Self-repairing flexible sensor based on modified wood-bamboo nanocellulose and 3D printing preparation method and application of self-repairing flexible sensor

Abstract

The invention relates to a self-repairing flexible sensor based on modified wood-bamboo nanocellulose and a 3D printing preparation method and application thereof, and belongs to the technical field of flexible sensors. In order to solve the problems that an existing flexible sensor is low in sensitivity, poor in durability and incapable of self-repairing, the invention provides a 3D printing preparation method of a self-repairing flexible sensor based on modified wood-bamboo nanocellulose. The 3D printing preparation method comprises the steps that firstly, the modified wood-bamboo nanocellulose is prepared; 2, 3D printing slurry is prepared; and step 3, preparing the self-repairing flexible sensor through 3D printing. The flexible sensor has a multi-scale conductive network structure, and is good in sensitivity and flexible strain response capability; the introduction of the dynamic disulfide covalent bond endows the material with a reversible crosslinking characteristic, the mechanical property can be efficiently recovered within 2.5 hours after the material is damaged, and the material has relatively good structural stability and anti-fatigue performance. According to the method, the bio-based wood-bamboo nanofibers are used as raw materials, and low-cost and high-precision customized manufacturing is achieved through 3D printing.

Description

Technical Field

[0001] This invention belongs to the field of flexible sensor technology, and particularly relates to a self-healing flexible sensor based on modified wood and bamboo nanocellulose, its 3D printing preparation method and application. Background Technology

[0002] With the aging population and the increasing number of patients with chronic diseases, the demand for real-time and accurate health monitoring is becoming increasingly urgent. While traditional rigid sensors (such as metal or semiconductor-based sensors) offer high sensitivity, their brittleness and poor flexibility make them unsuitable for adapting to the complex deformations of human skin, such as bending and stretching, limiting their application in wearable health monitoring. In contrast, flexible sensors, with their excellent conductivity, stretchability, and biocompatibility, can conform to human skin or be implanted in tissues, enabling long-term stable monitoring of physiological signals such as heart rate, blood pressure, and muscle activity, making them a key component in smart healthcare and wearable devices.

[0003] Currently, flexible sensors are mainly constructed by embedding conductive materials, such as graphene, carbon nanotubes, and metal nanowires, into an elastic polymer matrix. Although this method is simple, it still has the following problems: (1) Limited sensitivity: The dispersion and interfacial bonding ability of the conductive filler are insufficient, resulting in a weak signal response; (2) Poor mechanical durability: After long-term use, the polymer matrix is ​​prone to microcracks or fractures, and the conductive network is damaged, leading to sensor failure; (3) Reduced flexibility: The addition of conductive filler often makes the polymer matrix harder, affecting the stretchability and fit of the sensor; (4) Inability to self-repair: Once traditional flexible sensors are damaged, the conductive path and mechanical properties are difficult to restore, shortening the service life.

[0004] Existing flexible sensors still have shortcomings in sensitivity, durability, flexibility, and self-healing capabilities, limiting their widespread application in long-term health monitoring, wearable devices, and smart healthcare. Therefore, developing low-cost flexible sensors that combine high sensitivity, excellent reliability, and self-healing capabilities has become a critical issue that urgently needs to be addressed. Summary of the Invention

[0005] To address the issues of low sensitivity, poor durability, and lack of self-repair capability in existing flexible sensors, this invention provides a self-healing flexible sensor based on modified wood and bamboo nanocellulose, along with its 3D printing preparation method and applications.

[0006] The technical solution of the present invention:

[0007] A 3D printing method for fabricating self-healing flexible sensors based on modified wood and bamboo nanocellulose includes the following steps:

[0008] Step 1: Preparation of modified wood and bamboo nanocellulose:

[0009] Add 2–3 g of hydrochloric acid solution to 130–140 g of wood and bamboo nanocellulose suspension and stir for 20–30 min at room temperature. Add 1.5–2 g of mercapto modifier to the resulting mixture and continue stirring at room temperature for 3–4 h. Then add 4–5 g of sodium hydroxide solution to adjust the pH of the reaction system. Continue stirring for 2–3 h at room temperature in the dark to complete the modification. Centrifuge the resulting reaction system, wash the centrifuged precipitate thoroughly, and resuspend it in deionized water to obtain a modified wood and bamboo nanocellulose dispersion with a mass concentration of 1.5–2 wt%.

[0010] Step 2: Prepare 3D printing paste:

[0011] 8-10g of the modified wood and bamboo nanocellulose dispersion, 14-15g of waterborne polyurethane, and deionized water were added to prepare a 30g suspension. The suspension was ultrasonically dispersed in an ice-water bath for 30-50 minutes. The mixture was then vacuum dried at 30-40°C for 3-4 hours to obtain a waterborne polyurethane / modified wood and bamboo nanocellulose composite slurry with a solid content of 30-40%.

[0012] 6–7 g of the modified wood and bamboo nanocellulose dispersion and 0.01–0.03 g of carbon nanotubes were mixed with deionized water to prepare a 10 g suspension. The suspension was ultrasonically dispersed for 30–40 min under ice-water bath conditions to obtain CNT / modified wood and bamboo nanocellulose composite slurry.

