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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 1,441 records · Page 80
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Elasticity of two-dimensional ferroelectrics across their paraelectric phase transformation

The mechanical behavior of two-dimensional (2D) materials across 2D phase changes is unknown, and the finite temperature (T) elasticity of paradigmatic SnSe monolayers—ferroelectric 2D materials turning paraelectric as their unit cell turns from a rectangle into a square—is described here in a progressive manner. To begin with, their zero–T total energy landscape gives way to (Boltzmann-like) averages from which the elastic behavior is determined. Furthermore, these estimates are complemented with results from the strain-fluctuation method, which employs the energy landscape or ab initio molecular dynamics data. All approaches capture the coalescence of elastic moduli < C 11 (T) > = < C 22 (T) > due to the structural transformation. The broad evolution and sudden changes of elastic parameters < C 11 (T) >, < C 22 (T) >, and < C 12 (T) > of these atomically thin phase-change membranes establishes a heretofore overlooked connection among 2D materials and soft matter.

2-dimensional systems↗
DOE OSTI2023

Transformer spin-triplet superconductivity at the onset of isospin order in bilayer graphene

We consider the origin of superconductivity found recently in Bernal bilayer graphene at the onset of isospin-polarized order, trying to infer the pairing mechanism and superconducting order from the measurements available to date. The superconductivity is induced by a parallel magnetic field and persists well above the Pauli limit, indicating an unconventional scenario of quantum-critical pairing, where soft fluctuations of isospin give rise to spin-triplet superconductivity. We consider the scenario in which the pairing interaction is entirely repulsive, which stands in contrast to the typical quantum-critical pairing mechanisms. Superconductivity emerges through a “transformer” mechanism where, in the presence of an in-plane magnetic field, the incipient valley polarization converts a frequency-independent repulsion into one with a strong nonmonotonic frequency dependence. Such an interaction enables a nonzero solution for the pairing gap function that changes sign as a function of frequency. Furthermore, the same mechanism holds at zero field in the presence of spin-orbit coupling, providing a likely explanation for the recently observed superconductivity in bilayer graphene on the WSe 2 monolayer.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

200-fold increase in dynamic strength of platinum at 430 GPa without a phase transformation

Here, the high-pressure strength of solid platinum is studied at the National Ignition Facility via Rayleigh-Taylor ripple growth under ramp compression. Laser-driven experiments reached pressures up to 430 GPa, collecting velocimetry and radiography data. Despite no phase transformation, the observed ripple growth aligns with hydrodynamic simulations using an amplified Steinberg-Guinan model, resulting in a 200-fold increase in strength. Molecular dynamics simulations of platinum ramp compression yield similar von Mises stress at comparable high pressure and high strain rate conditions. These findings represent the highest-pressure strength measurements ever achieved for platinum and offer critical insight into its significant strengthening behavior under high pressure and strain rate conditions.

Righi, Gaia [Lawrence Livermore National Laborator↗
DOE OSTI2020

Impact of transforming to conformal Fermi coordinates on quasisingle field non-Gaussianity

In general relativity, predictions for observable quantities can be expressed in a coordinate independent way. Nonetheless it may be inconvenient to do so. Using a particular frame may be the easiest way to connect theoretical predictions to measurable quantities. For the cosmological curvature bispectrum such frame is described by the conformal Fermi coordinates. In single field inflation it was shown that going to this frame cancels the squeezed limit of the density perturbation bispectrum calculated in global coordinates. Furthermore, we explore this issue in quasisingle field inflation when the curvaton mass and the curvaton-inflaton mixing are small. In this case, the contribution to the bispectrum from the coordinate transformation to conformal Fermi coordinates is of the same order as that from the inflaton-curvaton interaction term but does not cancel it.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Precise cosmological constraints from BOSS galaxy clustering with a simulation-based emulator of the wavelet scattering transform

For this study, we perform a reanalysis of the BOSS CMASS DR12 galaxy dataset using a simulation-based emulator for the wavelet scattering transform (WST) coefficients. Moving beyond our previous works, which laid the foundation for the first galaxy clustering application of this estimator, we construct a neural net-based emulator for the cosmological dependence of the WST coefficients and the 2-point correlation function multipoles, trained from the state-of-the-art suite of abacussummit simulations combined with a flexible halo occupation distribution (HOD) galaxy model. In order to confirm the accuracy of our pipeline, we subject it to a series of thorough internal and external mock parameter recovery tests, before applying it to reanalyze the CMASS observations in the redshift range 0.46 < z < 0.57. We find that a joint WST+2-point correlation function likelihood analysis allows us to obtain marginalized 1⁢σ errors on the Λ⁢ CDM parameters that are tighter by a factor of 2.5–6, compared to the 2-point correlation function, and by a factor of 1.4–2.5 compared to the WST-only results. This corresponds to a competitive 0.9%, 2.3% and 1% level of determination for parameters ω c , ⁢σ 8 &n s , respectively, and also to a 0.7% and 2.5% constraint on derived parameters h and ƒ⁡(z)⁢⁢σ 8 ⁡(z), in agreement with the Planck 2018 results. Our results reaffirm the constraining power of the WST and highlight the exciting prospect of employing higher-order statistics in order to fully exploit the power of upcoming stage-IV spectroscopic observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Improved limits on n → n ' transformation from the Spallation Neutron Source

