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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Examination of probability distribution of mixture fraction in LES/FDF modelling of a turbulent partially premixed jet flame

An accurate prediction of the probability density function (PDF) of the mixture fraction is crucial to the prediction of combustion since mixing plays an important role in turbulent non-premixed and partially premixed flames. This work provides an assessment of the large-eddy simulation (LES)/filtered density function (FDF) method for the prediction of the PDF of the mixture fraction. The advantage of the LES/FDF method is that it provides the full predictions of the statistical distribution of scalars including the mixture fraction. The predictive accuracy of the method for the PDF is yet to be fully validated. Assessing the prediction of the PDF of the mixture fraction, a conserved scalar, is an important starting point. The Sydney/Sandia inhomogeneous inlet jet flame is used as a test case. A quick comparison shows that the LES/FDF predicted PDF shapes of the mixture fraction deviate significantly from the commonly presumed Beta-PDF as well as from the experimental data in the flame. Here, to examine the source of the discrepancy, we clarify the different PDF definitions used in the comparison among the predictions, measurements, and the presumed shape PDFs. The discrepancy observed from the comparison is largely reconciled by clarifying the difference between the PDFs that are examined. The PDF of the resolved mixture fraction is shown to be close to the Beta-PDF in both the measurements and predictions, while the PDF directly deduced from the LES/FDF particles deviates significantly from the Beta-PDF. A multimodal PDF analysis and a pseudo convergence analysis are conducted to provide plausible evidence to support the predicted multimodal PDF shapes. The sub-filter scale FDF is shown to be close to the Beta-PDF too through the construction of a synthesized PDF, which supports the common presumed Beta-PDF assumption used in the presumed PDF methods when combined with LES.

42 ENGINEERING↗
DOE OSTI2020

Durability of Disposable N95 Mask Material When Exposed to Improvised Ozone Gas Disinfection

The principle finding of this report is that both commercial and a novel material used for N95 mask filters can endure many cycles of disinfection by ozone gas (20 ppm for 30 minutes) without detectable degradation or loss of filtration efficiency. N95 masks and surgical masks (hereafter referred to as masks) typically use a filtration material fabricated from meltblown polypropylene. To achieve maximum filtration efficiency while maintaining a reasonable pressure drop, these nonwoven fabrics are also electrostatically charged (corona discharge is the most common method used), to maximize attraction and capture of aerosols and solid particulates. Under normal circumstances, the reuse of masks is generally discouraged, but in times of crisis has become a necessity, making disinfection after each use a necessity. To be acceptable, any disinfection procedure must cause minimal degradation to the performance of the filter material. Possible performance degradation mechanisms include mechanical damage, loss of electrostatic charge, or both. One of the most practical and direct ways to measure combined mechanical and electrostatic integrity, and the subsequent ability to reuse mask filter material, is by the direct measurement of filtration efficiency. In this paper, we report that small numbers of disinfection cycles at reasonable virucidal doses of ozone do not significantly degrade the filtration efficiency of meltblown polypropylene filter material. By comparison, laundering quickly results in a significant loss of filtration efficiency and requires subsequent recharging to restore the electrostatic charge and filtration efficiency. A common assumption among biomedical scientists that ozone is far too destructive for this application. However, these direct measurements show that mask materials, specifically the filtration material, can withstand dozens of ozone disinfection cycles without any measurable degradation of filtration efficiency, nor any visible discoloration or loss of fiber integrity. The data are clear: when subjected to a virucidal dose of ozone for a much longer duration than is required for viral inactivation, there was no degradation of N95 filtration efficiency. The specific dosages of ozone needed for ~99% viral inactivation are thought to be at least 10 ppm for up to 30 minutes based upon an extensive literature review, but to standardize our testing, we consider a dose of 20 ppm for 30 minutes to be a reasonable and conservatively high ozone disinfection cycle. Finally, the material tested in this study withstood dosages of up to 200 ppm for 90 minutes, or alternatively 20 ppm for up to 36 hours, without detectable degradation, and further testing suggests that up to 30 or more disinfection cycles (at 20 ppm for 30 minutes) would result in less than a 5% loss of filtration efficiency. This report does not address the effect of ozone cycling on other mask components, such as elastics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Combining Three-Dimensional Modeling with Artificial Intelligence to Increase Specificity and Precision in Peptide–MHC Binding Predictions

