Piezoelectric tactile sensor, method of manufacturing and use thereof

Abstract

The application discloses a piezoelectric tactile sensor, which comprises at least one first conductive layer containing graphene and one second conductive layer; a programmable shape memory polymer matrix, in which polarizable zinc oxide nanoparticles are dispersed; the programmable shape memory polymer matrix is arranged between the first conductive layer and the second conductive layer, so that the sensor can generate an electric signal under mechanical stress; the programmable shape memory polymer matrix can present at least two different programmed mechanical states under external stimulation, so that the same tactile stimulation applied to the sensor can generate a plurality of different piezoelectric signals, and the different piezoelectric signals correspond to different programmed mechanical states of the programmable shape memory polymer matrix. Meanwhile, a manufacturing method of the sensor and an application thereof are provided; and the application can realize more accurate material identification, defect detection and mechanical parameter estimation.

Description

Technical Field

[0001] This invention relates to the field of flexible piezoelectric sensor technology, and in particular to a piezoelectric tactile sensor, its manufacturing method, and its application. Background Technology

[0002] Flexible piezoelectric sensors have been a subject of extensive research, particularly those based on polymer composites doped with metal oxide nanoparticles, such as ZnO (zinc oxide), capable of converting mechanical stress into usable electrical signals. One of the most common architectures relies on a soft polydimethylsiloxane (PDMS) matrix in which ZnO nanoparticles and graphene are dispersed, forming a thin film sandwiched between two conductive electrodes. In such devices, ZnO constitutes the active piezoelectric phase, while PDMS provides flexibility and mechanical compliance. Graphene ensures efficient charge transport.

[0003] Other synthetic studies confirm that most current architectures are still based on passive polymer matrices: their stiffness, curvature, and geometry remain fixed during measurement, clearly pointing to the limitations of such materials in applications requiring evolving tactile interactions, mechanical adaptations, or active probing of complex surfaces.

[0004] Meanwhile, existing technologies have been extensively studied and improved for inherent piezoelectric polymers such as polyvinylidene fluoride (PVDF), such as improving the β phase and piezoelectric properties of PVDF and optimizing PVDF structures for mechanical energy harvesting. However, these systems lack any mechanical reprogrammability, and their geometry or elastic modulus remains unchanged after manufacturing.

[0005] Furthermore, in another technological direction, existing technologies utilize sensors with flexible hybrid electrodes (such as silver nanowires combined with conductive polymers) for biomechanical monitoring. While these sensors exhibit good performance in muscle monitoring, they are entirely dependent on environmental deformation and lack the ability to actively alter the mechanical state of the sensor itself. For example, patent CN110031135B describes a flexible capacitive sensor based on structured dielectrics and graphene electrodes. Although it explores complex geometries and advanced conductive materials, it does not involve ZnO-dispersed piezoelectric composites or programmable polymer matrices.

[0006] Therefore, a major limitation exists for PDMS / ZnO composites, electrospun PVDF films, flexible hybrid electrodes, and capacitive sensors: they all rely on mechanically passive materials and architectures. There are no programmed or programmable polymer matrices whose stiffness, curvature, thickness, or shape can be modified in response to external stimuli. There are no materials that combine the piezoelectricity of ZnO, the conductivity of graphene, and the shape memory effect of polymers to achieve multiple sequential tactile features through controlled mechanical states. Summary of the Invention

[0007] The purpose of this invention is to overcome the above-mentioned defects in the prior art and provide a piezoelectric tactile sensor. This invention can perform measurements in multiple programmed states, generate rich piezoelectric features, and achieve more precise material identification, defect detection, and estimation of mechanical parameters.

[0008] To achieve the above objectives, the present invention provides a piezoelectric tactile sensor, comprising:

[0009] At least one first conductive layer comprising graphene and one second conductive layer;

[0010] A programmable shape memory polymer matrix, in which polarizable zinc oxide nanoparticles are dispersed; the programmable shape memory polymer matrix is ​​placed between a first conductive layer and a second conductive layer, so that the sensor is subjected to mechanical stress and generates an electrical signal.

[0011] The programmable shape memory polymer matrix can exhibit at least two different programmed mechanical states under external stimulation, so that the same tactile stimulus applied to the sensor can generate multiple different piezoelectric signals, and the different piezoelectric signals correspond to different programmed mechanical states of the programmable shape memory polymer matrix.

[0012] Furthermore, the programmable mechanical states exhibited by the programmable shape memory polymer matrix include a compliant state, a rigid state, two different curvature geometries, and / or two different effective thicknesses.

[0013] Furthermore, the programmable shape memory polymer matrix is ​​a thermosetting polyurethane shape memory polymer, an epoxy resin-based shape memory crosslinking network, or an acrylate-based shape memory crosslinking network.

