Device stress isolation system and method

Abstract

The invention discloses a device stress isolation system and method, and relates to the technical field of stress isolation, and the method comprises the steps: preparing a magnetic topological insulator film on the surface of a device, forming a heterojunction structure through deposition and annealing treatment, verifying the conversion efficiency of converting mechanical stress into spin waves, and outputting the energy flux density distribution of the spin waves; a magnetic topological insulator film and a space-time coding metamaterial layer are integrated, a sensor array is deployed to monitor a magnetic field and temperature in real time, a spin wave path and coding parameters are controlled and adjusted through cooperation of multiple physical fields, and dynamic traveling wave stiffness field distribution is output; and dynamically matching the propagation characteristics of the spin wave and the traveling wave stiffness field through iterative updating of an optimization algorithm, outputting optimized dynamic traveling wave stiffness field calibration parameters, carrying out full-condition vibration testing, and verifying the isolation performance. According to the invention, through a multi-physical field cooperative control and dynamic optimization mechanism, full-link performance improvement of device stress isolation is satisfied.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of stress isolation, in particular to a device stress isolation system and method. BACKGROUND

[0002] In recent years, the integration of spintronics and metamaterial technology has provided a new approach to mechanical stress isolation. Magnetic topological insulators can efficiently convert mechanical stress into spin wave energy due to their topologically protected surface states; and time-space coding metamaterials can achieve dynamic stress cancellation by actively adjusting the propagating field through a piezoelectric array. In the prior art, passive vibration isolation schemes based on piezoelectric materials are limited by narrow frequency bands and low energy density, while spin wave control technology has high energy leakage rates at high frequencies due to the lack of dynamic path matching mechanisms.

[0003] Traditional methods rely on static heterojunctions and cannot adapt to the dynamic changes of vibration frequency spectrum in real time, resulting in a mismatch between the propagation characteristics of spin waves and propagating fields, especially under wideband random vibration, which significantly degrades the isolation performance. Single physical field control ignores the thermal-magnetic coupling effect, which exacerbates the scattering loss of spin waves in lattice defects, limiting their application in precision instruments. SUMMARY

[0004] In view of the above existing problems, the present application is proposed.

[0005] Therefore, the present application provides a device stress isolation method to solve the problem of low stress isolation efficiency caused by the insufficient dynamic matching precision of magnetic topological insulators and metamaterials under high-frequency vibration.

[0006] To solve the above technical problems, the present application provides the following technical solutions:

[0007] In a first aspect, the present application provides a device stress isolation method, which comprises preparing a magnetic topological insulator thin film on the surface of a device, forming a heterojunction structure through deposition and annealing treatment, verifying the conversion efficiency of mechanical stress into spin waves, and outputting the spin wave energy flow density distribution.

[0008] Laying a time-space coding metamaterial layer in the device dissipation zone, generating a propagating field that matches the spin wave propagation direction through a piezoelectric array, and outputting a set of coding instructions;

[0009] Integrating the magnetic topological insulator thin film with the time-space coding metamaterial layer, deploying a sensor array to monitor the magnetic field and temperature in real time, adjusting the spin wave path and coding parameters through multi-physical field collaborative control, and outputting a dynamic propagating field stiffness distribution;

[0010] Iteratively updating through an optimization algorithm to dynamically match the propagation characteristics of spin waves and propagating field stiffness, outputting optimized dynamic propagating field calibration parameters, performing full-condition vibration testing and verifying the isolation performance.

[0011] As a preferred embodiment of the device stress isolation method of the present invention, the steps of preparing a magnetic topological insulator thin film on the device surface, forming a heterojunction structure through deposition and annealing, verifying the conversion efficiency of mechanical stress into spin waves, and outputting the spin wave energy flux density distribution are as follows:

[0012] A heterojunction structure is formed on the surface of a magnetic topological insulator film through a dynamic stress-tuned deposition process, and the stress distribution is monitored in real time.

[0013] The film is subjected to nonlinear field coupling annealing treatment, combined with an alternating magnetic field to optimize lattice defect repair;

[0014] Apply local pressure through a scanning probe to measure the spin wave energy flux density;

[0015] A frequency domain weighted function is constructed according to the spin wave energy flux density, and the frequency domain weighted function is combined with the multi-physics field coupling model to output the spin wave energy flux density distribution.

[0016] As a preferred solution of the device stress isolation method of the present invention, wherein: a spatiotemporal coding metamaterial layer is laid in the dissipative region of the device, a traveling wave stiffness field matching the propagation direction of the spin wave is generated by a piezoelectric array, and a coding instruction set is output. The specific steps are as follows:

[0017] Real-time monitoring of spin wave propagation parameters, calculation of dynamic phase gradient fields, construction of deep reinforcement learning models, and optimization of piezoelectric array driving parameters;

[0018] The spin wave propagation parameters include wave vector, frequency, phase gradient, group velocity and energy flux density, and the piezoelectric array driving parameters include driving voltage, driving frequency, phase delay and spatial distribution pattern;

[0019] According to the optimized piezoelectric array driving parameters, a nonlinear interference traveling wave stiffness field is generated, sparse coding compression is performed, and a coding instruction set is output.

[0020] As a preferred solution of the device stress isolation method of the present invention, wherein: the magnetic topological insulator film is integrated with the spatiotemporal coding metamaterial layer, and a sensor array is deployed to monitor the magnetic field and temperature in real time. The specific steps are as follows:

[0021] interfacially bonding the magnetic topological insulator film and the spatiotemporal encoding metamaterial layer to form a composite structure;

[0022] Deploy a Hall sensor array on the surface of the composite structure to monitor the magnetic field strength and calculate the magnetic field gradient in real time;

[0023] A thermocouple array is deployed on the surface of the composite structure to monitor the temperature distribution and calculate the temperature gradient in real time.

[0024] As a preferred scheme of the device stress isolation method, the method comprises the following steps of:

[0025] The magnetic field gradient and the temperature gradient are input into the multi-physical field cooperative control to analyze the spin wave path offset and the coding parameter deviation.

