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At least 127 records · Page 7

High-Frequency 3D Photoacoustic Computed Tomography Using an Optical Microring Resonator

3D photoacoustic computed tomography (3D-PACT) has made great advances in volumetric imaging of biological tissues, with high spatial-temporal resolutions and large penetration depth. The development of 3D-PACT requires high-performance acoustic sensors with a small size, large detection bandwidth, and high sensitivity. In this work, we present a new high-frequency 3D-PACT system that uses a microring resonator (MRR) as the acoustic sensor. The MRR sensor has a size of 80 μ m in diameter and was fabricated using the nanoimprint lithography technology. Using the MRR sensor, we have developed a transmission-mode 3D-PACT system that has achieved a detection bandwidth of ~23 MHz, an imaging depth of ~8 mm, a lateral resolution of 114 μ m, and an axial resolution of 57 μ m. We have demonstrated the 3D PACT’s performance on in vitro phantoms, ex vivo mouse brain, and in vivo mouse ear and tadpole. The MRR-based 3D-PACT system can be a promising tool for structural, functional, and molecular imaging of biological tissues at depths.

47 OTHER INSTRUMENTATION↗

Performance Demonstration of an Occupancy Sensor-enabled Integrated Solution for Commercial Buildings

Traditionally, a single-loop fixed-gain controller is applied to supply fan (SF) and cooling coil (CC) valve controls while a fixed-damper position control is applied to outdoor air (OA) damper control at air handling units (AHUs) in commercial buildings. With the increasing application of occupancy sensors, the information generated by occupancy sensors is applied to not only reduce the electricity loads from lighting and controllable plug loads, but also reset OA intake and minimum supply airflow setpoints. Meanwhile, these intermittent operation actions greatly elevate the dynamics of AHU systems, which may introduce unstable SF and CC valve operations and inaccurate OA flow control at AHUs and consequently degrade maximum energy efficiency gains. With virtual fan and valve flow meter technologies, two advanced controls, including cascade control and gain scheduling control, can be implemented on both the SF and CC valve, and an advanced control using a virtual OA flow meter can be implemented on OA damper integrated with occupancy sensors. The goal of this project is to demonstrate the savings, cost, and performance of an integrated solution that integrates the three advanced HVAC controls with occupancy sensors to allow accurate and stable AHU operations in real buildings. The project objectives are to: 1) develop and validate an advance SF control algorithm; 2) develop and validate an advanced CC valve control algorithm; 3) validate an algorithm to implement a virtual OA flow meter; and 4) demonstrate the savings, cost, and performance of the integrated solution in real buildings. The technical approaches are to: 1) select a test system at the University of Oklahoma; 2) develop and implement the algorithms of advanced SF and CC valve controls and validate the performance; 3) develop and implement the advanced OA control using a virtual OA flow meter and validate the performance; 4) demonstrate the savings, cost, and performance of the proposed integrated solution with and without three advanced HVAC controls; and 5) disseminate the project results through publications and presentations. For the SF control, both the gain scheduling and cascade controls can improve the fan energy performance by reducing the fan power during the transient period and the fan control performance at lower speeds by reducing fan speed variation. Moreover, the gain scheduling control provides a simple and low-cost solution and is recommended. The fan power savings can reach 30% in a transient period. For the CC valve control, the gain scheduling control can considerably reduce the supply air temperature oscillation range and frequency under both higher and lower load conditions and the control valve response is much more stable. As a result, the gain scheduling control is recommended. The projected pump energy consumption can be reduced by 68.5%. With the developed virtual OA flow meter, the OA can be accurately controlled at its setpoint, which is determined based on the actual number of occupants in the building provided by occupancy sensors. The RMSE of the proposed OA control is 15.9 L/s. The energy data shows that the fan power and CC cooling energy were significantly reduced. On the other hand, the energy savings majorly results from the occupancy sensors and the energy savings by the advanced HVAC controls is minimal because that the controllers in the test AHU were tuned with very slow response. An annual technical savings potential is estimated as 0.5 quads in the commercial sector.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Probing the role of CNTs in Pt nanoparticle/CNT/graphene nanohybrids H 2 sensors

