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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 OSTI2023

Chemical compression and ferroic orders in La substituted BiFe O 3

Chemical compression effects on the ferroic orders in La substituted BiFeO 3 are studied by atomic pair distribution function analysis and structure modeling. While rhombohedral BiFeO 3 exhibits ferroelectricity and antiferromagnetism (AF) with a cycloidal Fe spin arrangement leading to zero magnetization, La substituted BiFeO 3 exhibits a reduced lattice polarization, strengthened AF order, and an apparently suppressed spin cycloid leading to nonzero magnetization. Furthermore, the observed changes in the ferroic orders arise from the chemical compression induced changes in the octahedral rotation and ferroelectric displacement of Bi atoms, which appear as lattice degrees of freedom entangling the electronic and magnetic orders in BiFeO 3 .

36 MATERIALS SCIENCE↗
DOE OSTI2020

Distributed Many-to-Many Protein Sequence Alignment using Sparse Matrices

Identifying similar protein sequences is a core step in many computational biology pipelines such as detection of homologous protein sequences, generation of similarity protein graphs for downstream analysis, functional annotation, and gene location. Performance and scalability of protein similarity search have proven to be a bottleneck in many bioinformatics pipelines due to increase in cheap and abundant sequencing data. This work presents a new distributed-memory software PASTIS. PASTIS relies on sparse matrix computations for efficient identification of possibly similar proteins. We use distributed sparse matrices for scalability and show that the sparse matrix infrastructure is a great fit for protein similarity search when coupled with a fully-distributed dictionary of sequences that allow remote sequence requests to be fulfilled. Our algorithm incorporates the unique bias in amino acid sequence substitution in search without altering basic sparse matrix model, and in turn, achieves ideal scaling up to millions of protein sequences.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Use of virus‐induced gene silencing to characterize genes involved in modulating hypersensitive cell death in maize

Abstract Plant disease resistance proteins (R‐proteins) detect specific pathogen‐derived molecules, triggering a defence response often including a rapid localized cell death at the point of pathogen penetration called the hypersensitive response (HR). The maize Rp1‐D21 gene encodes a protein that triggers a spontaneous HR causing spots on leaves in the absence of any pathogen. Previously, we used fine mapping and functional analysis in a Nicotiana benthamiana transient expression system to identify and characterize a number of genes associated with variation in Rp1‐D21 ‐induced HR. Here we describe a system for characterizing genes mediating HR, using virus‐induced gene silencing (VIGS) in a maize line carrying Rp1‐D21 . We assess the roles of 12 candidate genes. Three of these genes, SGT1 , RAR1 , and HSP90 , are required for HR induced by a number of R‐proteins across several plant–pathogen systems. We confirmed that maize HSP90 was required for full Rp1‐D21 ‐induced HR. However, suppression of SGT1 expression unexpectedly increased the severity of Rp1‐D21 ‐induced HR while suppression of RAR1 expression had no measurable effect. We confirmed the effects on HR of two genes we had previously validated in the N. benthamiana system, hydroxycinnamoyltransferase and caffeoyl CoA O‐methyltransferase . We further showed the suppression the expression of two previously uncharacterized, candidate genes, IQ calmodulin binding protein ( IQM3 ) and vacuolar protein sorting protein 37 , suppressed Rp1‐D21 ‐induced HR. This approach is an efficient way to characterize the roles of genes modulating the hypersensitive defence response and other dominant lesion phenotypes in maize.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Nannochloropsis oceanica IMET1 and its bacterial symbionts for carbon capture, utilization, and storage: biomass and calcium carbonate production under high pH and high alkalinity

ABSTRACT To combat the increasing levels of carbon dioxide (CO 2 ) released from the combustion of fossil fuels, microalgae have emerged as a promising strategy for biological carbon capture, utilization, and storage. This study used a marine microalgal strain, Nannochloropsis oceanica IMET1, which thrives in high CO 2 concentrations. A high-pH, high-alkalinity culture was designed for CO 2 capture through algal biomass production as well as permanent sequestration through calcium carbonate (CaCO 3 ) precipitation. This was accomplished by timed pH elevation and the addition of sodium bicarbonate to cultures of N. oceanica grown at lab scale (1 L) and pilot scale (500 L) with 10% and 5% CO 2 , respectively. Our data showed that 0.02 M NaHCO 3 promoted algal growth and that sparging cultures with ambient air after 12 days raised pH and created favorable CaCO 3 formation conditions. At the 1 L scale, we reached 1.52 g L −1 biomass after 12 days and an extra 9.3% CO 2 was captured in the form of CaCO 3 precipitates. At the 500 L pilot scale, an extra 60% CO 2 was captured (Day 40) with a maximum CO 2 capture rate of 63.2 g m −2 day −1 (Day 35). Bacterial communities associated with the microalgae were dominated by two novel Patescibacteria. Functional analysis revealed that genes for several plant growth-promotion traits (PGPTs) were enriched within this group. The microalgal-bacterial coculture system offers advantages for enhanced carbon mitigation through biomass production and simultaneous precipitation of recalcitrant CaCO 3 for long-term CO 2 storage. IMPORTANCE Capturing carbon dioxide (CO 2 ) released from fossil fuel combustion is of the utmost importance as the impacts of climate change continue to worsen. Microalgae can remove CO 2 through their natural photosynthetic pathways and are additionally able to convert CO 2 into a stable, recalcitrant form as calcium carbonate (CaCO 3 ). We demonstrate that microalgae-based carbon capture systems can be greatly improved with high pH and high alkalinity by providing optimal conditions for carbonate precipitation. Our results with the microalga, Nannochloropsis oceanica strain IMET1, show an extra 9.3% CO 2 captured as CaCO 3 at the 1 L scale and an extra 60% CO 2 captured at the 500 L (pilot) scale. Our optimized system provides a novel approach to capture CO 2 through two mechanisms: (i) as organic carbon within microalgal biomass and (ii) as inorganic carbon stored permanently in the form of CaCO 3.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Dynamical Components Analysis (DCA) v1.0.0

