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At least 487 records · Page 27

Femtosecond laser fabrication of nanograting-based distributed fiber sensors for extreme environmental applications

Abstract The femtosecond laser has emerged as a powerful tool for micro- and nanoscale device fabrication. Through nonlinear ionization processes, nanometer-sized material modifications can be inscribed in transparent materials for device fabrication. This paper describes femtosecond precision inscription of nanograting in silica fiber cores to form both distributed and point fiber sensors for sensing applications in extreme environmental conditions. Through the use of scanning electron microscope imaging and laser processing optimization, high-temperature stable, Type II femtosecond laser modifications were continuously inscribed, point by point, with only an insertion loss at 1 dB m −1 or 0.001 dB per point sensor device. High-temperature performance of fiber sensors was tested at 1000 °C, which showed a temperature fluctuation of ±5.5 °C over 5 days. The low laser-induced insertion loss in optical fibers enabled the fabrication of a 1.4 m, radiation-resilient distributed fiber sensor. The in-pile testing of the distributed fiber sensor further showed that fiber sensors can execute stable and distributed temperature measurements in extreme radiation environments. Overall, this paper demonstrates that femtosecond-laser-fabricated fiber sensors are suitable measurement devices for applications in extreme environments.

Wang, Mohan (ORCID:0000000166784993)↗

An Active Detection Scheme for Sensor Spoofing in Grid-tied PV Systems

In this paper an active detection scheme for sensor spoofing (manipulated externally via a cyber attack) in grid-tied PV systems is discussed. The core of the proposed active detection scheme is to introduce a private (secret) watermarking signal into the control inputs of the DC-DC converter and DC-AC inverter stages to detect any malicious spoofing (manipulation) of voltage/current sensor measurements controlling both the DC-DC converter maximum power point tracking (MPPT) stage and the DC-AC inverter of the grid-tied PV system. Several types of possible spoofing mechanisms (attack models) are discussed. The proposed sensor spoofing attack detector system consists of injecting a small magnitude of digital watermarking signal (DWS) and conduct three statistical watermark tests on the reported sensor measurements to determine if a) the proposed system is healthy and operating as expected b) if sensor signals were spoofed (manipulated) externally or c) if a particular sensor is malfunctioning due to a faulty hardware. It is shown via extensive simulations that the proposed DWS approach is robust in detecting malicious external manipulation of sensors controlling the grid tied PV system. A testing platform is currently under development and the experimental results will be discussed in the conference presentation.

Ibrahim, Hasan↗

Digital Filter Design for Point-on-Wave Sensors: Highlighting Frequency Response Limitations and Enhancing Grid Simulation Accuracy

Data is proving to be the backbone of today's and, more importantly, tomorrow's grid. As the system changes and introduces fast-acting devices like power electronics, overall observability tends to decrease from the utility point-of-view. This can be mitigated by adding more high-fidelity sensors onto the grid, although this incurs a cost. These sensors are never ideal, and each have unique frequency responses that may influence the data produced. This may, in turn, impact the protection and control of the power grid. This paper presents a methodology of representing these point-on-wave sensors digitally by estimating digital-filter representations of them, thereby introducing means of improving the sensor models used in electromagnetic-transient (EMT) simulations. This may help with identifying potential high-frequency, sensor-induced distortions, and system resonance compensation. Three commercial-grade medium-voltage point-on-wave sensors are utilized in a lab environment to obtain experimental frequency responses with a frequency sweep, and it is shown that both Infinite Impulse Response (IIR) and Finite Impulse Response (FIR) filter representations may approximate these responses with varying degrees of accuracy, though each has their own strengths and weaknesses. It is found that, in general, FIR estimation better approximates these sensors than IIR estimation does.

