Search NASA⌕ Search

SEARCH · Search NASA

Results for “Variants”

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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Improved genome editing by an engineered CRISPR-Cas12a

CRISPR-Cas12a is an RNA-guided, programmable genome editing enzyme found within bacterial adaptive immune pathways. Unlike CRISPR-Cas9, Cas12a uses only a single catalytic site to both cleave target double-stranded DNA (dsDNA) (cis-activity) and indiscriminately degrade single-stranded DNA (ssDNA) (trans-activity). To investigate how the relative potency of cis- versus trans-DNase activity affects Cas12a-mediated genome editing, we first used structure-guided engineering to generate variants of Lachnospiraceae bacterium Cas12a that selectively disrupt trans-activity. The resulting engineered mutant with the biggest differential between cis - and trans -DNase activity in vitro showed minimal genome editing activity in human cells, motivating a second set of experiments using directed evolution to generate additional mutants with robust genome editing activity. Notably, these engineered and evolved mutants had enhanced ability to induce homology-directed repair (HDR) editing by 2–18-fold compared to wild-type Cas12a when using HDR donors containing mismatches with crRNA at the PAM-distal region. Finally, a site-specific reversion mutation produced improved Cas12a (iCas12a) variants with superior genome editing efficiency at genomic sites that are difficult to edit using wild-type Cas12a. This strategy establishes a pipeline for creating improved genome editing tools by combining structural insights with randomization and selection. The available structures of other CRISPR-Cas enzymes will enable this strategy to be applied to improve the efficacy of other genome-editing proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Metagenomics harvested genus-specific single-stranded DNA-annealing proteins improve and expand recombineering in Pseudomonas species

The widespread Pseudomonas genus comprises a collection of related species with remarkable abilities to degrade plastics and polluted wastes and to produce a broad set of valuable compounds, ranging from bulk chemicals to pharmaceuticals. Pseudomonas possess characteristics of tolerance and stress resistance making them valuable hosts for industrial and environmental biotechnology. However, efficient and high-throughput genetic engineering tools have limited metabolic engineering efforts and applications. To improve their genome editing capabilities, we first employed a computational biology workflow to generate a genus-specific library of potential single-stranded DNA-annealing proteins (SSAPs). Assessment of the library was performed in different Pseudomonas using a high-throughput pooled recombinase screen followed by Oxford Nanopore NGS analysis. Among different active variants with variable levels of allelic replacement frequency (ARF), efficient SSAPs were found and characterized for mediating recombineering in the four tested species. New variants yielded higher ARFs than existing ones in Pseudomonas putida and Pseudomonas aeruginosa, and expanded the field of recombineering in Pseudomonas taiwanensisand Pseudomonas fluorescens. These findings will enhance the mutagenesis capabilities of these members of the Pseudomonas genus, increasing the possibilities for biotransformation and enhancing their potential for synthetic biology applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

VISTA Enhancer browser: an updated database of tissue-specific developmental enhancers

Regulatory elements (enhancers) are major drivers of gene expression in mammals and harbor many genetic variants associated with human diseases. Here, we present an updated VISTA Enhancer Browser (https://enhancer.lbl.gov), a database of transgenic enhancer assays conducted in developing mouse embryos in vivo. Since the original publication in 2007, the database grew nearly 20-fold from 250 to over 4500 experiments and currently harbors over 23 500 images. The updated database provides structured information on experiments conducted at different stages of embryonic development, including enhancer activities of human pathogenic and synthetic variants and sequences derived from a variety of species. In addition to manually curated results of thousands of individual experiments, the new database also features hundreds of manually curated comparisons between alleles. The VISTA Enhancer Browser provides a crucial resource for study of human genetic variation, gene regulation and developmental biology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Metabolic Source Isotopic Pair Labeling and Genome-Wide Association Are Complementary Tools for the Identification of Metabolite-Gene Associations in Plants