[0026] The driving voltage phase and frequency of the space-time coding metamaterial layer are dynamically adjusted to output the dynamic traveling wave stiffness field distribution.

[0027] The coding parameters include spin wave phase, spin wave frequency, driving frequency, driving voltage amplitude, nonlinear enhancement index and spatial attenuation coefficient.

[0028] As a preferred scheme of the device stress isolation method, the method comprises the following steps of:

[0029] The spin wave energy flow density distribution and the dynamic traveling wave stiffness field distribution are iteratively updated by the optimization algorithm to generate an adjustment instruction set.

[0030] The driving voltage amplitude, phase and frequency of the piezoelectric array are dynamically updated according to the adjustment instruction.

[0031] The propagation direction matching degree of the updated traveling wave stiffness field and the spin wave energy flow density is verified by the laser interferometer to output the dynamic traveling wave stiffness field calibration parameter.

[0032] A multi-axis vibration excitation source is deployed on the surface of the device to load full-condition vibration spectrum parameters, and the piezoelectric array generates an anti-phase traveling wave stiffness field matched with the vibration spectrum to apply dynamic stress isolation.

[0033] As a preferred scheme of the device stress isolation method, the vibration spectrum parameters include frequency range, vibration intensity, phase information, direction component and time modulation characteristics.

[0034] In a second aspect, the application provides a device stress isolation system, comprising a magnetic film preparation module, a metamaterial coding module, a multi-field coupling module and a calibration verification module.

[0035] The magnetic film preparation module prepares a magnetic topological insulator film on the surface of the device, forms a heterojunction structure through deposition and annealing treatment, verifies the conversion efficiency of mechanical stress into spin waves, and outputs the spin wave energy flow density distribution.

[0036] The metamaterial encoding module is used to lay a spatiotemporal encoding metamaterial layer in the device dissipative region, generate a traveling wave stiffness field that matches the propagation direction of the spin wave through a piezoelectric array, and output a coding instruction set;

[0037] The multi-field coupling module is used to integrate the magnetic topological insulator film with the spatiotemporal coding metamaterial layer, deploy a sensor array to monitor the magnetic field and temperature in real time, adjust the spin wave path and coding parameters through multi-physics field collaborative control, and output a dynamic traveling wave stiffness field distribution;

[0038] The calibration verification module is used to iteratively update the optimization algorithm, dynamically match the propagation characteristics of the spin wave and the traveling wave stiffness field, output the optimized dynamic traveling wave stiffness field calibration parameters, perform full-condition vibration testing and verify the isolation performance.

[0039] In a third aspect, the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, any step of the device stress isolation method described in the first aspect of the present invention is implemented.

[0040] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, any step of the device stress isolation method described in the first aspect of the present invention is implemented.

[0041] The beneficial effects of the present invention are: through the collaborative control and dynamic optimization mechanism of multiple physical fields, the full-link performance improvement of device stress isolation is met. Through dynamic stress tuning deposition and non-equilibrium annealing process, the lattice matching and spin-orbit coupling characteristics of the heterojunction are optimized, the directional conversion efficiency of mechanical stress to spin wave energy is improved, and the energy capture capability of the high-frequency stress segment is enhanced by using the frequency domain weighted function to ensure the efficient conversion and transmission of broadband stress waves. The space-time coding metamaterial layer is combined with a deep reinforcement learning model to analyze the propagation characteristics of spin waves in real time and dynamically optimize the piezoelectric drive parameters to generate a traveling wave stiffness field with nonlinear interference effect, accurately match the spin wave group velocity and phase gradient, and realize the directional dissipation of stress energy and far-field leakage suppression. The spin wave path offset and the traveling wave field distribution characteristics are monitored in real time, and the driving voltage phase and frequency are dynamically adjusted to ensure the stability of the isolation performance under complex working conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0043] Fig. 1 System architecture diagram for the device stress isolation method of Example 1.

[0044] Fig. 2 Flowchart for the magnetic topological heterojunction preparation of Example 1.

[0045] Fig. 3 Flowchart for the coordinated control of the traveling wave stiffness field dynamic matching of Example 1.

[0046] Fig. 4 Flowchart for the full-spectrum isolation verification of Example 1. DETAILED DESCRIPTION

[0047] In order to make the above objectives, characteristics and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0048] In the following description, a large number of specific details are set forth in order to facilitate a thorough understanding of the present application, but the present application can also be implemented in other ways different from those described herein, and those skilled in the art can make similar generalizations without departing from the spirit of the present application, therefore the present application is not limited to the specific embodiments disclosed below.

[0049] Secondly, the "one embodiment" or "embodiment" referred to herein can include specific features, structures or characteristics included in at least one implementation of the present application. "In one embodiment" appearing in different places in the specification does not mean the same embodiment, nor is it an embodiment that is separate or alternative to other embodiments.

[0050] Example 1, with reference to Figs. 1-4 , the first embodiment of the present application provides a device stress isolation method, comprising the following steps:

[0051] S1, a magnetic topological insulator film is prepared on the surface of the device, a heterojunction structure is formed by deposition and annealing treatment, the conversion efficiency of mechanical stress into spin wave is verified, and the output spin wave energy flow density distribution is verified.

[0052] Furthermore, a heterojunction structure is formed on the surface of the magnetic topological insulator film by a dynamic stress tuning deposition process, and the stress distribution is monitored in real time;

[0053] Specifically, when forming a heterojunction structure on the surface of a magnetic topological insulator film through a dynamic stress-tuned deposition process, molecular beam epitaxy is used to alternately deposit topological insulator and ferromagnetic material layers, and a dynamic mechanical stress field is simultaneously applied during the deposition process. The dynamic mechanical stress field periodically controls the deformation of the substrate through a piezoelectric actuator, inducing the orderly reconstruction of the film lattice along a specific direction, forming an atomically smooth heterojunction interface. Real-time monitoring is achieved through the collaboration of a laser interferometer and a scanning probe microscope. The laser interferometer non-contactly measures the displacement field on the film surface and inverts the global stress distribution. The scanning probe uses nanoindentation technology to locally quantify the stress gradient, which is fed back to the deposition control in real time to dynamically adjust the stress loading frequency and deposition rate.

