Plastic induction frame of intelligent glasses, material and manufacturing method

Abstract

The invention discloses a plastic induction frame of intelligent glasses, a material and a manufacturing method, and the manufacturing method comprises the following steps: compounding a carbon nanotube, metal powder and a thermoplastic elastomer base material through a segmented internal mixing process to form gradient conductive elastic master batches, injecting the gradient conductive elastic master batches into a multi-layer injection mold, and forming a plastic induction prefabricated member through an electric field auxiliary injection molding process; then carrying out surface functionalization treatment, forming a conductive channel with a micro-nano rough structure through plasma etching, integrating an impedance monitoring module at the tail end of the conductive channel, establishing a material-process parameter mapping model, and optimizing the plastic induction prefabricated member; assembling the optimized plastic induction prefabricated member and a flexible circuit board, filling a contact interface with a conductive adhesive to form a complete capacitance loop, and obtaining a plastic induction frame substrate; through the split-phase design of the gradient conductive elastic master batch, the synergism of the conductivity and the plastic deformation performance of the material is realized, and the high precision and the high reliability of the intelligent glasses in the wearing state detection are ensured.

Description

Technical Field

[0001] The present invention relates to the field of induction frames, and particularly to a plastic induction frame, material and manufacturing method for smart glasses. Background Art

[0002] With the popularization of wearable health monitoring and intelligent interaction technologies, traditional glasses are gradually being upgraded to smart glasses integrated with biosensing (such as heart rate monitoring and fatigue detection) and environmental perception (such as light adaptation and temperature and humidity sensing) functions. Such glasses need to achieve invisible circuit integration and accurate identification of the human contact state while maintaining the thinness of the conventional frame (<5 mm) and wearing comfort (elastic modulus <3 MPa), which poses dual challenges to the mechanical adaptability (tolerating cyclic deformation caused by daily taking on and off) and electrical stability (capacitance detection error <±5%) of the frame material.

[0003] In the prior art, smart glasses frames mostly adopt mechanically blended composites based on silicone / TPE matrices, and basic sensing functions are realized by embedding sensing components. However, in the cyclic deformation caused by long-term wearing of such materials, due to the fracture of sensing components and the peeling of the matrix interface, there will be fluctuations in resistance values and attenuation of capacitance signals, directly leading to an increase in the misjudgment rate of the wearing state and severely restricting the reliability of the product. This defect essentially stems from the linear coupling mechanism of the conductive-elastic properties of traditional composite materials and cannot meet the requirements of microstructure reorganization under dynamic deformation.

[0004] In view of this, it is necessary to address the technical problem of the inaccurate capacitance detection signal caused by the damage of the conductive network of traditional flexible conductive materials during the long-term deformation of the smart glasses frame materials in the prior art. Summary of the Invention

[0005] The purpose of the present invention is to provide a plastic induction frame, material and manufacturing method for smart glasses to solve the above technical problems.

[0006] To achieve this purpose, the present invention adopts the following technical solutions: A manufacturing method for a plastic induction frame material of smart glasses, comprising the following steps: Compound carbon nanotubes, metal powder and a thermoplastic elastomer substrate through a segmented internal mixing process to form a gradient conductive elastic masterbatch with a phase-separated distribution of a surface conductive layer and an inner elastic layer; Inject the gradient conductive elastic masterbatch into a multi-layer injection mold and form a plastic induction preform with a directional conductive channel through an electric field-assisted injection molding process; Perform surface functionalization treatment on the plastic induction preform, form a conductive channel with a micro-nano rough structure through plasma etching, and impregnate a dynamic cross-linking agent to construct an interface strengthening layer; Integrate an impedance monitoring module at the end of the conductive channel of the plastic induction preform, establish a material-process parameter mapping model, optimize the electric field parameters and injection pressure through real-time data feedback, and obtain an optimized plastic induction preform; Assemble the optimized plastic induction preform with a flexible circuit board, and fill the contact interface with conductive adhesive to form a complete capacitance circuit, obtaining a plastic induction frame substrate with integrated capacitance detection function.

[0007] Optionally, the carbon nanotubes are any one of single-walled carbon nanotubes, multi-walled carbon nanotubes or amino-modified carbon nanotubes; The metal powder is any one of spherical silver powder, flaky copper powder, nickel powder or silver-coated copper powder; The thermoplastic elastomer substrate is any one of SEBS-based TPE, TPU or SBS.

[0008] Optionally, the mass percentages of the carbon nanotubes, metal powder and thermoplastic elastomer substrate are: carbon nanotubes 5-40%, metal powder 10-30%, and the balance is the thermoplastic elastomer substrate.

[0009] Optionally, the carbon nanotubes, metal powder and thermoplastic elastomer substrate are compounded by a segmented internal mixing process to form a gradient conductive elastic masterbatch with a phase-separated distribution of a surface conductive layer and an inner elastic layer, specifically including: Modify the carbon nanotubes by treatment with a silane coupling agent, screen the metal powder by ball milling to a preset particle size, and pre-dry and pre-treat the thermoplastic elastomer substrate to a target moisture content; Put the pretreated thermoplastic elastomer substrate and modified carbon nanotubes into an internal mixer, and internally mix at 160-170°C for 5-8 minutes to form a matrix molten phase with pre-dispersed conductive phases; Gradually add the metal powder to the matrix molten phase in three steps, with an interval of 1-2 minutes each time, and continue to internally mix at 180-190°C for 10-15 minutes to form a composite melt with interpenetrating conductive networks; Transfer the composite melt to a two-stage twin-screw extruder, inject a dynamic crosslinking agent into the second-stage screw, and achieve the extrusion of phase-separated masterbatch of the surface conductive layer and the inner elastic layer through temperature zone control; among them, the temperature zones are zone 1 at 175°C / zone 2 at 195°C; Perform secondary coating on the extruded masterbatch by fluidized bed, and use atomized spraying of metal powder and elastomer solution to form a functional surface layer with a preset thickness to obtain a gradient conductive elastic masterbatch.

