This PDF file contains the front matter associated with SPIE Proceedings Volume 12532, including the Title Page, Copyright information, Table of Contents, and Conference Committee information.

In this presentation, the concept, theory, and application of ‘lab-on-sensors’ are briefly introduced. The ‘lab-on-sensors’ concept is detailed in its application to corrosion sensors. Then, the recent development of metal-coated corrosion sensors based on long period fiber gratings (LPFG) is reviewed in three forms of metal coatings: (1) nano iron particles mixed with epoxy, (2) Fe-C mixture applied over a silver layer, and (3) Fe-C mixture applied over a graphene layer. Such a corrosion sensor is used to monitor the change in wavelength as the metal coating is corroded gradually. The wavelength change is calibrated with the degree of corrosion in metal coating. When the corrosion sensor is deployed next to a steel member, the measurement of wavelength change from the corrosion sensor enables the prediction of steel member corrosion from the calibration curve and the wavelength measurement.

The maintenance and inspection of power transformers can be a time-consuming task for electric utilities, but it is a necessity for maintaining electrical grid reliability. A standard strategy for diagnosis of fault conditions in an oil-filled transformer is to periodically acquire oil samples and perform dissolved gas analysis (DGA). Aging and temperature variation can induce varying concentrations of hydrogen, methane, and other hydrocarbons, which all form as the oil degrades. Acetylene (C₂H₂) is generated only during localized, high-temperature events such as partial discharge, and its presence is a key marker for identifying these conditions.. The development of optical fiber-based sensors to fill the role of DGA offers several advantages, including the option to implement real-time, in-situ, or even spatially resolved (distributed or quasi-distributed) sensing schemes. The evanescent field approach, in conjunction with tailored sensing materials, provides a cheap and scalable solution to this problem. However, this solution is oftentimes hampered by long-term stability and cross-sensitivity issues. One solution is to gather data from multiple optical fiber sensors designed to eliminate cross-sensitivity and calibrate drift. In this work, a multi-sensor array is developed to target multiple gas species relevant to transformer monitoring (C₂H₂, CH₄, H₂). This approach, combined with machine learning models such as support vector machines (SVM), can be used to identify the gas species present at concentrations relevant to DGA (ppm levels) with dramatically increased accuracy.

Hydrogen can be stored in underground wells to mitigate the imbalance between hydrogen supply and demand in the future hydrogen economy. The concentration of stored hydrogen can vary due to microbial reactions and leakage through caprocks in the subsurface storage facilities such as salt caverns, saline aquifers, and depleted hydrocarbon reservoirs. Thus, monitoring hydrogen concentration in subsurface storage is essential to ensure integrity of the storage infrastructure and to detect early signs of gas leakage. Optical fiber-based hydrogen monitoring has advantages of stability in harsh environments, real-time and remote sensing, and improved safety compared to electrical-based sensors in flammable gases. An optical fiber sensor with a palladium nanoparticles-incorporated SiO₂ film (Pd/SiO₂) was previously demonstrated for hydrogen sensing over a wide range of hundreds ppm to 100% in dry conditions. However, the Pd-based hydrogen sensitive materials are susceptible to water vapor interference, which leads to a significant reduction in hydrogen sensitivity under humid conditions. To address this challenge, this study focused on the enhancement of hydrogen sensing response under humid conditions by applying a hydrophobic filter film over the Pd/SiO₂ sensing layer. The optical fiber sensor covered by the filter layer showed significant improvement on the baseline drift issue and reduction in hydrogen sensitivity caused by high humidity (99% RH). In addition, the developed optical fiber sensor demonstrated negligible impact by hydrocarbon contaminants such as CO₂ and CH₄ which are present in the subsurface hydrogen storage reservoirs. The Pd/SiO₂-coated optical fiber sensor coupled with the filter layer has high potential to be deployed in the subsurface hydrogen storage areas to monitor hydrogen concentration without cross-sensitivity of hydrocarbons and humidity.

