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At least 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Thermally tunable mid-infrared nanocavity resonance of coupled surface plasmon-phonon polaritons

Phase-change materials (PCMs) are essential for achieving tunability of metasurfaces. However, they frequently face limitations in the long-wave infrared range because of their lossy behavior. Here, we experimentally demonstrate a thermally tunable mid-infrared nanocavity resonance from coupled surface plasmon-phonon polaritons that are supported within a trilayer structure of metal-PCM layer-polar dielectric (Au-VO 2 -SiC). The top metal structures configure the Fabry-Perot cavity resonance near 840 cm −1 (11.9 µm), which is sensitively tunable and reversible with small changes in the VO 2 refractive index ∆n near below its insulator-to-metal phase transition temperature where the loss is small. The maximum resonance shift of 7.7 cm −1 is induced by a small ∆n = 0.3 over a temperature change of 3°C. The tuning figure of merit is comparable to the current standard in photonic modulator applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

SCEC/USGS Community Stress-Drop Validation Study: How Spectral Fitting Approaches Influence Measured Source Parameters

Spectral source parameters used to estimate an earthquake’s stress drop (⁠Δσ⁠) can vary significantly across measurement approaches. The Statewide California Earthquake Center/U.S. Geological Survey Community Stress‐Drop Validation Study was initiated to compare source parameter estimates, focusing initially on a dataset from the 2019 Ridgecrest earthquake sequence. As part of that validation effort, here we focus on one potential source of uncertainty: whether spectral fitting approaches alone, applied to a common set of spectra from the 2019 Ridgecrest sequence result in different source parameter estimates. By using a common set of benchmark spectra analyzed across a consistent frequency band of 1–40 Hz, we eliminate many sources of variability. A subgroup of validation study participants volunteered to estimate the low‐frequency displacement (⁠Ω 0 ⁠) and corner frequency (⁠ƒ c ⁠) by fitting a smooth function to benchmark displacement spectra. Participants used linear‐ or log‐sampled spectra, assumed a Brune or Boatwright spectral model, and applied different misfit criteria. We compare 17 approaches used to estimate ⁠Ω 0 ⁠, ƒ c ⁠, and Δσ for 54 earthquake spectra. Our results reveal that 35% of events have Δσ estimates within a factor of two, whereas others exhibit variations exceeding an order of magnitude. The variability in and can largely be attributed to whether a spectrum is consistent with the smooth function of an idealized simple crack model. The trade‐off between Ω 0 and ƒ c may be more pronounced when using linearly sampled spectra, as higher frequency spectral bumps control the fits. As expected, methods that assumed a Boatwright model tended to have lower Ω 0 and somewhat higher ƒ c compared to those assuming a Brune model, although resulting Δσ estimates are similar. Finally, when compared to the overall validation study results, the fitting approach alone may account for between 5% and 90% (25% on average) of the total variability in spectral Δσ⁠.

58 GEOSCIENCES↗
DOE OSTI2025

Overview of the SCEC/USGS Community Stress Drop Validation Study Using the 2019 Ridgecrest Earthquake Sequence

We present initial findings from the ongoing Community Stress Drop Validation Study to compare spectral stress-drop estimates for earthquakes in the 2019 Ridgecrest, California, sequence. This study uses a unified dataset to independently estimate earthquake source parameters through various methods. Stress drop, which denotes the change in average shear stress along a fault during earthquake rupture, is a critical parameter in earthquake science, impacting ground motion, rupture simulation, and source physics. Spectral stress drop is commonly derived by fitting the amplitude-spectrum shape, but estimates can vary substantially across studies for individual earthquakes. Sponsored jointly by the U.S. Geological Survey and the Statewide (previously, Southern) California Earthquake Center our community study aims to elucidate sources of variability and uncertainty in earthquake spectral stress-drop estimates through quantitative comparison of submitted results from independent analyses. The dataset includes nearly 13,000 earthquakes ranging from M 1 to 7 during a two-week period of the 2019 Ridgecrest sequence, recorded within a 1° radius. Here, in this article, we report on 56 unique submissions received from 20 different groups, detailing spectral corner frequencies (or source durations), moment magnitudes, and estimated spectral stress drops. Methods employed encompass spectral ratio analysis, spectral decomposition and inversion, finite-fault modeling, ground-motion-based approaches, and combined methods. Initial analysis reveals significant scatter across submitted spectral stress drops spanning over six orders of magnitude. However, we can identify between-method trends and offsets within the data to mitigate this variability. Averaging submissions for a prioritized subset of 56 events shows reduced variability of spectral stress drop, indicating overall consistency in recovered spectral stress-drop values.

