Abstract:The temperature fluctuation in a single-phase microchannel heat sink (MCHS) is investigated using the integrated temperature sensors with deionized water as the coolant. Results show that the temperature fluctuation in single phase is not negligible. The causes of the temperature fluctuation are revealed based on both simulation and experiment. It is found that the inlet temperature fluctuation and the gas bubbles separated out from coolant are the main causes. The effect of the inlet temperature fluctuation i… Show more
“…Additionally, different materials, such as graphene and negative thermo-optic coefficient (TOC) materials, are being explored in the context of photonic temperature sensors. [251][252][253][254][255] The silicon has a large TOC (≈1.86 × 10 −4 °C−1 ) compare to silicon oxide. Therefore, silicon-based temperature photonic sensor is usually employed where requires precise temperature because of their high sensing solution at small temperature variations.…”
In recent years, with the further ministration of the semiconductor device in integrated circuits, power consumption and data transmission bandwidth have become insurmountable obstacles. As an integrated technology, photonic integrated circuits (PICs) have a promising potential in the post‐Moore era with more advantages in data processing, communication, and diversified sensing applications for their ultra‐high process speed and low power consumption. Silicon photonics is believed to be an encouraging solution to realize PICs because of the mature CMOS process. The past decades have witnessed a huge growth in silicon PICs. However, there is still a demand for the development of silicon PICs to enable powerful chip‐scale systems and new functionalities. In this paper, a review of the photonic components, functional blocks, and emerging applications for PICs is offered. The common photonic components are classified into several sections, including on‐chip light sources, fiber‐to‐chip couplers, photonic resonators, waveguide‐based sensors, on‐chip photodetectors, and modulators. The functional blocks of the PICs mentioned in this review are photonic memories and photonic neural networks. Finally, the paper concludes with emerging applications for further study.
“…Additionally, different materials, such as graphene and negative thermo-optic coefficient (TOC) materials, are being explored in the context of photonic temperature sensors. [251][252][253][254][255] The silicon has a large TOC (≈1.86 × 10 −4 °C−1 ) compare to silicon oxide. Therefore, silicon-based temperature photonic sensor is usually employed where requires precise temperature because of their high sensing solution at small temperature variations.…”
In recent years, with the further ministration of the semiconductor device in integrated circuits, power consumption and data transmission bandwidth have become insurmountable obstacles. As an integrated technology, photonic integrated circuits (PICs) have a promising potential in the post‐Moore era with more advantages in data processing, communication, and diversified sensing applications for their ultra‐high process speed and low power consumption. Silicon photonics is believed to be an encouraging solution to realize PICs because of the mature CMOS process. The past decades have witnessed a huge growth in silicon PICs. However, there is still a demand for the development of silicon PICs to enable powerful chip‐scale systems and new functionalities. In this paper, a review of the photonic components, functional blocks, and emerging applications for PICs is offered. The common photonic components are classified into several sections, including on‐chip light sources, fiber‐to‐chip couplers, photonic resonators, waveguide‐based sensors, on‐chip photodetectors, and modulators. The functional blocks of the PICs mentioned in this review are photonic memories and photonic neural networks. Finally, the paper concludes with emerging applications for further study.
“…and transmits a resulting impulse for measurement and control system. [24][25][26][27][28][29] In addition to the most common complementary metal oxide semiconductor (CMOS)-based image sensor for computer vision, microelectromechanical systems (MEMS)-based microphone for voice recognition, another MEMS sensors (such as accelerometers, gyroscopes, pressure sensors, tactile sensors, biosensors, etc.) were widely applied to many applications, [30][31][32][33][34] especially for wearable electronics, due to their advantages of small size, low power consumption, low cost, high reliability, and robustness.…”
Significant growth in the development and deployment of artificial intelligence (AI) is being witnessed. Driven by the great versatility of emerging computer science and material science, various AI sensors provide cost‐effective approaches for a wide range of monitoring applications toward the realization of smart homes and personal healthcare. Advanced AI sensors have multiple sensors capable of detecting multidimensional information and human‐brain‐like computation device for data processing. Herein, this review outlines the recent advances in the development of AI sensors. This review first introduces the materials, fabrication methods, and algorithms of current AI sensors and their applications, i.e., complementary metal oxide semiconductor image sensors for computer vision, microelectromechanical systems, microphone sensors for voice recognition, and wearable sensors for gesture recognition. Then, the recent advances in AI wearables sensors and self‐powered sensor systems are highlighted. Next, the current developments of neuromorphic computing systems, multimodality, and digital twins are reviewed. Last, a perspective on future directions for further research development is also provided. In summary, the trend of advanced AI sensors is the complementary between edge computing and cloud computing, which will show great potential in the applications of smart buildings, individual healthcare, the Internet of things, etc.
“…Microelectromechanical system (MEMS) devices have been developed and widely tremendously in the past decades [1][2][3][4][5][6]. Pressure sensors are one of the most significant branches of MEMS devices in the commercial market.…”
In this paper we demonstrate a novel acoustic wave pressure sensor, based on an aluminum nitride (AlN) piezoelectric thin film. It contains an integrated vacuum cavity, which is micro-fabricated using a cavity silicon-on-insulator (SOI) wafer. This sensor can directly measure the absolute pressure without the help of an external package, and the vacuum cavity gives the sensor a very accurate reference pressure. Meanwhile, the presented pressure sensor is superior to previously reported acoustic wave pressure sensors in terms of the temperature drift. With the carefully designed dual temperature compensation structure, a very low temperature coefficient of frequency (TCF) is achieved. Experimental results show the sensor can measure the absolute pressure in the range of 0 to 0.4 MPa, while the temperature range is from 20 °C to 220 °C with a TCF of −14.4 ppm/°C. Such a TCF is only about half of that of previously reported works.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.