Skip to main content

Reflective Hybrid Sensor

A Reflective Hybrid Sensor for Dual-parameter Measurement of Refractive Index and Temperature


A reflective hybrid sensor for simultaneous measurement of refractive index (RI) and temperature is proposed and demonstrated. The sensor is constructed by cascading a tapered singlemode fiber-nocore fiber-singlemode fiber (TSNS) structure and an Fabry-Perot interferometer (FPI). The characteristic peaks or dips corresponding to TSNS and FPI can be identified from the reflected composite spectrum, which gives rise to the direct interrogations of TSNS and FPI for RI and temperature.
 
An ultrahigh RI sensitivity up to 1145.9 nm/RIU is obtained by tapering the nocore fiber; while the temperature sensitivity is available to be 193 pm/°C due to the excellent thermal response property of UV glue that seals the FPI air cavity. The sensor is featured with ability of dual-parameter measurement, high sensitivity, easy fabrication and ultralow cross-sensitivity, which makes it attractive in RI-based chemical and biological sensing applications.

Structure and principle

The schematic diagram of the proposed hybrid sensor structure is presented in Fig. 1. (a). A TSNS structure and an FPI are concatenated in a fiber, where d denotes the waist diameter of tapered NCF; L and L1 represent the length of tapered NCF and FPI cavity, respectively. The FPI is formed by inserting the right SMF of TSNS structure and another segment of SMF at both ends of HCC. When light is injected into NCF from lead-in SMF, a number of higher-order modes are excited due to the core.
Fig. 9 presents a schematic diagram of the experimental setup, consisting of a broadband light source (BBS, NKT Photonics, SuperK Compact), an optical spectrum analyzer (OSA, Anritsu, MS9740A), and a circulator. We prepared ten groups of glycerol solutions for RI sensing test. The RI of the glycerol solutions were calibrated by an Abbe refractometer at room temperature of 20 °C. After each test, the whole sensor was carefully cleaned with deionized water to eliminate the residual liquid.
In summary, we have proposed and demonstrated a reflective sensor for simultaneous measurement of refractive index and temperature by cascaded TSNS and FPI, which results in a reflective probe configuration that is conductive for the application in liquid environment. The TSNS and FPI respond independently to RI and temperature, respectively, implying an ultralow cross-sensitivity. Experimental results show that the hybrid sensor offers a maximum RI sensitivity of 1145.9 nm/RIU.

Hybrid sensor technology, smart sensing devices, multi-functional sensors, IoT hybrid sensors, biomedical hybrid sensor, environmental monitoring sensor, hybrid optical sensor, wearable hybrid sensor, hybrid pressure sensor, wireless hybrid sensor, hybrid biosensor, next-generation sensors, hybrid imaging sensor, hybrid energy sensor, real-time hybrid sensing, hybrid motion sensor, hybrid nanotechnology sensor, hybrid chemical sensor, hybrid sensor applications, advanced hybrid sensor

Comments

Popular posts from this blog

HealthAIoT: Revolutionizing Smart Healthcare! HealthAIoT combines Artificial Intelligence and the Internet of Things to transform healthcare through real-time monitoring, predictive analytics, and personalized treatment. It enables smarter diagnostics, remote patient care, and proactive health management, enhancing efficiency and outcomes while reducing costs. HealthAIoT is the future of connected, intelligent, and patient-centric healthcare systems. What is HealthAIoT? HealthAIoT is the convergence of Artificial Intelligence (AI) and the Internet of Things (IoT) in the healthcare industry. It integrates smart devices, sensors, and wearables with AI-powered software to monitor, diagnose, and manage health conditions in real-time. This fusion is enabling a new era of smart, connected, and intelligent healthcare systems . Key Components IoT Devices in Healthcare Wearables (e.g., smartwatches, fitness trackers) Medical devices (e.g., glucose monitors, heart rate sensors) Rem...
Detecting Co-Resident Attacks in 5G Clouds! Detecting co-resident attacks in 5G clouds involves identifying malicious activities where attackers share physical cloud resources with victims to steal data or disrupt services. Techniques like machine learning, behavioral analysis, and resource monitoring help detect unusual patterns, ensuring stronger security and privacy in 5G cloud environments. Detecting Co-Resident Attacks in 5G Clouds In a 5G cloud environment, many different users (including businesses and individuals) share the same physical infrastructure through virtualization technologies like Virtual Machines (VMs) and containers. Co-resident attacks occur when a malicious user manages to place their VM or container on the same physical server as a target. Once co-residency is achieved, attackers can exploit shared resources like CPU caches, memory buses, or network interfaces to gather sensitive information or launch denial-of-service (DoS) attacks. Why are Co-Resident Attack...

Network Architecture

An introduction to satellite network architecture Satellite networking is a digital revolution that connects people from across the world instantly -- from enabling real-time communications to making the world a safer place. A satellite is an artificial object put into the Earth's orbit to gather and distribute crucial data. Since the late 1950s, satellites have only transmitted and received data, as bent pipe satellites weren't able to perform other functions. In modern times, a group of satellites in the same orbit forms a satellite network. Satellite networks process data and provide accurate visual and textual information. Unlike terrestrial network infrastructure, satellite network scalability isn't limited by geography and cost. According to a March 2025 report from Goldman Sachs, the global satellite market is expected to hit $108 billion by 2035, growing sevenfold from its current valuation. Satellite networks consist of the following: The ground equipment. The sa...