Flexible all-solid-state two-dimensional nanofluid pressure sensor based on direct osmotic energy drive and its application

Abstract

The present invention discloses a flexible all-solid-state two-dimensional nanofluid pressure sensor directly driven by osmotic energy and its application, belonging to the field of flexible wearable pressure sensor devices and artificial intelligence interaction technology. The pressure sensor is encapsulated by a GO film layer and a KGO film layer, combined with a MXene charge collection layer, a CNF isolation layer and a conductive graphite paper. The present invention uses osmotic energy to drive the selective migration of ions in nanochannels, and converts external pressure into an electrical signal through interlayer spacing modulation. The unique structural design of the present invention improves sensitivity, response speed, etc. Based on the excellent performance and wearable characteristics of the sensor, the present invention combines a deep learning algorithm to achieve real-time human-computer interaction with a single sensor, and the gesture recognition accuracy rate is as high as 95.78%.

Description

Technical Field

[0001] The present invention belongs to the field of flexible wearable pressure sensor devices and artificial intelligence interaction technology, and specifically relates to a flexible all-solid-state two-dimensional nanofluid pressure sensor directly driven by osmotic energy and a preparation method thereof, and especially to the application of the sensor in flexible wearable devices and human-machine intelligent interaction. Background Art

[0002] As a renewable energy widely found in nature, osmotic energy has great potential for utilization, such as in areas where seawater and freshwater are mixed, saline-alkali lakes, and acid-base wastewater. Osmotic energy mainly comes from the salinity difference of ions, and in theory it can be converted into electrical energy through the nanofluid effect. At present, most studies focus on improving the power density and conversion efficiency of osmotic energy by optimizing the material and structural design of ion-selective membranes. However, in practical application scenarios, the utilization of osmotic energy faces many difficulties. The traditional way of utilizing osmotic energy requires it to be collected and stored in an energy storage device before it is supplied to consumer electronic products. This complex conversion process seriously hinders the development of wearable electronic devices towards miniaturization, integration, and portability. For example, when designing a sensor system for outdoor portable devices, the need for additional energy storage and conversion devices makes the entire system bulky and heavy, which is not conducive to carrying and using. At present, how to efficiently store and utilize the electrical energy generated by osmotic energy is still in the exploratory stage. The development of an efficient portable electronic device that can be directly driven by salinity differences has become a key challenge in establishing a new paradigm for the utilization of osmotic energy.

[0003] In the past, the recognition of human gestures mostly relied on a combination of multiple pressure sensors to monitor the dynamic changes of different positions of the hand, but the equipment was complex and required additional power, which increased redundancy and reduced the portability and integration of wearable devices. Since the tiny fluctuations generated by human wrist tendons when making gestures are difficult to be effectively captured, recognized and distinguished, there is an urgent need for highly sensitive pressure sensors to detect and collect these weak signals, and at the same time, there must be an accurate recognition system to process the signals to achieve real-time human-computer interaction. Therefore, the use of a single high-resolution sensor combined with a neural network can solve the above problems, while accurately analyzing the motion characteristics in the received signal to complete the accurate recognition of gestures. Therefore, the development of a new type of pressure sensor with excellent performance combined with human-computer interaction technology has broad application prospects in the fields of artificial intelligence, virtual reality, etc. Summary of the invention

[0004] Based on the above background technology, the purpose of the present invention is to provide a flexible all-solid-state two-dimensional nanofluid pressure sensor directly driven by osmotic energy, and apply it to human-machine intelligent interaction scenarios. The present invention is inspired by the ion concentration gradient driving mechanism in the human skin biosensor system to develop this new type of pressure sensor. The sensor uses the adjustable interlayer spacing of two-dimensional materials under pressure field to regulate the selective migration of ions, thereby converting external pressure into an encodable electrical signal, achieving efficient utilization of osmotic energy in structure and function ( Figure 1 ). This flexible, all-solid-state two-dimensional nanofluid pressure sensor has the advantages of self-power, strong dynamic / static monitoring capabilities and good cycle stability. It has the characteristics of fast response / recovery time (98.0 / 107.0 ms), long cycle life (up to 15,000 cycles) and wide pressure detection range (up to 357 kPa). At the same time, combined with deep learning algorithms, a single sensor can achieve high-resolution human-computer intelligent interaction with a recognition accuracy of up to 95.78%, providing a new solution for intelligent human-computer interaction systems. Specifically, the present invention is implemented using the following technical solutions:

[0005] First, the present invention provides a flexible all-solid-state two-dimensional nanofluid pressure sensor based on direct osmotic energy drive, which comprises, from bottom to top, a conductive graphite paper, an isolation layer, a MXene / GO membrane layer, a KGO / MXene membrane layer and a conductive graphite paper ( Figure 2 ), the isolation layer is a CNF isolation layer, the MXene / GO film is formed by coating a MXene layer on the lower surface of the GO layer, the KGO / MXene film is formed by coating a MXene layer on the upper surface of the KGO layer, the upper surface of the GO layer is bonded to the lower surface of the KGO layer, and the KGO layer is obtained by mixing and drying a GO solution and a KOH solution at room temperature, wherein the concentration of the KOH solution is 0.05-1 M, preferably 0.1-0.5 M. In the present invention, only one side of the GO film layer and the KGO film layer is coated with MXene as a charge collector, and the sides of the GO film layer and the KGO film layer that are not coated with MXene charge collectors are bonded to each other during assembly, and the entire device can be coated with ultra-thin flexible materials such as PET and the like.

