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At least 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Generalized Ellipsometry Measurements of Crystalline Thin Film and Bulk Tin Oxide

Here, several bulk and thin-film crystals of SnO2 are grown and examined using generalized ellipsometry techniques. The bulk samples are grown using the chemical vapor transport technique and thin films of SnO2 are grown using the pulsed laser deposition technique. The bulk samples are examined using the two-modulator generalized ellipsometry microscope (2-MGEM) at normal incidence and the spectroscopic two-modulator generalized ellipsometer (2-MGE). The spectroscopic optical functions of tin oxide are then obtained using the 2-MGE from 1.46 to 6.2 eV. The material is highly birefringent, and the ordinary bandgap is less than the extraordinary band edge. 2-MGE measurements are also made on thin-film samples of crystalline tin oxide grown on sapphire and rutile, showing no cross polarization. Because of the complicated morphology of the tin oxide films grown on sapphire, the ellipsometry data are simulated using the Tauc–Lorentz model. Films grown on rutile had the optic axis perpendicular to the sample surface, but the film is strained, resulting in a more complicated ellipsometric spectrum. These films are modeled using the air/surface roughness/tin oxide/interface/rutile model, where the roughness and interface are modeled using the incomplete Beta function.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Evaluation of the Quasi‐Biennial Oscillation in global climate models for the SPARC QBO‐initiative

Abstract Quasi‐biennial oscillations (QBOs) in thirteen atmospheric general circulation models forced with both observed and annually repeating sea surface temperatures (SSTs) are evaluated. In most models the QBO period is close to, but shorter than, the observed period of 28 months. Amplitudes are within ±20 % of the observed QBO amplitude at 10 hPa, but typically about half of that observed at lower altitudes (50 and 70 hPa). For almost all models, the oscillation's amplitude profile shows an overall upward shift compared to reanalysis and its meridional extent is too narrow. Asymmetry in the duration of eastward and westward phases is reasonably well captured, though not all models replicate the observed slowing of the descending westward shear. Westward phases are generally too weak, and most models have an eastward time mean wind bias throughout the depth of the QBO. The intercycle period variability is realistic and in some models is enhanced in the experiment with observed SSTs compared to the experiment with repeated annual cycle SSTs. Mean periods are also sensitive to this difference between SSTs, but only when parametrized non‐orographic gravity wave (NOGW) sources are coupled to tropospheric parameters and not prescribed with a fixed value. Overall, however, modelled QBOs are very similar whether or not the prescribed SSTs vary interannually. A portrait of the overall ensemble performance is provided by a normalized grading of QBO metrics. To simulate a QBO, all but one model used parametrized NOGWs, which provided the majority of the total wave forcing at altitudes above 70 hPa in most models. Hence the representation of NOGWs either explicitly or through parametrization is still a major uncertainty underlying QBO simulation in these present‐day experiments.

Bushell, A. C.↗
DOE OSTI2023

A riming‐dependent parameterization of scattering by snowflakes using the self‐similar Rayleigh–Gans approximation

Abstract Riming is a key process of precipitation formation in ice‐containing clouds, but quantifying riming from observations is challenging, limiting our ability to evaluate the riming process in numerical weather models. One challenge for radar observations is that riming changes both the physical properties (mass, area cross‐section) and scattering properties of ice particles. These changes need to be implemented consistently as a function of riming in radar forward operators, which are required for retrievals and model evaluation in observation space. In this study, mass–size, cross‐section area–size, and backscattering cross‐section relations are developed as a function of the normalized rime mass for aggregates composed of various monomer types (columns, dendrites, needles, plates, and rosettes). The proposed framework allows us to simulate scattering properties of aggregated ice particles consistently as a function of riming in retrievals and radar forward operators. The parameterizations are developed from a large data set of simulated rimed aggregates of different sizes and monomer crystal types. The backscattering cross‐section parameterization (the “riming‐dependent parameterization”) is evaluated for radar frequencies of 35.6 and 94.0 GHz and is based on the Self‐Similar Rayleigh–Gans approximation (SSRGA), which is increasingly used to calculate microwave scattering of ice crystals and snowflakes. Compared with parameterizations from the literature that do not consider riming, the riming‐dependent parameterization leads to significantly smaller biases in terms of backscattering cross‐section. When using the particle masses and scattering properties of the individual particles simulated by the aggregation and riming model as a reference, the bias of our parameterization is below 1 dB when integrating over an exponential particle size distribution with sizes from 0.1–10 mm.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Large-Volume Injection and Assessment of Reference Standards for n -Alkane δD and δ 13 C Analysis via Gas Chromatography Isotope Ratio Mass Spectrometry