In this work, we demonstrate a reflection-based nanocomposite-functionalized fiber H₂ sensor for ease of installation and H₂ sensing in energy storage, fuel cells, electrolyzers, and other similar devices. High-temperature H₂ fiber probes decorated with Au-Pt bimetallic alloy nanoparticles (NPs) in rutile titania matrix are characterized with scanning electron microscopy (SEM) and grazing incidence x-ray diffraction (GIXRD), and tested experimentally with varying H₂ concentration and cycling gas conditions. In response to reducing H₂, fully reversible reflectance intensity changes at the alloy NPs’ localized surface plasmon resonance (LSPR) absorption peak are demodulated in real-time. The reflection fiber probe coated with bimetallic Au-Pt NPs in titania show 15x higher sensitivity than corresponding monometallic Au NPs in titania. The demonstration of reflection hydrogen fiber probe provides an installation advantage in various reactor environment applications, and the investigation of the Au-Pt binary alloy system unfolds new sensitivity-enhancing pathways for NP-based LSPR modulation in reducing H₂ environment at high temperatures.

We review recent work at the US Naval Research Laboratory using stimulated Brillouin scattering in optical fiber for applications in distributed sensing, spectroscopy, and optical signal processing. In particular, we describe recent advances in distributed strain and temperature sensing enabled by simultaneously monitoring the complex Stokes and anti-Stokes Brillouin interactions. We then show how this scheme can be modified to enable high-speed, high-resolution spectroscopy. Finally, we describe how the narrow-linewidth of the SBS process can enable line-by-line optical frequency comb control for applications in RF photonics and optical arbitrary waveform generation.

A new single-mode optical fiber with two Brillouin gain peaks is designed and fabricated to increase the differences in the temperature and strain coefficients between the peaks. The gains of the two Brillouin peaks are at a similar level and the temperature coefficient difference is ~0.2 MHz/°C. The fiber is well suited for simultaneous temperature and strain measurement with reduced uncertainties in Brillouin distributed fiber sensing applications.

We present a distributed fiber optic sensor that discriminates between temperature and strain along a 500 m fiber with 5 m spatial resolution and a quasi-static temperature (strain) resolution of 15 mK (130 nɛ). The technique relies on a slope-assisted Brillouin system that combines gain and phase information from both the Stokes and anti-Stokes components and a frequency-scanning Rayleigh system that measures the shift in the Rayleigh backscattered spectrum. Uniquely, this hybrid approach enables dynamic measurements with a bandwidth of 1.7 kHz and temperature (strain) noise spectral density of 0.52 mK/√Hz (4.6 nɛ/√Hz), while suppressing cross sensitivity by 25 dB.

Concerns over global climate change are driving the need for increased emission monitoring of greenhouse gases from various sources. As such, there is a need for new and improved sensing platforms capable of remote interrogation over large geographical areas with varied terrain, large-scale infrastructure, or in areas not accessible to conventional sensing technologies. One sensing platform which is well-suited to these niche applications is a waveguide-based optical fiber sensor. The application of a physical sorbent coating to the optical fiber provides a remote and reversible sensing mechanism where absorption of the analyte gas into the coating induces a change in transmitted power due to a change in the refractive index of the coating. Advances in the development of moisture-resistant refractive index-based fiber optic gas sensors which operate at near-infrared wavelengths will be presented, as well as the results on coating optimization.

Each year, the global cost that is accounted to corrosion was estimated at $2.5 trillion. Corrosion not only imposes an economic burden, when corroded structures are under various loading conditions, it may also lead to structurally brittle failure, posing a potential threat to structural reliability and service safety. Although considerable studies investigated the combined effect of external loads and structural steel corrosion, many of the current findings on synergetic interaction between stress and corrosion are contrary. In this study, the combined effects of dynamic mechanical loads and corrosion on epoxy coated steel are investigated using the distributed fiber optic sensors based on optical frequency domain reflectometry. Experimental studies were performed using the serpentine-arranged distributed fiber optic strain sensors embedded inside the epoxy with three different scenarios including the impact loading-only, corrosion-only, and combined impact loading-corrosion tests. Test results demonstrated that the distributed fiber optic sensors can locate and detect the corrosion processing paths by measuring the induced strain changes. The combined impact loading-corrosion condition showed significantly accelerated corrosion progression caused by mechanical loads, indicating the significant interaction between dynamic mechanical loading and corrosion on epoxy coated steel.