58 GEOSCIENCES↗
DOE OSTI2025

Simulating High-Frequency Seismograms in Realistic Earth Models to Better Understand Source Discrimination Based on Differential Magnitudes ( M L− M c)

Discriminating low-yield underground nuclear explosions from small earthquakes is a key task in monitoring nuclear test ban treaties. P/S amplitude ratios have been an effective discriminant for moderate-sized events recorded at regional distances, but it is unclear if they are as effective in discriminating small seismic events recorded at local distances (<150 km). The difference between local magnitude (M L ) and coda duration magnitude (M c ) has been proposed as a new discriminant that may complement P/S amplitude ratios at local distances. Here, in this work, we calculate high-frequency (up to ∼4 Hz) synthetic seismograms at epicentral distances of 0–30 km in realistic models of the Salt Lake basin (Utah, United States) to better understand how variations in source type and depth affect M L −M c values. The Earth models incorporate simplified 1D and deterministic 3D structures, small-wavelength stochastic velocity perturbations, and surface topography. Coda waves are enhanced for the more complicated models compared to the base 1D model, but still underpredict observed durations by about a factor of two, which results in overprediction of amplitude to duration ratios (i.e., M L −M c values) for a near-surface explosion and a 7 km deep earthquake. For both source types, the predicted M L and M c values decrease as source depth increases, and M L −M c shows only minor variation with depth; however, M L −M c is on average ∼0.5 units smaller for explosions than earthquakes. This finding may imply that M L −M c has sensitivity to source type, in addition to being a depth discriminant, but more modeling is needed given the limitations of the current study. Future modeling should incorporate higher-frequency (≳5 Hz) simulations over a larger distance range (0–150 km), where M L and M c are commonly measured, while honoring low shear velocities (<300 m/s) near the surface and sampling a wider range of earthquake and explosion source mechanisms.

Hutchings, Sean J. [Univ. of Utah, Salt Lake City,↗
DOE OSTI2025

The future of the correlated electron problem

A central problem in modern condensed matter physics is the understanding of materials with strong electron correlations. Despite extensive work, the essential physics of many of these systems is not understood and there is very little ability to make predictions in this class of materials. In this manuscript we share our personal views on the major open problems in the field of correlated electron systems. We discuss some possible routes to make progress in this rich and fascinating field. This manuscript is the result of the vigorous discussions and deliberations that took place at Johns Hopkins University during a three-day workshop January 27, 28, and 29, 2020 that brought together six senior scientists and 46 more junior scientists. Our hope, is that the topics we have presented will provide inspiration for others working in this field and motivation for the idea that significant progress can be made on very hard problems if we focus our collective energies.

Alexandradinata, Aris [Univ. of Illinois at Urbana↗
DOE OSTI2020

Evaluation of ASCE 4-16 and AISC 43-18 (Draft) for use in the Risk-Informed Performance-Based Seismic Design of Nuclear Power Plant Structures, Systems, and Components

