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At least 613 records · Page 34

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DOE OSTI2019

Monitoring of Actinide Concentrations in Molten LiCl-KCl Salt using Alpha Spectroscopy: Final Progress Report

This project addresses the need for real time monitoring of actinide concentrations for spent fuel reprocessing utilizing alpha spectroscopy. This project specifically focuses on spent fuel reprocessing with the pyroprocessing technique that uses high temperature molten salt. Pyroprocessing uses molten salt such as lithium chloride and potassium chloride to separate out uranium and plutonium from spent fuel. To prevent any possible diversion of high purity plutonium in this process, monitoring of the actinide concentrations within the refinery are essential for safeguards and non-proliferation efforts. Alpha spectroscopy enables the identification and quantification of actinide isotopic concentrations. However, current assay methods involving intrusive sampling and ex-suit measurement require weeks to provide accurate information. A near real-time and in-situ measurement system is required to quickly quantify actinide isotopic concentrations within the salt. Semiconductor radiation detectors provide a compact, high energy resolution option for completing these measurement needs. Silicon carbide (SiC) has been shown to operate effectively at high temperatures and high chemical stability in the molten salt environment. 4H-SiC Schottky diode alpha particle detectors were fabricated and tested to determine their alpha spectroscopy capabilities. The detectors need to operate at the elevated temperatures, survive the molten salt environment, be radiation hard, and have sufficient energy resolution under all these conditions to determine isotopic concentrations. Along with the detector, a method of producing samples of the actinides in the salt is required. To produce a thin film of the actinides on the detector, which is a necessity for alpha spectroscopy, electrodeposition can be used. Electrodeposition uses an electric potential difference to selectively deposit uranium or other actinides from the salt using an anode and cathode. Deposition of the material directly onto the sensor would produce a thin film of material that would enable materials accountability measurements to be taken in real time.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2018

Electrochemical compressor refrigeration appartus with integral leak detection system

An electrochemical compressor system, such as an electrochemical refrigeration system includes a sealed vessel that reduces leak issues related to the electrochemical cell. The sealed vessel may be molded or formed from a polymer or a composite polymer having reinforcing materials, such as fibers therein. The sealed vessel may be plated with metal to reduce gas permeation through the wall of the vessel and to accommodate and improve the attachment of conduits, including metal conduits thereto. A metal conduit may be brazed onto a vessel and the brazing material may be selected for polymer to metal joining and for reduced contamination potential of the system. The electrochemical compressor system incorporates a leak sensor configured at least partially within the sealed rigid vessel that measures the pressure within the vessel.

Bahar, Bamdad↗

DOE OSTI2020

Source identification by non-negative matrix factorization combined with semi-supervised clustering

Machine-learning methods and apparatus are provided to solve blind source separation problems with an unknown number of sources and having a signal propagation model with features such as wave-like propagation, medium-dependent velocity, attenuation, diffusion, and/or advection, between sources and sensors. In exemplary embodiments, multiple trials of non-negative matrix factorization are performed for a fixed number of sources, with selection criteria applied to determine successful trials. A semi-supervised clustering procedure is applied to trial results, and the clustering results are evaluated for robustness using measures for reconstruction quality and cluster separation. The number of sources is determined by comparing these measures for different trial numbers of sources. Source locations and parameters of the signal propagation model can also be determined. Disclosed methods are applicable to a wide range of spatial problems including chemical dispersal, pressure transients, and electromagnetic signals, and also to non-spatial problems such as cancer mutation.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Ionic liquid carbon nanotube composites for wireless chemical sensing

A wireless sensor platform design and a single walled carbon nanotube/ionic liquid-based chemidosimeter system can incorporated into a highly sensitive and selective chemical hazard badge that can dosimetrically detect an analyte down to a sub parts-per-million concentration.

