Search NASA⌕ Search

SEARCH · Search NASA

Results for “Frequency extraction”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Resolving Discrepancies in Spin-Torque Ferromagnetic Resonance Measurements: Lineshape versus Linewidth Analyses

When spin-orbit torques are measured using spin-torque ferromagnetic resonance, two alternative ways of analyzing the results to extract the torque efficiencies—lineshape analysis and analysis of the change in linewidth versus direct current—often give inconsistent results. We identify a source for these inconsistencies. We show that fits of spin-torque ferromagnetic resonance data to the standard analysis framework leave significant residuals that we identify as due to (i) current-induced excitations of a small volume of magnetic material with magnetic damping much larger than that of the bulk of the magnetic layer, which we speculate is associated with the heavy-metal–magnet interface and (ii) oscillations of the sample magnetization at the modulation frequency due to heating. Here, the dependence of the residual signals on direct current can interfere with an accurate extraction of spin-torque efficiencies by the linewidth method. We show that the discrepancies between the two types of analysis can be largely eliminated by extrapolation of the window of magnetic fields used in the linewidth fits to small values so as to minimize the influence of the residual signals.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Increased flood exposure in the Pacific Northwest following earthquake-driven subsidence and sea-level rise

Climate-driven sea-level rise is increasing the frequency of coastal flooding worldwide, exacerbated locally by factors like land subsidence from groundwater and resource extraction. However, a process rarely considered in future sea-level rise scenarios is sudden (over minutes) land subsidence associated with great (>M8) earthquakes, which can exceed 1 m. Along the Washington, Oregon, and northern California coasts, the next great Cascadia subduction zone earthquake could cause up to 2 m of sudden coastal subsidence, dramatically raising sea level, expanding floodplains, and increasing the flood risk to local communities. Here, we quantify the potential expansion of the 1% floodplain (i.e., the area with an annual flood risk of 1%) under low (~0.5 m), medium (~1 m), and high (~2 m) earthquake-driven subsidence scenarios at 24 Cascadia estuaries. If a great earthquake occurred today, floodplains could expand by 90 km 2 (low), 160 km 2 (medium), or 300 km 2 (high subsidence), more than doubling the flooding exposure of residents, structures, and roads under the high subsidence scenario. By 2100, when climate-driven sea-level rise will compound the hazard, a great earthquake could expand floodplains by 170 km 2 (low), 240 km 2 (medium), or 370 km 2 (high subsidence), more than tripling the flooding exposure of residents, structures, and roads under the high subsidence scenario compared to the 2023 floodplain. Our findings can support decision-makers and coastal communities along the Cascadia subduction zone as they prepare for compound hazards from the earthquake cycle and climate-driven sea-level rise and provide critical insights for tectonically active coastlines globally.

Science & Technology - Other Topics↗
DOE OSTI2025

Revealing rotational symmetry breaking charge density wave order in the kagome superconductor (Rb, K)⁢V 3 ⁢Sb 5 by ultrafast pump-probe experiments

The recently discovered Kagome superconductor 𝐴⁢V 3 ⁢Sb 5 (where 𝐴 refers to K, Rb, Cs) has stimulated widespread research interest due to its interplay of nontrivial topology and unconventional correlated physics including charge-density waves (CDW) and superconductivity. The essential prerequisite to understanding the microscopic mechanisms of this complex electronic landscape is to unveil the configuration and symmetry of the charge-density wave order. As to now, little consensus has been made on what symmetry is broken. Herein, we clarify the microscopic structure and symmetry breaking of the CDW phase in RbV 3 ⁢Sb 5 and KV 3 ⁢Sb 5 by ultrafast time-resolved reflectivity. Our approach is based on extracting coherent phonon spectra induced by three-dimensional CDW and comparing them to calculated phonon frequencies via density-functional theory. The combination of these experimental results and calculations provides compelling evidence that the CDW structure of both compounds prevailing up to 𝑇 CDW is the 2 × 2 × 2 staggered inverse Star-of-David pattern with interlayer 𝜋 phase shift, in which the sixfold rotational symmetry is broken. Finally, these observations thus corroborate sixfold rotational symmetry breaking throughout the CDW phase of RbV 3 ⁢Sb 5 and KV 3⁢ Sb 5 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

High-precision mass measurements of the isomeric and ground states of 44 V: Improving constraints on the isobaric multiplet mass equation parameters of the A=44, 0 + quintet

