Multi-parameter distributed fiber optic sensing using double-Brillouin peak fiber in Brillouin optical time domain analysis.

In this paper, we demonstrate a multi-parameter fiber sensing system based on stimulated Brillouin scattering in a double-Brillouin peak specialty fiber with enhanced Brillouin gain response. The amplitude level of the second Brillouin gain peak, which originated from the higher-order acoustic modes, has been improved with an approximately similar amplitude level to the first Brillouin gain peak from the fundamental acoustic mode. Compared to other multi-Brillouin peak fibers presented in the literature, the proposed fiber significantly reduces the measured Brillouin frequency shift error, thus improving strain and temperature accuracies. By utilizing the sensitivity values of the strain and temperature associated with each Brillouin gain spectrum (BGS) peak, a successful discriminative measurement of strain and temperature is performed with an accuracy of ±13 µÉ›, and ±0.5 °C, respectively. The proposed double-Brillouin peak fiber appears to be a possible alternative to other multi-BGS peak fibers, for instance, large effective area fiber and dispersion compensating fibers, which are inherently accompanied by large measurement errors due to the weak Brillouin gain values originating from the higher-order acoustic modes. The demonstrated results show different strain and temperature coefficients of 47 kHz/µÉ›, 1.15 MHz/°C for peak 1 and 51 kHz/µÉ›, 1.37 MHz/°C for peak 2. Moreover, the enhanced BGS peak gains having nearly the same amplitude levels enable the discriminative measurement of strain and temperature. Such fibers in Brillouin interrogation eliminate the need for complex monitoring setups and reduce measurement errors. We recommend that for long-distance natural gas pipeline monitoring, where discriminative strain and temperature measurement is crucial, the proposed double-Brillouin peak fiber can be highly beneficial.

A machine learning based computational approach for prediction of cation distribution in spinel crystal.

In this study, a machine learning based computational approach has been developed to investigate the cation distribution in spinel crystals. The computational approach integrates the construction of datasets consisting of the energies calculated from density functional theory, the training of machine learning models to derive the relationship between system energy and structural features, and atomistic Monte Carlo simulations to sample the thermodynamic equilibrium structures of spinel crystals. It is found that the support vector machine model yields excellent performance in energy predictions based on spinel crystal structures. Furthermore, the developed computational approach has been applied to predict the cation distribution in single spinel MgAl2O4 and MgFe2O4 and double spinel MgAl2-aFeaO4. Agreeing with the available experimental data, the computational approach correctly predicts that the equilibrium degree of inversion of MgAl2O4 increases with temperature, whereas the degree of inversion of MgFe2O4 decreases with temperature. Additionally, it is predicted that the equilibrium occupancy of Mg cations at the tetrahedral and octahedral sites in MgAl2-aFeaO4 could be tuned as a function of chemical composition. Therefore, this study presents a reliable computational approach that can be extended to study the variation of cation distribution with processing temperature and chemical composition in a wide range of complex multi-cation spinel oxides with numerous applications.

Investigation of Goubau Wave Propagation on Large Pipes for Sensing Applications.

We examine the application of guided waves on a single conductor (Goubau waves) for sensing. In particular, the use of such waves to remotely interrogate surface acoustic wave (SAW) sensors mounted on large-radius conductors (pipes) is considered. Experimental results using a small-radius (0.0032 m) conductor at 435 MHz are reported. The applicability of published theory to conductors of large radius is examined. Finite element simulations are then used to study the propagation and launching of Goubau waves on steel conductors up to 0.254 m in radius. Simulations show that waves can be launched and received, although energy loss into radiating waves is a problem with current launcher designs.

Reflective Fiber Temperature Probe Based on Localized Surface Plasmon Resonance towards Low-Cost and Wireless Interrogation.

Reflection fiber temperature sensors functionalized with plasmonic nanocomposite material using intensity-based modulation are demonstrated for the first time. Characteristic temperature optical response of the reflective fiber sensor is experimentally tested using Au-incorporated nanocomposite thin films deposited on the fiber tip, and theoretically validated using a thin-film-optic-based optical waveguide model. By optimizing the Au concentration in a dielectric matrix, Au nanoparticles (NP) exhibit a localized surface plasmon resonance (LSPR) absorption band in a visible wavelength that shows a temperature sensitivity ~0.025%/°C as a result of electron-electron and electron-phonon scattering of Au NP and the surrounding matrix. Detailed optical material properties of the on-fiber sensor film are characterized using scanning electron microscopy (SEM) and focused-ion beam (FIB)-assisted transmission electron microscopy (TEM). Airy's expression of transmission and reflection using complex optical constants of layered media is used to model the reflective optical waveguide. A low-cost wireless interrogator based on a photodiode transimpedance-amplifier (TIA) circuit with a low-pass filter is designed to integrate with the sensor. The converted analog voltage is wirelessly transmitted via 2.4 GHz Serial Peripheral Interface (SPI) protocols. Feasibility is demonstrated for portable, remotely interrogated next-generation fiber optic temperature sensors with future capability for monitoring additional parameters of interest.

