating factor, For acoustic velocity, For second-order steady-state acoustic velocity, The volume of the immobilized microdroplets; For the integration region, For volume integral variables; As a volumetric infinitesimal element, it is used in spatial regions Earn points; It is a step function.

[0067] In step one, the acoustic velocity Calculated using the following formula:

[0068] (2)

[0069] in, The average acoustic energy density in the fluid, or simply acoustic energy density; For the density of the fluid, The speed at which sound waves propagate in a fluid.

[0070] In step one, the acoustic energy density Calculated using the following formula:

[0071] (3)

[0072] in, For first-order sound pressure, It is the first-order speed of sound.

[0073] As can be seen from the above formula, the key to solving the acoustic flow suppression coefficient is to find... as well as :

[0074] Second-order steady-state acoustic velocity The velocity of a cell under acoustic manipulation can be measured using cell tracing methods.

[0075] acoustic velocity That is, the acoustic energy density in microdroplets The solution can be obtained by substituting the microdroplet amplitude obtained from the laser Doppler vibration meter into the multiphysics simulation and using numerical calculation.

[0076] A schematic diagram of the quantification process is shown below. Figure 1 As shown, Figure 1 Figure (a) shows the principle of laser Doppler vibration meter, which measures the vibration amplitude of the droplet surface by measuring the Doppler frequency shift between the measurement beam and the reference beam.

[0077] In the process of calculating vibration amplitude, studies have shown that when the vibration amplitude of the droplet surface is greater than 100 nm, the perturbation method is no longer applicable. Therefore, a non-perturbation method is needed to calculate the vibration amplitude under large amplitude.

[0078] Figure 1 When measuring the vibration amplitude of the fixed microdroplet using a laser Doppler vibrometer in (a), the voltage signal output by the photodetector of the laser Doppler vibrometer... Satisfy the following formula:

[0079] (4)

[0080] in, Let be the impedance of the photodetector. The amplitude of the current density at the photodetector. The heterodyne frequency shift between the reference beam and the measurement beam, For time, Wavelength, To fix the mechanical vibration amplitude on the surface of the microdroplets, To determine the migration frequency of the immobilized microdroplet surface, For the initial phase, For the fixed phase of the reference beam, To measure the fixed phase of the beam, The imaginary unit, This indicates taking the real part.

[0081] when When the amplitude is much greater than unit 1, especially when the mechanical vibration amplitude on the surface of the fixed microdroplets is much greater than unit 1, For values ​​greater than 100 nm, the mechanical vibration amplitude is calculated using a non-perturbation method. The non-perturbation method is based on Jacobi-Anger expansion according to formula (4):

[0082] (5)

[0083] in, for Bessel equation of order 1, The spectrum is composed of a series of frequencies. , amplitude The peaks are composed of n, where n is an integer. Therefore, the mechanical vibration amplitude of the object surface can be obtained by the amplitude ratio between the peaks. By measuring the amplitude ratio between each harmonic, the mechanical vibration amplitude of the surface of the fixed microdroplet is obtained by substituting it into formula (5). For example, the ratio of the second harmonic to the first harmonic can be written as: ,in Then the amplitude can be obtained. ,in It is the amplitude ratio of the second harmonic to the first harmonic in the experiment, a function. visible Figure 1 (b) Figure 1 (c) in the figure represents the calculation process of particle velocity and second-order steady-state acoustic velocity in the fixed microdroplet.

[0084] This invention proposes a non-perturbative vibration amplitude calculation method applicable to large amplitudes (>100 nm), improving the accuracy of acoustic energy density measurement. The perturbation method proposed by Royer et al. is only applicable to droplet surface vibration amplitudes less than 100 nm, while the vibration amplitudes of the fixed microdroplets involved in this invention are often greater than 100 nm, rendering the perturbation method inapplicable. This invention employs a non-perturbative method based on Jacobi-Anger expansion. By measuring the amplitude ratio of each harmonic (e.g., first harmonic to second harmonic) in the output signal of a laser Doppler vibrometer, the true mechanical vibration amplitude is inverted, thereby accurately calculating acoustic energy density and acoustic velocity, ensuring the accuracy of acoustic flow intensity quantification.

[0085] As a specific example, in step two: the interdigitated electrode is an indium tin oxide transparent interdigitated electrode; the dielectric layer is a chloroethyl pullulan dielectric layer; the hydrophobic layer is a Teflon hydrophobic layer; the active control of the contact angle follows the Lippmann-Young equation, that is, the contact angle decreases as the applied voltage increases.

