ABSTRACT
An FMCW LiDAR (frequency-modulated continuous-wave light detection and ranging) is a sensor that can measure distance using optical interference frequency (fb). This sensor has recently attracted interest because it is robust to harsh environmental conditions and sunlight due to the wave properties of the laser. Theoretically, when the frequency of the reference beam is linearly modulated, a constant fb is obtained with respect to the distance. However, when the frequency of the reference beam fails to be linearly modulated, the distance measurement is not accurate. In this work, linear frequency modulation control using frequency detection is proposed to improve the distance accuracy. The FVC (frequency to voltage converting) method is used to measure fb for high-speed frequency modulation control. The experimental results show that linear frequency modulation control using an FVC improves FMCW LiDAR performance in terms of control speed and frequency accuracy.
ABSTRACT
In the emerging Internet of Things (IoT) society, there is a significant need for low-cost, high-performance flexible humidity sensors in wearable devices. However, commercially available humidity sensors lack flexibility or require expensive and complex fabrication methods, limiting their application and widespread use. We report a high-performance printed flexible humidity sensor using a cellulose nanofiber/carbon black (CNF/CB) composite. The cellulose nanofiber enables excellent dispersion of carbon black, which facilitates the ink preparation and printing process. At the same time, its hydrophilic and porous nature provides high sensitivity and fast response to humidity. Significant resistance changes of 120% were observed in the sensor at humidity ranging from 30% RH to 90% RH, with a fast response time of 10 s and a recovery time of 6 s. Furthermore, the developed sensor also exhibited high-performance uniformity, response stability, and flexibility. A simple humidity detection device was fabricated and successfully applied to monitor human respiration and noncontact fingertip moisture as a proof-of-concept.
ABSTRACT
Tactile sensing, particularly the detection of object slippage, is required for skillful object handling by robotic grippers. The real-time measurement and identification of the dynamic shear forces that result from slippage events are crucial for slip detection and effective object interaction. In this study, a ferroelectric polymer-based printed soft sensor for object slippage detection was developed and fabricated by screen printing. The proposed sensor demonstrated a sensitivity of 8.2 µC·cm-2 and was responsive to shear forces applied in both the parallel and perpendicular directions. An amplifier circuit, based on a printed organic thin-film transistor, was applied and achieved a high sensitivity of 0.1 cm2/V·s. Therefore, this study experimentally demonstrates the effectiveness of the proposed printable high-sensitivity tactile sensor, which could serve as part of a wearable robotic e-skin. The sensor could facilitate the production of a system to detect and prevent the slippage of objects from robotic grippers.
ABSTRACT
There are few reports on resistive strain sensors that exhibit both high sensitivity and a wide working range under stretching. We have newly developed a high-performance strain sensor based on a brittle-stretchable conductive network that consists of both brittle and stretchable conductive layers and is fabricated on a stretchable substrate using the screen-printing method. Adding strain usually generates structural cracks in brittle conductive layers leading to a significant increase in resistance, while a stretchable conductive layer bridges these cracks to maintain the conductive pathways under high-strain conditions. This novel conductive network endows superior electrical-mechanical performance to the strain sensors, which possess high sensitivity (gauge factor > 870) over the entire working range (â¼100%). Additionally, the developed sensors showed unique anisotropic bend-sensing characteristics, which could be used to detect the bending directions. This high degree of comprehensive performance results in a strain sensor with the capability for full-range human motion detection and robotic motion sensing.
ABSTRACT
Salmon cartilage proteoglycan fractions have recently gained favor as ingredients of functional food and cosmetics. An optimal hot water method to extract proteoglycan from salmon cartilage has recently been developed. The extracted cartilage includes hyaluronan and collagen in addition to proteoglycan as counterparts that interact with each other. In this study, biochemical analyses and atomic force microscopical analysis revealed global molecular images of proteoglycan in the hot water extract. More than seventy percent of proteoglycans in this extract maintained their whole native structures. Hyaluronan purified from the hot water extract showed a distribution with high molecular weight similar to hyaluronan considered to be native hyaluronan in cartilage. The current data is evidence of the quality of this hot water cartilage extract.
