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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Preliminary results of teleseismic double-difference relocation of earthquakes around Indonesian archipelago region

Indonesian archipelago region is located in active tectonic setting and high seismicity zone. During the last decade, Indonesian was experienced with destructive major earthquakes causing damage and victims. The information of precise earthquake location parameters are very important in partular for earthquake early warning to the society and for advance seismic studies. In this study, we attempted to improve hypocenter location compiled by BMKG for time periods of April, 2009 up to June, 2014 for about 22,000 earthquake events around Indonesian region. For the firts time, we applied teleseismic double-difference relocation algorithm (teletomoDD) to improve hypocenter region in Indonesia region combining regional and teleseismic stations. Hypocenter relocation was performed utilizing local, regional, and teleseismic P-wave arrival time data. Our relocation result show that travel-time RMS errors were greatly reduced compared to the BMKG catalog. Seismicity at shallower depth (less than 50 km) shows significantly improvement especially in depth, and refined shallow geological structures, e.g. trench and major strike slip faults. Clustered seismicity is also detected beneath volcanic region, and probably related volcano activities and also major faults nearby. In the Sunda arc region, seismicity at shallower depth centered at two major distributions parallel to the trench strike direction, i.e. around fore-arc and in mainland that related to major fault, e.g. the Sumatran fault, and volcanic fronts. Below Central Java region, relocated hypocenter result showed double seismic zone pattern. A seismic gap is detected around the Sunda-Banda transition zone where transition between oceanic subduction to continental crust collision of Australian plate occurs. In Eastern Indonesia region, shallow earthquakes are observed related to major strike slip faults, e.g. Sorong and Palu-Koro fault, volcanism, and shallow part of subduction and collision zones. We also compare our result in the Sunda Arc region with slab1.0 model and our relocated seismicity shows good agreement with the previous slab geometry. Horizontal position shift of relocated events are mostly perpendicular to the trench directions.

58 GEOSCIENCES↗
DOE OSTI2017

XRootD popularity on hadoop clusters

Performance data and metadata of the computing operations at the CMS experiment are collected through a distributed monitoring infrastructure, currently relying on a traditional Oracle database system. This paper shows how to harness Big Data architectures in order to improve the throughput and the efficiency of such monitoring. A large set of operational data - user activities, job submissions, resources, file transfers, site efficiencies, software releases, network traffic, machine logs - is being injected into a readily available Hadoop cluster, via several data streamers. The collected metadata is further organized running fast arbitrary queries; this offers the ability to test several Map&Reduce-based frameworks and measure the system speed-up when compared to the original database infrastructure. By leveraging a quality Hadoop data store and enabling an analytics framework on top, it is possible to design a mining platform to predict dataset popularity and discover patterns and correlations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

RECOVERY ACT - Robust Optimization for Connectivity and Flows in Dynamic Complex Networks

The goal of this project was to study robust connectivity and flow patterns of complex multi-scale systems modeled as networks. Networks provide effective ways to study global, system level properties, as well as local, multi-scale interactions at a component level. Numerous applications from power systems, telecommunication, transportation, biology, social science, and other areas have benefited from novel network-based models and their analysis. Modeling and optimization techniques that employ appropriate measures of risk for identifying robust clusters and resilient network designs in networks subject to uncertain failures were investigated in this collaborative multi-university project. In many practical situations one has to deal with uncertainties associated with possible failures of network components, thereby affecting the overall efficiency and performance of the system (e.g., every node/connection has a probability of partial or complete failure). Some extreme examples include power grid component failures, airline hub failures due to weather, or freeway closures due to emergencies. These are also situations in which people, materials, or other resources need to be managed efficiently. Important practical examples include rerouting flow through power grids, adjusting flight plans, and identifying routes for emergency services and supplies, in the event network elements fail unexpectedly. Solutions that are robust under uncertainty, in addition to being economically efficient, are needed. This project has led to the development of novel models and methodologies that can tackle the optimization problems arising in such situations. A number of new concepts, which have not been previously applied in this setting, were investigated in the framework of the project. The results can potentially help decision-makers to better control and identify robust or risk-averse decisions in such situations. Formulations and optimal solutions of the considered problems need to capture uncertainty and risk using appropriate probabilistic, statistical and optimization concepts. The main difficulty arising in addressing these issues is the dramatic increase in the computational complexity of the resulting optimization problems. This project studied novel models and methodologies for risk-averse network optimization- specifically, network design, network flows and cluster detection problems under uncertainty. The approach taken was to incorporate a quantitative risk measure known as conditional value-at-risk that is widely used in financial applications. This approach presents a viable alternate modeling and optimization framework to chance-constrained optimization and mean-variance optimization, one that also facilitates the detection of risk-averse solutions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Characterization and Regulation of Aquaporin Genes of Sorghum [ Sorghum bicolor (L.) Moench] in Response to Waterlogging Stress

