Quantum dot (QD)-based technologies have undergone rapid development since their initial discovery, particularly in the field of sensing. As a result, several use cases and new opportunities are emerging that benefit from these technologies across multiple areas relevant to energy applications. Researchers have exploited the unique properties of QDs, including their electronic, spintronic, magnetic, optical and magnetic behaviors, combined with well-established surface functionalization protocols to design high-performance sensor devices. Critical parameters including stability, robustness, accuracy, and sensitivity in different environmental settings have been evaluated during these studies. While a plethora of reviews have described QD sensors in extensive detail, this review is unique in that it focuses specifically on energy sector applications, an area that has largely been neglected to date, providing insights on the current state and possible avenues for deploying QD sensors. We provide updates on QD applications for gas sensing, deployment in pipelines and other energy infrastructure, pH sensing, environmental monitoring, detection of critical minerals such as rare earths, and fluid flow sensing and monitoring. We also briefly describe the possibility of adapting promising QD-based biomedical applications to the energy sector with little or no engineering efforts.

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.

Evanescent-field optical fiber sensors offer a wide range of benefits for gas and chemical sensing applications, including low cost per sensor node, stability under conditions that would be unfriendly for electronic sensor packages (e.g., high temperature, chemically harsh conditions, electromagnetic interference), and a small "footprint" for space-constrained applications. Optical fiber sensors also offer multiple unique capabilities, such as multi-wavelength interrogation via wavelength multiplexing and compatibility with spatially distributed interrogation techniques for multi-point detection. This approach relies upon the development of materials that demonstrate (1) high sensitivity, (2) selectivity, (3) fast response, and (4) long-term stability under relevant operating conditions. In this work, machine learning tools will be demonstrated to improve the performance in these areas, using a combination of experimental and simulated sensor data. The application of recurrent neural networks in the form of a long short-term memory (LSTM) model will be applied to simulated time-series sensor data to demonstrate improvement in selectivity and effective response time. Multi-parameter sensing applications relevant to energy sector applications will be discussed.

Hydrogen has substantially different combustion properties from natural gas and can dramatically affect the operation of combustion systems. So to achieve operational flexibility in combustion equipment which may use blends of natural gas with hydrogen, fast analysis of the variation of gas composition is important. The National Energy Technology Laboratory's (NETL) Raman gas analyzer (RGA) is a prototype field instrument for rapidly determining the composition of a gaseous mixture for real-time process control. The RGA uses a low power laser at visible wavelength and a reflective hollow waveguide as a sample gas cell for more intense Raman signals and fast sampling rates. The RGA unit has been calibrated with various pure gas species of interest including natural gas species and hydrogen, nitrogen, and oxygen. It has been characterized with varying hydrogen gas blends such as methane/hydrogen, ethane/hydrogen, and propane/hydrogen and natural gas model blends. In this paper, the measurement time and measurement accuracy of the composition of these gas blends at moderate pressures will be discussed. Demonstration of the RGA technology used to determine the composition of hydrogen blends quickly and continuously through laboratory and field tests, contributes to providing tools to ensure the safe and effective transport of hydrogen blends through existing natural gas and new gas pipelines.

Natural gas pipeline integrity monitoring is crucial to detect potential leaks, find structural issues, and prevent environmental damage. This article presents a system of natural gas pipeline monitoring that uses a specialized double Brillouin peak sensing fiber along with the Brillouin optical time domain analysis (BOTDAs) technique. The calibrated sensing fiber coefficients for strain and temperature are 41.8 kHz/mu epsilon and 0.9 MHz/degrees C for peak 1; and 47.2 kHz/mu epsilon, and 1.11 MHz/degrees C for peak 2, respectively. Initially, lab tests were performed by installing a short section of double Brillouin peak fiber (DBPF) on a 1-in steel pipe under pressure up to 1000 per square inch (psi) at elevated temperatures. Simultaneous distributed measurements of temperature and pressure-induced hoop strain were successfully measured. Considering the long processing speed to extract Brillouin frequency shift (BFS), we employ a novel probabilistic deep neural network (PDNN) framework for rapid BFS prediction. Additionally, using the Finite Element Method, the effects of the pipeline pressure on hoop strain were modeled and compared to the experimental hoop strain under the same set of pipeline conditions. Finally, an actual 4-in outer diameter steel natural gas pipeline was used for pilot-scale tests, where hoop strain was measured at various pressure levels. Leaks were simulated to demonstrate accurate pipeline integrity monitoring. At an internal pipe pressure of 1000 psi, hoop strain of approximately 300 mu epsilon was observed, and the sensitivity was calculated as0.28 mu epsilon/psi. The results of this pilot-scale study demonstrated that the system is capable of performing distributed monitoring sufficient to detect pipeline pressure and the presence of leaks to ensure the safe operation of gas pipelines in the field.

