Preparation method and application of ion-conducting carrageenan-based hydrogel

Abstract

This invention discloses a method for preparing a carrageenan-based ion-conductive hydrogel, comprising the following steps: mixing a carrageenan solution, acrylamide, manganese chloride, and lithium bis(trifluoromethanesulfonylimide), stirring to obtain a precursor solution; adding a crosslinking agent and an initiator, mixing thoroughly and uniformly, cooling, and irradiating under ultraviolet light to obtain the carrageenan-based ion-conductive hydrogel. This invention provides a carrageenan-based ion-conductive hydrogel with high extensibility, adhesion, self-healing properties, and ion piezoelectricity, serving as a flexible self-powered sensor for human motion detection and human-computer interaction.

Description

Technical Field

[0001] This invention belongs to the field of conductive gel preparation technology, specifically, it relates to a method for preparing and applying an ion-conducting hydrogel based on carrageenan. Background Technology

[0002] In recent years, the research and development of flexible wearable sensors has attracted increasing attention. With the development of digitalization and people's increasing awareness of personal health, these sensors show broad prospects in a variety of application fields. Compared with traditional electronic devices with rigid and robust characteristics, flexible wearable sensors have unique advantages due to their ability to be in contact with human tissue for extended periods, such as flexibility, bendability, foldability, adaptability, portability, and excellent biocompatibility.

[0003] Hydrogels are hydrophilic polymers with high water content, flexibility, and extremely high bending and stretching capabilities. Therefore, hydrogels are ideal materials that can highly mimic the mechanical, chemical, and biological properties of human tissue, resulting in stronger affinity and adhesion to tissues, making them suitable for developing flexible wearable sensors. However, traditional hydrogels suffer from weak mechanical properties and lack of conductivity, limiting their application in the field of flexible sensors. To improve the mechanical properties of hydrogel flexible sensors, researchers have undertaken several improvement efforts, such as applying energy dissipation systems, incorporating fillers / dopants, using hybrid platforms, and employing anisotropic materials.

[0004] Conductive hydrogels (CH) show great promise in wearable devices, flexible sensors, medical monitoring, human-machine interfaces, and soft robotics. As a conversion medium, CH can sense subtle changes caused by external forces or deformation and convert these changes into recordable electrical signals (such as resistance, current, voltage, and capacitance). However, traditional hydrogels generally have poor conductivity. To address this, various strategies have been developed to enhance conductivity, such as using conductive polymers to prepare hydrogels or incorporating conductive fillers / dopants (such as graphene, conductive polymers, and metal nanomaterials). However, the non-uniform distribution of fillers / dopants and the mismatch in elastic modulus between the flexible polymer matrix and the rigid filler make conductive hydrogels prone to fracture under external forces, thus limiting their practical applications.

[0005] As a novel ionic material, ionic piezoelectric hydrogels have attracted considerable attention due to their ability to generate electrical output through the ion gradient created by the difference in migration rates between anions and cations under pressure. The ionic piezoelectric effect refers to the migration of ions (anions and cations) under pressure, a process that can be converted into measurable voltage and current. Based on ion transport properties, ionic piezoelectric materials can convert mechanical stimulation into electrical signals, possessing advantages such as self-powered operation and flexibility, and showing broad application prospects (e.g., artificial skin, wearable electronic devices, self-powered sensors, energy harvesters, human-machine interfaces, etc.). Unlike the piezoelectric effect of crystals, the moving ions generated by the ionic piezoelectric effect are similar to signal generation and transmission in biological systems, making ionic piezoelectric materials an ideal alternative to flexible wearable sensors. Furthermore, the porous structure of ionicly conductive hydrogels provides continuous channels for the migration of anions and cations; for example, introducing mobile ions (such as sodium chloride and potassium chloride) into the hydrogel can significantly enhance conductivity. Nevertheless, developing ionicly conductive hydrogels that combine high conductivity and mechanical properties remains a challenge.

[0006] κ-carrageenan (κ-CG) is a linear double-helix sulfated polysaccharide derived from algae. It belongs to the polyelectrolyte carbohydrate biopolymer category and possesses excellent biocompatibility and biodegradability. The sulfate groups in the κ-CG molecule can form diverse intermolecular interactions, while its double-helix structure endows the material with mechanical reinforcement properties and ion-responsive network extensibility. κ-CG, with its self-healing capabilities, can enhance the mechanical properties of hydrogels by rebuilding the cross-linked network. Currently, flexible sensors based on hydrogels typically have limited functionality and obvious limitations. Multifunctional hydrogel sensors possessing the fundamental characteristics of flexibility, conformability, and comfort will become the future development trend. Summary of the Invention

[0007] The purpose of this invention is to provide a method for preparing carrageenan-based ion-conducting hydrogels.

[0008] Another object of the present invention is to provide an application of the carrageenan-based ion-conductive hydrogel prepared by the method described above in the preparation of a flexible wearable piezoresistive sensor.

[0009] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0010] In a first aspect, the present invention provides a method for preparing an ion-conducting hydrogel based on carrageenan, comprising the following steps:

[0011] A carrageenan solution with a concentration of 0.0001~0.05 g / mL, acrylamide, manganese chloride, and lithium bis(trifluoromethanesulfonyl)imide are mixed, with a molar ratio of 1:2~1000:0.05~1:1~50. The mixture is stirred (preferably for 0.1~1 hours, most preferably for 30 minutes) to obtain a precursor solution. A crosslinking agent and an initiator are added, with a molar ratio of 1:0.05~1:1~20. The mixture is stirred thoroughly and then cooled (at a temperature of 4°C for at least 30 minutes). The mixture is then irradiated under a UV lamp for 0.5~2 hours (preferably 1 hour) to obtain the carrageenan-based ion-conductive hydrogel.

[0012] The concentration of the carrageenan solution is 0.008 g / mL.

[0013] The method for preparing the carrageenan solution:

[0014] Carrageenan is dissolved in deionized water at a temperature of 40~60℃ (preferably 50℃) to obtain a carrageenan solution with a concentration of 0.0001~0.05g / mL.

[0015] The carrageenan is κ-carrageenan.