Waterlogging is a significant environmental constraint to crop production, and a better understanding of plant responses is critical for the improvement of crop tolerance to waterlogged soils. Aquaporins (AQPs) are a class of channel-forming proteins that play an important role in water transport in plants. Our study aimed to examine the regulation of AQP genes under waterlogging stress and to characterize the genetic variability of AQP genes in sorghum (Sorghum bicolor). Transcriptional profiling of AQP genes in response to waterlogging stress in nodal root tips and nodal root basal regions of two tolerant and two sensitive sorghum genotypes at 18 and 96 h after waterlogging stress imposition revealed significant gene-specific pattern with regard to genotype, root tissue sample, and time point. For some tissue sample and time point combinations, PIP2-6, PIP2-7, TIP2-2, TIP4-4, and TIP5-1 expression was differentially regulated in tolerant compared to sensitive genotypes. The differential response of these AQP genes suggests that they may play a tissue specific role in mitigating waterlogging stress. Genetic analysis of sorghum revealed that AQP genes were clustered into the same four subfamilies as in maize (Zea mays) and rice (Oryza sativa) and that residues determining the AQP channel specificity were largely conserved across species. Single nucleotide polymorphism (SNP) data from 50 sorghum accessions were used to build an AQP gene-based phylogeny of the haplotypes. Phylogenetic analysis based on single nucleotide polymorphisms of sorghum AQP genes placed the tolerant and sensitive genotypes used for the expression study in distinct groups. Expression analyses suggested that selected AQPs may play a pivotal role in sorghum tolerance to water logging stress. Furthermore experimentation is needed to verify their role and to leverage phylogenetic analyses and AQP expression data to improve water logging tolerance in sorghum.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

GazeAppraise v. 0.1

GazeAppraise advances the state of the art of gaze pattern analysis using methods that simultaneously analyze spatial and temporal characteristics of gaze patterns. GazeAppraise enables novel research in visual perception and cognition; for example, using shape features as distinguishing elements to assess individual differences in visual search strategy. Given a set of point-to-point gaze sequences, hereafter referred to as scanpaths, the method constructs multiple descriptive features for each scanpath. Once the scanpath features have been calculated, they are used to form a multidimensional vector representing each scanpath and cluster analysis is performed on the set of vectors from all scanpaths. An additional benefit of this method is the identification of causal or correlated characteristics of the stimuli, subjects, and visual task through statistical analysis of descriptive metadata distributions within and across clusters.

Wilson, Andrew↗
DOE OSTI2023

Large-scale genomic analyses with machine learning uncover predictive patterns associated with fungal phytopathogenic lifestyles and traits

Abstract Invasive plant pathogenic fungi have a global impact, with devastating economic and environmental effects on crops and forests. Biosurveillance, a critical component of threat mitigation, requires risk prediction based on fungal lifestyles and traits. Recent studies have revealed distinct genomic patterns associated with specific groups of plant pathogenic fungi. We sought to establish whether these phytopathogenic genomic patterns hold across diverse taxonomic and ecological groups from the Ascomycota and Basidiomycota, and furthermore, if those patterns can be used in a predictive capacity for biosurveillance. Using a supervised machine learning approach that integrates phylogenetic and genomic data, we analyzed 387 fungal genomes to test a proof-of-concept for the use of genomic signatures in predicting fungal phytopathogenic lifestyles and traits during biosurveillance activities. Our machine learning feature sets were derived from genome annotation data of carbohydrate-active enzymes (CAZymes), peptidases, secondary metabolite clusters (SMCs), transporters, and transcription factors. We found that machine learning could successfully predict fungal lifestyles and traits across taxonomic groups, with the best predictive performance coming from feature sets comprising CAZyme, peptidase, and SMC data. While phylogeny was an important component in most predictions, the inclusion of genomic data improved prediction performance for every lifestyle and trait tested. Plant pathogenicity was one of the best-predicted traits, showing the promise of predictive genomics for biosurveillance applications. Furthermore, our machine learning approach revealed expansions in the number of genes from specific CAZyme and peptidase families in the genomes of plant pathogens compared to non-phytopathogenic genomes (saprotrophs, endo- and ectomycorrhizal fungi). Such genomic feature profiles give insight into the evolution of fungal phytopathogenicity and could be useful to predict the risks of unknown fungi in future biosurveillance activities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2012

