High-performance, multifunctional flexible electronic devices

Student thesis: PhD Thesis


Wearable sensing electronics capable of detecting and differentiating multiple mechanical stimuli are critical and promising devices in the applications of healthcare monitoring, robotics, and human-machine interface. Compared with commercial wearable electronic devices features with rigid and discomfortable, the flexible, stretchable, ultrathin, attachable and wearable sensors are more desirable to attach to human skin. Based on different working mechanisms, wearable sensors can generally be divided into resistive, capacitive, piezoelectric and triboelectric types. Among these pressure sensors, piezoresistive sensors which transfer mechanical information into resistance variation, have multiple advantages, including high sensing performance, low energy consumption, ease of device assembly, simple signal acquisition, etc. There are a lot of piezoresistive pressure sensors developed by many fabrication methods, such as the template method, 3D printing, etc.; however, most of the developed sensors suffer from low sensitivity and poor linearity over a broad range. Although a lot of strategies are reported to improve the sensitivity and sensing range, such as fabricating micro/nano structure, porous structure, hierarchical structure, etc., the piezoresistive pressure sensor fabricated by these methods still can’t achieve a high sensitivity and broad linear sensing range simultaneously. Hence, there is a strong need to develop a method to fabricate a piezoresistive pressure sensor with both high sensitivity and broad linear sensing range. In addition, most existing types of wearable sensors are designed and optimized for detecting only uniaxial mechanical stimuli and cannot monitor and differentiate multiple mechanical stimuli, which severely hinders their use in real-world applications, which always involve very complex mechanical stimuli. The sensing features of these sensors present the same electrical output trend under different mechanical stimuli such as pressure, stretching, bending and twisting. As a result, the measurement of one directional mechanical stimulus will be interfered by mechanical stimuli coming from other directions, indicating the inability to sense and differentiate between multiple mechanical stimuli. Thus, it is necessary to develop a multifunctional wearable sensor capable of detecting and differentiating multiple mechanical stimuli including pressure, stretching, convex and concave bending.
Firstly, a hierarchical in-situ filling porous piezoresistive sensor (HPPS) is fabricated by direct ink writing (DIW) printing and curing of carbon nanofibers (CNFs)/polydimethylsiloxane (PDMS) emulsion template method. Hierarchical porous geometry significantly increases the contact area, distributes stress to multilayered lattice and internal porous structure, resulting in a broad sensing range. Moreover, unlike conventional hollow porous structure, the in-situ filling porous structure is formed by the solidification of CNFs/PDMS and evaporation of emulsified water, while the CNFs dispersed in emulsified water remain inside the pores, forming CNFs networks embedded in the pores. The CNFs networks in-situ filling porous structure generates more contact sites and conductive pathways during compression, thereby achieving high sensitivity and linearity over the entire sensing range. Therefore, the optimized HPPS achieves high sensitivity (4.7 kPa−1 ) and linearity (coefficient of determination, R2 = 0.998) over a broad range (0.03–1000 kPa), together with remarkable response time and repeatability. Benefiting from its high sensitivity and broad linear sensing range, the prepared sensor also exhibits high pressure resolution. Then the sensor is demonstrated in detecting various stimuli from low pressure, such as pulse detection, voice recognition, to high pressure, such as human foot motion and tire pressure detection.
Secondly, a wing-like structure with a pressure sensing module in the middle and stretching sensing module in both wings is fabricated with the capability of detecting and differentiating multiple mechanical stimuli, including pressure, stretching, and convex and concave bending. The wing-like multifunctional sensor (WMS) is designed with a hierarchical in situ filling porous structure as the pressure sensing layer and wrinkled CNTs/Ag nanoflakes hybrid film as stretch sensing layer, resulting in excellent pressure and stretch sensing performance. When measuring the pressure, the signal of the pressure sensing module is not interfered by the external stretching because the lower Young’s modulus stretch sensing module in both wings bears all the stretch without deforming the pressure sensing module. In stretch sensing, the response of the stretch sensing module will not be disturbed by external normal pressure because of the higher thickness and high compressibility of the hierarchical porous sensing layer that withstands the entire pressure. In addition, the WMS sensor could detect and differentiate convex and concave bending based on the breakage and overlap of the CNTs/Ag nanoflakes in the stretch sensing module. Then WMS is demonstrated for accurately detecting of human kinesthesia, recognizing various types and sizes of objects with a robotic gripper, monitoring locomotion and perceiving environmental information by a crawling robot, and human-machine interaction.
In summary, we developed a high sensing performance piezoresistive pressure sensor with high sensitivity over a broad linear sensing range by 3D printing technique and the emulsion template method. We reported a multifunctional sensor with the capability to detect and differentiate multiple mechanical stimuli by a wing-like structure with a mismatch of Young’s modules and thickness between the pressure and stretch sensing module. The developed sensor is demonstrated in the applications of health monitoring, human motion recognition, robotic and human-machine interface.
Date of AwardJul 2023
Original languageEnglish
Awarding Institution
  • University of Nottingham
SupervisorGuang Zhu (Supervisor) & Mengxia Xu (Supervisor)

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