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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

VipariNama: RNA viral vectors to rapidly elucidate the relationship between gene expression and phenotype

Synthetic transcription factors have great promise as tools to help elucidate relationships between gene expression and phenotype by allowing tunable alterations of gene expression without genomic alterations of the loci being studied. However, the years-long timescales, high cost, and technical skill associated with plant transformation have limited their use. In this work, we developed a technology called VipariNama (ViN) in which vectors based on the tobacco rattle virus are used to rapidly deploy Cas9-based synthetic transcription factors and reprogram gene expression in planta. We demonstrate that ViN vectors can implement activation or repression of multiple genes systemically and persistently over several weeks in Nicotiana benthamiana, Arabidopsis (Arabidopsis thaliana), and tomato (Solanum lycopersicum). By exploring strategies including RNA scaffolding, viral vector ensembles, and viral engineering, we describe how the flexibility and efficacy of regulation can be improved. We also show how this transcriptional reprogramming can create predictable changes to metabolic phenotypes, such as gibberellin biosynthesis in N. benthamiana and anthocyanin accumulation in Arabidopsis, as well as developmental phenotypes, such as plant size in N. benthamiana, Arabidopsis, and tomato. These results demonstrate how ViN vector-based reprogramming of different aspects of gibberellin signaling can be used to engineer plant size in a range of plant species in a matter of weeks. In summary, ViN accelerates the timeline for generating phenotypes from over a year to just a few weeks, providing an attractive alternative to transgenesis for synthetic transcription factor-enabled hypothesis testing and crop engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Prediction of L⁢i 3 ⁢F⁡e 8 ⁢B 8 compound with rapid one-dimensional ion diffusion channels

Using a computational crystal structure search in the Li-Fe-B ternary system, we predict a stable phase of L⁢i 3 ⁢F⁡e 8 ⁢B 8 , featuring 1D channels that enable rapid Li-ion transport. Ab initio molecular dynamics simulations show that the Li-ion diffusion coefficient in L⁢i 3 ⁢F⁡e 8⁢ B 8 surpasses that of common electrode and conductive additive materials by several orders of magnitude. The high diffusion in L⁢i 3 ⁢F⁡e 8 ⁢B 8 can be explained by the Frenkel–Kontorova model, which describes an incommensurate state between the Li diffusion chain and the periodic potential field caused by the FeB backbone structure. The favorable lithium-ion diffusivity and mechanical properties of L⁢i 3 ⁢F⁡e 8 ⁢B 8 make it a promising conductive additive for battery materials. Furthermore, an external magnetic field can further manipulate the properties of this material due to its predicted itinerant ferromagnetism, which also offers a platform for exploring spin-dependent phenomena.

1-dimensional systems↗
DOE OSTI2025

Measurement of elliptic flow of 𝐽/𝜓 in $\sqrt{s_{NN}}$ = 200 GeV ⁢Au + Au collisions at forward rapidity

Here, we report the first measurement of the azimuthal anisotropy of 𝐽/𝜓 at forward rapidity (1.2 < |𝜂| < 2.2) in Au + Au collisions at $\sqrt{s_{NN}}$ = 200 GeV at the BNL Relativistic Heavy Ion Collider. The data were collected by the PHENIX experiment in 2014 and 2016 with integrated luminosity of 14.5 nb −1 . The second Fourier coefficient (𝑣 2 ) of the azimuthal distribution of 𝐽/𝜓 is determined as a function of the transverse momentum (𝑝𝑇) using the event-plane method. The measurements were performed for several selections of collision centrality: 0%–50%, 10%–60%, and 10%–40%. We find that in all cases the values of 𝑣 2 ⁡(𝑝 𝑇 ), which quantify the elliptic flow of 𝐽/𝜓, are consistent with zero. Within uncertainties, the results are consistent with measurements at midrapidity, indicating no significant elliptic flow of the 𝐽/𝜓 within the quark-gluon-plasma medium at collision energies of $\sqrt{s_{NN}}$ = 200 GeV.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Robust Mølmer-Sørensen gate for neutral atoms using rapid adiabatic Rydberg dressing