Swager, Timothy M.↗

DOE OSTI2020

Advances in PFAS Monitoring and Remediation Using a Functionalized Material Approach

The growing global concerns about the effects to public health from human exposure to per- and polyfluoroalkyl substances (PFAS) motivates the development of strategies for reliable monitoring of PFAS in environmental streams, as well as for their rapid, effective removal if detected. For the continuous PFAS monitoring, an inexpensive, field-deployable, in situ sensor is urgently needed; yet the prevalent in situ techniques often struggle to strike a balance between the practical sensitivity and selectivity demands of the real world. Similarly, for effective PFAS removal, strategies for their fast, selective, and quantitative capture are desired, yet the present commercially available sorbents are unable to meet the requirements of rapid, quantitative capture of all PFAS components, and are notably inefficient in removing the more toxic smaller chains. To address these twin challenges, Pacific Northwest National Laboratory is developing strategies for improved detection and remediation of PFAS. For the rapid, selective, quantitative removal of PFAS from environmental streams, the strategy relies on designing capture probes with exclusively tailored electronic and spatial affinities for the PFAS that are able to selectively capture them from environmental streams. For the in situ detection and quantification of PFAS in complex, multicomponent matrices such as groundwater, the approach relies on the targeted capture of specific PFAS by these PFAS-specific capture probes immobilized on a platform. The platform acts as an electrode to directly measure PFAS concentration through a proportional change in electrical response upon their capture. A combination of optimization of platform design and incorporation of additional, sensitive detection modalities have allowed us to achieve detection limits as low as 0.5 ng/L for detection of PFAS compounds (compared to the 70 ng/L Health Advisory Limit of the U.S. Environmental Protection Agency).

Per- and poly-fluorinated alkyl substances (PFAS),↗

DOE OSTI2023

Source identification by non-negative matrix factorization combined with semi-supervised clustering

Alexandrov, Boian S.↗

DOE OSTI2024

Tailoring the d-band center on Ru 1 Cu single-atom alloy nanotubes for boosting electrochemical non-enzymatic glucose sensing

The development of cost-effective and highly efficient electrocatalysts is critical to help electrochemical non-enzymatic sensors achieve high performance. Here, in this work, a new class of catalyst, Ru single atoms confined on Cu nanotubes as a single-atom alloy (Ru 1 Cu NTs), with a unique electronic structure and property, was developed to construct a novel electrochemical non-enzymatic glucose sensor for the first time. The Ru 1 Cu NTs with a diameter of about 24.0 nm showed a much lower oxidation potential (0.38 V) and 9.0-fold higher response (66.5 μA) current than Cu nanowires (Cu NWs, oxidation potential 0.47 V and current 7.4 μA) for glucose electrocatalysis. Moreover, as an electrochemical non-enzymatic glucose sensor, Ru1Cu NTs not only exhibited twofold higher sensitivity (54.9 μA mM −1 cm −2 ) and wider linear range (0.5–8 mM) than Cu NWs, but also showed a low detection limit (5.0 μM), excellent selectivity, and great stability. According to theoretical calculation results, the outstanding catalytic and sensing performance of Ru 1 Cu NTs could be ascribed to the upshift of the d-band center that helped promote glucose adsorption. This work presents a new avenue for developing highly active catalysts for electrochemical non-enzymatic sensors.

