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At least 73 records · Page 4

Gradient sensing via cell communication

Experimental evidence lends support to the conjecture that cell-to-cell communication plays a role in the gradient sensing of chemical species by certain chains of cells. Models have been formulated to explore this idea. For cells with no identifiable sensing structure, Mugler et al. [Proc. Natl. Acad. Sci. (U.S.A.) 113, E689 (2016)] have defined a particular local excitation, global inhibition (LEGI) model that pits nearest-neighbor communication against local reactions in a noisy environment to suggest how this sensing capability might arise in a physical system. In this study, we generalize the nearest-neighbor communication mechanism in the aforementioned LEGI model in order to explore the extent to which the gradient sensing characteristics depend on the parametrization of the communication itself, as well as on the cell size, the radius of influence of neighboring cells, and the influence of the background noise. Using our generalization and a collection of particular candidate communication models, we find that the precision of gradient sensing is indeed sensitive to the particular communication model, and we derive physical and analytic explanations for these results. The framework established and the associated results should prove useful in understanding the appropriateness of particular cell-to-cell communication models in gradient sensing studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Critical Review of LPBF Metal Print Defects Detection: Roles of Selective Sensing Technology

The integrative potential of LPBF-printed parts for various innovative applications depends upon the robustness and infallibility of the part quality. Eliminating or sufficiently reducing factors contributing to the formation of defects is an integral step to achieving satisfiable part quality. Significant research efforts have been conducted to understand and quantify the triggers and origins of LPBF defects by investigating the material properties and process parameters for LPBF-printed geometries using various sensing technologies and techniques. Frequently, combinations of sensing techniques are applied to deepen the understanding of the investigated phenomena. The main objectives of this review are to cover the roles of selective sensing technologies by (1) providing a summary of LPBF metal print defects and their corresponding causes, (2) informing readers of the vast number and types of technologies and methodologies available to detect defects in LPBF-printed parts, and (3) equipping readers with publications geared towards defect detection using combinations of sensing technologies. Due to the large pool of developed sensing technology in the last few years for LPBF-printed parts that may be designed for targeting a specific defect in metal alloys, the article herein focuses on sensing technology that is common and applicable to most common defects and has been utilized in characterization for an extended period with proven efficiency and applicability to LPBF metal parts defect detection.

36 MATERIALS SCIENCE↗

Sensing at the Nanoscale Using Nitrogen-Vacancy Centers in Diamond: A Model for a Quantum Pressure Sensor

The sensing of stress under harsh environmental conditions with high resolution has critical importance for a range of applications including earth’s subsurface scanning, geological CO2 storage monitoring, and mineral and resource recovery. Using a first-principles density functional theory (DFT) approach combined with the theoretical modelling of the low-energy Hamiltonian, here, we investigate a novel approach to detect unprecedented levels of pressure by taking advantage of the solid-state electronic spin of nitrogen-vacancy (NV) centers in diamond. We computationally explore the effect of strain on the defect band edges and band gaps by varying the lattice parameters of a diamond supercell hosting a single NV center. A low-energy Hamiltonian is developed that includes the effect of stress on the energy level of a ±1 spin manifold at the ground state. By quantifying the energy level shift and split, we predict pressure sensing of up to 0.3 MPa/Hz using the experimentally measured spin dephasing time. We show the superiority of the quantum sensing approach over traditional optical sensing techniques by discussing our results from DFT and theoretical modelling for the frequency shift per unit pressure. Importantly, we propose a quantum manometer that could be useful to measure earth’s subsurface vibrations as well as for pressure detection and monitoring in high-temperature superconductivity studies and in material sciences. Our results open avenues for the development of a sensing technology with high sensitivity and resolution under extreme pressure limits that potentially has a wider applicability than the existing pressure sensing technologies.

36 MATERIALS SCIENCE↗

Multiparameter optical fiber sensing for energy infrastructure through nanoscale light–matter interactions: From hardware to software, science to commercial opportunities