[0013] 1-2g of the modified wood and bamboo nanocellulose dispersion, 100-150mg of MXene powder and 8-10mL of deionized water were ultrasonically dispersed in an ice-water bath for 30-40 minutes to obtain an MXene / modified wood and bamboo nanocellulose composite slurry.

[0014] Step 3: 3D printing to fabricate a self-healing flexible sensor:

[0015] First, an aqueous polyurethane / modified wood-bamboo nanocellulose composite film was prepared by 3D printing using an aqueous polyurethane / modified wood-bamboo nanocellulose composite slurry. After drying the composite film at 30–40 °C for 20–30 min, a CNT / modified wood-bamboo nanocellulose composite slurry was printed and deposited on the surface of the composite film to prepare a CNT layer. After drying the CNT layer at 30–40 °C for 10–15 min, an MXene / modified wood-bamboo nanocellulose composite slurry was printed and deposited on the surface of the CNT layer to prepare an MXene layer. The CNT / modified wood-bamboo nanocellulose composite slurry and MXene / modified wood-bamboo nanocellulose composite slurry were alternately and repeatedly deposited on the surface of the MXene layer. After vacuum drying at 30–40 °C for 6–8 h, a self-healing flexible sensor was obtained.

[0016] Furthermore, the mass concentration of the wood and bamboo nanocellulose suspension in step one is 2-4 wt%, the length of the wood and bamboo nanocellulose ranges from 0.5 to 15 μm, and the molecular weight is 10,000 to 120,000.

[0017] Furthermore, the concentration of the hydrochloric acid solution in step one is 0.4–0.6 M; the mercapto modifier is one of (3-mercaptopropyl)-trimethoxysilane, (3-mercaptopropyl)-triethoxysilane, or γ-mercaptopropyltriethoxysilane; and the concentration of the sodium hydroxide solution is 0.4–0.6 M.

[0018] Furthermore, the specific conditions for centrifugation in step one are centrifugation at a centrifugal force of 6000×g for 4–5 min; the thorough washing involves alternating washing with acetone and deionized water and centrifugation 6–8 times to fully remove unreacted substances and impurities.

[0019] Furthermore, the waterborne polyurethane mentioned in step two is one or a combination of several of WPU1624, WPU1964, WPU2050, WPU2080 or BASFImpranil® DLN 100.

[0020] Furthermore, the carbon nanotubes described in step two have a diameter of 0.5–2.0 nm and a length of 5–30 μm.

[0021] Furthermore, the MXene powder mentioned in step two is Ti2CT. x V2CT x Nb2CT x or Mo2CT x One or more of the above, wherein the MXene powder has a lateral dimension of 2 to 20 μm.

[0022] Furthermore, the thickness of the waterborne polyurethane / modified wood-bamboo nanocellulose composite film after drying is 300–500 μm; the thickness of the CNT layer after drying is 300–500 μm; the thickness of the MXene layer after drying is 200–300 μm; the alternating deposition consists of 4–5 CNT layers and 4–5 MXene layers.

[0023] A self-healing flexible sensor based on modified wood and bamboo nanocellulose, prepared by a 3D printing method provided by the present invention.

[0024] The invention discloses the application of a self-healing flexible sensor based on modified wood and bamboo nanocellulose prepared by a 3D printing method in the fields of flexible electronic devices, personal health monitoring, wearable devices, smart healthcare, and smart human-computer interaction.

[0025] The beneficial effects of this invention are:

[0026] The self-healing flexible sensor based on modified wood and bamboo nanocellulose provided by this invention utilizes DIW 3D printing technology to deposit carbon nanotubes (CNTs) and MXene nanosheets layer by layer on the surface of a composite film, forming a multi-scale conductive network structure. This enables the sensor to output a stable electrical signal response under external strain. Experiments have demonstrated that this sensor can monitor complex human dynamic behaviors such as finger bending in real time, and achieves stable signal transmission by closely adhering to the skin, exhibiting excellent sensitivity and flexible strain response capabilities.

[0027] Flexible sensors based on modified wood and bamboo nanocellulose possess both excellent flexibility and mechanical stability, enabling them to adapt to complex deformations and maintain long-term performance. Furthermore, the introduction of dynamic disulfide covalent bonds on the modified wood and bamboo nanocellulose endows the material with reversible cross-linking properties. The flexible sensors exhibit significant self-healing characteristics after damage, achieving efficient recovery of mechanical properties within 2.5 hours. This further enhances the sensor's structural stability and fatigue resistance, extends its lifespan, and reduces maintenance costs, making it suitable for long-term wearable or dynamic monitoring scenarios.

[0028] The printing paste formulated in this invention possesses excellent shear-thinning properties and rheological properties, making it suitable for direct ink writing (DIW) 3D printing technology. This enables low-cost, high-precision customized manufacturing of complex structures. By optimizing the ratio of modified wood and bamboo nanocellulose with CNT and MXene powders, the printing paste achieves good molding results, providing a feasible solution for the large-scale production of flexible electronic devices.