[0010] Optionally, inject the gradient conductive elastic masterbatch into a multi-layer injection mold, and form a plastic induction preform with a directional conductive channel through an electric field-assisted injection molding process, specifically including the following steps: Preheat the multi-layer injection mold to 80 - 100 °C on the conductive layer side and 40 - 60 °C on the elastic layer side, and etch conductive grooves with a width of 20 - 50 μm on the mold cavity surface; Put the gradient conductive elastic masterbatch into a double-channel injection molding machine, control the temperature of the conductive layer runner at 200 - 210 °C and the temperature of the elastic layer runner at 170 - 180 °C, and achieve melt phase separation flow through the shear rate gradient; Apply an axial pulsed electric field with the first electric field strength during the injection stage to make the conductive particles in the masterbatch migrate directionally along the conductive grooves, and synchronously apply a radial shear field to suppress the anisotropy of the conductive network; Maintain the second electric field strength during the holding pressure stage and cooperate with the mold temperature gradient control. After cooling and demolding, a plastic induction preform with oriented conductive channels is obtained; wherein, the first electric field strength is much greater than the second electric field strength.

[0011] Optionally, perform surface functionalization treatment on the plastic induction preform, form conductive channels with micro-nano rough structures through plasma etching, and impregnate with a dynamic cross-linking agent to construct an interface strengthening layer, which specifically includes the following steps: Place the plastic induction preform in an ultrasonic cleaning device, clean the surface with a mixed solution of isopropyl alcohol and deionized water, and perform drying treatment in a vacuum drying oven; Load the cleaned plastic induction preform into a plasma treatment chamber, introduce a mixed gas of argon and carbon tetrafluoride with a ratio of 9:1, and perform pulsed plasma etching under preset conditions to form a fractal microstructure with a preset depth on the surface of the conductive channels; Adopt a mask-assisted laser ablation technique to process array grooves with a preset width on the surface of the etched conductive channels, and cover a graphene quantum dot enhancement layer on the inner wall of the array grooves; Immerse the preform in a dynamic cross-linking agent solution containing thiosulfate-based siloxane, and achieve gradient penetration of the cross-linking agent under the alternating action of ultrasonic vibration and negative pressure; Optionally, after the step of immersing the preform in a dynamic cross-linking agent solution containing thiosulfate-based siloxane and achieving gradient penetration of the cross-linking agent under the alternating action of ultrasonic vibration and negative pressure, the following steps are further included: Place the penetrated preform under a UV-infrared composite light source for curing. First, irradiate with ultraviolet light with a wavelength of 365 nm for the first duration to initiate surface cross-linking, and then switch to infrared light with a wavelength of 850 nm to irradiate for the second duration to activate deep-layer dynamic bond recombination; Perform helium protection annealing treatment on the cured preform, and spray a hydrophobic protective film containing fluorosilane after annealing.

[0012] Optionally, an impedance monitoring module is integrated at the end of the conductive channel of the plastic induction preform, a material-process parameter mapping model is established, and the electric field parameters and injection pressure are optimized through real-time data feedback to obtain an optimized plastic induction preform. The specific steps are as follows: Integrate a micro impedance sensor at the end of the conductive channel of the plastic induction preform in a detachable manner, and encapsulate a flexible circuit board to form an embedded monitoring node; Connect the embedded monitoring node to a high-speed data connector to collect the timing data of the electric field strength, melt pressure, and conductive channel impedance value in the injection molding stage in real time; Construct a process feature matrix based on multi-source data fusion, use the adaptive random forest algorithm to establish a material conductivity-process parameter mapping model, dynamically predict the optimal electric field strength threshold and pressure compensation coefficient, and obtain optimized parameters; Verify the optimized parameters through a digital twin system and screen out the parameter combination with the highest verification effect index; Encrypt and write the verified optimized parameters into the process database, and generate a dynamic adjustment instruction set to feedback to the injection molding machine control system to synchronously update the masterbatch ratio recommendation scheme.

[0013] The present invention also provides a plastic induction frame for smart glasses, including the plastic induction frame material of the smart glasses as described above. The plastic induction frame material is processed into the main frame of the smart glasses. The plastic induction frame further includes: A flexible circuit board assembly is connected to the conductive channel of the plastic induction frame through conductive glue to form a closed-loop capacitance detection circuit; A functional contact area is configured as an elastic contact interface adapted to the wearer's facial contour to realize the dynamic perception of pressure distribution and deformation signals.

[0014] The present invention also provides a pair of smart glasses, including lenses and the plastic induction frame of the smart glasses as described above. The lenses are myopia lenses or optical lenses with light screening.

[0015] Compared with the prior art, the present invention has the following beneficial effects: First, a gradient conductive elastic masterbatch is prepared by compounding carbon nanotubes, metal powder and thermoplastic elastomer through a segmented internal mixing process. Then, an electric field-assisted injection molding technology is used to form the masterbatch into a plastic induction preform with a directional conductive channel. Next, the preform is subjected to plasma etching to form a micro-nano rough surface and impregnated with a dynamic cross-linking agent to strengthen the interface. Then, an impedance monitoring module is integrated to construct a data feedback system to optimize the process parameters. Finally, the optimized preform and a flexible circuit board are assembled through a conductive adhesive to form a plastic induction frame matrix integrating a capacitance detection function. This process realizes the coordinated optimization of material conductivity and plasticity through the phase separation design of the gradient conductive elastic masterbatch. The directional conductive channel formed by electric field-assisted injection molding improves the signal transmission efficiency. Plasma etching and dynamic cross-linking treatment enhance the surface contact sensitivity and mechanical durability. Combining the data feedback mechanism of the impedance monitoring module ensures the dynamic optimization of process parameters, meets the coordination of the conductive stability and plastic deformation performance of the flexible sensing material, and ensures high precision and high reliability in the wearing state detection of smart glasses. Description of the Drawings

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0017] The structures, proportions, sizes, etc. shown in the drawings of this specification are only used to cooperate with the content disclosed in the specification for those familiar with this technology to understand and read, and are not used to limit the limiting conditions under which the present invention can be implemented. Therefore, they do not have a technical essence. Any modification of the structure, change of the proportional relationship or adjustment of the size, without affecting the effects that the present invention can produce and the purposes that can be achieved, should still fall within the scope that can be covered by the technical content disclosed in the present invention.