The Rydberg blockade mechanism is now routinely considered for entangling qubits encoded in clock states of neutral atoms. Challenges towards implementing entangling gates with high fidelity include errors due to thermal motion of atoms, laser amplitude inhomogeneities, and imperfect Rydberg blockade. Here, we show that adiabatic rapid passage by Rydberg dressing provides a mechanism for implementing two-qubit entangling gates by accumulating phases that are robust to these imperfections. We find that the typical error in implementing a two-qubit gate, such as the controlled phase gate, is dominated by errors in the single-atom light shift, and that this can be easily corrected using adiabatic dressing interleaved with a simple spin echo sequence. This results in a two-qubit Mølmer-Sørensen gate. A gate fidelity ~ 0.995 is achievable with modest experimental parameters and a path to higher fidelities is possible for Rydberg states in atoms with a stronger blockade, longer lifetimes, and larger Rabi frequencies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

First-order structural phase transition at low temperature in GaPt 5 P and its rapid enhancement with pressure

Single crystals of X Pt 5 ⁢P (X = Al, Ga, and In), belonging to the 1-5-1 family of compounds, were grown from a Pt-P solution at high temperatures, and measurements of the ambient pressure, temperature-dependent magnetization, resistivity, and x-ray diffraction were made. Additionally, the ambient-pressure Hall resistivity and temperature-dependent resistance under pressure were measured on GaPt 5 ⁢P. All three compounds have a tetragonal P4/mmm crystal structure at room temperature with metallic transport and weak diamagnetism over the 2–300 K temperature range. Surprisingly, at ambient pressure, both the transport and magnetization measurements on GaPt 5 ⁢P show a steplike feature in the 70–90 K region, suggesting a possible structural phase transition. Neither AlPt 5 ⁢P nor InPt 5 ⁢P have any signatures of a phase transition in their temperature-dependent electrical resistance and magnetization data. Both the hysteretic nature and sharpness of the features in the GaPt 5 ⁢P data suggest that the transition is first-order. Further, single-crystal x-ray diffraction measurements provided further details of the structural transition with a possibility of a crystal symmetry different from P⁢4/mmm below the transition temperature. The transition is characterized by anisotropic changes in the lattice parameters and a volume collapse with respect to the high-temperature tetragonal crystal structure. Furthermore, satellite peaks are observed at two distinct and nonequivalent wave vectors (0, 0, 0.5) and (0.5, 0.5, 0.5), and density functional theory calculations present phonon softening, especially at (0.5, 0.5, 0.5), as a possible driving mechanism. Additionally, we find that the structural transition temperature increases rapidly with increasing pressure, reaching room temperature by ~2.2 GPa, highlighting the high degree of pressure sensitivity of GaPt 5 ⁢P and fragile nature of its room-temperature structure. Even though the volume collapse and extreme pressure sensitivity suggest chemical pressure should drive a similar structural change in AlPt 5⁢ P, where both unit-cell dimensions and volume are smaller, its structure is found to be the same as that of the room-temperature GaPt 5 ⁢P. Overall, GaPt 5 ⁢P stands out as a sole member of the 1-5-1 family of compounds for which a temperature-driven structural change has been observed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Covariant formulation of spinodal decomposition in rapidly expanding quark gluon plasma

Quantum chromodynamics (QCD) is expected to have a first order phase transition between the confined hadron gas and the deconfined quark gluon plasma at high baryon densities. This will result in phase boundary effects in the metastable and unstable regions. It is important to include these effects in phenomenological models of heavy ion collisions to identify experimental signatures of a phase transition. This requires building intuition on phase separation in rapidly expanding fluids. In this work we present the covariant equations of relativistic hydrodynamics with a phase boundary, provide prescriptions to extend the equation of state to metastable and unstable regions, and show the effects of spinodal separation in a Bjorken flow. Published by the American Physical Society 2024