Dynamical Components Analysis is a Python implementation of the method described in "Unsupervised discovery of temporal structure in noisy data with dynamical components analysis". It implements the method as well as related data analysis functions.

Livezey, Jesse↗
DOE OSTI2021

Dynamical Components Analysis (DCA) v1.0.0

Dynamical Components Analysis is a Python implementation of the method described in "Unsupervised discovery of temporal structure in noisy data with dynamical components analysis". It implements the method as well as related data analysis functions.

Livezey, Jesse↗
DOE OSTI2026

EFBMC

SAND2026-23986O EFBMC performs elastic Bayesian model calibration by applying Bayesian statistics and functional analysis. The software provides Python, R, and MATLAB scripts that enable users to calibrate models. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Tucker, J. Derek [Sandia National Lab. (SNL-CA), L↗
DOE OSTI2021

Dynamic structural views in solar energy materials by femtosecond electron diffraction

Solar materials convert light into other forms of energy through excited state processes occurring on ultrafast time and atomic length scales. Understanding and controlling such nonequilibrium processes is essential for applications ranging from photovoltaics to photocatalysis. These processes are commonly studied by transient optical techniques, which resolve charge carrier dynamics. However, optical spectroscopy does not directly probe the atomic-scale motions that play a central role in the ultimate functionality of these materials. Filling this missing gap, ultrafast electron and x-ray scattering techniques enable monitoring of structural dynamics in materials with femtosecond time resolution. In this work, we focus on the use of ultrafast electron diffraction (UED) techniques to probe photoinduced energy conversion dynamics in solar energy materials. First, we discuss the use of UED as an ultrafast lattice thermometer allowing a direct probe of nonradiative relaxations such as hot carrier cooling and Auger recombination. Second, we present a time-resolved atomic pair distribution function analysis enabled by UED, which uncovers lattice deformations arising from excitation localization in materials. Finally, we provide an outlook looking toward new approaches for resolving in situ energy conversion dynamics and uncovering structure–property relationships in solar energy materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Pursuing Dark Energy with Large Galaxy Redshift Surveys: Baryon Acoustic Oscillations and Beyond (Final Technical Report)

We have developed and applied methods of large-scale structure from galaxy redshift surveys to the study of dark energy. This program supported my group's development of the baryon acoustic method and our participation in the Dark Energy Spectroscopic Instrument (DESI) survey. In addition to my leadership role in the DESI collaboration, my group at Harvard focused on several topics addressing key needs of the DESI science program. 1) We continued our design, validation, and documentation of DESI target selection of the luminous red galaxy and emission-line galaxy samples. 2) We applied simulations from our novel and extremely fast N-body code to make DESI catalogs. With these, we will search for possible systematic shifts in the acoustic scale due to clustering bias with an unprecedented volume of simulations. 3) We extended our method for the fast construction of covariance matrices for correlation functions. 4) We developed new large-scale structure methods, including density-field reconstruction and three-point function analysis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

High Fidelity Modeling of WELL58-32 DFITS

Between 2017 and 2019, a series of injection tests were performed at pilot vertical well 58-32 at the Utah FORGE site. These injection activities were conducted in three distinct zones, isolated with packers and bridge plugs during the tests. Zone 1 consists of an open-hole section at the toe of the well, whereas Zones 2 and 3 are three-meter long cased and perforated sections. Several injection cycles were conducted in each zone. A detailed description of the geology of the FORGE site, of well 58-32 and of all injection cycles can be found in (Xing et al., 2020). The injection cycles included Diagnostic Fracture Injection Tests (DFITs). DFITs comprise two primary stages: an injection (pump-in) phase, where controlled fluid injection is employed to create a small hydraulic fracture in the surrounding rock, followed by a shut-in phase, where injection ceases, allowing observation of the formation’s pressure response. Utilizing methodologies such as the G-function analysis, DFITs provide valuable insights, including fracture closure pressure and the Instantaneous Shut-in Pressure (ISIP) and can be employed to estimate the minimum horizontal stress.