[0054] Dynamically adjust the deposition rate and substrate temperature, the expression is:

[0055] ;

[0056] Where, Expressed as the dynamically adjusted deposition rate, is the initial deposition rate, represents the gradient operator, Expressed as the two-dimensional stress distribution coordinates on the film surface, Expressed as a stress gradient field, Expressed as the film surface integral area, Expressed as the temperature coupling coefficient, , is the base temperature, Expressed as the stress diffusion constant, , Expressed as a natural exponential function, Expressed as a pair Double integral of a region, represents the horizontal space coordinate, represents the vertical space coordinate, represents the area differential element.

[0057] It should be noted that the temperature coupling coefficient is obtained by fixing the deposition rate in molecular beam epitaxy, changing the substrate temperature (300K-600K), measuring the film stress distribution by laser interferometer, and using finite element simulation to invert the relationship curve between the stress gradient integral and the substrate temperature, and then extracting it through nonlinear regression.

[0058] The film is subjected to nonlinear field coupling annealing treatment, combined with an alternating magnetic field to optimize lattice defect repair;

[0059] Specifically, in the nonlinear field coupled annealing treatment of the thin film, the directional repair of lattice defects is achieved by synchronously applying an alternating magnetic field and a gradient temperature field.

[0060] During the annealing process, the alternating magnetic field dynamically modulates the magnetic anisotropy of the material at a specific frequency, prompting the movement of magnetic domain walls and dragging the reordering of the lattice distortion region; at the same time, the gradient temperature field forms a non-uniform thermal stress distribution along the surface of the film, which, after coupling with the alternating magnetic field, produces a synergistic effect to drive dislocation slip and fill vacancy defects.

[0061] By real-time monitoring of the lattice reconstruction process with a scanning probe, the frequency of the magnetic field and the direction of the temperature gradient are dynamically adjusted to adapt the annealing path to the local defect density difference, ultimately realizing the step-by-step relaxation of lattice distortion and atomic-level bonding repair of the interface, and improving the topological protection characteristics and stress bearing capacity of the film.

[0062] The annealing time is coupled, and the expression is:

[0063]

[0064] In the formula, represents the annealing time, represents the frequency of the alternating magnetic field, represents the temperature response factor, represents the annealing termination temperature, represents the annealing starting temperature, represents the temperature difference, represents the magnetic field-defect density coefficient, , represents the time-varying magnetic field strength, represents the current time.

[0065] It should be noted that the magnetic field-defect density coefficient is obtained by linear regression fitting based on the relationship between the defect density change rate and the magnetic field energy by counting the dislocation density after annealing under different peak magnetic field strengths at the same temperature.

[0066] The spin wave energy flow density is measured by applying local pressure with a scanning probe;

[0067] Specifically, on the surface of the magnetic topological insulator film, a nanoindentation probe of a scanning probe microscope is used to apply local pressure, and the probe tip is used to perform micro-mechanical loading on the film surface to excite the non-equilibrium state propagation of spin waves. While the probe applies pressure, the phase and amplitude distribution of the spin waves are detected in real time by a magnetic force microscope mode, and the spatial gradient of the energy flow density is analyzed by combining phase-sensitive detection technology.

[0068] By synchronously collecting the mechanical loading signal and the magnetic response signal of the probe, a mapping relationship between local stress and spin wave energy flow is established, the energy transmission efficiency under different pressures is quantified, and finally the conversion efficiency of mechanical stress into spin waves is verified.

[0069] The stress-spin wave conversion efficiency is expressed as: ​

[0070] ;

[0071] Where, represents the stress-spin wave conversion efficiency, represents the spin wave energy flux density distribution, represents the effective stress acting area on the device surface, Expressed as The weight coefficient of each stress sensor, , Expressed as The real-time stress time domain signal measured by a stress sensor, represents the time decay factor, Indicates the total time the pressure is applied, Expressed as pressure applied, Represented as stress sensor index, Express The measured values ​​of the stress sensors are weighted summed. Expressed as the total number of stress sensors, Indicates the effective stress area on the device surface Perform double integral on , Indicated as in the area Upper horizontal space coordinate and vertical spatial coordinates Integrate in the direction, Expressed as a time differential element, Expressed as a natural constant.

[0072] It should be noted that the weight coefficient of the stress sensor is calculated by deploying piezoresistive stress sensors on the surface of the device, using a spiral fractal topology to cover the high stress gradient area, and simulating the stress distribution under different working conditions through COMSOL to calculate the weight coefficient of each stress sensor.

[0073] A frequency domain weighted function is constructed according to the spin wave energy flux density, and the frequency domain weighted function is combined with the multi-physics field coupling model to output the spin wave energy flux density distribution.

[0074] Specifically, in magnetic topological insulator films, based on the spatial distribution of spin wave energy flux density obtained by the scanning probe, the energy proportion characteristics of different frequency bands are extracted through frequency domain analysis, and a frequency domain weighted function with high-frequency stress capture as the core is constructed.

[0075] The frequency-domain weighting function uses bandpass filtering and gain adjustment to enhance the energy weight of high-frequency bands (e.g., 1-10kHz) while suppressing low-frequency noise interference. Embedding the frequency-domain weighting function into a multi-physics coupling model coordinates the magnetic field gradient and temperature field distribution to control the phase matching relationship between the spin wave group velocity and the traveling wave stiffness field.

[0076] a frequency domain weighting optimization function expressed as:

[0077]

[0078] wherein, represents a frequency domain weighting function, represents a Sigmoid function steepness coefficient, , represents a cutoff frequency, , represents a sinc function bandwidth adjustment coefficient, , represents a center frequency, represents a frequency component of a stress wave, represents a normalized sinc function, represents a maximum value.