Compound-specific stable isotope analysis of hydrogen (δD) and carbon (δ 13 C) in organic compounds is a valuable tool in biogeochemical research. A key limitation of this method is the relatively large amount of sample required to achieve desirable precision. We developed a large-volume (20 μL) injection method that allows for high throughput analysis of less concentrated samples and tested it for δ 13 C and δD measurements of n-alkanes. We also conducted a comparison of reference standards and assessed several methods to normalize and correct n-alkane δD and δ13C measurements. The mean precision of the δD method based on 233 environmental n-alkane samples (two to three replications per sample) is 4.0‰ (1σ, estimated from the weighted mean of the pooled unbiased standard deviations) and 0.46‰ (1σ) for δ 13 C from 37 environmental samples (two to three replications per sample). The evaluation of reference standards shows that the use of n-alkane standards with large offsets in δD values in adjacent n-alkane chains can lead to biases in measurement correction. The large-volume injection method shows good reproducibility of δ 13 C and δD measurements of n-alkanes and reduces the required sample concentration by about 80%. We propose that for δD measurements, a reference standard set should be used in which each reference standard has a limited range of δD values and no adjacent n-alkane chains, to minimize memory effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

New Safety Feedback Control Design to Guarantee Adequate Frequency Performance in Microgrids

Safety analysis of power systems is concerned with the system's ability to maintain critical variables within specified limits following a disturbance. Frequency control adequacy has become increasingly important as the system inertia decreases due to the increase in renewable energy penetration. Various controllers for inverters have been proposed to improve the system frequency response and few are capable to ensure the safety of the response. In this article, a diesel-wind energy system is considered and modeled as a switching system between normal, faulted, and post-fault modes. Further, a safety feedback controller is designed as a supplementary signal for a wind turbine generator such that the speed of the diesel generator stays within a permissible range in the presence of a finite energy disturbance. Numerical results on the modified 33-bus microgrid system obtained of the proposed novel approach indicate that the suggested control configuration can guarantee adequate frequency response without excessive conservativeness.

barrier function↗
DOE OSTI2021

Power grid frequency prediction using spatiotemporal modeling

Understanding power system dynamics is essential for interarea oscillation analysis and the detection of grid instabilities. The FNET/GridEye is a GPS-synchronized wide-area frequency measurement network that provides an accurate picture of the normal real-time operational condition of the power system-dynamics, giving rise to new and intricate spatiotemporal patterns of power loads. We propose to model FNET/GridEye grid frequency data from the U.S. Eastern Interconnection with a spatiotemporal statistical model. We predict the frequency data at locations without observations, a critical need during disruption events where measurement data are inaccessible. Spatial information is accounted for either as neighboring measurements in the form of covariates or with a spatiotemporal correlation model captured by a latent Gaussian field. Finally, the proposed method is useful in estimating power system dynamic response from limited phasor measurements and holds promise for predicting instability that may lead to undesirable effects such as cascading outages.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Activating Layered Metal Oxide Nanomaterials via Structural Engineering as Biodegradable Nanoagents for Photothermal Cancer Therapy

Layered metal oxides including MoO 3 and WO 3 have been widely explored for biological applications owing to their excellent biocompatibility, low toxicity, and easy preparation. However, they normally exhibit weak or negligible near-infrared (NIR) absorption and thus are inefficient for photo-induced biomedical applications. Herein, the structural engineering of layered MoO 3 and WO 3 nanostructures is first reported to activate their NIR-II absorption for efficient photothermal cancer therapy in the NIR-II window. White-colored micrometre-long MoO 3 nanobelts are transformed into blue-colored short, thin, defective, interlayer gap-expanded MoO 3–x nanobelts with a strong NIR-II absorption via the simple lithium treatment. The blue MoO 3–x nanobelts exhibit a large extinction coefficient of 18.2 L g –1 cm –1 and high photothermal conversion efficiency of 46.9% at 1064 nm. After surface modification, the MoO 3–x nanobelts can be used as a robust nanoagent for photoacoustic imaging-guided photothermal therapy to achieve efficient cancer cell ablation and tumor eradication under irradiation by a 1064 nm laser. Importantly, the biodegradable MoO 3–x nanobelts can be rapidly degraded and excreted from body. We report the study highlights that the structural engineering of layered metal oxides is a powerful strategy to tune their properties and thus boost their performances in given applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Dilute Regeneration-Driven Membrane Capacitive Deionization of Synthetic Seawater Using Nanopatterned Membranes and Prussian Blue Analog Electrodes