In this paper, we field demonstrate a natural gas pipeline monitoring based on optical frequency domain reflectometry (OFDR). OFDR can monitor distributed temperature and strain measurements along the natural gas pipelines and provide valuable information about pipe structural health, like hoop strain changes caused by pipe wall thinning or temperature changes from gas leaks based on Joule-Thomson effect. Distributed temperature and strain measurements were demonstrated where the pipeline operated at various pressure levels. The static pressure-induced hoop strain in a pilot-scale field test in a natural gas flowing high-pressure loop. The pilot scale testing results demonstrated in this paper indicate that the OFDR system is a promising tool for real-time monitoring of a pipeline without influence on normal operating conditions of the gas pipeline.

Distributed acoustic fiber optic sensors (DAS) enable spatially distributed monitoring of perturbations and contain rich multidimensional information that can be used in structural health monitoring. Machine learning based on physics-based simulations can make a breakthrough in traditional data analysis methods to improve their efficiency and performance, solving a series of problems such as huge data volume, low data processing speed, data signal-to-noise ratio, etc. Here, the relationship of DAS response and corrosion type are studied. First, we present a systematic theoretical study of the potential of direct coupling of quasi-distributed acoustic sensing (q-DAS) with guided ultrasound typically used for real-time pipeline health monitoring. To investigate properties of scattered acoustic waves and the performance of DAS and q-DAS in identifying defects, we use finite element analysis to simulate the response in a variety of pipeline structures including welds, clamps, defect types, and sensor installations representing various corrosion patterns expected in practice. A specific emphasis will be placed upon simulating and modeling pitting corrosion defects and contrasting with other types of corrosion observed in practice. We also aim to compare and analyze signal characteristics due to different kinds of corrosion types and structures, and to enhance machine learning algorithms for detection and size prediction of major pipeline structural changes and corrosion types. Ultimately, results of simulated DAS and q-DAS sensor networks are analyzed by a neural network-based machine learning algorithm for defect identification through supervised learning. To evaluate and improve effectiveness, we estimate model uncertainty and identify features of simulated results that contribute most to the model performance and efficacy.

The fiber-optic distributed acoustic sensing (DAS) technique has increasingly become more attractive for structural health monitoring (SHM) and non-destructive evaluation (NDE) purposes. When it comes to traditional acoustic NDE methods, the presence of weldings can present a significant challenge as it can heavily scatter waves resulting in complex data analysis and interpretation. The present work aims to develop an improved understanding and interpretation framework in cases where welds play an important role in the signal with an emphasis on the steel shell of a canister, typically used for Dry Cask Storage Systems (DCSSs) that house spent nuclear waste fuel rods. We also introduce a promising approach in the use of guided ultrasonic waves along with fiber optic sensors that seeks to overcome the challenges that emerge when using traditional acoustic sensing based NDE techniques in welded structures. The study is conducted in a simulation theoretical manner, using a canister model constructed from a representative stainless-steel plate, with different configurations of weldings typically present for DCSS structure. Progressively increasing complexity of the weld physical representation is considered to fully incorporate in physics-based analysis. Furthermore, the acoustic response of these models is obtained from the simulations as a response of an assumed DAS or quasi-distributed acoustic sensing Q-DAS system network. The features originated from the welds are extracted and analyzed, and additional features associated with structure integrity associated with corrosion defects, etc. will also be explored for NDE inspection as in a traditional acoustic NDE approach.