Background: The quadratic isobaric multiplet mass equation (IMME) has been very successful at predicting the masses of isobaric analog states in the same multiplet, while its coefficients are known to follow specific trends as functions of mass number. The Atomic Mass Evaluation 2016 [Chin. Phys. C 41, 030003 (2017)] 44 V mass value results in an anomalous negative c coefficient for the IMME quadratic term; a consequence of large uncertainty and an unresolved isomeric state. The b and c coefficients can provide useful constraints for construction of the isospin-nonconserving Hamiltonians for the pf shell. In addition, the excitation energy of the 0 + , T = 2 level in 44 V is currently unknown. This state can be used to constrain the mass of the more exotic 44 Cr. Purpose: The aim of the experimental campaign was to perform high-precision mass measurements to resolve the difference between 44 V isomeric and ground states, to test the IMME using the new ground state mass value and to provide necessary ingredients for the future identification of the 0 + , T = 2 state in 44 V. Method: High-precision Penning trap mass spectrometry was performed at LEBIT, located at the National Superconducting Cyclotron Laboratory, to measure the cyclotron frequency ratios of [ 44g,m VO] + versus [ 32 SCO] + , a well-known reference mass, to extract both the isomeric and ground state masses of 44 V. Results: The mass excess of the ground and isomeric states in 44 V were measured to be -23 804.9(80) keV/c 2 and -23 537.0(55) keV/c 2 , respectively. This yielded a new proton separation energy of S p = 1 773(10) keV. Conclusion: The new values of the ground state and isomeric state masses of 44 V have been used to deduce the IMME b and c coefficients of the lowest 2 + and 6 + triplets in A = 44. The 2 + c coefficient is now verified with the IMME trend for lowest multiplets and is in good agreement with the shell-model predictions using charge-dependent Hamiltonians. The mirror energy differences were determined between 44 V and 44 Sc, in line with isospin-symmetry for this multiplet. Finally, the new value of the proton separation energy determined, to an uncertainty of 10 keV, will be important for the determination of the 0 + , T = 2 state in 44 V and, consequently, for prediction of the mass excess of 44 Cr.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Simultaneous real-time measurement of composition, flow, attenuation, density, and pipe-wallthickness in multiphase fluids

Apparatus (10) and methods for making simultaneous measurements of composition (water-cut), fluid flow, and sound attenuation in a multiphase fluid flowing (15) through a pipe (12) in real-time, using the same apparatus (10) are described. Additionally, the apparatus (10) provides real-time pipe wall thickness monitoring for observing pipe corrosion or internal deposition. Knowledge of wall thickness is necessary to correct for water-cut (oil-water composition) automatically by adjusting the liquid path length internal to the pipe (spool). The use of short duration frequency chirp excitation signals (24) enables the apparatus to provide information that can be used to extract multiple levels of information from the same measurement in multiphase fluids including the presence of a significant quantity of gas (˜60% gas volume fraction) in different flow regimes. Besides measuring steady flow, this device is useful for measurements during fast changing flows, such as for a rod-pumped well. Measurements up to about 1000 times a second can reliably be made.

Sinha, Dipen N.↗
DOE OSTI2022

Thiocyanate Ions Form Antiparallel Populations at the Concentrated Electrolyte/Charged Surfactant Interface

Anions play significant roles in the separation of lanthanides and actinides. The molecular-scale details of how these anions behave at aqueous interfaces are not well understood, especially at high ionic strengths. Here, we describe the interfacial structure of thiocyanate anions at a soft charged interface up to 5 M bulk concentration with combined classical and phase-sensitive and molecular dynamics (MD) simulations. At low concentrations thiocyanate ions are mostly oriented with their sulfur end pointing toward the charged surfactants. In this work, the VSFG signal reaches a plateau at around 100 mM bulk concentration, followed by significant changes above 1 M. At high concentrations a new thiocyanate population emerges with their sulfur end pointing toward the bulk liquid. The –CN stretch frequency is different for up and down oriented SCN – ions, indicating different coordination environments. These results provide key molecular-level insights for the interfacial behavior of complex anions in highly concentrated solutions.