electrochemistry↗

DOE OSTI2012

TEMPERATURE MONITORING OPTIONS AVAILABLE AT THE IDAHO NATIONAL LABORATORY ADVANCED TEST REACTOR

As part of the Advanced Test Reactor National Scientific User Facility (ATR NSUF) program, the Idaho National Laboratory (INL) has developed in-house capabilities to fabricate, test, and qualify new and enhanced sensors for irradiation testing. To meet recent customer requests, an array of temperature monitoring options is now available to ATR users. The method selected is determined by test requirements and budget. Melt wires are the simplest and least expensive option for monitoring temperature. INL has recently verified the melting temperature of a collection of materials with melt temperatures ranging from 100 to 1000 C with a differential scanning calorimeter installed at INL’s High Temperature Test Laboratory (HTTL). INL encapsulates these melt wires in quartz or metal tubes. In the case of quartz tubes, multiple wires can be encapsulated in a single 1.6 mm diameter tube. The second option available to ATR users is a silicon carbide temperature monitor. The benefit of this option is that a single small monitor (typically 1 mm x 1 mm x 10 mm or 1 mm diameter x 10 mm length) can be used to detect peak irradiation temperatures ranging from 200 to 800 C. Equipment has been installed at INL’s HTTL to complete post-irradiation resistivity measurements on SiC monitors, a technique that has been found to yield the most accurate temperatures from these monitors. For instrumented tests, thermocouples may be used. In addition to Type-K and Type-N thermocouples, a High Temperature Irradiation Resistant ThermoCouple (HTIR-TC) was developed at the HTTL that contains commercially-available doped molybdenum paired with a niobium alloy thermoelements. Long duration high temperature tests, in furnaces and in the ATR and other MTRs, demonstrate that the HTIR-TC is accurate up to 1800 C and insensitive to thermal neutron interactions. Thus, degradation observed at temperatures above 1100 C with Type K and N thermocouples and decalibration due to transmutation with tungsten-rhenium and platinum rhodium thermocouples can be avoided. INL is also developing an Ultrasonic Thermometry (UT) capability. In addition to small size, UT’s offer several potential advantages over other temperature sensors. Measurements may be made near the melting point of the sensor material, potentially allowing monitoring of temperatures up to 3000 C. In addition, because no electrical insulation is required, shunting effects are avoided. Most attractive, however, is the ability to introduce acoustic discontinuities to the sensor, as this enables temperature measurements at several points along the sensor length. As discussed in this paper, the suite of temperature monitors offered by INL is not only available to ATR users, but also to users at other MTRs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Freestanding VO 2 membranes on epidermal nanomesh for ultra-sensitive correlated breathable sensors

The interest in highly sensitive sensors is rapidly increasing for detecting very tiny signals for Internet of Things devices. Here, we achieve ultra-sensitive correlated breathable sensors based on freestanding VO 2 membranes. We fabricate the membranes by growing VO 2 films onto sacrificial Sr 3 Al 2 O 6 layer grown on SrTiO 3 , selectively dissolving the Sr 3 Al 2 O 6 in water, and then rendering freestanding VO 2 membrane on nanomesh. The nanomeshes are extremely flexible, sweat permeable, and readily skin-adhesive. The resistance of the VO 2 membranes is reversibly tuned by human’s tiny mechanical stimuli and breath stimuli. The stimuli modulate the Peierls dimerization of one-dimensional V-V chains in the VO 2 lattice which concomitantly controls the electron correlation and hence resistivity. Since our breathable sensors operate based on quantum-mechanical correlation effects, their sensitivity is 1-2 orders of magnitude higher than conventional tactile and respiratory sensors based on other materials. Thus, the freestanding membranes of correlated oxides on epidermal nanomeshes are multifunctional platforms for developing ultra-sensitive correlated breathable sensors.

36 MATERIALS SCIENCE↗

DOE OSTI2013

A new adaptive light beam focusing principle for scanning light stimulation systems

In this article a novel principle to achieve optimal focusing conditions or rather the smallest possible beam diameter for scanning light stimulation systems is presented. It is based on the following methodology: First, a reference point on a camera sensor is introduced where optimal focusing conditions are adjusted and the distance between the light focusing optic and the reference point is determined using a laser displacement sensor. In a second step, this displacement sensor is used to map the topography of the sample under investigation. Finally, the actual measurement is conducted, using optimal focusing conditions in each measurement point at the sample surface, that are determined by the height difference between camera sensor and the sample topography. This principle is independent of the measurement values, the optical or electrical properties of the sample, the used light source, or the selected wavelength. Furthermore, the samples can be tilted, rough, bent, or of different surface materials. In the following the principle is implemented using an optical beam induced current system, but basically it can be applied to any other scanning light stimulation system. Measurements to demonstrate its operation are shown, using a polycrystalline silicon solar cell.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2017