This paper summarizes our recent progress on using 3D printing and laser micromachining methods to fabricate optical microsensors for various applications. Optical grade glasses are printed by 3D extrusion and laser sintering. High-precision and high surface quality optical structures of arbitrary shapes are obtained by ultrafast laser micromachining and CO2 laser resurfacing. Combining these advanced manufacturing methods, various optical structures and components can be made with flexible shape and desired accuracy. With unique advantages such as compact size, high thermal stability, and integrated optical functions, these 3D printed structures can be used as sensors for many applications.

Anello photonic is a silicon valley based startup developing next generation navigation technologies. The heart of the Anello’s products is the silicon photonics optical gyro, the SiPhOG™ which is a 10X reduction in SWAP-C compared to current products.

This paper presents a technique for measuring gas flow velocity using femtosecond laser-induced active fiber Bragg grating (FBG) sensors. When the in-fiber high-power laser is turned off, a small volume of gas in the flow stream is heated 0.05 °C to 1 °C above the ambient temperature using an electrical pulse heater. The temperature change of the gas is measured by the FBG sensors, allowing for the calculation of flow velocity based on time-of-flight measurements. Conversely, when the high-power laser is activated, the FBG sensors can be significantly heated by 23.5 °C to 281.9 °C above the ambient temperature through an energy conversion coating that converts leaked light into heat. The flow rate can be calculated according to how much the sensors’ temperature drops. The experimental results show that Type-II FBG sensors can be used as highly multiplexable active optical sensors for both temperature and flow sensing with better response times than thermocouple devices.

Absence of a final repository for nuclear waste has increased attention on dry cask storage systems (DCSSs) which were originally intended for temporary storage, increasing the need for new structural health monitoring paradigms considering safety and environmental impacts. Current integrity inspection requirements consist of periodic manned inspections due in part to the difficulties with real-time monitoring of internal canister conditions without penetrating the canister surface. Here we overview a new approach to nuclear canister integrity structural health monitoring which combines both quasi-distributed fiber optic acoustic (and other) sensing modalities deployed external to the canister as well as physics-based modeling to enable real-time inference of internal canister conditions, including the identification, localization, and classification of various active or incipient failure conditions. More specifically, we overview the vision for the proposed monitoring approach and describe results to date in theoretical physics-based modeling and artificial intelligence-based analytics to accelerate the development of classification frameworks for rapid interpretation of quasi-distributed acoustic and other complementary fiber optic sensing responses. In addition, we describe early results obtained for a quasi-distributed fiber optic sensor network based upon multimode interferometer sensors using an experimental test bed established for dry-cask storage canister sensing experiments. Future work will be overviewed and discussed in the context of expanded scope of the proposed real-time monitoring system and planned field validations.

Pipeline infrastructure monitoring based on distributed fiber-optic acoustic sensing is gaining significant attention aimed at real-time rapid detection of leakages, third-party intrusion, geo-hazards, corrosion, and other structural damages. Typical fibers installations are external to a pipeline, however retrofitting of existing pipelines through internal installation is desirable despite deployment challenges. Highly sensitive distributed acoustic sensing integrated within new pipelines or retrofit in existing pipelines can enable early detection of damage and degradation. In this work, we demonstrate pipeline integrity monitoring using distributed acoustic sensing and the Rayleigh backscattering-enhanced optical fibers deployed internal to the pipeline for high sensitivity detection of acoustic events. More specifically, traditional and backscattering-enhanced optical fibers are interrogated using bench-top phase-sensitive optical time-domain reflectometry (Φ-OTDR). The distributed acoustic sensing characteristics of two types of backscattered-enhanced fibers, Type A and Type B, are experimentally investigated. Our measurement analysis shows that the SNR of the acoustic event detection enhances ~2-fold and ~3-fold using the Type A and Type B fiber, respectively than that of the traditional SMF for pipeline monitoring. The presented investigation is a first validation for in-pipe deployed distributed acoustic sensing with high SNR and provides useful insight for diverse pipeline monitoring applications in the oil and gas distribution industry.

