Boosting SNR of cascaded FBGs in a sapphire fiber through a rapid heat treatment.

This Letter reports the performance of femtosecond (fs) laser-written distributed fiber Bragg gratings (FBGs) under high-temperature conditions up to 1600°C and explores the impact of rapid heat treatment on signal-to-noise ratio (SNR) enhancement. FBGs are essential for reliable optical sensing in extreme temperature environments. Comprehensive tests demonstrate the remarkable performance and resilience of FBGs at temperatures up to 1600°C, confirming their suitability for deployment in such conditions. The study also reveals significant fringe visibility improvements of up to ∼10 dB on a 1-m-long sapphire optical fiber through rapid heat treatment, representing a first-time achievement to the best of our knowledge. These enhancements are vital for improving the SNR and overall performance of optical fiber systems in extreme temperatures. Furthermore, the research attains long-term stability for the cascaded FBGs over a 24-hr period at 1600°C. This research expands our understanding of the FBG behavior in high-temperature environments and opens avenues for developing robust optical fiber systems for energy, aerospace, oil and gas, and high-temperature distributed sensing applications.

Calculations of adsorption-dependent refractive indices of metal-organic frameworks for gas sensing applications.

Detection of volatile organic compounds (VOCs) is one of the most challenging tasks in modelling breath analyzers because of their low concentrations (parts-per-billion (ppb) to parts-per-million (ppm)) in breath and the high humidity levels in exhaled breaths. The refractive index is one of the crucial optical properties of metal-organic frameworks (MOFs), which is changeable via the variation of gas species and concentrations that can be utilized as gas detectors. Herein, for the first time, we used Lorentz-Lorentz, Maxwell-Ga, and Bruggeman effective medium approximation (EMA) equations to compute the percentage change in the index of refraction (Δn%) of ZIF-7, ZIF-8, ZIF-90, MIL-101(Cr) and HKUST-1 upon exposure to ethanol at various partial pressures. We also determined the enhancement factors of the mentioned MOFs to assess the storage capability of MOFs and the biosensors' selectivity through guest-host interactions, especially, at low guest concentrations.

Identification of Volatile Organic Liquids by Combining an Array of Fiber-Optic Sensors and Machine Learning.

In this paper, we report an array of fiber-optic sensors based on the Fabry-Perot interference principle and machine learning-based analyses for identifying volatile organic liquids (VOLs). Three optical fiber tip sensors with different surfaces were included in the array of sensors to improve the accuracy for identifying liquids: an intrinsic (unmodified) flat cleaved endface, a hydrophobic-coated endface, and a hydrophilic-coated endface. The time-transient responses of evaporating droplets from the optical fiber tip sensors were monitored and collected following the controlled immersion tests of 11 different organic liquids. A continuous wavelet transform was used to convert the time-transient response signal into images. These images were then utilized to train convolution neural networks for classification (identification of VOLs). We show that diversity in the information collected using the array of three sensors helps machine learning-based methods perform significantly better. We explore different pipelines for combining the information from the array of sensors within a machine learning framework and their effect on the robustness of models. The results showed that the machine learning-based methods achieved high accuracy in their classification of different liquids based on their droplet evaporation time-transient events.

Thermally robust and highly stable method for splicing silica glass fiber to crystalline sapphire fiber.

This research reports an advancement in splicing silica glass fiber to sapphire single-crystal optical fiber (SCF) using a specialized glass processing device, including data that demonstrate the thermal stability of the splice to 1000°C. A filament heating process was used to produce a robust splice between the dissimilar fibers. A femtosecond laser is used to inscribe a fiber Bragg gratings sensor into the SCF to measure the high-temperature capabilities and signal attenuation characteristics of the splice joint. The experimental results demonstrate that the proposed splicing method produces a splice joint that is robust, stable, repeatable, and withstands temperatures up to 1000°C with a low attenuation of 0.5 dB. The proposed method allows placement of SCF-based sensors in the extreme environments encountered in various engineering fields, such as nuclear, chemical, aviation, and metals manufacturing, to enable improvements in process monitoring, product quality, and production efficiency.

A Fiber-Optic Sensor-Embedded and Machine Learning Assisted Smart Helmet for Multi-Variable Blunt Force Impact Sensing in Real Time.