[0086] Active control of droplet contact angle is achieved by combining electrical modulation methods. Transparent indium tin oxide (ITO) electrodes are selected; the interdigitated ITO electrodes enable dynamic control of the contact angle of the immobilized microdroplets. A schematic diagram is shown below. Figure 2 As shown, interdigitated electrodes were fabricated on an ITO glass substrate and then sequentially coated with a cyanoethyl pullulan (CEP) dielectric layer and a Teflon hydrophobic layer. The contact angle of the droplet was actively controlled by altering the interfacial tension between the droplet and the solid surface using an applied DC voltage. The detailed processing procedure is as follows:

[0087] ① Fabrication of substrate and interdigitated electrodes (conductive layer)

[0088] ITO-coated glass was selected as the substrate and transparent electrode material. Patterns were defined on the ITO glass using standard photolithography, followed by wet etching to form interdigitated electrodes with a finger width and finger spacing of 50 μm.

[0089] ② Dielectric layer coating (CEP layer)

[0090] CEP is a polymer material with a high dielectric constant, which can effectively store charge and withstand high electric fields. The film is formed by spin coating onto the surface of ITO glass with pre-fabricated electrodes. After coating, appropriate drying or curing treatment is performed to ensure that the film layer is dense and insulating. The thickness of the dielectric layer after curing reaches approximately 410 nm.

[0091] ③ Hydrophobic coating (Teflon layer)

[0092] The same spin-coating process is used to coat Teflon onto the CEP dielectric layer, with a final thickness of approximately 60 nm.

[0093] ④ Principle of active contact angle control (electrowetting effect)

[0094] After the substrate fabrication is completed, the contact angle can be dynamically controlled using electrical methods: a DC power supply is connected to the interdigital electrodes, and a driving voltage is applied below the droplet. The voltage accumulates charge above and below the dielectric layer (CEP), generating electrostatic force and altering the effective tension of the solid-liquid interface. According to the Lippmann-Young equation, the contact angle θ decreases as the voltage increases (i.e., the droplet spreads more widely). By continuously adjusting the excitation voltage, the equilibrium contact angle of the droplet is always kept lower than the retreating contact angle, thereby forcing the droplet contact line to remain in a "pinned" state, achieving dynamic adjustment of the contact angle while keeping the contact line unchanged.

[0095] This invention introduces active electrowetting control technology into the acoustic flow optimization of immobilized microdroplets, achieving real-time, reversible, and active control of the droplet contact angle. Existing acoustic flow control schemes (such as shape-optimized channels) are based on rigid-walled microchannels, which cannot be adapted to immobilized microdroplet systems, and the complex three-dimensional curved channel structures are difficult to fabricate. Furthermore, the contact angle of traditional immobilized microdroplets is passively determined by the substrate surface properties and fluid properties, and cannot be actively adjusted. This invention uses an indium tin oxide (ITO) transparent interdigitated electrode, a chloroethyl pullulan (CEP) dielectric layer, and a Teflon hydrophobic layer to construct an electrowetting structure. By applying an external DC voltage, the droplet contact angle can be actively controlled in real time and reversibly (following the Lippmann-Young equation), achieving active intervention in droplet shape. The process is simple and easy to implement.

[0096] As a specific example, in step three, the relationship between the droplet contact angle and the acoustic flow intensity in the fixed microdroplet is explored, and a quantitative mapping relationship between the acoustic flow intensity and the droplet geometric parameters (contact angle) is established.

[0097] Building such Figure 3 The apparatus shown uses an LDV (Light Detector Vapor Transducer) to emit a laser to measure the droplet vibration amplitude, a lead zirconate titanate (PZT) piezoelectric transducer to provide acoustic energy, a microscope to observe the particle velocity within the droplet, and an ITO (Index Torque Transducer) interdigitated electrode to control the contact angle of the immobilized microdroplet. By changing the ITO control voltage, the droplet is positioned at different contact angles, and the acoustic flux intensity at these different contact angles is quantified. The detailed process is as follows:

[0098] ① Keep the droplet contact angle constant, and calculate the acoustic flow intensity in the fixed microdroplet at this time by measuring the droplet vibration amplitude, particle running speed and other information.

[0099] ② Change the excitation voltage to change the droplet contact angle, and then calculate the acoustic flow intensity in the fixed microdroplet at this time.

[0100] ③ By continuously changing the excitation voltage, the acoustic flow intensity at different droplet contact angles can be obtained.