Monitoring of energy infrastructure through robust yet economical sensing platforms is becoming an area of increased importance, with ubiquitous applications including the electrical grid, natural gas and oil transportation pipelines, H2 infrastructure (storage and transportation), carbon storage, power generation, and subsurface environments. Plasmonic and functional nanomaterial enabled fiber optic sensors show excellent promise for a wide range of sensing applications due to their versatility to be engineered for specific analytes of interest while retaining inherent advantages of the optical fiber sensor platform. Through the design of novel sensing layers, the optical transduction mechanism and wavelength dependence can also be tailored for ease of integration with low-cost interrogation systems enabling an inexpensive yet highly functional optical fiber sensing platform. In addition, recent advances in artificial intelligence and machine learning theoretical methods have been leveraged to simultaneously extract multiple parameters through multi-wavelength interrogation such that unique wavelengths can also serve as unique sensing elements, analogous to electronic nose sensor technologies. The concept of an optical fiber based “photonic nose” via multiple interrogation wavelengths and/or sensor nodes offers a compelling platform technology to realize multiparameter speciation of chemical analytes within complex gas mixtures. In this Perspective, we further generalize the notion of multiparameter sensing through the novel “photonic nervous system” concept based upon low-cost, functionalized optical fiber sensor probes monitoring a variety of distinct analyte classes (physical, chemical, electromagnetic, etc.) simultaneously to provide broad situational awareness via integrated sensors.

Su, Yang-Duan (ORCID:0000000214820902)↗

A recyclable self-healing composite with advanced sensing property

Polymer-based composites frequently encounter damage, often lurking beneath the surface and proving challenges to their early detection and repair. While material-based sensors show promise for encoding self-sensing properties within these composites, their in situ healing and reprocessability remain significant challenges. Therefore, the overarching goal of this study is the creation of a reprocessable polymeric composite encoded with self-healing attributes and the ability to autonomously sense damage. At the core of this innovation are vitrimers, a polymeric material characterized by a covalently adaptive dynamic network responsive to external factors such as heat. They combine thermoset-like resilience with thermoplastic-like flowability on demand under external stimuli. We nanoengineer a polyester-based vitrimeric polymer by incorporating piezoresistive carbon nanotubes (CNTs) as reinforcing elements that not only enhance its mechanical strength but also create a percolation network within the composite, thereby enabling piezoresistive self-sensing properties, all the while preserving the intrinsic self-healing capabilities offered by the vitrimeric matrix. The fabrication process of the composite involves a solvent-free in situ polymerization method that combines epoxy and anhydride-containing monomers with ~ 0.1 wt.% of CNTs. Once it was established that the introduction of CNTs into the polymeric matrix did not compromise the mechanical properties of the composite, their strain-sensing properties were characterized by applying cyclic loading while measuring their electrical resistance. Strikingly, CNT-enhanced vitrimer composite consistently retains its mechanical and sensing properties through repeated cycles of reshaping and reprocessing, underscoring its potential as a robust distributed strain sensor. This polyester-based vitrimeric composite is also easily recyclable without harsh chemical treatments. Preliminary findings from this study conclusively demonstrate that the bulk composite boasts both self-sensing capabilities and in situ detect healing properties, charting a promising course towards the development of a mechanically resilient multifunctional composite that seamlessly integrates selfsensing and healing capabilities.

Rohewal, Sargun Singh↗

Nickel-incorporated Oxide Composites for Fiber-Optic Based Gas Sensing

Numerous high-value applications within the energy sector involve environmental conditions that are incompatible with traditional sensor technology due to degradation of electrical interconnects, packaging, or the sensors themselves. These can include chemically harsh conditions, high temperature operation, or the presence of electromagnetic interference due to high voltage. The fiber optic platform, constructed of robust, electrically insulating glass or single crystal oxides, offers a versatile and often low cost per node solution to this problem, especially with the integration of distributed sensing techniques such as optical time-domain and frequency-domain reflectometry (OTDR, OFDR). A major challenge of gas and chemical sensing on the optical fiber platform is the fabrication of robust and stable sensing materials that interact quickly and reversibly to the presence of the target analytes. In this work, we discuss the utilization of nickel-incorporated oxides on evanescent-field optical fiber sensors for gas sensing under harsh conditions relevant to multiple energy infrastructure applications. This paper will discuss a Ni/GDC (Ni / Gd-doped ceria) based sensing layer targeting conditions relevant for high-temperature (up to at least 800 oC) hydrogen sensing applications (e.g., for operation within a solid oxide fuel cell or electrolyzer). The impact of hydrogen at elevated temperatures on the optical properties of Ni/GDC will be shown and the material mechanisms for the optical response will be discussed.

gas sensors↗

Virtual Refrigerant Charge Sensing Method for Next-Generation Refrigerant in Residential Heat Pumps