The reliable prediction of the affinity of candidate peptides for the MHC is important for predicting their potential antigenicity and thus influences medical applications, such as decisions on their inclusion in T cell–based vaccines. In this study, we present a rapid, predictive computational approach that combines a popular, sequence-based artificial neural network method, NetMHCpan 4.0, with three-dimensional structural modeling. We find that the ensembles of bound peptide conformations generated by the programs MODELLER and Rosetta FlexPepDock are less variable in geometry for strong binders than for low-affinity peptides. In tests on 1271 peptide sequences for which the experimental dissociation constants of binding to the well-characterized murine MHC allele H-2D b are known, by applying thresholds for geometric fluctuations the structure-based approach in a standalone manner drastically improves the statistical specificity, reducing the number of false positives. Furthermore, filtering candidates generated with NetMHCpan 4.0 with the structure-based predictor led to an increase in the positive predictive value (PPV) of the peptides correctly predicted to bind very strongly (i.e., Kd < 100 nM) from 40 to 52% (p = 0.027). The combined method also significantly improved the PPV when tested on five human alleles, including some with limited data for training. Overall, an average increase of 10% in the PPV was found over the standalone sequence-based method. The combined method should be useful in the rapid design of effective T cell–based vaccines.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Quantitative radiography for determining density fluctuations in HED experiments

We have developed a method to extract density fluctuation measurements from x-ray radiographs of high-energy density (HED) instability growth and turbulence experiments. We use this information to calculate density fluctuation statistics for constraining the performance of turbulent mix models in HED systems. The density calculation combines image filtering, removal of systemic effects such as backlighter variation, calculation of transmission across multiple materials, and use of tracer materials to generate an approximate single-material density field. From the density map, we calculate both average density and a variance-like moment b (density-specific-volume covariance), which we compare to our models. We infer both quantities from a single image, which is significantly more information than the historic single scalar mix width measurements. We also develop a method of analyzing simulation outputs that incorporate both the density fluctuation metric from a turbulence model and the bulk material maps from the hydrodynamic code. This analysis helps address the question of how to initialize the simulations for best comparison to data from systems with large separations of scale in the mixing perturbation initial condition. We find that our data analysis method yields 1D average density and b curves with similar morphology and amplitudes as those from preliminary simulation comparisons.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

A digital twin based on OpenFAST linearizations for real-time load and fatigue estimation of land-based turbines

Monitoring a wind turbine requires intensive instrumentation, which would be too cost-prohibitive to deploy to an entire wind plant. This work presents a technique that uses readily available measurements to estimate signals that would otherwise require additional instrumentation. This study presents a digital twin concept with a focus on estimating wind speed, thrust, torque, tower-top position, and loads in the tower using supervisory control and data acquisition (SCADA) measurements. The model combines a linear state-space model obtained using OpenFAST linearizations, a wind speed estimator, and a Kalman filter algorithm that integrates measurements with the state model to perform state estimations. The measurements are: top acceleration, generator torque, pitch, and rotational speed. The article extends previous work that derived the linear state-space model using a different method. The new implementation, based on OpenFAST linearization capability, allows for a systematic extension of the method to more states, inputs, outputs, and to the offshore environment. Results from the two methods are compared, and the validation is made with additional measurements using the GE 1.5-MW turbine located at the National Renewable Energy Laboratory test site. Real-time damage equivalent loads of the tower bottom moment are estimated with an average accuracy of approximately 10%. Overall, the results from this proof of concept are encouraging, and further application of the model will be considered.

17 WIND ENERGY↗
DOE OSTI2021

Learning the structure of wind: A data-driven nonlocal turbulence model for the atmospheric boundary layer

In this work, we develop a novel data-driven approach to modeling the atmospheric boundary layer. This approach leads to a nonlocal, anisotropic synthetic turbulence model which we refer to as the deep rapid distortion (DRD) model. Our approach relies on an operator regression problem that characterizes the best fitting candidate in a general family of nonlocal covariance kernels parameterized in part by a neural network. This family of covariance kernels is expressed in Fourier space and is obtained from approximate solutions to the Navier–Stokes equations at very high Reynolds numbers. Each member of the family incorporates important physical properties such as mass conservation and a realistic energy cascade. The DRD model can be calibrated with noisy data from field experiments. After calibration, the model can be used to generate synthetic turbulent velocity fields. To this end, we provide a new numerical method based on domain decomposition which delivers scalable, memory-efficient turbulence generation with the DRD model as well as others. We demonstrate the robustness of our approach with both filtered and noisy data coming from the 1968 Air Force Cambridge Research Laboratory Kansas experiments. Using these data, we witness exceptional accuracy with the DRD model, especially when compared to the International Electrotechnical Commission standard.