Wilson, Aaron [ORNL] (ORCID:0000000327331697)↗

Spectroelectrochemistry as a Strategy for Improving Selectivity of Sensors for Security and Defense Applications

Spectroelectrochemistry provides improved selectivity for sensors by electrochemically modulating the optical signal associated with the analyte. The sensor consists of an optically transparent electrode (OTE) coated with a film that preconcentrates the target analyte. The OTE functions as an optical waveguide for attenuated total reflectance (ATR) spectroscopy, which detects the analyte by absorption. Alternatively, the OTE can serve as the excitation light for fluorescence detection, which is generally more sensitive than absorption. The analyte partitions into the film, undergoes an electrochemical redox reaction at the OTE surface, and absorbs or emits light in its oxidized or reduced state. The change in the optical response associated with electrochemical oxidation or reduction at the OTE is used to quantify the analyte. Absorption sensors for metal ion complexes such as [Fe(CN)6]4- and [Ru(bpy)3]2+ and fluorescence sensors for [Ru(bpy)3]2+ and the polycyclic aromatic hydrocarbon 1-hydroxypyrene have been developed. The sensor concept has been extended to binding assays for a protein using avidin–biotin and 17β-estradiol–anti-estradiol antibodies. The sensor has been demonstrated to measure metal complexes in complex samples such as nuclear waste and natural water. This sensor has qualities needed for security and defense applications that require a high level of selectivity and good detection limits for target analytes in complex samples. Quickly monitoring and designating intent of a nuclear program by measuring the Ru/Tc fission product ratio is such an application.

Environmental Molecular Sciences Laboratory↗

A method for estimating the amplitude response of smartphone built-in microphone sensors below 4 kHz

A method for estimating the amplitude response of built-in smartphone microphone sensors is pre- sented. The method is intended to be accessible to the general public, and comparison calibration measurements are performed in a non-isolated environment using conventional consumer products. A double reference sensor scheme is set up, consisting of a MB3 digital microbarometer (reference over the 0.5–2 Hz octave bands) and the iPrecisionMic smartphone microphone (reference above the 2 Hz octave band). The amplitude response of the iPrecisionMic sensor is first evaluated over the 1–2000 Hz octave bands. The amplitude response of three Samsung Galaxy S8 built-in smart- phone microphone sensors is then measured over the 0.5–2000 Hz octave bands. The Redvox Infrasound Recorder application (app) for Android is used to measure acoustic signals with the built-in smartphone microphone sensors. Amplitude response models in terms of digital gain are estimated for the test sensors based on the results. Last, self-noise levels for the iPrecisionMic and Samsung Galaxy S8 microphones are estimated and compared to infrasound ambient noise models. Results show an experimental capability for estimating the amplitude response of built-in smartphone microphone sensors in a non-isolated environment with conventional consumer products.

47 OTHER INSTRUMENTATION↗

Review—Electrolytic Metal Atoms Enabled Manufacturing of Nanostructured Sensor Electrodes

Sensing materials play a key role in the successful implementation of electrochemical sensors, and nanotechnology has emerged as an important and rapidly growing field for stimulating the innovation of high-performance sensors. The fabrication, characterization, and evaluation of the nanostructured electrodes are therefore a focus of this field. Compared to a variety of dry and wet technologies which have been extensively developed for this purpose, electrochemical methods are typically convenient, highly effective, and potentially low-cost for the production of different nanostructures. This minireview is designed to introduce a unique electrochemical method - electrolytic metal-atom enabled manufacturing (EM 2 ) and its application in electrochemical sensors. The EM 2 technique employs electrolytic metal atoms generated from their corresponding salt precursor as a tool to nanostructure a wide range of substrate electrodes used in electrochemical sensors, based on a one-pot electrochemical deposition and dissolution of the metal atoms in the same electrolyte bath. Briefly, the metal atoms are electrodeposited on a substrate electrode during the cathode reduction, and they are selectively removed from the substrate during the subsequent anode oxidation. Because of the interactions between the electrolytic metal atoms and the substrate atoms, the repetitive electrodeposition and dissolution of the former on the substrate enable the nanostructuration of the substrate, particularly within its surface layers. The nanostructured electrodes have demonstrated very attractive performance for the determination of numerous analytes, such as high sensitivity and selectivity, high interference tolerance, and low detection limits. However, the EM 2 technique and the application of the resulting nanostructured electrodes in electrochemical sensors and beyond have still been very limitedly investigated. In order to bring the community from academic, industries, agencies, and customers together to develop the EM 2 technique and advance electrochemical sensor systems, this minireview will introduce the thermodynamic and kinetic fundamentals of this technique, the characterization of resulting nanostructures, the analysis of their electrochemical behavior, and the implementation of this technique for the development of advanced sensor electrodes. Finally, an outlook with a focus on further research areas is provided.

