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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Estimating biofuel contaminant concentration from 4D ERT with mixing models

Here, we present the results of a lab-scaled feasibility study to assess the performance of electrical resistivity tomography for detection, characterization, and monitoring of fuel grade ethanol releases to the subsurface. Further, we attempt to determine the concentration distribution of the ethanol from the electrical resistivity tomography data using mixing-models. Ethanol is a renewable fuel source as well as an oxygenate fuel additive currently used to replace the known carcinogen methyl tert-butyl ether; however, ethanol is preferentially biodegraded and a cosolvent. When introduced to areas previously impacted by nonethanol-based fuels, it will facilitate the persistence of carcinogenic fuel compounds like benzene and ethylbenzene, as well as remobilize them to the ground water. These compounds would otherwise be retained in the soil column undergoing active or passive remediation processes such as soil vapor extraction or natural attenuation. Here, we introduce ethanol to a saturated Ottawa sand in a tank instrumented for four-dimensional geoelectrical measurements. Forward model results suggest pure phase ethanol released into a water saturated silica sand should present a detectable target for electrical resistivity tomography relative to a saturated silica sand only. We observe the introduction of ethanol to the closed hydraulic system and subsequent migration over the duration of the experiment. One-dimensional and three–dimensional temporal data are assessed for the detection, characterization, and monitoring of the ethanol release. Results suggest one-dimensional geoelectrical measurements may be useful for monitoring a release, while three-dimensional geoelectrical field imaging would be useful to characterize, monitor, and design effective remediation approaches for an ethanol release, assuming field conditions do not preclude the application of geoelectrical methods. We then attempt to use predictive mixing models to calculate the distribution of ethanol concentration within the measurement domain. For this study we examine four different models: a nested parallel mixing model, a nested cubic mixing model, the complex refractive index model (CRIM), and the Lichtenecker-Rother (L-R) model. The L-R model, modified to include an electrical formation factor geometry term, provided the best agreement with expected EtOH concentrations.

09 BIOMASS FUELS↗
DOE OSTI2020

Dielectrophoresis assisted rapid, selective and single cell detection of antibiotic resistant bacteria with G-FETs

Time-consuming, expensive and low sensitivity diagnostic methods used for monitoring bacterial infections lead to unnecessary or delays in prescription of the right antibiotic treatment. Determining an optimal clinical treatment requires rapid detection and identification of pathogenic bacteria and their sensitivity to specific antimicrobials. However, diagnostic devices that meet all of these criteria have proven elusive thus far. Graphene field effect transistors (G-FET) are a promising solution, since they are highly sensitive to chemical/biological modification, can have fast detection times and can be placed on different substrates. Here, by integrating specific peptide probes over G-FETs, we present a proof-of-concept study for species and strain specific label-free detection of clinical strains of pathogenic bacteria with high specificity and sensitivity. We found that pyrene-conjugated peptides immobilized on G-FETs were capable of detecting pathogenic Staphylococcus aureus at the single-cell level and discriminate against other gram-positive and gram-negative bacterial pathogens. A similar device was able to discriminate between antibiotic resistant and sensitive strains of Acinetobacter baumannii , suggesting that these devices can also be used for detecting antibiotic resistive pathogens. Furthermore, a new means of enhancing attachment, electric-field assisted binding, reduced the detection limit to 104 cells/ml and the detection time to below 5 minutes. Here, the combination of single step attachment, inexpensive production, rapid, selective and sensitive detection suggest G-FETs plus pyrene-conjugated peptides are a new platform for solving major challenges faced in point of care diagnostics to fight infectious diseases and antimicrobial resistance.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

3D modeling of deep borehole electromagnetic measurements with energized casing source for fracture mapping at the Utah Frontier Observatory for Research in Geothermal Energy