Kapusta, Joseph I. (ORCID:0000000259429835)↗
DOE OSTI2020

Production of b b ¯ at forward rapidity in p + p collisions at s = 510 GeV

The cross section of bottom quark-antiquark ( b b ¯ ) production in p + p collisions at s = 510 GeV is measured with the PHENIX detector at the Relativistic Heavy Ion Collider. The results are based on the yield of high mass, like-sign muon pairs measured within the PHENIX muon arm acceptance ( 1.2 < | y | < 2.2 ). The b b ¯ signal is extracted from like-sign dimuons by utilizing the unique properties of neutral B meson oscillation. We report a differential cross section of d σ b b ¯ → μ ± μ ± / d y = 0.16 ± 0.01 ( stat ) ± 0.02 ( syst ) ± 0.02 ( global ) nb for like-sign muons in the rapidity and p T ranges 1.2 < | y | < 2.2 and p T > 1 GeV / c , and dimuon mass of 5 – 10 GeV / c 2 . The extrapolated total cross section at this energy for b b ¯ production is 13.1 ± 0.6 ( stat ) ± 1.5 ( syst ) ± 2.7 ( global ) μ b . The total cross section is compared to a perturbative quantum chromodynamics calculation and is consistent within uncertainties. The azimuthal opening angle between muon pairs from b b ¯ decays and their p T distributions are compared to distributions generated using ps pythia 6, which includes next-to-leading order processes. The azimuthal correlations and pair p T distribution are not very well described by pythia calculations, but are still consistent within uncertainties. Flavor creation and flavor excitation subprocesses are favored over gluon splitting.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Gravitational Waves from Rapid Structure Formation on Microscopic Scales before Matter-Radiation Equality

We propose a new scenario for the formation of asteroid-mass primordial black holes (PBHs). Our mechanism is based on the annihilation of the string-wall network associated with thebreaking of a U(1) global symmetry into a discrete ZN symmetry. If the potential hasmultiple local minima (N > 1) the network is stable, and the annihilation is guaranteed by a biasamong the different vacua. The collapse of the string-wall network is accompanied bycatastrogenesis, a large production of pseudo-Goldstone bosons (pGBs) — e.g. axions,ALPs, or majorons — gravitational waves, and PBHs. If pGBs rapidly decay into products thatthermalize, as predicted e.g. in the high-quality QCD axion and heavy majoron models, they do notcontribute to the dark matter population, but we show that PBHs can constitute 100% of the darkmatter. The gravitational wave background produced by catastrogenesis with heavy unstable axions,ALPs, or majorons could be visible in future interferometers.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

CuXASNet: Rapid and accurate prediction of copper L-edge x-ray absorption spectra using machine learning

In this work, we have developed CuXASNet, a dense neural network that predicts simulated Cu -edge x-ray absorption spectra (XAS) from atomic structures. Featurization of the Cu local environment is performed using a component of M3GNet, a graph neural network developed for predicting the potential energy surface. CuXASNet is trained on simulated spectra from FEFF9 at the multiple scattering level of theory, and can predict the and edges for Cu sites to quantitative accuracy. To validate our approach, we compare 14 experimental spectra extracted from the literature with the predictions of CuXASNet. The agreement of CuXASNet with experiments is shown by an average mean absolute error of 0.125 and an average Spearman's correlation coefficient of 0.891, which is comparable to FEFF9's values of 0.131 and 0.898 for the same metrics. As such, CuXASNet can rapidly predict a large number of -edge XAS spectra at the same accuracy as FEFF9 simulations. This can be used as a drop-in replacement for multiple scattering codes for fast screening of candidate atomic structure models of a measured system. This model establishes a general framework for Cu XAS prediction, and can be extended to more computationally expensive levels of theory and to other transition metal edges.

36 MATERIALS SCIENCE↗
DOE OSTI2024

The RAPTR furnace: a rapid heating and cooling sample furnace for in situ X-ray scattering studies of temperature-induced reactions

In situX-ray scattering provides valuable insights into the mechanisms and kinetics of reactions and structural transformations. For reactions and structural transformations primarily driven by temperature, and not coupled to chemical/electrochemical triggers, our ability to initiate and quench processes thermally is a practical limit for probing fast reactive phenomena. Meaningful quantitative analysis requires the dynamic phenomena to be triggered on fast time scales relative to the reaction/transformation kinetics. This article describes a new sample furnace, the Rapid-Actuating Pneumatic Thermal Reactor or RAPTR, for time-resolvedin situX-ray scattering studies initiated by temperature. The RAPTR quickly heats and cools samples by translating them into and out of a pre-heated hot zone. Using diffraction thermometry, it is shown that the samples can be heated/cooled in 10 s or less, with temperatures up to ∼1000°C being accessible. The application of the RAPTR furnace is demonstrated by exploring a fast solid-state reaction: the synthesis of scheelite-type lead tungstate, PbWO 4 , from PbO and WO 3 for which Pb 3 WO 6 is identified as a previously unrecognized reaction intermediate.