Conversions between neutrons n and dark matter candidate sterile neutrons n' have been proposed as a mechanism for baryon number $\mathscr{B}$ violation. In the case that there is a small mass difference Δ⁢m between the n and the n' states, oscillations can be induced by compensating for Δ⁢m with a magnetic field. A search for such neutron oscillations was performed at the Spallation Neutron Source by looking for anomalous neutron transmission through a strongly absorbing cadmium wafer inside of a 6.6 T magnet. The approach described here saw no regenerated neutrons above background, which provides an improved limit for neutron–sterile neutron transformations for a range of Δ⁢m between 0.1 and 1000 neV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Facile ab initio approach for self-localized polarons from canonical transformations

Electronic states in a crystal can localize due to strong electron-phonon (e-ph) interactions, forming so-called small polarons. Methods to predict the formation and energetics of small polarons are either computationally costly or not geared toward quantitative predictions. Here we show a formalism based on canonical transformations to compute the polaron formation energy and wave function using ab initio e-ph interactions. Comparison of the calculated polaron and band-edge energies allows us to determine whether charge carriers in a material favor a localized small polaron over a delocalized Bloch state. Due to its low computational cost, our approach enables efficient studies of the formation and energetics of small polarons, as we demonstrate by investigating electron and hole polaron formation in alkali halides and metal oxides and peroxides. We outline refinements of our scheme and extensions to compute transport in the polaron hopping regime.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Size-dependent ferroelectric-to-paraelectric sliding transformations and antipolar-to-ferroelectric topological phase transitions in binary homobilayers

The recent discovery of ferroelectric behavior in few-layer materials, accompanied by the observation of antipolar domains in hexagonal boron nitride and transition metal dichalcogenide moiré bilayers, is paving the way for revolutionary advancements in the generation and manipulation of intrinsic electric dipoles through stacking. In addition, these cutting-edge quantum materials are reshaping our comprehension of phase transitions. Within the present paper, we unveil a size-dependent sliding behavior that marks a significant departure from conventional ferroelectrics. We also shed light on thermally induced spontaneous hyperlubric sliding within moiré bilayers, which can be used as a signal to distinguish topological phase transitions from an antipolar onto a ferroelectric bilayer. Furthermore, our findings also suggest that the (topological) pinning of AA nodes in antipolar moiré homobilayers prevents the occurrence of an antipolar-to-paraelectric transformation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Broadband coplanar-waveguide-based impedance-transformed Josephson parametric amplifier

Quantum-limited Josephson parametric amplifiers play a pivotal role in advancing the field of circuit quantum electrodynamics by enabling the fast and high-fidelity measurement of weak microwave signals. Therefore, it is necessary to develop robust parametric amplifiers with low noise, broad bandwidth, and reduced design complexity for microwave detection. However, current broadband parametric amplifiers either have degraded noise performance or rely on complex designs. Here, we present a device based on the broadband impedance-transformed Josephson parametric amplifier that integrates a hornlike coplanar waveguide transmission line, which significantly decreases the design and fabrication complexity while keeping comparable performance. The device shows an instantaneous bandwidth of 700 (200) MHz for 15 (20) dB gain with an average input saturation power of − 110 dBm and near quantum-limited added noise. The operating frequency can be tuned over 1.4 GHz using an external flux bias. We further demonstrate the negligible backaction from our device on a transmon qubit. The amplification performance and simplicity of our device promise its wide adaptation in quantum metrology, quantum communication, and quantum information processing. Published by the American Physical Society 2024

Qing, Bingcheng (ORCID:0000000345227017)↗
DOE OSTI2024

tomoCAM : fast model-based iterative reconstruction via GPU acceleration and non-uniform fast Fourier transforms