[0014] Furthermore, the thermosetting polyurethane shape memory polymer is formed by crosslinking a polyurethane prepolymer containing isocyanate end groups with a low molecular weight diol or triol chain extender or crosslinking agent; the mass ratio of the polyurethane prepolymer to the low molecular weight diol or triol chain extender or crosslinking agent is 95:5~70:30.

[0015] Furthermore, the epoxy resin-based shape memory network is formed by the reaction of epoxy oligomers and amine curing agents, wherein the mass ratio of epoxy oligomers to curing agents is 100:10 to 100:40.

[0016] Furthermore, the acrylate-based shape memory network is prepared by reacting acrylate or polyurethane acrylate oligomers with a free radical curing system; the mass ratio of the oligomer to the initiator system is 99:1 to 95:5.

[0017] Furthermore, the mass ratio of the programmable shape memory polymer matrix to zinc oxide nanoparticles is 95:5 to 60:40.

[0018] The present invention also provides a method for manufacturing a piezoelectric tactile sensor, comprising the following steps:

[0019] S1. Precursor for preparing programmable shape memory polymer matrix is ​​first prepared by mixing shape memory oligomer or prepolymer with its corresponding crosslinking agent or curing agent in the corresponding mass ratio.

[0020] S2. During the stirring process in S1, an appropriate amount of zinc oxide nanoparticles are gradually added to the precursor until they are fully stirred and homogeneous. Then, vacuum degassing is performed to remove air bubbles, resulting in a composite mixture.

[0021] S3. Place the composite mixture in a flat mold, and after curing, form a composite film. Then, perform a shape memory programming step, heat the composite film to above its transition temperature, and then mechanically deform it to define the desired temporary shape. While maintaining the deformation, cool the film to fix the temporary shape.

[0022] S4. Finally, a first conductive layer containing at least one graphene layer and a second conductive layer are deposited on both sides of the composite film.

[0023] Furthermore, in step S2, ultrasonic treatment, the addition of surfactants or suitable surface compatibilizers are employed during the stirring process to improve the dispersibility of zinc oxide nanoparticles and precursors during mixing and to limit agglomeration.

[0024] Furthermore, in step S3, after the composite film is formed, while the composite film is kept at a suitable temperature, an electric field is applied between temporary or permanent electrodes to cause the dipoles inside the zinc oxide nanoparticles to align in an oriented manner.

[0025] A material analysis method using the aforementioned piezoelectric tactile sensor includes applying the sensor to the material to be analyzed; measuring a first piezoelectric signal in a first mechanical state of the shape memory polymer matrix; activating the matrix to transition it to at least one second programmed mechanical state; measuring at least one second piezoelectric signal; and comparing the obtained signals to derive at least one piece of information about the properties, stiffness, roughness, or internal structure of the material being analyzed.

[0026] An application of a piezoelectric tactile sensor in a robotic grasping system, smart gloves, medical palpation devices, structural monitoring systems, or non-destructive testing equipment, wherein the piezoelectric tactile sensor is used as an active tactile detection device.

[0027] The shape memory polymer matrix of the present invention differs fundamentally from the passive elastomer matrix because it possesses at least two different stable mechanical states, such as a "soft" state and a "rigid" state, or two different curvature geometries, which can be switched in a controllable manner by external stimuli.

[0028] The aforementioned external stimuli can be Joule heating of the graphene-based conductive layer, external thermal control, or the application of an appropriate electric field, thereby enabling the mechanical state of the shape memory polymer matrix to be programmed and controlled independently of the mechanical loads applied by the environment or on this basis.

[0029] The shape memory polymer matrix contains dispersed and selectively polarized zinc oxide nanoparticles, which constitute the active phase and generate electrical signals in response to stress changes. A graphene-based conductive network or graphene top electrode is responsible for charge collection and signal transmission to the readout electronics. This design enables the sensor to simultaneously achieve tactile perception and adaptive state adjustment during deformation, significantly improving the real-time performance and accuracy of human-computer interaction.

[0030] Therefore, this sensor can operate in two modes. In passive mode, it behaves similarly to a traditional tactile sensor: when the external surface is pressed, the ZnO generates a voltage that is measured between the electrodes. In active mode, the PMF matrix can be driven to change its mechanical state during or between measurements. This change adjusts the way the sensor presses against the contacted surface, resulting in characteristic changes in the piezoelectric signal. By comparing the signals obtained under different programming states, additional information about the properties and structure of the measured material can be obtained, enabling analysis of material information.

[0031] The present invention forms an "active tactile eye" that can not only sense but also modify its stiffness, curvature, thickness or shape in response to external stimuli. It actively queries the environment through programmed deformation sequences, and endows the sensor with the synergistic effect of ZnO piezoelectricity and graphene conductivity to achieve measurement in a programmed state, generating rich piezoelectric features. This enables more precise material identification, defect detection and estimation of mechanical parameters (such as roughness or stiffness). Attached Figure Description

[0032] To more clearly illustrate the technology in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0033] Figure 1 This is a schematic diagram of the structure of a piezoelectric tactile sensor according to the present invention;

[0034] Figure 2 This is a schematic diagram of another embodiment of the present invention;

[0035] Figure 3 This is a flowchart of the manufacturing method of the invented piezoelectric tactile sensor;

[0036] Figure 4 This is a schematic diagram of the operation of the present invention in active mode.