[0016] The molar ratio of carrageenan, acrylamide, manganese chloride, and lithium bis(trifluoromethanesulfonylimide) is 1:320:0.6:14.

[0017] The manganese chloride is MnCl2·6H2O.

[0018] The crosslinking agent is selected from N,N'-methylenebisacrylamide (DMBA, Macklin, China).

[0019] The initiator is selected from ammonium persulfate.

[0020] The molar ratio of carrageenan, crosslinking agent, and initiator is 1:0.26:3.52.

[0021] The irradiation conditions of the ultraviolet lamp are: λ=395nm, 6W.

[0022] In a second aspect, the present invention provides a carrageenan-based ion-conducting hydrogel prepared by the method described above.

[0023] A third aspect of the present invention provides an application of the carrageenan-based ion-conductive hydrogel in the fabrication of a flexible wearable piezoresistive sensor.

[0024] In a fourth aspect, the present invention provides an application of the aforementioned carrageenan-based ion-conductive hydrogel in the preparation of emergency communication and emergency information transmission devices.

[0025] By adopting the above technical solution, the present invention has the following advantages and beneficial effects:

[0026] This invention addresses the common problems of weak mechanical properties and poor electrical conductivity in traditional hydrogels by constructing a hydrogel based on κ-CG and manganese ions (Mn). 2+ A dual-network ion-conducting hydrogel (GPLM) of polyacrylamide (PAAM) and LiTFSI. The first network of the double helix structure is formed by crosslinking κ-CG with manganese ions. This network interacts with PAAM through multiple hydrogen bonds and π-π stacking to form the second network. LiTFSI is dynamically bound to the dual network through non-covalent bonds (e.g., hydrogen bonds and halogen bonds).

[0027] This invention provides a carrageenan-based ion-conductive hydrogel with high extensibility, adhesion, self-healing properties, and ion-piezoelectricity, serving as a flexible, self-powered sensor for human motion detection and human-computer interaction. This hydrogel exhibits excellent mechanical properties (elongation at break 922.45%, tensile modulus 0.51 MPa, and toughness 2.72 MJ / m). 3 Furthermore, the hydrogel possesses excellent adhesion and self-healing capabilities due to the formation of multiple dynamic structures. It exhibits superior ionic conductivity (1.15 S / m) due to ion migration. Simultaneously, due to the difference in migration rates between anions and cations, it displays an ionic piezoelectric effect under pressure. As a strain sensor, this piezoresistive hydrogel can monitor human movement with a response time of 208 ms. By integrating the hydrogel sensor with deep learning algorithms, an intelligent gesture recognition system was developed, achieving a finger bending signal recognition accuracy exceeding 93%. This hydrogel, combining ionic conductivity and piezoelectric properties, holds great potential for developing flexible wearable sensors to monitor human movement and achieve human-computer interaction. Attached Figure Description

[0028] Figure 1 This is a schematic diagram of the hydrogel preparation process.

[0029] Figure 2 This is a schematic diagram of the spectral results of the hydrogel.

[0030] Figure 3 This is a schematic diagram showing the mechanical properties of the hydrogel.

[0031] Figure 4 This is a schematic diagram showing the results of adhesion and fatigue resistance.

[0032] Figure 5 This is a schematic diagram illustrating the self-healing performance results.

[0033] Figure 6 This is a schematic diagram showing the piezoelectric performance characterization results.

[0034] Figure 7 This is a schematic diagram showing the strain piezoresistive sensing performance of the GPLM hydrogel sensor.

[0035] Figure 8 This is a schematic diagram showing the resistance signal results for strain monitoring of different organs using a hydrogel sensor for piezoresistive sensing applications.

[0036] Figure 9 This is a schematic diagram illustrating the results of a hydrogel sensor being used as a real-time monitoring device to track human movement.

[0037] Figure 10 This is a schematic diagram illustrating the results of deep learning and human-computer interaction. Detailed Implementation

[0038] To more clearly illustrate the present invention, the following description, in conjunction with preferred embodiments, further clarifies the invention. Those skilled in the art should understand that the specific descriptions below are illustrative rather than restrictive, and should not be construed as limiting the scope of protection of the present invention.

[0039] Example 1

[0040] Preparation and characterization of hydrogels

[0041] Mn-containing materials were synthesized via a one-pot method. 2+ κ-carrageenan (κ-CG, MERYER, China)-based hydrogel (GPLM) of polyacrylamide (PAAM) and lithium bis(trifluoromethanesulfonylimide) (LiTFSI, Macklin, China).

[0042] κ-CG (2.5×10) -4 Dissolve 0.2 g of carrageenan in 25 mL of deionized water at 50 °C to obtain a carrageenan solution with a concentration of 0.008 g / mL.

[0043] 25 mL of a 0.008 g / mL carrageenan solution, 0.08 mol (6.0 g) of acrylamide (AM, Macklin, China), and 1.5 × 10⁻⁶ g of MnCl₂·6H₂O (Macklin, China) were added. -4 0.03 g of lithium trifluoromethanesulfonylimide (0.0035 mol, 1.0 g) was mixed and stirred for 30 minutes to obtain a precursor solution; then, N,N'-methylenebisacrylamide (DMBA, Macklin, China) (6.5 × 10⁻⁶ mol, 0.03 g) was added as a crosslinking agent. -5 mol, 0.01 g) and initiator ammonium persulfate (APS, Macklin, China) (8.8 × 10⁻⁶ mol, 0.01 g) -4The initiator (0.2 g, mol) was thoroughly stirred to ensure homogeneity. The mixture was then injected into polytetrafluoroethylene molds of different sizes, and the samples were cooled at 4°C for 30 minutes. After irradiation under a UV lamp (λ=395nm, 6W) for 1 hour, ion-conducting hydrogels based on carrageenan, namely GPLM hydrogels, were obtained. The successful preparation of GPLM was confirmed by FTIR, Raman, XPS, and rheological analysis.

[0044] Comparative Example 1

[0045] Mn 2+ The preparation method of β-CG hydrogel (CGM) includes the following steps:

[0046] Add 25 mL of a 0.008 g / mL carrageenan solution and 1.5 × 10⁻⁶ MnCl₂·6H₂O. -4 Mix (0.03 g, mol) and stir for 30 minutes. Inject the mixture into polytetrafluoroethylene molds of different sizes. Cool the samples at 4°C for 30 minutes to obtain CGM hydrogels.