Quasi-Distributed Fiber Sensor-Based Approach for Pipeline Health Monitoring: Generating and Analyzing Physics-Based Simulation Datasets for Classification.

This study presents a framework for detecting mechanical damage in pipelines, focusing on generating simulated data and sampling to emulate distributed acoustic sensing (DAS) system responses. The workflow transforms simulated ultrasonic guided wave (UGW) responses into DAS or quasi-DAS system responses to create a physically robust dataset for pipeline event classification, including welds, clips, and corrosion defects. This investigation examines the effects of sensing systems and noise on classification performance, emphasizing the importance of selecting the appropriate sensing system for a specific application. The framework shows the robustness of different sensor number deployments to experimentally relevant noise levels, demonstrating its applicability in real-world scenarios where noise is present. Overall, this study contributes to the development of a more reliable and effective method for detecting mechanical damage to pipelines by emphasizing the generation and utilization of simulated DAS system responses for pipeline classification efforts. The results on the effects of sensing systems and noise on classification performance further enhance the robustness and reliability of the framework.

Fiber Coupled Near-Field Thermoplasmonic Emission from Gold Nanorods at 1100 K.

Nanostructured gold has attracted significant interest from materials science, chemistry, optics and photonics, and biology due to their extraordinary potential for manipulating visible and near-infrared light through the excitation of plasmon resonances. However, gold nanostructures are rarely measured experimentally in their plasmonic properties and hardly used for high-temperature applications because of the inherent instability in mass and shape due to the high surface energy at elevated temperatures. In this work, the first direct observation of thermally excited surface plasmons in gold nanorods at 1100 K is demonstrated. By coupling with an optical fiber in the near-field, the thermally excited surface plasmons from gold nanorods can be converted into the propagating modes in the optical fiber and experimentally characterized in a remote manner. This fiber-coupled technique can effectively characterize the near-field thermoplasmonic emission from gold nanorods. A direct simulation scheme is also developed to quantitively understand the thermal emission from the array of gold nanorods. The experimental work in conjunction with the direct simulation results paves the way of using gold nanostructures as high-temperature plasmonic nanomaterials, which has important implications in thermal energy conversion, thermal emission control, and chemical sensing.

Fiber Optic Sensing Technologies for Battery Management Systems and Energy Storage Applications.

Applications of fiber optic sensors to battery monitoring have been increasing due to the growing need of enhanced battery management systems with accurate state estimations. The goal of this review is to discuss the advancements enabling the practical implementation of battery internal parameter measurements including local temperature, strain, pressure, and refractive index for general operation, as well as the external measurements such as temperature gradients and vent gas sensing for thermal runaway imminent detection. A reasonable matching is discussed between fiber optic sensors of different range capabilities with battery systems of three levels of scales, namely electric vehicle and heavy-duty electric truck battery packs, and grid-scale battery systems. The advantages of fiber optic sensors over electrical sensors are discussed, while electrochemical stability issues of fiber-implanted batteries are critically assessed. This review also includes the estimated sensing system costs for typical fiber optic sensors and identifies the high interrogation cost as one of the limitations in their practical deployment into batteries. Finally, future perspectives are considered in the implementation of fiber optics into high-value battery applications such as grid-scale energy storage fault detection and prediction systems.

Multiplexable high-temperature stable and low-loss intrinsic Fabry-Perot in-fiber sensors through nanograting engineering.

This paper presents a method of using femtosecond laser inscribed nanograting as low-loss- and high-temperature-stable in-fiber reflectors. By introducing a pair of nanograting inside the core of a single-mode optical fiber, an intrinsic Fabry-Perot interferometer can be created for high-temperature sensing applications. The morphology of the nanograting inscribed in fiber cores was engineered by tuning the fabrication conditions to achieve a high fringe visibility of 0.49 and low insertion loss of 0.002 dB per sensor. Using a white light interferometry demodulation algorithm, we demonstrate the temperature sensitivity, cross-talk, and spatial multiplexability of sensor arrays. Both the sensor performance and stability were studied from room temperature to 1000°C with cyclic heating and cooling. Our results demonstrate a femtosecond direct laser writing technique capable of producing highly multiplexable in-fiber intrinsic Fabry-Perot interferometer sensor devices with high fringe contrast, high sensitivity, and low-loss for application in harsh environmental conditions.