Jiang, Junhua (ORCID:0000000324379812)↗

Retro-Commissioning Sensor Suitcase

This software package is the Graphic User Interface (GUI) software component for the Sensor Suitcase Retro-Commissioning project, which is a sensor and analysis system to support monitoring-based retro-commissioning of small commercial buildings, performed by non-experts. Small commercial buildings typically do not have the budgets or business economics to allow investing in energy efficiency enhancements the building retro-commissioning provides. In addition, they do not have in-house staff with expertise in building systems who can perform building retro-commissioning or identify energy efficiency improvement opportunities. The solution to this problem is to develop a turn-key hardware/software solution (the RCx Sensor Suitcase) that can be used by non-experts to automatically generate low and no-cost energy efficiency rec commendations that will improve building operating costs, occupant comfort and building energy performance. This is a joint project between Lawrence Berkeley National Laboratory, leading the development of the software and analysis elements, and Pacific Northwest National Laboratory (PNNL), leading the development of the hardware and sensor elements with an associated table-based configuration support tool. The project is funded by the U.S. Department of Energy. This software package was developed as a proof-of-concept prototype for the sensor suitcase software component. The software component was developed with a Microsoft Excel spreadsheet which reads the sensor data and calls a MATLAB DLL to analyze the sensor data.

Lin, Guanjing↗

A simplified framework for prediction of sensor network coverage in real-time structural health monitoring of plate-like structures

In this article, the coverage area prediction of piezoelectric sensor network for detecting a specific type of under-surface crack in plate-like structures is addressed. In particular, this article proposes a simplified framework to estimate the coverage of any given sensor network arrangement when a critical defect is known. Based on numerical results from finite element methods (FEM), a simplified framework to estimate coverage area of any given network arrangement is developed. Using such a simplified framework, one can avoid time-consuming procedure of evaluating numerous FEM models in estimating sensor network coverage. Back-scatter fields of partial cracks are estimated using a proposed function, whose parameters are estimated from the results of a limited number of FEM simulations. The proposed function efficiently predicts the back-scattered field of any combination of transmitters and receivers for a given crack geometry. Superposition is used to estimate the coverage area of an arbitrary piezoelectric (e.g., PZT) sensor network. It is shown that the coverage area of a sensor network depends on both sensor network geometry and defect properties (e.g., crack inclination) and it is not necessarily a linear function of the number of sensors. Furthermore, it is shown that the network arrangement has an important effect on the geometry of the coverage area. Experimental results of a network of 14 PZTs in two clusters confirm the accuracy of the method.

Engineering↗

Zero-crosstalk silicon photonic refractive index sensor with subwavelength gratings

Abstract Silicon photonic index sensors have received significant attention for label-free bio and gas-sensing applications, offering cost-effective and scalable solutions. Here, we introduce an ultra-compact silicon photonic refractive index sensor that leverages zero-crosstalk singularity responses enabled by subwavelength gratings. The subwavelength gratings are precisely engineered to achieve an anisotropic perturbation-led zero-crosstalk, resulting in a single transmission dip singularity in the spectrum that is independent of device length. The sensor is optimized for the transverse magnetic mode operation, where the subwavelength gratings are arranged perpendicular to the propagation direction to support a leaky-like mode and maximize the evanescent field interaction with the analyte space. Experimental results demonstrate a high wavelength sensitivity of − 410 nm/RIU and an intensity sensitivity of 395 dB/RIU, with a compact device footprint of approximately 82.8 μm 2 . Distinct from other resonant and interferometric sensors, our approach provides an FSR-free single-dip spectral response on a small device footprint, overcoming common challenges faced by traditional sensors, such as signal/phase ambiguity, sensitivity fading, limited detection range, and the necessity for large device footprints. This makes our sensor ideal for simplified intensity interrogation. The proposed sensor holds promise for a range of on-chip refractive index sensing applications, from gas to biochemical detection, representing a significant step towards efficient and miniaturized photonic sensing solutions. Graphical Abstract

Materials Science↗

Schneider Springs Fire Study 2023 for Ecosystem Respiration Rates: Surface Water Chemistry and Hydrologic Sensor Data across the Yakima River Basin, Washington, USA (v2)