17 WIND ENERGY↗
DOE OSTI2025

Dark matter substructure or source model systematics? A case study of cluster lens Abell S1063

Mapping the small-scale structure of the universe through gravitational lensing is a promising tool for probing the particle nature of dark matter. Curved Arc Basis (CAB) has been proposed as a local lensing formalism in galaxy clusters, with the potential to detect low-mass dark matter substructure. In this work, we analyse the cluster lens Abell S1063 in search of dark matter substructure with the CAB formalism, using multiband imaging data from James Webb Space Telescope ( JWST ). We use two different source modelling methods: shapelets and pixel-based source reconstruction based on Delaunay triangulation. We find that source modelling systematics from shapelets result in a disagreement between CAB parameters measured from different filters. Source modelling with Delaunay significantly alleviates this systematic, as seen in the improvement in agreement across filters. We also find that inadequate complexity in source modelling can result in convincing spurious detections of dark matter substructure from strong gravitational lenses, as seen by our $\Delta \text{BIC} > 20$ measurement of a $M \sim 10^{10}$ ${\rm M}_{\odot }$ subhalo with shapelets, a spurious detection that is not reproduced with Delaunay source modelling. We demonstrate that multiband analysis with different JWST filters is key for disentangling source and lens model systematics from dark matter substructure detections.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

A Knowledge Network-Based Approach to Facilitate Annotation of Clinical Pathway Component Clusters

Mining electronic health records (EHRs) to identify contextually related clinical concept clusters that tend to co-occur temporarily and consistently could improve data-driven clinical pathway (CP) construction. However, the automatic extraction of contextually related clinical concept clusters contains a vast amount of irrelevant information. Hence, this paper proposes a knowledge network-enabled literature-based discovery (LBD) approach to remove noise from clusters. The authors used published literature to filter spurious concepts from the clusters and used data from the US Department of Veterans Affairs’s major depressive disorder (MDD) cohort of Operation Enduring Freedom/Operation Iraqi Freedom (OEF/OIF) for their experimentation. The approach was applied to 2,967 clusters extracted from the MDD OEF/OIF database. The experimental results demonstrate that the proposed approach can filter 94% of the irrelevant information. Moreover, the authors applied various network mining algorithms to analyze the clusters and demonstrated that LBD, along with network mining techniques, is a useful method for finding accurate contextually related clinical concept clusters. This could help domain researchers perform advanced analytics in CPs.

Hasan, S M Shamimul↗
DOE OSTI2021

Data-driven Event Identification in the U.S. Power Systems Based on 2D-OLPP and RUSBoosting Trees

Accurate event identification is an essential part of situation awareness ability for power system operators. Therefore, this work proposes an integrated event identification algorithm for power systems. First, to obtain and filter suitable inputs for event identification, an event detection trigger based on the rate of change of frequency (RoCoF) is presented. Then, the wave arrival time difference-based triangulation method considering the anisotropy of wave propagation speed is utilized to estimate the location of the detected event. Next, the two-dimensional orthogonal locality preserving projection (2D-OLPP)-based method, which is suitable for multiple types of measured data, is employed to achieve higher effectiveness in extracting the event features compared with traditional one-dimensional projection and principle component analysis (PCA). Finally, the random undersampling boosted (RUSBoosted) trees-based classifier, which can mitigate the data sample imbalance issue, is utilized to identify the type of the detected event. Furthermore, the proposed approach is demonstrated using the actual measurement data of U.S. power systems from FNET/GridEye. Comparison results show that the proposed event identification algorithm can achieve better performance than existing approaches.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Production and characterization of extracellular cellulases from a native strain of Trichoderma harzianum using wheat straw from the Mexicali valley as the carbon source. Producción y caracterización de celulasas Extracelulares a partir de cepa nativa de Trichoderma harzianum usando como fuente de Carbono paja de trigo del valle de Mexicali