The optimal extraction of information from untargeted metabolomics analyses is a continuing challenge. Here, we describe an approach that combines stable isotope labeling, liquid chromatography– mass spectrometry (LC–MS), and a computational pipeline to automatically identify metabolites produced from a selected metabolic precursor. Here, we identified the subset of the soluble metabolome generated from phenylalanine (Phe) in Arabidopsis thaliana, which we refer to as the Phe-derived metabolome (FDM) In addition to identifying Phe-derived metabolites present in a single wild-type reference accession, the FDM was established in nine enzymatic and regulatory mutants in the phenylpropanoid pathway. To identify genes associated with variation in Phe-derived metabolites in Arabidopsis, MS features collected by untargeted metabolite profiling of an Arabidopsis diversity panel were retrospectively annotated to the FDM and natural genetic variants responsible for differences in accumulation of FDM features were identified by genome-wide association. Large differences in Phe-derived metabolite accumulation and presence/absence variation of abundant metabolites were observed in the nine mutants as well as between accessions from the diversity panel. Many Phe-derived metabolites that accumulated in mutants also accumulated in non-Col-0 accessions and was associated to genes with known or suspected functions in the phenylpropanoid pathway as well as genes with no known functions. Overall, we show that cataloguing a biochemical pathway’s products through isotopic labeling across genetic variants can substantially contribute to the identification of metabolites and genes associated with their biosynthesis.

09 BIOMASS FUELS↗
DOE OSTI2022

Evolutionary analysis of the LORELEI gene family in plants reveals regulatory subfunctionalization

Abstract A signaling complex comprising members of the LORELEI (LRE)-LIKE GPI-anchored protein (LLG) and Catharanthus roseus RECEPTOR-LIKE KINASE 1-LIKE (CrRLK1L) families perceive RAPID ALKALINIZATION FACTOR (RALF) peptides and regulate growth, reproduction, immunity, and stress responses in Arabidopsis (Arabidopsis thaliana). Genes encoding these proteins are members of multigene families in most angiosperms and could generate thousands of signaling complex variants. However, the links between expansion of these gene families and the functional diversification of this critical signaling complex as well as the evolutionary factors underlying the maintenance of gene duplicates remain unknown. Here, we investigated LLG gene family evolution by sampling land plant genomes and explored the function and expression of angiosperm LLGs. We found that LLG diversity within major land plant lineages is primarily due to lineage-specific duplication events, and that these duplications occurred both early in the history of these lineages and more recently. Our complementation and expression analyses showed that expression divergence (i.e. regulatory subfunctionalization), rather than functional divergence, explains the retention of LLG paralogs. Interestingly, all but one monocot and all eudicot species examined had an LLG copy with preferential expression in male reproductive tissues, while the other duplicate copies showed highest levels of expression in female or vegetative tissues. The single LLG copy in Amborella trichopoda is expressed vastly higher in male compared to in female reproductive or vegetative tissues. We propose that expression divergence plays an important role in retention of LLG duplicates in angiosperms.

Plant Sciences↗
DOE OSTI2019

Attempts to develop an enzyme converting DHIV to KIV

Abstract Dihydroxy-acid dehydratase (DHAD) catalyzes the dehydration of R-2,3-dihydroxyisovalerate (DHIV) to 2-ketoisovalerate (KIV) using an Fe-S cluster as a cofactor, which is sensitive to oxidation and expensive to synthesize. In contrast, sugar acid dehydratases catalyze the same chemical reactions using a magnesium ion. Here, we attempted to substitute the high-cost DHAD with a cost-efficient engineered sugar acid dehydratase using computational protein design (CPD). First, we tried without success to modify the binding pocket of a sugar acid dehydratase to accommodate the smaller, more hydrophobic DHIV. Then, we used a chemically activated substrate analog to react with sugar acid dehydratases or other enolase superfamily enzymes. Mandelate racemase from Pseudomonas putida (PpManR) and the putative sugar acid dehydratase from Salmonella typhimurium (StPutD) showed beta-elimination activity towards chlorolactate (CLD). CPD combined with medium-throughput selection improved the PpManR kcat/KM for CLD by four-fold. However, these enzyme variants did not show dehydration activity towards DHIV. Lastly, assuming phosphorylation could also be a good activation mechanism, we found that mevalonate-3-kinase (M3K) from Picrophilus torridus (PtM3K) exhibited adenosine triphosphate (ATP) hydrolysis activity when mixed with DHIV, indicating phosphorylation activity towards DHIV. Engineering PpManR or StPutD to accept 3-phospho-DHIV as a substrate was performed, but no variants with the desired activity were obtained.

