Flexible electronic devices are normally based on organic polymer substrate. In this work, ultra-thin glass based flexible, transparent and ultra-sensitive ZnO/glass surface acoustic wave (SAW) humidity sensor is developed using a composite sensing layer of ZnO nanowires (NWs) and graphene quantum dots (GQDs). It shows much larger effective electromechanical coupling coefficients and signal amplitudes, compared with those of flexible polymer based SAW devices reported in literature. Attributed to large specific surface areas of ZnO NWs, large numbers of hydrophilic functional groups of GQDs, as well as the formation of p-n heterojunctions between GQDs and ZnO NWs, the developed ZnO/glass flexible SAW sensor shows an ultra-high humidity sensitivity of 40.16 kHz/%RH, along with its excellent stability and repeatability. This flexible and transparent SAW sensor has demonstrated insignificant deterioration of humidity sensing performance, when it is bent on a curved surface with a bending angle of 30, revealing its potential applications for sensing on curved and complex surfaces. The humidity sensing and human breathing detection have further been demonstrated for wearable electronic applications using ultra-thin glass based devices with completely inorganic materials.

Flexible and stretchable strain sensors are vital for emerging fields of wearable and personal electronics, but it is a huge challenge for them to possess both wide-range measurement capability and good sensitivity. In this study, a highly stretchable strain sensor with a wide strain range and a good sensitivity is fabricated based on smart composites of carbon black (CB)/wrinkled Ecoflex. The sensor exhibits a maximum recoverable strain up to 500% and a high gauge factor of 67.7. It has a low hysteresis, a fast signal response (as short as 120 ms) and a high reproducibility (up to 5000 cycles with a strain of 150%). The sensor is capable of detecting and capturing wide-range human activities, from speech recognition, pulse monitoring, to vigorous motions. It is also applicable for real-time monitoring of robot movements and vehicle security crash in an anthropomorphic field. More importantly, the sensor is successfully used to send signals of a volunteer's breathing data to a local hospital in real time through a big-data cloud platform. This research provides the feasibility using strain sensor for wearable internet of things and demonstrates its exciting prospect for healthcare applications.

A nano-patterning process is reported in this paper, which can achieve surface acoustic wave (SAW) devices with an extremely high frequency and a super-high mass sensitivity. An integrated lift-off process with ion beam milling is used to minimize short-circuiting problem and improve quality of nanoscale interdigital transducers (IDTs). A specifically designed PEC algorithm is applied to mitigate proximity effects occurring in the conventional electron-beam lithography process. The IDTs with a period of 160 nm and a finger width of 35 nm are achieved, enabling a frequency of 30 GHz on

Surface acoustic wave (SAW) devices are widely used for physical, chemical, and biological sensing applications, and their sensing mechanisms are generally based on frequency changes due to mass-loading effects at the acoustic wave propagation area between two interdigitated transducers (IDTs). In this paper, a new sensing mechanism has been proposed based on a significantly enhanced mass-loading effect generated directly on Au IDT electrodes, which enables significantly enhanced sensitivity, compared with that of conventional SAW devices. The fabricated ultrahigh-frequency SAW devices show a significant mass-loading effect on the electrodes. When the Au-electrode thickness increased from 12 to 25 nm, the Rayleigh mode resonant frequency decreased from 7.77 to 5.93 GHz, while that of the higher longitudinal leaky SAW decreased from 11.87 to 9.83 GHz. The corresponding mass sensitivity of 7309 MHz•mm 2 •μg −1 (Rayleigh mode) is ∼8.9 × 10 11 times larger than that of a conventional quartz crystal balance (with a frequency of 5 MHz) and ∼1000 times higher than that of conventional SAW devices (with a frequency of 978 MHz). Trinitrotoluene concentration as low as 4.4 × 10 −9 M (mol•L −1 ) can be detected using the fabricated SAW sensor, proving its giant mass-loading effect and ultrahigh sensitivity.

The tomography technique is an effective way to quantitatively evaluate damage from reconstruction imaging in structure health monitoring (SHM). The reconstruction algorithm for the probabilistic inspection of damage (RAPID) algorithm based on the signal difference coefficient (SDC) feature is a promising approach due to its superior performance. This paper focuses on the influence of different patterns of PZT (Lead Zirconate Titanate) sensor array configurations, i.e., the circular, square, and parallel array, on reconstruction image qualities for evaluating hole and crack damage. Variable shape parameters are applied to account for the unequal damage distances of different actuator-sensor pairs. Considering the directionality scattering fields of cracks, the angular scattering pattern of the SDC values are studied by simulation. The SDC variations for different groups of sensing paths at the same actuator are applied to predict the crack orientation. An improved RAPID algorithm is proposed by defining an additional SDC value of 1 in the path along the predicted crack orientation, which is determined by the point of the actuator causing the minimal SDC variation and the center point of the initial reconstruction image of the crack. The results show that the improved RAPID algorithm is effective for the evaluation of crack damage. Reconstruction image qualities with three PZT sensor array configurations for both holes and cracks are compared. The research is significant for selecting the PZT sensor array configuration in SHM.