Short-term solar irradiance forecasting via satellite/model coupling

Here, the short-term (0-3 h) prediction of solar insolation for renewable energy production is a problem well-suited to satellite-based techniques. The spatial, spectral, temporal and radiometric resolution of instrumentation hosted on the geostationary platform allows these satellites to describe the current cloud spatial distribution and optical properties. These properties relate directly to the transient properties of the downwelling solar irradiance at the surface, which come in the form of 'ramps' that pose a central challenge to energy load balancing in a spatially distributed network of solar farms. The short-term evolution of the cloud field may be approximated to first order simply as translational, but care must be taken in how the advection is handled and where the impacts are assigned. In this research, we describe how geostationary satellite observations are used with operational cloud masking and retrieval algorithms, wind field data from Numerical Weather Prediction (NWP), and radiative transfer calculations to produce short-term forecasts of solar insolation for applications in solar power generation. The scheme utilizes retrieved cloud properties to group pixels into contiguous cloud objects whose future positions are predicted using four-dimensional (space + time) model wind fields, selecting steering levels corresponding to the cloud height properties of each cloud group. The shadows associated with these clouds are adjusted for sensor viewing parallax displacement and combined with solar geometry and terrain height to determine the actual location of cloud shadows. For mid/high-level clouds at mid-latitudes and high solar zenith angles, the combined displacements from these geometric considerations are non-negligible. The cloud information is used to initialize a radiative transfer model that computes the direct and diffuse-sky solar insolation at both shadow locations and intervening clear-sky regions. Here, we describe the formulation of the algorithm and validate its performance against Surface Radiation (SURFRAD; Augustine et al., 2000, 2005) network observations. Typical errors range from 8.5% to 17.2% depending on the complexity of cloud regimes, and an operational demonstration outperformed persistence-based forecasting of Global Horizontal Irradiance (GHI) under all conditions by ~10 W/m 2 .

14 SOLAR ENERGY↗

DOE OSTI2016

Advanced In-situ Diagnostics for Multicomponent Gas Analysis and Material Aging

Current methods of detecting material aging rely heavily on accelerated aging studies expensive, bulky, and resource-hungry diagnostics. We are developing compact gas analysis methods based on sensor platforms such as quartz crystal microbalances (QCM), using nanoporous metals and Metal-Organic Frameworks (MOFs), which enhance sensitivity and impart selectivity to analytes. Targeted analytes are O2 and other volatile analytes. In FY16 we installed and tested a new QCM system coupled to a commercial gas mixing system. This instrumentation provides a new multi-use capability that: 1) allows evaluation of detection of novel materials to enable selective detection of volatile species relevant to Enhanced Surveillance; 2) accelerates development of new thin film deposition methods for depositing these materials on sensing devices; and 3) enables in-situ monitoring, with sub-monolayer sensitivity, of the interaction of volatile species with material surfaces subject to aging or corrosion.

36 MATERIALS SCIENCE↗

DOE OSTI2020

The Consortium for Advanced Sorghum Phenomics (CASP). Final report

The goal of CASP was to accelerate breeding of biomass sorghum [Sorghum bicolor (L.) Moench] by identifying genotypes exhibiting high yield under well-watered, pre- or post-drought and/or salinity-stress conditions. We did this by combining high-throughput, non-invasive drone phenotyping with genomics and molecular profiling. Field-based phenotyping utilized a multi-modal sensor suite of LiDAR, multispectral cameras, and thermal cameras mounted on a commercial drone to detect traits required for yield prediction and selection of drought and saline tolerant lines of sorghum. Traits of interest included plant height (PH), leaf area index (LAI), wet biomass (BMW), and biomass at 65% moisture (BM65) and were measured from emergence to harvest on a weekly basis over three growing seasons. The final output were measurements of traits on a plot-by-plot basis, identified by the plot ID used by the Proprietary data processing software enabled raw field data to be turned into plant traits and delivered to the PNNL and JGI within the same workday.