Nanostructured sapphire optical fiber embedded with Au nanorods for high-temperature plasmonics in harsh environments.

Sensors for harsh environments must exhibit robust sensing response and considerable thermal and chemical stability. We report the exploration of a novel all-alumina nanostructured sapphire optical fiber (NSOF) embedded with Au nanorods (Au NRs) for plasmonics-based sensing at high temperatures. Temperature dependence of the localized surface plasmon resonance (LSPR) of Au NRs was studied in conjunction with numerical calculations using the Drude model. It was found that LSPR of Au NRs changes markedly with temperature, red shifting and increasing in transmission amplitude as the temperature increases. Furthermore, this variation is highly localized through tunneling by overlapping the near-field of thin cladding and sapphire optical fiber. The NSOF embedded with Au NRs has the potential for sensing in advanced energy generation systems.

Plasmonic Au nanorods stabilized within anodic aluminum oxide pore channels against high-temperature treatment.

Au nanorods (Au NRs) are promising candidates for sensing applications due to their tunable localized surface plasmon resonance wavelength. At temperatures above 250 °C, however, these structures are morphologically unstable and tend to evaporate. We herein report a novel refractory plasmonic nanocomposite system comprising Au NRs entrapped in anodized aluminum oxide (AAO) scaffolds that are stable up to 800 °C. Au NRs were synthesized in the cylindrical pores of sapphire-supported AAO via in situ electroless deposition on catalytic Au nanoparticles (Au NPs) anchored on the pore walls. The morphological characteristics and surface-enhanced Raman scattering (SERS) functionality of Au NRs before and after heat treatment were evaluated using SEM, XRD and Raman spectroscopy. Compared to unconfined Au NRs that evolved into spherical particles at temperatures below 250 °C and subsequently evaporated from the substrate surface, the morphology of Au NRs in AAO was preserved upon heat treatment at temperatures up to 800 °C. Furthermore, by tuning the AAO scaffolds thickness and pore diameter, the aspect ratio (AR) of the entrapped Au NRs was varied from 2.4 to 7.8. The SERS sensitivity of Au NRs in AAO was found to increase with decreasing AR when the incident light was parallel to the rod longitudinal axis, in close agreement with the calculated fourth power of the local electromagnetic field using the finite-difference time domain method.

Theoretical study of the optical and thermodynamic properties of LaxSr1-xCo1-yFeyO3-δ (x/y = 0.25, 0.5, 0.75) perovskites.

The performance of LaxSr1-xCo1-yFeyO3-δ perovskite systems in applications such as solid oxide fuel cells and catalysis is related to the proportion of substitution atoms. Using a density functional theory method, we investigate the doping effect on the electronic, optical, and thermodynamic properties of LaxSr1-xCo1-yFeyO3-δ (x/y = 0.25, 0.5, 0.75). Our results show that La doping introduces an empty state and pushes the Fermi level upwards. The doping Fe derived states locate away from the Fermi level as compared with Co states. From the results of optical absorption, the peak at 200-300 nm is enhanced and experiences a blue-shift with increasing La concentration. The corresponding peak at 400-700 nm also shows a blue-shift induced by both La and Fe doping, and it could be enhanced by Fe doping while being suppressed by La doping. And the peak above 1500 nm is enhanced by the cooperation of La and Fe doping. From thermodynamic calculations via an Ellingham diagram, it is found that the parent SrCoO3 is the most favorable composition for releasing O2, with both La and Fe doping hampering the reduction reaction. Therefore, the optical and thermodynamic properties of LaxSr1-xCo1-yFeyO3-δ could be adjusted by special doping values.

The influence of oxygen vacancy on the electronic and optical properties of ABO3-δ (A = La, Sr, B = Fe, Co) perovskites.