Abstract In the carbon nanotubes film/graphene heterostructure decorated with catalytic Pt nanoparticles using atomic layer deposition (Pt-NPs/CNTs/Gr) H 2 sensors, the CNT film determines the effective sensing area and the signal transport to Gr channel. The former requires a large CNT aspect ratio for a higher sensing area while the latter demands high electric conductivity for efficient charge transport. Considering the CNT’s aspect ratio decreases, while its conductivity increases ( i.e. , bandgap decreases), with the CNT diameter, it is important to understand how quantitatively these effects impact the performance of the Pt-NPs/CNTs/Gr nanohybrids sensors. Motivated by this, this work presents a systematic study of the Pt-NPs/CNTs/Gr H 2 sensor performance with the CNT films made from different constituent CNTs of diameters ranging from 1 nm for single-wall CNTs, to 2 nm for double-wall CNTs, and to 10–30 nm for multi-wall CNTs (MWCNTs). By measuring the morphology and electric conductivity of SWCNT, DWCNT and MWCNT films, this work aims to reveal the quantitative correlation between the sensor performance and relevant CNT properties. Interestingly, the best performance is obtained on Pt-NPs/MWCNTs/Gr H 2 sensors, which can be attributed to the compromise of the effective sensing area and electric conductivity on MWCNT films and illustrates the importance of optimizing sensor design.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Glass Additive and Subtractive Manufacturing of a Fiber Optic Rotary Encoder for Downhole Pressure Sensing

This article presents a fiber optic rotary encoder-based pressure sensor for downhole applications. The rotary encoder, which is composed of an encoding pad and an all-glass optical fiber sensing head, converts the rotation angles of a pressure transducer to digital codes. The optical fiber only serves as the telemetry channel to directly transmit the data in digital format such that the environmental temperature influence and the long-time drift are minimized. The glass additive and subtractive manufacturing (ASM) techniques are used to embed the multichannel optical fibers into a bulk-fused silica glass substrate. Because the fused silica glass shares a similar material property to the optical fiber (e.g., thermal expansion coefficient), the optical fiber sensing head is well sealed and fixed even at an elevated temperature. The picosecond laser blackening technique is used to fabricate the high reflectivity contrast encoding pad with high accuracy. Here, the proposed pressure sensor was manufactured and experimentally verified to have a signal-to-noise ratio (SNR) of 23 dB and a linear pressure response with a root-mean-square error (RMSE) of 0.37. During the 400-h 250 °C long-term stability test, there was no digital code variation. In addition, a mathematical model to study the relationships between the sensor’s performances and design parameters was established. According to the model, a 12-bit encoder (0.02% pressure sensitivity) can be achieved with a radius of 20 mm.

02 PETROLEUM↗

Forming more and sharper sensing protrusions on graphene-based electrodes through annealing

A better understanding of the microstructure, physicochemical properties, and sensing behavior of an electrode is critical in developing quick, high sensitivity, and robust electrochemical sensors. Here, in this study, a single electrode was fabricated with self-prepared graphene ink through a drop-cast process followed with a subsequent annealing treatment. The graphene ink-based electrodes were characterized through AFM, contact angle, FTIR, impedance spectra, Raman, and SEM to understand annealing treatment effects. The dynamic response of the electrode to humidity, and vapors of ethanol, propanol, or acetone was measured using a four-point probe station in a closed chamber. The annealing treatment increased the conductivity of the electrode and improved its sensing performance by forming more and sharper protrusions on the electrode surface. These unique surface protrusions suggest that the annealed graphene ink-based electrodes hold great potential in developing high-performance electrochemical sensors.