[0006] Among them, GO and KGO used in the two-dimensional nanofluid pressure sensor are both two-dimensional layered structure materials ( Figure 3 a in 3 and b in 3), while C and O elements are evenly distributed on the surface of GO, and C, O and K elements are evenly distributed on the surface of KGO. KGO is a modified two-dimensional layered material obtained by modifying GO with KOH.

[0007] Secondly, the present invention also provides a method for preparing the flexible all-solid-state two-dimensional nanofluid pressure sensor directly driven by osmotic energy, which includes the preparation of MXene / GO membrane layer, the preparation of KGO / MXene membrane layer, the preparation of isolation layer, and the assembly of two-dimensional nanofluid pressure sensor.

[0008] Preferably, the preparation of the MXene / GO film layer comprises the following steps:

[0009] Step (1): The GO solution is uniformly coated on a glass substrate with a surface microstructure, and the GO loading is 0.5-3 mg / cm 2 , and place in a cool and ventilated place to dry for 12-48 hours;

[0010] Step (2): A layer of MXene solution is evenly coated on the surface of the GO membrane after drying in step (1), and the MXene loading amount is 0.1-1 mg / cm 2 , and place in a cool and ventilated place to dry for 12-48 hours;

[0011] Step (3): Remove the GO membrane obtained after drying in step (2) and use it as the MXene / GO membrane layer of the two-dimensional nanofluid pressure sensor.

[0012] Preferably, the preparation of the KGO / MXene film layer comprises the following steps:

[0013] Step (4): Stir the GO solution and 0.05-1 M KOH solution at room temperature for 10-60 minutes until the solution color completely turns black, and the volume ratio of GO:KOH is 2:1;

[0014] Step (5): The KGO solution obtained after mixing in step (4) is uniformly coated on a glass substrate with a surface microstructure, and the KGO loading amount is 0.2-2 mg / cm 2 , and place in a cool and ventilated place to dry for 12-48 hours;

[0015] Step (6): A layer of MXene solution is uniformly coated on the surface of the KGO membrane after drying in step (5), and the MXene loading amount is 0.1-1 mg / cm 2 , and place in a cool and ventilated place to dry for 12-48 hours;

[0016] Step (7): Remove the KGO film obtained after drying in step (6) and use it as the KGO / MXene film layer of the two-dimensional nanofluid pressure sensor.

[0017] The MXene in the MXene / GO film layer and the KGO / MXene film layer serves as a charge collector. The GO solution concentration in step (1) and step (4) is 3-6 mg / ml. In step (1) and step (5), the glass substrate with a surface microstructure is obtained by placing an ordinary glass plate under a laser engraving machine and engraving a square solid pattern. The power of the laser engraving machine used is 10%-15%. In step (6), the MXene solution concentration is 2-5 mg / ml, and the MXene loading is more preferably 0.1-1 mg / cm 2 .

[0018] For the flexible all-solid-state two-dimensional nanofluid pressure sensor directly driven by osmotic energy, preferably, the GO solution can be prepared by commercial products or by the improved Hummers method. For example, the preparation method can be: add NaNO3 (1g) to 46ml of concentrated H2SO4 under stirring in an ice water bath and stir for 10min, add graphite (2g) after NaNO3 is completely dissolved, and continue stirring for 10min. Then slowly add KMnO4 (6g is added in 6 times, once every 10min), and keep the temperature of the solution below 20°C, and continue stirring for 30min. React in a water bath at 35°C for 6 to 7 hours until a gray thick paste or a cracked and hardened shape is formed. Use a glass rod to assist the rotation of the magnet, and under the condition of vigorous stirring, continuously and slowly add deionized water (92mL) to stir the thick paste again. Place the beaker containing the solution in a water bath at 98°C for 10 minutes. Then pour the solution into 300 ml (0.997 mol / L) H2O2 solution at room temperature to completely react the remaining KMnO4. Then add deionized water to about one liter, seal the beaker with plastic wrap and let it stand until it is completely precipitated, and remove the upper clear liquid. Add deionized water to 240 ml and ultrasonicate for 2 minutes. The obtained sample is washed several times with 3% HCl solution, then washed several times with deionized water, and then ultrasonicated at low temperature for 5 minutes. Finally, the above mixture is centrifuged at low speed for 3 minutes, and the upper brown-yellow suspension is collected as the GO solution.