This dataset supports a broader study examining the drivers of spatial variability in wildfire impacts across the Yakima River Basin. Data provided within this dataset were generated from sample collection across 17 total sites (8 sites affected by a recent wildfire, 9 sites unaffected by a recent wildfire) within multiple rivers throughout the Yakima River Basin in Washington, USA from May-July 2023. Fire affected sites are defined as those affected by the 2021 Schneider Springs Fire, based on the drainage area of the streams being within the 2021 Schneider Springs Fire burn perimeter or not (Figure 1, below). The contents include surface water geochemistry data (dissolved organic carbon; total dissolved nitrogen; total suspended solids); short-term sonde data (specific conductivity; turbidity; pH; chlorophyll A; temperature); stream depth data; stream velocity; manual chamber open channel respiration data; sensor time-series data (oxygen; water pressure; barometric pressure); field metadata (including qualitative information on in stream and river corridor characteristics); and environmental context photos taken in the field. The dataset also includes a summary file of the sensor data and plots of the sensor data. Sensors were only recovered at 15 out of the 17 sites, and not all sensors were recovered at all 15 sites (see Methods section for more details), therefore all data does not exist at all sites. Data from a 2022 study at the same sites, as well as additional sites, can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1969566. The data package was originally published in November 2023. It was updated in June 2025 (v2; modified files). See the change history section in the readme for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of one folder with field photos and one main data folder with two subfolders. The main data folder consists of (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) field protocol; (5) readme; (6) international generic sample number (IGSN) mapping file; and (7) stream depth and averages. The sensor data subfolder consists of (1) sensor installation methods summary; (2) stream velocity; and (3) six subfolders. The BarotrollAtm (barometric pressure; temperature), DepthHOBO (water pressure; temperature), MantaRiver (specific conductivity; turbidity; pH; chlorophyll A; temperature), EXO (specific conductivity; pH; temperature), miniDOT (dissolved oxygen; temperature), and miniDOTManualChamber (dissolved oxygen; temperature) contain time-series data, plots, and summary files. The sample data subfolder consists of (1) total suspended solids (TSS) data; (2) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (3) total dissolved nitrogen (TN) data and averages; and (4) methods codes. All files are .csv, .pdf, .jpg, .jpeg, or .mov.

54 ENVIRONMENTAL SCIENCES↗

Practical procedures for sensor quality assessment

Sensors are increasingly deployed for process monitoring and control. These produce on-line measurements at a high frequency, in parallel with low-frequency laboratory measurements. Compared to laboratory practices, sensor data quality assessment and control practices are far less structured at most utilities. This leads to inaccurate sensor data with unknown uncertainty factors.This chapter shows how to establish standard operating procedures (SOPs) to support sensor data quality assessment and control and subsequent maintenance actions by producing relevant sensor metadata. Furthermore, SOPs are provided for the most commonly used wastewater quality sensors, inspired by utility and academic best practices. This chapter builds on definitions provided in Chapter 3 and provides additional definitions specifically related to sensors maintenance. Chapter 6 complements the methods in this chapter, which are based on reference measurements, with data-analytical techniques.

Alferes, Janelcy↗

Leak Detection and H2 Sensor Development for Hydrogen Applications

Recent developments in the search for sustainable and renewable energy coupled with the advancements in fuel cell powered vehicles (FCVs) have augmented the demand for hydrogen safety sensors. There are several sensor technologies that have been developed to detect hydrogen, including deployed systems to detect leaks in manned space systems and hydrogen safety sensors for laboratory and industrial usage. Among the several sensing methods electrochemical devices that utilize high temperature-based ceramic electrolytes are largely unaffected by changes in humidity and are more resilient to electrode or electrolyte poisoning. The desired sensing technique should meet a detection threshold of 1% (10,000 ppm) H 2 and response time of ≤1 min, which is a target for infrastructure and vehicular uses. Further, a review of electrochemical hydrogen sensors by Korotcenkov et.al and the report by Glass et.al suggest the need for inexpensive, low power, and compact sensors with long-term stability, minimal cross-sensitivity, and fast response. This view has been largely validated and supported by the fuel cell and hydrogen infrastructure industries by the NREL/DOE Hydrogen Sensor Workshop held on June 8, 2011. Many of the issues preventing widespread adoption of best-available hydrogen sensing technologies available today outside of cost, derive from excessive false positives and false negatives arising from signal drift and unstable sensor baseline; both of these problems necessitate the need for unacceptable frequent calibration.