[0079] It should be noted that the Sigmoid function steepness coefficient is optimized by matching the energy gradient of the frequency band, and is obtained by adapting the high-frequency stress energy attenuation slope; the sinc function bandwidth adjustment coefficient is optimized by sidelobe suppression and calibrated by the center frequency.

[0080] Preferably, high-quality interface preparation of magnetic topological insulator heterojunction is realized by dynamically stress-tuned deposition process, which reduces the interface defect density and improves the lattice matching degree; combined with nonlinear annealing treatment of alternating magnetic field and gradient temperature field, the lattice distortion is precisely repaired, and the topological protection characteristics and spin wave transmission efficiency of the thin film are enhanced; based on local pressure loading and multi-modal detection of scanning probe, nanoscale spatial analysis of spin wave energy flow density is realized, providing high-precision data support for frequency energy distribution; through the collaborative optimization of frequency domain weighting function and multi-physical field coupling model, high-frequency stress energy is guided along the low-loss path, ensuring the stability and reliability of the isolation performance under complex working conditions.

[0081] S2, lay a space-time encoding metamaterial layer when the device dissipates, generate a traveling wave stiffness field matched with the spin wave propagation direction through a piezoelectric array, and output an encoding instruction set.

[0082] Further, real-time monitoring of spin wave propagation parameters, calculation of dynamic phase gradient field, construction of deep reinforcement learning model, optimization of piezoelectric array driving parameters;

[0083] Specifically, on the surface of the magnetic topological insulator thin film, the wave vector, frequency and phase gradient distribution of the spin wave are captured in real time through the magneto-optical Kerr effect, and the dynamic propagation characteristics thereof are analyzed using phase-sensitive detection technology; based on the spatiotemporal evolution of the spin wave group velocity and the phase gradient, the global dynamic phase gradient field is calculated, and the deflection trend of the energy transmission path is quantified. ​

[0084] The spin wave propagation parameters are input into the deep reinforcement learning model, the driving voltage amplitude, phase delay and spatial activation mode of the piezoelectric array are generated through the policy network, the deep reinforcement learning model outputs instructions to real-time control the deformation of the piezoelectric unit, and generates a traveling wave stiffness field accurately matched with the spin wave propagation direction.

[0085] A high-precision magneto-optical sensor array is deployed on the surface of the magnetic topological insulator film, the spin wave wave vector and frequency are collected in real time, and the dynamic phase gradient field is calculated, and the expression is:

[0086] ;

[0087] In the formula, is the phase of the spin wave, is the reduced Planck constant, is the wave vector of the spin wave, is the differential time variable, is the integral time variable, is the partial derivative, is the rate of change of the wave vector with time, is the group velocity of the spin wave, is the frequency diffusion coefficient, , is the frequency of the spin wave, is the second-order derivative of the frequency with respect to the transverse spatial coordinate , is the integral of the function with respect to time from 0 to .

[0088] A deep reinforcement learning model is constructed to optimize the driving parameters of the piezoelectric array, and the expression is:

[0089] ;

[0090] In the formula, is the driving voltage of the th piezoelectric unit, is the index of the piezoelectric unit, is the deep reinforcement learning model, is the transverse spatial coordinate of the th piezoelectric unit, is the integral operation of the function within the time interval , is the time window length, is the driving voltage of the th piezoelectric unit at time , is the phase of the spin wave For horizontal space coordinates and time The mixed second-order partial derivatives of .

[0091] Spin wave propagation parameters include wave vector, frequency, phase gradient, group velocity and energy flux density, and piezoelectric array driving parameters include driving voltage, driving frequency, phase delay and spatial distribution pattern;

[0092] It should be noted that the wave vector refers to the interference direction of the traveling wave stiffness field, which ensures that the piezoelectric drive phase matches the spin wave propagation path.

[0093] Frequency refers to the benchmark for determining the piezoelectric drive frequency to avoid energy reflection caused by frequency mismatch.

[0094] Phase gradient refers to the dynamic adjustment of the phase delay distribution of the traveling wave field to suppress interference failure caused by path deviation.

[0095] Group velocity refers to the propagation rate of the traveling wave field, which ensures synchronous energy transmission and reduces dynamic mismatch loss.

[0096] The energy flux density is a measure of the stress-spin wave conversion efficiency, which drives the amplitude modulation of the piezoelectric array.

[0097] The driving voltage is used to adjust the local amplitude of the traveling wave stiffness field and enhance the energy dissipation in the target area.

[0098] The driving frequency is to ensure the time domain synchronization between the traveling wave field and the spin wave, and to avoid the energy retention caused by the formation of standing waves.

[0099] Phase delay refers to controlling the propagation direction of the traveling wave field and guiding the spin wave to transmit along a preset path.

[0100] The spatial distribution pattern refers to the suppression of energy leakage in non-target directions by selectively activating units and matching the topological structure of the spin wave path.

[0101] According to the optimized piezoelectric array driving parameters, a nonlinear interference traveling wave stiffness field is generated, sparse coding compression is performed, and a coding instruction set is output.

[0102] Specifically, in the device integrating magnetic topological insulators and space-time encoding metamaterials, the optimized piezoelectric driving parameters are synchronously loaded into the piezoelectric array through a multi-channel signal generator, driving each unit to produce periodic deformation according to the preset phase delay and spatial distribution pattern, forming a traveling wave stiffness field with nonlinear interference effect.

[0103] The traveling wave stiffness field is constructed through the cooperative deformation superposition of piezoelectric units to spatially construct a stiffness gradient distribution that matches the spin wave propagation path, and the interference enhancement effect is used to enhance the energy transmission in the target direction, while the cubic attenuation characteristics are used to suppress energy leakage in the non-target direction.

[0104] The spatiotemporal distribution of the traveling wave stiffness field is subjected to wavelet transformation and screening to extract key frequency bands and spatial domain features, and a low-dimensional sparse coding instruction set is generated after removing redundant information.