ABO3-δ (A = La, Sr, B = Fe, Co) perovskites are useful in a wide range of applications, including their recent exploration for application in high-temperature optical oxygen sensing for energy conversion devices such as solid oxide fuel cells. To elucidate the dependence of functional properties and oxygen vacancy formation on defect chemistry and composition, first principles calculations are presented. The obtained results show that oxygen vacancy (VO) formation energies are in the order of LaFeO3 > LaCoO3 > SrFeO3 > SrCoO3. Furthermore, the influence of VO on the electronic and optical properties is investigated for the high temperature stable phases (T = 1100 K). For the LaFeO3 insulator, the VO donated electrons are all localized on the down-spin d3z2-r2 orbitals of the nearest Fe ions. These defect states located in the band gap induce a drop in the energy onset of absorption as pristine bulk → V2+O → V1+O → V0O, and especially, an extra absorption peak appears between 0.5 and 1.5 eV due to V0O and V1+O formation. In the rest of the crystals that expressed a metallic feature, the VO donated electrons partially localize on the down-spin d3z2-r2 orbital and partially delocalize through the lattice, by which the absorption peaks (0.5-2.0 eV for LaCoO3, 0.0-0.5 eV for SrFeO3 and SrCoO3) from the electronic excitation near the Fermi level are enhanced. A high VO concentration of oxygen divacancy in SrFeO3 and SrCoO3 could enhance charge localization on down-spin d3z2-r2 orbitals, resulting in a remarkable increase of optical absorption at 1.5-3.0 eV.

Corrosion Sensors for Structural Health Monitoring of Oil and Natural Gas Infrastructure: A Review.

Corrosion has been a great concern in the oil and natural gas industry costing billions of dollars annually in the U.S. The ability to monitor corrosion online before structural integrity is compromised can have a significant impact on preventing catastrophic events resulting from corrosion. This article critically reviews conventional corrosion sensors and emerging sensor technologies in terms of sensing principles, sensor designs, advantages, and limitations. Conventional corrosion sensors encompass corrosion coupons, electrical resistance probes, electrochemical sensors, ultrasonic testing sensors, magnetic flux leakage sensors, electromagnetic sensors, and in-line inspection tools. Emerging sensor technologies highlight optical fiber sensors (point, quasi-distributed, distributed) and passive wireless sensors such as passive radio-frequency identification sensors and surface acoustic wave sensors. Emerging sensors show great potential in continuous real-time in-situ monitoring of oil and natural gas infrastructure. Distributed chemical sensing is emphasized based on recent studies as a promising method to detect early corrosion onset and monitor corrosive environments for corrosion mitigation management. Additionally, challenges are discussed including durability and stability in extreme and harsh conditions such as high temperature high pressure in subsurface wellbores.

Flexible nanograss with highest combination of transparency and haze for optoelectronic plastic substrates.

Transparent polymer substrates have recently received increased attention for various flexible optoelectronic devices. Optoelectronic applications such as solar cells and light emitting-diodes would benefit from substrates with both high transparency and high haze, which increase how much light scatters into or out of the underlying photoactive layers. In this letter, we demonstrate a new flexible nanograss plastic substrate that displays the highest combination of transparency and haze in the literature for polyethylene terephthalate (PET). As opposed to other nanostructures that increase haze at the expense of transparency, our nanograss demonstrates the potential to improve both haze and transparency. Furthermore, the monolithic nanograss may be fabricated in a facile scalable maskless reactive ion etching process without the need for additional lithography or synthesis of nanostructures. Our 9 µm height nanograss sample exhibits a transparency and haze of 92.4% and 89.4%, respectively, and our 34 µm height nanograss displays a transparency and haze of 91.0% and 97.1%, respectively. We also performed durability experiments that demonstrate these nanostructured PET substrates are robust from bending and show similar transmission and haze values after 5000 cycles of bending.

Plasmonic nanopatch array with integrated metal-organic framework for enhanced infrared absorption gas sensing.

In this letter, we present a nanophotonic device consisting of plasmonic nanopatch array (NPA) with integrated metal-organic framework (MOF) for enhanced infrared absorption gas sensing. By designing a gold NPA on a sapphire substrate, we are able to achieve enhanced optical field that spatially overlaps with the MOF layer, which can adsorb carbon dioxide (CO2) with high capacity. Experimental results show that this hybrid plasmonic-MOF device can effectively increase the infrared absorption path of on-chip gas sensors by more than 1100-fold. The demonstration of infrared absorption spectroscopy of CO2 using the hybrid plasmonic-MOF device proves a promising strategy for future on-chip gas sensing with ultra-compact size.

SAW Sensors for Chemical Vapors and Gases.