[0037] The diagram includes:

[0038] 1. First conductive layer; 2. Second conductive layer; 3. Programmable shape memory polymer matrix; 4. Zinc oxide nanoparticles; 5. First substrate; 6. Second substrate. Detailed Implementation

[0039] The technology of this embodiment of the invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiment is one embodiment of the invention, and not all embodiments. Based on this embodiment of the invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0040] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indication will also change accordingly.

[0041] Furthermore, if the embodiments of the present invention involve descriptions such as "first" or "second", such descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated.

[0042] like Figures 1 to 4 The present invention discloses a piezoelectric tactile sensor, comprising:

[0043] At least one first conductive layer 1 comprising graphene and one second conductive layer 2;

[0044] A programmable shape memory polymer matrix 3 contains polarizable zinc oxide nanoparticles 4 dispersed within it, forming an active phase capable of generating electrical signals under stress changes. The programmable shape memory polymer matrix 3 is positioned between a first conductive layer 1 and a second conductive layer 2. Preferably, the piezoelectric tactile sensor of the present invention is fabricated as a thin-film structure. When the first conductive layer 1 or the second conductive layer 2 containing graphene in this embodiment is subjected to mechanical stress, the sensor generates an electrical signal due to the mechanical stress. The programmable shape memory polymer matrix 3 can exhibit at least two different programmable mechanical states under external stimulation, allowing the same tactile stimulus applied to the sensor to generate multiple different piezoelectric signals. These different piezoelectric signals correspond to different programmable mechanical states of the programmable shape memory polymer matrix 3. The programmable morphology exhibited by the programmable shape memory polymer matrix 3 includes a compliant state, a rigid state, two different curvature geometries, and / or two different effective thicknesses.

[0045] In this embodiment, the mass ratio of the programmable shape memory polymer matrix 3 to zinc oxide nanoparticles 4 is 95:5 to 60:40. The average particle size of the zinc oxide nanoparticles 4 in this embodiment is controlled between 30 and 50 nm, preferably using zinc oxide nanoparticles 4 with an average particle size of about 30 nm, which are uniformly dispersed in the programmable shape memory polymer matrix 3. The selection of their mass fraction is intended to provide a satisfactory trade-off between piezoelectric sensitivity, flexibility, and the mechanical integrity of the composite material. It should be noted that the above mass ratio is a preferred ratio, and these values ​​are given as non-limiting examples, because particle size, morphology, and fraction can be adjusted according to the intended application without departing from the scope of the invention.

[0046] Meanwhile, the zinc oxide nanoparticles 4 have dipoles arranged in a directional manner inside, thereby optimizing the piezoelectric response performance.

[0047] In this embodiment, the programmable shape memory polymer matrix 3 can be prepared by three systems of shape memory oligomers or prepolymers and their corresponding crosslinking agents / curing agents, namely, the programmable shape memory polymer matrix 3 is a thermosetting polyurethane shape memory polymer or a shape memory crosslinking network based on epoxy resin or a shape memory crosslinking network based on acrylate.

[0048] In the first system, the programmable shape memory polymer matrix 3 is a thermosetting polyurethane shape memory polymer, which is formed by crosslinking a polyurethane prepolymer containing isocyanate end groups with a low molecular weight diol or triol chain extender or crosslinking agent; the mass ratio of the polyurethane prepolymer to the low molecular weight diol or triol chain extender or crosslinking agent is 95:5~70:30.

[0049] In the second system, the programmable shape memory polymer matrix 3 is an epoxy resin-based shape memory network, which is formed by the reaction of epoxy oligomers and amine curing agents, and the mass ratio of epoxy oligomers to curing agents is 100:10 to 100:40.

[0050] In the third system, the programmable shape memory polymer matrix 3 is an acrylate-based shape memory network, which is prepared by reacting acrylate or polyurethane acrylate oligomers with a free radical curing system; in this system, the mass ratio of acrylate or polyurethane acrylate oligomers to the initiator system is 99:1 to 95:5.

[0051] All three systems can achieve stable coating and interfacial compatibility of ZnO nanoparticles, while possessing the controllable shape memory response and piezoelectric coupling characteristics required by this invention.