42 ENGINEERING↗
DOE OSTI2025

FRAM Version 7.1’s Bias

The Fixed-Energy Response-Function Analysis with Multiple Efficiency (FRAM) code was developed at Los Alamos National Laboratory to measure the gamma-ray spectrometry of the isotopic composition of plutonium, uranium, and other actinides. For FRAM versions 4 and earlier, the reported uncertainties of the results come from the propagation of the statistics in the peak areas only. No systematic error components are included in the reported uncertainties. For FRAM versions 5 and 6, we examined the FRAM analytical results of both the archival plutonium data and the data specifically acquired for the isotopic uncertainty analysis project and found the relationship between the bias and other parameters. We worked out the equations representing the biases of the measured isotopes from each measurement using internal spectral parameters, such as peak resolution and shape, region of analysis, and burnup (for plutonium) or enrichment (for uranium). The resulting biases were included in the reported uncertainties of FRAM v.5 and v.6.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

FRAM v.7.1

Fixed-energy Response-function Analysis with Multiple efficiency (FRAM) is a software code designed primarily for plutonium and uranium isotopic analysis. It is widely used in both the domestic and international safeguards community. FRAM can quickly and accurately determine the isotopic compositions of plutonium, uranium, and mixed oxides (MOX) when measuring with a high-purity germanium (HPGe), cadmium zinc telluride (CZT), or lanthanum bromide (LaBr3) detector. The capabilities of FRAM have been enhanced to analyze the data of the pixelated CZT detector (made by H3D) and to measure the mass of plutonium, uranium, and MOX. Both the isotopic composition and mass of the item can be quickly determined with one measurement using a gamma detector with FRAM v.7.1.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2026

Final Report for Closing the Loop Between In Situ Stress Complexity and EGS Fracture Complexity

Characterizing in situ stress is essential in Enhanced Geothermal System (EGS) for both risk assessment and operation design. Standard stress measurement techniques such as diagnostic fracture injection tests (DFITs) require creating hydraulic fractures and apply analytical methods such as the G -function analysis to estimate the stress. These classical approaches rely on several assumptions, including but not limited to: (i) the induced fracture is planar and persistent, and (ii) the fracture plane is normal to the minimum horizontal stress. However, these assumptions may not hold in EGS environments like Utah FORGE, where thermo-hydro-mechanical (THM) coupling, wellbore deviation, and rock heterogeneity can alter the local stress condition and consequently lead to fracture complexities in both near-well and far-field regions.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

DeepComplex: A Web Server of Predicting Protein Complex Structures by Deep Learning Inter-chain Contact Prediction and Distance-Based Modelling

Proteins interact to form complexes. Predicting the quaternary structure of protein complexes is useful for protein function analysis, protein engineering, and drug design. However, few user-friendly tools leveraging the latest deep learning technology for inter-chain contact prediction and the distance-based modelling to predict protein quaternary structures are available. To address this gap, we develop DeepComplex, a web server for predicting structures of dimeric protein complexes. It uses deep learning to predict inter-chain contacts in a homodimer or heterodimer. The predicted contacts are then used to construct a quaternary structure of the dimer by the distance-based modelling, which can be interactively viewed and analysed. The web server is freely accessible and requires no registration. It can be easily used by providing a job name and an email address along with the tertiary structure for one chain of a homodimer or two chains of a heterodimer. The output webpage provides the multiple sequence alignment, predicted inter-chain residue-residue contact map, and predicted quaternary structure of the dimer.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

ATOMIC AND MICROSTRUCTURAL ORIGINS OF STORED ENERGY RELEASE IN NEUTRON-IRRADIATED SILICON CARBIDE

Here, we employ a combination of advanced synchrotron-based scattering characterization techniques to understand and unravel the atomic origins of the colossal stored energy release in neutron irradiated silicon carbide. The quantification of the neutron irradiation-induced defects, and their impact on the structureproperty relationship is important for the design and safe operation of advanced fission and fusion reactors. Our experimental results show that the atomic structure in the as irradiated samples is significantly perturbed due to a large fraction of vacancy and interstitial type defects that lead to complex microstructures and additional components in the x-ray diffraction and pair distribution function results. We directly correlate the stored energy release to the recovery of the sub-lattices, with pair distribution function analysis highlighting that the carbon interstitial and vacancy-type defects contribute to stored energy more than those of silicon. We find these results to be striking and believe our discoveries to be timely and noteworthy given the technological importance of silicon carbide to the nuclear fission and fusion communities.

Sprouster, D.J.↗