[0105] According to the piezoelectric array driving parameters optimized by the deep reinforcement learning model, the traveling wave stiffness field parameters are generated through the inverse effect of piezoelectric ceramics. The expression is:

[0106] ;

[0107] Where, Expressed as the traveling wave stiffness field in the transverse space coordinate and time The amplitude of Expressed as the reference amplitude of the traveling wave stiffness field, Express The contribution of each piezoelectric unit is summed up, Expressed as the piezoelectric traveling wave number, represents the piezoelectric traveling wave, Expressed as the piezoelectric traveling wave angular frequency, Expressed as The piezoelectric unit is The additional phase of represents the spatial attenuation coefficient, Expressed as horizontal space coordinates With the The spatial coordinates of the piezoelectric unit The Euclidean distance of Expressed as the nonlinear enhancement index, .

[0108] It should be noted that the spatial attenuation coefficient is determined by measuring the spatial distribution of the traveling wave field amplitude using a laser Doppler vibrometer and fitting the attenuation curve: .

[0109] The sparse coding algorithm is used to compress the traveling wave stiffness field parameters in real time to generate a low-bandwidth instruction set, which is expressed as:

[0110] ;

[0111] Where, Represented as a sparsely coded instruction set, represents the sparse coding algorithm, Expressed as the traveling wave stiffness field About time The partial derivative of Expressed as the traveling wave stiffness field The Laplace operator of Expressed as the traveling wave stiffness field In the space area The integral within Represented as a spatial region, represents the differential space variable.

[0112] S3. Integrate the magnetic topological insulator film with the space-time coding metamaterial layer, deploy a sensor array to monitor the magnetic field and temperature in real time, adjust the spin wave path and coding parameters through multi-physics field collaborative control, and output the dynamic traveling wave stiffness field distribution.

[0113] Furthermore, the magnetic topological insulator film is interfacially bonded to the spatiotemporal encoding metamaterial layer to form a composite structure;

[0114] Specifically, during the interface bonding process between the magnetic topological insulator film and the space-time encoding metamaterial layer, a low-temperature van der Waals force bonding process is used to grow an ultra-thin transition layer at the interface between the two through atomic layer deposition (ALD), ensuring interface lattice matching and suppressing performance degradation caused by atomic diffusion.

[0115] The surface of the magnetic topological insulator is plasma activated to expose its topologically protected active sites; then the spatiotemporal encoding metamaterial layer is precisely aligned with the film surface in an inert gas environment, and directional mechanical pressure and an alternating electric field are applied simultaneously to induce interfacial charge rearrangement and van der Waals bond formation.

[0116] After bonding, the interface stress distribution is detected by a scanning probe, and the transition layer thickness and lattice constant are dynamically adjusted to eliminate local distortion and optimize the spin wave transmission channel.

[0117] Deploy a Hall sensor array on the surface of the composite structure to monitor the magnetic field strength and calculate the magnetic field gradient in real time;

[0118] Specifically, on the surface of the composite structure, by arranging the Hall sensor array in a high-density grid, the micro-Hall elements are integrated at the interface area between the magnetic topological insulator and the metamaterial layer at micron-level spacing, capturing the spatial distribution data of the three-dimensional magnetic field intensity in real time.

[0119] Each sensor node synchronously collects the transverse and longitudinal components of the magnetic field intensity within a plane. By performing spatial differential calculations on the data from adjacent nodes, the gradient of the magnetic field intensity along different directions is analyzed. After the collected data is subjected to an adaptive filtering algorithm to remove environmental noise and thermal drift interference, the effective magnetic field gradient characteristics associated with the spin wave propagation path are extracted. This temperature field distribution information is then integrated into the multi-physics control model to generate dynamic correction instructions for the drive parameters.

[0120] Calculate the magnetic field gradient using the expression:

[0121] ;

[0122] Where, Expressed as the magnetic field intensity in the transverse space coordinate and time The distribution of Indicates the magnetic field strength For horizontal space coordinates The partial derivative of Indicates the magnetic field strength For vertical space coordinates The partial derivative of .

[0123] A thermocouple array is deployed on the surface of the composite structure to monitor the temperature distribution and calculate the temperature gradient in real time.

[0124] Specifically, a high-precision array of micro-thermocouples is deployed in a gridded pattern across the surface of the composite structure, covering the interface between the magnetic topological insulator and the metamaterial layer, as well as the dissipation zone. This allows real-time acquisition of both lateral and longitudinal temperature distribution data. Each thermocouple node simultaneously measures the local temperature, and spatial differential calculations between adjacent nodes are used to analyze temperature gradients along different directions. After eliminating ambient thermal noise and device self-heating interference, the effective temperature gradient signature associated with spin wave transmission is extracted.

[0125] Calculate the temperature gradient using the expression:

[0126] ;

[0127] Where, Expressed as temperature in the transverse space coordinate and time The distribution of Expressed as temperature For horizontal space coordinates The partial derivative of Expressed as temperature For vertical space coordinates Partial derivatives.

[0128] The magnetic field gradient and temperature gradient are input into the multi-physics field collaborative control to analyze the spin wave path offset and encoding parameter deviation;

[0129] Specifically, within the composite structure, multi-physics coordinated control is used to spatially and temporally align and fuse the real-time monitored magnetic field gradients and temperature gradients, constructing a correlation map between the spin wave propagation path and the thermal-magnetic coupling field. Based on the topological properties of the spin wave phase being modulated by the magnetic field gradient, and the mechanism by which the temperature gradient-induced lattice thermal expansion affects the group velocity, the offset direction and magnitude of the spin wave path under the current operating conditions are determined, and the dynamic deviation of encoding parameters (such as drive phase and frequency) relative to the target values ​​is quantified.

[0130] During the analysis process, a nonlinear interpolation algorithm is used to compensate for the discrete error of the gradient field caused by the limitation of the sensor's spatial resolution. A sliding window of historical data is introduced to predict the path deviation trend and generate a dynamic correction instruction set for the driving parameters.