[0047] Comparative Example 2

[0048] Mn 2+ The preparation method of κ-CG-PAAM hydrogel (GPAM) includes the following steps:

[0049] 25 mL of a 0.008 g / mL carrageenan solution, 0.08 mol (6.0 g) of acrylamide, and 1.5 × 10⁻⁶ MnCl₂·6H₂O were added. -4 Mix 0.03 g (mol) and stir for 30 minutes to obtain the precursor solution; add cross-linking agent N,N'-methylenebisacrylamide (6.5 × 10⁻⁶ mol, 0.03 g ... -5 mol, 0.01 g) and initiator ammonium persulfate (8.8 × 10⁻⁶ mol, 0.01 g) -4 The initiator (0.2 g, mol) was thoroughly stirred to ensure uniform mixing. The mixture was then injected into polytetrafluoroethylene molds of different sizes, and the samples were cooled at 4°C for 30 minutes. After irradiation under a UV lamp (λ=395nm, 6W) for 1 hour, GPAM hydrogels were obtained.

[0050] Application Example 1

[0051] The hydrogel was characterized by scanning electron microscopy and energy dispersive spectroscopy (SEM, EDS, S-4800, Hitachi, Japan), X-ray photoelectron spectroscopy (XPS, Thermo Scientific K-Alpha, USA), Fourier transform infrared spectroscopy (FTIR, Nicoletis 50, USA), and Raman spectroscopy (Raman, DXR3xi, China).

[0052] I. Performance Testing Methods

[0053] 1. Rheological and mechanical properties

[0054] The rheological properties of the samples were tested using a rotational rheometer (TheHakke MARS3, USA). A constant shear stress of 1 Pa and a plate gap of 1.0 mm were used. The frequency sweep range was 0.1 to 10 Hz, and the shear rate range was 0 to 100 rad / s. Rheological data of the hydrogels were obtained through angular frequency scanning to evaluate their rheological properties. The mechanical properties of the hydrogels were tested using a computer-controlled electronic universal testing machine (2T / CMT 4204, Shenzhen, China). Tensile stress tests were performed using a 10×20×1 mm... 3 Hydrogel specimens were tested at a speed of 2 mm / min. Compression tests were performed using cylindrical specimens 15 mm high and 20 mm in diameter, also at a speed of 2 mm / min. Stress-strain curves were obtained by testing the mechanical properties of the samples.

[0055] 2. Adhesion and self-healing properties

[0056] The adhesive properties of the hydrogel were evaluated using an overlap shear test. Hydrogel discs with a diameter of 20 mm and a thickness of 1 mm were divided into four groups and placed between two layers of glass, two layers of polytetrafluoroethylene (PTFE) sheets, two layers of wood, and two layers of metal foil, respectively. After applying a pressure of 500 g, the discs were allowed to stand for 4 hours, followed by shear tensile tests. Tensile force and elongation were recorded using a universal testing machine. The self-healing properties of the samples were demonstrated by cutting the hydrogel sample, reconnecting the two parts, and placing them in a petri dish for healing for 24 hours. The repaired samples were first subjected to LED light illumination tests to light a small bulb. Subsequently, the conductivity and rheological properties of the repaired samples were measured and compared with the original samples.

[0057] 3. Fatigue resistance

[0058] Load-unloading cyclic tests were performed on the hydrogel using a computer-controlled electronic universal testing machine (CMT4503, China). In the tensile cyclic test, the specimen was stretched to a preset 200% strain and then returned to its initial length; this process was repeated multiple times. In the compression cyclic test, the sample was stretched to a preset strain of 100%–500%, then returned to its initial length; this was repeated multiple times. In the compression cyclic test, the gel-like hydrogel was compressed to a preset strain of 50%, then returned to its initial length; this was repeated multiple times. Energy loss was calculated using different cyclic curves to evaluate the fatigue resistance of the hydrogel. All mechanical tests were performed at room temperature.

[0059] 4. In vitro degradability

[0060] Degradation experiments were conducted by storing the hydrogel in PBS (Servicebio, China) solution (0.01 M, pH 7.4). The hydrogel was freeze-dried and weighed at different time points (1 day, 7 days, 14 days, and 28 days). The degradation rate was calculated using the following formula:

[0061]

[0062] M0 is the initial mass of the hydrogel, and Mi is the mass of the hydrogel after degradation at different times.

[0063] 5. Electrochemical performance

[0064] The hydrogel was encapsulated using a polyimide film and copper wires. The encapsulation material consisted of five layers: the first and fifth layers were polyimide films, serving as external insulating layers; the second and fourth layers were copper wires, serving as conductive layers; and the third layer was the hydrogel material itself, serving as the testing layer. The encapsulated hydrogel was connected to an oscilloscope (TBS1102C, China) and an amplifier (SR570, China). The piezoelectric properties of the encapsulated hydrogel were measured by applying stresses of different amplitudes and pressure frequencies. The hydrogel was cut into cubes, with leads connected at both ends, and real-time resistance was measured using a digital multimeter (Keithley DMM6500, China). The conductivity (σ, S / m) was calculated using the following formula based on the cross-sectional area (S) and length (L):

[0065]

[0066] R represents the volume resistivity of the hydrogel.

[0067] 6. Sensing performance

[0068] A digital multimeter (Keithley DMM6500) was connected to a computer to record the sensing performance of different samples under various strain conditions. The hydrogel, serving as a strain sensor, was molded into a strip (15mm × 10mm × 1mm) and fixed to a wire with copper foil. The resistance and strain coefficient changes of various samples were detected by joint movements at different parts of the human body. The relative resistance value was defined by the following formula:

[0069]

[0070] Where R0 is the resistance value of the sample at 0% strain, and R is the resistance value of the sample at a specific strain.

[0071] The strain coefficient (GF) is defined by the following formula:

[0072]

[0073] Where ε is the axial strain, R0 is the initial resistance value, and ΔR is the relative change in resistance.