Three-dimensional fabrication and characterisation of core-shell nano-columns using electron beam patterning of Ge-doped SiO{sub 2}

A focused electron beam in a scanning transmission electron microscope (STEM) is used to create arrays of core-shell structures in a specimen of amorphous SiO{sub 2} doped with Ge. The same electron microscope is then used to measure the changes that occurred in the specimen in three dimensions using electron tomography. The results show that transformations in insulators that have been subjected to intense irradiation using charged particles can be studied directly in three dimensions. The fabricated structures include core-shell nano-columns, sputtered regions, voids, and clusters.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Tau-REx I: A next generation retrieval code for exoplanetary atmospheres

Spectroscopy of exoplanetary atmospheres has become a well established method for the characterization of extrasolar planets. We here present a novel inverse retrieval code for exoplanetary atmospheres. T-REx(Tau Retrieval for Exoplanets) is a line-by-line radiative transfer fully Bayesian retrieval framework. T-REx includes the following features:(1) the optimized use of molecular line lists from the ExoMol project; (2) an unbiased atmospheric composition prior selection, through custom built pattern recognition software; (3) the use of two independent algorithms to fully sample the Bayesian likelihood space: nested sampling as well as a more classical Markov Chain Monte Carlo approach; (4) iterative Bayesian parameter and model selection using the full Bayesian Evidence as well as the Savage–Dickey Ratio for nested models; and (5) the ability to fully map very large parameter spaces through optimal code parallelization and scalability to cluster computing. In this publication we outline the T-REx framework and demonstrate, using a theoretical hot-Jupiter transmission spectrum, the parameter retrieval and model selection. We investigate the impact of signal-to-noise ratio and spectral resolution on the retrievability of individual model parameters, both in terms of error bars on the temperature and molecular mixing ratios as well as its effect on the model’s global Bayesian evidence.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Thrombopoietin signaling to chromatin elicits rapid and pervasive epigenome remodeling within poised chromatin architectures

Thrombopoietin (TPO) is a critical cytokine regulating hematopoietic stem cell maintenance and differentiation into the megakaryocytic lineage. However, the transcriptional and chromatin dynamics elicited by TPO signaling are poorly understood. Here, we study the immediate early transcriptional and cis-regulatory responses to TPO in hematopoietic stem/progenitor cells (HSPCs) and use this paradigm of cytokine signaling to chromatin to dissect the relationship between cis-regulatory activity and chromatin architecture. We show that TPO profoundly alters the transcriptome of HSPCs, with key hematopoietic regulators being transcriptionally repressed within 30 min of TPO. By examining cis-regulatory dynamics and chromatin architectures, we demonstrate that these changes are accompanied by rapid and extensive epigenome remodeling of cis-regulatory landscapes that is spatially coordinated within topologically associating domains (TADs). Moreover, TPO-responsive enhancers are spatially clustered and engage in preferential homotypic intra- and inter-TAD interactions that are largely refractory to TPO signaling. By further examining the link between cis-regulatory dynamics and chromatin looping, we show that rapid modulation of cis-regulatory activity is largely independent of chromatin looping dynamics. Finally, we show that, although activated and repressed cis-regulatory elements share remarkably similar DNA sequence compositions, transcription factor binding patterns accurately predict rapid cis-regulatory responses to TPO.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Search for Soft Unclustered Energy Patterns in Proton-Proton Collisions at 13 TeV

The first search for soft unclustered energy patterns (SUEPs) is performed using an integrated luminosity of 138 fb −1 of proton-proton collision data at $\sqrt{𝑠}$ = 13 TeV, collected in 2016–2018 by the CMS detector at the LHC. Such SUEPs are predicted by hidden valley models with a new, confining force with a large ’t Hooft coupling. In events with boosted topologies, selected by high-threshold hadronic triggers, the multiplicity and sphericity of clustered tracks are used to reject the background from standard model quantum chromodynamics. With no observed excess of events over the standard model expectation, limits are set on the cross section for production via gluon fusion of a scalar mediator with SUEP-like decays.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Insights of Molecular Mechanism of Xylem Development in Five Black Poplar Cultivars