Oki, Kenji↗
DOE OSTI2025

High-resolution X-ray structure of Gln143Asn manganese superoxide dismutase captures multiple hydrogen peroxide-binding sites

Human mitochondrial manganese superoxide dismutase (MnSOD) converts superoxide into hydrogen peroxide and molecular oxygen, serving as a key defence against oxidative damage. Despite extensive studies, the full structural characterization of H 2 O 2 -binding sites in MnSOD remains largely unexplored. Previous H 2 O 2 -soaked MnSOD structures have identified two distinct H 2 O 2 -binding sites: one directly ligated to the catalytic manganese (LIG position) and another at the active-site gateway (PEO position) between the second-shell residues Tyr34 and His30. In this study, a kinetically impaired Gln143Asn MnSOD variant is used to trap and explore additional H 2 O 2 -binding sites beyond the second-shell solvent gate. In the wild-type enzyme, Gln143 mediates proton transfers with the manganese-bound solvent (WAT1) to drive redox cycling of the metal, which is necessary for effective superoxide dismutation. Substitution with Asn stalls catalysis because the increased distance from WAT1 disrupts critical proton-coupled electron-transfer (PCET) events, and the redox cycling of the active-site metal is impaired. This, in turn, stalls the electrostatic cycling of positive charge on the enzyme surface and enhances the likelihood of trapping transient H 2 O 2 -bound states in this variant. The results reveal several H 2 O 2 molecules leading up to the active site, in addition to the canonical LIG and PEO positions.

Dasgupta, Medhanjali [University of Nebraska Medic↗
DOE OSTI2020

Design of an Axial Flux Machine With an Integrated Hydraulic Pump for Off-Highway Vehicle Electrification

Axial flux machines offer an inherent torque density advantage over conventional radial flux machines and are increasingly being considered for transportation electrification applications. Electrification of off-highway vehicles is notoriously challenging due to extreme power density requirements. This paper investigates the use of axial flux machines for off-highway vehicle electrification. To maximize the power density, a hydraulic pump is integrated with the axial flux machine, resulting in a single modular, electric/hydraulic machine. This paper first compares three popular axial flux machine variants using an FEA-based design optimization approach. The single rotor, single stator variant is identified to be the most promising for integration with the hydraulic pump. Next, a multi-physics framework of the complete integrated hydraulic pump and axial flux machine is developed to search the design space. The results indicate promising potential for this concept to realize efficiency over 85% and power density over 5kW/kg for the complete machine (electric machine, hydraulic pump, and thermal management system), while utilizing conventional materials (thin gauge silicon steel, N45 magnets, and magnet wire)

Off-highway vehicles, Axial flux machines, Multi-p↗
DOE OSTI2024

Comparative Study of Large Language Model Architectures on Frontier

Large language models (LLMs) have garnered significant attention in both the AI community and beyond. Among these, the Generative Pre-trained Transformer (GPT) has emerged as the dominant architecture, spawning numerous variants. However, these variants have undergone pre-training under diverse conditions, including variations in input data, data preprocessing, and training methodologies, resulting in a lack of controlled comparative studies. Here we meticulously examine two prominent open-sourced GPT architectures, GPT-NeoX and LLaMA, leveraging the computational power of Frontier, the world’s first Exascale supercomputer. Employing the same materials science text corpus and a comprehensive end-to-end pipeline, we conduct a comparative analysis of their training and downstream performance. Our efforts culminate in achieving state-of-the-art performance on a challenging materials science benchmark. Furthermore, we investigate the computation and energy efficiency, and propose a computationally efficient method for architecture design. To our knowledge, these pre-trained models represent the largest available for materials science. Our findings provide practical guidance for building LLMs on HPC platforms.