Optical fiber based electro-magnetic field sensors is a diverse and expanding field in fiber sensor technology with applications spanning from geomagnetism, biomagnetism, nuclear magnetism to safety and operational monitoring of power grid systems. Particularly, because of the dielectric silica material of the fiber that provides high electric insulation and immunity to the electromagnetic interference (EMI), a major reason contributing to the limitations in conventional sensors, the efforts have been focused on developing the fiber-optic sensors with increased sensitivity, bandwidth, and detection range specific to an application but all benefit from the advantages of the platform. Various fiber structures, interrogation schemes and sensing materials have been investigated. One major interest is on the fiber-optic sensor based on multi-mode interference (MMI) where a multimode mode fiber is fusion spliced between two single mode fibers also known as SMS (single-mode/multimode/single mode) fiber sensor. Ease of fabrication, compactness, higher sensitivity, and low cost are some of the driving factors in addition to the potential for direct integration of the platform with functional sensor materials to tailor for specific applications. For the purpose of magnetic field sensing, the magnetic fluid is the most widely used functional material as the sensing/cladding layer on the fiber-structure. Here we present efforts to enhance and optimize the sensitivity of such SMS structure with magnetic fluid as the sensing material exploiting the unique “self-imaging” property of the SMS sensor where the sensor produces a filterlike spectral response and is highly sensitive to the change in magneto-optical property of surrounding medium. The performance metrics of the sensor are analyzed against DC magnetic field range keeping an eye in detecting typical current induced magnetic field in power grid systems.

This paper discusses the design of a unique conformal SAL sensor which has been invented, prototyped, and has gone through preliminary field testing. The sensor was designed to meet or exceed all of the Key Performance Parameters (KPPs) of SAL sensors currently in use, with a smaller envelope, fewer components, and a lower cost. The design is generic, in that it can be scaled as required, to meet specific customer requirements like field-of-view, field-of-regard and sensitivity. Because the sensor optical design is conformal, it has a negligible impact on the outer mold lines and no impact on typical fuse architectures.

Detecting leaks early and reliably is essential for preventing environmental contamination. However, very small leaks often go undetected using conventional gauges and sensors due to their low sensitivity and limitation to measuring only at discrete gauge locations. Leak detection using optical fiber-based sensors is becoming increasingly popular as they are immune to electromagnetic interference, do not require any electronics at the measurement location, are resistant to corrosion, and enable sensing capability at multiple locations simultaneously and in real-time, with high sensitivity. In this study, the authors experimentally investigate the sensitivity to detect and quantify leaks using two commonly used fiber-optic sensors: distributed acoustic sensors (DAS) and fiber Bragg grating (FBG)-based sensors. Controlled leaks at different flow rates were created in an experimental flow loop with DAS and FBG attached to the outer pipe walls. The strain rate data obtained from DAS was processed using time- and frequency-domain signal processing techniques to detect the location of the leak and quantify the volumetric leak rate as low as 0.07 gallons per minute (gpm). FBGs were used to localize the leak in a quasi-distributed fashion. Since FBGs are responsive to both strain and temperature, the two effects were decoupled using independent temperature measurements to separately study the strain and temperature response due to the leak. The sensitivity to detect leaks was evaluated by comparing the leak signature for both sensors. The effect of environmental noise and background signals on the ability to detect leaks was investigated for different pipe flow rates and leak volumes.

This study presents a novel in situ high-temperature fiber optic Raman probe that enables the study of the physical properties and structure of molten samples at temperatures up to 1400 °C. To demonstrate the functionality of the high-temperature fiber optic Raman probe, different composition mold fluxes were evaluated in this report. The Raman spectra at flux molten temperature were successfully collected and analyzed. A deconvolution algorithm was employed to identify peaks in the spectra associated with the molecular structure of the components in each sample. The experimental results demonstrate that the composition-dependent Raman signal shift can be detected at high temperatures, indicating that molten materials analysis using a high-temperature Raman system shows significant promise. This flexible and reliable high-temperature Raman measurement method has great potential for various applications, such as materials development, composition and structure monitoring during high-temperature processing, chemical identification, and process monitoring in industrial production.