Surface acoustic wave (SAW) technology provides a sensitive platform for sensing chemicals in gaseous and fluidic states with the inherent advantages of passive and wireless operation. In this review, we provide a general overview on the fundamental aspects and some major advances of Rayleigh wave-based SAW sensors in sensing chemicals in a gaseous phase. In particular, we review the progress in general understanding of the SAW chemical sensing mechanism, optimization of the sensor characteristics, and the development of the sensors operational at different conditions. Based on previous publications, we suggest some appropriate sensing approaches for particular applications and identify new opportunities and needs for additional research in this area moving into the future.

Engineering metal oxide nanostructures for the fiber optic sensor platform.

This paper presents an effective integration scheme of nanostructured SnO2 with the fiber optic platform for chemical sensing applications based on evanescent optical interactions. By using a triblock copolymer as a structure directing agent as the means of nano-structuring, the refractive index of SnO2 is reduced from >2.0 to 1.46, in accordance with effective medium theory for optimal on-fiber integration. High-temperature stable fiber Bragg gratings inscribed in D-shaped fibers were used to perform real-time characterization of optical absorption and refractive index modulation of metal oxides in response to NH3 from the room temperature to 500 °C. Measurement results reveals that the redox reaction of the nanostructured metal oxides exposed to a reactive gas NH3 induces much stronger changes in optical absorption as opposed to changes in the refractive index. Results presented in this paper provide important guidance for fiber optic chemical sensing designs based on metal oxide nanomaterials.

Achieving precise multiparameter measurements with distributed optical fiber sensor using wavelength diversity and deep neural networks.

The development of advanced distributed optical fiber sensing systems that are capable of performing accurate and spatially resolved multiparameter measurements is of great interest to a wide range of scientific and industrial applications. Here, we propose and experimentally demonstrate a wavelength diversity based advanced distributed optical fiber sensor system to accomplish multiparameter sensing while greatly enhancing measurement accuracy. A suite of deep neural network (DNN) algorithms are developed and verified for data denoising, rapid Brillouin frequency shift estimation, and vibration data event classification. As a proof-of-concept, we demonstrate the effectiveness of the proposed advanced wavelength diversity distributed fiber sensor system assisted by DNN for simultaneous, independent measurements of static strain, temperature, and acoustic vibrations over a 25 km long sensing fiber at 3 m spatial resolution. These results suggest the potential for an intelligent multiparameter monitoring system with enhanced performance in advanced structural health monitoring applications.

All-Around Electromagnetic Wave Absorber Based on Ni-Zn Ferrite.

Exploring a convenient, scalable, yet effective broadband electromagnetic wave absorber (EMA) in the gigahertz (GHz) region is of high interest today to quench its expanding demand. Ni-Zn ferrite is considered as a potential EMA; however, their performance study as a scalable effective millimeter-length absorber is still limited. Herein, we investigated EM wave attenuation properties of Ni0.5Zn0.5Fe2O4 (NZF) samples substituting Mn ion in place of Fe3+ as well as Zn2+ within a widely used frequency range of 0.1-9 GHz. Through composition optimization, Ni0.5Zn0.4Mn0.1Fe2O4 (NZM0.1F) EMA demonstrates excellent microwave absorption performance accompanied by simultaneous maximum reflection loss (RL) of -50.2 dB and wide BW of 6.8 GHz (with RL < -10 dB, i.e., attenuation >90%) at an optimum thickness of 6 mm. Moreover, the attenuation constant significantly increases from ∼217 to 301 Np/m with Mn doping. The key contribution arises from magnetic-dielectric properties synergy along with enhanced dielectric and magnetic losses owing to cation chemistry and site occupation in spinel NZF. In addition, porosity is induced in the system by a controlled two-step heat treatment process that promotes total loss with multiple internal reflections of the EM wave. Furthermore, RL is simulated by varying incident EM wave angles for the NZM0.1F sample displaying its angle insensitivity up to 50°. Our results reveal NZM0.1F as a futuristic environment-friendly microwave absorber material that is suitable for practical high-frequency applications.

Surface acoustic wave devices for harsh environment wireless sensing.

Langasite surface acoustic wave devices can be used to implement harsh-environment wireless sensing of gas concentration and temperature. This paper reviews prior work on the development of langasite surface acoustic wave devices, followed by a report of recent progress toward the implementation of oxygen gas sensors. Resistive metal oxide films can be used as the oxygen sensing film, although development of an adherent barrier layer will be necessary with the sensing layers studied here to prevent interaction with the langasite substrate. Experimental results are presented for the performance of a langasite surface acoustic wave oxygen sensor with tin oxide sensing layer, and these experimental results are correlated with direct measurements of the sensing layer resistivity.