Yin, Junqi↗
DOE OSTI2022

Evaluation of PV Module Packaging Strategies of Monofacial and Bifacial PERC Using Degradation Pathway Network Modeling

As the PV industry is rapidly expanding, it is important to thoroughly investigate the long-term impact of packaging strategies on the performance of PV modules. In this study, the variants in sets differ on the basis of manufacturer (A/B), encapsulant (EVA/POE), rear encapsulant (UV-cutoff/opaque/transparent), module architecture (GB/DG) and cell type (monofacial/bifacial). The minimodules were exposed for 2520 hours in modified damp heat, with or without full spectrum light. Every 504 hours, stepwise electrical characterization techniques were employed to track changes in minimodules. Degradation pathway modeling using network structural equation modeling was employed to study pairwise relationships between variables and service lifetime prediction in minimodules. Through this study, differences in quality control are identified in minimodules made by different manufacturers. Minimodules with UV-cutoff rear encapsulant show relatively better stability, whereas the ones with opaque rear encapsulant show greater power loss. In addition, GB having UV-cutoff rear encapsulation and GB with POE having opaque rear encapsulation were identified to be stable as they lack a best model fit. Here, the primary power loss mechanism in degrading variants is interconnect corrosion.

14 SOLAR ENERGY↗
DOE OSTI2022

Development of an Integrated Electro-Hydraulic Machine to Electrify Off-highway Vehicles

Electrification of off-highway vehicles is notoriously challenging due to extreme power density requirements. This paper proposes and develops an axial flux machine integrated with a hydraulic pump to realize a single modular, electro-hydraulic machine to electrify off-highway vehicle implements. This integrated machine eliminates redundant bearings, couplings, and shaft seals, re-uses surfaces, and enables direct cooling of the electric machine with the hydraulic fluid, to significantly increase power density. Three popular axial flux machine variants are first compared using an FEA-based design optimization approach. The single rotor, single stator variant is identified to be the most promising for integration with the hydraulic pump. Next, a multi-physics framework of the complete integrated hydraulic pump and axial flux machine is developed to characterize the design space. The results indicate promising potential for this concept to realize efficiency over 85% and power density over 5kW/kg for the complete machine (electric machine, hydraulic pump, and thermal management system), while utilizing conventional materials (thin gauge silicon steel, N45 magnets, and enamelled copper wire). Furthermore, a prototype axial flux machine has been experimentally characterized and integrated with a hydraulic pump to demonstrate the integrated electro-hydraulic machine concept.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

A Review of Axial Flux Permanent Magnet Machine Technology

Axial flux permanent magnet machines (AFPM) are popular for applications that benefit from high torque density and an axially compact form factor, such as in-wheel traction drives. Although the radial flux permanent magnet machine (RFPM) and the AFPM work based on the same underlying principle, the differences in their geometry introduce complexities in analysis of the AFPM. In this paper, the different AFPM design variants, their sizing approaches, computationally efficient design optimization techniques, and manufacturing techniques reported in literature are reviewed. In addition to classical AFPM machines, emerging variants and research opportunities with potential to push the boundaries of electric machine technology are reviewed. Furthermore, these include bearingless AFPMs, magnetically geared AFPMs, and combined radial-axial flux machines.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Evaluation of Torque-Dense Electric Machine Technology for Off-Highway Vehicle Electrification