[0074] 7. Deep Learning

[0075] Deep learning-assisted signal classification technology collects, processes, and stores diverse joint motion signals using a GPLM sensor. A deep learning algorithm model is built on the Jupyter Notebook platform and trained on various signal features to ultimately achieve the goal of motion signal recognition and classification. Each gesture was tested 20 times. By employing artificial intelligence data processing algorithms, deep learning and human-computer interaction experiments are implemented, followed by in-depth analysis and processing of the response signal data to efficiently and accurately predict different signals collected by the sensor.

[0076] 8. Data Analysis

[0077] Each experiment (n>3) was conducted independently, and results are expressed as mean ± standard deviation. Data analysis was performed using one-way ANOVA, and p < 0.05 was considered statistically significant.

[0078] II. Results and Discussion

[0079] 1. Sample Characterization

[0080] Figure 1 The diagram shows the preparation process of the hydrogels. Specifically, a is a schematic diagram of the preparation process of the GPLM hydrogel; b is a schematic diagram of the GPLM hydrogel structure; c is a schematic diagram of digital photographs and SEM images of the CGM hydrogel, GPAM hydrogel, and GPLM hydrogel; d is a schematic diagram of the molecular simulation results of the GPAM hydrogel; e is a schematic diagram of the molecular simulation results of the GPLM hydrogel; and f is a schematic diagram of the binding energy results between the GPAM hydrogel and the GPLM hydrogel.

[0081] As shown in a and b, the GPLM dual-network hydrogel contains coordination bonds between manganese ions and κ-CG, intermolecular forces between κ-CG and PAAM, and hydrogen bonds between LiTFSI and the main chain. Current main strategies for improving the mechanical properties of ion-conducting hydrogels include dual-network (DN) structures, nanocomposites, and topology engineering. DN hydrogels consist of two types of networks: one is a highly cross-linked, rigid, and brittle network, and the other is a flexible and extensible network. These two types of networks can exist independently, cross-linked, or interpenetratingly. This unique network architecture endows the hydrogel with an efficient energy dissipation mechanism, giving it excellent mechanical strength. This invention designs a composite GPLM hydrogel using a DN structure, in which manganese ions and κ-CG form a highly cross-linked first network, and κ-CG and PAAM form a flexible and extensible second network. The two networks form an interpenetrating structure, giving it excellent properties.

[0082] As shown in image c, the CGM, GPAM, and GPLM hydrogels are all colorless and transparent. SEM images reveal that the GPAM and GPLM hydrogels, with their dual-network structure, exhibit a porous structure with pore sizes ranging from 25 to 40 micrometers; while the CGM hydrogel, with its single-network structure, also possesses a porous structure with a pore size of approximately 250 micrometers. Image d shows that molecular simulations of the GPAM hydrogel show the formation of eight hydrogen bonds (including one non-standard hydrogen bond). Image e shows that molecular simulations of the GPLM hydrogel show the formation of two hydrogen bonds (including one non-standard hydrogen bond), one electrostatic interaction, one coordination bond, and two halogen-related interactions. Image f shows that the binding energies of the GPAM and GPLM hydrogels are -1.25 kcal / mol and -1.36 kcal / mol, respectively. The higher binding energy of the GPLM hydrogel compared to the GPAM hydrogel indicates that the introduction of LiTFSI enhances its stability.

[0083] Figure 2 The diagrams show the spectral results of the hydrogels. Specifically, a represents the Fourier transform infrared (FTIR) spectra of CGM, GPAM, and GPLM hydrogels; b represents the Raman spectra of CGM, GPAM, and GPLM hydrogels; c represents the XPS spectra of CGM and GPLM hydrogels; d represents the high-resolution C1s XPS spectra of CGM and GPLM hydrogels; e represents the high-resolution O1s XPS spectra of GPLM hydrogels; f represents the high-resolution S2p XPS spectra of GPLM hydrogels; g represents the high-resolution F1s XPS spectra of GPLM hydrogels; h represents the high-resolution N1s XPS spectra of GPLM hydrogels; and i represents the high-resolution Mn2p XPS spectra of GPLM hydrogels.

[0084] As can be seen from a, compared with CGM hydrogel, both GPAM hydrogel and GPLM hydrogel exhibit a 3193 cm⁻¹. -1 and 3201 cm -1 The NH stretching vibration peak at 1443 cm⁻¹, and the peak at 1443 cm� -1 and 1450 cm -1 The NH bending vibration peak at 744 cm⁻¹ indicates that PAAM has been incorporated into the CGM system. Furthermore, compared to GPAM hydrogels, the wavenumbers of these two peaks did not change significantly in GPLM hydrogels. As can be seen from b, compared to CGM and GPAM hydrogels, the wavenumbers at 744 cm⁻¹ in GPLM hydrogels are significantly higher. -1The sharp and intense peak at point c is attributed to the symmetric CF bending vibration of LiTFSI, confirming the incorporation of LiTFSI. As can be seen from c, compared to CGM hydrogel (containing only C, O, and Mn), GPLM hydrogel exhibits peaks for C, O, Mn, N, S, and F elements.

[0085] As shown in d, the fitting peaks of the CGM hydrogel are located at 284.8 eV (CC bond), 286.8 eV (CO), and 288.7 eV (C=O); while the corresponding peaks of the GPLM hydrogel appear at 284.8 eV (CC), 286.5 eV (CO), and 288.2 eV (C=O). Compared with the CGM hydrogel, the binding energies of CO and C=O bonds in the GPLM hydrogel shift to lower wavenumbers, indicating that the introduction of PAAM and LiTFSI into the CGM hydrogel altered the electronic environment and electron density of these functional groups on the carbon atoms.

[0086] From equation e, we can see that the binding energies at 531.6 eV and 532.5 eV are attributed to the C=O and CO bonds, respectively. From equation f, we can see that the binding energies at 168.7 eV (S 2p3 / 2) and 170.0 eV (S 2p1 / 2) are both attributed to the sulfonic acid group (R-SO3H). From equation g, we can see that the binding energy at 688.6 eV is attributed to the CF bond. From equation h, we can see that the binding energies at 399.7 eV (CN bond) and 401.8 eV (NR4 bond) are attributed to the CF bond. + The binding energy at 641.7 eV (Mn 2p3 / 2) and 653.8 eV (Mn 2p1 / 2) is attributed to the nitrogen atom. From i, it can be seen that the binding energies at 641.7 eV (Mn 2p3 / 2) and 653.8 eV (Mn 2p1 / 2) are respectively attributed to the nitrogen atom. 2+ In summary, κ-CG interacts with Mn in GPLM hydrogels through intermolecular forces, hydrogen bonds, and ionic coordination. 2+ PAAM and LiTFSI interact to form a more robust dual-network structure.