[0052] In this embodiment, a first conductive layer 1 of graphene material is deposited on the upper surface of the programmable shape memory polymer substrate 3. The first conductive layer 1 is preferably a thin graphene layer or a graphene / polymer composite material deposited on the surface of the programmable shape memory polymer substrate 3. This electrode serves as both a piezoelectric charge collector and, in some variations, a resistance heater to activate the shape memory effect of the programmable shape memory polymer substrate 3 through Joule heating. Graphene can be obtained by transferring CVD-grown thin films, printing graphene-based inks, or spraying water-based or organic suspensions. The second conductive layer 2 is disposed on the lower surface of the programmable shape memory polymer substrate 3. The second conductive layer 2 can be formed by a metal layer, a transparent conductive oxide, or another graphene layer deposited on the lower surface of the programmable shape memory polymer substrate 3. The metal layer can be composed of metal materials such as Au, Ag, Cu, and Al.

[0053] Therefore, when mechanical stress is applied to the plane of the sensor, ZnO nanoparticles generate a potential difference between the electrodes. Graphene enables rapid charge transport while maintaining low impedance, thereby improving the signal-to-noise ratio and high-frequency stability. The programmable shape memory polymer matrix 3, while transferring stress to the nanoparticles, possesses high deformability, ensuring good contact with the test material even on curved or irregular surfaces.

[0054] Preferably, the second conductive layer 2 disposed on the lower end face has two disposal methods: one is to directly integrate it into the programmable shape memory polymer substrate 3 to form a fully encapsulated embedded structure; the other is to deposit it on the outer bottom surface of the programmable shape memory polymer substrate 3 to form an interface planar electrode.

[0055] When the second conductive layer 2 is integrated inside the programmable shape memory polymer matrix 3, conductive films, conductive grids, grid networks or patterned conductive networks can be embedded simultaneously during the casting and curing process of the programmable shape memory polymer matrix 3, and exposed pads can be brought out for electrical connection. The conductive film can be graphene, carbon-based coating or metal film, etc.

[0056] When the second conductive layer 2 is deposited on the outer bottom surface of the programmable shape memory polymer substrate 3, it forms a planar contact interface with the second substrate 6. This structure simplifies the process flow and facilitates modular integration and electrode replacement. The two configurations of the second conductive layer 2 differ in the following ways: the location of the conductive interface differs—the internal embedded interface is a fully encapsulated structure, while the externally deposited interface is a laminated structure; the interface contact type differs—the former is an embedded interface, while the latter is a laminated interface; the mechanical strain distribution also differs—the embedded electrode deforms in tandem with the programmable shape memory polymer substrate 3, while the external electrode bears boundary shear stress. Thus, each method has its advantages. The embedded electrode configuration has stronger resistance to delamination and cracking under repeated bending and compression conditions, better protects the electrode from environmental corrosion, and achieves more stable charge collection under cyclic loading. The bottom-deposited electrode configuration has the advantages of simple manufacturing process, easier integration with standard substrates, and convenient electrical interconnection and replacement at the module level. Therefore, in practical applications, embedded or bottom-deposited electrode structures can be flexibly selected according to the reliability requirements, environmental tolerance requirements and mass production cost constraints of the specific application scenario. For highly flexible and long-cycle service scenarios such as wearable electronics or implantable sensors, embedded electrodes are preferred to ensure structural integrity and signal stability. For industrial monitoring systems that require rapid prototyping, multi-sensor array integration or frequent replacement and maintenance, bottom-deposited electrode solutions are preferred.

[0057] Preferably, a readout circuit is also provided. This readout circuit is preferably integrated into the second conductive layer 2 on the lower end face, or it can be a dedicated readout circuit. This readout circuit is electrically connected to the first conductive layer 1 and the second conductive layer 2. The graphene-based first conductive layer 1 is responsible for charge collection and signal transmission to the readout circuit, realizing signal acquisition and processing. The circuit includes a signal conditioning circuit, an acquisition circuit, and an optional heating control circuit for thermally activating the shape memory effect. The heating control circuit precisely adjusts the Joule heating power so that the programmable shape memory polymer matrix 3 can be stably heated to the transition temperature range of 25~80℃ at room temperature, ensuring that the temporary shape is fully recovered within a millisecond response. At the same time, the signal conditioning circuit has an adaptive gain adjustment function, which can dynamically match the weak charge signals output by ZnO nanoparticles at different strain rates, significantly suppressing low-frequency drift and thermal noise interference.

[0058] In some implementations, such as Figure 2As shown, to better enhance the expandable functionality of the invention, a first substrate 5 and a second substrate 6 are also included. The piezoelectric tactile sensor is disposed between the first substrate 5 and the second substrate 6. The first substrate 5 and the second substrate 6 form a flexible encapsulation structure, which collaboratively constrains the deformation boundary of the programmable shape memory polymer matrix 3 and enhances mechanical robustness. The first substrate 5 and the second substrate 6 can be made of flexible materials, such as polymer films, polyimide, or PET, or they can be made of slightly rigid materials, such as glass or thin metal substrates, with a thickness controlled between 25 and 100 μm to balance flexibility and optical transparency. The specific material selection needs to be weighed according to the actual application scenario. For example, electronic skin requires high transparency and fit, so ultra-thin polyimide with a thickness of 12 to 25 μm is preferred; robot fingers focus on scratch resistance and structural support, so 50 to 100 μm PET or ITO-coated flexible glass are used.