08 HYDROGEN↗

Microwave Readout Techniques for Very Large Arrays of Nuclear Sensors

During this project, we transformed the use of microwave readout techniques for nuclear sensors from a speculative idea to reality. The core of the project consisted of the development of a set of microwave electronics able to generate and process large numbers of microwave tones. The tones can be used to probe a circuit containing a series of electrical resonances whose frequency locations and widths depend on the state of a network of sensors, with one sensor per resonance. The amplitude and phase of the tones emerging from the circuit are processed by the same electronics and are reduced to the sensor signals after two demodulation steps. This approach allows a large number of sensors to be interrogated using a single pair of coaxial cables. We successfully developed hardware, firmware, and software to complete a scalable implementation of these microwave control electronics and demonstrated their use in two areas. First, we showed that the electronics can be used at room temperature to read out a network of diverse sensor types relevant to safeguards or process monitoring. Second, we showed that the electronics can be used to measure large numbers of ultrasensitive cryogenic sensors such as gamma-ray microcalorimeters. In particular, we demonstrated the undegraded readout of up to 128 channels and established a path to even higher multiplexing factors. These results have transformed the prospects for gamma-ray spectrometers based on cryogenic microcalorimeter arrays by enabling spectrometers whose collecting areas and count rates can be competitive with high purity germanium but with 10x better spectral resolution.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Status Report for NEET In-Pile Sensor Irradiation Capabilities at TREAT

The recently-established in-pile sensor development project under the Nuclear Energy Enabling Technology (NEET) program is focused on the development of measurement technologies to enable acquisition of data focused on the performance, properties, and boundary conditions of nuclear fuels/materials under irradiation in nuclear reactors. These sensors can be used in steady state irradiation tests to measure parameters of interest under conditions representing normal nuclear plant operation, or in transient irradiation tests to determine specimen performance under postulated unplanned conditions. In either case, development of suitable sensor technologies must include instrument irradiations to help guide sensor material/design selection, verify instrument performance, and demonstrate deployment viability. The Transient Reactor Test facility (TREAT) while just a part of the overall capabilities portfolio needed to enable this sensor development mission, has unique capabilities and characteristics that make it well poised for a number of instrument irradiation data objectives including sensor survivability screening, response characterization, qualification tests, and in-situ properties measurements. TREAT’s brilliantly-basic design, when married with appropriate irradiation hardware and analytic capabilities, fills a crucial capability gap between out-of-pile testing and irradiation in steady state high power research reactors. Leveraging a recently developed approach to irradiation testing in TREAT, the present work demonstrates that cost-effective and scientifically-impactful instrument irradiation capabilities for TREAT are a well-placed capability in the NEET in-pile sensor development project.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Embedment of sensors in ceramic structures

Ceramic materials such as silicon carbide (SiC) are attractive for many nuclear applications due to their ability to withstand high temperatures, which inherently improve the thermal efficiency of the power conversion cycle and can in some cases provide high-temperature process heat. SiC is particularly attractive because of its high-temperature strength retention, stability under neutron irradiation, and low neutron absorption. The TCR program has recently demonstrated the ability to fabricate monolithic SiC components with complex geometries using a binder jet additive manufacturing technique followed by densification using chemical vapor infiltration (CVI). This technology presents an opportunity to embed sensors within ceramic components at critical locations that allow for enhanced process monitoring and control of advanced nuclear energy systems. The challenges with embedding sensors in ceramic components are to identify appropriate materials that can survive the CVI process, remain embedded after cooling to room temperature, and be suitable for operation in a high-temperature nuclear environment. This report summarizes the sensors that are being considered for embedding within ceramics, the sensor embedding process, material compatibility studies, and characterization of the embedded components. Material selection is first guided by computational thermodynamics and is confirmed by embedding coupons and examining material interactions using electron microscopy. This work shows that a wide range of refractory metals, as well as certain fiber optic sensors, can be successfully embedded in 3D-printed SiC. Future work will involve testing of functional sensors including thermocouples and optical fiber-based, spatially distributed temperature/strain sensors.