Here, we present a 3D numerical modelling analysis evaluating the deployment of a borehole electromagnetic measurement tool to detect and image a stimulated zone at the Utah Frontier Observatory for Research in Geothermal Energy geothermal site. As the depth to the geothermal reservoir is several kilometres and the size of the stimulated zone is limited to several 100 m, surface-based controlled-source electromagnetic measurements lack the sensitivity for detecting changes in electrical resistivity caused by the stimulation. To overcome the limitation, the study evaluates the feasibility of using a three-component borehole magnetic receiver system at the Frontier Observatory for Research in Geothermal Energy site. To provide sufficient currents inside and around the enhanced geothermal reservoir, we use an injection well as an energized casing source. To efficiently simulate energizing the injection well in a realistic 3D resistivity model, we introduce a novel modelling workflow that leverages the strengths of both 3D cylindrical-mesh-based electromagnetic modelling code and 3D tetrahedral-mesh-based electromagnetic modelling code. The former is particularly well-suited for modelling hollow cylindrical objects like casings, whereas the latter excels at representing more complex 3D geological structures. In this workflow, our initial step involves computing current densities along a vertical steel-cased well using a 3D cylindrical electromagnetic modelling code. Subsequently, we distribute a series of equivalent current sources along the well's trajectory within a complex 3D resistivity model. We then discretize this model using a tetrahedral mesh and simulate the borehole electromagnetic responses excited by the casing source using a 3D finite-element electromagnetic code. This multi-step approach enables us to simulate 3D casing source electromagnetic responses within a complex 3D resistivity model, without the need for explicit discretization of the well using an excessive number of fine cells. We discuss the applicability and limitations of this proposed workflow within an electromagnetic modelling scenario where an energized well is deviated, such as at the Frontier Observatory for Research in Geothermal Energy site. Using the workflow, we demonstrate that the combined use of the energized casing source and the borehole electromagnetic receiver system offer measurable magnetic field amplitudes and sensitivity to the deep localized stimulated zone. The measurements can also distinguish between parallel-fracture anisotropic reservoirs and isotropic cases, providing valuable insights into the fracture system of the stimulated zone. Besides the magnetic field measurements, vertical electric field measurements in the open well sections are also highly sensitive to the stimulated zone and can be used as additional data for detecting and imaging the target. We can also acquire additional multiple-source data by grounding the surface electrode at various locations and repeating borehole electromagnetic measurements. This approach can increase the number of monitoring data by several factors, providing a more comprehensive dataset for analysing the deep-localized stimulated zone. The numerical analysis indicates that it is feasible to use the combination of the energized casing and downhole electromagnetic measurements in monitoring localized stimulated zone at large depths.

58 GEOSCIENCES↗
DOE OSTI2021

Fault Detection Utilizing Convolution Neural Network on Timeseries Synchrophasor Data From Phasor Measurement Units

An end-to-end supervised learning method is proposed for fault detection in the electric grid using Big Data from multiple Phasor Measurement Units (PMUs). The approach consists of preprocessing steps aimed at reducing data noise and dimensionality, followed by utilization of six classification models considered for detecting faults. Three of the models were variants of Convolutional Neural Network (CNN) architectures that consider a single type of measurement (voltage, current or frequency) at all PMUs or all types together also at all PMUs. CNN based models were compared to traditional methods of Logistic Regression (LR), Multi-layer Perceptron (MLP) and Support Vector Machine (SVM). Evaluation was conducted on two-year data measured by PMUs at 37 locations in a large electric grid. Here, the response variable for classification were extracted from the grid-wide outage event log. Experiments show that CNN-based models outperformed traditional methods on one year out-of-sample outage detection over the entire grid.

42 ENGINEERING↗
DOE OSTI2023

Radioimaging for real-time tracking of high-voltage breakdown

An interferometric radioimager provides real-time, high-fidelity radioimaging of high voltage breakdown (HVB) both internal and external to electrical components at sub-nanosecond and sub-millimeter resolution and has an ability to resolve multiple/spatially-extensive HVB simultaneously. Therefore, radioimaging can be used to screen for early life weakness/failure and enable non-destructive screening of defective electrical components. In particular, radioimaging can detect precursors to catastrophic HVB, allowing for early detection of weakness in critical electrical components. Radioimaging can also be used to track HVB and pinpoint defects in electrical components real time, including transformers, capacitors, cables, switches, and microelectronics.

Tilles, Julia Napolin↗
DOE OSTI2020

Crystal orientation dependence of interfacial magnetic anisotropy at heavy-metal/magnetic-garnet interfaces

Ferrimagnetic insulators capped with a heavy metal are becoming an increasingly interesting materials system in spintronics due to their unique ability for electrical manipulation and detection of magnetic states and spin textures via spin-orbit torques. The ability to engineer magnetic anisotropy is a powerful tool for tuning the recently discovered phenomena in these bilayers such as electrical switching or the stabilization of topological magnetic textures. Here, we observe large shifts in the magnetic anisotropy in Tm 3 Fe 5 O 13 and Y 3 Fe 5 O 12 thin films due to heavy-metal capping layers, which strongly depends on the orientation of the substrate and therefore the orientation of the epitaxial films. This work suggests large Rashba spin-orbit coupling at the metal/ferrimagneticinsulator interface, which can be engineered in spintronic devices that utilize spin-orbit torques for electrical control of the magnetization in magnetic insulators.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Quantum-enhanced sensing of displacements and electric fields with two-dimensional trapped-ion crystals