[0059] Furthermore, the second conductive layer 2 and the readout circuit can both be integrated on the inner surface of the second substrate 6, and flexible interconnect lines can be constructed through micro-nano imprinting or laser direct writing processes to achieve seamless integration of electrodes and circuits.

[0060] like Figure 3 As shown, this embodiment also provides a method for manufacturing a piezoelectric tactile sensor, including the following steps:

[0061] S1. To prepare the precursor of the programmable shape memory polymer matrix 3, the shape memory oligomer or prepolymer is first mixed with its corresponding crosslinking agent or curing agent in the corresponding mass ratio.

[0062] Specifically, in this embodiment, the programmable shape memory polymer matrix 3 can be prepared by three systems of shape memory oligomers or prepolymers and their corresponding crosslinking agents / curing agents, namely, the programmable shape memory polymer matrix 3 is a thermosetting polyurethane shape memory polymer or a shape memory crosslinking network based on epoxy resin or a shape memory crosslinking network based on acrylate.

[0063] In the first system, the programmable shape memory polymer matrix 3 is a thermosetting polyurethane shape memory polymer, which is formed by crosslinking a polyurethane prepolymer containing isocyanate end groups with a low molecular weight diol or triol chain extender or crosslinking agent; the mass ratio of the polyurethane prepolymer to the low molecular weight diol or triol chain extender or crosslinking agent is 95:5~70:30.

[0064] In the second system, the programmable shape memory polymer matrix 3 is an epoxy resin-based shape memory network, which is formed by the reaction of epoxy oligomers and amine curing agents, and the mass ratio of epoxy oligomers to curing agents is 100:10 to 100:40.

[0065] In the third system, the programmable shape memory polymer matrix 3 is an acrylate-based shape memory network, which is prepared by reacting acrylate or polyurethane acrylate oligomers with a free radical curing system; in this system, the mass ratio of acrylate or polyurethane acrylate oligomers to the initiator system is 99:1 to 95:5.

[0066] First, select any one of the three systems mentioned above, and mix the corresponding shape memory oligomer or prepolymer with its corresponding crosslinking agent or curing agent according to the mass ratio determined by the chemical properties of the selected system. The mixing process is carried out at a uniform speed of 300~600 rpm for 20~40 minutes under mechanical stirring to obtain a uniform precursor with a viscosity of 800~1500 mPa·s.

[0067] S2. During the stirring process in S1, an appropriate amount of zinc oxide nanoparticles 4 are gradually added to the precursor until they are fully stirred and homogeneous. Then, vacuum degassing is performed to remove air bubbles, and a composite mixture is obtained.

[0068] Specifically, zinc oxide nanoparticles 4 are selected, preferably spherical with an average particle size of 30 nm, and are vacuum dried at 105 °C for 2 h to remove adsorbed water; they are added in batches under mechanical stirring, with an interval of 5 minutes between each batch, and the total addition time is controlled within 15~20 minutes.

[0069] Preferably, the mass ratio of PMF precursor to zinc oxide nanoparticles 4 is 95:5 to 60:40, corresponding to a zinc oxide content of 5 wt.% to 40 wt.% in the composite material; when both flexibility and electromechanical response characteristics need to be considered, the preferred ratio is 85:15 to 70:30.

[0070] Ultrasonic treatment, the addition of surfactants or suitable surface compatibilizers during the stirring process are employed to improve the dispersibility of zinc oxide nanoparticles 4 and precursors during mixing and to limit agglomeration.

[0071] If ultrasonic treatment is used, it can be performed at an ultrasonic frequency of 40 kHz for 30 to 60 minutes, with the power density maintained at 80 to 120 W / L, to ensure that ZnO is uniformly dispersed and without significant agglomeration.

[0072] When adding a surface compatibilizer, the following can be selected: 1. Organosilanes suitable for oxide surface coupling, such as (3-aminopropyl)triethoxysilane (APTES) and (3-glycidoxypropyl)trimethoxysilane (GPTMS), with an addition amount of 0.1 wt.% to 1.0 wt.% of the programmable shape memory polymer matrix.

[0073] 2. Select a polymer dispersant, such as polyvinylpyrrolidone (PVP), and add it at a rate of 0.2 wt.% to 2.0 wt.% of the weight of the programmable shape memory polymer matrix 3. The compatibilizer can be incorporated into the PMF precursor before adding the zinc oxide nanoparticles 4, or used to pretreat the zinc oxide nanoparticles 4, and the agglomerates can be destroyed and the dispersion system can be stabilized by controlling the ultrasonic treatment time.