Electrification of off-highway vehicles offers the benefits of improved energy efficiency, enhanced control, and reduction in greenhouse gas emissions. However, progress towards electrification has been limited by the low torque density (30 kNm/m 3 ) of conventional electric machines compared to mobile hydraulic machines (up to approximately 1000 kNm/m 3 ). This paper reviews emerging variants of electric machines that offer a step improvement in torque density and potential pathway to enable electrified off-highway vehicles. First, sizing approaches for electric and hydraulic machines are developed, and torque-dense electric machines reviewed in literature are compared to commercial hydraulic machines to identify design trends in terms of speed, torque density, and power density. Next, key metrics are identified for the electric machine, based on which the following four emerging electric machine variants that promise to improve torque density are reviewed: i) multi-harmonic machines injection, ii) combined radial-axial flux machines, iii) magnetic gears, and iv) magnetically-geared machines. Here, the findings from this review show that these new electric machines can achieve upwards of 300% improvement in electric machine torque density, with several designs exceeding 100 kNm/m 3 , making them worthy candidates for further research to bridge the torque density gap with hydraulic machines.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Anomaly Detection, Localization and Classification using Drifting Synchrophasor Data Streams

With ongoing automation and digitization of the electric power system, several Phasor Measurement Units(PMUs) have been deployed for monitoring and control. PMU data can have multiple anomalies, and many of the researchers in the past have concentrated on training machine/deep learning algorithms offline for anomaly detection over PMU data (i.e., not in real time). These machine/deep learning algorithms, when trained offline on a sample rather than a population of the dataset, fail to consider the dynamic behavior of the power grid in real-time, resulting in low accuracy. Considering the dynamic behavior of the power grid (e.g., change in load, generation, distributed energy resources (DERs) switching, network, controls), the definition of data anomalies varies in time and requires online training. A fundamental challenge is to enable online (i.e., real-time) training of machine/deep learning algorithms for anomaly detection over streaming PMU data. While machine/deep learning is often desirable to manage data streams, training a deep learning algorithm over streaming PMU data is nontrivial due to changes in data statistics caused by dynamic streaming data. This paper proposes PMUNET: a novel device-level deep learning-based data-driven approach for anomaly detection, localization, and classification over streaming PMU data, using online learning and multivariate data-drift detection algorithm .Two variants of PMUNET, Dynamic data Change Driven Learning (DCDL) and Continuity Driven Learning (CDL), are proposed and compared. DCDL aims to train the deep learning algorithm whenever the definition of anomaly changes due to the power grid dynamics. On the other hand, CDL continuously trains the deep learning algorithm over the PMU data-stream. The experimental results verify that DCDL outperforms CDL and other efficient anomaly detection methods over multiple events such as faults and load/ generator/capacitor/DERs variations/switching for IEEE 14 and 39 Bus test system as well as real PMU industrial data. The result verifies that DCDL variant of PMUNET improves over existing approach with a gain of 2% - 10% in terms of accuracy, false-positive rate, and false-negative rate.

adversarial deep learning↗
DOE OSTI2023

PacBio high‐throughput multi‐locus sequencing reveals high genetic diversity in mushroom‐forming fungi

Abstract Multi‐locus sequence data are widely used in fungal systematic and taxonomic studies to delimit species and infer evolutionary relationships. We developed and assessed the efficacy of a multi‐locus pooled sequencing method using PacBio long‐read high‐throughput sequencing. Samples included fresh and dried voucher specimens, cultures and archival DNA extracts of Agaricomycetes with an emphasis on the order Cantharellales. Of the 283 specimens sequenced, 93.6% successfully amplified at one or more loci with a mean of 3.3 loci amplified. Our method recovered multiple sequence variants representing alleles of rDNA loci and single copy protein‐coding genesrpb1,rpb2 andtef1. Within‐sample genetic variation differed by locus and taxonomic group, with the greatest genetic divergence observed among sequence variants ofrpb2 andtef1 from corticioid Cantharellales. Our method is a cost‐effective approach for generating accurate multi‐locus sequence data coupled with recovery of alleles from polymorphic samples and multi‐organism specimens. These results have important implications for understanding intra‐individual genomic variation among genetic loci commonly used in species delimitation of fungi.