Chemistry↗
DOE OSTI2026

LaueMatching: an approach for rapid and robust indexing of Laue diffraction patterns

Traditional Laue diffraction pattern indexing often struggles with noisy data, weak signals, peak overlap and missing reflections, particularly from complex or deformed microstructures. Here, we introduce LaueMatching, a high-throughput indexing algorithm designed to overcome these limitations. LaueMatching utilizes a fundamentally different approach based on direct pattern correlation: experimentally pre-processed images are compared against a comprehensive pre-computed library of simulated diffraction patterns corresponding to a dense grid of possible orientations. This approach bypasses the need for explicit peak identification and fitting, steps that are often a failure point for traditional methods. The algorithm rapidly and robustly indexes multiple crystallographic orientations and crystal systems simultaneously, even from challenging patterns. LaueMatching's effectiveness and accuracy have been rigorously tested and validated on diverse experimental (Ni, Al, EuAl 2 O 4 ) and simulated diffraction patterns, demonstrating high-fidelity orientation refinement. Code to implement this approach on both CPU and GPU resources can be downloaded from https://github.com/AdvancedPhotonSource/LaueMatching.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Transferable Hirshfeld atom model for rapid evaluation of aspherical atomic form factors

Form factors based on aspherical models of atomic electron density have brought great improvement in the accuracies of hydrogen atom parameters derived from X-ray crystal structure refinement. Today, two main groups of such models are available, the banks of transferable atomic densities parametrized using the Hansen–Coppens multipole model which allows for rapid evaluation of atomic form factors and Hirshfeld atom refinement (HAR)-related methods which are usually more accurate but also slower. In this work, a model that combines the ideas utilized in the two approaches is tested. It uses atomic electron densities based on Hirshfeld partitions of electron densities, which are precalculated and stored in a databank. This model was also applied during the refinement of the structures of five small molecules. A comparison of the resulting hydrogen atom parameters with those derived from neutron diffraction data indicates that they are more accurate than those obtained with the Hansen–Coppens based databank, and only slightly less accurate than those obtained with a version of HAR that neglects the crystal environment. The advantage of using HAR becomes more noticeable when the effects of the environment are included. To speed up calculations, atomic densities were represented by multipole expansion with spherical harmonics up to l = 7, which used numerical radial functions (a different approach to that applied in the Hansen–Coppens model). Calculations of atomic form factors for the small protein crambin (at 0.73 Å resolution) took only 68 s using 12 CPU cores.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

A Fully Automatic Method for Rapidly Mapping Impacted Area by Natural Disaster

Deep learning based change detection methods have achieved the state-of-the-art performance in several recent studies. However, such methods usually are supervised, and therefore a large number of training samples is often a requisite. Manually preparing those training samples is not only expensive but also time-consuming, which does not fit the need of rapidly mapping the impacted area caused by nature disaster for further rescue mission and damage assessment. In this study, a fully automatic method was proposed to address the issue by automating training sample generation for mapping the impacted area caused by nature disaster. We used the 2011 tornado event in Joplin, Missouri, US, as an example of its application. The generated impacted area map was both visually and quantitatively evaluated against the ground truth data collected by US Federal Emergency Management Agency (FEMA). The results show that the map matches well with the FEMA ground truth data with 86% of major-damaged and destroyed buildings identified by FEMA on the ground also detected by this fully automatic framework using very high resolution (VHR) satellite images.

Liu, Tao↗
DOE OSTI2020

RAPID STRUCTURE DETECTION IN SUPPORT OF DISASTER RESPONSE : A CASE STUDY OF THE 2018 KILAUEA VOLCANO ERUPTION

Disaster response requires timely damage assessment to prioritize rescue and restoration resources. However, providing critical and actionable knowledge after a natural disaster can be challenging due to the scale and the type of damages. This paper describes how remote sensing and machine learning techniques can be used to support rapid structure detection in the wake of a disaster. We use high resolution satellite imagery to identify structures on Hawaii’s Big Island to support the Federal Emergency Management Agency’s response efforts during the 2018 K¯ilauea lava flow incident. This framework specifically showcases the generalizability of CNN models with no need to collect additional training samples to quickly map structures in pre- and post-event imagery and provide timely information to assist government agencies evaluating the extent and potential loss of disaster. With this case study, we further point out future directions to benefit similar larger scale efforts based on the lessons learned.