[0101] This invention establishes for the first time a quantitative mapping relationship between acoustic flow intensity and droplet geometric parameters (contact angle) in immobilized microdroplets. Existing direct measurement methods such as particle image velocimetry (PIV) and laser Doppler velocimetry (LDV) can only provide transient or time-averaged spatial distribution information of acoustic flow velocity, and have not yet established a quantitative relationship between acoustic flow intensity and geometric parameters such as droplet contact angle and contact line diameter. Through step three, by continuously changing the excitation voltage to adjust the droplet contact angle, and using the acoustic flow suppression coefficient quantification method in step one, a quantitative mapping curve of "contact angle-acoustic flow intensity" is systematically established. This transforms the search for the optimal acoustic flow state from empirical trial-and-error to precise control based on quantitative evidence.

[0102] As a specific example, the collaborative control program in step four is a Python program;

[0103] The real-time monitoring includes: acquiring the vibration amplitude of the top of the fixed microdroplet using a laser Doppler vibrometer, acquiring a side view image of the fixed microdroplet using a microscope to calculate the contact angle, and tracking the particle displacement to obtain the particle velocity.

[0104] The real-time adjustment of the applied voltage includes: when the calculated acoustic flow suppression coefficient is obtained... When the target range is deviated from the preset target range, the target contact angle is found according to the quantitative mapping relationship between the contact angle and the acoustic flow intensity established in step three, and the required voltage change is calculated, thereby controlling the applied voltage to change the current contact angle.

[0105] Furthermore, Python code was used to collaboratively analyze the microscope camera and LDV measurement results, control the ITO voltage control source to set an appropriate droplet contact angle, and adjust it in real time, thereby achieving dynamic maintenance of the strongest acoustic flow state. The process is as follows:

[0106] ①System calibration and parameter setting

[0107] The droplet contact angle versus acoustic flow intensity curve obtained in step three is stored in a lookup table in a Python program for real-time lookup of the optimal voltage.

[0108] Set the target range for sound flow intensity If the voltage exceeds this range, voltage adjustment will be triggered.

[0109] Set the contact angle variation step size (e.g., each time) This avoids droplet instability caused by mutations.

[0110] ② Real-time monitoring and signal acquisition

[0111] LDV signal acquisition: every (e.g., 1 second) Collect the amplitude of the droplet top vibration once. Sound energy density was calculated using a non-perturbation amplitude calculation method. And calculate the second-order steady-state acoustic velocity. .

[0112] Microscope image acquisition: Simultaneously acquire side view images of the droplet, and calculate the contact angle using an edge detection algorithm. .

[0113] By tracking the particle displacement, the particle velocity can be obtained. And convert the acoustic flow suppression coefficient. .

[0114] ③ Feedback control algorithm

[0115] Determine the current state, if This indicates that the sound flow is too weak and the sound flow intensity needs to be increased. If This indicates that the acoustic flow is too strong, which may cause droplet instability and should be appropriately reduced. Based on the current... The contact angle-acoustic flow intensity mapping curve can be used to find the solution. Contact angle reaching the target range .according to and current Calculate the required voltage change. Send a command to the Picoscope to output the adjusted voltage, thereby changing the contact angle. Wait for a period of time (e.g., 2-3 seconds) to allow the droplet shape and sound field to stabilize again, and then proceed to the next round of monitoring.

[0116] ④ Dynamic maintenance

[0117] When the droplet shrinks in volume and changes its contact angle due to evaporation, the system automatically detects and recalculates the optimal voltage to maintain the strongest acoustic flow state. If slippage of the droplet contact line is detected (contact angle exceeds the retreat or advance angle range), the system stops voltage adjustment and issues an alarm to prevent droplet breakage or overflow.

[0118] This invention employs a real-time feedback-coordinated control mechanism based on "droplet shape, resonant frequency, and acoustic flow intensity" to dynamically maintain the strongest acoustic flow state. In existing biological applications, droplet evaporation causes changes in volume and contact angle over time, thereby altering the acoustic resonant frequency and making it difficult to sustain the strongest acoustic flow state with fixed-frequency excitation. This invention uses a Python-based collaborative control program to collect vibration amplitude data from a laser Doppler vibrometer (LDV) and particle velocity data from a microscope in real time, calculates the current acoustic flow suppression coefficient SqSq, compares it with a preset target range, and dynamically adjusts the applied voltage to change the contact angle, ensuring that the acoustic flow intensity is always maintained at its strongest state. Simultaneously, the system can detect contact line slippage and trigger an alarm to prevent droplet breakage.

