Miniature Optical Fiber Fabry-Perot Interferometer Based on a Single-Crystal Metal-Organic Framework for the Detection and Quantification of Benzene and Ethanol at Low Concentrations in Nitrogen Gas.

This study reports for the first time, to the best of our knowledge, a real-time detection of ultralow-concentration chemical gases using fiber-optic technology, combining a miniaturized Fabry-Perot interferometer (FPI) with metal-organic frameworks (MOFs). The sensor consists of a short and thick-walled silica capillary segment spliced to a lead-in single-mode fiber (SMF), housing a tiny single crystal of HKUST-1 MOF, imparting chemoselectivity features. Ethanol and benzene gases were tested, resulting in a shift in the FPI interference signal. The sensor demonstrated high sensitivity, detecting ethanol gas concentrations (EGCs) with a sensitivity of 0.428 nm/ppm between 24.9 and 40.11 ppm and benzene gas concentrations (BGCs) with a sensitivity of 0.15 nm/ppm between 99 and 124 ppm. The selectivity study involved a combination of three ultralow concentrations of ethanol, benzene, and toluene gases, revealing an enhancement factor of 436% for benzene and 140% for toluene, attributed to the improved miscibility of these conjugated ring molecules with the alkane chains of the ethanol-modified HKUST-1. Experimental tests confirmed the sensor's viability, demonstrating significantly improved response time and spectral characteristics through crystal polishing, indicating its potential for quantifying and detecting chemical gases at ultralow concentrations. This technology may prevent energy resource losses, and the sensor's small size and robust construction make it applicable in confined and hazardous locations.

Miniaturized fluorescence pH sensor with assembly free ball lens on a tapered multimode optical fiber.

In biochemistry, the absence of a compact, assembly-free pH sensor with high sensitivity and signal-to-noise ratio has been a persistent hurdle in achieving accurate pH measurements in real time, particularly in complex liquid environments. This manuscript introduces what we believe to be a novel solution in the form of a miniaturized pH sensor utilizing an assembly-free ball lens on a tapered multimode optical fiber (TMMF), offering the potential to revolutionize pH sensing in biochemical applications. A multimode optical fiber (MMF) was subjected to tapering processes, leading to the creation of an ultra-thin needle-like structure with a cross-sectional diameter of about 12.5 µm and a taper length of 3 mm. Subsequently, a ball lens possessing a diameter of 20 µm was fabricated at the apex of the taper. The resultant structure was coated utilizing the dip-coating technique, involving a composite mixture of epoxy and pH-sensitive dye, 2',7'-bis(2-carboxyethyl)-5-(and-6)-carboxyfluorescein (BCECF), thereby ensconcing the tapered ball lens with dye molecules for pH sensing. This study encompassed the fabrication and evaluation of six distinct fiber structures, incorporating the cleaved endface, the convex lens, and the ball lens structures to compare light focal lengths and propagation intensities. Computational simulations and numerical analyses were conducted to elucidate the encompassing light focal distances across the full array of lens configurations. The efficacy of the proposed pH sensor was subsequently assessed through its deployment within a complex liquid medium spanning a pH spectrum ranging from 6 to 8. Real-time data acquisition was performed with a fast response time of 0.5 seconds. A comparative analysis with a pH sensor predicated upon a single TMMF embedded with the fluorescent dye underscored the substantial signal enhancement achieved by the proposed system twice the fluorescence signal magnitude. The proposed assembly-free miniaturized pH sensor not only substantiates enhanced signal collection efficiency but also decisively addresses the persistent challenges of poor signal-to-noise ratio encountered within contemporary miniaturized pH probes.

One-dimensional sensor learns to sense three-dimensional space.

A sensor system with ultra-high sensitivity, high resolution, rapid response time, and a high signal-to-noise ratio can produce raw data that is exceedingly rich in information, including signals that have the appearances of "noise". The "noise" feature directly correlates to measurands in orthogonal dimensions, and are simply manifestations of the off-diagonal elements of 2nd-order tensors that describe the spatial anisotropy of matter in physical structures and spaces. The use of machine learning techniques to extract useful meanings from the rich information afforded by ultra-sensitive one-dimensional sensors may offer the potential for probing mundane events for novel embedded phenomena. Inspired by our very recent invention of ultra-sensitive optical-based inclinometers, this work aims to answer a transformative question for the first time: can a single-dimension point sensor with ultra-high sensitivity, fidelity, and signal-to-noise ratio identify an arbitrary mechanical impact event in three-dimensional space? This work is expected to inspire researchers in the fields of sensing and measurement to promote the development of a new generation of powerful sensors or sensor networks with expanded functionalities and enhanced intelligence, which may provide rich n-dimensional information, and subsequently, data-driven insights into significant problems.