[0018] Figure 1 It is one of the flow diagrams of the manufacturing method of the plastic induction frame material of the smart glasses in Embodiment 1; Figure 2 It is another flow diagram of the manufacturing method of the plastic induction frame material of the smart glasses in Embodiment 1; Figure 3 It is the structural diagram of the plastic induction frame of the smart glasses in Embodiment 2; Figure 4 It is the structural diagram of the main part of the plastic induction frame of the smart glasses in Embodiment 2. Detailed Embodiments

[0019] In order to make the objectives, features, and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the embodiments described below are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0020] In the description of the present invention, it should be understood that the orientation or positional relationships indicated by the terms "upper", "lower", "top", "bottom", "inner", "outer", etc. are based on the orientation or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to the present invention. It should be noted that when a component is considered to be "connected" to another component, it can be directly connected to the other component or there may be an intermediate component present at the same time.

[0021] The technical solutions of the present invention will be further described below with reference to the accompanying drawings and through specific embodiments.

[0022] Embodiment 1: Combined with Figure 1 and Figure 2 As shown, the embodiment of the present invention provides a method for manufacturing a plastic induction frame material for smart glasses, including the following steps: S1, compound carbon nanotubes, metal powder and a thermoplastic elastomer substrate through a segmented mixing process to form a gradient conductive elastomer masterbatch with a phase-separated distribution of a surface conductive layer and an inner elastic layer; Compound carbon nanotubes, metal powder and a thermoplastic elastomer substrate through a segmented mixing process, and utilize the phase separation characteristics of different components in the molten state to form a gradient structure of a surface high-conductivity layer and an inner high-elasticity layer. During the segmented mixing process, by controlling the temperature rise in stages and the feeding sequence (such as first mixing carbon nanotubes to form a conductive network skeleton, and then gradually introducing metal powder to fill the voids), the conductive phase is preferentially enriched on the surface layer, while the elastic matrix remains a continuous phase in the inner layer. This gradient design decouples the conductive performance and mechanical flexibility in space at the material level, providing a masterbatch raw material with both functionality and structural adaptability for subsequent injection molding.

[0023] S2, inject the gradient conductive elastomer masterbatch into a multi-layer injection mold, and form a plastic induction preform with a directional conductive channel through an electric field-assisted injection process; Based on the characteristics of the gradient masterbatch, a multi-layer injection mold is combined with an electric field-assisted process for molding. The application of the electric field causes the conductive particles in the masterbatch to migrate and align along the preset direction, forming a directional conductive channel that penetrates the preform within the mold. The temperature gradient control of the multi-layer mold (high temperature on the conductive layer side to promote melt flow and low temperature on the elastic layer side to maintain morphological stability) further enhances the gradient distribution characteristics of the material. The core of this process lies in the synergistic effect of physical fields (electric field, temperature field) and the mold structure, converting the component gradient of the masterbatch into a functionalized structure of the preform, ensuring the continuity and spatial directivity of the conductive channel.

[0024] S3. Perform surface functionalization on the plastic induction preform, form a conductive channel with a micro-nano rough structure through plasma etching, and impregnate with a dynamic cross-linking agent to construct an interface strengthening layer; The surface functionalization process includes two key links: plasma etching and dynamic cross-linking. Plasma etching forms a micro-nano scale rough structure on the surface of the conductive channel through high-energy particle bombardment, increasing the effective contact area and reducing the interface impedance; the impregnation and penetration of the dynamic cross-linking agent (a silicone compound containing reversible chemical bonds) constructs an adaptive cross-linking network inside the matrix. This network can dissipate stress through dynamic bond breakage-recombination during the deformation process while maintaining the topological connectivity of the conductive channel. This step improves the durability of the material from two dimensions of micro-topography and interface chemistry, solving the problem of the failure of the conductive network during cyclic deformation.

[0025] S4. Integrate an impedance monitoring module at the end of the conductive channel of the plastic induction preform, establish a mapping model of material-process parameters, and optimize the electric field parameters and injection pressure through real-time data feedback to obtain an optimized plastic induction preform; By integrating an impedance monitoring module at the end of the conductive channel, real-time collect the correlation data of process parameters (such as electric field strength, injection pressure) and electrical conductivity (impedance value). Using algorithms such as random forest to establish a mapping model of material properties and process conditions, the influence weights of key parameters can be identified and the optimization direction can be predicted. The innovation of this step lies in transforming the traditional trial-and-error process optimization into a data-driven mode: based on the performance feedback of the current preform, dynamically adjust the electric field parameters and injection pressure of subsequent production batches to achieve self-iterative optimization of process parameters.

[0026] S5. Assemble the optimized plastic induction preform with a flexible circuit board, fill the contact interface with conductive adhesive to form a complete capacitor circuit, and obtain a plastic induction frame substrate with an integrated capacitor detection function.

[0027] In the final assembly stage, the optimized preform is bonded to the flexible circuit board with conductive adhesive, and a closed capacitive circuit is formed by the bridging effect of the conductive adhesive. The selection of the conductive adhesive needs to meet two requirements: one is the wettability with the micro-nano rough surface to ensure low-impedance contact; the other is the elastic modulus matching to avoid interface peeling caused by stress concentration. The essence of this step is to convert the intrinsic properties of the material into device functions, detect the wearing state through the change of capacitance value, and at the same time maintain the structural integrity and wearing comfort of the glasses frame.