Quantum sensors provide sensitivity that is unattainable by classical sensors, allowing detection of the weak magnetic fields generated by the electron spins of rare earth elements (REEs). A specific electronic spin state in nitrogen vacancy (NV) centers in nanodiamonds has energies that are highly sensitive to the change in local electromagnetic fields, temperature, and pressure, and thus can be used to engineer sensors for the detection of these physical quantities. In this study, we conduct optically detected magnetic resonance (ODMR) using NV centers in nanodiamonds to detect the presence of nearby REEs. We observed an additional Zeeman splitting of similar to 1.17 MHz/mT per mu M of Gd relative to the Zeeman splitting observed in the absence of Gd, revealing the potential to use this technique for REE detection.

We investigate self-segregation of dopants in a crystal matrix within a single-crystal (SC) fiber. SC fiber is coated with dopant materials via a sol-gel dip coating method and used as the host material during laser-heated pedestal growth (LHPG). Due to differences in self-segregation coefficients, dopants are pulled toward the center or periphery of the fiber via convection forces induced by the temperature gradient in the molten zone. This results in a SC fiber with a dopant-rich core and reduced-dopant cladding layer (or vice-versa). Here, we report on self-segregation of Cr and Ti dopants within a sapphire matrix induced during LHPG. Variations of different experimental parameters are investigated, including fiber pull speeds, laser power, and whether growth takes place within a reducing environment. The cross-sectional dopant concentrations are measured via electron-probe micro-analysis. The cross- sectional constituent profiles are characterized as a function of varying growth parameters to identify the conditions that result in the best quality fiber for distributed sensor applications.

The ability to exploit quantum phenomena has enabled sensing technologies with detection limits below the classical limit. Sensors with applications in energy discovery, production, transportation and consumption can be enhanced through quantum or hybrid quantum–classical sensors. In this Review, we provide an overview of commercial and emerging quantum sensor platforms and their areas of opportunity specific to advanced energy technologies. Key examples include: power-grid-enhancing technologies, where quantum magnetometers can detect powerline and transformer faults; electric-vehicle-to-grid applications, where chip-scale atomic clocks can enable grid synchronization; and carbon capture and storage, where quantum gravimeters and single-photon light detection and ranging (LiDAR) can detect microscopic leaks. Quantum sensor deployment requires further research into miniaturization and ruggedization for field deployment, cost reduction and workforce development. The maturation of clean energy technologies and quantum sensors provides opportunities for synergy, so that the integration of quantum sensors into advanced energy technologies can maximize their security, reliability and efficiency. The development and deployment of clean technologies requires high-precision sensing, which quantum sensors can provide. This Review explores the development of quantum sensing technologies for emerging energy generation, transmission and storage applications.

The integration of Rayleigh and Brillouin scattering in a hybrid sensor system has revolutionized the field of distributed fiber optic sensing. This hybrid sensor system provides a strong and all-encompassing solution for monitoring multiple physical parameters, including strain, temperature, and vibrations along the sensing fiber length by combining the strengths of both scattering phenomena. We present a hybrid multi-parameter distributed sensing system in this paper that is based on the Brillouin and Rayleigh scattering mechanisms. Utilizing a single-end access to the sensing fiber, we measured acoustic vibrations based on phase-sensitive optical time domain reflectometry (Φ-OTDR), whereas we employed a Brillouin optical time reflectometry (BOTDR) for strain and temperature monitoring. The experimental results demonstrate the effectiveness of the hybrid sensor system to achieve simultaneous and independent measurements over a 25 km long single-mode silica fiber at 3 m spatial resolution. Furthermore, we used a large effective area fiber (LEAF) for simultaneous and discriminative strain, temperature, and vibration monitoring in order to get around the cross-sensitivity between the strain and temperature in the BOTDR system. A variety of applications, such as the structural health monitoring of buildings, bridges, and oil and gas pipelines, industrial process control, security, and surveillance, can be served by the suggested multi-parameter hybrid distributed sensor system.

This paper describes a low-cost fiber optical temperature sensor technology with wide operation temperature ranges and immune to complex electromagnetic environments. Using a low-cost passive frequency-double Q-switch YAG laser as the excitation source, multi-point fiber optical temperature sensors based on Raman backscattering are demonstrated. Using CCD cameras as optical sensors to detect both Stokes and Anti-Stokes backscattering signal, this paper shows that a 176-mu W excitation optical power coupled into optical fiber is sufficient to perform accurate temperature measurement. The temperature sensors are calibrated against thermocouple sensors from 20 degrees C to 120 degrees C with temperature measurement mean square errors better than 2 degrees C. The technology described in this paper is particularly suitable for renewable energy applications such as battery monitoring.