In the oil and gas, CO₂ sequestration, H₂ subsurface storage, and geothermal energy sectors, subsurface pH measurements are critical for monitoring the geochemical conditions and structural integrity of wellbore systems. Real-time pH measurements in these conditions are vital for detecting and predicting corrosion deterioration of wellbore components that may jeopardize the safety and continued operation of wellbore systems. The viability of TiO₂-coated optical fibers has previously been demonstrated as an effective sensor design for continuous distributed pH monitoring at elevated temperatures and ambient pressures. However, real wellbore conditions contain high pressures and the effects of high pressures on sensor results and the sensing layer have not been well studied. As TiO₂ has been established in the literature as being stable at temperatures and pressures substantially higher than those expected in typical wellbore conditions, it makes for a promising sensing material for applications requiring high-pressure, high-temperature (HPHT) conditions. In this study, a sol-gel deposition method is used to coat the optical fiber sensors with TiO₂ sensing layer. The sensor performance was measured using optical transmission measurements at various pH and using optical backscatter reflectometry for distributed pH sensing demonstration in wellbore-relevant pressures (up to 1000 psi) and temperatures (~80 °C). The TiO₂ sensing layer was characterized using scanning electron microscopy (SEM) and full spectrum UV-Vis-NIR transmission data for a planar substrate. The TiO₂-coated optical fiber sensor is tested for any pressure-derived effects and the viability of this sensor design for real-time in-situ wellbore pH monitoring is discussed.

Hydration reactions of cement-based materials are of great significance to their properties and durability. Various technologies have been investigated to study the hydration processes regarding reaction heat, chemical changes, or microstructures. As a non-destructive chemical analysis technique, Raman spectroscopy provides detailed information about chemical structures, which takes advantage of tracking and monitoring the chemical change during the hydration reaction. In this study, a novel in situ fiber optic Raman probe was utilized to continuously monitor the long-term hydration process of cement clinker stages, from early to late hydration stages and from fresh to hardened state of paste samples. With the remarkable capability of this technique for dry or moist, crystalline or amorphous samples, the hydration process of tricalcium silicate (C₃S) pastes with different water-to-solid (w/s) ratios can be monitored from the beginning of the hydration reaction. The main hydration products, especially C-S-H and silicate (CH), have been successfully identified, and there in situ quantitative changes have been continuously monitored. The effect of the w/s ratio on the hydration process of C3S slurries is also discussed. Moreover, the X-Ray Powder Refraction (XRD) results strongly correlate with the Raman spectra of the hydration products, demonstrating the technique's reliability. By comparing with the existing in situ fiber optic Raman spectroscopy technique, the proposed sensor performs a significantly better signal-to-noise ratio (SNR), providing essential aid for future use in the construction field for monitoring and assessing the health and performance of concrete structures.

In this paper, we field demonstrate a water pipeline flow detection based on a simple, low-cost, and highly sensitive fiber optic acoustic sensor. The fiber acoustic sensor consists of a multimode interference effect in a single-mode-multimode-single-mode (SMS) fiber structure. In the field test, we mounted an SMS fiber sensor on a 6” diameter water pipeline, where water flow is precisely controlled by a variable frequency driver (ABB-ACQ580 sensor-less drive). The experimental results indicate that the proposed SMS fiber acoustic sensor can be effectively applied for practical applications of pipeline flow monitoring and identify leak detection with high sensitivity and accuracy.