This report describes the assessment of ASCE Standards 4-16 and 43-18 (Draft) for use in the Risk-Informed Performance-Based (RIPB) seismic design of structures, systems, and components (SSCs) at nuclear power plants. This work was performed for the U.S. Nuclear Regulatory Commission (NRC) Office of Regulatory Research (RES), to support potential endorsement of these industry standards for the design of nuclear power plants based on the RIPB approach. Currently, the NRC endorses a deterministic design approach for demonstrating the design adequacy of SSCs based on the Standard Review Plan (NUREG-0800) and NRC Regulatory Guides. In the RIPB approach, the design criteria are developed to achieve a target performance goal, which is defined by the annual frequency of occurrence of the design basis earthquake (i.e., Seismic Design Category) and the acceptable level of structural performance (i.e., Limit State) for the SSCs. ASCE 4-16 provides methods for performing a seismic analysis of structures to obtain the seismic response of these structures (e.g., building displacements, accelerations, in-structure response spectra) which are used in the design of the SSCs. It also provides methods for performing seismic analysis of SSCs to determine the seismic demands (e.g. member forces and displacements) needed to design individual SSCs. ASCE 43-18 (Draft) provides the criteria for the seismic design of SSCs using the seismic demands developed in ASCE 4-16. The use of ASCE Standard 43-18 (Draft), along with ASCE 4-16, provides the criteria for the seismic design of the SSCs. ASCE 43-18 (DRAFT) relies on other consensus codes and standards such as ACI 349 for reinforced concrete, AISC/N690 for steel structures, ASME Section III for pressure-retaining mechanical components and Containments, and IEEE-344 for Class 1E equipment. The goal of this technical review was to assess the adequacy of the provisions in these standards for use by the NRC in developing regulatory guidance for design of SSCs in nuclear power plants, based on the RIPB approach. The research reported herein describes the basis for acceptance of the new standards and identifies areas where additional staff guidance is needed for the seismic design of SSCs at nuclear power plants. This technical review has determined that ASCE 4-16 and ASCE 43-18 (Draft) provide an appropriate framework for the seismic design of SSCs at nuclear power plants using a Risk-Informed Performance-Based approach. However, some of the criteria therein warrant exceptions, qualifications, and/or clarifications.

42 ENGINEERING↗
DOE OSTI2021

S0 Uncrewed Aircraft System Measurement Characterization Field Campaign Report

The lower atmosphere contributes directly to the modulation of weather and climate. Understanding the importance of this part of the atmosphere, scientists have worked to improve the representation of the atmospheric boundary layer in numerical prediction tools. Such work depends upon information from observing systems, including remote sensors, weather balloons, and research aircraft. Recent years have seen significant advances in uncrewed aircraft systems (UAS) for atmospheric research. Those efforts have provided new perspectives on atmospheric and surface conditions, particularly from smaller UAS (sUAS) platforms. This field campaign included collection of data using several sUAS, and comparing the sUAS data to those from different observing facilities at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility’s Southern Great Plains (SGP) observatory in Oklahoma. Over the course of one week, the Black Swift Technologies and University of Nebraska teams conducted flights for the sole purpose of system evaluation and intercomparison. In addition, these teams conducted joint flight operations at the Marshall, Oklahoma Mesonet site alongside teams from the University of Colorado, University of Oklahoma, and Oklahoma State University to collect additional data for side-by-side comparison. Platforms operated by Black Swift Technologies and the University of Nebraska under this project included one fixed-wing and two rotary-wing platforms, as well as an instrumented surface vehicle. These include the Black Swift Technologies S0 UAS, the University of Nebraska M600 UAS, a University of Nebraska-operated Meteomatics Meteodrone UAS, and the University of Nebraska CoMeT (Combined Mesonet and Tracker) vehicle. Additional details on all of these platforms can be found in de Boer et al. (in prep). In total, 95 sUAS flights were conducted for a combined total of 18.6 flight hours. The S0 was operated both to the south and north of the SGP 60 m tower, while the M600 and Meteodrone were operated directly to the east of the tower. Weather conditions were generally good, with moderate winds. Flights were conducted both to follow the extra radiosondes that were launched as part of this campaign, as well as to conduct extended statistical sampling at tower instrument heights. The later flights also provided data for statistical platform intercomparison.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Raman Spectroscopy to Detect and Measure NOW Pheromones. Annual Report [Jan 2021]