[0028] The working principle of the present invention is as follows: First, a gradient conductive elastic masterbatch is prepared by compounding carbon nanotubes, metal powder and thermoplastic elastomer through a segmented internal mixing process. Then, the masterbatch is formed into a plastic induction preform with a directional conductive channel by using an electric field-assisted injection molding technology. Then, the preform is subjected to plasma etching to form a micro-nano rough surface and impregnated with a dynamic cross-linking agent to strengthen the interface. Then, an impedance monitoring module is integrated to construct a data feedback system to optimize the process parameters. Finally, the optimized preform and the flexible circuit board are assembled with conductive adhesive to form a plastic induction frame matrix integrated with a capacitance detection function. This process realizes the synergistic optimization of material conductivity and plasticity through the phase separation design of the gradient conductive elastic masterbatch. The directional conductive channels formed by electric field-assisted injection molding improve the signal transmission efficiency. Plasma etching and dynamic cross-linking treatment enhance the surface contact sensitivity and mechanical durability. Combining with the data feedback mechanism of the impedance monitoring module ensures the dynamic optimization of process parameters, meets the synergy of the conductive stability and plastic deformation performance of the flexible sensing material, and ensures high precision and high reliability in the wearing state detection of the smart glasses.

[0029] In this embodiment, optionally, the carbon nanotubes are any one of single-walled carbon nanotubes, multi-walled carbon nanotubes or amino-modified carbon nanotubes; the metal powder is any one of spherical silver powder, flaky copper powder, nickel powder or silver-coated copper powder; the thermoplastic elastomer substrate is any one of SEBS-based TPE, TPU or SBS. Among them, SEBS-based TPE is a thermoplastic elastomer based on styrene-ethylene-butene-styrene block copolymer (SEBS); TPU is thermoplastic polyurethane, and SBS is styrene-butadiene-styrene block copolymer.

[0030] The material options provided in this embodiment are based on considerations of functional adaptability and process compatibility: single-walled carbon nanotubes have excellent conductivity and aspect ratio, and are suitable for constructing a highly sensitive conductive network; multi-walled carbon nanotubes have higher mechanical strength and can enhance the creep resistance of the composite material; amino-modified carbon nanotubes improve their dispersion in the matrix through surface functional groups.

[0031] The selection of metal powder takes into account both conductive efficiency and economy - spherical silver powder provides the lowest contact impedance, flaky copper powder enhances isotropic conductivity through a laminated structure, and silver-coated copper powder achieves a balance between cost and antioxidant properties.

[0032] Among thermoplastic elastomer substrates, SEBS-based TPE has excellent resilience and biocompatibility, TPU provides higher wear resistance, and SBS is beneficial for low-temperature processing and molding. This combination scheme provides a customizable material basis for the realization of a gradient conductive structure.

[0033] In this embodiment, optionally, the mass percentages of carbon nanotubes, metal powder, and thermoplastic elastomer substrate are: 5-40% for carbon nanotubes, 10-30% for metal powder, and the balance is the thermoplastic elastomer substrate.

[0034] The proportion range of 5-40% carbon nanotubes covers the conductive percolation threshold to the mechanical property critical point (exceeding 40% is likely to cause brittle fracture), ensuring the elastic deformation ability of the material body while forming a continuous conductive network; the addition of 10-30% metal powder can reduce the contact resistance by filling the gaps between carbon nanotubes and avoid problems such as excessive density and deteriorated processing fluidity caused by excessive metal powder. The remaining interval of 30-85% for the substrate provides the necessary mechanical support for the material. When the substrate is SEBS-based TPE, its content needs to be ≥50% to meet the requirement of elongation at break of more than 200%. This proportion system realizes the gradient regulation of the electrical and mechanical properties of the material through the synergistic effect of the conductive phase and the elastic phase.

[0035] In this embodiment, specifically, step S1 specifically includes: S11, modifying the carbon nanotubes with a silane coupling agent, screening the metal powder to a preset particle size by ball milling, and pre-drying the thermoplastic elastomer substrate to a target moisture content; In the pretreatment stage, the surface of the carbon nanotubes is modified with a silane coupling agent to enhance their interfacial compatibility with the matrix and avoid discontinuity of the conductive network caused by agglomeration during subsequent processing; the metal powder is screened to a preset particle size (such as ≤5μm) by ball milling to control the particle size distribution and reduce local stress concentration caused by particle size differences; pre-drying the substrate to a low moisture content (such as <0.1%) can prevent pores from being generated due to water volatilization during melt processing and ensure the denseness of the material. This step lays the foundation for the uniform composite of the conductive phase and the elastic phase through refined raw material pretreatment.

[0036] S12, putting the pretreated thermoplastic elastomer substrate and the modified carbon nanotubes into an internal mixer, and mixing them at 160-170°C for 5-8 minutes to form a matrix molten phase with pre-dispersed conductive phase; The base material and modified carbon nanotubes are kneaded at 160 - 170 °C. This temperature range not only ensures the full melting of the thermoplastic elastomer (the melting temperature of SEBS - based TPE is usually 150 - 180 °C), but also avoids the high - temperature oxidative degradation of carbon nanotubes. The kneading time of 5 - 8 min balances the dispersion efficiency and energy consumption, enabling the carbon nanotubes to initially form a three - dimensional conductive framework while retaining the elastic recovery ability of the matrix. The key at this stage is to pre - construct the conductive network through the precise matching of temperature and time.

[0037] S13, Add metal powder to the molten matrix phase in three gradients at intervals of 1 - 2 min each, and continue to knead at 180 - 190 °C for 10 - 15 min to form a composite melt with an interpenetrating conductive network; The process design of adding metal powder in three gradients can alleviate the problem of sudden change in melt viscosity caused by a large amount of addition at one time. The interval of 1 - 2 min each allows the melt to gradually adapt to the increase in filler. The temperature - rising kneading at 180 - 190 °C promotes the embedding of metal powder into the gaps of the carbon nanotube framework to form an interpenetrating conductive network. This temperature is slightly higher than the melting point of the base material (for example, the melting point of TPU is 170 - 190 °C), which can not only enhance the melt fluidity to promote filler dispersion, but also avoid the thermal decomposition of the elastomer (the thermal decomposition temperature of SEBS > 250 °C).