Membrane capacitive deionization (MCDI) offers energy-efficient seawater desalination but is limited at high salinity by membrane resistance and incomplete electrode regeneration. Nanopatterned ion-exchange membranes, dilute regeneration protocols, and Prussian blue analog (PBA)-functionalized electrodes are combined in a flow-by-MCDI cell. Nanopatterned ion-exchange membranes (hexagonal, octagonal, double-ring, rectangular) enhance interfacial ion transport, with hexagonal geometry delivering ≈12.5% greater surface area and the best performance. PBA-functionalized electrodes increase salt adsorption and charge-transfer kinetic rates. The integrated system lowers the area-specific resistance by 45 Ω cm2, resulting in a 500 mV reduction in the cell voltage for a current density of 2 mA cm−2 for a 35 000 ppm NaCl feed. This improves the energy-normalized salt adsorption six fold (64–382 mmol J−1). Low salinity (2000 ppm) and mixed-salt regeneration sustains a ≈39% water recovery and stable performance for at least seven cycles. Overall, combining nanopatterned membranes, which promote confinement-enhanced ion mobility, and PBA electrodes, which enhance salt adsorption, improved the energy efficiency of MCDI.

Hasan, Mahmudul↗
DOE OSTI2025

Dual‐Functional High‐Entropy Polymer Exhibiting Giant Cross‐Energy Couplings at Low Fields

A key component of cooling devices is the transfer of entropy from the cold load to heat sink. An electrocaloric (EC) polymer capable of generating both large electrocaloric effect (ECE) and substantial electroactuation can enable EC cooling devices to pump heat without external mechanisms, resulting in compact designs and enhanced efficiency. However, achieving both high ECE and significant electroactuation remains challenging. Herein, it is demonstrated that poly(vinylidene fluoride‐trifluoroethylene‐chlorofluoroethylene‐double bond) [P(VDF‐TrFE‐CFE‐DB)] tetrapolymers can simultaneously generate high electrocaloric effects and electroactuations under low fields. These P(VDF‐TrFE‐CFE‐DB) tetrapolymers are synthesized through the dehydrochlorination of P(VDF‐TrFE‐CFE) terpolymer. By facile tuning the composition of the initial terpolymer to avoid pure relaxor state, tetrapolymers with optimal DB compositions are achieved, near the critical endpoint of normal ferroelectric phase with diffused phase transition. The nearly vanishing energy barriers between the nonpolar to polar phases result in a strong electrocaloric response and significant electroactuation. Specifically, the P(VDF‐TrFE‐CFE‐DB) tetrapolymer exhibits an EC entropy change Δ S of 100 J kg −1 K −1 under 100 MV m −1 : comparable to state‐of‐the‐art (SOA) EC polymers, while delivering nearly twice the electroactuation of the SOA EC polymers. This work presents a general strategy for developing EC materials that combine large electrocaloric effect and electroactuation at low electric fields.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Nanosized Zirconium Porphyrinic Metal–Organic Frameworks that Catalyze the Oxygen Reduction Reaction in Acid

Porphyrinic metal–organic frameworks (PMOFs) are very appealing electrocatalytic materials, in part, due to their highly porous backbone, well-defined and dispersed metal active sites, and their long-range order. Herein a series of (Co)PCN222 (PCN: porous coordination network) (nano)particles with different sizes are successfully prepared by coordination modulation synthesis. These particles exhibit stability in 0.1 M HClO 4 electrolyte with no obvious particle size or compositional changes observed after being soaked for 3 days in the electrolyte or during electrocatalysis. This long-term stability enables the in-depth investigation into the electrocatalytic oxygen reduction, and it is further demonstrated that the (Co)PCN222 particle size correlates with its catalytic activity. Of the three particle sizes evaluated (characteristic length scales of 200, 500, and 1000 nm), the smallest size demonstrates the highest mass activity while the largest size has the highest surface area normalized activity. Together these results highlight the importance of determining the structural stability of framework catalysts and provide insights into the important roles of particle size, opening new avenues to investigate and improve the electrocatalytic performance of this class of framework material.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Long-Term Degradation of Passivated Emitter and Rear Contact Silicon Solar Cell under Light and Heat