Early on-site diagnosis of mild traumatic brain injury (mTBI) will provide the best guidance for clinical practice. However, existing methods and sensors cannot provide sufficiently detailed physical information related to the blunt force impact. In the present work, a smart helmet with a single embedded fiber Bragg grating (FBG) sensor is developed, which can monitor complex blunt force impact events in real time under both wired and wireless modes. The transient oscillatory signal "fingerprint" can specifically reflect the impact-caused physical deformation of the local helmet structure. By combination with machine learning algorithms, the unknown transient impact can be recognized quickly and accurately in terms of impact magnitude, direction, and latitude. Optimization of the training dataset was also validated, and the boosted ML models, such as the S-SVM+ and S-IBK+, are able to predict accurately with complex databases. Thus, the ML-FBG smart helmet system developed by this work may become a crucial intervention alternative during a traumatic brain injury event.

Miniaturized 7-in-1 fiber-optic Raman probe.

This Letter reports a miniature 7-in-1 fiber-optic Raman probe that eliminates the inelastic background Raman signal from a long-fused silica fiber. Its foremost purpose is to enhance a method for investigating extraordinarily tiny substances and effectively capturing Raman inelastic backscattered signals using optical fibers. We successfully used our home-built fiber taper device to combine seven multimode fibers into a single fiber taper with a probe diameter of approximately 35 µm. By experimentally comparing the traditional bare fiber-based Raman spectroscopy system with the miniaturized tapered fiber-optic Raman sensor using liquid solutions, the novel probe's capability is demonstrated. We observed that the miniaturized probe effectively removed the Raman background signal originating from the optical fiber and confirmed expected outcomes for a series of common Raman spectra.

Micromachined Optical Fiber Sensors for Biomedical Applications.

Optical fibers revolutionized the rate of information reception and transmission in telecommunications. The revolution has now extended to the field of physicochemical sensing. Optical fiber sensors (OFSs) have found a multitude of applications, spanning from structural health monitoring to biomedical and clinical measurements due to their unique physical and functional advantages, such as small dimensions, light weight, immunity to electromagnetic interference, high sensitivity and resolution, multiplexing, and remote operation. OFSs generally rely on the detection of measurand-induced changes in the optical properties of the light propagating in the fiber, where the OFS essentially functions as the conduit and physical link between the probing light waves and the physicochemical parameters under investigation. Several advanced micromachining techniques have been developed to optimize the structure of OFSs, thus improving their sensing performance. These techniques include fusion splicing, tapering, polishing, and more complicated femtosecond laser micromachining methods. This chapter discusses and reviews the most recent developments in micromachined OFSs specifically for biomedical applications. Step-by-step procedures for several optical fiber micromachining techniques are detailed.

Machine learning identifies liquids employing a simple fiber-optic tip sensor.

We proposed an extremely simple fiber-optic tip sensor system to identify liquids by combining their corresponding droplet evaporation events with analyses using machine learning techniques. Pendant liquid droplets were suspended from the cleaved endface of a single-mode fiber during the experiment. The optical fiber-droplet interface and the droplet-air interface served as two partial reflectors of an extrinsic Fabry-Perot interferometer (EFPI) with a liquid droplet cavity. As the liquid pendant droplet evaporated, its length diminished. A light source can be used to observe the effective change in the net reflectivity of the optical fiber sensor system by observing the resulting optical interference phenomenon of the reflected waves. Using a single-wavelength probing light source, the entire evaporation event of the liquid droplet was precisely captured. The measured time transient response from the fiber-optic tip sensor to an evaporation event of a liquid droplet of interest was then transformed into image data using a continuous wavelet transform. The obtained image data was used to fine-tune pre-trained convolution neural networks (CNNs) for the given task. The results demonstrated that machine learning-based classification methods achieved greater than 98% accuracy in classifying different liquids based on their corresponding droplet evaporation processes, measured by the fiber-optic tip sensor.

Fiber optic sensor embedded smart helmet for real-time impact sensing and analysis through machine learning.

BACKGROUND: Mild traumatic brain injury (mTBI) strongly associates with chronic neurodegenerative impairments such as post-traumatic stress disorder (PTSD) and mild cognitive impairment. Early detection of concussive events would significantly enhance the understanding of head injuries and provide better guidance for urgent diagnoses and the best clinical practices for achieving full recovery. NEW METHOD: A smart helmet was developed with a single embedded fiber Bragg grating (FBG) sensor for real-time sensing of blunt-force impact events to helmets. The transient signals provide both magnitude and directional information about the impact event, and the data can be used for training machine learning (ML) models. RESULTS: The FBG-embedded smart helmet prototype successfully achieved real-time sensing of concussive events. Transient data "fingerprints" consisting of both magnitude and direction of impact, were found to correlate with types of blunt-force impactors. Trained ML models were able to accurately predict (R2 ∼ 0.90) the magnitudes and directions of blunt-force impact events from data not used for model training. COMPARISON WITH EXISTING METHODS: The combination of the smart helmet data with analyses using ML models provides accurate predictions of the types of impactors that caused the events, as well as the magnitudes and the directions of the impact forces, which are unavailable using existing devices. CONCLUSION: This work resulted in an ML-assisted, FBG-embedded smart helmet for real-time identification of concussive events using a highly accurate multi-metric strategy. The use of ML-FBG smart helmet systems can serve as an early-stage intervention strategy during and immediately following a concussive event.