[0038] S14, Transfer the composite melt to a two - stage twin - screw extruder, inject a dynamic cross - linker (a siloxane compound containing disulfide bonds) into the second - stage screw, and achieve the extrusion of phase - separated masterbatches of the surface conductive layer and the inner elastic layer through temperature - zone control; among them, the temperature zones are zone 1 at 175 °C / zone 2 at 195 °C; The temperature - zone control (zone 1 at 175 °C / zone 2 at 195 °C) of the two - stage twin - screw extruder realizes functional zoning through a gradient heating strategy: the temperature in zone 1 maintains the melt fluidity to ensure the uniform dispersion of the dynamic cross - linker (a siloxane compound containing disulfide bonds); the temperature in zone 2 is raised to 195 °C to trigger the selective activation of the dynamic cross - linker (the sulfur - sulfur bond recombination temperature is about 190 - 200 °C), promoting a higher cross - link density in the conductive layer than in the elastic layer. This combination of zone - temperature control and dynamic cross - linking technology endows the masterbatch with gradient characteristics of high conductivity on the surface layer (the cross - linked network fixes the conductive path) and high elasticity in the inner layer (retaining the segmental mobility).

[0039] S15, The extruded masterbatch is secondarily coated in a fluidized bed, and an atomized spray of metal powder and elastomer solution is used to form a functional surface layer with a preset thickness to obtain a gradient - conductive elastic masterbatch.

[0040] The fluidized bed secondary coating process forms a functional surface layer with a thickness of 50 - 100 μm on the surface of the masterbatch by atomizing and spraying a mixed slurry of metal powder and elastomer solution. The gas-solid two-phase flow characteristics of the fluidized bed ensure a uniform coating thickness. The addition of the elastomer solution (such as a solid content of 20%) enhances the bonding strength between the metal powder and the matrix. This step further strengthens the surface conductivity on the basis of the gradient structure of the masterbatch body, while avoiding the negative impact on the overall elasticity caused by directly mixing excessive conductive phases.

[0041] In this embodiment, specifically, step S2 specifically includes the following steps: S21, preheat the multi-layer injection mold to 80 - 100 °C on the conductive layer side and 40 - 60 °C on the elastic layer side, and etch conductive grooves with a width of 20 - 50 μm on the surface of the mold cavity; The mold is preheated to 80 - 100 °C on the conductive layer side and 40 - 60 °C on the elastic layer side to match the phase state characteristics of the materials through the temperature gradient: the high-temperature side (conductive layer) reduces the melt viscosity to fill the micro-grooves, and the low-temperature side (elastic layer) maintains the morphological stability of the matrix. Conductive grooves with a width of 20 - 50 μm are etched on the surface of the mold cavity to guide the migration path of conductive particles through geometric constraints, ensuring the linearity and spatial distribution controllability of the conductive channels during subsequent electric field-assisted forming.

[0042] S22, put the gradient conductive elastic masterbatch into a two-channel injection molding machine, control the temperature of the conductive layer runner at 200 - 210 °C and the temperature of the elastic layer runner at 170 - 180 °C, and achieve melt phase separation flow through the shear rate gradient; The two-channel injection molding machine adopts a zoning temperature control strategy of 200 - 210 °C for the conductive layer runner and 170 - 180 °C for the elastic layer runner, corresponding to the high melt fluidity requirements of the conductive layer masterbatch (such as SEBS-based TPE containing metal powder) and the low-temperature heat degradation prevention requirements of the elastic layer substrate (such as TPU). The shear rate gradient (500 - 800 s-1 for the conductive layer and 200 - 400 s-1 for the elastic layer) achieves melt phase separation flow through differential shear stresses: a high shear rate promotes the full filling of the groove details by the conductive layer melt, and a low shear rate protects the structural integrity of the elastic layer.

[0043] S23, apply an axial pulsed electric field with a first electric field strength (field strength 4 - 6 kV / cm, frequency 1 - 3 kHz) during the injection stage to make the conductive particles in the masterbatch migrate directionally along the conductive grooves, and simultaneously apply a radial shear field to suppress the anisotropy of the conductive network; During the injection stage, a high-field-strength axial pulsed electric field is applied. The electric field force is used to drive the conductive particles to migrate directionally along the conductive grooves to form a main conductive path. At the same time, a radial shear field (300 - 500 s-1) is applied, which inhibits the over-orientation of the conductive particles through shear-induced Brownian motion and balances the anisotropy of the conductive network. The synergistic effect of this composite field ensures the directivity of the conductive channel (extending along the groove) and avoids the mechanical weakness problem caused by single-direction conduction.

[0044] S24. During the pressure-holding stage, the second electric field strength is maintained and combined with mold temperature gradient control (the cooling rate on the conductive layer side is 5°C / s, and the cooling rate on the elastic layer side is 2°C / s). After cooling and demolding, a plastic induction preform with a directional conductive channel is obtained. Among them, the first electric field strength is much greater than the second electric field strength.

[0045] During the pressure-holding stage, the electric field strength is reduced (such as 2 - 3 kV / cm). The formed conductive network is stabilized by the residual electric field. At the same time, the mold temperature gradient control (fast cooling at 5°C / s on the conductive layer side and slow cooling at 2°C / s on the elastic layer side) realizes the functional-structure co-curing: the fast cooling of the conductive layer locks the arrangement of the conductive particles, and the slow cooling of the elastic layer releases the internal stress to maintain the resilience. Through the dynamic regulation of the physical field parameters in this stage, a preform with continuous conductive channels and matching mechanical properties is finally obtained.

[0046] In this embodiment, specifically, step S3 specifically includes the following steps: S31. Place the plastic induction preform in an ultrasonic cleaning device, clean the surface with a mixed solution of isopropanol and deionized water (preferably with a volume ratio of 3:1), and perform drying treatment in a vacuum drying oven. Cleaning with a mixed solution of isopropanol and deionized water with a volume ratio of 3:1 can effectively remove the grease and fine particles on the surface of the preform (isopropanol dissolves organic substances, and deionized water avoids impurity deposition), and at the same time avoids the swelling effect of a single solvent on the elastic substrate. The vacuum drying treatment (such as 60°C) accelerates the volatilization of water through a low-pressure environment, prevents the residual liquid droplets from gasifying to form micropores in the subsequent high-temperature process, and ensures the surface cleanliness and structural integrity.