Advanced designs enable high-efficiency solar cells; however, more complex structures create new long-term stability concerns. Herein, the long-term degradation processes affecting advanced silicon solar cells using laboratory-based illumination and heating over hundreds of hours are investigated. The activation energy for the degradation of voltage is estimated and the degradation rates to normal solar cell operating temperature ranges are extrapolated. The cell degradation observed at high temperatures in the lab is kinetically similar to the process affecting field-deployed modules contributing to 0.37% year-1 of annualized degradation. Electroluminescence and photoluminescence mapping show that the degradation is dominated by minority carrier lifetime reduction. Suns-open-circuit voltage and light beam-induced current results indicate that the degradation could result from passivation degradation at the surface or defect formation in the near-subsurface region, leading to increased minority carrier recombination. This work highlights a long-term degradation process under elevated temperature and illumination that may continue to affect cells in an irreversible manner that is separate from recoverable light-induced degradation and light- and elevated temperature-induced degradation.

14 SOLAR ENERGY↗
DOE OSTI2024

Reducing Ohmic Resistances in Membrane Capacitive Deionization Using Micropatterned Ion-Exchange Membranes, Ionomer Infiltrated Electrodes, and Ionomer-Coated Nylon Meshes

Membrane capacitive deionization (MCDI) is an emerging water desalination platform that is compact, electrified, and does not require high-pressure piping. Herein, highly conductive poly(phenylene alkylene) ion-exchange membranes (IEMs) are micropatterned with different surface geometries for MCDI. The micropatterned membranes increase the interfacial area with the liquid stream leading to a 700 mV reduction in cell voltage when operating at constant current (2 mA cm -2 ; 2000 ppm NaCl feed) while improving the energy normalized adsorbed salt (ENAS) value by 1.4 times. Combining the micropatterned poly(phenylene alkylene) IEMs with poly(phenylene alkylene) ionomer-filled electrodes reduces the cell voltage by 1000 mV and improves the ENAS values by 2.3 times relative to the base case. This reduction in cell voltage allows for higher current density operation (i.e., 3–4 mA cm -2 ) . The reduction in cell voltage is ascribed to the ameliorating ohmic resistances related to ion transport at the membrane-process stream interface and in the carbon cloth electrode. Finally, porous ionic conductors are implemented into the spacer channel with flat and micropatterned IEM configurations and ionomer infiltrated electrodes. For the configuration with flat IEMs, the porous ionic conductor improves ENAS values across the current density regime (2–4 mA cm -2 ), while for micropatterned IEMs it gets improved only at 4 mA cm -2 .

42 ENGINEERING↗
DOE OSTI2021

Numerical investigation of wind turbine wakes under high thrust coefficient

Abstract We study wind turbine wakes of rotors operating at high thrust coefficients ( C T > 24/25) using large‐eddy simulations with a rotating actuator disk model. Wind turbine wakes at high thrust coefficients are different from wakes at low thrust coefficients. Wakes behave differently at high thrust, with increased turbulence and faster recovery. Lower induction in the wake is achieved because wakes in high‐thrust conditions recover much faster than in normal operating conditions. This enhanced recovery is possible thanks to the turbulence generated in the near wake. We explore the mechanism behind this behavior and propose a simple model to reproduce it. We also propose a Gaussian fit for the wakes under high‐thrust conditions and use it use it to initialize an Ainslie type model within the FAST.Farm framework.

FAST.Farm↗
DOE OSTI2023

Predicting wind farm operations with machine learning and the P2D‐RANS model: A case study for an AWAKEN site

Abstract The power performance and the wind velocity field of an onshore wind farm are predicted with machine learning models and the pseudo‐2D RANS model, then assessed against SCADA data. The wind farm under investigation is one of the sites involved with the American WAKE experimeNt (AWAKEN). The performed simulations enable predictions of the power capture at the farm and turbine levels while providing insights into the effects on power capture associated with wake interactions that operating upstream turbines induce, as well as the variability caused by atmospheric stability. The machine learning models show improved accuracy compared to the pseudo‐2D RANS model in the predictions of turbine power capture and farm power capture with roughly half the normalized error. The machine learning models also entail lower computational costs upon training. Further, the machine learning models provide predictions of the wind turbulence intensity at the turbine level for different wind and atmospheric conditions with very good accuracy, which is difficult to achieve through RANS modeling. Additionally, farm‐to‐farm interactions are noted, with adverse impacts on power predictions from both models.