The purpose of this study was to produce cellulase enzyme from a native strain Trichoderma harzianum, isolated from crop soil. Cellulase production was carried out by two different methods of fermentation, submerging and solid state fermentation. Mandels mineral medium was used as a source of nitrogen and ammonium sulfate. Dry and ground wheat straw was used in fermentation as a carbon source. Cellulase activity was determined using the 3,5-dinitrosalicylic acid (DNS) method. The results showed that wheat straw has the potential to be used as a substrate in the production of cellulases. Trichoderma harzianum showed enzymatic activity of 0.125 FPU / ml (filter paper units) and 1. 35 U / ml CMC (carboxymethyl cellulose units) by solid state fermentation (FSS) after 96 hours of fermentation. The optimum pH for the two substrates was determined by testing with citrate buffers (pH 4 to 6), phosphates (pH 6 to 7) and tris-HCL (pH 8 to 9). To determine the optimum temperature the range of 30 ° C to 80 ° C was investigated. Storage tests were performed every seven days over a period of 6 weeks. The optimum activity pH on paper and CMC was found to be 6. The optimum activity temperature is 70 ° C for PF and 80 ° C for CMC. El propósito de este estudio fue producir enzima celulasa a partir de una cepa nativa Trichoderma harzianum, aislada de suelo de cultivo. La producción de celulasa se realizó por dos métodos diferentes de fermentación, sumergida y fermentación en estado sólido. Se utilizó medio mineral Mandels y como fuentes de nitrógeno urea y sulfato de amonio. Se utilizó paja de trigo seca y molida en las fermentaciones como fuente de carbono. La actividad de la celulasa se determinó por medición de azúcares reductores al papel filtro y a la carboximetilcelulosa usando el método del ácido 3,5- dinitrosalicílico (DNS). Los resultados mostraron que la paja de trigo tiene el potencial para usarse como sustrato en la producción de celulasas. Trichoderma harzianum mostró actividad enzimática de 0.125 FPU/ml (unidades de papel filtro) y 1.35 U/ml a la CMC (unidades de carboximetilcelulosa) por fermentación en estado sólido (FSS) después de 96 horas de fermentación. El pH óptimo para los dos sustratos se determinó realizando pruebas con buffers de citratos (pH 4 a 6), de fosfatos (pH 6 a 7) y tris- HCL (pH 8 a 9). Para la determinación de la temperatura óptima se manejó el rango de 30°C a 80°C. Las pruebas de almacenamiento se realizaron cada siete días en un periodo de 6 semanas. Se encontró que el pH óptimo de actividad en papel y CMC es de 6. La temperatura óptima de actividad es de 70°C para PF y de 80°C para CMC.

09 BIOMASS FUELS↗
DOE OSTI2023

Analysis of Needlet Internal Linear Combination performance on B -mode data from sub-orbital experiments

The observation of primordial B modes in cosmic microwave background (CMB) polarisation data represents the main scientific goal of most of the future CMB experiments. This signal is predicted to be much lower than polarised Galactic emission (foregrounds) in any region of the sky, pointing to the need for effective component separation methods. Aims. Among all the techniques, the blind Needlet Internal Linear Combination (NILC) is of great relevance given our current limited knowledge of the B-mode foregrounds. In this work, we explore the possibility of employing NILC for the analysis of B modes reconstructed from partial-sky data, specifically addressing the complications that such an application yields such as E–B leakage, needlet filtering, and beam convolution. We consider two complementary simulated datasets of future experiments: the balloon-borne Short Wavelength Instrument for the Polarisation Explorer (SWIPE) of the Large Scale Polarisation Explorer, which targets the observation of both reionisation and recombination peaks of the primordial CMB B-mode angular power spectrum, and the ground-based Small Aperture Telescope of Simons Observatory, which, instead, is designed to observe only the recombination bump at ℓ ~ 80. We assessed the performance of the following two alternative techniques to correct for the CMB E–B leakage: the recycling technique and the Zhao-Baskaran method. We find that both techniques reduce the E–B leakage residuals at a negligible level given the sensitivity of the considered experiments, except for the recycling method in the SWIPE footprint at ℓ < 20. Thus, we implemented two extensions of the pipeline, the iterative B decomposition and the diffusive inpainting, which enabled us to recover the input CMB B-mode power for ℓ ≥ 5. For the considered experiments, we demonstrate that needlet filtering and beam convolution do not affect the CMB B-mode reconstruction. Finally, with an appropriate masking strategy, we find that NILC foregrounds subtraction allows one to achieve sensitivities on the tensor-to-scalar ratio in agreement with the targets of the considered CMB experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Cyber-Attack Detection for Active Neutral Point Clamped (ANPC) Photovoltaic (PV) Converter using Kalman Filter