[0119] This invention also provides a detection system for the strongest Rayleigh acoustic current in immobilized microdroplets, used to implement a method for detecting the strongest Rayleigh acoustic current in the immobilized microdroplets, the system comprising:

[0120] Indium tin oxide transparent interdigitated electrode substrate is used to support immobilized microdroplets and actively control the contact angle of the immobilized microdroplets by applying voltage to the substrate;

[0121] Lead zirconate titanate piezoelectric transducers are used to provide sound source energy to excite acoustic streams.

[0122] Laser Doppler vibration meter is used to measure the vibration amplitude of fixed microdroplets;

[0123] Microscopes are used to observe the velocity of particles in fixed microdroplets to obtain second-order steady-state acoustic flow rates. ;

[0124] A collaborative control module is connected to the indium tin oxide transparent interdigitated electrode substrate, the laser Doppler vibrometer, and the microscope, respectively. The collaborative control module receives vibration amplitude data measured by the laser Doppler vibrometer and particle velocity data measured by the microscope, calculates the real-time acoustic flow intensity in the fixed microdroplets, dynamically calculates the required voltage adjustment based on the comparison between the real-time acoustic flow intensity and the preset strongest acoustic flow state, and outputs a control voltage to the indium tin oxide transparent interdigitated electrode substrate to adjust the contact angle of the fixed microdroplets, thereby maintaining the strongest acoustic flow state.

[0125] This invention exhibits excellent biocompatibility and insensitivity to fluid properties in complex biological fluids. Some acoustic flow driving methods (such as bulk acoustic waves and surface acoustic waves) are sensitive to fluid viscosity and ionic strength, and their performance deteriorates in complex biological fluids such as blood and plasma. The Rayleigh acoustic flow method of this invention demonstrates excellent biocompatibility and insensitivity to fluid composition and viscosity in complex biological fluids such as blood, plasma, serum, saliva, and urine, enabling its direct application in practical biological detection scenarios without the need for complex sample pretreatment.

[0126] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for detecting the strongest Rayleigh acoustic flux in immobilized microdroplets, characterized in that, Includes the following steps: Step 1: Quantitatively measure and calculate the acoustic flow in the immobilized microdroplets using experimental methods, including: measuring the second-order steady-state acoustic velocity using cell tracing methods. The vibration amplitude of the fixed microdroplets was measured using a laser Doppler vibrometer, and the vibration amplitude was then substituted into a multiphysics simulation to obtain the acoustic energy density through numerical calculation. Furthermore, based on the acoustic energy density Calculate the acoustic velocity According to the second-order steady-state acoustic velocity and the acoustic velocity Calculate the acoustic flow suppression coefficient ; Step 2: Actively control the contact angle of droplets by combining electrical control methods, including: fabricating interdigital electrodes on a transparent electrode substrate and coating them with dielectric and hydrophobic layers in sequence; changing the interfacial tension between the immobilized microdroplets and the solid surface by applying an external voltage, thereby actively controlling the contact angle of the immobilized microdroplets. Step 3: Investigate the relationship between the contact angle of the immobilized microdroplet and the acoustic flow intensity in the immobilized microdroplet, including: changing the excitation voltage to set the immobilized microdroplet at different contact angles, and repeating Step 1 at each contact angle to quantify the corresponding acoustic flow intensity, thereby establishing a quantitative mapping relationship between the contact angle and the acoustic flow intensity. Step 4: Achieve coordinated control of droplet contact angle and acoustic flow intensity in droplet to dynamically maintain the strongest acoustic flow state. This includes: monitoring the vibration amplitude, particle speed and contact angle of the fixed microdroplet in real time through a coordinated control program, and adjusting the applied voltage in real time according to the quantitative mapping relationship established in Step 3, so that the acoustic flow intensity is dynamically maintained at the preset strongest state.

2. The method for detecting the strongest Rayleigh acoustic flux in immobilized microdroplets according to claim 1, characterized in that, In step one, the acoustic flow suppression coefficient Calculated using the following formula: （1） in, The acoustic flow suppression coefficient is... As a regulating factor, For acoustic velocity, For second-order steady-state acoustic velocity, The volume of the immobilized microdroplets; For the integration region, For volume integral variables; As a volumetric infinitesimal element, it is used in spatial regions Earn points; It is a step function.

3. The method for detecting the strongest Rayleigh acoustic flux in immobilized microdroplets according to claim 2, characterized in that, In step one, the acoustic velocity Calculated using the following formula: （2） in, The average acoustic energy density in the fluid, or simply acoustic energy density; For the density of the fluid, The speed at which sound waves propagate in a fluid.