The charge level of refrigerant in heat pump systems significantly affects their operational performance. Virtual refrigerant charge (VRC) sensing technology has been well-established for traditional refrigerants (HFCs and HCFCs) for its low cost compared to physical sensors. However, other than traditional refrigerants, HFOs are increasingly used in next-generation heat pumps; whether these conventional VRC sensing methods remain applicable for heat pump systems utilizing next-generation refrigerants requires further investigation. To address these issues, this study develops a low-cost VRC sensing method for next-generation refrigerant heat pumps used in residential buildings. The developed algorithm is evaluated by using simulation models to evaluate the accuracy, considering an R454B heat pump with a nominal heating capacity of 51K Btu/hr (14.95 kW) as an example, and compared with those of the two reference VRC sensing algorithms. Though the developed VRC sensing algorithm and the two reference methods can accurately predict the charge level for the R454B heat pump system (with mean absolute percentage error for various cooling and heating conditions less than 7%), the developed VRC sensing algorithm uses fewer sensors and improves the overall accuracy for heating conditions by 7.1%, and the accuracy for undercharge cooling conditions 14.2%, compared with a mainstream algorithm. This technology will complement physical leakage detectors, and promote the adoption of next-generation heat pump systems, along with reducing wasted energy and maintenance costs.

Liang, Chenjiyu↗

Nickel-incorporated Oxide Composites for Fiber-Optic Based Gas Sensing

Numerous high-value applications within the energy sector involve environmental conditions that are incompatible with traditional sensor technology due to degradation of electrical interconnects, packaging, or the sensors themselves. These can include chemically harsh conditions, high temperature operation, or the presence of electromagnetic interference due to high voltage. The fiber optic platform, constructed of robust, electrically insulating glass or single crystal oxides, offers a versatile and often low cost per node solution to this problem, especially with the integration of distributed sensing techniques such as optical time-domain and frequency-domain reflectometry (OTDR, OFDR). A major challenge of gas and chemical sensing on the optical fiber platform is the fabrication of robust and stable sensing materials that interact quickly and reversibly to the presence of the target analytes. In this work, we discuss the utilization of nickel-incorporated oxides on evanescent-field optical fiber sensors for gas sensing under harsh conditions relevant to multiple energy infrastructure applications. This paper will discuss a Ni/GDC (Ni / Gd-doped ceria) based sensing layer targeting conditions relevant for high-temperature (up to at least 800oC) hydrogen sensing applications (e.g., for operation within a solid oxide fuel cell or electrolyzer). The impact of hydrogen at elevated temperatures on the optical properties of Ni/GDC will be shown and the material mechanisms for the optical response will be discussed.

gas sensors↗

Radio frequency sensing and its innovative applications in diverse sectors: A comprehensive study

Recent advancements in radio frequency (RF) sensing technology can be attributed to the development of the Internet of Things (IoT), healthcare, RF-identification, and communication applications. RF sensing is a multidisciplinary research field that requires expertise in computing, electronics, and electromagnetics to cover all system features, including protocol development, antenna design, sensor integration, algorithm formulation, interconnection, data, and analytics. The overarching aim of this work is to present detailed information about RF technologies and their innovations and application diversity from the novel work carried out at CSI Lab1, together in one platform with an extensive survey. This study presents state-of-the art applications and RF sensing that include W-Fi, radar, and SDR and RFID-based sensing. A comprehensive survey and study of the advantages and limitations of each non-contact technology is discussed. Additionally, open research gaps have been identified as well. Decades of knowledge and experience have been put to use to meet new challenges and demands. The development and study of RF systems, IoT, RFID sensing, and research and deployment activities, are briefly discussed. The emerging research projects with industry, institutional research centers, and academic studies are also addressed. Finally, an outline of identified potential future research areas is provided, emphasizing opportunities and challenges.

47 OTHER INSTRUMENTATION↗

Self-Sustainable IoT-Based Remote Sensing Powered by Energy Harvesting Using Stacked Piezoelectric Transducer and Thermoelectric Generator