[0019] For the flexible all-solid-state two-dimensional nanofluid pressure sensor directly driven by osmotic energy, preferably, the MXene solution can be prepared by commercial products or common methods, such as the preparation method can be: first, prepare 60 ml of HCl solution with a concentration of 9 M. Then, weigh LiF (4.5 g) and MAX phase (Ti3AlC2) powder (3 g) respectively. Next, slowly add LiF to the HCl solution (9 M). After sufficient stirring, add MAX phase powder (3 g) to the mixed solution in 3 portions, and then stir at 35°C for 24 hours. The obtained sample is washed several times with deionized water until the pH value of the supernatant reaches about 6. The clay-like sediment obtained after centrifugation is treated with low-temperature ultrasound for 1 hour under flowing argon to delaminate MXene nanosheets. Finally, the above mixture is centrifuged at low speed for 1 hour to remove the unpeeled MXene. The collected dark green suspension is a MXene nanosheet dispersion.

[0020] Preferably, the isolation layer is prepared by dissolving CNF stock solution in a mixed solution of alcohol and water, wherein the volume ratio of CNF stock solution: alcohol: water is 2:2:1. The CNF mixed solution is evenly coated on the surface of the conductive graphite paper by coating or spraying, wherein the CNF loading is 0.05-1 mg / cm 2 , and then placed it on a heating table to dry at 20-60°C. The obtained film was recorded as CNF isolation layer.

[0021] Preferably, the two-dimensional nanofluid pressure sensor is assembled in the order of a conductive graphite paper MXene / GO film layer with a CNF isolation layer, a KGO / MXene film layer, and a conductive graphite paper from bottom to top, wherein the sides of the MXene / GO film layer and the KGO / MXene film layer that are not covered with a MXene charge collector are bonded to each other, and the conductive graphite paper with a CNF isolation layer is bonded to the MXene charge collector side of the MXene / GO film layer, and finally encapsulated with a flexible PET material.

[0022] Thirdly, the present invention also provides the application of the above-mentioned flexible all-solid-state two-dimensional nanofluid pressure sensor directly driven by osmotic energy in smart wearable devices.

[0023] Fourthly, the present invention also provides the application of the above-mentioned flexible all-solid-state two-dimensional nanofluid pressure sensor directly driven by osmotic energy in a human-computer intelligent interaction system.

[0024] Fifth, the present invention also provides a human-machine intelligent interaction system, including a flexible all-solid-state two-dimensional nanofluid pressure sensor directly driven by osmotic energy, a microprocessor, a manipulator, a signal filtering and amplifying module, and a power supply module, wherein:

[0025] A flexible all-solid-state two-dimensional nanofluid pressure sensor directly driven by osmotic energy, used to collect motion response signals at the tendon of the human wrist;

[0026] A microprocessor is used to process the collected action response signal data and analyze and feedback the imported data through an internal preset algorithm;

[0027] A robotic arm, used to simulate the gestures of a human hand;

[0028] A signal filtering and amplifying module, used for amplifying and filtering the signal;

[0029] The power module is used to provide electrical energy to the signal filtering and amplifying module, the microprocessor and the manipulator.

[0030] The flexible all-solid-state two-dimensional nanofluid pressure sensor directly driven by osmotic energy of the present invention is prepared by preparing a specific GO (graphene oxide) film layer and a KGO (potassium-containing graphene oxide) film layer, combined with a MXene charge collection layer, a CNF (nanocellulose) isolation layer and a conductive graphite paper package. The present invention relates to the technical field of flexible wearable electronics. The present invention uses osmotic energy to drive the ion selective migration in nanochannels, and converts the external pressure into an electrical signal through interlayer spacing modulation. In terms of performance optimization, the unique structural design improves sensitivity, response speed, etc. The present invention is also based on the excellent performance and wearable characteristics of the sensor, combined with a deep learning algorithm, to achieve real-time human-computer interaction with a single sensor, and the gesture recognition accuracy rate is as high as 95.78%. This invention opens up a new path for the direct application of osmotic energy in actual scenarios, has great potential in the field of next-generation smart wearable electronic devices, and is expected to promote the development and innovation of related technologies.

[0031] On the one hand, the flexible all-solid-state two-dimensional nanofluid pressure sensor based on direct osmotic energy drive described in the present invention draws on the sensing mechanism of biological skin. Figure 4 Figure a shows the working principle of mechanoreceptor cells in biological skin. Because there is an ion concentration gradient on both sides of the mechanoreceptor cell membrane, and the ion channel protein of the cell membrane is selective and switchable to different ions, the anions and cations inside and outside the membrane will undergo controllable directional migration when stimulated, thereby directly converting the ion concentration difference into a conductive bioelectric signal. In contrast, in the two-dimensional nanofluid pressure sensor of the present invention, the ion concentration gradient in the two-dimensional GO membrane is used to achieve a similar function ( Figure 4 b). When the original MXene / GO membrane and the KGO / MXene membrane are assembled to form an ion concentration gradient, the KGO side is rich in K + and OH - Migrate from high concentration to low concentration. Since the abundant oxygen-containing functional groups on the surface of GO carry a large amount of negative charge, the K in the KGO membrane+ can smoothly migrate into the interlayer of the GO membrane, while OH - are repelled, forming a nanofluid effect.

