Application Cases

Experimental Name: High-Resolution Three-Dimensional Graphene Strain Sensing Network and Self-Monitoring Deformation Devices

Research Direction:
Addressing the need for high-precision sensing under complex deformation fields, this study investigates a novel strain sensing system based on a three-dimensional graphene network. The focus is on three key technological breakthroughs:

1. Multilevel microstructure regulation (gradient pore structures with pore sizes ranging from 50 nm to 20 μm prepared via ice-templated directional freezing).

2. Strain-electrical coupling modeling (establishing a multiscale correlation model with a gauge factor of up to 120 at 50% strain).

3. Intelligent noise suppression algorithms (Kalman filtering combined with machine learning for temperature drift compensation).

Through plasma interface modification and PVDF piezoelectric coupling design, the system achieves micro-strain monitoring at 0.1% (signal-to-noise ratio > 40 dB) and self-powered operation (conversion efficiency of 15.3%). This addresses the challenges of multi-dimensional strain resolution and dynamic stability faced by traditional sensors in applications such as flexible electronics and deformable aircraft wings.

Experimental Objective:
The aim is to develop a highly sensitive three-dimensional graphene strain sensing network. By leveraging microstructure design and multimodal signal coupling mechanisms, the material achieves self-perception of deformation. Integrated with shape-memory polymers, the system forms intelligent devices capable of electrically driven deformation and real-time self-monitoring. This provides a high-resolution, wide-range, and environmentally robust strain monitoring solution for flexible electronics, soft robotics, and aerospace deployable structures.

Testing Equipment:
Chemical vapor deposition furnace, scanning electron microscope, Raman spectrometer, electronic universal testing machine, digital source meter, infrared thermal imager, dynamic mechanical analyzer (DMA), sound level meter, function generator, power amplifier, digital oscilloscope.

Experimental Procedure:
A single-layer graphene foam (GrF/Ni) was grown on a nickel foam substrate using chemical vapor deposition. After immersion and spin-coating with PDMS solution and subsequent curing, the nickel skeleton was etched away using FeCl₃ solution, followed by freeze-drying to obtain a three-dimensional flexible SLGF material. Dynamic strain ranging from 0.033% to 51% was applied to the SLGF using an electronic universal testing machine. Simultaneously, resistance change data were collected via a Keithley 7510 digital source meter, and wavelet denoising and linear fitting were performed using the LabVIEW platform. The temperature rise curve of the shape-memory polymer (SMP) driven by Joule heating was monitored using an infrared thermal imager, while the shape recovery process was recorded with a high-speed camera (1000 fps). Finally, MATLAB was used to analyze the multiphysics coupling of strain, resistance, and temperature, establishing a dynamic response model for the self-monitoring device.

Figure 1: Multiphyiscs Coupling System Architecture of the Three-Dimensional Graphene Strain Sensing Network and Joule Heating-Driven Self-Monitoring Device

Experimental Results:
This study systematically validated the self-monitoring performance and functional integration capabilities of the material under wide strain ranges and extreme environments by constructing a three-dimensional graphene strain sensing network (SLGF) and its composite device with shape-memory polymer (SMP). Experiments showed that sensors made from this material not only exhibit extremely high sensitivity (detecting micro-deformations as small as one-thousandth the thickness of a human hair) but also maintain stable performance after 3000 repeated stretching cycles. By integrating with smart materials, the sensors can automatically deform upon electrification and provide real-time feedback on their own status, reliably operating in extreme environments ranging from -40°C cold to 150°C heat. This technology overcomes the limitations of traditional sensors, which can only detect deformation separately or require external power sources, providing a lighter and more durable self-sensing solution for applications such as intelligent robots, wearable devices, and spacecraft folding structures. Examples include flexible robotic hands that monitor their own bending status in real time or satellite solar panels capable of autonomously adjusting their shape.

Figure 2: Shape Recovery Process of the SS1 Deformable Device Under 15V Voltage, with Insets Showing Corresponding Infrared Images

Figure 3: Static Thermal and Electrical Performance Testing of SS2 Under 15V Voltage:
(a) Infrared images during electrified heating;
(b) Curve of relative resistance change over time (blue) and average temperature change over time (red).

Figure 4: Self-Monitoring Performance Testing of SS2 Under 20V Voltage:
(a) Infrared images of the shape recovery process;
(b) Curve of relative resistance change (blue) and shape recovery rate curve (red).

Figure 5: Self-Monitoring Results of SS2 Deformable Device Under Different Applied Voltages:
(a) 18V, (b) 22V.

Product Recommendation: ATA-4000 Series High-Voltage Power Amplifier

Figure: ATA-4000 Series High-Voltage Power Amplifier Specifications and Parameters

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