[0131] By applying local pressure through a scanning probe microscope, the spin wave energy flux density is measured, and the path offset and encoding parameter deviation are calculated. The expression is:

[0132] ;

[0133] Where, Indicates the amount of change, Expressed as the deflection angle of the spin wave propagation path, represents the inverse tangent function, Indicates the horizontal space coordinate and time The spin wave energy flux density, Expressed as the spin wave energy flux density in the longitudinal space coordinate The spatial partial derivatives on , Expressed as the spin wave energy flux density in the transverse space coordinate The spatial partial derivatives on .

[0134] Dynamically adjust the driving voltage phase and frequency of the spatiotemporal encoding metamaterial layer to output a dynamic traveling wave stiffness field distribution;

[0135] Specifically, in the dynamic control of the spatiotemporally encoded metamaterial layer, the driving voltage phase and frequency of each element of the piezoelectric array are adjusted in real time via a multi-channel signal generator based on the path offset and parameter deviation analyzed by multi-physics field collaborative control. The phase delay is dynamically corrected according to the offset in the propagation direction of the spin wave, ensuring synchronization between the traveling wavefront and the spin wave phase gradient. The driving frequency is adaptively matched to the group velocity changes caused by the temperature gradient to compensate for the time domain mismatch caused by thermal stress. The driving voltage is compressed through sparse coding and then applied to the piezoelectric elements. Through the coordinated deformation and interference effects between the elements, a dynamic traveling wave stiffness field distribution with nonlinear attenuation characteristics is generated in space.

[0136] The encoding parameters include spin wave phase, spin wave frequency, driving frequency, driving voltage amplitude, nonlinear enhancement index and spatial attenuation coefficient.

[0137] It should be noted that spin wave phase refers to suppressing reflected waves and enhancing constructive interference in the target path by adjusting the phase matching degree (such as advance or lag), thereby optimizing the direction of energy transmission.

[0138] The spin wave frequency refers to the benchmark for determining the driving frequency of the traveling wave field, avoiding energy reflection or standing wave formation caused by frequency mismatch.

[0139] The driving frequency refers to the dynamic matching of the spin wave group velocity (such as speeding up in the high-frequency band and decelerating in the low-frequency band) to ensure that the energy transmission of the traveling wave field and the spin wave is synchronized.

[0140] The driving voltage amplitude refers to adjusting the amplitude strength of the traveling wave field, enhancing the energy capture capability of the target area and suppressing energy leakage in the non-target area.

[0141] The nonlinear enhancement index refers to enhancing the nonlinear effect, improving the energy flux density of the target path, and suppressing multipath scattering interference.

[0142] The spatial attenuation coefficient refers to the suppression of far-field energy leakage and optimization of the localized range of stress isolation by adjusting the attenuation gradient.

[0143] S4. Dynamically match the propagation characteristics of the spin wave and traveling wave stiffness fields through iterative updates of the optimization algorithm, output the optimized dynamic traveling wave stiffness field calibration parameters, conduct full-condition vibration testing, and verify the isolation performance.

[0144] Furthermore, the spin wave energy flux density distribution and the dynamic traveling wave stiffness field distribution are iteratively updated through an optimization algorithm to generate an adjustment instruction set;

[0145] Specifically, in devices integrating magnetic topological insulators and space-time encoding metamaterials, the spin wave energy flux density distribution and the dynamic traveling wave stiffness field distribution are collected in real time through a multi-objective optimization algorithm. The matching deviations between the two in the frequency domain, spatial domain and time domain are also collected. Based on the reinforcement learning framework, historical data and real-time feedback are combined to iteratively generate adjustment instruction sets for the piezoelectric array driving parameters. For the high-frequency energy flux density concentrated area, the driving voltage amplitude is preferentially increased to enhance the local traveling wave field stiffness; for the propagation path with phase gradient mismatch, the driving phase delay is dynamically corrected to compensate for the path offset; at the same time, the driving frequency is adaptively adjusted according to the temperature field distribution to suppress the group velocity mismatch caused by thermal stress.

[0146] Dynamically update the driving voltage amplitude, phase and frequency of the piezoelectric array according to the adjustment instruction;

[0147] Specifically, according to the phase gradient offset of the spin wave propagation path, the adjustment instruction drives the phase delay module to generate a compensation signal opposite to the path deflection direction, thereby correcting the wavefront distribution of the traveling wave field;

[0148] According to the energy flux density distribution characteristics, the driving voltage amplitude of each unit is dynamically adjusted to make the traveling wave stiffness field amplitude positively correlated with the local stress energy density, thereby enhancing the energy capture capability of the target area.

[0149] At the same time, combined with the temperature field feedback data, the driving frequency is adaptively adjusted to match the spin wave group velocity after thermal stress modulation, thereby suppressing the interference attenuation caused by time domain mismatch.

[0150] The matching degree between the updated traveling wave stiffness field and the propagation direction of the spin wave energy flux density is verified by laser interferometer, and the calibration parameters of the dynamic traveling wave stiffness field are output;

[0151] Specifically, a phase-sensitive laser interferometer emits two coherent laser beams on the surface of the composite device, tracking the propagation paths of the spin wave energy flux density distribution and the traveling wave stiffness field, respectively, and capturing the dynamic changes in the interference fringes between them in real time. The interferometer analyzes the fringe displacement and phase difference to determine the angular deviation between the traveling wavefront and the propagation direction of the spin wave. This phase difference is input into a calibration algorithm to calculate the drive voltage phase compensation and frequency correction value, dynamically adjusting the drive parameters of the piezoelectric array unit to synchronize the traveling wave field propagation direction with the spin wave path in real time.

[0152] A multi-axis vibration excitation source is deployed on the surface of the device, and the vibration spectrum parameters of all working conditions are loaded. The piezoelectric array is used to generate an anti-phase traveling wave stiffness field that matches the vibration spectrum to apply dynamic stress isolation.