[0032] Similarly, Figure 5 The working process of the two-dimensional nanofluid pressure sensor of the present invention is demonstrated. When there is no external pressure, the potential overlap of the double electric layer is low due to the wide GO film interlayer spacing, resulting in K + and OH - No obvious selective transport occurred during migration ( Figure 5 a in 5 and b in 5). At the same time, the presence of the CNF isolation layer increases the device impedance and further hinders ion migration, so the sensor is in a static state. When external pressure is applied to the sensor, the GO membrane interlayer spacing is compressed, the nanofluid effect is enhanced, and the ion transport dynamics are further regulated ( Figure 5 c in the figure). At this time, K + The migration rate is accelerated and the ion channel selectivity is further improved. After the MXene charge collector adsorbs the transmitted ions, a voltage signal is generated in the external circuit. As the pressure increases, the interlayer spacing is further reduced, and the ion migration efficiency continues to improve, causing the output voltage of the sensor to gradually increase, converting the external pressure into an encodable electrical signal. In short, the external pressure plays a role similar to the stimulation signal in biological skin, and the conversion of pressure to electrical signals is achieved by regulating ion migration. Importantly, unlike traditional devices that require complex energy conversion processes, this two-dimensional nanofluid pressure sensor directly utilizes osmotic energy to achieve self-powered operation, can effectively respond to static and dynamic pressure changes, and provides an efficient and convenient solution for pressure detection.

[0033] On the other hand, the present invention verifies the change of ionic conductivity under periodic external force by electrochemical impedance spectroscopy (EIS). When a pressure of 141-337 kPa is applied to the two-dimensional nanofluid pressure sensor, the ionic conductivity gradually increases ( Figure 6 Due to the excellent flexibility of the GO / KGO membrane, the ionic conductivity can be restored to its original value when the pressure is removed ( Figure 6 b). Since the change of ion migration characteristics of GO under pressure field can be proved by the impedance of the device, the present invention further analyzes the equivalent circuit of the two-dimensional nanofluid pressure sensor ( Figure 6 The voltage signal (U) detected by the two-dimensional nanofluid pressure sensor is shown in Figure 2 (c) to study its sensing mechanism. OC ) is as follows:

[0034]

[0035] Among them, R intRepresents the impedance of the device, R V is the internal resistance of the voltmeter (its value is fixed), U int It represents the intrinsic potential of the device. According to the laws of thermodynamics, when the ion concentration gradient remains constant, U int As the external pressure gradually increases, the interlayer spacing of the two-dimensional material is compressed, and the ion migration rate is accelerated, which in turn causes R int Gradually decreases, at this time U OC It can be seen that by adjusting the external pressure, the output voltage can be accurately regulated, so that the two-dimensional nanofluid pressure sensor has the ability to effectively distinguish electrical signals under different pressures, providing a reliable basis for accurate measurement and monitoring of pressure.

[0036] Thirdly, the geometric structure design of the two-dimensional nanofluid pressure sensor is the key factor to improve its performance. First, the sensor performance is optimized by introducing surface microstructure and CNF isolation layer ( Figure 7 a in 7 and b in 7). Figure 1 The three-dimensional depth of field morphology of the surface microstructure and CNF isolation layer on the right shows that these designs make the two-dimensional nanofluid pressure sensor have a strong longitudinal compression ability, thereby changing the interface impedance and regulating the electromechanical transfer function. At the same time, CNF isolation layers of different thicknesses will show different electromechanical response linearity ( Figure 7 b in the figure). This structural design enables the sensor to more effectively convert pressure signals into electrical signals under different pressure conditions, improving the sensitivity and response accuracy of the sensor. Ultra-thin two-dimensional MXene with excellent charge conduction performance is selected as the charge collector, and it is closely contacted with the GO and KGO membrane layers. This design achieves efficient and stable electrical signal output without affecting the performance of the surface microstructure ( Figure 7 In addition, using different concentrations of KOH to make KGO film will also produce different output voltages ( Figure 7 d in the figure), but too high a KOH concentration will cause the KGO film to precipitate KOH crystals at room temperature, resulting in material denaturation. Therefore, the present invention generally uses a relatively stable 0.2 M KGO film for testing. The present invention uses flexible PET as the packaging material. On the one hand, it ensures that the sensor can provide a stable electrical response ( Figure 7 e and Figure 7 On the other hand, the flexible PET material packaging makes the sensor have excellent flexibility and can maintain good performance even when bent at a large angle ( Figure 7This allows the sensor to adapt to a variety of complex installation environments and usage scenarios. For example, in wearable devices or monitoring applications on curved surfaces, it can fit closely to the monitored object and accurately obtain pressure information.