[0047] S32. Load the cleaned plastic induction preform into the plasma treatment chamber, introduce a mixed gas of argon and carbon tetrafluoride with a ratio of 9:1, and perform pulsed plasma etching under the conditions of a preset power of 300 W and a gas pressure of 50 Pa to form a fractal microstructure with a preset depth on the surface of the conductive channel. Plasma treatment of argon and carbon tetrafluoride mixed gas (9:1) produces physical etching through argon ion bombardment, and fluorine radicals generated by the decomposition of carbon tetrafluoride chemically modify the surface. The pulse mode (such as a duty cycle of 40%) controls the etching depth (200 - 500 nm) through intermittent energy input, forming a dendritic fractal microstructure to increase the effective contact area. This structural design can improve the charge transport efficiency of the conductive channel and provide anchoring points for the subsequent penetration of the dynamic crosslinking agent.

[0048] S33. Using a mask-assisted laser ablation technique, array grooves with a preset width of 10 - 20 μm are processed on the surface of the etched conductive channel, and a graphene quantum dot enhancement layer is covered on the inner wall of the array grooves; The mask-assisted laser ablation technique controls the spot size and energy density to process a 10 - 20 μm wide groove array on the etched surface, and its geometric parameters match the current density distribution requirements of the conductive channel. The graphene quantum dot enhancement layer (with a thickness of 50 - 100 nm) binds to the carbon-based material through π-π bonds, fills the microcracks generated by laser ablation, improves the carrier mobility of the inner wall of the groove, and reduces the contact impedance.

[0049] S34. Immerse the preform in a dynamic crosslinking agent solution containing thiosulfate-based siloxane, and achieve gradient penetration of the crosslinking agent under the alternating action of ultrasonic vibration and negative pressure; The alternating action of ultrasonic vibration (frequency 28 kHz) and negative pressure (-0.08 MPa) forms a dynamic penetration environment: the ultrasonic cavitation effect promotes the diffusion of the crosslinking agent into the micro-nano structure, and the negative pressure stage drives the deep penetration of the solution through the pressure difference. The dynamic crosslinking characteristics of thiosulfate-based siloxane (reversible cleavage of disulfide bonds) allow the crosslinking density to decrease gradually from the surface layer to the inner layer. The high crosslinking degree on the surface layer fixes the conductive network, and the low crosslinking degree in the inner layer maintains the elastic deformation ability.

[0050] S35. Place the infiltrated preform under a UV-infrared composite light source for curing. First, irradiate with ultraviolet light with a wavelength of 365 nm for the first duration to initiate surface crosslinking, and then switch to infrared light with a wavelength of 850 nm to irradiate for the second duration to activate deep dynamic bond recombination; Ultraviolet light (wavelength 365 nm) selectively activates the surface photoinitiator to quickly construct a surface crosslinking network to stabilize the microstructure; infrared light (wavelength 850 nm) penetrates to the deep layer of the material and triggers dynamic bond recombination (such as disulfide bond exchange reaction) through the photothermal effect, eliminating internal stress and endowing the material with self-adaptability. The sequential design of the photocuring parameters (such as UV 5 min + IR 10 min) balances the surface curing speed and the relaxation requirements of the deep structure.

[0051] S36. Carry out a helium protection annealing treatment (temperature 120 °C, time 2 h) on the cured preform, and spray a hydrophobic protective film containing fluorosilane after annealing.

[0052] Helium protection annealing (120°C, 2 h) utilizes the high thermal conductivity of helium to achieve uniform heating, eliminate processing residual stress, and stabilize the dynamic crosslinking network. The fluorosilane hydrophobic protective film (thickness 1 - 2 μm) is bonded to the substrate through the hydrolysis and condensation reaction of siloxane. Its low surface energy characteristic (fluorinated alkyl group orientation arrangement) forms an anti-pollution barrier to prevent the attenuation of electrical conductivity caused by environmental factors such as sweat and grease.

[0053] In this embodiment, specifically, step S4 specifically includes the following steps: S41, Integrate a micro impedance sensor at the end of the conductive channel of the plastic induction preform in a detachable manner, and encapsulate a flexible circuit board to form an embedded monitoring node; Adopt a detachable micro impedance sensor integration scheme, temporarily fix the sensor through magnetic contacts or conductive adhesives, which not only ensures the stable contact between the monitoring node and the conductive channel but also avoids the thermal damage to the flexible substrate caused by permanent welding. The flexible circuit board is encapsulated with a polyimide substrate (such as a thickness of 50 μm), and its low modulus characteristic (≈3 GPa) is elastically matched with the preform to prevent interface peeling during bending. This design realizes the modularization and reusability of the monitoring module.

[0054] S42, Connect the embedded monitoring node to a high-speed data connector to collect the time-series data of the electric field strength, melt pressure, and conductive channel impedance value in the injection molding stage in real time.

[0055] S43, Construct a process feature matrix based on multi-source data fusion, adopt an adaptive random forest algorithm to establish a mapping model between material conductivity and process parameters, dynamically predict the optimal electric field strength threshold and pressure compensation coefficient, and obtain optimized parameters; The process feature matrix integrates multi-dimensional data in the time domain (pressure gradient, electric field volatility) and frequency domain (impedance spectrum phase angle). After dimensionality reduction by principal component analysis (PCA), it is input into the adaptive random forest model. This model introduces a dynamic feature weight adjustment mechanism (such as the initial weight of conductivity-related features is set to 60%), combined with an incremental learning strategy. After each batch of data is input, the node splitting rule is automatically updated to realize the online iterative optimization of process parameters, improving the prediction accuracy and working condition adaptability.