[0087] 2. Mechanical properties

[0088] Figure 3The diagrams show the mechanical properties of the hydrogels. Specifically: a) is a digital photograph of the GPLM hydrogel under stress (heavy load, puncture, torsion, and tensile loads); b) is a schematic diagram of the G' results for different hydrogels; c) is a schematic diagram of the G" frequency scanning rheological curves for different hydrogels; d) is a schematic diagram of the quantitative analysis results of G' and G" for different hydrogels under steady-state conditions; e) is a schematic diagram of the compressive stress-strain curves for different hydrogels; f) is a schematic diagram of the relationship between the fracture compression ratio and compressive strength; g) is a schematic diagram of the relationship between compressive toughness and compressive modulus; h) is a schematic diagram of the tensile stress-strain curves for different hydrogels; i) is a schematic diagram of the relationship between elongation at break and tensile strength; and j) is a schematic diagram of the relationship between tensile modulus and tensile toughness.

[0089] As shown in sample a, GPLM hydrogel can withstand a weight of 100 grams and resist mechanical deformations such as puncture, torsion, and tension. It can still recover its original shape after 500% strain stretching, demonstrating excellent ductility. As shown in samples b and c, the G' and G" values ​​of all samples did not increase significantly, indicating excellent stability. Compared with CGM hydrogel, GPAM hydrogel shows a significant increase in both G' and G" due to the formation of a double crosslinking network between κ-CG and PAAM. Furthermore, due to the introduction of LiTFSI, GPLM hydrogel forms hydrogen bonds with the hydrogel backbone, further enhancing its G' and G" values ​​compared to GPAM hydrogel, thus achieving the strongest crosslinking strength and the highest energy dissipation capacity.

[0090] As shown in d, at a frequency scan of 1 Hz, the G' value of all hydrogels is higher than the G'' value, indicating that they mainly exhibit elastic behavior within the test frequency range. Specifically, GPLM hydrogel exhibits the highest G' value, which increases slightly with increasing frequency, suggesting stronger elastic properties. In short, the enhanced elastic and viscous properties of GPLM hydrogel are attributed to more complex molecular interactions or higher crosslinking density. As shown in e, GPLM hydrogel exhibits the best compressibility, followed by GPAM hydrogel, while CGM hydrogel shows the weakest performance. As shown in f, compared to CGM hydrogel, GPAM hydrogel shows significantly improved compression ratio at break and compressive strength. Compared to GPAM hydrogel, GPLM hydrogel exhibits the highest compression ratio at break of 66.13% under a compressive stress of 0.28 MPa.

[0091] As can be seen from g, compared with CGM hydrogel, GPAM hydrogel exhibits significantly improved compressive toughness and compressive modulus. The compressive moduli of GPAM hydrogel and GPLM hydrogel are 0.219 MPa and 0.265 MPa, respectively, and their compressive toughness is 53.57 kJ / m. 3 and 58.31 kJ / m 3The GPLM hydrogel exhibits significantly better single-network hydrogel properties than the CGM hydrogel, which is attributed to the entanglement between κ-CG and PAAM chains. Furthermore, compared to the GPAM hydrogel, the increased intermolecular and intramolecular hydrogen bonds and halogen bonds in the GPLM hydrogel promote the formation of a more compact internal network. Figure h shows that the GPLM hydrogel exhibits the best tensile properties. Figure i shows that the GPLM hydrogel has the highest elongation at break (922.45%) and relatively high tensile strength (0.45 MPa). Figure j shows that the GPLM hydrogel exhibits the best tensile modulus (0.51 MPa) and toughness (2.72 MJ / m). 3 In summary, the entanglement of chain segments in the dual-network hydrogel prepared by this invention, combined with intramolecular and intermolecular interactions, significantly improves the mechanical properties of the GPLM hydrogel.

[0092] 3. Adhesion and fatigue resistance

[0093] Figure 4 The diagrams show the adhesion and fatigue resistance results. Specifically: a) shows the adhesion behavior of GPLM hydrogel on different substrates; b) shows the lap shear test results; c) shows the lap shear strength results of GPLM hydrogel with different substrates; d) shows the load-unload curve results under different strains; e) shows the energy dissipation results under different strains; f) shows the load-unload curve results at 200% elongation after cycling; g) shows the energy dissipation results after different number of cycles; h) shows the load-unload curve results; and i) shows the energy dissipation and recovery efficiency results after different number of cycles (0, 1 day, 4 days, and 7 days).

[0094] The adhesion ability of hydrogel sensors is crucial for acquiring accurate and stable electrical signals; the sensor must adhere firmly to human skin or other substrate surfaces. As shown in Figure a, GPLM hydrogel exhibits excellent adhesion properties on various substrates, including polytetrafluoroethylene (PTFE), glass, metal, and wood. Furthermore, GPLM hydrogel can withstand a weight of 100 grams without detaching, confirming its excellent adhesion. Figure b demonstrates an overlap shear test, used to quantitatively evaluate the adhesive strength between GPLM hydrogel and different materials. As shown in Figure b, GPLM exhibits adhesion strengths of 27.3 kPa, 26.9 kPa, 20.6 kPa, and 23.8 kPa to PTFE, glass, metal, and wood, respectively, demonstrating strong adhesion.

[0095] As shown in Figure c, the shear stresses of GPLM hydrogel with polytetrafluoroethylene, glass, metal, and wood are 27.3 kPa, 26.9 kPa, 20.6 kPa, and 23.8 kPa, respectively, indicating that GPLM hydrogel has good adhesion strength to different substrates. GPLM hydrogel exhibits strong adhesion properties when in contact with different surfaces through various forces, including van der Waals forces, ion-dipole interactions, dipole-dipole interactions, electrostatic interactions, and metal coordination interactions. These intermolecular forces provide mechanical support for flexible electronic sensors.