We propose a self-powered remote multi-sensing system for traffic sensing which is powered by the collective energy harvested from the mechanical vibration of the road caused by the passing vehicles and from the temperature gradient between the asphalt of the road and the soil underneath. A stacked piezoelectric transducer converts mechanical vibrations into electrical energy and a thermoelectric generator harvests the thermal energy from the thermal gradient. Electrical energy signals from the stacked piezoelectric transducer and the thermoelectric generators are converted into usable DC power to recharge the battery using AC-DC and DC-DC converters working simultaneously. The multi-sensing system comprises an embedded system with a microcontroller that acquires data from the sensors and sends the sensory data to an IoT transceiver which transmits the data as RF packets to an ethernet gateway. The gateway converts the RF packets into Internet Protocol (IP) packets and sends them to a remote server. Laboratory and road-testing results showed over 98% sensory data accuracy with the system functioning solely powered by the energy harvested from the alternative energy sources. The successful maximum transmission distance obtained between the IoT, and the gateway was approximately 1 mile, which is a considerable transmission distance achieved in an urban environment. Successful operation of the self-powered multi-sensing system under both laboratory and road conditions contributes considerably to the fields of energy harvesting and self-powered remote sensing systems. The energy flow chart and efficiency for the steps in the system were found to be mechanical power from vehicles to the energy harvester of 0.25%, stacked PZT transducer efficiency was found to be 37%, and for the TEGs the efficiency is 11%. AC-to-DC and DC-to-DC converters’ efficiencies were found to be 90% and 11%. The wireless communication RF transceiver efficiency was found to be 62.5%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Additively Manufactured Strain Sensing for Nuclear Reactor Applications

Real-time monitoring of materials in harsh environments is a crucial technique towards reducing innovation time in nuclear systems. The successful measurement of real time, in-situ strain measurements during nuclear reactor operation requires innovative sensing solutions, including novel sensing strategies as well as advanced sensor design, manufacturing, and materials selection. In this paper, we will discuss two primary strategies for in-situ strain measurement strategies: additively manufactured (AM) capacitive strain gauges (CSGs) and digital image correlation (DIC). Current commercial strain gauges have limited applications in reactors due to the harsh operating conditions and non-trivial attachment strategies (i.e., welding, epoxy-adhesive) that can affect both the sensing performance and the underlying substrate under testing. AM CSGs are a viable solution as they have a low profile, low hysteresis, and wireless sensing integration capabilities that will enhance nuclear sensing technologies. In this work, the mechanical and thermal performance of the AM CSGs were tested up to 300 °C using ASTM standardized testing procedures to simulate the temperatures found in existing light water reactors. The AM CSGs had a similar performance across multiple samples which correlates to analytical models. This work leads towards the development of CSGs designed for higher temperatures and additional environmental factors found in Generation-IV reactors. Non-contact sensors, such as DIC, offer a less destructive way to measure deformation of materials when compared to alternative methods of in-situ strain determination, such as weldable strain gauges. However, DIC requires high contrast surfaces, which often relies on the implementation of artificial patterns. Using traditional splatter techniques to fabricate these patterns have limitations, including poor surface adhesion and reproducibility. In this work, AM fabrication techniques were implemented to avoid such limitations. Accordingly, aerosol jet printing (AJP) was used to print small scale periodic patterns of silver on stainless steel and aluminum tensile specimens. DIC was employed to monitor strain (up to 1100 µe) during temperature cycling from 23-600 °C. The results validated the use of AJP to better control pattern parameters for small fields of view applications at high temperatures.

36 MATERIALS SCIENCE↗

Freestanding BaTiO 3 ‐Au Vertically Aligned Nanocomposite toward Flexible Multi‐Sensing Platform

Abstract Flexible and wearable sensors show enormous potential for personalized healthcare devices by real‐time monitoring of an individual's health. Typically, a single functional material is selected for one sensor to sense a particular physical signal while multiple materials will be selected for multi‐mode sensing. Vertically aligned nanocomposites (VANs) have recently demonstrated various material combinations and novel coupled multifunctionalities that are hard to achieve in any single‐phase material alone, including multiphase multiferroics, magneto‐optic coupling, and strong magnetic and optical anisotropy. Integrating these novel VANs into wearable sensors shows enormous potential in multi‐mode sensing owing to their multifunctional nature. In this work, the transfer of VANs onto polydimethylsiloxane as a novel flexible chemical and pressure sensor is demonstrated. For this demonstration, the classical BaTiO 3 ‐Au VAN with combined plasmonic and piezoelectric properties is used to demonstrate a multi‐sensing mechanism. A thin water‐soluble buffer of Sr 3 Al 2 O 6 serves as a buffer layer for the epitaxial growth and transfer process. The electrical output based on the piezoelectric responses and identifying 4‐mercaptobenzoic acid by surface‐enhanced Raman spectroscopy reveal great potential for free‐standing VANs in a wearable multifunctional sensing platform.