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

Progressive transfer learning for low-frequency data prediction in full waveform inversion

To effectively overcome the cycle-skipping issue in full waveform inversion (FWI), we developed a deep neural network (DNN) approach to predict the absent low-frequency components by exploiting the hidden physical relation connecting the low- and the high-frequency data. To efficiently solve this challenging nonlinear regression problem, two novel strategies were proposed to design the DNN architecture and to optimize the learning process: (1) dual data feed structure; (2) progressive transfer learning. With the dual data feed structure, not only the high-frequency data, but also the corresponding beat tone data are fed into the DNN to relieve the burden of feature extraction. The second strategy, progressive transfer learning, enables us to train the DNN using a single evolving training dataset. Within the framework of the progressive transfer learning, the training dataset continuously evolves in an iterative manner by gradually retrieving the subsurface information through the physics-based inversion module, progressively enhancing the prediction accuracy of the DNN and propelling the inversion process out of the local minima. Here, the synthetic numerical experiments suggest that, without any a priori geological information, the low-frequency data predicted by the progressive transfer learning are sufficiently accurate for an FWI engine to produce reliable subsurface velocity models free of cycle-skipping artifacts.

02 PETROLEUM↗
DOE OSTI2020

Predicting molecular dipole moments by combining atomic partial charges and atomic dipoles

The molecular dipole moment ( μ ) is a central quantity in chemistry. It is essential in predicting infrared and sum-frequency generation spectra as well as induction and long-range electrostatic interactions. Furthermore, it can be extracted directly—via the ground state electron density—from high-level quantum mechanical calculations, making it an ideal target for machine learning (ML). Here, we choose to represent this quantity with a physically inspired ML model that captures two distinct physical effects: local atomic polarization is captured within the symmetry-adapted Gaussian process regression framework which assigns a (vector) dipole moment to each atom, while the movement of charge across the entire molecule is captured by assigning a partial (scalar) charge to each atom. The resulting “MuML” models are fitted together to reproduce molecular μ computed using high-level coupled-cluster theory and density functional theory (DFT) on the QM7b dataset, achieving more accurate results due to the physics-based combination of these complementary terms. The combined model shows excellent transferability when applied to a showcase dataset of larger and more complex molecules, approaching the accuracy of DFT at a small fraction of the computational cost. We also demonstrate that the uncertainty in the predictions can be estimated reliably using a calibrated committee model. The ultimate performance of the models—and the optimal weighting of their combination—depends, however, on the details of the system at hand, with the scalar model being clearly superior when describing large molecules whose dipole is almost entirely generated by charge separation. These observations point to the importance of simultaneously accounting for the local and non-local effects that contribute to μ ; furthermore, they define a challenging task to benchmark future models, particularly those aimed at the description of condensed phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Probing specific ion effects at air-aqueous dibutyl phosphate interfaces using vibrational sum frequency generation spectroscopy

Molecular properties at air–liquid and liquid–liquid interface hold the key to many processes involving molecular transport across phase boundaries from aerosol formation to carbon cycling and material separation using solvent extraction techniques. Using dibutyl phosphate (DBP) as a representative for partially aqueous soluble surfactants, the specific ion effect (SIE) of the Hofmeister series cations Cs + , Na + , Li + , and Mg 2+ on the partition and interaction between surfactant molecules and water molecules in the air–aqueous interface are investigated using vibrational sum frequency generation spectroscopy and surface tension measurements. In the presence of 1 mM and 1M bulk aqueous phase ionic strength salt concentrations, fundamental qualitative relationships are observed for the salting out of DBP relative to bulk aqueous phase nitrate salt concentrations and the specific cations species. At 1 mM ionic strength, the interfacial charge and hence the interfacial potential modulates the electrostatic interactions; in particular, the counter cations partially screen the negatively charged interface induced by the DBP in a direct Hofmeister order. At 1M ionic strength, the electric field at the interface or interfacial potential is effectively neutralized, and the counter cations promote the partitioning of DBP to the interface depending on their specific interaction with the DBP head group and metal ion hydration properties. The present results lay a foundation to study SIEs of heavier metals on hydrophobic-aqueous DBP interfaces.

Louie, Christina [Washington State University, Pul↗
DOE OSTI2022

Laser Doppler vibrometry for piezoelectric coefficient ($d_{33}$) measurements in irradiated aluminum nitride