[0096] As shown in d, the annular region gradually expands with increasing tensile strain. As shown in e, when the strain increases from 100% to 500%, the energy dissipation of the GPLM hydrogel increases from 6.546 kJ / m². 3 It rose to 111.631 kJ / m 3 This indicates that the hydrogen bonds formed by the PAAM and κ-CG entanglement within the GPLM hydrogel continuously dissociate, gradually leading to internal breakage. These dynamic cross-linking points gradually break down with increasing strain, consuming additional energy. As shown in f, due to the breakdown of hydrophobic bonds, hydrogen bonds, and manganese coordination bonds, as well as energy dissipation from internal friction between molecular chains during stretching, the GPLM hydrogel exhibits significant hysteresis after the initial cycle at 200% elongation. As shown in g, the dissipated energy remains consistently at 8.8 kJ / m. 3 The relatively constant value indicates that the breaking and recombination of dynamic bonds inside the hydrogel has reached a dynamic equilibrium.

[0097] As shown in h, the GPLM hydrogel underwent loading-unloading cycles for different numbers of days after the initial load-unload cycle, and the results showed no significant change in the hysteresis loop after different numbers of days. As shown in i, the energy dissipation and recovery efficiency of the GPLM hydrogel after different cycle periods (0 days, 1 day, 4 days, and 7 days) are analyzed. The GPLM hydrogel exhibits excellent recovery performance, maintaining a recovery efficiency of 98.14% even after 7 days of use. The rapid self-recovery capability of the GPLM hydrogel stems from its purely physical cross-linked network structure. During unloading, the dynamically reversible physical bonds rapidly rearrange to rebuild the network architecture. Therefore, the GPLM hydrogel exhibits excellent fatigue resistance, significantly extending the service life of the flexible hydrogel sensor.

[0098] 4. Self-healing performance

[0099] Figure 5The diagram shows the results of the self-healing performance. Specifically, a is a schematic diagram of the self-healing process of the GPLM hydrogel; b is a schematic diagram of the light bulb experiment results; c is a schematic diagram of the changes in conductivity of the GPLM hydrogel before and after self-healing; d is a schematic diagram of the amplitude scanning rheological curve results of the GPLM hydrogel; e is a schematic diagram of the time-scanning cyclic rheological curve results; and f is a schematic diagram of the degradation rate results of different hydrogels.

[0100] Self-healing capability is a key performance indicator in the fabrication of flexible wearable sensors. To achieve this characteristic, this invention explores various strategies, such as non-covalent bonds or dynamic covalent bonds. As shown in Figure a, after the disc-shaped sample was divided into two halves, the two halves gradually healed without external force intervention within 24 hours. Experimental results show that the self-healing GPLM hydrogel material can support its own weight when held by tweezers. This self-healing capability stems from the synergistic effect between dynamic dipole-dipole forces and hydrogen bonds, enabling the hydrogel network to achieve rapid and efficient self-repair through a synergistic effect.

[0101] As shown in b, the GPLM hydrogel, or self-healing hydrogel, maintains continuous conductivity and successfully lights the miniature light bulb after being connected to a battery via wires. As shown in c, the conductivity before self-healing (ionic conductivity 1.15 S / m) and after self-healing (ionic conductivity 0.99 S / m) showed no significant change, indicating that the GPLM hydrogel possesses the ability to restore its original conductivity.

[0102] As shown in d, when the shear stress reaches 4343.7 Pa, the G' and G" values ​​of the GPLM hydrogel tend to be equal, indicating that the hydrogel is sheared to a liquefied state at this critical point. As shown in e, under cyclic shear stresses of 100 Pa and 5000 Pa, the GPLM hydrogel exhibits stable self-healing properties, rapidly recovering its original G' and G" values ​​even after multiple cycles. After stress relief, the G' value remains higher than the G" value, indicating that the system has returned to a gel state. This cyclic experiment confirms that the hydrogel possesses an elastic network structure and rheological properties, demonstrating excellent self-healing capabilities. As shown in f, the degradation rates of GPAM and GPLM hydrogels are significantly lower than those of CGM hydrogels, indicating that dual-network hydrogels have superior stability compared to single-network systems. In short, the excellent self-healing properties of GPLM hydrogels stem from the dynamic cross-linking between ionic and hydrogen bonds within the hydrogel, making it an ideal candidate material for flexible sensing applications.

[0103] 5. Characterization of piezoelectric properties

[0104] Figure 6The diagram shows the piezoelectric performance characterization results. Specifically, a) is a schematic diagram of the ion piezoelectric effect and the working principle of the GPLM hydrogel; b) is a schematic diagram of the open-circuit voltage of the GPLM hydrogel under different stresses; c) is a schematic diagram of the short-circuit current of the GPLM hydrogel under different stresses; d) is a schematic diagram of the open-circuit voltage of the GPLM hydrogel under different stress frequencies; e) is a schematic diagram of the short-circuit current of the GPLM hydrogel under different stress frequencies; and f) is a schematic diagram of the voltage output of the GPLM hydrogel after 1000 seconds of cyclic pressurization.

[0105] The ionic piezoelectric effect refers to the phenomenon where hydrogels with ionic conductivity generate a potential difference due to changes in the migration or distribution of ions within them under mechanical stress. Because of differences in ionic radii, anions and cations migrate at different rates within the hydrogel, thus triggering the ionic piezoelectric effect.

[0106] As can be seen from a, when subjected to external force, the GPLM hydrogel network deforms, leading to the release of anions (Cl). - ) and cations (Li + The migration rate of ) produces differences (Cl - < Li + This generates a potential difference. From b and c, it can be seen that when the stress varies within the range of 0 to 10 kPa, the open-circuit voltage increases from 0.36 mV to 26.62 mV, and the short-circuit current increases from 0.01 μA to 5.91 μA. From d and e, it can be seen that the change in stress frequency has a significant impact on the open-circuit voltage and short-circuit current, but does not change their amplitude, indicating that the stress frequency can be obtained by analyzing the output signal frequency. From f, it can be seen that when the cyclic pressure is 5 kPa, the GPLM hydrogel can obtain a stable voltage output, indicating that it has high sensitivity and fast response, and has broad application prospects in the field of flexible sensors. GPLM hydrogel based on the ion piezoelectric effect can be used to manufacture self-powered wearable flexible sensors.