Fully controllable ultracold atomic systems are creating opportunities for quantum sensing, yet demonstrating a quantum advantage in useful applications by harnessing entanglement remains a challenging task. Here, we realize a many-body quantum-enhanced sensor to detect displacements and electric fields using a crystal of ~150 trapped ions. The center-of-mass vibrational mode of the crystal serves as a high- Q mechanical oscillator, and the collective electronic spin serves as the measurement device. By entangling the oscillator and collective spin and controlling the coherent dynamics via a many-body echo, a displacement is mapped into a spin rotation while avoiding quantum back-action and thermal noise. We achieve a sensitivity to displacements of 8.8 ± 0.4 decibels below the standard quantum limit and a sensitivity for measuring electric fields of 240 ± 10 nanovolts per meter in 1 second. Feasible improvements should enable the use of trapped ions in searches for dark matter.

Gilmore, Kevin A.↗
DOE OSTI2026

Electrical Switching and Imaging of Antiferromagnetic Spins in Perovskite Epitaxial Thin Films

Electrical control of antiferromagnets is essential for the field of antiferromagnetic spintronics that promises ultrafast speed and terahertz dynamics. However, the large family of complex oxide antiferromagnets such as perovskites have been largely unexplored. Here, we demonstrate electrical switching and detection of Néel vector in LaFeO 3 epitaxial thin films with an epitaxy-enabled biaxial anisotropy, of which the switching behavior is understood by comparing to magnetic field controlled spin Hall magnetoresistance measurements. The electrical switching is corroborated by imaging of antiferromagnetic domains using X-ray Magnetic Linear Dichroism Photoemission Electron Microscopy. Electrical switching of 3-nm and 10-nm LaFeO 3 films was achieved over a wide temperature range of 25 to 300 K. This work offers an attractive platform for exploration of antiferromagnetic spintronics and other emerging phenomena such as potential insulating altermagnetism.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Homomorphic Encryption for Electrical Metering Aggregation: Protecting the Privacy of Building Tenants

Electrical meters are devices that measure consumer electricity usage. The data collected by these meters is necessary for utility billing and electrical grid management but can also be used to assess the environmental impact of buildings. Prior research has found that unprotected metering data could potentially be used to infer some information about the behaviors of building tenants by detecting changes in electricity usage. For example, a period of low electricity usage could suggest that the tenants are not in the building. As smart metering becomes more common, there is a growing need for data privacy protections for metering data that do not negatively impact the quality and availability of data used for energy management and billing applications. To identify potential solutions, we developed a Python-based data aggregation platform to analyze the potential efficacy of privacy-enhancing technologies for energy metering applications. This platform aggregates groups of metering sites into virtual buildings, which could potentially detach changes in electrical activity from individual tenants, making it more difficult to track the activity of a specific tenant. To further protect data during analysis, this project utilizes homomorphic encryption as part of its initial approach. Homomorphic encryption offers a means of protecting energy consumption data while permitting mathematical operations to be performed without the need to know the data contents. This allows for data to be processed into usable statistics without revealing energy consumption information. A series of homomorphic encryption libraries were evaluated to determine their applicability and limitations in the context of metering data. The use of these techniques may help to reassure consumers and encourage further adoption of smart grid infrastructure.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Exceptional NH 3 Detection by Cu(cyhdc) MOF Sensor Due to H 2 O Coadsorption