[0153] Specifically, when deploying a multi-axis vibration excitation source on the surface of the device, a three-axis orthogonal electromagnetic exciter array is used to apply wide-band (1Hz-10kHz) and multi-modal (sinusoidal, random, transient impact) vibration excitation along the X / Y / Z directions, respectively, and load the full-condition vibration spectrum parameters including frequency range, intensity gradient, phase distribution and time modulation characteristics.

[0154] The piezoelectric array receives vibration spectrum data in real time and analyzes the vibration propagation direction and phase characteristics through multi-physics field collaborative control, dynamically generating a spatiotemporal modulated traveling wave stiffness field with equal amplitude and opposite phase to the input vibration spectrum. This anti-phase field, through the interference superposition of the piezoelectric unit deformation, spatially constructs a stiffness gradient distribution that matches the vibration wavefront propagation path, offsetting the transmission of vibration energy through destructive interference.

[0155] At the same time, combined with the real-time collected vibration displacement feedback data, the driving voltage amplitude and phase delay are dynamically adjusted through an adaptive algorithm to compensate for the matching deviation caused by temperature drift and nonlinear distortion.

[0156] Vibration spectrum parameters include frequency range, vibration intensity, phase information, directional component and time modulation characteristics.

[0157] It should be noted that the frequency range refers to the frequency matching range that determines the traveling wave field generated by the piezoelectric array. For example, in the high frequency range (>5kHz), the driving frequency needs to be increased to synchronize the spin wave group velocity, while in the low frequency range (<100Hz), the resonance effect needs to be suppressed.

[0158] Vibration intensity refers to the dynamic adjustment of the driving voltage amplitude to ensure that the traveling wave field amplitude matches the input vibration intensity to avoid undercompensation (insufficient isolation) or overcompensation (energy reflection).

[0159] Phase information is a key parameter for generating an anti-phase traveling wave field. The phase difference is used to control the interference cancellation effect between the traveling wave field and the input vibration.

[0160] The directional component refers to the spatial distribution pattern of the guiding piezoelectric array, activating the driving unit in the corresponding axis and suppressing the multi-axis coupled vibration transmission.

[0161] Time modulation characteristics refer to the response speed and stability of dynamic adjustment of driving parameters.

[0162] This embodiment also provides a device stress isolation system, including: a magnetic film preparation module, a metamaterial encoding module, a multi-field coupling module, and a calibration verification module; the magnetic film preparation module prepares a magnetic topological insulator thin film on the device surface, forms a heterojunction structure through deposition and annealing, verifies the conversion efficiency of mechanical stress into spin waves, and outputs the spin wave energy flux density distribution; the metamaterial encoding module is used to lay a spatiotemporal encoding metamaterial layer in the device dissipation region, generate a traveling wave stiffness field that matches the propagation direction of the spin wave through a piezoelectric array, and output a coding instruction set; the multi-field coupling module is used to integrate the magnetic topological insulator thin film with the spatiotemporal encoding metamaterial layer, deploy a sensor array to monitor the magnetic field and temperature in real time, adjust the spin wave path and encoding parameters through multi-physical field collaborative control, and output a dynamic traveling wave stiffness field distribution; the calibration verification module is used to iteratively update the optimization algorithm to dynamically match the propagation characteristics of the spin wave and the traveling wave stiffness field, output the optimized dynamic traveling wave stiffness field calibration parameters, perform full-operating vibration testing, and verify the isolation performance.

[0163] This embodiment also provides a computer device suitable for the device stress isolation method, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement the device stress isolation method proposed in the above embodiment.

[0164] The computer device can be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected by a system bus. The processor of the computer device is configured 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 and a computer program. The internal memory provides an environment for running the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is configured to perform wired or wireless communication with an external terminal. The wireless communication can be achieved by WIFI, a carrier network, NFC (Near Field Communication) or other technologies. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer overlaid on the display screen, or a key, a trackball or a touchpad arranged on the shell of the computer device, or an external keyboard, a touchpad or a mouse, etc.

[0165] The embodiment also provides a storage medium having a computer program stored thereon, and the computer program is executed by a processor to implement the device stress isolation method provided in the above embodiment. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as a static random access memory (SRAM), an electrically erasable programmable read-only memory (EEPROM), an erasable programmable read-only memory (EPROM), a programmable read-only memory (PROM), a read-only memory (ROM), a magnetic memory, a flash memory, a magnetic disk or an optical disk.

[0166] In summary, the application meets the full-link performance improvement of device stress isolation through the multi-physics field cooperative control and dynamic optimization mechanism. Through dynamic stress tuning deposition and non-equilibrium annealing process, the lattice matching and spin-orbit coupling characteristics of heterojunction are optimized, the directional conversion efficiency of mechanical stress to spin wave energy is improved, the energy capture ability of high frequency stress section is enhanced by using frequency domain weighting function, and the efficient conversion and transmission of wideband stress wave are ensured. The space-time coding metamaterial layer combines with the deep reinforcement learning model to analyze the spin wave propagation characteristics in real time and dynamically optimize the piezoelectric driving parameters, generate a traveling wave stiffness field with nonlinear interference effect, accurately match the spin wave group velocity and phase gradient, realize the directional dissipation and far field leakage suppression of stress energy. The spin wave path deviation and traveling wave field distribution characteristics are monitored in real time, and the driving voltage phase and frequency are dynamically adjusted to ensure the stability of the isolation performance under complex working conditions.

[0167] It should be noted that the above examples are only used to illustrate the technical solutions of the present application and are not limiting. Although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced by equivalents without departing from the spirit and scope of the present application, which should be covered by the scope of the claims of the present application.