Metal-organic Framework Materials Coupled to Optical Fibers for Chemical Sensing: A Review.

Metal-organic frameworks (MOFs), a newer class of crystalline nanoporous materials, have been in the limelight owing to their exceptional tunability for structures and physicochemical properties, and have found successful applications in gas storage, gas separation, and catalysis. The mesmerizing properties of MOFs, especially the extensive and tunable porosity and chemical selectivity, also make them an excellent candidate class as chemo-sensory materials. Moreover, MOF-based sensors have attracted considerable attention in the past decade. Recent literature reviews focused on the progress of MOF-based electronic sensors and luminescent MOF sensors, while sensors exploiting the dielectric properties (refractive index) of MOFs were also demonstrated and discussed very recently. The motivation of this report is to provide, for the first time, a general review on such MOF sensors with a particular focus on miniature optical fiber (OF) based MOF sensors and to demonstrate the promising potential of MOFs as dielectric coatings on OF for highly sensitive chemical sensing. The fundamental principle of OF-MOF sensors relies on the tunability of the refractive index of a MOF, which is dependent on the amount and type of adsorbed guest molecules in the MOF pores. MOF sensors based on different optical sensing principles are reviewed; challenges and perspectives on further research into the field of OF-MOF sensors are also discussed.

NMR studies of materials loaded into porous-wall hollow glass microspheres.

Porous-wall hollow glass microspheres (PWHGMs) are a form of glass materials that consist of 1-µm-thick porous silica shells, 20-100 µm in diameter, with a hollow cavity in the center. Utilizing the central cavity for material storage and the porous walls for controlled release is a unique combination that renders PWHGMs a superior vehicle for targeted drug delivery. In this study, loaded PWHGMs were characterized for the first time employing proton nuclear magnetic resonance (1H NMR) spectroscopy. A vacuum-based loading system was developed to load PWHGMs with various liquid materials followed by a washing procedure that uses solvents immiscible with the loaded materials. Immiscible binary model systems (chloroform/water, n-dodecane/water), as well as the hydrolysis reaction of isopropyl acetate, were investigated to obtain 1H NMR evidence of loading materials into PWHGMs and their subsequent release to the surrounding solutions. The unique 1H NMR peak shapes and relative integrals of the materials loaded in PWHGMs were distinguishable from those of the same materials in the surrounding solutions. Encounters of isopropyl acetate contained in the PWHGMs with acid protons from concentrated H2SO4 added to the surrounding solution become evident by the formation of the reaction product isopropanol. PWHGMs loaded with H2O and suspended in D2O were used to obtain quantitative release kinetics of H2O-loaded PWHGMs. A five-parameter double-exponential curve fit of experimental 1H NMR signal intensities as a function of time indicated two release rates for H2O from H2O-loaded PWHGMs suspended in D2O with one time constant of 18-20 min and another one of 160 min. The two disparate release-rate time constants are consistent with loaded PWHGMs with breached and unbreached porous walls. The results demonstrate that 1H NMR spectroscopy is particularly useful for investigating formulations and applications of PWHGMs in targeted drug delivery.

A Spatially Distributed Fiber-Optic Temperature Sensor for Applications in the Steel Industry.

This paper presents a spatially distributed fiber-optic sensor system designed for demanding applications, like temperature measurements in the steel industry. The sensor system employed optical frequency domain reflectometry (OFDR) to interrogate Rayleigh backscattering signals in single-mode optical fibers. Temperature measurements employing the OFDR system were compared with conventional thermocouple measurements, accentuating the spatially distributed sensing capability of the fiber-optic system. Experiments were designed and conducted to test the spatial thermal mapping capability of the fiber-optic temperature measurement system. Experimental simulations provided evidence that the optical fiber system could resolve closely spaced temperature features, due to the high spatial resolution and fast measurement rates of the OFDR system. The ability of the fiber-optic system to perform temperature measurements in a metal casting was tested by monitoring aluminum solidification in a sand mold. The optical fiber, encased in a stainless steel tube, survived both mechanically and optically at temperatures exceeding 700 °C. The ability to distinguish between closely spaced temperature features that generate information-rich thermal maps opens up many applications in the steel industry.