With the upgrading of communication technology, cyber threats to power converters are increasing. In this paper, a model-based cyber-attack detection methodology is proposed for the interleaved Active neutral point clamped (ANPC) Photovoltaic (PV) converter. The proposed methodology identifies cyber-attacks using two estimations based on the Kalman filter and the state-space model of the ANPC PV converter. The residual between the two estimations is analyzed from a statistical perspective. Based on the Cumulative Sum (CUSUM) Control Chart, the standard errors shift of the residual is used to identify cyber-attacks. Besides, to validate the feasibility of the proposed methodology, several conditions are considered in the simulation, including white noise in the sensor, irradiance variation, and cyber-attacks in the PV converter. Furthermore, the simulation result demonstrates the proposed method can identify cyber-attacks in the ANPC PV converter.

14 SOLAR ENERGY↗
DOE OSTI2023

Methane monitoring and detection apparatus and methods

A low cost, low power, passive optical methane monitoring system for fixed-position installation at oil and gas production well pads and gathering centers is disclosed. The optical methane monitoring system disclosed can be a scannable field of view Near Infrared (NIR) filter photometer to detect and quantify methane concentration in a two dimensional or a three dimensional grid above and around a facility. A randomized fiber optic bundle is disclosed that can be used to direct the total optical power from a collection lens to two or more isolated optical channels. Band pass filters isolate a desired wavelength range for transmission measurements for the two or more channels. Also disclosed is an absorption algorithm which accounts for variable background spectral intensity as well as correcting for water vapor and overall scattering effects to measure methane concentration for a given field of view.

Lievois, John↗
DOE OSTI2023

Scoping Study for Fast Flux Testing in the Advanced Test Reactor

The value of fast spectrum reactors remains prominent in the nuclear technology portfolio. The performance of these reactors can be maximized with advancements in nuclear fuel technologies, but development of these technologies is currently held back by lack of fast spectrum test reactors available to the United States. Spectral modification of experiment positions in the thermal spectrum Advanced Test Reactor (ATR) has long been used to support fast reactor fuel development, but these methods have not been progressed to their full potential. This study investigated the use of concentric rings of aluminum-clad fuel plates in ATR flux traps and thermal neutron absorbing filters to increase fast neutron flux on test specimens. This concept was termed the Boosted Energy Advanced Spectrum Test (BEAST). This approach will enable irradiation of advanced fuel designs in prototypic-length fuel pins and representative flux environment to support post irradiation exams, enable transient testing, and produce the type of data that will permit lead test assembly irradiations in true Sodium Fast Reactors (SFRs) when they become available. Neutronic predictions were performed to investigate BEAST design options and thermal hydraulic models were produced to ensure feasibility of BEAST. Two versions were considered based on the geometric limitations of ATR’s small and large flux traps. The small version was found to be preferable due to slightly higher fast flux and fast-to-thermal neutron ratio. Perhaps more influentially, the small flux trap option was also preferred to avoid conflict with ongoing very high temperature reactor fuel irradiation programs in ATR’s large northeast flux trap. The small flux trap option provided less than half the test volume of the large version, but still had adequate volume for seven SFR pins in cross section which could be stacked two-high in ATR’s 1.2m long core to accommodate up to 14 EBR-II size pins. The preference for the small flux trap configuration should be revisited if additional collaborative test programs emerge with the need to irradiate a significant volume of additional specimens. Calculations were performed regarding a lithium deuteride ring to convert thermal neutrons into 14 MeV fusion neutrons. At the time this report was written these calculations were partially complete and it remains to be seen whether the concept would be worth including in BEAST. Given the preference for the small flux trap option, which does not afford enough room for the 14 MeV ring, it was concluded to defer future work on the lithium deuteride ring. This decision could be revisited if fusion material research programs emerge for collaborative testing in BEAST. A cadmium-lined specimen holder design was found to be adequate in filtering thermal neutrons and preferred over other neutron absorbers based on past experience with cadmium baskets. It was acknowledged that cadmium-bearing hardware would become depleted and need to be replaced occasionally, which appeared feasible from a mechanical design perspective. Neutronic studies investigated different enrichment levels in the booster fuel using uranium-molybdenum alloy dispersion fuel which has performed well in past ATR irradiations. Both options were able to drive fuel pins to SFR-like fission heating rates. The high enriched booster fuel option outperformed the low enriched option by ~20% on key metrics including fast flux and fast-to-thermal ratio, but the low enriched option was favored in order to broaden options for potential fuel suppliers. The preferred BEAST design options including cadmium filter with low enriched booster fuel in the small flux trap configuration was predicted to achieve 6.2E14 n/cm2sec fast flux (>0.1 MeV) with a fast-to-thermal ratio of 44.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Luminescence based fiber optic probe for the detection of rare earth elements