Insect sex pheromones are chemical compounds that insects release to attract their partners over distances of hundreds of meters or even kilometers, in complete darkness and without any audible signals. Use of synthetic forms of key compounds have in some cases become an essential component of monitoring and/or managing key pests of agricultural crops, including navel orangeworm (Amyelois transitella) (NOW) in California tree nuts. These pheromone-based strategies can include monitoring, mating disruption, mass trapping, attract-and-kill and push-pull. There are currently multiple commercially available mating disruption products available for NOW and recent studies have demonstrated that they can be effectively used to reduce crop damage by this pest. Just how mating disruption works is not fully established and likely varies across products and target species. For instance, the extent to which synthetic pheromones compete with natural pheromone is not well understood, or in the case of monitoring, how efficaciously the insect follows the diffusing plumes, especially across large blocks and at plot borders. Furthermore, there may be specific conditions under which poor or impeded diffusion of synthetic pheromone diminishes the disruption effect, which could result in some males effectively locating females for reproduction. At the same time, many commercially available synthetic lures are also available, and growers have been effectively using them to track population development – although the attractive range of these lures remains unclear. That is, while pheromone lures can attract many moths, the relationship between trap capture and local populations, much less crop damage, remains unclear.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Raman Spectroscopy to Detect and Measure NOW Pheromones. Annual Report [2021]

Insect sex pheromones are chemical compounds that insects release to attract mates over distances of hundreds of meters or even kilometers, in complete darkness and without any audible signals. Use of synthetic forms of key compounds have in some cases become an essential component of monitoring and/or managing key pests of agricultural crops, including navel orangeworm (Amyelois transitella) (NOW) in California tree nuts There are currently multiple commercially available mating disruption products available for NOW and recent studies have demonstrated that they can be effectively used to reduce crop damage. How mating disruption works is not fully established and likely varies across products and target species. For instance, it is not well understood how synthetic pheromones compete with natural pheromones and, in the case of monitoring, how efficaciously the insect follows the diffusing plumes and how those evolve from emission points, especially across large blocks and at plot borders. We proposed to evaluate the use of enhanced Raman spectroscopy for the detection of synthetic and natural NOW pheromones and, were that to be successful, use it in subsequent years to measure pheromone diffusion in orchards.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Raman Spectroscopy to Detect and Measure NOW Pheromones. Annual Report [Dec 2021]

Insect sex pheromones are chemical compounds that insects release to attract mates over distances of hundreds of meters or even kilometers, in complete darkness and without any audible signals. Use of synthetic forms of key compounds have in some cases become an essential component of monitoring and/or managing key pests of agricultural crops, including navel orangeworm (Amyelois transitella) (NOW) in California tree nuts There are currently multiple commercially available mating disruption products available for NOW and recent studies have demonstrated that they can be effectively used to reduce crop damage. How mating disruption works is not fully established and likely varies across products and target species. For instance, it is not well understood how synthetic pheromones compete with natural pheromones and, in the case of monitoring, how efficaciously the insect follows the diffusing plumes and how those evolve from emission points, especially across large blocks and at plot borders. We proposed to evaluate the use of enhanced Raman spectroscopy for the detection of synthetic and natural NOW pheromones and, were that to be successful, use it in subsequent years to measure pheromone diffusion in orchards.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Raman Spectroscopy to Detect and Measure NOW Pheromones

Insect sex pheromones are chemical compounds that insects release to attract mates over distances of hundreds of meters or even kilometers, in complete darkness and without any audible signals. Use of synthetic forms of key compounds have in some cases become an essential component of monitoring and/or managing key pests of agricultural crops, including navel orangeworm (Amyelois transitella) (NOW) in California tree nuts. There are currently multiple commercially available mating disruption products available for NOW and recent studies have demonstrated that they can effectively help reducing crop damage. How mating disruption works is not fully established and likely varies across products and target species. For instance, it is not well understood how synthetic pheromones compete with natural ones and, in the case of monitoring, how efficaciously the insect follows the diffusing plumes and how those evolve from emission points, especially across large blocks and at plot borders.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Raman Spectroscopy to Detect and Measure NOW Pheromones ("Orchard in a box")