X-ray-based computed tomography is a well established technique for determining the three-dimensional structure of an object from its two-dimensional projections. In the past few decades, there have been significant advancements in the brightness and detector technology of tomography instruments at synchrotron sources. These advancements have led to the emergence of new observations and discoveries, with improved capabilities such as faster frame rates, larger fields of view, higher resolution and higher dimensionality. These advancements have enabled the material science community to expand the scope of tomographic measurements towards increasingly in situ and in operando measurements. In these new experiments, samples can be rapidly evolving, have complex geometries and restrictions on the field of view, limiting the number of projections that can be collected. In such cases, standard filtered back-projection often results in poor quality reconstructions. Iterative reconstruction algorithms, such as model-based iterative reconstructions (MBIR), have demonstrated considerable success in producing high-quality reconstructions under such restrictions, but typically require high-performance computing resources with hundreds of compute nodes to solve the problem in a reasonable time. Here, tomoCAM , is introduced, a new GPU-accelerated implementation of model-based iterative reconstruction that leverages non-uniform fast Fourier transforms to efficiently compute Radon and back-projection operators and asynchronous memory transfers to maximize the throughput to the GPU memory. The resulting code is significantly faster than traditional MBIR codes and delivers the reconstructive improvement offered by MBIR with affordable computing time and resources. tomoCAM has a Python front-end, allowing access from Jupyter -based frameworks, providing straightforward integration into existing workflows at synchrotron facilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Explainable AI for Multivariate Time Series Pattern Exploration: Latent Space Visual Analytics With Temporal Fusion Transformer and Variational Autoencoders in Power Grid Event Diagnosis

Detecting and analyzing complex patterns in multivariate time-series data is crucial for decision-making in urban and environmental system operations. However, challenges arise from the high dimensionality, intricate complexity, and interconnected nature of complex patterns, which hinder the understanding of their underlying physical processes. Existing AI methods often face limitations in interpretability, computational efficiency, and scalability, reducing their applicability in real-world scenarios. This paper proposes a novel visual analytics framework that integrates two generative AI models, Temporal Fusion Transformer (TFT) and Variational Autoencoders (VAEs), to reduce complex patterns into lower-dimensional latent spaces and visualize them in 2D using dimensionality reduction techniques such as PCA, t-SNE, and UMAP with DBSCAN. These visualizations, presented through coordinated and interactive views and tailored glyphs, enable intuitive exploration of complex multivariate temporal patterns, identifying patterns’ similarities and uncover their potential correlations for a better interpretability of the AI outputs. The framework is demonstrated through a case study on power grid signal data, where it identifies multi-label grid event signatures, including faults and anomalies with diverse root causes. Additionally, novel metrics and visualizations are introduced to validate the models and assess the performance, efficiency, and consistency of latent maps generated by VAE, which have been utilized in prior studies for latent space cartography and used as a benchmark in this study, and the emerging TFT architecture under various configurations. These analyses provide actionable insights for model parameter tuning and reliability improvements. Comparative results highlight that TFT achieves shorter run times and superior scalability to diverse time-series data shapes compared to VAE. This work advances fault diagnosis in multivariate time series, fostering explainable AI to support critical system operations.

Explainable AI↗
DOE OSTI2021

A Transformer Flux Balancing Scheme Based on Magnetizing Current Harmonic in Dual-Active-Bridge Converters

The Dual-Active-Bridge (DAB) converter transformer flux unbalance, or dc bias, could be a critical issue due to the mismatches of converter circuit parameters and control transients. In this paper, a steady-state flux balancing scheme, based on the second-order harmonic of magnetizing current has been proposed. The relationship between steady-state flux/magnetizing current unbalance and its harmonic contents has been analyzed, with which a new current sensing method and control strategy are introduced. The proposed magnetizing current sensing method can be implemented for both unity and complicated fractional turns ratios, without high sensitivity to dc offset from the analog circuitry. The proposed scheme has been validated with experimental results on 850-V/850-V DAB converters within a system, as well as in an 850-V/6700-V medium voltage DAB unit.

Gao, Zihan↗
DOE OSTI2023

Medium Voltage Solid State Transformer for Extreme Fast Charging Applications

A modular and scalable solid state transformer (SST) with direct medium voltage (MV) AC connectivity is proposed to enable DC extreme fast charging (XFC) of electric vehicles. Single-phase-modules (SPMs), each consisting of an active-front-end (AFE) stage and an isolated DC-DC stage, are connected in input-series-output-parallel (ISOP) configuration. The modular hardware is co-designed with decentralized control of the DC-DC stages where voltage and power balancing are achieved by each SPM using only its local sensor feedback; a centralized controller (CC) regulates the low voltage (LV) DC bus through the AFE stages without any sensor feedback form the SPMs. The controller architecture contrasts sharply with the prior art for MV AC to LV DC SSTs where high-speed bidirectional communication among SPMs and a CC are required for module-level voltage and power balancing, which severely limits the scalability and practical realization of higher voltage and higher power units. Detailed small-signal analysis and controller design guidelines are developed. Furthermore, a soft start-up strategy is presented. The proposed converter and control structure are validated through simulation and experimental results.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Performance Profile of Transformer Fine-Tuning in Multi-GPU Cloud Environments

The study presented here focuses on performance characteristics and trade-offs associated with running machine-learning tasks in multi-GPU environments on both on-site cloud computing resources and commercial cloud services (Azure). Specifically, this study examines these tradeoffs by examining the performance of training and fine-tuning of transformer-based deep-learning (DL) networks on clinical notes and data, a task of critical importance in the medical domain. To this end, we perform DL-related experiments on the widely deployed NVIDIA V100 GPUs and on the newer A100 GPUs connected via NVLink or PCIe. This study analyzes the execution time of major operations to train DL models and investigate popular options to optimize each of them. We examine and present the findings on the impacts that various operations (e.g. data loading into GPUs, training, fine-tuning), optimizations, and system configurations (single vs. multi-GPU, NVLink vs. PCIe) have on the overall training performance.