42 ENGINEERING↗

Overview of Quantum Sensing Materials and Techniques for Energy Sector Applications

The energy sector has become increasingly dependent upon highly sensitive sensing devices for a wide range of applications. Variables such as temperature, pH, electromagnetic fields, ions, and pressure must be measured with high precision, often in harsh conditions (e.g. highly corrosive environments due to high temperature, pressure and humidity). These sensors are deployed in infrastructure such as transformers, pipelines, mines, nuclear power plants, and other areas to ensure safe operating conditions and uninterrupted, optimized service. Moreover, new opportunities for sensors have emerged due to the expansion of smart grids/meters, driverless vehicles, and the discovery of new oil, gas, and critical mineral deposits. The continued maturation of quantum sensing technologies offers exciting opportunities for quantum-enhanced measurements within the energy sector that may provide significant improvements in sensitivity beyond the classical limit. Here, an overview of established and emerging quantum materials for sensing applications will be provided, from trapped ions to color centers in diamond and silicon carbide. Associated quantum sensing methods for these materials will be discussed, with an emphasis on platforms that are nearing commercial viability. Specific application opportunities within the energy sector for quantum sensors will then be analyzed, including oil/gas discovery, greenhouse gas emission monitoring, pH and ion sensing, current measurement in electric vehicle batteries, and quantum-enhanced spectroscopy. Remaining barriers, such as quantum sensor platform miniaturization and ruggedization, will also be analyzed. A specific project at the National Energy Technology Laboratory involving the functionalization of qubits using metal-organic frameworks for enhanced quantum sensing will also be highlighted. Here, nitrogen vacancy centers (NV) in nanodiamonds, a commercially available qubit with long coherence times and utilizable quantum properties at room temperature, are encapsulated in a controlled way using the metal-organic framework ZIF-8. The ZIF-8 provides a well-defined, porous scaffold that can be controlled to promote the selective uptake of specific target analytes, such as gas molecules or ions. The quantum sensing performance of this composite material is either preserved or enhanced following ZIF-8 encapsulation; the optically detected magnetic resonance response of the NV nanodiamonds with and without the ZIF-8 coating are identical, while the ZIF-8 coating increases the longitudinal spin relaxation lifetime (T1) of the NV centers, an important parameter for spin relaxometry-based quantum sensing experiments. Taken together, these results demonstrate the importance of qubit functionalization as a crucial step for rationally designing high performance quantum sensors.

Crawford, Scott↗

Overview of Quantum Sensing Materials and Techniques for Energy Sector Applications

The energy sector is dependent upon highly sensitive sensing devices for a wide range of applications. Variables such as temperature, pH, electromagnetic fields, and pressure must be measured with high precision, often in harsh conditions (e.g. high temperature, pressure and humidity). These sensors are deployed in infrastructure such as transformers, pipelines, mines, nuclear power plants, and other areas to ensure safe operating conditions and uninterrupted, optimized service. Moreover, new opportunities for sensors have emerged due to the expansion of smart grids/meters, driverless vehicles, and the discovery of new oil/gas deposits. The continued maturation of quantum sensors offers exciting opportunities for quantum-enhanced measurements to improve sensitivity beyond the classical limit. Here, an overview of established and emerging quantum materials and methods for sensing applications will be provided. Opportunities within the energy sector for quantum sensors will then be analyzed, including oil/gas discovery, greenhouse gas emission monitoring, pH and ion sensing, current measurements, and quantum-enhanced spectroscopy, along with barriers such as quantum sensor platform miniaturization and ruggedization. A specific project at the National Energy Technology Laboratory involving the functionalization of qubits using metal-organic frameworks for enhanced quantum sensing will then be highlighted. Here, nitrogen vacancy centers (NV) in nanodiamonds, a commercially available qubit with long coherence times and utilizable quantum properties at room temperature, are encapsulated using the metal-organic framework ZIF-8. Significantly, the ZIF-8 coating increases the longitudinal spin relaxation lifetime of the NV centers, an important parameter for spin relaxometry-based quantum sensing experiments. These results demonstrate the importance of qubit functionalization as a crucial step for rationally designing high performance quantum sensors.