Metal–organic framework (MOF)-based electrical impedance sensors are a growing class of sensors that show utility in the detection of environmentally toxic gases. Detection of trace NH 3 has been particularly difficult to design due to the low electrical response of NH 3 . However, this has been circumvented by judiciously selecting a MOF that has enhanced electrical response to NH 3 due to coadsorption with predominant atmospheric gases such as water. Herein, an MOF Cu(cyhdc) based sensor has been successfully demonstrated for the enhanced detection of environmentally toxic NH 3 gas. The sensor shows a change in impedance when it is exposed to 5 ppm of NH 3 . At 20 °C, >30% relative humidity (RH) is necessary to elicit a change, with the response increasing with RH and reaching 3170× at 92% RH, producing the largest published response to NH 3 for a MOF direct electrical sensor. In the absence of water, no change is observed toward 5 ppm of NH 3 over 20–50 °C. Here, this electrical response is largely driven by huge decreases in the imaginary component of the impedance, attributed to increased capacitance at the surface of the MOF crystallites upon NH 3 and H 2 O coadsorption. Complementary structural and microstructural characterization proves that the Cu(cyhdc) crystalline structure and morphology remain intact under trace NH 3 and/or H 2 O adsorption. Despite extremely low NH 3 , loadings seen in TGA, XPS, and FT-IR confirm NH 3 and H 2 O adsorption, and changes to the metal-carboxylate IR peak positions are observed upon NH 3 adsorption. Concentrated primarily at the outer surfaces of the MOF crystallites, this NH 3 and H 2 O coadsorption effectively increases the surface capacitance across the Cu(cyhdc) powder and enables direct electrical detection of trace NH 3 . Together, these results demonstrate how coadsorption of specific molecules (H 2 O) can be used to enable the electrical detection of trace toxic gases that would otherwise not have produced a MOF sensor response.

ammonia↗
DOE OSTI2024

Coherent homodyne detection for amplified cross-beam electric-field induced second harmonic

The electric-field induced second harmonic (E-FISH) signal sensing is commonly used as a nonlinear optical technique to probe electric fields inside a plasma region. Cross-beam E-FISH is being investigated to improve spatial resolution by defining the interaction volume via a controlled geometry of two overlapping noncolinear optical beams. This drastic reduction in interaction length of the electric field and laser region results in a significant signal reduction. Here, to overcome this signal reduction, we introduce coherent amplification of the cross-beam E-FISH signal by mixing the low E-FISH signal with a phase-locked bright local oscillator. We demonstrate enhancement of the signal. By introducing a local oscillator we can now derive the polarity of the measured electric field through the phase of the homodyne signal. To illustrate the technique, we, for the first time, to the best of our knowledge, measure the magnitude and the direction of the electric field in a cold atmospheric pressure plasma jet, which dynamically follows the profile of the applied bias current.

42 ENGINEERING↗
DOE OSTI2023

Nanopore device for reversible ion and molecule sensing or migration

Disclosed are methods and devices for detection of ion migration and binding, utilizing a nanopipette adapted for use in an electrochemical sensing circuit. The nanopipette may be functionalized on its interior bore with metal chelators for binding and sensing metal ions or other specific binding molecules such as boronic acid for binding and sensing glucose. Such a functionalized nanopipette is comprised in an electrical sensor that detects when the nanopipette selectively and reversibly binds ions or small molecules. Also disclosed is a nanoreactor, comprising a nanopipette, for controlling precipitation in aqueous solutions by voltage-directed ion migration, wherein ions may be directed out of the interior bore by a repulsing charge in the bore.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Detection efficiency of a water condensation particle counter using electrically neutral sulfuric acid and sulfuric acid-dimethylamine clusters

Recent advances in condensation particle counters (CPCs) have improved the detection of sub-3 nm particles, increasing the accuracy of new particle formation (NPF) measurements. However, the detection efficiencies for neutrally charged, atmospherically relevant, sub-1 nm particles, which are critical for the accurate derivation of atmospheric NPF rates, are currently unknown. Here, this study presents a method to measure the detection efficiency of sulfuric acid and clusters of sulfuric acid and dimethylamine using measured CPC concentrations and modeled cluster distributions at atmospherically relevant concentrations. This study finds that water-based CPCs can measure these clusters at detection efficiencies relevant to NPF studies.

Cheng, Darren [Carnegie Mellon Univ., Pittsburgh, ↗
DOE OSTI2025

Observation of thermally activated coherent magnon-magnon coupling in a magnonic hybrid system

In this work, we experimentally demonstrate coherent magnon-magnon coupling by thermal spin excitations in yttrium iron garnet/permalloy (YIG/Py) hybrid structures using microfocused Brillouin light scattering—an optical technique that enables the detection of zero-wave-vector and higher-order wave-vector spin waves in a broad frequency range. The thermally activated magnons in the bilayer lead to a hybrid excitation between magnon modes in the conductive Py layer with a wide wave-vector range and the first perpendicular standing magnon modes in the insulating YIG layer, facilitated by strong interfacial exchange coupling. To further investigate this coupling, we compare the thermal magnon spectra with the results obtained from electrical excitation and detection methods, which primarily detect the uniform Py mode. The realization of coherent coupling between incoherent (thermal) magnons is important for advancing energy-efficient magnonic devices, particularly in classical as well as quantum spin-wave computing technologies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Adaptive Hierarchical Cyber Attack Detection and Localization in Active Distribution Systems