Sensors used for experiments in advanced reactors must survive in harsh environments. Few material systems can be used to construct sensors viable for extreme conditions. Aluminum nitride (AlN) is one such material because it has high thermal stability and radiation resistance and sustains good piezoelectric and dielectric properties at high temperatures. In this work, the piezoelectric coefficient $d_{33}$ of the AlN single-crystal with thermal and irradiation damage was investigated using an indirect method with a laser Doppler vibrometer (LDV). Surface electrodes were deposited on the AlN samples, and the vibration response of the samples to an applied voltage was monitored using the LDV as a function of the excitation frequency. The $d_{33}$ estimation was based on the excitation voltage and the thickness-mode displacement extracted from the LDV measurements. Further, six AlN substrates were irradiated with 8 MeV Al 2+ at three fluences (10 15 , 10 16 , and 10 17 ions/cm 2 ) and two temperatures (300 °C and 500 °C). The $d_{33}$ for the six irradiated samples and one pristine sample were measured, and the measurement uncertainty was estimated based on five repeated tests. All samples were also measured by a commercial piezometer for comparison. The experimental results demonstrate that the piezoelectric coefficients obtained by LDV were about 0.8–1.16 pm/V lower than those obtained by the piezometer. With the compensation of the clamping effect, the corrected LDV values are similar to the piezometer results. Both show similar trends in all samples, which validates the feasibility of the proposed method for $d_{33}$ measurement. Based on the LDV results, the irradiated samples show a 12%–22% decrease in $d_{33}$ compared with the pristine samples. The samples irradiated under the same fluence at a higher temperature (500 °C) demonstrated a lower $d_{33}$ than those at 300 °C. The effect of the retro-reflective tape, sample temperature, and sample size on the $d_{33}$ measurement were also studied.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Alpha particle channeling in ITER

Alpha particle channeling, the attempt to extract energy from high-energy fusion alpha particles using a combination of high- and low-frequency waves introduced in the plasma with antennae, is studied using a guiding center code. We examine the effect of the combination of cooling caused by a cyclotron mode, particle diffusion due to Alfvén modes introduced for ash removal, the inclusion of microturbulent diffusion, and the slowing down of the alpha particles on electrons. Induced cooling is achieved with a cyclotron resonance, producing additional losses of particles above 3.5 MeV in an amount about equal to the prompt loss. The removal of the low-energy cooled particles by additional modes or by microturbulent diffusion is the hardest challenge for alpha channeling. The cooled alpha particles remain deep in the plasma center, so for this removal, the method used must be capable of providing transport from the plasma center to the edge without also causing losses of high-energy particles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Balance of Plant Modeling and Real-Time Hardware-in-the-Loop Integration with the Microreactor Automated Control System

The advent of novel microreactor technology has driven a focused effort to explore safety and efficiency improvements that can be achieved through the use of automated system control. Development of control strategies, especially for initial demonstration, requires an adequate surrogate environment to safely research failure modes and control integration with realistic hardware delay. However, efficiency gains from control strategies are improved when the scope of controller action is expanded to include system-level dynamics such as downstream heat extraction and mass flow. For this reason, a balance-of-plant (BOP) model of a representative microreactor system has been developed using the TRANsient Simulation Framework of Reconfigurable Models library in Modelica. This model captures a reactor and primary NaK coolant loop that represent corresponding system components of the Microreactor Applications Research Validation and EvaLuation (MARVEL) design as well as a secondary coolant loop and heat extraction representative of the Microreactor Agile Non-Nuclear Experimental Test Bed (MAGNET). This model configuration allows for hardware-in-the-loop (HIL) integration with microreactor automated control system (MACS) hardware in real time through a Python-based gRPC client. Real-time simulation of model performance with emulated hardware and communication delay suggests that under independent proportional-integral-derivative control of BOP model drum dynamics and downstream heat extraction, stable power load following is achievable. A slight delay in load following, filtering of high-frequency dynamics, and localized temperature fluctation suggest room for improvement through the development of higher-level control strategies. The simulated coupling of the MAGNET facility lays the groundwork for future digital twin analysis with a coupled MACS-MAGNET HIL demonstration.

McConnell, Jono [ORNL] (ORCID:0000000238984741)↗
DOE OSTI2022

Cross-correlation spectra in interacting quantum dot systems

Two-color spin-noise spectroscopy of interacting electron spins in singly charged semiconductor quantum dots provides information on the interquantum dot interactions. We investigate the spin cross-correlation function in a quantum dot ensemble employing a modified semiclassical approach. Spin-correlation functions are calculated using a Hamilton quaternion approach that maintains local quantum mechanical properties of the spins. This method takes into account the effects of the nuclear-electric quadrupolar interactions, the randomness of the coupling constants, and the variation of the electron g factor on the spin-noise power spectra. We demonstrate that the quantum dot ensemble can be mapped on an effective two-quantum dot problem and discuss how the characteristic length scale of the interdot interaction modifies the low-frequency cross-correlation spectrum. Here, we argue that details on the interaction strength distribution can be extracted from the cross-correlation spectrum when applying a longitudinal or a transversal external magnetic field.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Low power and privacy preserving sensor platform for occupancy detection