[0056] S44, Simulate and verify the optimized parameters through a digital twin system, and screen out the parameter combination with the highest verification effect index; The digital twin system constructs a multi-physics coupling model based on COMSOL Multiphysics, injecting process fluctuations of ±5% (such as random offsets in electric field strength and transient changes in melt temperature) to simulate actual production disturbances. The verification effect index is comprehensively calculated by weighting and evaluating the conductivity channel linearity (weight 40%), impedance stability (weight 30%), and fatigue life (weight 30%), screening parameter combinations with a fault tolerance rate > 95% to ensure the reliability of the optimization scheme under non-ideal conditions.

[0057] S45, encrypt the verified optimized parameters and write them into the process database, and generate a dynamic adjustment instruction set to feedback to the injection molding machine control system, and synchronously update the masterbatch ratio recommendation scheme.

[0058] The optimized parameters are encrypted by AES-256 and written into the process database to prevent data tampering; the dynamic adjustment instruction set is sent to the injection molding machine PLC in real time through the OPC UA protocol to achieve a millisecond-level response (delay < 50ms) of the electric field strength and injection pressure. The masterbatch ratio recommendation scheme is generated based on the material-process association rule library (for example, for every 10% increase in conductivity, the proportion of metal powder needs to increase by 2%), forming a cross-process closed-loop optimization link to improve the overall process coordination efficiency.

[0059] Example Two: Combined with Figure 3 and Figure 4 As shown, the present invention also provides a plastic induction frame for smart glasses, including the plastic induction frame material of the smart glasses mentioned in Example One. The plastic induction frame material is processed into the main frame 10 of the smart glasses. The plastic induction frame 10 further includes: A flexible circuit board assembly 20, connected to the conductive channels of the plastic induction frame through conductive glue to form a closed-loop capacitance detection circuit.

[0060] A functionalized contact area 30, configured as an elastic contact interface adapted to the wearer's facial contour to achieve dynamic perception of pressure distribution and deformation signals.

[0061] Example Three: Combined with Figure 3 , the present invention also provides a pair of smart glasses, including lenses and the plastic induction frame of the smart glasses in Example Two. The lenses are myopia lenses or optical lenses with light screening.

[0062] I. Adaptive Plastic Deformation and Structural Stability The plastic-sensing framework is designed based on gradient conductive elastic materials and a dynamic crosslinking network, achieving plasticity and self-adaptability similar to that of plasticine. When the user manually bends or adjusts the frame angle, the high-modulus conductive layer on the surface of the frame provides shape-retaining force, while the low-modulus elastic matrix inside absorbs deformation stress through the reversible fracture-recombination mechanism of dynamic crosslinking bonds (such as disulfide bonds), enabling the frame to maintain the preset shape after the external force is removed. At the same time, the interpenetrating structure of carbon nanotubes and metal powder in the conductive network repairs microcracks through dynamic bond recombination during the deformation process, ensuring the continuity of the conductive channels, controlling resistance fluctuations, and taking into account both mechanical shaping and electrical stability.

[0063] II. Bio-Sensing and Wearing State Detection Mechanism The frame realizes non-invasive biological monitoring through a capacitance-impedance dual-mode sensing system. The flexible circuit board and the conductive channels are connected by conductive adhesive to form a "frame-skin-circuit" closed-loop circuit. When not worn, the air dielectric layer results in an extremely low capacitance value; after wearing, the skin contacts the functionalized area (the micro-nano rough surface enhances the contact area), and the capacitance value increases significantly, triggering the power-on command and activating the biological sensing function. Physiological signals are captured in real time through the impedance change of the conductive channels: heart rate detection relies on the impedance fluctuation of the microvascular pulsation at the temple, and fatigue monitoring analyzes the time-frequency characteristics of the electromyogram signals around the eyes (such as the blink frequency and intensity), and combines with a machine learning model to output a health status assessment, achieving invisible health monitoring.

[0064] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A manufacturing method of a plastic induction frame material for smart glasses, characterized in that, It includes the following steps: Composite carbon nanotubes, metal powder and a thermoplastic elastomer substrate through a segmented internal mixing process to form a gradient conductive elastic masterbatch with a phase-separated distribution of a surface conductive layer and an inner elastic layer; Inject the gradient conductive elastic masterbatch into a multi-layer injection mold and form a plastic induction preform with a directional conductive channel through an electric field-assisted injection process; Perform surface functionalization treatment on the plastic induction preform, form a conductive channel with a micro-nano rough structure through plasma etching, and impregnate a dynamic crosslinking agent to construct an interface strengthening layer; Integrate an impedance monitoring module at the end of the conductive channel of the plastic induction preform, establish a material-process parameter mapping model, optimize the electric field parameters and injection pressure through real-time data feedback, and obtain an optimized plastic induction preform; Assemble the optimized plastic induction preform with a flexible circuit board, fill a conductive adhesive at the contact interface to form a complete capacitance circuit, and obtain a plastic induction frame substrate with an integrated capacitance detection function.

2. The manufacturing method of the plastic induction frame material of the smart glasses according to claim 1, characterized in that, The carbon nanotubes are any one of single-walled carbon nanotubes, multi-walled carbon nanotubes or amino-modified carbon nanotubes; The metal powder is any one of spherical silver powder, flaky copper powder, nickel powder or silver-coated copper powder; The thermoplastic elastomer substrate is any one of SEBS-based TPE, TPU or SBS.

3. The manufacturing method of the plastic induction frame material of the smart glasses according to claim 2, characterized in that, The mass percentages of the carbon nanotubes, metal powder and thermoplastic elastomer substrate are: 5-40% for carbon nanotubes, 10-30% for metal powder, and the balance is the thermoplastic elastomer substrate.