Crawford, Scott↗

Real-Time Distribution System State Estimation with Asynchronous Measurements

We report state estimation is a fundamental task in power systems. Although distribution systems are increasingly equipped with sensing devices and smart meters, measurements are typically reported at different rates and asynchronously; these aspects pose severe strains on workhorse state estimation algorithms, which are designed to process batches of data collected in a synchronous manner from all the measurement units. In this paper, we develop a novel state estimation algorithm to continuously update the estimate of the state based on measurements received in an asynchronous manner from measurement units. The synthesis of the algorithm hinges on a proximal-point type method, implemented in an online fashion, and capable of processing measurements received sequentially from sensors. A performance analysis is presented by providing bounds on the estimation error in terms of the mean and variance that hold at each iteration and asymptotically. The scheme is also compared with a more traditional Weighted Least Squares estimator that compensates for the lack of measurement data by using, as pseudo measurements, the measurement retrieved during a certain time window. Numerical simulations on the IEEE 37-bus feeder corroborate the analytical findings.

24 POWER TRANSMISSION AND DISTRIBUTION↗

High Fluence Active Irradiation and Combined Effects Testing of Sapphire Optical Fiber Distributed Temperature Sensors

Investigate the in-pile performance of sapphire optical fiber temperature sensors and to develop clad sapphire optical fibers for in-pile instrumentation. Evaluate the distributed sensing performance of the sensors through optical backscatter reflectometry under combined radiation and temperature effects, and high fluence.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Studying phonon coherence with a quantum sensor

Nanomechanical oscillators offer numerous advantages for quantum technologies. Their integration with superconducting qubits shows promise for hardware-efficient quantum error-correction protocols involving superpositions of mechanical coherent states. Limitations of this approach include mechanical decoherence processes, particularly two-level system (TLS) defects, which have been widely studied using classical fields and detectors. In this manuscript, we use a superconducting qubit as a quantum sensor to perform phonon number-resolved measurements on a piezoelectrically coupled phononic crystal cavity. This enables a high-resolution study of mechanical dissipation and dephasing in coherent states of variable size ($\overline{n}$ ≃ 1 – 10 phonons). We observe nonexponential relaxation and state size-dependent reduction of the dephasing rate, which we attribute to TLS. Using a numerical model, we reproduce the dissipation signatures (and to a lesser extent, the dephasing signatures) via emission into a small ensemble (N = 5) of rapidly dephasing TLS. Our findings comprise a detailed examination of TLS-induced phonon decoherence in the quantum regime.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Sequential Perturbation-based FDIA Detection using DERs for Unbalanced Distribution System

The power distribution system with its reliance on automated monitoring and control infrastructure makes it a complicated cyber-physical system and vulnerable to various cyber-attacks. This paper proposes a moving target defense inspired false data injection attack (FDIA) detection mechanism for an unbalanced distribution system. In the proposed grid diagnosis service framework, the distribution system operator judiciously manipulates power outputs of a subset of inverter-based distribution energy resources (DERs) to create secret low magnitude voltage perturbations which are inconsequential to the normal operation of the grid. A mixed-integer-linear-programming algorithm is developed to select the optimal set of DERs that can create a voltage perturbation signal of the required magnitude at each sensor location at a minimum cost. Then, a sequential detector is applied that detects for the FDIA as measurements are received from individual sensors. The performance of the proposed perturbation-based FDIA detection framework is demonstrated via simulation of the IEEE 123 bus test system.

Attack Detection↗

Massively distributed fiber strain sensing using Brillouin lasing

Brillouin based distributed fiber sensors present a unique set of characteristics amongst fiber sensing architectures. They are able to measure absolute strain and temperature over long distances, with high spatial resolution, and very large dynamic range in off-the-shelf fiber. However, Brillouin sensors traditionally provide only modest sensitivity due to the weak dependence of the Brillouin frequency on strain and the high signal to noise ratio required to identify the resonance’s peak frequency to within a small fraction of its linewidth. Recently, we introduced a technique which substantially improves the precision of Brillouin fiber sensors by exciting a series of lasing modes in a fiber loop cavity that experience Brillouin amplification at discrete locations in the fiber. The narrow-linewidth and high intensity of the lasing modes enabled ultra-low noise Brillouin sensors with large dynamic range. However, our initial demonstration was only modestly distributed: measuring strain at 40, non-contiguous positions along a 400 m fiber. In this work, we greatly extend this methodology to enable fully distributed sensing at 1000 contiguous locations along 3.5 km of fiber—an order of magnitude increase in sensor count and range. This highly-multiplexed Brillouin fiber laser sensor provides a strain noise as low as 34 nɛ/√Hz and we analyze the limiting factors in this approach.