A low-cost, low-power, stand-alone sensor platform having a visible-range camera sensor, a thermopile array, a microphone, a motion sensor, and a microprocessor that is configured to perform occupancy detection and counting while preserving the privacy of occupants. The platform is programmed to extract shape/texture from images in spatial domain; motion from video in time domain; and audio features in frequency domain. Embedded binarized neural networks are used for efficient object of interest detection. The platform is also programmed with advanced fusion algorithms for multiple sensor modalities addressing dependent sensor observations. The platform may be deployed for (i) residential use in detecting occupants for autonomously controlling building systems, such as HVAC and lighting systems, to provide energy savings, (ii) security and surveillance, such as to detect loitering and surveil places of interest, (iii) analyzing customer behavior and flows, (iv) identifying high performing stores by retailers.

Velipasalar, Senem↗
DOE OSTI2023

Microscale Imaging of Thermal Conductivity Suppression at Grain Boundaries

Abstract Grain‐boundary engineering is an effective strategy to tune the thermal conductivity of materials, leading to improved performance in thermoelectric, thermal‐barrier coatings, and thermal management applications. Despite the central importance to thermal transport, a clear understanding of how grain boundaries modulate the microscale heat flow is missing, owing to the scarcity of local investigations. Here, thermal imaging of individual grain boundaries is demonstrated in thermoelectric SnTe via spatially resolved frequency‐domain thermoreflectance. Measurements with microscale resolution reveal local suppressions in thermal conductivity at grain boundaries. Also, the grain‐boundary thermal resistance – extracted by employing a Gibbs excess approach – is found to be correlated with the grain‐boundary misorientation angle. Extracting thermal properties, including thermal boundary resistances, from microscale imaging can provide comprehensive understanding of how microstructure affects heat transport, crucially impacting the materials design of high‐performance thermal‐management and energy‐conversion devices.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Predicting battery capacity from impedance at varying temperature and state of charge using machine learning

Prediction of battery health from electrochemical impedance spectroscopy (EIS) data can enable rapid measurement of battery state in real-world applications without using additional sensors or time-consuming performance measurements. However, deconvoluting the effect of capacity, state of charge, and temperature on EIS response is complicated analytically. Here, various machine-learning models, such as linear, Gaussian process, random forest, and artificial neural network regression, are utilized to predict capacity from EIS using hundreds of capacity, direct current (DC) resistance, and EIS measurements recorded under varying conditions of health, temperature, and state of charge (SOC). Several feature extraction and selection methods from traditional electrochemical analysis and statistical modeling are explored using machine-learning pipelines. EIS data from just two frequencies can accurately predict capacity, and interrogation shows that the optimal set of frequencies is not usually intuitive. Best results are achieved with an ensemble model, which predicts battery capacity with a mean absolute error of 1.9% on data from unobserved cells.

25 ENERGY STORAGE↗
DOE OSTI2021

Spatially resolved x-ray detection with photonic crystal scintillators

We study the self-collimation phenomenon in photonic crystals (PhC) of wide bandgap materials for ultra-fast and high spatial resolution x-ray detection. We work on various heavy inorganic scintillators: BaF 2 , GaN, ZnO, CsI:Tl, NaI:Tl, LYSO, WO 4 compounds, and plastic scintillators. Conventional scintillator detectors do not rely on a direct detection mechanism; hence, they require intricate design and fabrication processes. We offer a PhC design to observe self-collimation phenomena and overcome the ongoing spatial resolution challenges with these types of materials. We investigate the photonic band diagrams and iso-frequency contours. Fourier transforms based on finite-difference time-domain and frequency domain simulations are done for verifying and analyzing the self-collimation with the selected material. Light extraction efficiency at the PhC–air interface, depending on the truncation distance from the excitation point, is measured. Beam divergence values are calculated at 1 mm propagation distance. The vertical field profiles are obtained to observe the confinement. For the spatial resolution analysis, cross-sectional beam profiles have been examined. Furthermore, Gaussian envelopes are fitted to beam profiles for a consistent data analysis, and full-width-at-half-maximum values are considered. As a result, we theoretically prove and demonstrate the spatially resolved x-ray detection at the sub-micrometer level for a wide range of scintillator materials.

36 MATERIALS SCIENCE↗