Laverdiere, Melanie↗
DOE OSTI2021

Rapid Open-Air Processing of Low-Cost Perovskite Solar Modules

We report an industrially relevant approach to both scalable and fast open-air perovskite photovoltaic (PV) module production. This work resolves some of the most formidable barriers to module-level scaling that the perovskite community has been facing. Key advances include scalable large-area spray deposition, new monolithic integration scribing techniques, advanced photoluminescence characterization, and reproducible high-throughput manufacturability. Our rapid spray processing techniques enabled the highest perovskite PV efficiency produced in open-air. Innovations in scribing techniques enabled the first single-source laser process to achieve perovskite module monolithic integration and technoeconomic analysis led to a comprehensive cost model for perovskite module manufacturing. We report significant progress in reducing perovskite manufacturing costs necessary to potentially compete with incumbent Si-based PV for utility-scale power generation.

cost modeling↗
DOE OSTI2024

Rapid Characterization and Statistical Analysis of High-Volume Field-Harvested Photovoltaic Connectors

Photovoltaic (PV) installations heavily depend on connectors for efficient module and string interconnections without requiring skilled labor. Yet this seemingly innocuous component of PV systems is a leading cause of module failures, multiple high-profile fires, and lawsuits in the PV industry. This work aims to answer critical questions regarding why connectors fail and the contributing factors to their failure. The study involves collecting and analyzing more than 17,000 field-harvested connectors from various solar installations across the United States. The vast dataset, which includes connector metadata, visual inspections, and resistance measurements, provides unprecedented insight into the state of health of PV connectors across the US, including the geographic locations, connector types, and installation practices most prone to failures. The work presented here describes a novel rapid characterization method for processing large numbers of connectors and is supported by parallel forensic analysis to discern the root causes of failures as well as a levelized cost of lifetime model to determine the economic ramifications of connector failure. Ultimately, the findings may inform PV developers about the best practices to extend connector longevity and lead to more resilient and reliable PV systems.

connectors↗
DOE OSTI2024

Rapid Monitoring and Defense Approach for Resilience Improvement of Grid Cyber Security

Cyber-physical systems and electric utilities significantly depend on the reliability and efficiency of information and operational technology. However, false data injection attacks based on synchrophasor measurement data pose a serious threat to the safe and reliable operation of modern power systems. Here, to mitigate this problem, a rapid monitoring and defense approach is proposed to defend against cyber attacks. Initially, the Time and Frequency based Convolutional neural Network (TFCN) is proposed to detect different types of attacks. Within the TFCN, the advances are that both time and frequency domain information can be fused without extra spectrum analysis methods, and can save detection time to speed the calculation efficiency using the developed time-frequency block. Next, a comprehensive defense strategy is developed for multiple cyber attacks to ensure the stability and resilience of the power system according to the feedback detection results. The advances of this strategy are that different control strategies can be automatically selected to recover the stability to the greatest extent according to the detected attacks. To verify the effectiveness of the proposed approach, the high-speed frequency measurements collected from the wide-area monitoring system are used. The results demonstrate that the cyber attack detection performance can reach 95.57% accuracy, outperforming both traditional and some advanced neural networks. Importantly, the defense strategy is conducted and verified in a modified IEEE 39 bus system as well, which illustrates profound performance in faster stability restoration.

Comprehensive defense strategy↗
DOE OSTI2023

Modeling and Rapid Prototyping of Integrated Transmission-Distribution OPF Formulations with PowerModelsITD.jl

Conventional electric power systems are composed of different unidirectional power flow stages of generation, transmission, and distribution, managed independently by transmission system and distribution system operators. However, as distribution systems increase in complexity due to the integration of distributed energy resources, coordination between transmission and distribution networks will be imperative for the optimal operation of the power grid. However, coupling models and formulations between transmission and distribution is non-trivial, in particular due to the common practice of modeling transmission systems as single-phase, and distribution systems as multi-conductor phase-unbalanced. To enable the rapid prototyping of power flow formulations, in particular in the modeling of the boundary conditions between these two seemingly incompatible data models, we introduce PowerModelsITD.jl, a free, open-source toolkit written in Julia for integrated transmission-distribution (ITD) optimization that leverages mature optimization libraries from the InfrastructureModels.jl-ecosystem. The primary objective of the proposed framework is to provide baseline implementations of steady-state ITD optimization problems, while providing a common platform for the evaluation of emerging formulations and optimization problems. In this work, we introduce the nonlinear formulations currently supported in PowerModelsITD.jl, which include AC-polar, AC-rectangular, current-voltage, and a linear network transportation model. Results are validated using combinations of IEEE transmission and distribution networks.

24 POWER TRANSMISSION AND DISTRIBUTION↗