Claims

1. A device stress isolation method, characterized by: include, A magnetic topological insulator thin film was prepared on the device surface, and a heterojunction structure was formed through deposition and annealing. The conversion efficiency of mechanical stress into spin waves was verified, and the spin wave energy flux density distribution was output. A spatiotemporal encoding metamaterial layer is laid in the dissipative region of the device, and a traveling wave stiffness field matching the propagation direction of the spin wave is generated through a piezoelectric array to output a coded instruction set. Integrate a magnetic topological insulator film with a spatiotemporal encoding metamaterial layer, deploy a sensor array to monitor the magnetic field and temperature in real time, adjust the spin wave path and encoding parameters through multi-physics collaborative control, and output a dynamic traveling wave stiffness field distribution; Through iterative updates of the optimization algorithm, the propagation characteristics of the spin wave and the traveling wave stiffness field are dynamically matched, and the optimized dynamic traveling wave stiffness field calibration parameters are output to conduct full-condition vibration tests and verify the isolation performance.

2. The device stress isolation method according to claim 1, wherein: The method involves preparing a magnetic topological insulator film on the device surface, forming a heterojunction structure through deposition and annealing, verifying the conversion efficiency of mechanical stress into spin waves, and outputting the spin wave energy flux density distribution. The specific steps are as follows: A heterojunction structure is formed on the surface of a magnetic topological insulator film through a dynamic stress-tuned deposition process, and the stress distribution is monitored in real time. The film is subjected to nonlinear field coupling annealing treatment, combined with an alternating magnetic field to optimize lattice defect repair; Apply local pressure through a scanning probe to measure the spin wave energy flux density; A frequency domain weighted function is constructed according to the spin wave energy flux density, and the frequency domain weighted function is combined with the multi-physics field coupling model to output the spin wave energy flux density distribution.

3. The device stress isolation method according to claim 2, wherein: The spatiotemporal coding metamaterial layer is laid in the dissipative region of the device, a traveling wave stiffness field matching the propagation direction of the spin wave is generated through a piezoelectric array, and a coding instruction set is output. The specific steps are as follows: Real-time monitoring of spin wave propagation parameters, calculation of dynamic phase gradient fields, construction of deep reinforcement learning models, and optimization of piezoelectric array driving parameters; The spin wave propagation parameters include wave vector, frequency, phase gradient, group velocity and energy flux density, and the piezoelectric array driving parameters include driving voltage, driving frequency, phase delay and spatial distribution pattern; According to the optimized piezoelectric array driving parameters, a nonlinear interference traveling wave stiffness field is generated, sparse coding compression is performed, and a coding instruction set is output.

4. The device stress isolation method according to claim 3, wherein: The specific steps of integrating the magnetic topological insulator film with the spatiotemporal encoding metamaterial layer and deploying a sensor array to monitor the magnetic field and temperature in real time are as follows: interfacially bonding the magnetic topological insulator film and the spatiotemporal encoding metamaterial layer to form a composite structure; Deploy a Hall sensor array on the surface of the composite structure to monitor the magnetic field strength and calculate the magnetic field gradient in real time; A thermocouple array is deployed on the surface of the composite structure to monitor the temperature distribution and calculate the temperature gradient in real time.

5. The device stress isolation method according to claim 4, wherein: The spin wave path and encoding parameters are adjusted through multi-physics field collaborative control to output the dynamic traveling wave stiffness field distribution. The specific steps are as follows: The magnetic field gradient and temperature gradient are input into the multi-physics field collaborative control to analyze the spin wave path offset and encoding parameter deviation; Dynamically adjust the driving voltage phase and frequency of the spatiotemporal encoding metamaterial layer to output a dynamic traveling wave stiffness field distribution; The encoding parameters include spin wave phase, spin wave frequency, driving frequency, driving voltage amplitude, nonlinear enhancement index and spatial attenuation coefficient.

6. The device stress isolation method according to claim 5, wherein: The optimization algorithm is iteratively updated to dynamically match the propagation characteristics of the spin wave and the traveling wave stiffness field, output the optimized dynamic traveling wave stiffness field calibration parameters, conduct full-condition vibration testing and verify the isolation performance. The specific steps are as follows: The spin wave energy flux density distribution and the dynamic traveling wave stiffness field distribution are iteratively updated through an optimization algorithm to generate an adjustment instruction set; Dynamically update the driving voltage amplitude, phase and frequency of the piezoelectric array according to the adjustment instruction; The matching degree between the updated traveling wave stiffness field and the propagation direction of the spin wave energy flux density is verified by laser interferometer, and the calibration parameters of the dynamic traveling wave stiffness field are output; A multi-axis vibration excitation source is deployed on the surface of the device, and the vibration spectrum parameters of all working conditions are loaded. The piezoelectric array is used to generate an anti-phase traveling wave stiffness field that matches the vibration spectrum to apply dynamic stress isolation.

7. The device stress isolation method according to claim 6, wherein: The vibration spectrum parameters include frequency range, vibration intensity, phase information, direction component and time modulation characteristics.

8. A device stress isolation system, based on the device stress isolation method according to any one of claims 1 to 7, characterized in that: Including magnetic film preparation module, metamaterial encoding module, multi-field coupling module and calibration verification module; The magnetic film preparation module prepares a magnetic topological insulator thin film on the device surface, forms a heterojunction structure through deposition and annealing, verifies the conversion efficiency of mechanical stress into spin waves, and outputs the spin wave energy flux density distribution; The metamaterial encoding module is used to lay a spatiotemporal encoding metamaterial layer in the device dissipative region, generate a traveling wave stiffness field that matches the propagation direction of the spin wave through a piezoelectric array, and output a coding instruction set; The multi-field coupling module is used to integrate the magnetic topological insulator film with the spatiotemporal coding metamaterial layer, deploy a sensor array to monitor the magnetic field and temperature in real time, adjust the spin wave path and coding parameters through multi-physics field collaborative control, and output a dynamic traveling wave stiffness field distribution; The calibration verification module is used to iteratively update the optimization algorithm, dynamically match the propagation characteristics of the spin wave and the traveling wave stiffness field, output the optimized dynamic traveling wave stiffness field calibration parameters, perform full-condition vibration testing and verify the isolation performance.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the device stress isolation method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the device stress isolation method according to any one of claims 1 to 7 are implemented.

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