[0029] This invention utilizes bio-based wood and bamboo nanofibers and waterborne polyurethane as raw materials, combined with green processing techniques, to promote the application of biomass materials in the field of high-performance flexible electronics. This sensor has broad application prospects in flexible electronic devices, personal health monitoring, wearable devices, and smart healthcare, offering both environmental friendliness and economic advantages. Attached Figure Description

[0030] Figure 1 A comparison of stress-strain curves of the aqueous polyurethane / modified wood-bamboo nanocellulose composite film prepared in Example 1 at different self-healing times;

[0031] Figure 2 Viscosity-shear rate relationship of the aqueous polyurethane / modified wood-bamboo nanocellulose composite slurry prepared in Examples 1-4;

[0032] Figure 3 Linear viscoelastic region determination diagrams of the waterborne polyurethane / modified wood-bamboo nanocellulose composite slurry prepared in Examples 1-4;

[0033] Figure 4Strain scanning curves of the aqueous polyurethane / modified wood-bamboo nanocellulose composite slurry prepared in Examples 1-4;

[0034] Figure 5 Time scan curves of the aqueous polyurethane / modified wood-bamboo nanocellulose composite slurry prepared in Examples 1-4;

[0035] Figure 6 Photographs of self-healing flexible sensors of different shapes prepared by the 3D printing method provided in Example 3;

[0036] Figure 7 The images show the real-time resistance monitoring effect of the self-healing flexible sensor sample prepared by the 3D printing method provided in Example 3 under different states: a) finger pressing, b) finger bending, c) elbow bending, d) arm raised to the side, e) sample twisting, and f) walking. Detailed Implementation

[0037] The technical solution of the present invention will be further described below with reference to embodiments, but it is not limited thereto. Any modifications or equivalent substitutions to the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention should be covered within the protection scope of the present invention. In the following embodiments, the process equipment or apparatus not specifically specified are all conventional equipment or apparatus in the art. Unless otherwise specified, the raw materials used in the embodiments of the present invention are all commercially available; unless otherwise specified, the technical means used in the embodiments of the present invention are all conventional means well known to those skilled in the art.

[0038] Example 1

[0039] A 3D printing method for fabricating self-healing flexible sensors based on modified wood and bamboo nanocellulose includes the following steps:

[0040] Step 1: Preparation of modified wood and bamboo nanocellulose:

[0041] Add 2.5 g of 0.5 M hydrochloric acid solution to 135 g of a 3 wt% wood and bamboo nanocellulose suspension and stir for 25 min at room temperature. Add 2 g of mercaptomodifier (3-mercaptopropyl)-trimethoxysilane to the resulting mixture and continue stirring at room temperature for 3 h. Then add 4 g of 0.5 M sodium hydroxide solution to adjust the pH of the reaction system. Continue stirring for 2 h at room temperature in the dark to complete the modification. Centrifuge the resulting reaction system at 6000 × g for 4 min and remove the supernatant. Wash the centrifuged precipitate 8 times with acetone and deionized water to remove unreacted substances and impurities. Resuspend the washed precipitate in deionized water to obtain a 2 wt% modified wood and bamboo nanocellulose dispersion.

[0042] The wood-bamboo nanocellulose used in this invention is derived from abundant biomass resources in nature, including lignin-based materials such as wood, straw, wheat straw, and bamboo. The wood-bamboo nanocellulose is prepared via TEMPO oxidation and exhibits good dispersibility and reactivity. The wood-bamboo nanocellulose used in this embodiment was purchased from Tianjin Wood Elf Biotechnology Co., Ltd., and its length ranges from 0.5 to 15 μm, with a molecular weight of 10,000 to 120,000.

[0043] Step 2: Prepare 3D printing paste:

[0044] 10g of modified wood and bamboo nanocellulose dispersion, 15g of waterborne polyurethane, and deionized water were added to prepare a 30g suspension. The suspension was ultrasonically dispersed for 50min under ice-water bath conditions. Then, the mixture was vacuum dried at 40℃ for 3h to obtain a waterborne polyurethane / modified wood and bamboo nanocellulose composite slurry with a solid content of 5%.

[0045] 7 g of modified wood and bamboo nanocellulose dispersion and 0.03 g of carbon nanotubes were mixed with deionized water to prepare a 10 g suspension. The suspension was ultrasonically dispersed for 40 min under ice-water bath conditions to obtain CNT / modified wood and bamboo nanocellulose composite slurry.

[0046] 2g of modified wood and bamboo nanocellulose dispersion, 150mg of MXene powder and 10mL of deionized water were ultrasonically dispersed in an ice-water bath for 40 min to obtain MXene / modified wood and bamboo nanocellulose composite slurry.

[0047] The carbon nanotubes used in this embodiment have a diameter of 0.5–2.0 nm and a length of 5–30 μm, and were purchased from Suqian Nakaite New Material Technology Co., Ltd.

[0048] The MXene powder used in this embodiment is titanium carbide (Ti2CT). x MXene multilayer nanosheets with lateral dimensions of 2–20 μm were purchased from Shanghai Maclean Biotechnology Co., Ltd.

