Fiber–optic sensors have been widely deployed in various applications, and their use has gradually increased since the 1980 s. Distributed fiber–optic sensors, which enable continuous and real–time measurements along the entire length of an optical fiber cable, have undergone significant improvements in underlying industries. In the oil and gas industry, distributed fiber–optic sensors can provide significantly valuable information throughout the life cycle of a well and can monitor pipelines transporting hydrocarbons over great distances. Here, we review the deployment of fiber–optic Rayleigh–based distributed acoustic sensing (DAS), Raman–based distributed temperature sensing (DTS), and Brillouin–based distributed temperature and strain sensing (DTSS) in the oil and gas industry. In particular, we describe the operation principle and basic experimental setups of the DAS, DTS, and DTSS, highlighting their applications in the upstream, midstream, and downstream sectors of the oil and gas industry. We further developed a prototype of a fiber–optic hybrid DAS–DTS system that simultaneously measures vibration and temperature along a multimode fiber (MMF). The reported hybrid sensing system was tested in an operational oil well. This work also discusses the challenges that might hinder the growth of the distributed fiber–optic sensing market in the petroleum industry, and we further point out the future directions of related research.

Red palm weevil (RPW) poses a serious threat to the cultivation of date palms. It is considered to be the most destructive epidemic pest of palms, responsible for massive economic losses worldwide. Curative methods for RPW are not difficult to apply; however, the early detection of the pest remains a great challenge. Although several detection techniques have been implemented for the early detection of RPW, none of these methods have been proven to be reliable. Here, we use an optical-fiber-distributed acoustic sensor (DAS) as a paradigm shift technology for the early detection of RPW. Our sensitive sensor shows a detection of feeding sound produced by larvae as young as 12 days, in an infested tree. In comparison with existing, commonly-used technologies, this novel sensing technique represents a cost-effective and non-invasive alternative that could provide 24-7, real-time monitoring of 1,000 palm trees or even more. It could also monitor the temperature, an essential feature to control farm fires, another major problem for the cultivation of palm trees around the world.

The ultraviolet (UV) wavelength regime is typically divided into four wavelength ranges, i.e., UV-A (320 to 400 nm), UV-B (280 to 320 nm), UV-C (200 to 280 nm), and vacuum-UV (10 to 200 nm). Across these ranges, there are huge needs to realize UV-based photonic and electronic devices, e.g., laser diodes (LDs), light-emitting diodes (LEDs), photodetectors (PDs), high-electron-mobility transistors (HEMTs), metal-oxide-semiconductor field effect transistors, and radio-frequency switches. For instance, the market forecast for UV-LEDs is increasing from $90 million in the year 2014 to $800 million by the year 2020 due to the increasing demands in epoxy curing, water purification, food or medical sterilization, and new emerging applications.¹ The new applications include light sources, lithography, gas or chemical or bioagent sensing, free-space nonline-of-sight communication, phototherapy, forgery detection, medical diagnostic, consumer electronics, and horticulture.²

Red palm weevil (RPW) is a detrimental pest, which has wiped out many palm tree farms worldwide. Early detection of RPW is challenging, especially in large-scale farms. Here, we introduce the combination of machine learning and fiber optic distributed acoustic sensing (DAS) techniques as a solution for the early detection of RPW in vast farms. Within the laboratory environment, we reconstructed the conditions of a farm that includes an infested tree with ∼12 day old weevil larvae and another healthy tree. Meanwhile, some noise sources are introduced, including wind and bird sounds around the trees. After training with the experimental time- and frequency-domain data provided by the fiber optic DAS system, a fully-connected artificial neural network (ANN) and a convolutional neural network (CNN) can efficiently recognize the healthy and infested trees with high classification accuracy values (99.9% by ANN with temporal data and 99.7% by CNN with spectral data, in reasonable noise conditions). This work paves the way for deploying the high efficiency and cost-effective fiber optic DAS to monitor RPW in open-air and large-scale farms containing thousands of trees.

Group-III-nitride optical devices are conventionally important for displays and solid-state lighting, and recently have garnered much interest in the field of visible-light communication. While visible-light laser technology has become mature, developing a range of compact, small footprint, high optical power components for the green-yellow gap wavelengths still requires material development and device design breakthroughs, as well as hybrid integration of materials to overcome the limitations of conventional approaches. The present review focuses on the development of laser and amplified spontaneous emission (ASE) devices in the visible wavelength regime using primarily group-III-nitride and halide-perovskite semiconductors, which are at disparate stages of maturity. While the former is well established in the violet-blue-green operating wavelength regime, the latter, which is capable of solution-based processing and wavelength-tunability in the green-yellow-red regime, promises easy heterogeneous integration to form a new class of hybrid semiconductor light emitters. Prospects for the use of perovskite in ASE and lasing applications are discussed in the context of facile fabrication techniques and promising wavelength-tunable light-emitting device applications, as well as the potential integration with group-III-nitride contact and distributed Bragg reflector layers, which is promising as a future research direction. The absence of lattice-matching limitations, and the presence of direct bandgaps and excellent carrier transport in halide-perovskite semiconductors, are both encouraging and thought-provoking for device researchers who seek to explore new possibilities either experimentally or theoretically. These combined properties inspire researchers who seek to examine the suitability of such materials for potential novel electrical injection devices designed for targeted applications related to lasing and operating-wavelength tuning.

Photodetectors used in wireless applications suffer from a trade-off between their response speeds and their active areas, which limits the received signal-to-noise ratio (SNR). Conventional light-focusing elements used to improve the SNR narrow the field of view (FOV). Herein, we demonstrate a versatile imaging light-focusing element featuring a wide FOV and high optical gain using fused fiber-optic tapers. To verify the practicality of the proposed design, we demonstrated and tested a wide-FOV optical detector for optical wireless communication that can be used for wavelengths ranging from the visible-light band to the near infrared. The proposed detector offers improvements over luminescent wide-FOV detectors, including higher efficiency, a broader modulation bandwidth, and indefinite stability.