4. The method for detecting the strongest Rayleigh acoustic current in immobilized microdroplets according to claim 3, characterized in that, In step one, the acoustic energy density Calculated using the following formula: （3） in, For first-order sound pressure, It is the first-order speed of sound.

5. The method for detecting the strongest Rayleigh acoustic current in immobilized microdroplets according to claim 4, characterized in that, In step one, when measuring the vibration amplitude of the fixed microdroplets using a laser Doppler vibrometer, the voltage signal output by the photodetector of the laser Doppler vibrometer... Satisfy the following formula: （4） in, Let be the impedance of the photodetector. The amplitude of the current density at the photodetector. The heterodyne frequency shift between the reference beam and the measurement beam, For time, Wavelength, To fix the mechanical vibration amplitude on the surface of the microdroplets, To determine the migration frequency of the immobilized microdroplet surface, For the initial phase, For the fixed phase of the reference beam, To measure the fixed phase of the beam, The imaginary unit, This indicates taking the real part.

6. The method for detecting the strongest Rayleigh acoustic current in immobilized microdroplets according to claim 5, characterized in that, When the mechanical vibration amplitude of the surface of the attached microdroplets For values ​​greater than 100 nm, the mechanical vibration amplitude is calculated using a non-perturbation method. The non-perturbation method is based on Jacobi-Anger expansion according to formula (4): （5） in, for The first-order Bessel equation, where n is an integer; By measuring the amplitude ratio between each harmonic, and substituting it into formula (5), the mechanical vibration amplitude of the surface of the fixed microdroplet can be solved. .

7. The method for detecting the strongest Rayleigh acoustic current in immobilized microdroplets according to claim 1, characterized in that, In step two: The interdigitated electrode is an indium tin oxide transparent interdigitated electrode; The dielectric layer is a chloroethyl pullulan dielectric layer; The hydrophobic layer is a Teflon hydrophobic layer; The active control of the contact angle follows the Lippmann-Young equation, which states that the contact angle decreases as the applied voltage increases.

8. The method for detecting the strongest Rayleigh acoustic flux in immobilized microdroplets according to claim 1, characterized in that, The collaborative control program in step four is a Python program; The real-time monitoring includes: acquiring the vibration amplitude of the top of the fixed microdroplet using a laser Doppler vibrometer, acquiring a side view image of the fixed microdroplet using a microscope to calculate the contact angle, and tracking the particle displacement to obtain the particle velocity. The real-time adjustment of the applied voltage includes: when the calculated acoustic flow suppression coefficient is obtained... When the target range is deviated from the preset target range, the target contact angle is found according to the quantitative mapping relationship between the contact angle and the acoustic flow intensity established in step three, and the required voltage change is calculated, thereby controlling the applied voltage to change the current contact angle.

9. The method for detecting the strongest Rayleigh acoustic current in immobilized microdroplets according to claim 1, characterized in that, Step four also includes: real-time detection of whether the contact line of the fixed microdroplet has slipped. When the contact angle is detected to exceed the range of the retreat angle or the advance angle, it is determined that the contact line has slipped. At this time, the system stops adjusting the voltage and issues an alarm to prevent the fixed microdroplet from breaking or overflowing.

10. A detection system for the strongest Rayleigh acoustic flux in immobilized microdroplets, characterized in that, A method for detecting the strongest Rayleigh acoustic flux in immobilized microdroplets according to any one of claims 1 to 9, the system comprising: Indium tin oxide transparent interdigitated electrode substrate is used to support immobilized microdroplets and actively control the contact angle of the immobilized microdroplets by applying voltage to the substrate; Lead zirconate titanate piezoelectric transducers are used to provide sound source energy to excite acoustic streams. Laser Doppler vibration meter is used to measure the vibration amplitude of fixed microdroplets; Microscopes are used to observe the velocity of particles in fixed microdroplets to obtain second-order steady-state acoustic flow rates. ; A collaborative control module is connected to the indium tin oxide transparent interdigitated electrode substrate, the laser Doppler vibrometer, and the microscope, respectively. The collaborative control module receives vibration amplitude data measured by the laser Doppler vibrometer and particle velocity data measured by the microscope, calculates the real-time acoustic flow intensity in the fixed microdroplets, dynamically calculates the required voltage adjustment based on the comparison between the real-time acoustic flow intensity and the preset strongest acoustic flow state, and outputs a control voltage to the indium tin oxide transparent interdigitated electrode substrate to adjust the contact angle of the fixed microdroplets, thereby maintaining the strongest acoustic flow state.

Images