Tsai, Benson Kunhung [School of Materials Engineer↗

Synergistic Integration of Chemo-Resistive and SERS Sensing for Label-Free Multiplex Gas Detection

Practical sensing applications such as real-time safety alerts and clinical diagnoses require sensor devices to differentiate between various target molecules with high sensitivity and selectivity, yet conventional devices such as oxide-based chemo-resistive sensors and metal-based surface-enhanced Raman spectroscopy (SERS) sensors usually do not satisfy such requirements. In this report a label-free, chemo-resistive/SERS multimodal sensor based on a systematically assembled 3D cross-point multifunctional nanoarchitecture (3D-CMA), which has unusually strong enhancements in both “chemo-resistive” and “SERS” sensing characteristics is introduced. 3D-CMA combines several sensing mechanisms and sensing elements via 3D integration of semiconducting SnO 2 nanowire frameworks and dual-functioning Au metallic nanoparticles. It is shown that the multimodal sensor can successfully estimate mixed-gas compositions selectively and quantitatively at the sub-100 ppm level, even for mixtures of gaseous aromatic compounds (nitrobenzene and toluene) with very similar molecular structures. This is enabled by combined chemo-resistive and SERS multimodal sensing providing complementary information.

36 MATERIALS SCIENCE↗

Hydrogen sensing in different hydrogen-carrying gases using composites of PdSnO 2 and halloysite nanotubes

Here, in this work, we developed composites of palladium-decorated tin dioxide (PdSnO 2 ) and halloysite nanotubes (HNTs) by adding different amounts of HNTs as additives into PdSnO 2 , and investigated how the different amounts of HNTs in the composites and the different hydrogen (H 2 ) carrying gases (air and helium (He)) could affect the H 2 sensing performance of such composites (PdSnO 2 -HNT). Through the sensing-performance characterization using H 2 carried by air, it was found that PdSnO 2 with an appropriate small amount of HNTs (i.e., 2 % of PdSnO 2 mass) can improve the sensing performance with respect to limit of detection (LOD) and response/recovery time. Further, the optimal PdSnO2-HNT composite as a sensor was tested to detect H 2 in He. The testing results indicated that the composite can detect H 2 in He, but its performance parameters (i.e., the profile of calibration curve, LOD, and response time) are different from those of such a sensor in detecting H 2 in air. Moreover, the composite still presented better sensing performance than PdSnO 2 without HNTs in detecting H 2 in He. Possible reasons for the effects of HNT and H 2 -carrying gas on the sensing performance of PdSnO 2 -HNT-based sensors were discussed. We believe that this study provides valuable insights into the functionality and the adaptability of PdSnO 2 -HNT-based H 2 sensors in diverse operational conditions.

36 MATERIALS SCIENCE↗

Tower-Based Remote Sensing Reveals Mechanisms Behind a Two-phased Spring Transition in a Mixed-Species Boreal Forest

The boreal forest is a major contributor to the global climate system, therefore, reducing uncertainties in how the forest will respond to a changing climate is critical. One source of uncertainty is the timing and drivers of the spring transition. Remote sensing can provide important information on this transition, but persistent foliage greenness, seasonal snow cover, and a high prevalence of mixed forest stands (both deciduous and evergreen species) complicate interpretation of these signals. We collected tower-based remotely sensed data (reflectance-based vegetation indices and Solar-Induced Chlorophyll Fluorescence [SIF]), stem radius measurements, gross primary productivity, and environmental conditions in a boreal mixed forest stand. Evaluation of this data set shows a two-phased spring transition. The first phase is the reactivation of photosynthesis and transpiration in evergreens, marked by an increase in relative SIF, and is triggered by thawed stems, warm air temperatures, and increased available soil moisture. The second phase is a reduction in bulk photoprotective pigments in evergreens, marked by an increase in the Chlorophyll-Carotenoid Index. Deciduous leaf-out occurs during this phase, marked by an increase in all remotely sensed metrics. The second phase is controlled by soil thaw. Our results demonstrate that remote sensing metrics can be used to detect specific physiological changes in boreal tree species during the spring transition. The two-phased transition explains inconsistencies in remote sensing estimates of the timing and drivers of spring recovery. Our results imply that satellite-based observations will improve by using a combination of vegetation indices and SIF, along with species distribution information.