Black poplar (Populus deltoides, P. nigra, and their hybrids) is the main poplar cultivars in China. It offers interesting options of large-scale biomass production for bioenergy due to its rapid growth and high yield. Poplar wood properties were associated with chemical components and physical structures during wood formation. In this study, five poplar cultivars, P. euramericana ‘Zhonglin46’ (Pe1), P. euramericana ‘Guariento’ (Pe2), P. nigra ‘N179’ (Pn1), P. deltoides ‘Danhong’ (Pd1), and P. deltoides ‘Nanyang’ (Pd2), were used to explore the molecular mechanism of xylem development. We analyzed the structural differences of developing xylem in the five cultivars and profiled the transcriptome-wide gene expression patterns through RNA sequencing. The cross sections of the developing xylem showed that the cell wall thickness of developed fiber in Pd1 was thickest and the number of xylem vessels of Pn1 was the least. A total of 10,331 differentially expressed genes were identified among 10 pairwise comparisons of the five cultivars, most of them were related to programmed cell death and secondary cell wall thickening. K-means cluster analysis and Gene Ontology enrichment analysis showed that the genes highly expressed in Pd1 were related to nucleotide decomposition, metabolic process, transferase, and microtubule cytoskeleton; whereas the genes highly expressed in Pn1 were involved in cell wall macromolecule decomposition and polysaccharide binding processes. Based on a weighted gene co-expression network analysis, a large number of candidate regulators for xylem development were identified. And their potential regulatory roles to cell wall biosynthesis genes were validated by a transient overexpression system. This study provides a set of promising candidate regulators for genetic engineering to improve feedstock and enhance biofuel conversion in the bioenergy crop Populus.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1995

Flight Schedule and the Circadian Clock Influence on Sleep Loss During Overnight Cargo Operations

Thirty-four flight crew members were monitored before, during, and after two 8-day overnight cargo duty patterns which involved multiple flights at night crossing no more than one time zone per 24 h. Rectal temperature, heart rate, and wrist activity were recorded every 2 min. Sleep quantity and quality, and nap timing, were noted in a logbook. To reduce the masking effects of physical activity on temperature, 0.28 C was added to each subject's raw temperature data whenever he reported being asleep. For both masked and unmasked data, daily temperature minima were estimated from the multiple complex demodulated waveform. The temperature minima did not show a progressive adaptation to night duty, which was interrupted by a night off after 5 nights on one trip pattern and after 3 nights on the other. On duty days, the average temperature minimum delayed by about 3 h, occurring near the end of the duty period. Daytime sleep episodes averaged 2.9 h shorter than nighttime sleep episodes, and were rated as lighter, less restorative, and poorer overall. Fifty-three percent of subjects slept more than once per 24 h while they were on night duty, compared to 17% when able to sleep at night. The total sleep per 24 h on duty days averaged 1.2 h less than pretrip. Twenty-nine percent of subjects lost more than 2 h of sleep per 24 h across the 8-day duty patterns. After night duty, subjects awoke around 1400 local time, even when they had slept 2-3 h less than a normal nocturnal sleep episode. Consequently, the duration of morning sleep episodes was correlated with the off-duty time (multiple r(sup 2)=0.44, F=37.23, p less than 0.0001). Anecdotally, crew members complained of being unable to sleep longer and not feeling well-rested. These wakeups were clustered 6 h after the temperature minimum, which suggests that they may have been a response to the circadian wakeup signal. Daytime layovers in which crew members were able to sleep again in the evening ended later (0200-0300) and were longer (average 19.2 h versus 14.8 h) than those in which they slept only once in the morning. Overnight cargo crew members are working around the time of the circadian nadir with an accumulating sleep debt. Two scheduling factors affect sleep loss during these operations: how long before the circadian wakeup signal crew members come off duty, and whether the layover lasts long enough to permit a second sleep episode in the early evening.

