This paper details the design of a poly(dimethylsiloxane) (PDMS)-shielded waterproof crack-based stretchable strain sensor, in which the electrical characteristics and sensing performance are not influenced by changes in humidity. This results in a higher number of potential applications for the sensor. A previously developed omni-purpose stretchable strain (OPSS) sensor was used as the basis for this work, which utilizes a metal cracking structure and provides a wide sensing range and high sensitivity. Changes in the conductivity of the OPSS sensor, based on humidity conditions, were investigated along with the potential possibility of using the design as a humidity sensor. However, to prevent conductivity variation, which can decrease the reliability and sensing ability of the OPSS sensor, PDMS was utilized as a shielding layer over the OPSS sensor. The PDMS-shielded OPSS sensor showed approximately the same electrical characteristics as previous designs, including in a high humidity environment, while maintaining its strain sensing capabilities. The developed sensor shows promise for use under high humidity conditions and in underwater applications. Therefore, considering its unique features and reliable sensing performance, the developed PDMS-shielded waterproof OPSS sensor has potential utility in a wide range of applications, such as motion monitoring, medical robotics and wearable healthcare devices.
Au/PDMS membranes are widely used to fabricate strain sensors which can detect input signals. An interfacial adhesion between metal films and polydimethylsiloxane (PDMS) substrates is one of the important factors determining the performance of strain sensors, in terms of robustness, reliability, and sensitivity. Here, we fabricate Au/PDMS membranes with (3-mercaptopropyl) trimethoxysilane (MPTMS) treatment. PDMS membranes were fabricated by spin-coating and the thickness was controlled by varying the spin rates. Au electrodes were deposited on the PDMS membrane by metal sputtering and the thickness was controlled by varying sputtering time. Owing to the MPTMS treatment, the interfacial adhesion between the Au electrode and the PDMS membrane was strengthened and the membrane was highly transparent. The Au electrode, fabricated with a sputtering time of 50 s, had the highest gauge factor at a maximum strain of ~0.7%, and the Au electrode fabricated with a sputtering time of 60 s had the maximum strain range among sputtering times of 50, 60, and 120 s. Our technique of using Au/PDMS with MPTMS treatment could be applied to the fabrication of strain sensors.
Precise motion control is important in robotic surgery, especially corneal surgery. This paper develops a new tension-measurement system for forceps used in corneal surgery, wherein contact force is applied only to a specific location for precise control, with precise movements detected by attaching a nano-crack sensor to the corresponding part. The nano-crack sensor used here customizes the working range and sensor sensitivity to match the strain rate of the tip of the forceps. Therefore, the tension in the suture can be sufficiently measured even at suture failure. The printed circuit board attached to the bottom of the system is designed to simultaneously collect data from several sensors, visualizing the direction and magnitude of the tension in order to inform the surgeon of how much tension is being applied. This system was verified by performing pig-corneal suturing.
In this study, we introduce a novel design for a three-dimensional (3D) controller, which incorporates the omni-purpose stretchable strain sensor (OPSS sensor). This sensor exhibits both remarkable sensitivity, with a gauge factor of approximately 30, and an extensive working range, accommodating strain up to 150%, thereby enabling accurate 3D motion sensing. The 3D controller is structured such that its triaxial motion can be discerned independently along the X, Y, and Z axes by quantifying the deformation of the controller through multiple OPSS sensors affixed to its surface. To ensure precise and real-time 3D motion sensing, a machine learning-based data analysis technique was implemented for the effective interpretation of the multiple sensor signals. The outcomes reveal that the resistance-based sensors successfully and accurately track the 3D controller’s motion. We believe that this innovative design holds the potential to augment the performance of 3D motion sensing devices across a diverse range of applications, encompassing gaming, virtual reality, and robotics.
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