36 MATERIALS SCIENCE↗

Market Survey of Airborne Small Unmanned Aircraft System Sensors February 2020

Sensors continue to decrease in size and power. This report presents results of a market survey conducted in February 2020 for commercial off-the-self sensors with optimal size, weight, and power to be carried onboard a small unmanned aircraft system. For this report, Sandia National Laboratories considered sensors that can detect an object in three dimensions. The sensors that were researched are broken into three categories: radio detection and ranging sensors, stereo camera sensors, and light detection and ranging sensors.

47 OTHER INSTRUMENTATION↗

Sensor Impacts Evaluation and Verification: Expert Interview Responses

The sensor configuration/deployment method has critical impacts on energy efficient building control and thermal comfort. However, traditional sensor techniques for building operation and fault detection and diagnostics (FDD) are not necessarily optimal in terms of energy efficiency and thermal comfort, and their global effects are not thoroughly investigated. In an effort to address and overcome this limitation, a multilaboratory and multiyear project, “Sensor Impact Evaluation and Verification,” was proposed. Its purpose is to develop a framework to investigate the impacts of sensor deployment and configuration on building energy optimization, FDD, occupant thermal comfort, and potentially grid efficiency. The first project task was a literature review to establish a solid knowledge of and a background related to sensor technologies and placement. To accomplish this task, an extensive review of previous research literature was performed. A series of expert interviews were conducted to augment the findings of the literature review. This report summarizes the interview design and interview results and findings. The interview was designed and performed to (1) investigate the current status and limitations of sensor configuration, (2) identify the research gaps and expectations for potential improvements in sensor configuration and deployment, and (3) integrate expert (e.g., researcher, building operation practitioner) knowledge and experience to develop use-case scenarios.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Multi-Functional Distributed Fiber Sensors for Pipeline Monitoring and Methane Detections. Final Report

As an abundant and cheap fossil energy source, natural gas has become a significant energy supply to support the United States’ economy. However, the large-scale extraction and utilization of natural gas also impose significant challenges on methane leakage. This problem is exacerbated by aging gas utility delivery systems, including interstate high-pressure pipelines, storage, and transmission facilities. This project aims to develop a cost-effective fiber optical sensing method that can perform multi-parameter real-time measurements of natural gas pipelines across long interrogation distances up to 100 km with 1-meter spatial resolution. This sensing tool can evaluate overall pipeline efficiency and reduce methane emissions for mid-stream methane infrastructures. To accomplish this objective, research and development efforts funded by this project have resulted in the following accomplishments: This project successfully has developed new functional sensory polymer materials using Metal-Organic Frameworks (MOFs) that can be coated on optical fiber through the reel-to-reel coating process. Functional polymer-coated optical fibers can perform sensitive methane detection through evanescence wave interaction and strain-based measurements to achieve 1% detection sensitivities. The new sensors fibers support both distributed measurements and multiplexed fiber sensors array for multi-point measurements. This project developed and optimized a new multi-core optical fiber that supports simultaneous and distributed measurements of strain and temperatures with 1-meter spatial resolutions across up to 100-km interrogation distance. This new fiber, combined with sensory polymercoated fiber, could perform both distributed temperature and methane detections. This project developed a new artificial intelligence big data algorithm approach that can effectively analyze high-resolution data harnessed by distributed fiber sensors to protect natural gas pipelines against external threats and detect internal defects induced by corrosion. Working with our industry partner, this project developed new optical fibers that support fiber sensor fabrications through polymer coating after the fibers are drawn. These new fibers eliminate the need for direct sensor fabrication when the fiber is fabricated on a fiber draw tower, which drastically expands fiber sensors' applicability. This research project has significantly advanced the distributed fiber sensing technology. It will dramatically increase the applicability and adaptability of distributed fiber sensors for a wide array of applications in energy, sustainability, and environmental science, including structural health monitoring of natural gas pipelines, oil infrastructures, hydrogen facilities, and environmental monitoring of carbon storage sites, water supply systems, and others.

03 NATURAL GAS↗