Gander, Philippa H.↗
NASA NTRS2014

Large Meteoroid Impact on the Moon on 17 March 2013

Since early 2006, NASA's Marshall Space Flight Center has observed over 300 impact flashes on the Moon, produced by meteoroids striking the lunar surface. On 17 March 2013 at 03:50:54.312 UTC, the brightest flash of an 8-year routine observing campaign was observed in two 0.35 m telescopes outfitted with Watec 902H2 Ultimate monochrome CCD cameras recording interleaved 30 fps video. Standard CCD photometric techniques, described in [1], were applied to the video after saturation correction, yielding a peak R magnitude of 3.0 +/- 0.4 in a 1/30 second video exposure. This corresponds to a luminous energy of 7.1 × 10(exp 6) J. Geographic Information System (GIS) tools were used to georeference the lunar impact imagery and yielded a crater location at 20.60 +/- 0.17deg N, 23.92 +/- 0.30deg W. The camera onboard the Lunar Reconnaissance Orbiter (LRO), a NASA spacecraft mapping the Moon from lunar orbit, discovered the fresh crater associated with this impact by comparing post-impact images from 28 July 2013 to pre-impact images on 12 Feb 2012. The images show fresh, bright ejecta around an 18 m diameter circular crater, with a 15 m inner diameter measured from the level of pre-existing terrain, at 20.7135deg N, 24.3302deg W. An asymmetrical ray pattern with both high and low reflectance ejecta zones extends 1-2 km beyond the crater, and a series of mostly low reflectance splotches can be seen within 30 km of the crater - likely due to secondary impacts [2]. The meteoroid impactor responsible for this event may have been part of a stream of large particles encountered by the Earth/Moon associated with the Virginid Meteor Complex, as evidenced by a cluster of 5 fireballs seen in Earth's atmosphere on the same night by the NASA All Sky Fireball Network [3] and the Southern Ontario Meteor Network [4]. Assuming a velocity-dependent luminous efficiency (ratio of luminous energy to kinetic energy) from [5] and an impact velocity of 25.6 km/s derived from fireball measurements, the impactor kinetic energy was 5.4 × 10(exp 9) J and the impactor mass was 16 kg. Assuming an impact angle of 56deg from horizontal (based on fireball orbit measurements), a regolith density of 1500 kg/m(exp 3), and impactor density between 1800 and 3000 kg/m(exp 3), the impact crater diameter was estimated to be 8-18 m at the pre-impact surface and 10-23 m rim-to-rim using the Holsapple [6] and Gault [7] models, a result consistent with the observed crater.

Moser, Danielle E.↗
NASA NTRS2003

The expression and function of the achaete-scute genes in Tribolium castaneum reveals conservation and variation in neural pattern formation and cell fate specification

The study of achaete-scute (ac/sc) genes has recently become a paradigm to understand the evolution and development of the arthropod nervous system. We describe the identification and characterization of the ac/sc genes in the coleopteran insect species Tribolium castaneum. We have identified two Tribolium ac/sc genes - achaete-scute homolog (Tc-ASH) a proneural gene and asense (Tc-ase) a neural precursor gene that reside in a gene complex. Focusing on the embryonic central nervous system we find that Tc-ASH is expressed in all neural precursors and the proneural clusters from which they segregate. Through RNAi and misexpression studies we show that Tc-ASH is necessary for neural precursor formation in Tribolium and sufficient for neural precursor formation in Drosophila. Comparison of the function of the Drosophila and Tribolium proneural ac/sc genes suggests that in the Drosophila lineage these genes have maintained their ancestral function in neural precursor formation and have acquired a new role in the fate specification of individual neural precursors. Furthermore, we find that Tc-ase is expressed in all neural precursors suggesting an important and conserved role for asense genes in insect nervous system development. Our analysis of the Tribolium ac/sc genes indicates significant plasticity in gene number, expression and function, and implicates these modifications in the evolution of arthropod neural development.

Non-NASA Center↗
DOE OSTI2013

Spatial-Temporal [{sup 18}F]FDG-PET Features for Predicting Pathologic Response of Esophageal Cancer to Neoadjuvant Chemoradiation Therapy