The disclosure relates to an apparatus, method and process for detecting rare earth elements. The system includes an LED powered by a first power source and a focusing lens in optical communication with the LED. A shortpass filter is in optical communication with the focusing lens; and a fiber bifurcated cable in optical communication with the shortpass filter. The system includes a probe tip in optical communication with the fiber bifurcated cable and a sample; a first aspheric lens in optical communication with the fiber bifurcated cable. A longpass filter is in optical communication with the first aspheric lens and a second aspheric lens in optical communication with the longpass filter. The system includes a spectrometer connected to a power source, where the spectrometer is in optical communication with the second aspheric lens.

Ahern, John C.↗
DOE OSTI2020

Ambient Mass Spectrometry Rapid Analysis Methods for Trace Inorganics

The ability to rapidly detect and characterize the chemistry of trace quantities of inorganic species has multiple potential applications, including nuclear safeguards, nuclear forensics, and environmental monitoring. Some mass spectrometric methods currently exist, but they are costly and time-intensive, often destroying chemical information in the process of ionization. Ambient mass spectrometry is a relatively new analytical method in which samples are introduced to the mass spectrometer from atmospheric pressure, rather than from high vacuum. Ambient MS can operate with gentler ionization methods such as electrospray ionization (ESI) and paper-spray ionization (PSI), reducing fragmentation and preserving the chemical information of the analyte. This may be useful for determining the intended purpose of material in a sample. Strontium, part of nuclear fallout, is analyzed here to test these new analytical methods for viability. Electrospray ionization mass spectrometry functions by spraying the sample as a solution through a needle charged to a few kV. A nebulizing gas flows out along with the sample to create the spray before droplets enter a drying chamber with heated drying gas to remove the solvent molecules. From there bare analyte ions enter the mass spectrometer. This method has the advantage of relatively fast sample preparation and stable ionization. More stable ionization produces higher-quality data. Paper-spray ionization mass spectrometry operates by applying sample to a paper triangle. The paper triangle is then electrified in a metal clamp to a few kV before spray solvent is applied. The spray solvent transports analyte in the sample to the tip, where it is ionized and enters the mass spectrometer. One advantage of this method is reduced sample preparation - an analyst can even swipe a surface and cut a triangle directly from the swipe. The data analysis serves to rapidly process tens of samples all at once. The mass spectrometer outputs a file containing a few hundred spectra for each sample. The pipeline processes each one to identify peaks of interest. A full palette of data analysis metrics are generated, including plots of the raw data and plots of calculated values such as isotopic ratios. The pipeline filters the raw data to remove noise and background peaks, as well as peaks representing detector saturation. A heat map is generated to show the overall spectrum in mass-time- intensity space. Post-processing, we obtained the desired calibration curves, demonstrating that both ESI-MS and PSI-MS are viable methods for quantifying trace amounts of inorganics while retaining their chemical speciation information. ESI-MS demonstrated a linear response region of 100 ppb to 20 ppm, with a limit-of-detection of around 100 ppb. At top left is an example spectrum with the {sup 88}SrNO{sub 3} peak identified to show the retention of chemical speciation. PSI-MS showed a linear response region of around 1 ppb to 1 ppm, with a limit-of-detection of near 1 ppb. PSI-MS produced more erratic results than ESI-MS, likely due to the variability in ionization resulting from manual positioning of the paper triangle near the MS inlet. Future efforts will focus on improving the repeatability of PSI-MS as well as analyzing other species of interest such as cerium and uranium. Improvements will also be made to create more reliable data extraction and intelligent data filtering.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Structural, Electrical, and Optical Properties of Single-Walled Carbon Nanotubes Synthesized through Floating Catalyst Chemical Vapor Deposition