[0037] Fourthly, the comprehensive performance of the two-dimensional nanofluid pressure sensor was comprehensively evaluated using a precision test system. The two-dimensional nanofluid pressure sensor has fast response and recovery capabilities. It can quickly respond to pressure changes under low pressure (such as 11 kPa) and high pressure (such as 357 kPa) conditions, with response times of 98.0 ms and 102.0 ms ( Figure 8 After 15,000 cycles of testing, the maximum output voltage of the two-dimensional nanofluid pressure sensor only lost 5% ( Figure 8 b), confirming the high stability of the sensor under long-term continuous operation. At the same time, it can accurately identify different frequency stimuli in the range of 0.277-2.5 Hz ( Figure 8 c), showing excellent dynamic / static detection capabilities. This is mainly reflected in monitoring human body movements. Whether it is slow posture adjustment or fast limb movement, the two-dimensional nanofluid pressure sensor can accurately sense and convert it into corresponding electrical signals, providing a reliable basis for subsequent data processing and analysis. Force-electric response curve ( Figure 8 d) shows that the two-dimensional nanofluid pressure sensor has good pressure recognition resolution. The constant current charge and discharge (GCD) test shows that ( Figure 8 (e) The two-dimensional nanofluid pressure sensor has reversible and stable charge-discharge characteristics under external pressure. This characteristic originates from the reversible embedding / de-embedding process of K⁺ between GO layers, which enables the sensor to maintain stable performance after multiple charge-discharge cycles.

[0038] Fifthly, with the help of deep learning algorithms, a single two-dimensional nanofluid pressure sensor is worn on the tendon of the human wrist, which can accurately monitor the subtle fluctuations of the tendon when the finger moves, thereby analyzing the gesture in real time. Fig. 9 The recognition accuracy of five different gestures reached 95.78% ( Fig. 9 The combination of this sensor and deep learning cleverly solves the problems of complex wiring, signal interference, and system redundancy that were previously faced when multiple sensor devices were relied upon to capture and analyze human movements.

[0039] The beneficial effects of the present invention are:

[0040] (1) This invention proposes for the first time a flexible all-solid-state two-dimensional nanofluid pressure sensor directly driven by osmotic energy, and this self-powered wearable pressure sensor can be used for human-machine intelligent interaction. This two-dimensional nanofluid pressure sensor simplifies the energy conversion process, improves energy utilization efficiency, provides a self-powered solution for portable electronic devices, and reduces dependence on external power sources. With its unique combined structural design, this two-dimensional nanofluid pressure sensor has excellent performance such as fast response / recovery time (98.0 / 107.0 ms) and wide pressure detection range (up to 357 kPa). It can accurately identify different frequency stimuli (0.277-2.5 Hz), demonstrates good dynamic / static detection capabilities and high stability, and is therefore very suitable for use in wearable human-machine intelligent interaction systems.

[0041] (2) The human-machine intelligent interaction system constructed by the present invention is based on the fusion of the two-dimensional nanofluid pressure sensor and the deep learning algorithm. With the help of the deep learning algorithm, a single pressure sensor can accurately recognize complex gestures with a recognition accuracy of up to 95.78%, effectively solving the complexity and redundancy problems of the multi-sensor system of the traditional intelligent human-machine interaction system and improving the portability and integration of the device. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a schematic diagram of the structure of the two-dimensional nanofluid pressure sensor of the present invention;

[0043] Figure 2 This is a schematic diagram of assembling the two-dimensional nanofluid pressure sensor of the present invention;

[0044] Figure 3 a in the figure is a SEM image of the cross section and surface C and O elements of the GO membrane layer of the two-dimensional nanofluid pressure sensor of the present invention, Figure 3 b is the SEM image of the cross section and surface C, O and K elements of the KGO film layer; the GO film layer and the KGO film layer have uniform texture, and K in the KGO film layer is + Even distribution;

[0045] Figure 4 The a in the figure is the working principle of human skin mechanical receptor cells in sensing external stimuli. Figure 4 b in the figure is the working principle of the two-dimensional nanofluid pressure sensor;

[0046] Figure 5 a in the equation is the potential distribution on the double layer surface. Figure 5 b in the figure is the two-dimensional interlayer nanochannel when no pressure is applied. Figure 5 c in the figure is the two-dimensional interlayer nanochannel when pressure is applied;

[0047] Figure 6a in the figure is the EIS curve of the two-dimensional nanofluid pressure sensor of the present invention under different pressures. Figure 6 b in FIG. 6 is an EIS curve of the two-dimensional nanofluid pressure sensor of the present invention when different pressures are removed, and c in FIG. 6 is an equivalent circuit diagram of the two-dimensional nanofluid pressure sensor of the present invention;

[0048] Figure 7 a in the figure is a VT diagram of the two-dimensional nanofluid pressure sensor of the present invention with a surface microstructure added. Figure 7 b in the figure is the electromechanical transmission function of the two-dimensional nanofluid pressure sensor of the present invention with CNF isolation layers of different thicknesses added. Figure 7 c in the figure is the output voltage of the MXene charge collector added at different positions in the two-dimensional nanofluid pressure sensor of the present invention. Figure 7 d in the figure is the VT diagram of the KGO film layer with different KOH concentrations assembled in the two-dimensional nanofluid pressure sensor of the present invention. Figure 7 e in the figure is the VT diagram of the two-dimensional nanofluid pressure sensor of the present invention under different ambient humidity. Figure 7 f in the figure is the VT diagram of the two-dimensional nanofluid pressure sensor of the present invention at different ambient temperatures. Figure 7 Where g is the two-dimensional nanofluid pressure sensor of the present invention bent into any angle;