Purpose: To extract and study comprehensive spatial-temporal {sup 18}F-labeled fluorodeoxyglucose ([{sup 18}F]FDG) positron emission tomography (PET) features for the prediction of pathologic tumor response to neoadjuvant chemoradiation therapy (CRT) in esophageal cancer. Methods and Materials: Twenty patients with esophageal cancer were treated with trimodal therapy (CRT plus surgery) and underwent [{sup 18}F]FDG-PET/CT scans both before (pre-CRT) and after (post-CRT) CRT. The 2 scans were rigidly registered. A tumor volume was semiautomatically delineated using a threshold standardized uptake value (SUV) of ≥2.5, followed by manual editing. Comprehensive features were extracted to characterize SUV intensity distribution, spatial patterns (texture), tumor geometry, and associated changes resulting from CRT. The usefulness of each feature in predicting pathologic tumor response to CRT was evaluated using the area under the receiver operating characteristic curve (AUC) value. Results: The best traditional response measure was decline in maximum SUV (SUV{sub max}; AUC, 0.76). Two new intensity features, decline in mean SUV (SUV{sub mean}) and skewness, and 3 texture features (inertia, correlation, and cluster prominence) were found to be significant predictors with AUC values ≥0.76. According to these features, a tumor was more likely to be a responder when the SUV{sub mean} decline was larger, when there were relatively fewer voxels with higher SUV values pre-CRT, or when [{sup 18}F]FDG uptake post-CRT was relatively homogeneous. All of the most accurate predictive features were extracted from the entire tumor rather than from the most active part of the tumor. For SUV intensity features and tumor size features, changes were more predictive than pre- or post-CRT assessment alone. Conclusion: Spatial-temporal [{sup 18}F]FDG-PET features were found to be useful predictors of pathologic tumor response to neoadjuvant CRT in esophageal cancer.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Spin Reorientation in Antiferromagnetic Layered FePt 5 P

FePt 5 P, a substitutional variant of the anti-CeCoIn 5 structure type in the space group P4/mmm, was synthesized by a high-temperature solid-state method and structurally characterized by X-ray diffraction. FePt 5 P contains layers of FePt 12 clusters formed by magnetically active Fe and heavy Pt with strong spin-orbit coupling (SOC); the layers are separated by P atoms. The various Fe–Pt distances in FePt 12 clusters generate complex magnetic orders in FePt 5 P. According to temperature-dependent magnetic and specific heat measurements, FePt 5 P shows a stripe-type antiferromagnetic order at T N ≈ 90 K, which is also confirmed by resistivity measurements. Furthermore, a spin reorientation occurs at ~74 and ~68 K in and out of the ab plane based on the specific heat measurements. The temperature-dependent neutron powder diffraction patterns demonstrate the antiferromagnetic order in FePt 5 P, and the spins orientate up to 58.4° with respect to the c axis at 10 K. First-principles calculations of FePt 5 P show the band splitting at the Fermi level by strong SOC and the s–d hybridization between P and Fe/Pt electrons enhances the structural stability and affects the magnetic ordering.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Influence of the Ag concentration on the medium-range order in a CuZrAlAg bulk metallic glass

Fluctuation electron microscopy of bulk metallic glasses of CuZrAl(Ag) demonstrates that medium-range order is sensitive to minor compositional changes. Furthermore, by analyzing nanodiffraction patterns medium-range order is detected with crystal-like motifs based on the B2 CuZr structure and its distorted structures resembling the martensitic ones. This result thus demonstrates some structural homology between the metallic glass and its high temperature crystalline phase. The amount of medium-range order seems slightly affected with increasing Ag concentration (0, 2, 5 at.%) but the structural motifs of the medium-range ordered clusters become more diverse at the highest Ag concentration. The decrease of dominant clusters is consistent with the destabilization of the B2 structure measured by calorimetry and accounts for the increased glass-forming ability.

36 MATERIALS SCIENCE↗
DOE OSTI2019

In‐depth comparative analysis of Illumina ® MiSeq run metrics: Development of a wet‐lab quality assessment tool

Abstract Whole genome sequencing of bacterial isolates has become a daily task in many laboratories, generating incredible amounts of data. However, data acquisition is not an end in itself; the goal is to acquire high‐quality data useful for understanding genetic relationships. Having a method that could rapidly determine which of the many available run metrics are the most important indicators of overall run quality and having a way to monitor these during a given sequencing run would be extremely helpful to this effect. Therefore, we compared various run metrics across 486 MiSeq runs, from five different machines. By performing a statistical analysis using principal components analysis and a K ‐means clustering algorithm of the metrics, we were able to validate metric comparisons among instruments, allowing for the development of a predictive algorithm, which permits one to observe whether a given MiSeq run has performed adequately. This algorithm is available in an Excel spreadsheet: that is, MiSeq Instrument & Run (In‐Run) Forecast. Our tool can help verify that the quantity/quality of the generated sequencing data consistently meets or exceeds recommended manufacturer expectations. Patterns of deviation from those expectations can be used to assess potential run problems and plan preventative maintenance, which can save valuable time and funding resources.

Kastanis, George John↗