Polystyrene (PS) opal and titania (TiO₂) inverse opal films were fabricated by the self-assembly colloidal crystal template technique. Based on Bragg’s law, these sensors were used to detect the different concentrations of ethanol solution. The results indicated that TiO₂ inverse opal films were advantageous over PS opal film for detecting the ethanol concentration. TiO₂ inverse opal films sintered at 600 °C retained the highest sensitivity for ethanol concentration identification, since the anatase phase was transformed into the rutile phase, which resulted in an enhancement of the refractive index, i.e., an increase in the amount of the red shift.

A two-dimensional (2D) grating guided-mode resonance (GMR) tunable filter is experimentally demonstrated using a low-cost two-step nanoimprinting technology with a one-dimensional (1D) grating polydimethylsiloxane mold. For the first nanoimprinting, we precisely control the UV LED irradiation dosage and demold the device when the UV glue is partially cured and the 1D grating mold is then rotated by three different angles, 30°, 60°, and 90°, for the second nanoimprinting to obtain 2D grating structures with different crossing angles. A high-refractive-index film ZnO is then coated on the surface of the grating structure to form the GMR filter devices. The simulation and experimental results demonstrate that the passband central wavelength of the filter can be tuned by rotating the device to change azimuth angle of the incident light. We compare these three 2D GMR filters with differential crossing angles and find that the filter device with a crossing angle of 60° exhibits the best performance. The tunable range of its central wavelength is 668−742 nm when the azimuth angle varies from 30° to 90°.

A transmitted-type guided-mode resonance (GMR) sensor is presented for using an electro-optic heterodyne interferometer to tune phase detection sensitivity. The GMR grating waveguide structure is fabricated using a low-cost nanoimprinting SiO₂ sol-gel process and sputtering TiO₂ film. The phase properties of the GMR sensor are numerically investigated to verify its phase detection capability in a heterodyne interferometer. The phase curves for both transmitted- and reflected-type GMR sensors are experimentally obtained and compared. We conclude that the transmitted-type GMR sensor is more feasible for tuning phase detection sensitivity by rotating the analyzer in the electro-optic heterodyne interferometer. In our experiment, we achieved the GMR sensor phase detection sensitivity as high as 1.8 × 10⁻⁷ RIU.

This paper proposes a design for a dielectric-grating-coupled surface plasmon resonance (SPR) sensor that can be fabricated using a low-cost nanoimprint process and exhibits a high phase detection sensitivity when light is incident on the backside of the sensor and does not pass through the analyte on the front-side of the sensor. A low-refractive-index material (mesoporous silica) is utilized to implement a reverse symmetric waveguide structure that can enhance electric-field strength on the sensor surface and improve detection sensitivity. A sol-gel method is used to fill the groove of the grating structure with a high-refractive-index material (titanium dioxide), and surface smoothness is improved via a flat silicon impression mold. The experimental results indicate that although the sensor device exhibits defects and non-smooth surface relief, phase detection sensitivity can still be achieved as high as 2 × 10⁻⁵ RIU by using an electro-optic heterodyne interferometer.

This paper presents an Internet of Things (IoT) application that utilizes an AI classifier for fast-object detection using the frame difference method. This method, with its shorter duration, is the most efficient and suitable for fast-object detection in IoT systems, which require energy-efficient applications compared to end-to-end methods. We have implemented this technique on three edge devices: AMD AlveoTMU50, Jetson Orin Nano, and Hailo-8TMAI Accelerator, and four models with artificial neural networks and transformer models. We examined various classes, including birds, cars, trains, and airplanes. Using the frame difference method, the MobileNet model consistently has high accuracy, low latency, and is highly energy-efficient. YOLOX consistently shows the lowest accuracy, lowest latency, and lowest efficiency. The experimental results show that the proposed algorithm has improved the average accuracy gain by 28.314%, the average efficiency gain by 3.6 times, and the average latency reduction by 39.305% compared to the end-to-end method. Of all these classes, the faster objects are trains and airplanes. Experiments show that the accuracy percentage for trains and airplanes is lower than other categories. So, in tasks that require fast detection and accurate results, end-to-end methods can be a disaster because they cannot handle fast object detection. To improve computational efficiency, we designed our proposed method as a lightweight detection algorithm. It is well suited for applications in IoT systems, especially those that require fast-moving object detection and higher accuracy.

In this paper, the phase detection properties of a grating-coupled surface plasmon resonance (GCSPR) sensor with a thin metal film on the grating structure has been studied by performing finite-difference time-domain simulation first. Both the metal film thickness and modulation height of the grating considerably affect the phase detection properties of GCSPR sensors. The manner in which the metal film thickness affects the phase curve in the grating-coupled configuration is slightly different from that in the conventional prism-coupled surface plasmon resonance (PCSPR) configuration. For experiment, an electro-optic heterodyne interferometer is used to perform phase detection of the GCSPR sensor and a refractive index resolution of 1.5 × 0⁻⁶ RIU are obtained. The results reveal that the phase detection sensitivity of the GCSPR sensor may be comparable to that of the PCSPR sensor.