54 ENVIRONMENTAL SCIENCES↗

Parallel high-frequency magnetic sensing with an array of flux transformers and multi-channel optically pumped magnetometer for hand MRI application

Here, we investigate an approach for parallel high-frequency magnetic sensing based on a multi-channel radio frequency (RF) optically pumped magnetometer (OPM) coupled to multiple flux transformers (FTs) with a focus on hand magnetic resonance imaging (MRI) application at ultra-low field (ULF). Multiple RF OPM sensing channels are realized by using a single large-area alkali-metal vapor cell and two laser beams for pumping and probing, shared for all the channels. This design leads to significant cost reduction when multi-channel sensing is desirable, as in the case of ULF MRI. The FT, composed of two connected coils, serves as a transmitter of a target magnetic field to the OPM, while decoupling the OPM from untargeted magnetic fields in the sensing area that can limit the OPM performance. For hand MRI application, theoretical and numerical analysis is performed to determine an optimal geometry for the FT array that could improve signal-to-noise ratio (SNR) and sufficiently reduce crosstalk between FTs. We estimate that the optimized multi-channel FT-OPM sensor can achieve a magnetic field sensitivity of the order of 1 fT / Hz 1 / 2 above 100 kHz, which would be sufficient for 1 mm resolution MRI. In general, the multi-channel capability enables simultaneous magnetic measurements, thus reducing the sensing time and improving the SNR, and we anticipate many applications of the multi-channel FT-OPM sensor beyond the targeted here hand MRI: anatomical parallel ULF MRI of the human brain and other parts of the body, airport security screening, magnetic material imaging, and many others.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Incubating advances in integrated photonics with emerging sensing and computational capabilities

As photonic technologies grow in multidimensional aspects, integrated photonics holds a unique position and continuously presents enormous possibilities for research communities. Applications include data centers, environmental monitoring, medical diagnosis, and highly compact communication components, with further possibilities continuously growing. Herein, we review state-of-the-art integrated photonic on-chip sensors that operate in the visible to mid-infrared wavelength region on various material platforms. Among the different materials, architectures, and technologies leading the way for on-chip sensors, we discuss the optical sensing principles that are commonly applied to biochemical and gas sensing. Our focus is on passive optical waveguides, including dispersion-engineered metamaterial-based structures, which are essential for enhancing the interaction between light and analytes in chip-scale sensors. We harness a diverse array of cutting-edge sensing technologies, heralding a revolutionary on-chip sensing paradigm. Our arsenal includes refractive-index-based sensing, plasmonics, and spectroscopy, which forge an unparalleled foundation for innovation and precision. Furthermore, we include a brief discussion of recent trends and computational concepts, incorporating Artificial Intelligence & Machine Learning (AI/ML) and deep learning approaches over the past few years to improve the qualitative and quantitative analysis of sensor measurements.

Jain, Sourabh (ORCID:0000000279923275)↗

Distributed electric field sensing using fibre optics in borehole environments

In the past decade, rapid advances in distributed optical fibre sensing technologies have made it possible to record various geophysical data (e.g. strain, temperature and pressure) continuously in both time and space along the fibre, providing an unprecedented quantity and spatial density of data compared to traditional geophysical measurements as well as reducing data acquisition cost. To date, no distributed fibre-based electromagnetic field sensing system has been implemented although electromagnetic sensing could have a broad range of applications to geophysical imaging and monitoring in borehole environments. The goal of this paper is to provide a theoretical feasibility study regarding the design and use of an electromagnetic sensing optical fibre for geophysical applications. First, we present the sensitivity analysis of a ‘hypothetical’ optical fibre coated with polyvinylidene fluoride, a polymer that provides relatively high piezoelectric properties, yet unlike ceramics, is flexible. Next, using a two-dimensional electromagnetic modelling algorithm, we simulate the earth electric-field-to-fibre-strain transfer function and estimate the theoretical sensitivity of the optical fibre to electric fields. Given the state-of-the-art distributed acoustic sensing strain sensitivities in the picometres strain range, our numerical modelling analysis suggests that a perfectly coupled polyvinylidene fluoride–coated optical fibre can measure electric field values in the mV/m to V/m amplitude range. We then apply a cylindrically symmetric modelling algorithm to simulate numerical models demonstrating the applicability of such a fibre in an oilfield environment. Scenarios investigated employ an electric field source and suggest that the measurements can be used to distinguish the oil versus water ratio with a fibre mounted inside a producing steel cased oil well as well as distinguishing between brine and hydrocarbon filled reservoir zones with a fibre located outside of the casing.

58 GEOSCIENCES↗