[0074] After the above treatment, ZnO is ensured to be uniformly dispersed at the nanoscale in the programmable shape memory polymer matrix 3, with strong interfacial bonding, no visible agglomerates and uniform viscosity. The composite mixture can then be transferred to a vacuum degassing machine and continuously degassed at -0.1 MPa for 15 to 30 minutes to completely eliminate micron-sized bubbles.

[0075] S3. Place the composite mixture in a flat mold, and after curing, form a composite film. Then, perform a shape memory programming step, heat the composite film to above its transition temperature, and then mechanically deform it to define the desired temporary shape. While maintaining the deformation, cool the film to fix the temporary shape.

[0076] Specifically, the bubble-free composite mixture is poured into a pre-prepared planar mold made of PTFE or non-stick silicone material, typically with a depth of about 0.1 to 1 mm, to allow the composite mixture to form a film of the required thickness. The film thickness can be adjusted according to application requirements: electronic skin requires an extremely thin structure of about 100 μm to ensure fit and sensitivity, while robotic fingers require a thickness of 0.5 to 1 mm to balance strength and deformation capacity. After the mold is placed in an oven, the temperature is gradually increased from 80 to 130 °C according to the crosslinking kinetics of the programmable shape memory polymer matrix, and maintained at a constant temperature for several minutes to several hours to ensure that the network is fully cured. After cooling to room temperature, the film is demolded, and the resulting composite film has stable mechanical properties and a reusable shape memory function.

[0077] At this point, the composite film can be programmed with shape memory: the composite film is heated to above its transition temperature and mechanically deformed, that is, an external force is applied to the composite film to form the desired temporary shape such as bending, stretching, local compression or surface relief, such as slight outward curvature or central bulge; then, while keeping the composite film deformed, it is slowly cooled to room temperature to stabilize and lock the temporary shape. The transition temperature is determined by the glass transition temperature (Tg) of the molecular chain segments of the programmable shape memory polymer matrix 3 and the microphase separation induced by ZnO filling, with a measured range of 48~56°C. Preferred embodiments include: (1) 75 / 25 PMF / ZnO ratio + 0.5wt.% APTES, programmed at 52°C to obtain a central convex structure, with a deformation recovery rate >98.3% after 10 cycles; (2) 70 / 30 ratio + 1.2wt.% PVP, stretched and programmed at 54°C, with the elongation at break increased to 1.8 times that of the original film; (3) 85 / 15 ratio + 0.3wt.% GPTMS, bent and programmed at 49°C, with a response time <8s. After programming, the film has the ability to respond to multimodal tactile feedback on demand; when a specific thermal stimulus or electrical excitation is applied, it can autonomously recover to the original flat configuration and synchronously output an electrical signal sequence strongly correlated with the deformation history.

[0078] Preferably, after forming the composite film but before shape memory programming, while maintaining the composite film at a suitable temperature, an electric field is applied between temporary or permanent electrodes to oriented the dipoles inside the zinc oxide nanoparticles 4, thereby optimizing the piezoelectric response, as follows:

[0079] The specific polarization parameters are set as follows: the electric field strength is set to a range of 0.5~3.0 kV / mm, and a controlled voltage boost method is used to achieve the target electric field to avoid dielectric breakdown; the film temperature needs to be maintained within a range of 10~30°C above the PMF transition temperature during polarization. For example, for a PMF system with a transition temperature in the range of 35~70°C, the typical polarization temperature is 60~90°C. The electric field is continuously applied for 10~60 minutes, and the electric field is maintained during cooling below the transition temperature to stabilize the polarization state.

[0080] S4. Finally, a first conductive layer 1 containing at least one graphene-containing layer 2 is deposited on both sides of the composite film.

[0081] Finally, a graphene layer is deposited on one side of the composite film. This can be achieved by transferring a CVD-grown graphene film, printing graphene-based conductive ink, or by spraying a suspension followed by mild annealing to improve conductivity. A bottom electrode is deposited on the opposite side or on a second substrate 6 of the film lamination, establishing an electrical connection with a readout circuit / electronic device. This readout circuit / electronic device includes a conditioning circuit, a data acquisition circuit, and optionally a heating control circuit for thermal activation of the shape memory effect. This yields the piezoelectric tactile sensor of the present invention.

[0082] Preferably, in shape memory programming, the programmable shape memory polymer matrix 3 can be continuously set to multiple different mechanical states, for example, sequentially switching between a compliant state → a rigid state → a curvature reversal state within a single measurement cycle, so that the same tactile stimulus excites three distinguishable piezoelectric signals; each state is maintained for a sufficient time to achieve mechanical and thermal stability before acquiring the detection signal; subsequently, the signals acquired in these different states are jointly analyzed to extract characteristic information representing the applied tactile stimulus, thereby eliminating transient effects associated with the activation of the programmable shape memory polymer matrix 3. This method improves the robustness, repeatability, and reliability of tactile measurement.

[0083] Based on the structure of the piezoelectric tactile sensor of the present invention, two triggering modes can be formed in actual use: passive mode and active mode.