[0107] 6. Strain Piezoresistive Sensing Performance

[0108] Figure 7This diagram illustrates the strain piezoresistive sensing performance of the GPLM hydrogel sensor. Specifically: a) shows the relative resistance-strain curve and the fitted curve within the strain range of 0% to 700%; b) shows the sensor's resistance response curve under large strain (100% to 500%); c) shows the sensor's resistance response curve under small strain (0.5% to 5%); d) shows the sensor's response time at 20% strain; e) shows the sensor's resistance response when strain gradually increases from 0% to 200% in a 40% gradient; f) shows the relative resistance changes during torsion, tension, and bending; and g) shows the real-time resistance change when subjected to 160% tensile strain over a 500-second period.

[0109] Due to the excellent stretchability, high conductivity, and superior transparency of GPLM hydrogel, samples were assembled into a flexible resistive strain sensor. The gel serving as the strain sensor was elongated (55mm × 15mm × 1mm). The gel and wires were fixed with copper foil to detect resistance changes during joint movement at different parts of the human body. Based on its high stretchability, the piezoresistive sensing performance of the GPLM hydrogel was evaluated by the relative resistance change (ΔR / R0). During tensile deformation, the extension and contraction of the conductive ion transport paths within the hydrogel led to an increase in relative resistance.

[0110] This invention evaluates the strain resistance sensing performance of a GPLM hydrogel sensor. As shown in Figure a, under applied strain, the resistance change exhibits a clear nonlinear piecewise trend, comprising three linear segments: the sensitivity coefficient (GF) is 2.01 for the strain range of 0% to 150%, 3.24 for 150% to 300%, and reaches 5.96 for 300% to 700%, indicating that the GPLM hydrogel sensor possesses high strain sensitivity. Therefore, this sensor can accurately distinguish between different degrees of deformation.

[0111] As shown in b, the GPLM sensor exhibits stable signal output under large strain (100-500%) conditions, indicating a wide measurement range. As shown in c, the GPLM sensor maintains stable signal output under small strain (0.5-5%) conditions, indicating a low detection limit. The GPLM hydrogel sensor maintains a stable electrochemical signal output, demonstrating excellent repeatability and recovery performance. The response time of the sensor at 20% strain was tested. As shown in d, the tensile response time is 299 ms and the release response time is 208 ms, fully meeting the requirements for real-time signal detection.

[0112] As shown in equation e, under a 40% strain gradient, the sensor's resistance response increases as the strain gradually increases from 0% to 200%. The sensor's output response signal increases synchronously with the tensile deformation and stabilizes instantaneously at a fixed strain level, achieving real-time motion detection and signal output. As shown in equation f, the sensor exhibits insensitivity to torsional deformation, displaying a negative relative resistance change under bending conditions. When the hydrogel sensor is bent or torn, the resistance change is negligible, eliminating potential deformation interference beyond tensile deformation. As shown in equation g, the GPLM hydrogel sensor possesses durability and mechanical stability. Throughout each stretch / release cycle, the resistance signal consistently exhibits nearly identical waveforms and amplitudes, demonstrating the GPLM hydrogel sensor's superior stability and fatigue resistance.

[0113] 7. Piezoresistive Sensing Applications

[0114] Figure 8 This diagram illustrates the resistance signal results for strain monitoring of different organs using a hydrogel sensor in a piezoresistive sensing application. Specifically, a represents the swallowing result, b represents the neck flexion result, c represents the finger movement result, d represents the elbow flexion result, e represents the knee movement result, and f represents the wrist movement result.

[0115] The hydrogel sensor exhibits excellent stretchability, high sensitivity, and superior adhesion, making it suitable for detecting human motion. As shown in a, the sensor detects swallowing signals when the volunteer swallows. As shown in b, the sensor instantly records highly stable and repeatable signals when the volunteer lowers their head. As shown in c-f, the GPLM hydrogel sensor was mounted on fingers and other body parts (such as elbows, knees, and wrists) for bending tests to obtain stable and repeatable changes in relative resistance. The results demonstrate that the GPLM hydrogel possesses good response recovery and stability, showing broad application prospects in the field of human motion detection.

[0116] Figure 9 This diagram illustrates the results of a hydrogel sensor used as a real-time monitoring device to track human movement. Specifically, a represents the monitoring results of a push-up exercise by the hydrogel sensor; b represents the elbow joint movement signal during a push-up; c represents the levator scapulae muscle movement signal during a push-up; d represents the Morse code signal results for different letters; e represents the Morse code signal sensing results; and f represents the "CHINA" sensing signal results.

[0117] As shown in image a, the sensor is placed on the elbow joint and trapezius muscle to monitor joint / muscle activity during push-ups. Image b shows that during the volunteer's push-up exercise, the GPLM hydrogel sensor corresponds to the relative resistance change of the elbow joint, recording joint activity signals. Image c shows that during the volunteer's push-up exercise, the GPLM hydrogel sensor corresponds to the relative resistance change of the trapezius muscle, recording muscle activity signals. These results indicate that hydrogel strain sensors have broad application potential in the field of sports training.

[0118] Hydrogel sensors have also been used to transmit information via Morse code. As shown in d and e, d illustrates the Morse code diagrams corresponding to different letters. e presents the resistive response of the GPLM hydrogel sensor to finger bending at different time points, where brief bending represents a "dot" and sustained bending represents a "stroke." Each English letter corresponds to a unique Morse sequence, and words can be decoded by rhythmic tapping. As shown in f, volunteers rhythmically bent their fingers, enabling the GPLM hydrogel sensor to transmit the signal "CHINA" in Morse code. This demonstrates the broad application prospects of GPLM hydrogel in monitoring human activity, emergency communication, and covert information transmission.