Microwave device inspired by fiber-optic extrinsic Fabry-Perot interferometer: a novel ultra-sensitive sensing platform.

The fiber-optic extrinsic Fabry-Perot interferometer (EFPI) is one of the simplest sensing configurations and is widely used in various applications. Inspired by the EFPI, we report a novel and universal ultra-sensitive microwave sensing platform based on an open-ended hollow coaxial cable resonator. Two highly-reflective microwave reflectors were fabricated in a coaxial cable to form a microwave Fabry-Perot etalon. Although the operating wavelength of the proposed device is increased by five orders of magnitude compared to the fiber-optic EFPI (e.g., from 1500 nm to 150 mm), the resolution regarding the "pseudo cavity length" of the proposed device is as high as 0.6 nanometer, which is comparable to that of the EFPI. The resolution can be further increased by high-precision machining of the device. Due to its low cost, high sensitivity, all-metal structure, robustness, and ease of signal demodulation, it is envisioned that the proposed device will revolutionize the sensing field and enable many important sensing applications that take place in harsh environments.

Chemical Detection Using a Metal-Organic Framework Single Crystal Coupled to an Optical Fiber.

The quantitative detection and real-time monitoring of target chemicals in the liquid phase are made possible by combining the tailored adsorption properties of metal-organic framework (MOF) material and the precise measuring capabilities of an optical fiber (OF) Fabry-Pérot interferometer (FPI) device. As the single-crystal MOF host adsorbs target analyte guests from the environment, its dielectric properties change causing the reflection spectrum derived from the FPI device to shift. A single crystal of HKUST-1 was attached to the end-face of an OF to form the sensor OF∪MOF (∪, union). The sensor's response curve was accurately measured using low concentrations of the target analyte nitrobenzene, an explosive simulant. Additionally, the uptake rate of nitrobenzene into the MOF single crystal was characterized. The experimental results show that the sensor achieved quantitative and real-time adsorption measurements of a target analyte.

Probing changes in tilt angle with 20 nanoradian resolution using an extrinsic Fabry-Perot interferometer-based optical fiber inclinometer.

In this paper, we introduce and demonstrate a novel optical fiber extrinsic Fabry-Perot interferometer (EFPI) for tilt measurements with 20 nrad resolution. Compared with in-line optical fiber inclinometers, an extrinsic sensing structure is used in the inclinometer reported herein. Our design greatly improves on the tilt angle resolution, the temperature stability, and the mechanical robustness of inclinometers with advanced designs. An EFPI cavity, which is formed between endfaces of a suspended rectangular mass block and a fixed optical fiber, is packaged inside a rectangular container box with an oscillation dampening mechanism. Importantly, the two reflectors of the EFPI sensor remain parallel while the cavity length of the EFPI sensor meters a change in tilt. According to the Fabry-Perot principle, the change in the cavity length can be determined, and the tilt angle of the inclinometer can be calculated. The sensor design and the measurement principle are discussed. An experiment based on measuring the tilt angle of a simply-supported 70-cm beam induced by a small load is presented to verify the resolution of our prototype inclinometer. The experimental results demonstrate significantly higher resolution (ca. 20 nrad) compared to commercial devices. The temperature cross-talk of the inclinometer was also investigated in a separate experiment and found to be 0.0041 µrad /°C. Our inclinometer was also employed for monitoring the daily periodic variations in the tilt angle of a windowsill in a cement building caused by local temperature changes during a five-day period. The multi-day study demonstrated excellent stability and practicability for the novel device. The significant inclinometer improvements in differential tilt angle resolution, temperature compensation, and mechanical robustness also provide unique opportunities for investigating spatial-temporal modulations of gravitational fields.

Capillary-tube package devices for the quantitative performance evaluation of nuclear magnetic resonance spectrometers and pulse sequences.