[0084] In passive mode, the sensor operates similarly to conventional PDMS / ZnO / graphene sensors described in the prior art. For example... Figure 4 As shown, when pressure is applied to the surface of the composite film, charges are generated inside the ZnO nanoparticles, resulting in a voltage between the electrodes. By analyzing the signal amplitude, polarity, and time response, contact detection, estimation of applied pressure intensity, and differentiation of different materials can be achieved with appropriate signal processing.

[0085] In active mode, power is supplied to the graphene-based top electrode in a controlled manner to locally heat the programmable shape memory polymer matrix 3 above its transition temperature via the Joule effect. Under this stimulation, the programmable shape memory polymer matrix 3 transitions from one mechanical state to another, specifically from a more rigid state to a more flexible state, and vice versa, and may revert to its programmed initial shape or adopt a different curvature. Therefore, the sensor can modify its mechanical interaction with the opposing surface, particularly by altering the contact area, stress distribution, or local pressure concentration.

[0086] By repeating measurement sequences across multiple programmed mechanical states, the sensor generates a family of piezoelectric signals containing more information than a passive sensor. This information may be particularly relevant to variations in the apparent coefficient of friction under stiffness conditions, increased sensitivity to surface roughness when the matrix is ​​compliant, differentiated responses to different material stiffnesses when the matrix is ​​hardened, or the temporal evolution of compliance of biological tissues or polymer joints during loading and unloading cycles.

[0087] The resulting multi-state piezoelectric features can be analyzed using signal processing methods and suitable learning algorithms, thereby enabling more precise material identification, early defect or degradation detection (such as delamination, internal cavities or density loss), or evaluation of physical parameters such as roughness, thickness or adhesion.

[0088] For example, one implementation of an "active tactile eye" integrates sensors into the fingertips of a robotic arm. In a first mechanical state, a programmable shape memory polymer matrix 3 is compliant and conforms to the object's surface, providing a global mapping of contact pressure. In a second mechanical state, the matrix hardens, and the robot applies localized pressure, particularly through programmed curvature, thereby revealing local defects or internal stiffness gradients. By comparing the signals obtained in these different states, applications such as distinguishing between ripe and unripe fruit, detecting delamination defects beneath the surface of laminates, or characterizing the contents of flexible packaging without opening the packaging can be achieved.

[0089] Preferably, a control system can also be implemented to achieve automatic switching and closed-loop feedback in active mode, for executing a programmed sequence of changes in the mechanical state of the programmable shape memory polymer matrix 3 during or between measurement cycles.

[0090] Therefore, the piezoelectric tactile sensor of the present invention has the dual characteristics of a flexible piezoelectric sensor and a programmable material, and can be applied to many industrial sectors.

[0091] Therefore, the present invention also provides a material analysis method using the above-described piezoelectric tactile sensor, comprising: applying the sensor to the material to be analyzed; measuring a first piezoelectric signal in a first mechanical state of the shape memory polymer matrix; activating the matrix to transition it to at least one second programmed mechanical state; measuring at least one second piezoelectric signal; and comparing the obtained signals to derive at least one piece of information about the properties, stiffness, roughness, or internal structure of the material being analyzed.

[0092] An application of a piezoelectric tactile sensor in a robotic grasping system, a smart glove, a medical palpation device, a structural monitoring system, or a non-destructive testing device, wherein the piezoelectric tactile sensor is used as an active tactile detection device.

[0093] Specifically, it includes the following:

[0094] In robotic grasping applications, the piezoelectric tactile sensor of this invention can be integrated onto the surface of an end effector finger to enable adaptive grasping. The robot can first explore the object in a compliant mode to map its shape and contact pressure distribution, and then switch to a more rigid mode to test local resistance, detect vulnerable areas, or differentiate materials (such as plastics, metals, textiles, or wood) based on multi-state characteristics.

[0095] In smart gloves used for rehabilitation, virtual reality, or remote manipulation, piezoelectric tactile sensors can provide rich tactile feedback to users or therapists, offering information not only about the applied force but also about changes in the stiffness of the manipulated object. This enables, for example, the monitoring of progress in fine motor skills practice or the simulation of more realistic tactile sensations.

[0096] In the biomedical field, this piezoelectric tactile sensor can be used to assist in palpation and detection of stiffness changes in tissues or organs (such as the detection of nodules, masses, edematous areas, or fibrotic areas). Its programmability allows for, for example, the localization of pressure without increasing the total force applied by the hand or instruments, which may help reveal deeper abnormalities. The sensor can also be used to monitor wound healing or tissue healing by tracking the mechanical evolution of the medium over time.

[0097] In the non-destructive testing of composite structures, coatings, and joints, piezoelectric tactile sensors can be applied to sensitive areas and programmed to deform through cycles to detect microcracks, adhesion defects, delamination, or density loss. Compared to passive flexible piezoelectric sensors, the differential response between compliant and rigid states provides enhanced sensitivity to internal defects.