[0049] Figure 8 a in the figure is the maximum / minimum pressure VT diagram of the two-dimensional nanofluid pressure sensor of the present invention, Figure 8 b in the figure is the cyclic electromechanical test of the two-dimensional nanofluid pressure sensor of the present invention. Figure 8 Where c is the frequency response range of the two-dimensional nanofluid pressure sensor of the present invention, Figure 8 d in the figure is the electromechanical response resolution diagram of the two-dimensional nanofluid pressure sensor of the present invention, Figure 8 e in the figure is the constant current charge-discharge curve of the two-dimensional nanofluid pressure sensor of the present invention;

[0050] Fig. 9 a in the figure is the human-machine interface of the human-machine intelligent interaction system of the present invention, Fig. 9 Where b is the accuracy confusion matrix of the human-machine intelligent interaction system of the present invention, Fig. 9 The c in the figure is the gesture action decoded by the system. DETAILED DESCRIPTION

[0051] The following embodiments are further descriptions of the content of the present invention as an explanation of the technical content of the present invention, but the essential content of the present invention is not limited to the following embodiments. Ordinary technicians in this field can and should know that any simple changes or replacements based on the essential spirit of the present invention should fall within the scope of protection required by the present invention.

[0052] Example 1

[0053] A method for preparing a flexible all-solid-state two-dimensional nanofluid pressure sensor directly driven by osmotic energy comprises the following steps:

[0054] Step (1): 5 mg / ml GO solution was uniformly coated on a glass substrate with surface microstructures, and the GO loading was 1.23 mg / cm 2 , and place in a cool and ventilated place to dry for 24 hours;

[0055] Step (2): A layer of 3 mg / ml MXene solution was uniformly coated on the surface of the GO membrane after drying in step (1) as a charge collector, and the MXene loading was 0.45 mg / cm 2 , and place in a cool and ventilated place to dry for 24 hours;

[0056] Step (3): Remove the GO membrane obtained after drying in step (2) and use it as the MXene / GO membrane layer of the two-dimensional nanofluid pressure sensor.

[0057] Step (4): Stir 5 mg / ml GO solution and 0.2 M KOH solution at room temperature for 15 minutes until the solution color completely turns black. The volume ratio of GO solution to KOH solution is 2:1.

[0058] Step (5): The KGO solution obtained after mixing in step (4) is uniformly coated on a glass substrate with a surface microstructure, and the KGO loading is 0.99 mg / cm 2 , and place in a cool and ventilated place to dry for 24 hours;

[0059] Step (6): A layer of 3 mg / ml MXene solution was uniformly coated on the surface of the KGO membrane after drying in step (5) as a charge collector, and the MXene loading was 0.45 mg / cm 2 , and place in a cool and ventilated place to dry for 24 hours;

[0060] Step (7): Remove the KGO film obtained after drying in step (6) and use it as the KGO / MXene film layer of the two-dimensional nanofluid pressure sensor.

[0061] Step (8): Dissolve the CNF stock solution in a mixed solution of alcohol solution and water, with the volume ratio of CNF stock solution: alcohol: water being 2:2:1. The CNF mixed solution is evenly coated on the surface of the conductive graphite paper by coating or spraying, wherein the CNF loading is 0.246 mg / cm 2 , and then placed it on a heating table to dry at 50°C. The obtained film was recorded as CNF isolation layer.

[0062] Step (9): Assemble the above-prepared components in the order of conductive graphite paper with CNF isolation layer, MXene / GO film layer, KGO / MXene film layer, and conductive graphite paper from bottom to top. The sides of the MXene / GO film layer and the KGO / MXene film layer not covered with the MXene charge collector are bonded to each other, and the side of the conductive graphite paper with the CNF isolation layer is bonded to the MXene charge collector side of the MXene / GO film layer. Finally, a flexible PET material is used for packaging.

[0063] In Example 1, the assembled device is fixed at the position of the wrist tendon, and the signal filtering and amplification module and the microprocessor Arduino Nano 33 BLE Sense are connected to the two-dimensional nanofluid pressure sensor. For the five gestures of zero, two, three, four, and five, the experimenter repeated it 5300 times to obtain a large number of time domain signals as a labeled data set. After cleaning the collected data set, it is processed with the Keras sequence model based on TensorFlow. First, the data is parsed, and the input and output pairs are randomly split and assigned according to the ratio of 60% training, 20% verification, and 20% testing to prepare for the construction of the neural network model. The data is then feature extracted and classified in the hidden layer of the neural network, and the gradient descent optimization algorithm is used to adaptively estimate the moment, reduce the microprocessor memory requirements and reduce gradient noise, and solve the problem of learning rate hyperparameter constraints. The fully connected layer uses the SoftMax activation function to synthesize feature information and associate output with input. The neural network is trained using the training set, and during the training process, the verification set is used to monitor the generalization ability of the model to prevent overfitting. After the training is completed, the recognition accuracy of the model is evaluated using the test set. After the model is built, the format is converted and embedded in Arduino, which analyzes the gesture pressure signal collected by the sensor in real time and transmits the feedback signal to the robot end to achieve real-time human-computer intelligent interaction.