This paper introduces a double-parameter distributed fiber sensing system that utilizes stimulated Brillouin scattering in a specialized fiber, distinguished by two gain peaks in its scattering spectrum with nearly identical intensity levels. Employing this specialty fiber in a Brillouin optical time domain analysis system, we conduct a comprehensive analysis highlighting their efficacy in the simultaneous measurement of strain and temperature. These fibers are characterized by a significant temperature coefficient disparity (similar to 0.2 MHz/degrees C) between the two peaks, and similar large peak gain amplitudes resulting minimal Brillouin frequency shift uncertainties, thereby substantially reducing strain and temperature measurement errors. We evaluated strain and temperature coefficients of 47 kHz/mu epsilon, 1.15 MHz/degrees C for the first peak, and 51 kHz/mu epsilon, 1.37 MHz/degrees C for the second one, which were then applied in the simultaneous measurement of strain and temperature under various conditions, including an applied strain of 1220 mu epsilon at temperatures of 62 degrees C and 72 degrees C. The results indicate a significant enhancement in measurement accuracy, reducing errors to similar to 17 mu epsilon and similar to 0.9 degrees C in terms of strain and temperature respectively. Additionally, strain and temperature errors due to the impact of the variance of Brillouin frequency shift uncertainty between two peaks are explored. This study underscores the potential of the proposed double-Brillouin peak fiber in critical applications such as long-distance natural gas pipeline monitoring, where precise and distinct measurements of strain and temperature are paramount.

Distributed fiber optic sensing is a cutting-edge technology that has found extensive applications in the monitoring of pipelines. Among them, distributed acoustic sensors, phase-sensitive optical time domain reflectometry (Phi-OTDR) is a versatile technology that can continuously detect external perturbations and provide spatial and real-time information along the kilometer lengths of sensing fiber. Considering the low backscattering level of standard single-mode fiber as fiber under test, a Rayleigh-enhanced optical fiber embedded within the tight-buffered cable is demonstrated in field testing. We analyzed the increased backscattering fiber cable's vibration performance to the conventional single-mode telecom fiber using a custom-built Phi-OTDR interrogator system. Thereafter, using a 4-inch steel pipeline with a flow rate of 5, 10, 15, and 20 ft/s and a fixed pressure level of 1000 psi, we field-tested the sensor system for monitoring natural gas pipeline acoustic vibrations. We also field-tested the Brillouin optical time domain analysis (BOTDA) system for pipeline hoop strain monitoring under various pressure conditions. The pilot-scale testing results presented in this study suggested that pipeline operators can accurately perform flow monitoring, leak detection, and pressure monitoring for pipeline integrity monitoring.

Brillouin optical time domain analysis (BOTDA) sensor systems play a pivotal role in distributed sensing, which enable precise measurements of strain and temperature across extensive fiber lengths. Nonetheless, challenges emerge as distances grow due to signal attenuation and noise interference resulting in measurement errors. This research offers a comprehensive strategy to extend the sensing range of BOTDA systems beyond tens of kilometers while maintaining high spatial resolutions. Such enhanced sensing is realized through hybrid system that employs the integration of distributed Raman amplification, and inline amplification using erbium-doped fiber amplifiers (EDFA), as well as advanced noise reduction techniques. By optimizing power levels for the Brillouin pump and probe signals, as well as for Raman pump, hybrid BOTDA system ensures the robustness of Brillouin scattering signals, effectively countering attenuation-induced losses. Distributed amplification not only conquers attenuation but also suppresses nonlinear effects that could undermine measurement accuracy. Additionally, enhancing weak Brillouin signals by strategically placing EDFAs at optimal fiber locations keeps sensor sensitivity high. Leveraging inherent redundancy in measured data as a function of frequency and fiber distance, the non-local means (NLM) filter removes noise while preserving essential physical information. This approach proves particularly advantageous in BOTDA systems, where accurate measurement of Brillouin scattering signals is paramount for long-range sensing with high spatial resolutions. In summary, this research has shown a holistic exploration of extending BOTDA's distance sensing capabilities up to 150 km with spatial resolutions of 8 meters, and Brillouin frequency shift error of 1 MHz.

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. Nageswara Lalam and colleagues demonstrate a multiparameter distributed optical fibre sensing. They employ the wavelength multiplexing technique in Brillouin and Rayleigh scattering with the deep neural networks and achieve an improved performance of strain, temperature and vibration detection.

Single crystal (SC) optical fiber has promising potential to be used for optical fiber sensing applications in harsh conditions due to its robustness to high temperature, high radioactivity, and resistance to chemical corrosion as compared to optical sensors using silica fiber. However, SC fiber grown via the laser-heated pedestal growth (LHPG) technique innately does not have a core-cladding structure found in standard optical fiber, resulting in optical losses. In this work we investigate optimization of the growth parameters of a two LHPG process used to grow SC fiber with a graded index via introduction of dopants to the feedstock material. Feedstock material is fabricated with the first LHPG device, then sol-gel dip-coated to deposit outer films of dopant material. The dip-coated feedstock is used to grow SC fiber in which segregation of the dopant constituents occurs, resulting in a graded index of refraction across the fiber, and an effective core- cladding structure. Hardware and software improvements to both LHPG systems are presented and the growth parameters for short pieces of similar to 320-330 mu m diameter YAG fiber has been established. Characterization techniques/procedures have also been established for future grown SC fiber. These improvements and preparations are anticipated to result in a significant increase in grown fiber quality with a similar growth rate to that previously established.