Evanescent wave sensors in photonic integrated circuits have been demonstrated for gas sensing applications. While some methods rely on the distinctive response of certain polymers for sensing specific gases, absorption spectroscopy identifies any gas uniquely from their unique vibration signatures. Based on the Beer-Lambert principle, the sensitivity of absorption by a gas on chip relies on the length of the sensing region, the optical overlap integral with the analyte gas and the absorption cross-section at the wavelength with the fundamental vibration signature. The overlap of the optical mode with the analyte has been enhanced in photonic devices by combining slot waveguide confinements with photonic crystal slow light effects. While the absorption cross-section is a property of the gas, the length of the sensing region is limited by the available area on a chip and waveguide propagation losses that limit the minimum signal to noise ratio. In this paper, we show that by incorporating reflecting loop mirrors, the absorption path length can be doubled for the same geometric length of the absorption sensing waveguide. Light from a waveguide is split into two paths, each with a slow light photonic crystal waveguide, by a 2×2 multimode interference (MMI) power splitter. Each path is terminated by a loop mirror that causes the light to retrace its path back down the sensing arms thereby doubling the optical path length over which light interacts with the analyte. Results on the enhancement of phase sensitivity and absorbance sensitivity in the interferometric configuration are presented.

THz phase-shifted waveguide Bragg gratings built on modular 3D-printed two-wire plasmonic waveguides are used experimentally for gas sensing. The physical parameters of a gas flowing along the grating are then monitored in real time by detecting the spectral position of a narrow transmission peak. The sensor sensitivity was found to be 133 GHz/RIU near 0.14 THz, with a theoretical sensor resolution of 7.5.10-5 RIU. The detection of glycerol vapors in air generated by an electronic cigarette was shown experimentally. The developed THz gas sensor can find its practical applications in environmental pollution monitoring and leak detection.

This paper reports a novel Extrinsic Fabry-Pérot Interferometer (EFPI) sensor platform based on ~50 μm-diameter porous silica microspheres attached to the ends of single-mode optical fibers. The glass spheres, with 45% internal void volumes, act as geometrically well-defined Fabry-Pérot (FP) cavities that produce interferograms that only depend on the index of refraction of guest molecule types and loadings. The primary advantage of the sensor is that the silica micropores inside the glass spheres present inherent surface hydroxyl groups, which can be chemically modified using a wide selection of silanization reactions. Silanized silica microspheres provide a novel and broad sensor platform where myriad silane coupling agents act as bridges connecting organic and inorganic materials. Commercially available silanization reagents are diverse and afford silica pores with selectivity for sensing chemicals and biochemicals. When guest molecules are adsorbed in the pores of the microspheres, a proportional change in the light path length can be calculated and measured. A gas sample generator consisting of vapor generators, analyte permeation tubes, and flow controllers were configured to characterize the sensor response to various volatile organic compounds. An optical interrogator with a 1 Hz scan frequency and 80 nm wavelength range was employed for full spectral scanning and data acquisition. Experimental results demonstrate shifts of the interferogram when an EFPI glass microsphere is exposed to different vapors and vapor concentrations. Future work will compare EFPI results of guest molecule adsorptions by unaltered versus silanized porous glass microspheres.

Fiber Bragg gratings (FBGs) are well-known optical sensors, which have been widely used to perform temperature and strain measurements. Due to the cross-sensitivities of FBGs to both temperature and axial strain changes, using these fiber sensors for high-accuracy temperature measurements remained questionable. This paper presents an FBG sensor packaging technique that produces strain-free, multiplexable fiber temperature sensors. Using a precision CO₂ laser heating process, a low-loss and mechanically robust fiber taper is formed near the FBG sensor, which relieves potential axial strain influence on FBG’s temperature measurements. FBG sensors with tapered junctions were housed in a two-hole PEEK tube. The entire structure is then inserted into a thicker hollow PEEK tubing and welded in place. This design protects the fiber sensor from mechanical breakage and isolates it from external stress. This paper reports highly accurate temperature measurements from 77k to 567k. It presents a viable approach to developing multiplexable temperature sensors for cryogenic environment applications.