[0049] Step 3: 3D printing to fabricate a self-healing flexible sensor:

[0050] Using an ink-to-write (DIW) 3D printer, a water-based polyurethane / modified wood-bamboo nanocellulose composite film was first prepared by 3D printing with a water-based polyurethane / modified wood-bamboo nanocellulose composite slurry. After drying at 30–40 °C for 20–30 min, the composite film had a thickness of 500 μm. A CNT / modified wood-bamboo nanocellulose composite slurry was then printed and deposited onto the surface of the composite film to prepare a CNT layer. After drying at 30–40 °C for 10–15 min, the CNT layer had a thickness of 500 μm. An MXene / modified wood-bamboo nanocellulose composite slurry was then printed and deposited onto the surface of the CNT layer to prepare an MXene layer. After drying at 30–40 °C for 10–15 min, the MXene layer had a thickness of 300 μm. The CNT / modified wood-bamboo nanocellulose composite slurry and MXene / modified wood-bamboo nanocellulose composite slurry were then alternately deposited on the surface of the MXene layer, resulting in a total of 4–5 CNT layers and 4–5 MXene layers. The layers were then vacuum-dried at 30–40 °C for 6–8 minutes. h, thus obtaining a self-healing flexible sensor.

[0051] Example 2

[0052] A 3D printing method for fabricating self-healing flexible sensors based on modified wood and bamboo nanocellulose includes the following steps:

[0053] Step 1: Preparation of modified wood and bamboo nanocellulose:

[0054] Add 2.5 g of 0.5 M hydrochloric acid solution to 135 g of a 3 wt% wood and bamboo nanocellulose suspension and stir for 25 min at room temperature. Add 2 g of mercaptomodifier (3-mercaptopropyl)-trimethoxysilane to the resulting mixture and continue stirring at room temperature for 3 h. Then add 4 g of 0.5 M sodium hydroxide solution to adjust the pH of the reaction system. Continue stirring for 2 h at room temperature in the dark to complete the modification. Centrifuge the resulting reaction system at 6000 × g for 4 min and remove the supernatant. Wash the centrifuged precipitate 8 times with acetone and deionized water to remove unreacted substances and impurities. Resuspend the washed precipitate in deionized water to obtain a 2 wt% modified wood and bamboo nanocellulose dispersion.

[0055] The wood-bamboo nanocellulose used in this invention is derived from abundant biomass resources in nature, including lignin-based materials such as wood, straw, wheat straw, and bamboo. The wood-bamboo nanocellulose is prepared via TEMPO oxidation and exhibits good dispersibility and reactivity. The wood-bamboo nanocellulose used in this embodiment was purchased from Tianjin Wood Elf Biotechnology Co., Ltd., and its length ranges from 0.5 to 15 μm, with a molecular weight of 10,000 to 120,000.

[0056] Step 2: Prepare 3D printing paste:

[0057] 10g of modified wood and bamboo nanocellulose dispersion, 15g of waterborne polyurethane, and deionized water were added to prepare a 30g suspension. The suspension was ultrasonically dispersed for 50min under ice-water bath conditions. Then, the mixture was vacuum dried at 40℃ for 3h to obtain a waterborne polyurethane / modified wood and bamboo nanocellulose composite slurry with a solid content of 5%.

[0058] 5 g of modified wood and bamboo nanocellulose dispersion and 0.08 g of carbon nanotubes were mixed with deionized water to prepare a 10 g suspension. The suspension was ultrasonically dispersed for 40 min under ice-water bath conditions to obtain CNT / modified wood and bamboo nanocellulose composite slurry.

[0059] 2g of modified wood and bamboo nanocellulose dispersion, 200mg of MXene powder and 10mL of deionized water were ultrasonically dispersed in an ice-water bath for 40 min to obtain MXene / modified wood and bamboo nanocellulose composite slurry.

[0060] The carbon nanotubes used in this embodiment have a diameter of 0.5–2.0 nm and a length of 5–30 μm, and were purchased from Suqian Nakaite New Material Technology Co., Ltd.

[0061] The MXene powder used in this embodiment is titanium carbide (Ti2CT). x MXene multilayer nanosheets with lateral dimensions of 2–20 μm were purchased from Shanghai Maclean Biotechnology Co., Ltd.

[0062] Step 3: 3D printing to fabricate a self-healing flexible sensor:

[0063] Using an ink-to-write (DIW) 3D printer, a water-based polyurethane / modified wood-bamboo nanocellulose composite film was first prepared by 3D printing with a water-based polyurethane / modified wood-bamboo nanocellulose composite slurry. After drying at 30–40 °C for 20–30 min, the composite film had a thickness of 500 μm. A CNT / modified wood-bamboo nanocellulose composite slurry was then printed and deposited onto the surface of the composite film to prepare a CNT layer. After drying at 30–40 °C for 10–15 min, the CNT layer had a thickness of 500 μm. An MXene / modified wood-bamboo nanocellulose composite slurry was then printed and deposited onto the surface of the CNT layer to prepare an MXene layer. After drying at 30–40 °C for 10–15 min, the MXene layer had a thickness of 300 μm. The CNT / modified wood-bamboo nanocellulose composite slurry and MXene / modified wood-bamboo nanocellulose composite slurry were then alternately deposited on the surface of the MXene layer, resulting in a total of 4–5 CNT layers and 4–5 MXene layers. The layers were then vacuum-dried at 30–40 °C for 6–8 minutes. h, thus obtaining a self-healing flexible sensor.