Insect sex pheromones are chemical compounds that insects release to attract mates over distances of hundreds of meters or even kilometers, in complete darkness and without any audible signals. Use of synthetic forms of key compounds have in some cases become an essential component of monitoring and/or managing key pests of agricultural crops, including navel orangeworm (Amyelois transitella) (NOW) in California tree nuts. There are currently multiple commercially available mating disruption products available for NOW and recent studies have demonstrated that they can be effectively used to reduce crop damage. How mating disruption works is not fully established and likely varies across products and target species. For instance, it is not well understood how synthetic pheromones compete with natural pheromones and, in the case of monitoring, how efficaciously the insect follows the diffusing plumes, especially across large blocks and at plot borders. Whether an aerosol puffer is used for mating disruption or lure for monitoring population development, we currently lack the ability to fully understand how these synthetic pheromone compounds diffuse away from their point-source of emission – and subsequently how this might affect the efficacy of mating disruption and/or the accuracy of monitoring efforts. In response to these unknowns, Raman spectroscopy may offer a way to detect synthetic pheromone because of its analytical properties and recent technological advancements. In combination with nanostructured probes, RS has demonstrated the capability to detect volatiles at extremely low concentrations. We proposed to evaluate the use of Raman for the detection of synthetic and natural NOW pheromones and, were that to be successful, use this tool in subsequent years to measure pheromone diffusion in orchards.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Developing an intrinsically secure information barrier for arms control verification through machine learning

Near-term solutions are needed to allow for flexible engagement in future nuclear arms control discussions. This project developed a method for implementing an information barrier (IB) on commercial systems, shortening the research and development lifecycle for warhead verification technologies while offering improved and inherently flexible capabilities. The crux of the verification challenge remains the difficulty in developing an authenticatable IB which prevents sensitive host country information from inadvertent transmission to an inspector. Many concepts for IB’s rely on dedicated “trusted” processor modules developed with dedicated custom radiation detection systems and associated algorithms. Without a priori knowledge of the treaty item, the parameter space for measurements can be nearly infinite and robustness against spoofing without the ability to view sensitive data is key. This project has produced an unclassified framework capable of ingesting data from common gamma detectors and identifying the presence of weapons grade nuclear material at over 90% accuracy.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2024

Implementation of Detailed Polyethylene Pyrolysis Kinetics into CFD Simulations using Machine Learning

Municipal solid waste (MSW) and waste plastics have received significant attention due to the issues of waste generation and storage, as well as their potential as an energy resource. High-density polyethylene (HDPE) makes up a large portion of plastic waste and has been the subject of several conversion studies. However, the mechanisms associated with converting HDPE through pyrolysis and gasification are extensive and complex making them difficult to implement into high-fidelity computational fluid dynamic (CFD) simulations. For this project, a primary pyrolysis mechanism containing 42 unique species and 737 heterogeneous reactions was used to generate kinetic data over a range of operating conditions. A machine learning (ML) model was developed to replicate the results of the detailed pyrolysis mechanism while significantly increasing the computational efficiency. A deep operator network (DeepONet) architecture was adopted to train the model using time steps relevant to CFD simulations. The ML used physics-based loss functions to ensure mass conservation. The ML model has been deployed in simple MFiX CFD simulations, single particle, and an experimental drop tube reactor, and has shown promising performance compared to the original scheme.

Houston, Ross↗
DOE OSTI2024

Development of a machine learning model for polyethylene pyrolysis using a detailed reaction mechanism

Waste plastics have recently received significant attention as the issue of waste generation continues to increase. Thermal conversion processes, such as pyrolysis and gasification, are attractive potential technologies for utilizing waste plastics and reducing overall waste generation. Efficient utilization of plastics requires a detailed understanding of the conversion process such as pyrolysis and gasification. However, a mechanistic understanding of these processes lead to large and complex kinetic schemes that are not suited for large-scale and long-time simulation methods. Currently, most modeling approaches for pyrolysis and gasification rely on globally lumped, simplified kinetic schemes that provide results that are classified by their product type and not individual species, which limit the level of fidelity achieved via modeling. A machine learning (ML) model has been developed for the primary reactions of high-density polyethylene (HDPE) in an attempt to increase computational efficiency while still maintaining a high level of detail and accuracy. The ML model is trained on a detailed reaction mechanism containing 42 total species and 737 chemical reactions. A DeepONet branch and trunk architecture was adopted to train the model using time-steps relevant to computational fluid dynamics simulations. The ML used physics-informed loss functions to ensure mass conservation. The surrogate model has been deployed in simple MFiX CFD simulations, single particle and an experimental drop tube reactor, and has shown promising performance compared to the original scheme.

Houston, Ross↗