4. The manufacturing method of the plastic induction frame material of the smart glasses according to claim 1, characterized in that, The process of forming a gradient conductive elastic masterbatch with a phase-separated distribution of a surface conductive layer and an inner elastic layer by composite carbon nanotubes, metal powder and a thermoplastic elastomer substrate through a segmented internal mixing process specifically includes: Modify the carbon nanotubes by silane coupling agent treatment, screen the metal powder to a preset particle size by ball milling, and pre-dry and pre-treat the thermoplastic elastomer substrate to a target moisture content; Put the pre-treated thermoplastic elastomer substrate and modified carbon nanotubes into an internal mixer, and internally mix at 160-170°C for 5-8 minutes to form a matrix melt phase with pre-dispersed conductive phases; Gradually add the metal powder to the matrix melt phase in three steps, with an interval of 1-2 minutes each time, and continue to internally mix at 180-190°C for 10-15 minutes to form a composite melt with interpenetrating conductive networks; Transfer the composite melt to a two-stage twin-screw extruder, inject a dynamic crosslinking agent into the second-stage screw, and realize the extrusion of phase-separated masterbatch of the surface conductive layer and the inner elastic layer through temperature zone control; among them, the temperature zones are zone 1 at 175°C / zone 2 at 195°C; Perform secondary coating on the extruded masterbatch through a fluidized bed, and use atomized spraying of metal powder and elastomer solution to form a functional surface layer with a preset thickness to obtain a gradient conductive elastic masterbatch.

5. The manufacturing method of the plastic induction frame material of the smart glasses according to claim 1, characterized in that, Inject the gradient conductive elastic masterbatch into a multi-layer injection mold and form a plastic induction preform with a directional conductive channel through an electric field-assisted injection process, which specifically includes the following steps: Preheat the multi-layer injection mold to 80-100°C on the conductive layer side and 40-60°C on the elastic layer side, and etch a conductive groove with a width of 20-50 μm on the cavity surface; Put the gradient conductive elastic masterbatch into a two-channel injection molding machine, control the temperature of the conductive runner at 200 - 210 °C and the temperature of the elastic runner at 170 - 180 °C, and achieve melt phase separation flow through the shear rate gradient; Apply an axial pulsed electric field with the first electric field strength during the injection stage to make the conductive particles in the masterbatch migrate directionally along the conductive grooves, and synchronously apply a radial shear field to suppress the anisotropy of the conductive network; Maintain the second electric field strength during the pressure holding stage and cooperate with the mold temperature gradient control. After cooling and demolding, a plastic induction preform with directional conductive channels is obtained; wherein, the first electric field strength is much greater than the second electric field strength.

6. The manufacturing method of the plastic induction frame material of the smart glasses according to claim 1, characterized in that, Perform surface functionalization treatment on the plastic induction preform, form conductive channels with micro-nano rough structures through plasma etching, and impregnate with a dynamic crosslinking agent to construct an interface strengthening layer, which specifically includes the following steps: Place the plastic induction preform in an ultrasonic cleaning device, clean the surface with a mixed solution of isopropyl alcohol and deionized water, and perform drying treatment in a vacuum drying oven; Load the cleaned plastic induction preform into a plasma processing chamber, introduce a mixed gas of argon and carbon tetrafluoride with a ratio of 9:1, and perform pulsed plasma etching under preset conditions to form a fractal microstructure with a preset depth on the surface of the conductive channels; Adopt a mask-assisted laser ablation technique to process array grooves with a preset width on the surface of the etched conductive channels, and cover a graphene quantum dot enhancement layer on the inner wall of the array grooves; Immerse the preform in a dynamic crosslinking agent solution containing thiosulfate-based siloxane, and achieve gradient penetration of the crosslinking agent under the alternating action of ultrasonic vibration and negative pressure.

7. The manufacturing method of the plastic induction frame material of the smart glasses according to claim 6, characterized in that, After immersing the preform in the dynamic crosslinking agent solution containing thiosulfate-based siloxane and achieving gradient penetration of the crosslinking agent under the alternating action of ultrasonic vibration and negative pressure, it further includes: Place the penetrated preform under a UV-infrared composite light source for curing. First, irradiate with ultraviolet light with a wavelength of 365 nm for the first duration to initiate surface crosslinking, and then switch to infrared light with a wavelength of 850 nm to irradiate for the second duration to activate deep-layer dynamic bond recombination; Perform helium protection annealing treatment on the cured preform, and spray a hydrophobic protective film containing fluorosilane after annealing.

8. The manufacturing method of the plastic induction frame material of the smart glasses according to claim 1, characterized in that, Integrate an impedance monitoring module at the end of the conductive channels of the plastic induction preform, establish a material-process parameter mapping model, and optimize the electric field parameters and injection pressure through real-time data feedback to obtain an optimized plastic induction preform, which specifically includes the following steps: Integrate a micro impedance sensor at the end of the conductive channels of the plastic induction preform in a detachable manner, and encapsulate a flexible circuit board to form an embedded monitoring node; Connect the embedded monitoring node to a high-speed data connector, and collect the timing data of the electric field strength, melt pressure, and conductive channel impedance value during the injection molding stage in real time; Construct a process feature matrix based on multi-source data fusion, adopt an adaptive random forest algorithm to establish a material conductivity-process parameter mapping model, dynamically predict the optimal electric field strength threshold and pressure compensation coefficient, and obtain optimized parameters; Verify the optimized parameters through a digital twin system, and screen out the parameter combination with the highest verification effect index; Encrypt and write the verified optimized parameters into the process database, generate a dynamic adjustment instruction set and feedback it to the injection molding machine control system, and synchronously update the masterbatch ratio recommendation scheme.

9. A plastic induction frame for smart glasses, characterized in that, It includes a plastic induction frame material of the smart glasses according to any one of claims 1 to 8, the plastic induction frame material is processed into the main frame of the smart glasses, and the plastic induction frame further includes: A flexible circuit board assembly, which is connected to the conductive channels of the plastic induction frame through conductive glue to form a closed-loop capacitance detection circuit; A functional contact area, configured as an elastic contact interface adapted to the wearer's facial contour, to realize the dynamic perception of pressure distribution and deformation signals.

10. An intelligent glasses, characterized in that, It includes lenses and a plastic induction frame of the smart glasses according to claim 9, and the lenses are myopia lenses or optical lenses with light screening.

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