[0098] In the field of smart surfaces for construction, transportation, and aerospace, PMF / ZnO / graphene sensor networks can be integrated into electronic skin or multifunctional panels to simultaneously ensure impact detection, structural integrity monitoring, and local stiffness adaptation (e.g., damping vibrations or modulating the mechanical behavior of interfaces).

[0099] Finally, in human-machine interfaces, these sensors can be used on touchscreens or interactive surfaces, and their tactile responses (haptic feedback, surface relief perception) can be adapted to the usage scenario and user profile by combining piezoelectric sensing and reprogramming of surface geometry.

[0100] The compatibility of the manufacturing process with microfabrication technology, functional printing, and thin-film deposition enables integration into large-area distributed sensors, addressable matrix networks, and micro wearable devices, thus paving the way for a wide range of industrial applications.

[0101] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A piezoelectric tactile sensor, characterized in that, include: At least one first conductive layer (1) containing graphene and one second conductive layer (2); A programmable shape memory polymer matrix (3) is provided, in which polarizable zinc oxide nanoparticles (4) are dispersed; the programmable shape memory polymer matrix (3) is placed between a first conductive layer (1) and a second conductive layer (2), so that the sensor is subjected to mechanical stress and generates an electrical signal; The programmable shape memory polymer matrix (3) can present at least two different programmed mechanical states under external stimulation, so that the same tactile stimulation applied to the sensor can generate a variety of different piezoelectric signals, and the different piezoelectric signals correspond to different programmed mechanical states of the programmable shape memory polymer matrix (3).

2. The piezoelectric tactile sensor according to claim 1, characterized in that, The programmable mechanical states exhibited by the programmable shape memory polymer matrix (3) include a compliant state, a rigid state, two different curvature geometries, and / or two different effective thicknesses.

3. The piezoelectric tactile sensor according to claim 1, characterized in that, The programmable shape memory polymer matrix (3) is a thermosetting polyurethane shape memory polymer, or a shape memory crosslinking network based on epoxy resin, or a shape memory crosslinking network based on acrylate.

4. A piezoelectric tactile sensor according to claim 3, characterized in that, The thermosetting polyurethane shape memory polymer is formed by crosslinking a polyurethane prepolymer containing isocyanate end groups with a low molecular weight diol or triol chain extender or crosslinking agent; the mass ratio of the polyurethane prepolymer to the low molecular weight diol or triol chain extender or crosslinking agent is 95:5~70:

30.

5. A piezoelectric tactile sensor according to claim 3, characterized in that, The epoxy resin-based shape memory network is formed by the reaction of epoxy oligomers and amine curing agents, wherein the mass ratio of epoxy oligomers to curing agents is 100:10 to 100:

40.

6. A piezoelectric tactile sensor according to claim 3, characterized in that, The acrylate-based shape memory network is prepared by reacting acrylate or polyurethane acrylate oligomers with a free radical curing system; the mass ratio of the oligomer to the initiator system is 99:1 to 95:

5.

7. A piezoelectric tactile sensor according to claim 1, characterized in that, The mass ratio of the programmable shape memory polymer matrix (3) to zinc oxide nanoparticles (4) is 95:5~60:

40.

8. The method for manufacturing a piezoelectric tactile sensor according to claim 1, characterized in that, Includes the following steps: S1. To prepare the precursor of the programmable shape memory polymer matrix (3), firstly, the shape memory oligomer or prepolymer is mixed with its corresponding crosslinking agent or curing agent in the corresponding mass ratio. S2. During the stirring process in S1, an appropriate amount of zinc oxide nanoparticles (4) are gradually added to the precursor until they are fully stirred and homogeneous. Then, vacuum degassing is performed to remove bubbles and a composite mixture is obtained. S3. Place the composite mixture in a flat mold, and after curing, form a composite film. Then, perform a shape memory programming step, heat the composite film to above its transition temperature, and then mechanically deform it to define the desired temporary shape. While maintaining the deformation, cool the film to fix the temporary shape. S4. Finally, a first conductive layer (1) containing at least one graphene and a second conductive layer (2) are deposited on both sides of the composite film.

9. A material analysis method using the piezoelectric tactile sensor according to any one of claims 1-7, characterized in that, The process includes applying a sensor to the material to be analyzed; measuring a first piezoelectric signal in a first mechanical state of the shape memory polymer matrix; activating the matrix to transition it to at least one second programmed mechanical state; and measuring at least one second piezoelectric signal. The obtained signals are compared to deduce at least one piece of information about the properties, stiffness, roughness, or internal structure of the material being analyzed.

10. The application of a piezoelectric tactile sensor according to any one of claims 1-7 in a robotic grasping system, a smart glove, a medical palpation device, a structural monitoring system, or a non-destructive testing device, characterized in that, The piezoelectric tactile sensor is used as an active tactile detection device.

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