Food quality and safety have been critical issues in the world. There is an urgent need for a fast, simple, selective, and inexpensive food detection method for the identification of the degree of food spoilage. As a molecular analysis tool, Raman spectroscopy has the advantages of high selectivity, accurate analysis, simple operation, and low sample consumption. This paper reports a novel remote fiber optic Raman sensor for real-time application in food spoilage detection. Eight volatile organic compounds (VOC) liquids that typically generated by corrupted food were under-tested. The proposed sensor successfully captures the back-scattered Raman spectra for all testing samples with various dilution levels. Multiple machine learning algorithms are also applied to further analyze the correlation between Raman spectra and molecules in spoiled foods by diluting chemical samples. As a result of combining with Raman spectroscopy and machine learning algorithm, the remote fiber optic Raman probe allows qualitative measurements of VOC samples at 100-fold dilution. In comparison with surface-enhanced Raman scattering (SERS), the remote fiber optic Raman sensor allows for direct Raman spectroscopy detection without sample and SERS substrate preparation, which opens a new chapter on the nondestructive and sensitive detection of food analytes.

To achieve high-efficiency turbine engine operation, turbine combustors must operate with a finely controlled fuel-air ratio near the flame extinction limit, informed by feedback from reliable in-situ temperature measurements. Distributed temperature sensing up to 900-1000 °C using Raman optical-time-domain-reflectometry (ROTDR) with single-crystal optical fiber is demonstrated in a combustion test rig. The distributed temperature sensing (DTS) system utilizes sapphire and yttrium-aluminum-garnet (YAG) fibers which were optimized to improve the signal-to-noise ratio (SNR) of collected Raman signals. Estimation of the SNR of recorded signals and predicted errors were analyzed to simulate the effect of a variety of system parameters and experimental conditions. Enhancement of the SNR through selective doping of the single-crystal fiber was investigated. The expected Stokes and Anti-Stokes collection efficiencies using high-sensitivity avalanche photodiodes were calculated for the optimized optical path. Denoising algorithms of the SNR were developed by exploring noise sources which constrain detection capability via uncorrelated and multiplicative noise. Calibration techniques have been implemented to correct the dynamic variation of the optical loss with temperature in the single-crystal fibers to obtain the calibration parameters and temperature profile.

This study presents an assembly-free ball lens structure at the tip of tapered multimode optical fiber to enhance the light collection efficiency for pH measurements. A 35 µm diameter ball lens was fabricated at the sensor tip. In addition, a thin layer of fluorescence dye was mixed with sol-gel that formed at the fiber tip for pH sensing. The simulation result demonstrates the light propagation on the ball lens tip. The experiment results reveal that the proposed sensor has a rapid response time (< 3 seconds), high sensitivity, and pinpoint accuracy (±1.0%) in the pH range of 6.0-8.0.

Silicon-glass microcavities have been widely used as a functional packaging method for many applications since its founding. During the process, sodium ion (Na⁺) gains mobility due to the high temperature and moves towards the cathode, where it receives an electron and further moves outside the glass, forming metal liquid at the glass/cathode interface, since the melting point of Na is 97.79 ºC. Naturally, a part of Na will stay at the cathode after the wafer is removed, and, without a proper cleaning, it accumulates. This allows liquid Na droplets to be blown inside the silicon/glass interface with a gas flow at the later bonding process, which can strongly influence the sensitive silicon elements. Standard methods such as Raman or mass spectroscopy are not appropriate for this application, because the contamination is either not detectable or the cavity will be destroyed. In this study, we experimentally analyzed the closed system using laser induced breakdown spectroscopy (LIBS). With a high-intensity laser, a gas breakdown was generated inside the cavity and measured via optical emission spectrum. The study was performed in two steps: first, the minimal dimension of the cavity was determined in order to not damage the walls; second, the system was fabricated according to the results from last step, and the measurement concept was proved.