[0064] Example 3

[0065] A 3D printing method for fabricating self-healing flexible sensors based on modified wood and bamboo nanocellulose includes the following steps:

[0066] Step 1: Preparation of modified wood and bamboo nanocellulose:

[0067] Add 2.5 g of 0.5 M hydrochloric acid solution to 135 g of a 3 wt% wood and bamboo nanocellulose suspension and stir for 25 min at room temperature. Add 2 g of mercaptomodifier (3-mercaptopropyl)-trimethoxysilane to the resulting mixture and continue stirring at room temperature for 3 h. Then add 4 g of 0.5 M sodium hydroxide solution to adjust the pH of the reaction system. Continue stirring for 2 h at room temperature in the dark to complete the modification. Centrifuge the resulting reaction system at 6000 × g for 4 min and remove the supernatant. Wash the centrifuged precipitate 8 times with acetone and deionized water to remove unreacted substances and impurities. Resuspend the washed precipitate in deionized water to obtain a 2 wt% modified wood and bamboo nanocellulose dispersion.

[0068] The wood-bamboo nanocellulose used in this invention is derived from abundant biomass resources in nature, including lignin-based materials such as wood, straw, wheat straw, and bamboo. The wood-bamboo nanocellulose is prepared via TEMPO oxidation and exhibits good dispersibility and reactivity. The wood-bamboo nanocellulose used in this embodiment was purchased from Tianjin Wood Elf Biotechnology Co., Ltd., and its length ranges from 0.5 to 15 μm, with a molecular weight of 10,000 to 120,000.

[0069] Step 2: Prepare 3D printing paste:

[0070] 10g of modified wood and bamboo nanocellulose dispersion, 15g of waterborne polyurethane, and deionized water were added to prepare a 30g suspension. The suspension was ultrasonically dispersed for 50min under ice-water bath conditions. Then, the mixture was vacuum dried at 40℃ for 3h to obtain a waterborne polyurethane / modified wood and bamboo nanocellulose composite slurry with a solid content of 5%.

[0071] 4 g of modified wood and bamboo nanocellulose dispersion and 0.11 g of carbon nanotubes were mixed with deionized water to prepare a 10 g suspension. The suspension was ultrasonically dispersed for 40 min under ice-water bath conditions to obtain CNT / modified wood and bamboo nanocellulose composite slurry.

[0072] 2g of modified wood and bamboo nanocellulose dispersion, 250mg of MXene powder and 10mL of deionized water were ultrasonically dispersed in an ice-water bath for 40 min to obtain MXene / modified wood and bamboo nanocellulose composite slurry.

[0073] The carbon nanotubes used in this embodiment have a diameter of 0.5–2.0 nm and a length of 5–30 μm, and were purchased from Suqian Nakaite New Material Technology Co., Ltd.

[0074] The MXene powder used in this embodiment is titanium carbide (Ti2CT). x MXene multilayer nanosheets with lateral dimensions of 2–20 μm were purchased from Shanghai Maclean Biotechnology Co., Ltd.

[0075] Step 3: 3D printing to fabricate a self-healing flexible sensor:

[0076] Using an ink-to-write (DIW) 3D printer, a water-based polyurethane / modified wood-bamboo nanocellulose composite film was first prepared by 3D printing with a water-based polyurethane / modified wood-bamboo nanocellulose composite slurry. After drying at 30–40 °C for 20–30 min, the composite film had a thickness of 500 μm. A CNT / modified wood-bamboo nanocellulose composite slurry was then printed and deposited onto the surface of the composite film to prepare a CNT layer. After drying at 30–40 °C for 10–15 min, the CNT layer had a thickness of 500 μm. An MXene / modified wood-bamboo nanocellulose composite slurry was then printed and deposited onto the surface of the CNT layer to prepare an MXene layer. After drying at 30–40 °C for 10–15 min, the MXene layer had a thickness of 300 μm. The CNT / modified wood-bamboo nanocellulose composite slurry and MXene / modified wood-bamboo nanocellulose composite slurry were then alternately deposited on the surface of the MXene layer, resulting in a total of 4–5 CNT layers and 4–5 MXene layers. The layers were then vacuum-dried at 30–40 °C for 6–8 minutes. h, thus obtaining a self-healing flexible sensor.

[0077] Example 4

[0078] A 3D printing method for fabricating self-healing flexible sensors based on modified wood and bamboo nanocellulose includes the following steps:

[0079] Step 1: Preparation of modified wood and bamboo nanocellulose:

[0080] Add 2.5 g of 0.5 M hydrochloric acid solution to 135 g of a 3 wt% wood and bamboo nanocellulose suspension and stir for 25 min at room temperature. Add 2 g of mercaptomodifier (3-mercaptopropyl)-trimethoxysilane to the resulting mixture and continue stirring at room temperature for 3 h. Then add 4 g of 0.5 M sodium hydroxide solution to adjust the pH of the reaction system. Continue stirring for 2 h at room temperature in the dark to complete the modification. Centrifuge the resulting reaction system at 6000 × g for 4 min and remove the supernatant. Wash the centrifuged precipitate 8 times with acetone and deionized water to remove unreacted substances and impurities. Resuspend the washed precipitate in deionized water to obtain a 2 wt% modified wood and bamboo nanocellulose dispersion.

[0081] The wood-bamboo nanocellulose used in this invention is derived from abundant biomass resources in nature, including lignin-based materials such as wood, straw, wheat straw, and bamboo. The wood-bamboo nanocellulose is prepared via TEMPO oxidation and exhibits good dispersibility and reactivity. The wood-bamboo nanocellulose used in this embodiment was purchased from Tianjin Wood Elf Biotechnology Co., Ltd., and its length ranges from 0.5 to 15 μm, with a molecular weight of 10,000 to 120,000.