[0064] Figure 1 It is a schematic diagram of the structure of the two-dimensional nanofluid pressure sensor of the present invention. On the right side, from top to bottom, are the three-dimensional depth of field morphologies of the surface microstructure of the KGO membrane layer, the surface microstructure of the GO membrane layer and the CNF isolation layer; MXene is a new type of two-dimensional material, which is a transition metal carbide, nitride or carbonitride material, GO is graphene oxide, CNF is nanocellulose, KOH is potassium hydroxide, and KGO is potassium-oxidized graphene.

[0065] Figure 2 This is a schematic diagram of assembling the two-dimensional nanofluid pressure sensor of the present invention;

[0066] Figure 3 a in the figure is a SEM image of the cross section and surface C and O elements of the GO membrane layer of the two-dimensional nanofluid pressure sensor of the present invention, Figure 3b is the SEM image of the cross section and surface C, O and K elements of the KGO film layer; the GO film layer and the KGO film layer have uniform texture, and K in the KGO film layer is + Even distribution;

[0067] Figure 4 The a in the figure is the working principle of human skin mechanical receptor cells in sensing external stimuli. Figure 4 b in the figure is the working principle of the two-dimensional nanofluid pressure sensor;

[0068] Figure 5 a in the equation is the potential distribution on the double layer surface. Figure 5 b in the figure is the two-dimensional interlayer nanochannel when no pressure is applied. Figure 5 c in the figure is the two-dimensional interlayer nanochannel when pressure is applied;

[0069] Figure 6 a in the figure is the EIS curve of the two-dimensional nanofluid pressure sensor of the present invention under different pressures. Figure 6 b in FIG. 6 is an EIS curve of the two-dimensional nanofluid pressure sensor of the present invention when different pressures are removed, and c in FIG. 6 is an equivalent circuit diagram of the two-dimensional nanofluid pressure sensor of the present invention;

[0070] Figure 7 a in the figure is a VT diagram of the two-dimensional nanofluid pressure sensor of the present invention with a surface microstructure added. Figure 7 b in the figure is the electromechanical transmission function of the two-dimensional nanofluid pressure sensor of the present invention with CNF isolation layers of different thicknesses added. Figure 7 c in the figure is the output voltage of the MXene charge collector added at different positions in the two-dimensional nanofluid pressure sensor of the present invention. Figure 7 d in the figure is the VT diagram of the KGO film layer with different KOH concentrations assembled in the two-dimensional nanofluid pressure sensor of the present invention. Figure 7 e in the figure is the VT diagram of the two-dimensional nanofluid pressure sensor of the present invention under different ambient humidity. Figure 7 f in the figure is the VT diagram of the two-dimensional nanofluid pressure sensor of the present invention at different ambient temperatures. Figure 7 Where g is the two-dimensional nanofluid pressure sensor of the present invention bent into any angle;

[0071] Figure 8 a in the figure is the maximum / minimum pressure VT diagram of the two-dimensional nanofluid pressure sensor of the present invention, Figure 8 b in the figure is the cyclic electromechanical test of the two-dimensional nanofluid pressure sensor of the present invention. Figure 8 Where c is the frequency response range of the two-dimensional nanofluid pressure sensor of the present invention, Figure 8 d in the figure is the electromechanical response resolution diagram of the two-dimensional nanofluid pressure sensor of the present invention, Figure 8 e in the figure is the constant current charge-discharge curve of the two-dimensional nanofluid pressure sensor of the present invention;

[0072] Fig. 9 a in the figure is the human-machine interface of the human-machine intelligent interaction system of the present invention, Fig. 9 Where b is the accuracy confusion matrix of the human-machine intelligent interaction system of the present invention, Fig. 9 The c in the figure is the gesture action decoded by the system.

[0073] Example 2

[0074] A main preparation method of a flexible all-solid-state two-dimensional nanofluid pressure sensor based on direct osmotic energy drive is similar to Example 1. However, in step (8) of the preparation method, there is a significant difference, that is, the CNF loading amount is changed to 0.021 mg / cm 2 This means that the CNF isolation layer is very thin under this experimental condition, which is comparable to the standard preparation method (i.e., the CNF loading in Example 1 is 0.246 mg / cm 2 A comparative study was conducted on the isolation layer of

[0075] After a series of experimental comparisons, it can be seen that the isolation layer obtained by this method is not very effective, and the linearity of the electromechanical transfer function is very low. Therefore, in order to obtain a two-dimensional nanofluid pressure sensor with good linearity characteristics, the appropriate CNF loading is a key factor. The experimental results show that when the CNF loading in the CNF isolation layer is between 0.1 and 1 mg / cm 2 In this range, the isolation layer part of the two-dimensional nanofluid pressure sensor can provide accurate and reliable results when measuring pressure changes.

[0076] In the technical solution involved in the present invention, although some specific values ​​such as CNF loading that can produce better effects have been given in the above embodiments, it should be clear that the present invention is not limited to these specific values. In practical applications, the CNF loading can be flexibly adjusted according to different usage scenarios and specific needs. For example, in some special application scenarios where the device output voltage requirements are extremely high and the linearity requirements are relatively less strict, the CNF loading may be appropriately reduced. In the precision measurement scenario with extremely high linearity requirements, the CNF loading will be strictly controlled within the optimal range. In short, the content claimed for protection in the present invention is based on the scope recorded and explained in the claims. This scope covers all possible situations for reasonable adjustment of various parameters according to actual needs, and aims to provide sufficient possibilities and guarantees for the wide application and further optimization of this technology in different application scenarios.