Biochemistry & Molecular Biology↗
DOE OSTI2026

Linking Domain Structure Evolution at a Grain Boundary to Piezoelectric Response via Nano‐Diffraction

Electric-field-induced domain structure switching in a 1 𝜇⁢m -thick Pb 0.99 (Zr 0.45 Ti 0.55 ) 0.98 Nb 0.02 O 3 (Nb-doped PZT) bicrystal film was characterized in situ via nano-focused synchrotron diffraction. The epitaxial film was deposited on a (100) SrTiO 3 bicrystal substrate. The changes in domain structure were mapped within a 5 𝜇⁢m × 5 𝜇⁢m area at and around an in-plane tilt-type (23.6°) grain boundary with 50 nm spatial resolution. Rocking curves collected at each point of the mapped area provided the ability to reconstruct spatially-varying three-dimensional (3D) reciprocal space maps around the grain boundary. The 3D reciprocal space maps reveal how different tilted 𝑎 -type domain variants interact with the grain boundary as a function of increasing electric field. Initially, a subset of 𝑎 -type domain variants with their polarization vectors largely orthogonal to the grain boundary were found in greater abundance within 570 nm of the grain boundary, possibly due to X-ray beam-induced local increases in the electrical conductivity, but after the coercive field was exceeded, reconfiguration of the ferroelastic domains was observed. The spatially-varying reciprocal space maps also facilitated evaluation of the strain field across the mapped area, along with 𝑑 33,𝑓 . Significant spatial heterogeneity of strain and 𝑑 33,𝑓 are observed, especially at the coercive field, which was attributed to maintaining deformation compatibility and correlated ferroelastic switching.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Quantitative order-parameter measurement in lattice-mismatched AlInP using precession electron diffraction

Precession electron diffraction (PED) was used to measure the long-range order parameter in lattice-mismatched AlInP epitaxial films under investigation for solid-state-lighting applications. Both double- and single-variant films grown at 620, 650, and 680°C were analyzed in TEM cross-section. PED patterns were acquired in selected-area-diffraction mode through external microscope control using serial acquisition, which allows inline image processing. The integrated peak intensities from experimental patterns were fit using dynamical simulations of diffraction from the ordered domain structures. Included in the structure-factor calculations were mean atomic displacements of the anions (P) due to ordering, which were found by valence-force-field calculations to have a nearly linear dependence on order parameter. A maximum order parameter of S = 0.36 was measured for a double-variant specimen grown at 650°C.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

Design and fabrication of ion traps for low RF power dissipation

Large surface-electrode ion traps with multiple trapping regions and junctions are a natural approach to scaling trapped ion quantum computers, supporting the connectivity and ion counts necessary for complex quantum algorithms. However, a major hurdle in this scaling is on-chip power dissipation from the applied RF voltage, which increases at a rate between linear and cubic relative to trap size, depending on whether the losses are dielectric or Ohmic. Here, we present two versions of a trap with features designed to reduce both types of RF power dissipation. The first variant contains a raised RF electrode that increases the electrode–ground distance to reduce capacitance. Different DC voltage sources are demonstrated on this trap to show that technical noise before the filter remains the dominant source of voltage noise and therefore motional heating. The second variant additionally includes a method for removing dielectric from beneath the RF electrode to further reduce dielectric losses. These traps were demonstrated at room temperature with 40 Ca + ions. In conclusion, the similar heating rates and heating rate axial frequency dependencies between 2.4 and 3.0 MHz illustrate that this dielectric modification is not detrimental to trap performance.

Sterk, J. D. [Sandia National Laboratories (SNL-NM↗