Begoli, Edmon↗
DOE OSTI2024

Power System Resilience Considering Hurricane Storms and Generator Step-up Transformers

Power system resilience describes the system’s ability to withstand and recover quickly from unexpected power outages due to extreme events. As society’s electrification continues at a rapid rate, it is imperative electric infrastructure is designed and operated with extra security. This work studies the impact of severe hurricane storms on the power system located along the United States’ Eastern Seaboard. Specific focus is designated to steady state system operation and loss of large generation step up power transformers. A series of phasor domain power system simulations are conducted to determine the critical point at which the system loses steady state operability. Additionally, active power load shedding and generator dispatching are studied as mitigation and recovery strategies. Results indicate generator dispatching as an effective proactive mitigation strategy and load shedding as an effective recovery strategy.

Liu, Yilu↗
DOE OSTI2020

Model-less Source Location for Forced Oscillation based on Synchrophasor and Moving Fast Fourier Transformation

Forced oscillations in power systems occur when the grid is driven by an external and periodic force. To quickly detect and locate the source of the forced oscillation is critical in terms of ensuring the reliability of an interconnected power grid. This paper explores the electromechanical wave propagation theory and the Fast Fourier Transformation to analyze the forced oscillations. It proposes a model-less, adaptive, fast, and accurate source location algorithm. The proposed algorithm is extensively evaluated through simulation data from a 70k-bus U.S. Eastern Interconnection test system and field-collected synchrophasor data from the distribution-level wide-area monitoring system, FNET/GridEye. The evaluation results demonstrate the correctness and effectiveness of the proposed model-less forced oscillation source location algorithm.

Wang, Weikang↗
DOE OSTI2025

Intercell Power Transformer for Power Balancing of Polyphase Wireless Power Transfer Systems

Polyphase wireless power transfer (PWPT) systems experience receiver side imbalances in misaligned conditions. This paper proposes a method for power balancing in PWPT systems, specifically addressing the challenges caused by receivers coil unequal coupling. An intercell power transformer (IPT) is introduced at the receiver side to mitigate the effects of coil mismatch. Simulations of the PWPT system incorporating IPT demonstrate its effectiveness in enhancing power distribution. For voltage-fed rectifiers (VFR), the IPT increases the conduction angle, resulting in higher output power. In current- fed rectifiers (CFR), the IPT promotes uniform power sharing among rectifiers, thereby reducing electrical stress on semiconductor devices and passive components. Simulation results indicate that, under coil misalignment, the IPT improves output power by approximately 49% for VFRs and 44% for CFRs compared to conventional PWPT systems without IPT.

Wojda, Rafal [ORNL] (ORCID:0000000286609268)↗
DOE OSTI2025

Advanced Photovoltaic Module Characterization: Using Image Transformers for Current–Voltage Curve Prediction From Electroluminescence Images

Individual photovoltaic (PV) module health monitoring can be a daunting task for operation and maintenance of solar farms. Modules can be inspected through luminescence, thermal imaging, and current–voltage (I–V) curve analyzes for identification of damage and power loss. I–V curves provide easily interpretable data to determine module health as they directly provide electrical performance metrics. However, in order to obtain these curves, modules must be disconnected from the array and either removed to a solar simulator or characterized in situ with corrections for module temperature, the incident solar spectrum, and intensity. Luminescence or thermal images of a module are relatively easy to acquire in situ. Electroluminescence (EL) images highlight physical defects in the modules but do not provide easily interpretable features to correlate with electrical performance. This work presents a SWin transformer network to predict I–V curves for PV modules from their corresponding EL images. The predicted I–V curves allow the accurate prediction of the maximum power point (MPP), short-circuit current I sc , and open-circuit voltage V oc with a mean error less of than 1%. Comparing single diode model (SDM) parameters extracted from the predicted curves to those extracted from the true curves, the series resistance R s demonstrates a mean error of 5.19%, and the photocurrent I a mean error of 0.197%. The shunt resistance R sh and dark current Io parameters are predicted with larger errors because of their sensitivity to small changes in the I–V curve.

Byford, Brandon K. [New Mexico State Univ., Las Cr↗