47 OTHER INSTRUMENTATION↗

Spectrometer-free quantitative vapor sensing and classification via spatiotemporal imaging of porous silicon metasurfaces

Metasurfaces offer a compact platform for optical vapor sensing, but their practical deployment has been limited by weak evanescent light–matter interactions and reliance on spectrally resolved instrumentation. Here, we report porous silicon (pSi) metasurfaces for spectrometer-free quantitative detection of volatile organic compounds (VOCs) with strongly enhanced light–matter interaction. The engineered porosity increases sensitivity by >100× relative to non-porous dielectric metasurfaces, enabling limits of detection of 1.65 ppm for methanol and 9.1 ppm for ethanol across a broad dynamic range (<10 ppm to >103 ppm). Imaging-based readout provides a lightweight, spectrometer-free pathway for real-time quantitative sensing. Beyond quantitative detection, the mesoporous architecture introduces adsorption–desorption kinetics as an additional information channel. Analysis of the resulting spatiotemporal signatures enables kinetic fingerprinting without reliance on infrared spectral features or surface functionalization, and a lightweight machine-learning classifier differentiates acetone, methanol, ethanol, and isopropanol with 91.6% accuracy. These results establish porous metasurfaces as spatiotemporal sensing elements that couple quantitative vapor detection with kinetic fingerprinting through real-time dynamical responses, enabling low-cost, high-performance optical sensors.

Dash, Tomoshree [Clemson University]↗

Super-resolution demodulation for fiber sensor arrays based on the MUSIC algorithm

This paper studies the use of MUltiple SIgnal Classification (MUSIC) as a super-resolution algorithm to improve demodulation results for intrinsic Fabry–Perot interferometer (IFPI) sensor arrays. Through distinction between noise and signal subspaces in an observation matrix, this paper shows that a 38-fold improvement in the full width at half maximum (FWHM) estimation of IFPI optical path differences (OPD) can be achieved using this algorithm. Based on this improved method, this paper demonstrates that a tunable laser with a 1.3-nm tuning range can achieve the same sensor demodulation performance as a tunable laser with a 50-nm tuning range if a conventional Fourier transform-based algorithm is used. This paper presents a new approach to analyzing optical signals produced by multiple multiplexed interferometers with similar OPDs with potential applications for both single-mode and multiple-mode devices.

Li, Yuqi (ORCID:0000000291643663)↗

A Graphics Processing Unit (GPU) Approach to Large Eddy Simulation (LES) for Transport and Contaminant Dispersion

Recent advances in the development of large eddy simulation (LES) atmospheric models with corresponding atmospheric transport and dispersion (AT&D) modeling capabilities have made it possible to simulate short, time-averaged, single realizations of pollutant dispersion at the spatial and temporal resolution necessary for common atmospheric dispersion needs, such as designing air sampling networks, assessing pollutant sensor system performance, and characterizing the impact of airborne materials on human health. The high computational burden required to form an ensemble of single-realization dispersion solutions using an LES and coupled AT&D model has, until recently, limited its use to a few proof-of-concept studies. An example of an LES model that can meet the temporal and spatial resolution and computational requirements of these applications is the joint outdoor-indoor urban large eddy simulation (JOULES). A key enabling element within JOULES is the computationally efficient graphics processing unit (GPU)-based LES, which is on the order of 150 times faster than if the LES contaminant dispersion simulations were executed on a central processing unit (CPU) computing platform. JOULES is capable of resolving the turbulence components at a suitable scale for both open terrain and urban landscapes, e.g., owing to varying environmental conditions and a diverse building topology. In this paper, we describe the JOULES modeling system, prior efforts to validate the accuracy of its meteorological simulations, and current results from an evaluation that uses ensembles of dispersion solutions for unstable, neutral, and stable static stability conditions in an open terrain environment.

54 ENVIRONMENTAL SCIENCES↗