Single-walled carbon nanotube (SWCNT) thin films were synthesized by using a floating catalyst chemical vapor deposition (FCCVD) method with a low flow rate (200 sccm) of mixed gases (Ar and H 2 ). SWCNT thin films with different thicknesses can be prepared by controlling the collection time of the SWCNTs on membrane filters. Transmission electron microscopy (TEM) showed that the SWCNTs formed bundles and that they had an average diameter of 1.46 nm. The Raman spectra of the SWCNT films suggested that the synthesized SWCNTs were very well crystallized. Although the electrical properties of SWCNTs have been widely studied so far, the Hall effect of SWCNTs has not been fully studied to explore the electrical characteristics of SWCNT thin films. In this research, Hall effect measurements have been performed to investigate the important electrical characteristics of SWCNTs, such as their carrier mobility, carrier density, Hall coefficient, conductivity, and sheet resistance. The samples with transmittance between 95 and 43% showed a high carrier density of 10 21– 10 23 cm –3 . The SWCNTs were also treated using Brønsted acids (HCl, HNO 3 , H 2 SO 4 ) to enhance their electrical properties. After the acid treatments, the samples maintained their p-type nature. The carrier mobility and conductivity increased, and the sheet resistance decreased for all treated samples. The highest mobility of 1.5 cm 2 /Vs was obtained with the sulfuric acid treatment at 80 °C, while the highest conductivity (30,720 S/m) and lowest sheet resistance (43 ohm/square) were achieved with the nitric acid treatment at room temperature. Different functional groups were identified in our synthesized SWCNTs before and after the acid treatments using Fourier-Transform Infrared Spectroscopy (FTIR).

36 MATERIALS SCIENCE↗
DOE OSTI2021

Estimating and Forecasting Time-Varying Groundwater Recharge in Fractured Rock: A State-Space Formulation with Preferential and Diffuse Flow to the Water Table

Rapid infiltration following precipitation may result in groundwater contamination from surface contaminants or pathogens. In fractured rock, contaminants can migrate rapidly to points of groundwater withdrawals. In contrast to the temporal availability of groundwater quality chemical indicators, meteorological and groundwater level observations are available in real-time to estimate time-varying recharge, which can act as a surrogate to identify periods of rapid infiltration that may indicate contamination susceptibility. Estimating recharge using methods, such as base-flow recession, unsaturated infiltration models, or Water-Table Fluctuations (WTF), cannot capitalize on currently available technologies and telecommunication infrastructure to conduct real-time recharge estimation at scales relevant to characterizing rapid infiltration. We present a linear, physics-based State-Space (SS) model of one-dimensional infiltration to estimate recharge, which includes preferential and diffuse-flow to the water table. The model can take advantage of real-time data for water-table altitude, precipitation, and evapotranspiration. Model parameters are calibrated over an observation period, and the Kalman Filter (KF) is subsequently applied to continuously update the observed (water-table altitude) and unobserved (groundwater recharge) system states and predict future states as new data become available. The SS/KF algorithm is demonstrated at the Masser Groundwater Recharge Site in Pennsylvania, USA and comparisons are made with recharge estimates from WTF methods. Model results indicate that the frequency of observations (daily versus sub-daily) dictates the allocation between preferential and diffuse flow. Additionally, because infiltration processes encompass many nonlinearities, model parameters estimated from observation periods need to be updated at least seasonally to account for changing recharge conditions.

groundwater, Recharge, infiltration, recursive est↗