[0082] Step 2: Prepare 3D printing paste:

[0083] 10g of modified wood and bamboo nanocellulose dispersion, 15g of waterborne polyurethane, and deionized water were added to prepare a 30g suspension. The suspension was ultrasonically dispersed for 50min under ice-water bath conditions. Then, the mixture was vacuum dried at 40℃ for 3h to obtain a waterborne polyurethane / modified wood and bamboo nanocellulose composite slurry with a solid content of 5%.

[0084] 3 g of modified wood and bamboo nanocellulose dispersion and 0.13 g of carbon nanotubes were mixed with deionized water to prepare a 10 g suspension. The suspension was ultrasonically dispersed for 40 min under ice-water bath conditions to obtain CNT / modified wood and bamboo nanocellulose composite slurry.

[0085] 2g of modified wood and bamboo nanocellulose dispersion, 250mg of MXene powder and 10mL of deionized water were ultrasonically dispersed in an ice-water bath for 40 min to obtain MXene / modified wood and bamboo nanocellulose composite slurry.

[0086] The carbon nanotubes used in this embodiment have a diameter of 0.5–2.0 nm and a length of 5–30 μm, and were purchased from Suqian Nakaite New Material Technology Co., Ltd.

[0087] The MXene powder used in this embodiment is titanium carbide (Ti2CT). xMXene multilayer nanosheets with lateral dimensions of 2–20 μm were purchased from Shanghai Maclean Biotechnology Co., Ltd.

[0088] Step 3: 3D printing to fabricate a self-healing flexible sensor:

[0089] Using an ink-to-write (DIW) 3D printer, a water-based polyurethane / modified wood-bamboo nanocellulose composite film was first prepared by 3D printing with a water-based polyurethane / modified wood-bamboo nanocellulose composite slurry. After drying at 30–40 °C for 20–30 min, the composite film had a thickness of 500 μm. A CNT / modified wood-bamboo nanocellulose composite slurry was then printed and deposited onto the surface of the composite film to prepare a CNT layer. After drying at 30–40 °C for 10–15 min, the CNT layer had a thickness of 500 μm. An MXene / modified wood-bamboo nanocellulose composite slurry was then printed and deposited onto the surface of the CNT layer to prepare an MXene layer. After drying at 30–40 °C for 10–15 min, the MXene layer had a thickness of 300 μm. The CNT / modified wood-bamboo nanocellulose composite slurry and MXene / modified wood-bamboo nanocellulose composite slurry were then alternately deposited on the surface of the MXene layer, resulting in a total of 4–5 CNT layers and 4–5 MXene layers. The layers were then vacuum-dried at 30–40 °C for 6–8 minutes. h, thus obtaining a self-healing flexible sensor.

[0090] Performance tests were conducted on the self-healing flexible sensors prepared in Examples 1-4:

[0091] I. Self-healing performance test

[0092] The aqueous polyurethane / modified wood-bamboo nanocellulose composite film prepared by 3D printing in step 3 of Example 1 was vacuum dried at 40°C for 18 h to prepare a dried film. The film was cut into rectangular samples with a length × width × height of 40 mm × 5 mm × 1 mm. A 2.5 mm incision was made in the center of the strip, i.e., the 5 mm width portion, using a scalpel blade. These incisions completely penetrated the film, and then the samples were irradiated under ultraviolet light.

[0093] The tests were conducted using a 100N material testing system (SAN microcomputer-controlled universal testing machine, model CMT6104) with a displacement rate of 40 mm / min. The mechanical properties of the composite film were determined based on the stress-strain curves.

[0094] Figure 1 The image shows a comparison of stress-strain curves of the aqueous polyurethane / modified wood-bamboo nanocellulose composite film prepared in Example 1 at different self-healing times. The present invention introduces dynamic disulfide covalent bonds into the modified wood-bamboo nanocellulose, giving the composite film reversible crosslinking properties, so that the composite film can recombine under ultraviolet light stimulation after being damaged and restore its mechanical properties. Figure 1 The results showed that the composite film could be repaired and its mechanical properties restored within 2.5 hours. This indicates that the composite film prepared based on modified wood and bamboo nanocellulose and waterborne polyurethane has a strong self-healing ability, and the flexible sensor prepared based on the composite film can also achieve self-healing.

[0095] II. Rheological Properties Testing of 3D Printing Slurry

[0096] 1. Rheological curve testing

[0097] The rheological properties of the slurry were tested using a Multi Drive rheometer (model: ARES-G2, TA Instruments) at 25 ℃ using a plate-to-plate geometry with a diameter of 25 mm and a gap of 0.25 mm. The shear viscosity as a function of shear rate (0.1–1000 s⁻¹) was recorded. -1 The relationship curve of the change.

[0098] Figure 2 Viscosity-shear rate relationship of the aqueous polyurethane / modified wood-bamboo nanocellulose composite slurry prepared in Examples 1-4; Figure 2 The results show that at high shear rates, the slurry viscosity decreases and its fluidity increases, which is beneficial for printing. At low shear rates, the viscosity recovers, maintaining structural stability. This indicates that the waterborne polyurethane / modified wood-bamboo nanocellulose composite slurry formulated in this invention exhibits significant shear thinning due to the dynamic disulfide bond network of the modified wood-bamboo nanocellulose, making it suitable for DIW 3D printing.