09 BIOMASS FUELS↗

DOE OSTI2021

COVID-19 Biomarkers and Advanced Sensing Technologies for Point-of-Care (POC) Diagnosis

COVID-19, also known as SARS-CoV-2 is a novel, respiratory virus currently plaguing humanity. Genetically, at its core, it is a single-strand positive-sense RNA virus. It is a beta-type Coronavirus and is distinct in its structure and binding mechanism compared to other types of coronaviruses. Testing for the virus remains a challenge due to the small market available for at-home detection. Currently, there are three main types of tests for biomarker detection: viral, antigen and antibody. Reverse Transcription-Polymerase Chain Reaction (RT-PCR) remains the gold standard for viral testing. However, the lack of quantitative detection and turnaround time for results are drawbacks. This manuscript focuses on recent advances in COVID-19 detection that have lower limits of detection and faster response times than RT-PCR testing. The advancements in sensing platforms have amplified the detection levels and provided real-time results for SARS-CoV-2 spike protein detection with limits as low as 1 fg/mL in the Graphene Field Effect Transistor (FET) sensor. Additionally, using multiple biomarkers, detection levels can achieve a specificity and sensitivity level comparable to that of PCR testing. Proper biomarker selection coupled with nano sensing detection platforms are key in the widespread use of Point of Care (POC) diagnosis in COVID-19 detection.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2012

Passive in-situ chemical sensor

A chemical sensor for assessing a chemical of interest. In typical embodiments the chemical sensor includes a first thermocouple and second thermocouple. A reactive component is typically disposed proximal to the second thermal couple, and is selected to react with the chemical of interest and generate a temperature variation that may be detected by a comparison of a temperature sensed by the second thermocouple compared with a concurrent temperature detected by the first thermocouple. Further disclosed is a method for assessing a chemical of interest and a method for identifying a reaction temperature for a chemical of interest in a system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Metal Oxide Nanoarrays for Chemical Sensing: A Review of Fabrication Methods, Sensing Modes, and Their Inter-correlations

In recent years, engineered nanostructure assemblies such as nanowire arrays have attracted much research attention due to their unique chemical and functional characteristics collectively. The engineered nano-assemblies usually carry the characteristics distinct from bulk as a result of a size effect in their comprised elemental building blocks. The nanoscale size induced high surface-to-volume ratio is a fundamental attribute responsible for various chemical and physical properties required in various technologically important applications such as catalysts and sensors. This review article surveys the latest progress in engineered metal oxide nanostructure arrays, i.e., nanoarrays, for advanced chemical sensors' design and application. It starts with an overview of gaseous chemical sensors followed by surveys of various fabrication methods and routes for metal oxide nanoarrays. Different sensing modes and corresponding applications have been highlighted in the mixed gaseous chemical sensing, which provides new approaches and perspectives to meet the challenges of selective gas sensing, such as the cross-sensitivity and inter-correlation of multiple sensing signals.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Wearable Sensor Application for Integrated Early Warning and Health Surveillance