[0119] 8. Deep Learning and Human-Computer Interaction

[0120] Figure 10 Figures 1-2 illustrate the results of deep learning and human-computer interaction. Figure 3 shows the flowchart of deep learning-assisted motion signal recognition and the detailed framework of the artificial neural network model; Figure 4 shows the results of displaying photos of robotic hands with different gestures ("one, four, six, OK, Rock, Yeah"); Figure 5 shows the results of the relative resistance change when the robotic finger bends and extends; Figures 6 and 7 show the ΔR / R0 change curves during the bending process of different gestures, with Figure 8 showing the "one, four, six" gesture and Figure 9 showing the "OK, Rock, Yeah" gesture; Figure 10 shows the confusion matrix results of deep learning gesture recognition based on artificial neural networks; and Figure 11 shows the robotic hand signal simulating the "hello" gesture.

[0121] As a computational model, Artificial Neural Networks (ANNs) simulate biological nervous systems, which consist of multiple interconnected layers of neurons, such as input layers, hidden layers, and output layers. Figure a shows a flowchart of deep learning-assisted action signal recognition and a detailed framework of the ANN model. By extracting features from input layer data to construct higher-level representations, the neural network can learn and predict corresponding action identifiers. Figure b presents photographs of robotic hands with different hand gestures ("one, four, six, OK, Rock, Yeah") used for deep learning. An array of strain sensors made of GPLM hydrogel material is mounted on the back of the robotic fingers to monitor the bending state of each joint. The bending of each finger produces a unique resistance change within its corresponding strain sensor. These changes are independently captured by a multi-channel data acquisition system, ensuring complete isolation from crosstalk between the five channels recording the resistance signals.

[0122] As shown in Figure c, the relative resistance changes of the robot's fingers during bending and straightening processes (thumb, index finger, middle finger, ring finger, and little finger) are 33.53%, 41.57%, 39.00%, 34.56%, and 24.58%, respectively. Figure d shows the trend of ΔR / R0 changes during bending processes of different gestures. Different ΔR / R0 values ​​were generated when monitoring gestures (one, four, six). Figure e shows that different ΔR / R0 values ​​were also generated when monitoring gestures (OK, Rock, Yeah). Figure f reveals the confusion matrices of deep learning based on artificial neural networks for different gesture results. The six confusion matrices summarize the action verification results, showing that the artificial neural network achieved an overall accuracy of 93.3% in 120 predictions, with two misclassifications of "four," one of "six," two of "OK," and three of "Yeah." Each gesture exhibits unique waveform characteristics in its corresponding five channels.

[0123] As shown in 'g', a schematic diagram of a robotic hand simulating the "hello" gesture is presented. Specific English words can be spelled by combining consecutive gestures of individual letters. For example, the letter "H" is formed by bending the thumb, ring finger, and little finger; in this case, only the ΔR / R0 values ​​of these three channels change, while the index and middle finger channels remain at 0%. When all fingers are bent to form the letter "E," the ΔR / R0 values ​​of all channels increase. In summary, the research results indicate that this hydrogel sensor possesses excellent real-time response capabilities and can quickly process input signals. It can not only instantly recognize gestures but also accurately distinguish different action patterns through deep learning technology, demonstrating superior human-computer interaction capabilities.

[0124] In summary, an ion-conductive hydrogel based on κ-carrageenan (κ-CG) was successfully developed by combining manganese ions, PAAM, and LiTFSI. This dual-network hydrogel exhibits excellent mechanical properties, including high elongation at break, tensile strength, tensile modulus, and stretchability, and its multi-dynamic structure also endows it with adhesive and self-healing characteristics. The hydrogel achieves good conductivity through ion current carrying, thus possessing highly sensitive and stable piezoresistive sensing performance for monitoring human motion. Under mechanical stress, the difference in migration rates between anions and cations causes it to exhibit a piezoelectric effect, making it suitable for fabricating self-powered flexible sensors. This hydrogel integrates strain sensing capabilities with machine learning algorithms to achieve high-precision gesture recognition. In conclusion, this hydrogel, possessing high stretchability, adhesion, self-healing ability, conductivity, and piezoelectric properties, demonstrates great potential as a flexible sensor in the fields of human motion monitoring and human-computer interaction.

[0125] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-described technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A method for preparing an ion-conducting hydrogel based on carrageenan, characterized in that, Includes the following steps: A carrageenan solution with a concentration of 0.0001~0.05 g / mL, acrylamide, manganese chloride, and lithium bis(trifluoromethanesulfonyl)imide were mixed, with a molar ratio of 1:2~1000:0.05~1:1~50. The mixture was stirred to obtain a precursor solution. A crosslinking agent and an initiator were added, with a molar ratio of 1:0.05~1:1~20. The mixture was stirred thoroughly and mixed evenly. After cooling, the mixture was irradiated under a UV lamp for 0.5~2 hours to obtain the carrageenan-based ion-conductive hydrogel.

2. The method for preparing carrageenan-based ion-conducting hydrogels according to claim 1, characterized in that, The concentration of the carrageenan solution is 0.008 g / mL.

3. The method for preparing carrageenan-based ion-conducting hydrogels according to claim 1, characterized in that, The method for preparing the carrageenan solution: Carrageenan was dissolved in deionized water at a temperature of 40-60℃ to obtain a carrageenan solution with a concentration of 0.0001-0.05 g / mL.

4. The method for preparing the carrageenan-based ion-conducting hydrogel according to claim 1, characterized in that, The molar ratio of carrageenan, acrylamide, manganese chloride, and lithium bis(trifluoromethanesulfonylimide) is 1:320:0.6:

14.

5. The method for preparing carrageenan-based ion-conducting hydrogels according to claim 1, characterized in that, The crosslinking agent is selected from N,N'-methylenebisacrylamide.

6. The method for preparing carrageenan-based ion-conducting hydrogels according to claim 1, characterized in that, The initiator is selected from ammonium persulfate.

7. The method for preparing the carrageenan-based ion-conducting hydrogel according to claim 1, characterized in that, The molar ratio of carrageenan, crosslinking agent, and initiator is 1:0.26:3.

52.

8. A carrageenan-based ion-conducting hydrogel prepared by the method of any one of claims 1 to 7.

9. The application of the carrageenan-based ion-conductive hydrogel of claim 8 in the preparation of a flexible wearable piezoresistive sensor.

10. The application of the carrageenan-based ion-conductive hydrogel of claim 8 in the preparation of emergency communication and emergency information transmission devices.

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