[0099] 2. Linear viscoelastic region test

[0100] To evaluate the mechanical properties of the slurry, an oscillating strain scan (strain range: 0.01%–250%) was performed at a frequency of 1 Hz to determine its linear viscoelastic region (LVR).

[0101] Figure 3 Linear viscoelastic region determination diagrams of the waterborne polyurethane / modified wood-bamboo nanocellulose composite slurry prepared in Examples 1-4; Figure 3 The results show that within the low stress range, G′ and G′′ remain constant with G′>G′′, indicating that the slurry is primarily elastic. When the stress exceeds a critical value, G′ drops sharply and intersects with G′′, resulting in G′′>G′, and the slurry begins to flow. Under high stress, both G′ and G′′ decrease, indicating that the slurry exhibits viscous dominance during 3D printing.

[0102] The high G′ value of the waterborne polyurethane / modified wood and bamboo nanocellulose composite slurry indicates that the dynamic disulfide bond network of modified wood and bamboo nanocellulose in the CNT / modified wood and bamboo nanocellulose composite slurry has strong elasticity and is suitable for supporting 3D printed structures. The dynamic disulfide bonds enhance the slurry's resistance to shear forces.

[0103] 3. Dynamic strain step response test

[0104] First, the test was performed by oscillating for 80 seconds under 0.1% strain, followed by shearing under 80% strain for 60 seconds, and finally by oscillating again under 0.1% strain for 80 seconds. The test frequency was 1Hz.

[0105] Figure 4 Strain scanning curves of the aqueous polyurethane / modified wood-bamboo nanocellulose composite slurry prepared in Examples 1-4; Figure 4 The results show that in the low strain range, G′ and G′′ remain constant and G′>G′′, at which point the slurry is mainly elastic. When the strain exceeds the critical value, G′ begins to decrease and intersects with G′′, G′′>G′, and the slurry changes from elastic dominance to viscous flow. The dynamic disulfide bond network of modified wood and bamboo nanocellulose exhibits high G′ within the LVR, which endows the printed membrane material with structural stability. The large LVR range ensures that the material is not prone to structural collapse during the printing process, and the viscous flow after yielding is conducive to the extrusion molding of the slurry.

[0106] Figure 5 Time scan curves of the aqueous polyurethane / modified wood-bamboo nanocellulose composite slurry prepared in Examples 1-4; Figure 5 The results show that the initial test showed that the oscillation and shearing destroyed some of the dynamic disulfide bonds, resulting in network weakening and modulus reduction; in the later stage, the disulfide bonds underwent an exchange reaction, rebuilding the crosslinked network, and the modulus recovered to the initial value, indicating that the slurry has dynamic adaptability.

[0107] The test results above show that the CNT / modified wood and bamboo nanocellulose composite slurry prepared in Example 3 has a better printing effect.

[0108] Figure 6 The images show self-healing flexible sensors of different shapes fabricated using the 3D printing method provided in Example 3. Because the printing paste provided by this invention has shear-thinning properties, it can achieve high-precision extrusion; it has moderate yield stress and thixotropy, enabling shape retention; and it has dynamic cross-linking properties, which are beneficial for interlayer fusion and self-healing. These properties collectively ensure reliability throughout the entire process, from printing technology to functional application.

[0109] IV. Flexible Sensor Performance Testing

[0110] The real-time resistance of the self-healing flexible sensor prepared in Example 3 was monitored using a CHI660E system.

[0111] Figure 7 The images show the real-time resistance monitoring performance of the self-healing flexible sensor sample prepared by the 3D printing method provided in Example 3 under different conditions. Figure 7 The results show that the self-healing flexible sensor maintains stable signal under localized point stress from finger pressure, large curvature deformation from finger and elbow joint bending, extreme torsional deformation, and cyclic loads from walking, demonstrating the wide strain range applicability and durability of the flexible sensor of this invention. This indicates that the CNT-MXene multi-layered conductive network deposited layer by layer through DIW 3D printing can maintain the conductive path and avoid breakage during material deformation through nanomaterial slippage / rearrangement. Simultaneously, the dynamic disulfide bonds in the aqueous polyurethane / modified wood-bamboo nanocellulose composite film of the substrate material reversibly cross-link, buffering mechanical stress and preventing the conductive filler from dispersing and failing due to excessive deformation. During the 3D printing process, the slurry is uniformly extruded due to shear thinning effect, and the interlayer is tightly fused through disulfide bond recombination, avoiding sudden changes in interfacial resistance. CNT / MXene and the composite substrate form a stable interface through chemical bonding, resisting the peeling effect caused by repeated deformation.