Objective: The Wearable Sensor Application developed by Pacific Northwest National Laboratory (PNNL) provides an early warning system for stressors to individual and group health using physiologic and environmental indicators. The application integrates health monitoring parameters from wearable sensors, e.g., temperature and heart rate, with relevant environmental parameters, e.g., weather and landscape data, and calculates the corresponding physiological strain index. The information is presented to the analyst in a group and individual view with real-time alerting of abnormal health parameters. This application is the first of its kind being developed for integration into the Defense Threat Reduction Agency's Biosurveillance Ecosystem (BSVE).Introduction: Wearable devices are a low cost, minimally invasive way to monitor health. Sensor data provides real-time physiological indictors of an individual’s health status without the requirement of health care professionals or facilities. Information gleamed from wearable sensors can be used to better understand physiological stressors and prodromal symptoms. In addition, this data can be used to monitor individuals that are in high risk of health-related problems.However, raw data from wearable sensors can be overwhelming to process and laborious to monitor for an individual and, even more so, for a group of individuals. Often specific combination of ranges of sensor readings are indicative of changes to health status and need to be evaluated together or used to calculate specific signal parameters. In addition, the environment surrounding the individual needs to be considered when interpreting the data. To address these issues, PNNL has developed an application that collects, analyzes, and integrates wearable sensor data with geographic landscape and weather information to provide a real-time early alert and situational awareness tool for monitoring the health of groups and individuals.Methods: The prototype application described here was a product of PNNL’s BSVE Application Development Competition. The final product that will be deployed in the BSVE is currently under development by PNNL and will vary slightly in the exact design and architecture described.Data. Wearable sensor data was collected from the Rim2Rim (R2R) Watch Study of individuals hiking the Grand Canyon in Arizona [1]. Weather information was obtained from nearby weather stations and mapping features were derived from Google Maps.Calculations. A physiological Strain Index (PSI) was calculated using core temperature estimates derived through a Kalman Filter approach and heart rate [2,3].Application. The prototype backend application development was based in Python with a MongoDB. The front-end development was built using a scalable architecture and modular approach with components in React and D3.Results: A prototype application was developed this past summer through the PNNL BSVE App Competition (Fig 1). The application was aimed at visualizing wearable sensor data from the Grand Canyon R2R hike dataset. Simulated real-time analysis was used to calculate health status of individuals hiking based on measured physiological parameters and to alert to individuals with signs of physiologic health stress. Visualization tools were incorporated to enable sensor data for individuals and the group to be viewed simultaneously along with pertinent weather, geographic, and elevation data.Many features described in the prototype application will be incorporated into the final BSVE application. The key changes will be 1) the ability to select given time periods for viewing historical data as well as the real-time data collection, 2) environmental data and map view will come from BSVE internal data sources, and 3) the alerts will provide more information and have their own page for reviewing.Conclusions: The Wearable Sensor Application developed by PNNL for integration into the BSVE provides an early warning system for individual and group health using physiologic and environmental parameters. The application highlights health status from wearable sensors and relevant environmental parameters while monitoring a calculated physiological strain index. With this tool, an analyst can easily monitor the health of individuals and groups with the aid of real-time alerting tool for early detection of abnormal health parameters.

Early Warning↗

DOE OSTI2020

A high-temperature mixed potential CO gas sensor for in situ combustion control

An in situ, accurate and robust sensor that can sustain a high temperature of above 1000 °C is needed for on-site combustion monitoring because it can give real-time and local data to the control system to adjust the overall combustion efficiency. In this work, we find that nickel oxide (NiO) is a promising sensing material for CO which is a direct indicator of the status of the combustion process of a power plant. Under the conditions of 0.5–3% O 2 and 1000 °C, the fabricated yttrium-stabilized zirconia (YSZ)-based mixed potential sensor using porous NiO demonstrates good sensitivity to CO, showing a signal as high as 36 mV to 1000 ppm CO. The effects of gas transport, structure and geometry of the NiO electrode on the sensing performance are studied. Results show that fast gas transport is much beneficial to improved sensitivity. NiO having a porous structure is much more sensitive to CO than that having a dense structure. But the t90 (time to achieve 90% final signal magnitude) of the former is much longer due to slower gas diffusion inside the pores. It's worth noting that the NiO sensor exhibits a positive relationship with the CO content, opposite to other reported results of mixed potential sensors to detect CO. We find that this might be due to the electrochemical reduction, instead of oxidation of CO during the interaction with NiO at 1000 °C. Selectivity tests on how CO 2 , CH 4 and steam affect CO sensing are also demonstrated. NiO is insensitive to even 10% CO 2 . CH 4 does not shift the average value of the CO sensing response. However, it makes the sensing signal fluctuate more intensively. 2% steam exerts a great influence on NiO sensitivity to CO: it magnifies the sensitivity of the porous NiO electrode to a low CO range of 0–100 ppm, but inhibits its sensitivity to a CO range of 100 ppm to 1000 ppm. Lastly, an 11 day stability test demonstrates the promising stability property of the proposed NiO-based YSZ sensor.

20 FOSSIL-FUELED POWER PLANTS↗