[0077] It should be noted that the above-mentioned technical contents of the present invention are only for explanation and clarification to enable those skilled in the art to understand the technical essence of the present invention, so the technical contents are not used to limit the substantial protection scope of the present invention. The substantial protection scope of the present invention shall be subject to the claims. Those skilled in the art should know that any modification, equivalent substitution and improvement based on the substantial spirit of the present invention shall be within the substantial protection scope of the present invention.

Claims

1. A flexible all-solid-state two-dimensional nanofluid pressure sensor directly driven by osmotic energy, characterized in that: From bottom to top, it includes conductive graphite paper, an isolation layer, a MXene / GO film layer, a KGO / MXene film layer and a conductive graphite paper, wherein the isolation layer is a CNF isolation layer, the MXene / GO film is formed by coating a MXene layer on the lower surface of the GO layer, the KGO / MXene film is formed by coating a MXene layer on the upper surface of the KGO layer, the upper surface of the GO layer is bonded to the lower surface of the KGO layer, and the KGO layer is obtained by mixing and drying a GO solution and a KOH solution at room temperature, wherein the concentration of the KOH solution is 0.05-1 M.

2. A method for preparing a flexible all-solid-state two-dimensional nanofluid pressure sensor directly driven by osmotic energy as claimed in claim 1, characterized in that: It includes the preparation of MXene / GO membrane layer, the preparation of KGO / MXene membrane layer, the preparation of isolation layer and the assembly of sensors.

3. The preparation method according to claim 2, characterized in that: The preparation of the MXene / GO film layer comprises the following steps: Step (1): The GO solution was uniformly coated on a glass substrate with a surface microstructure, and the GO loading was 0.5-3 mg / cm 2 , and place in a cool and ventilated place to dry for 12-48 hours; Step (2): A layer of MXene solution is evenly coated on the surface of the GO membrane after drying in step (1), and the MXene loading amount is 0.1-1 mg / cm 2 , and place in a cool and ventilated place to dry for 12-48 hours; Step (3): Remove the membrane obtained after drying in step (2) and use it as the MXene / GO membrane layer of the two-dimensional nanofluid pressure sensor.

4. The preparation method according to claim 2, characterized in that: The preparation of the KGO / MXene film layer comprises the following steps: Step (4): Stir the GO solution and 0.05-1 M KOH solution at room temperature for 10-60 minutes until the color of the solution completely turns black, and the volume ratio of GO solution to KOH solution is 2:1; Step (5): The KGO mixed solution obtained in step (4) is uniformly coated on a glass substrate with a surface microstructure, and the KGO loading amount is 0.2-2 mg / cm 2 , and place in a cool and ventilated place to dry for 12-48 hours; Step (6): A layer of MXene solution is uniformly coated on the surface of the KGO membrane after drying in step (5), and the MXene loading amount is 0.1-1 mg / cm 2 , and place in a cool and ventilated place to dry for 12-48 hours; Step (7): Remove the film obtained after drying in step (6) and use it as the KGO / MXene film layer of the two-dimensional nanofluid pressure sensor.

5. The preparation method according to claim 2, characterized in that: The isolation layer is prepared by coating or spraying the CNF mixed solution evenly on the surface of the conductive graphite paper, wherein the CNF loading is 0.05-1 mg / cm 2 , and then place it on a heating table at 20-60℃ to dry.

6. The preparation method according to claim 2, characterized in that: The two-dimensional nanofluid pressure sensor is assembled by sequentially assembling the conductive graphite paper, the CNF isolation layer, the MXene / GO membrane layer, the KGO / MXene membrane layer, and the conductive graphite paper from bottom to top.

7. Application of the flexible all-solid-state two-dimensional nanofluid pressure sensor directly driven by osmotic energy as described in claim 1 or obtained by the preparation method according to any one of claims 2 to 6 in smart wearable devices.

8. Application of the flexible all-solid-state two-dimensional nanofluid pressure sensor directly driven by osmotic energy as described in claim 1 or obtained by the preparation method according to any one of claims 2 to 6 in a human-computer intelligent interaction system.

9. A human-machine intelligent interaction system, comprising a flexible all-solid-state two-dimensional nanofluid pressure sensor directly driven by osmotic energy as described in claim 1 or obtained by the preparation method according to any one of claims 2 to 6, a microprocessor, a manipulator, a signal filtering and amplifying module, and a power module, wherein: A flexible all-solid-state two-dimensional nanofluid pressure sensor directly driven by osmotic energy, used to collect motion response signals at the tendon of the human wrist; A microprocessor is used to process the collected action response signal data and analyze and feedback the imported data through an internal preset algorithm; A robotic arm, used to simulate the gestures of a human hand; A signal filtering and amplifying module, used for amplifying and filtering the signal; The power module is used to provide electrical energy to the signal filtering and amplifying module, the microprocessor and the manipulator.

Images