Claims

1. A 3D printing method for fabricating a self-healing flexible sensor based on modified wood and bamboo nanocellulose, characterized in that, Includes the following steps: Step 1: Preparation of modified wood and bamboo nanocellulose: Add 2–3 g of hydrochloric acid solution to 130–140 g of wood and bamboo nanocellulose suspension and stir for 20–30 min at room temperature. Add 1.5–2 g of mercapto modifier to the resulting mixture and continue stirring at room temperature for 3–4 h. Then add 4–5 g of sodium hydroxide solution to adjust the pH of the reaction system. Continue stirring for 2–3 h at room temperature in the dark to complete the modification. Centrifuge the resulting reaction system, wash the centrifuged precipitate thoroughly, and resuspend it in deionized water to obtain a modified wood and bamboo nanocellulose dispersion with a mass concentration of 1.5–2 wt%. Step 2: Prepare 3D printing paste: 8-10g of the modified wood and bamboo nanocellulose dispersion, 14-15g of waterborne polyurethane, and deionized water were added to prepare a 30g suspension. The suspension was ultrasonically dispersed in an ice-water bath for 30-50 minutes. The mixture was then vacuum dried at 30-40°C for 3-4 hours to obtain a waterborne polyurethane / modified wood and bamboo nanocellulose composite slurry with a solid content of 30-40%. 6–7 g of the modified wood and bamboo nanocellulose dispersion and 0.01–0.03 g of carbon nanotubes were mixed with deionized water to prepare a 10 g suspension. The suspension was ultrasonically dispersed for 30–40 min under ice-water bath conditions to obtain CNT / modified wood and bamboo nanocellulose composite slurry. 1-2g of the modified wood and bamboo nanocellulose dispersion, 100-150mg of MXene powder and 8-10mL of deionized water were ultrasonically dispersed in an ice-water bath for 30-40 minutes to obtain an MXene / modified wood and bamboo nanocellulose composite slurry. Step 3: 3D printing to fabricate a self-healing flexible sensor: First, an aqueous polyurethane / modified wood-bamboo nanocellulose composite film was prepared by 3D printing using an aqueous polyurethane / modified wood-bamboo nanocellulose composite slurry. After drying the composite film at 30–40 °C for 20–30 min, a CNT / modified wood-bamboo nanocellulose composite slurry was printed and deposited on the surface of the composite film to prepare a CNT layer. After drying the CNT layer at 30–40 °C for 10–15 min, an MXene / modified wood-bamboo nanocellulose composite slurry was printed and deposited on the surface of the CNT layer to prepare an MXene layer. The CNT / modified wood-bamboo nanocellulose composite slurry and MXene / modified wood-bamboo nanocellulose composite slurry were alternately and repeatedly deposited on the surface of the MXene layer. After vacuum drying at 30–40 °C for 6–8 h, a self-healing flexible sensor was obtained.

2. The 3D printing method for fabricating a self-healing flexible sensor based on modified wood and bamboo nanocellulose according to claim 1, characterized in that, The mass concentration of the wood and bamboo nanocellulose suspension in step one is 2-4 wt%, the length of the wood and bamboo nanocellulose ranges from 0.5 to 15 μm, and the molecular weight is 10,000 to 120,000.

3. The 3D printing method for fabricating a self-healing flexible sensor based on modified wood and bamboo nanocellulose according to claim 1 or 2, characterized in that, The concentration of the hydrochloric acid solution in step one is 0.4–0.6 M; the mercapto modifier is one of (3-mercaptopropyl)-trimethoxysilane, (3-mercaptopropyl)-triethoxysilane, or γ-mercaptopropyltriethoxysilane; and the concentration of the sodium hydroxide solution is 0.4–0.6 M.

4. The 3D printing method for fabricating a self-healing flexible sensor based on modified wood and bamboo nanocellulose according to claim 3, characterized in that, The specific conditions for centrifugation in step one are centrifugation at a centrifugal force of 6000×g for 4 to 5 minutes; the thorough washing involves alternating washing with acetone and deionized water and centrifugation 6 to 8 times to fully remove unreacted substances and impurities.

5. The 3D printing method for fabricating a self-healing flexible sensor based on modified wood and bamboo nanocellulose according to claim 4, characterized in that, The waterborne polyurethane mentioned in step two is one or a combination of several of WPU1624, WPU1964, WPU2050, WPU2080 or BASFImpranil® DLN 100.

6. The 3D printing method for fabricating a self-healing flexible sensor based on modified wood and bamboo nanocellulose according to claim 5, characterized in that, The carbon nanotubes described in step two have a diameter of 0.5–2.0 nm and a length of 5–30 μm.

7. The 3D printing method for fabricating a self-healing flexible sensor based on modified wood and bamboo nanocellulose according to claim 6, characterized in that, The MXene powder mentioned in step two is Ti2CT. x V2CT x Nb2CT x or Mo2CT x One or more of the above, wherein the MXene powder has a lateral dimension of 2 to 20 μm.

8. The 3D printing method for fabricating a self-healing flexible sensor based on modified wood and bamboo nanocellulose according to claim 7, characterized in that, The thickness of the waterborne polyurethane / modified wood-bamboo nanocellulose composite film after drying is 300-500 μm; the thickness of the CNT layer after drying is 300-500 μm; the thickness of the MXene layer after drying is 200-300 μm; the alternating deposition consists of 4-5 CNT layers and 4-5 MXene layers.

9. A self-healing flexible sensor based on modified wood and bamboo nanocellulose, prepared by any one of the 3D printing methods described in claims 1-8.

10. An application of a self-healing flexible sensor based on modified wood and bamboo nanocellulose prepared by any of the 3D printing methods described in claims 1-8 in the fields of flexible electronic devices, personal health monitoring, wearable devices, smart healthcare, and smart human-computer interaction.

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