With the increased sensitivity of modern nuclear magnetic resonance (NMR) spectrometers, the minimum amount needed for chemical-shift referencing of NMR spectra has decreased to a point where a few microliters can be sufficient to observe a reference signal. The reduction in the amount of required reference material is the basis for the NMR Capillary-tube Package (CapPack) platform that utilizes capillary tubes with inner diameters smaller than 150 µm as NMR-tube inserts for external reference standards. It is shown how commercially available electrophoresis capillary tubes with outer diameters of 360 µm are filled with reference liquids or solutions and then permanently sealed by the arc discharge plasma of a commercially available fusion splicer normally employed for joining optical fibers. The permanently sealed capillaries can be used as external references for chemical-shift, signal-to-noise, resolution, and concentration calibration. Combining a number of permanently sealed capillaries to form CapPack devices leads to additional applications such as performance evaluation of NMR spectrometers and NMR pulse sequences. A 10-capillary-tube side-by-side Gradient CapPack device is used in combination with one or two constant gradients, produced by room-temperature shim coils, to monitor the excitation profiles of shaped pulses. One example illustrates the performance of hyperbolic secant (sech) pulses in the EXponentially Converging Eradication Pulse Train (EXCEPT) solvent suppression sequence. The excitation profile of the pulse sequence is obtained in a single gradient NMR experiment. A clustered T 1 CapPack device is introduced consisting of a coaxial NMR-tube insert that holds seven capillary tubes filled with aqueous solutions of different concentrations of the paramagnetic relaxation agent copper(ii) sulfate (CuSO4). The different CuSO4 concentrations lead to spin-lattice relaxation times in the seven capillary tubes that cover a range which extends to more than an order of magnitude. Clustered T 1 CapPack devices are best suited to quantify the effects that relaxation has on magnetizations and coherences during the execution of NMR experiments, which is demonstrated for the order-of-magnitude T 1 insensitivity of signal suppression with EXCEPT.

An Optical Interferometric Triaxial Displacement Sensor for Structural Health Monitoring: Characterization of Sliding and Debonding for a Delamination Process.

This paper presents an extrinsic Fabry-Perot interferometer-based optical fiber sensor (EFPI) for measuring three-dimensional (3D) displacements, including interfacial sliding and debonding during delamination. The idea employs three spatially arranged EFPIs as the sensing elements. In our sensor, the three EFPIs are formed by three endfaces of three optical fibers and their corresponding inclined mirrors. Two coincident roof-like metallic structures are used to support the three fibers and the three mirrors, respectively. Our sensor was calibrated and then used to monitor interfacial sliding and debonding between a long square brick of mortar and its support structure (i.e., a steel base plate) during the drying/curing process. This robust and easy-to-manufacture triaxial EFPI-based 3D displacement sensor has great potential in structural health monitoring, the construction industry, oil well monitoring, and geotechnology.

EXponentially Converging Eradication Pulse Train (EXCEPT) for solvent-signal suppression in investigations with variable T(1) times.

Selective presaturation is a common technique for suppressing excessive solvent signals during proton NMR analysis of dilute samples in protic solvents. When the solvent T1 relaxation time constant varies within a series of samples, parameters for the presaturation sequence must often be re-adjusted for each sample. The EXCEPT (EXponentially Converging Eradication Pulse Train) presaturation pulse sequence was developed to eliminate time consuming pulse-parameter re-optimization as long as the variation in the solvent's T1 remains within an order of magnitude. EXCEPT consists of frequency-selective inversion pulses with progressively decreasing interpulse delays. The interpulse delays were optimized to encompass T1 relaxation times ranging from 1 to 10s, but they can be easily adjusted by a single factor for other ranges that fall within an order of magnitude with respect to T1. Sequences with different numbers of inversion pulses were tested to maximize suppression while minimizing the number of pulses and thus the total time needed for suppression. The EXCEPT-16 experiment, where 16 denotes the number of inversion pulses, was found satisfactory for many standard applications. Experimental results demonstrate that EXCEPT provides effective T1-insensitive solvent suppression as predicted by the theory. The robustness of EXCEPT with respect to changes in solvent T1 allows NMR investigations to be carried out for a series of samples without the need for pulse-parameter re-optimization for each sample.

Dual lithium insertion and conversion mechanisms in a titanium-based mixed-anion nanocomposite.

The electrochemical reaction of lithium with a vacancy-containing titanium hydroxyfluoride was studied. On the basis of pair distribution function analysis, NMR, and X-ray photoelectron spectroscopy, we propose that the material undergoes partitioning upon initial discharge to form a nanostructured composite containing crystalline Li(x)TiO(2), surrounded by a Ti(0) and LiF layer. The Ti(0) is reoxidized upon reversible charging to an amorphous TiF(3) phase via a conversion reaction. The crystalline Li(x)TiO(2) is involved in an insertion reaction. The resulting composite electrode, Ti(0)-LiF/Li(x)TiO(2) ⇔ TiF(3)/ Li(y)TiO(2), allows reaction of more than one Li per Ti, providing a route to higher capacities while improving the energy efficiency compared to pure conversion chemistries.