Development of a cyber security strategy for the active distribution systems is challenging due to the inclusion of distributed renewable energy generations. Here this paper proposes an adaptive hierarchical cyber attack detection and localization framework for distributed active distribution systems via analyzing electrical waveforms. Cyber attack detection is based on a sequential deep learning model, via which even minor cyber attacks can be identified. The two-stage cyber attack localization algorithm first estimates the cyber attack sub-region, and then localize the specified cyber attack within the estimated subregion. We propose a modified spectral clustering-based network partitioning method for the hierarchical cyber attack ‘coarse’ localization. Next, to further narrow down the cyber attack location, a normalized impact score based on waveform statistical metrics is proposed to obtain a ‘fine’ cyber attack location by characterizing different waveform properties. Finally, compared with classical and state-of-art methods, a comprehensive quantitative evaluation with two case studies shows promising estimation results of the proposed framework.

42 ENGINEERING↗
DOE OSTI2022

Real-time bioelectronic sensing of environmental contaminants

Real-time chemical sensing is crucial for applications in environmental and health monitoring. Biosensors can detect a variety of molecules through genetic circuits that use these chemicals to trigger the synthesis of a coloured protein, thereby producing an optical signal. However, the process of protein expression limits the speed of this sensing to approximately half an hour, and optical signals are often difficult to detect in situ. Here we combine synthetic biology and materials engineering to develop biosensors that produce electrical readouts and have detection times of minutes. Here we programmed Escherichia coli to produce an electrical current in response to specific chemicals using a modular, eight-component, synthetic electron transport chain. As designed, this strain produced current following exposure to thiosulfate, an anion that causes microbial blooms, within 2 min. This amperometric sensor was then modified to detect an endocrine disruptor. The incorporation of a protein switch into the synthetic pathway and encapsulation of the bacteria with conductive nanomaterials enabled the detection of the endocrine disruptor in urban waterway samples within 3 min. Our results provide design rules to sense various chemicals with mass-transport-limited detection times and a new platform for miniature, low-power bioelectronic sensors that safeguard ecological and human health.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Single-Molecule Chemical Reactions Unveiled in Molecular Junctions

Understanding chemical processes at the single-molecule scale represents the ultimate limit of analytical chemistry. Single-molecule detection techniques allow one to reveal the detailed dynamics and kinetics of a chemical reaction with unprecedented accuracy. It has also enabled the discoveries of new reaction pathways or intermediates/transition states that are inaccessible in conventional ensemble experiments, which is critical to elucidating their intrinsic mechanisms. Thanks to the rapid development of single-molecule junction (SMJ) techniques, detecting chemical reactions via monitoring the electrical current through single molecules has received an increasing amount of attention and has witnessed tremendous advances in recent years. Research efforts in this direction have opened a new route for probing chemical and physical processes with single-molecule precision. This review presents detailed advancements in probing single-molecule chemical reactions using SMJ techniques. We specifically highlight recent progress in investigating electric-field-driven reactions, reaction dynamics and kinetics, host–guest interactions, and redox reactions of different molecular systems. Finally, we discuss the potential of single-molecule detection using SMJs across various future applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Thermal generation, manipulation and thermoelectric detection of skyrmions

The efficient generation, manipulation and detection of magnetic skyrmions are important for the development of future spintronic devices. One approach is to use electric-current-induced spin torques. Recently, thermally induced skyrmion motion has also been observed, but wider experimental evidence and its capabilities remain limited. Here we report the thermal generation, manipulation and thermoelectric detection of nanoscale skyrmions in microstructured metallic multilayers integrated with on-chip heaters. The local application of heat can facilitate a domain morphological transition and the formation of skyrmions at the device edge, where a low energy barrier exists. Here, we observe the unidirectional diffusion of skyrmions from hot regions to cold regions, which is due to the interplay among the repulsive forces between skyrmions, thermal spin–orbit torques, entropic forces and magnonic spin torques. The thermally generated skyrmions can also be electrically detected via the Nernst voltage.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