17 WIND ENERGY↗
DOE OSTI2020

ContourNet: Salient Local Contour Identification for Blob Detection in Fusion Plasma Simulation Data

We present ContourNet, a deep learning approach to identify salient local isocontours as blobs in large-scale 5D gyrokinetic tokamak simulation data. Blobs-regions of high turbulence that run along the edge wall down toward the diverter and can damage the tokamak-are non-well-defined features but have been empirically localized by isocontours in 2D normalized fluctuating density fields. The key of our study is to train ContourNet to follow the empirical rules to detect blobs over the time-varying simulation data. The architecture of ContourNet is a convolutional neural segmentation network: the inputs are the density field and a rasterized isocontour; the output is a set of isocontour encircling blobs. At the training stage, we feed the network with manually identified isocontours and propagated labels. At the inference stage, we extract isocontours from the segmented blob regions. Results show that our approach can achieve both high accuracy and performance, which enables scientists to understand the blob dynamics influencing the confinement of the plasma.

Blob detection↗
DOE OSTI2020

Using Low-Cost “Garage Band” Recording Technology for Acquiring High Resolution High-Speed Data

The Oak Ridge National Laboratory (ORNL) has developed and tested a novel system architecture for acquiring high fidelity high-speed data. The approach uses a consumer grade audio recording device that is normally associated with “garage band” recording of music. ORNL has coupled this low-cost data acquisition hardware with computing technology running open-source software. The main advantage of this approach is per-channel cost; an instrument grade data acquisition system typically costs between $800 to $2000 per channel compared to less than $50 per channel for these consumer grade components. Three systems, each featuring four channels, have been deployed for acquiring data from geophones and the electrical supply system that supports the High Flux Isotope Reactor (HFIR) and the Radiochemical Engineering Development Center (REDC) at ORNL. Each channel samples at 96 kHz at 24-bit resolution. The deployed systems operate continuously 24/7 and produce about 4 terabytes of data per month per system. This paper provides a technical overview of this approach, its implementation, and some preliminary results from qualification testing. This work was conducted in support of the Multi-Informatics for Nuclear Operations Scenarios (MINOS).Keywords: Data acquisition Measurement Informatics

Wetherington Jr, G↗
DOE OSTI2022

What is the iε for the S-matrix?

Can the S-matrix be complexified in a way consistent with causality? Since the 1960's, the affirmative answer to this question has been well-understood for 2→2 scattering of the lightest particle in theories with a mass gap at low momentum transfer, where the S-matrix is analytic everywhere except at normal-threshold branch cuts. We ask whether an analogous picture extends to realistic theories, such as the Standard Model, that include massless fields, UV/IR divergences, and unstable particles. Especially in the presence of light states running in the loops, the traditional iε prescription for approaching physical regions might break down, because causality requirements for the individual Feynman diagrams can be mutually incompatible. We demonstrate that such analyticity problems are not in contradiction with unitarity. Instead, they should be thought of as finite-width effects that disappear in the idealized 2→2 scattering amplitudes with no unstable particles, but might persist at higher multiplicity. To fix these issues, we propose an iε -like prescription for deforming branch cuts in the space of Mandelstam invariants without modifying the analytic properties. This procedure results in a complex strip around the real part of the kinematic space, where the S-matrix remains causal. In addition to giving a pedagogical introduction to the analytic properties of the perturbative S-matrix from a modern point of view, we illustrate all the points on explicit examples, both symbolically and numerically. Furthermore, to help with the investigation of related questions, we introduce a number of tools, including holomorphic cutting rules, new approaches to dispersion relations, as well as formulae for local behavior of Feynman integrals near branch points.

Anomalous thresholds↗
DOE OSTI2023

Digital Twins for Nuclear Power Plants and Facilities

The nuclear digital twin (DT) is the virtual representation of a nuclear energy system across its lifecycle. The nuclear DT uses real-time information and other data sources to improve the process of design, licensing, construction, security, O&M, decommissioning, and waste disposal. By leveraging the knowledge base and experience from the past 40 years of LWR operation, the nuclear DT is helping to accelerate the development and deployment of advanced nuclear technology in areas of passive safety, new fuel forms, instrumentation, and reactor control. For the currently operating nuclear fleet, DTs are reducing the operational risks, increasing plant availability, increasing energy capability, and reducing electricity production costs. For advanced fission and fusion reactors, DTs are being used to design for passive safety and built-in security-by-design. Rapidly deployable small modular reactor (SMR) and microreactor designs compatible with modular construction techniques and advanced manufacturing will be the new normal, reducing the need for large capital expenditures and compressing construction schedules. In addition, lower operational and maintenance costs will be realized by reducing the complexity of operations, staffing needs, and maintenance-related activities.

Kropaczek, Dave↗