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At least 163 records · Page 9

All sources NASA NTRS DOE OSTI

DOE OSTI2016

Application of air classification and formulation to manage feedstock cost, quality and availability for bioenergy

Biomass such as agricultural residues, energy crops and yard waste has significant potential to be used as renewable feedstocks for production of fuels, chemicals and energy. However, in a given location, biomass availability, cost and quality can vary markedly. Strategies to manage these traits must be identified and implemented so that consistent low-cost and high-quality feedstocks can be delivered to biorefineries year round. In this study, we examine air classification as a method to mitigate high ash concentrations in corn stover, switchgrass, and grass clippings. Formulation techniques were then used to produce blends that met ash quality and biomass quantity specifications at the lowest possible cost for biopower and biochemical conversion applications. It was found that air classification can separate the biomass into light fractions which contain concentrated amounts of elemental ash components introduced through soil contamination such as sodium, alumina, silica, iron and titania; and heavy fractions that are depleted in these components and have relatively lower total ash content. Light fractions of corn stover and grass clippings were found to be suitable for combustion applications since they had less propensity to slag than the whole biomass material. The remaining heavy fractions of corn stover or grass clippings could then be blended with switchgrass to produce blends that met the 5% total ash specifications suggested for biochemical conversions. However, ternary blends of the three feedstocks were not possible due to the high ash content of grass clippings. Lastly, it was determined that air classification by itself was not suitable to prepare these feedstocks for pyrolysis due to high ash content.

09 BIOMASS FUELS↗

DOE OSTI2017

An informatics guided classification of miscible and immiscible binary alloy systems

The classification of miscible and immiscible systems of binary alloys plays a critical role in the design of multicomponent alloys. By mining data from hundreds of experimental phase diagrams, and thousands of thermodynamic data sets from experiments and high-throughput first-principles (HTFP) calculations, we have obtained a comprehensive classification of alloying behavior for 813 binary alloy systems consisting of transition and lanthanide metals. Among several physics-based descriptors, the slightly modified Pettifor chemical scale provides a unique two-dimensional map that divides the miscible and immiscible systems into distinctly clustered regions. Based on an artificial neural network algorithm and elemental similarity, the miscibility of the unknown systems is further predicted and a complete miscibility map is thus obtained. Impressively, the classification by the miscibility map yields a robust validation on the capability of the well-known Miedema’s theory (95% agreement) and shows good agreement with the HTFP method (90% agreement). Our results demonstrate that a state-of-the-art physics-guided data mining can provide an efficient pathway for knowledge discovery in the next generation of materials design.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Organic Chemical Attribution Signatures for the Sourcing of a Mustard Agent and Its Starting Materials

Chemical attribution signatures (CAS) are being investigated for the sourcing of chemical warfare (CW) agents and their starting materials that may be implicated in chemical attacks or CW proliferation. The work reported here demonstrates for the first time trace impurities produced during the synthesis of tris(2-chloroethyl)amine (HN3) that point to specific reagent stocks used in the synthesis of this CW agent. Thirty batches of HN3 were synthesized using different combinations of commercial stocks of triethanolamine (TEA), thionyl chloride, chloroform, and acetone. The HN3 batches and reagent stocks were then analyzed for impurities by gas chromatography/mass spectrometry. Reaction-produced impurities indicative of specific TEA and chloroform stocks were exclusively discovered in HN3 batches made with those reagent stocks. In addition, some reagent impurities were found in the HN3 batches that were presumably not altered during synthesis and believed to be indicative of reagent type regardless of stock. Supervised classification using partial least squares discriminant analysis (PLSDA) on the impurity profiles of chloroform samples from seven stocks resulted in an average classification error by cross-validation of 2.4%. A classification error of zero was obtained using the seven-stock PLSDA model on a validation set of samples from an arbitrarily selected chloroform stock. In a separate analysis, all samples from two of seven chloroform stocks that were purposely not modeled had their samples matched to a chloroform stock rather than assigned a “no class” classification.

chemical forensics↗

DOE OSTI2023

Chemical and genetic characterization of the ungrouped pallasite Lieksa

The meteorite Lieksa was found in 2017 in Löpönvaara, Finland, and later donated to the Finnish Museum of Natural History. Here, we report siderophile element concentrations, genetic isotopic data, and a metal–silicate segregation age for the meteorite. The ~280 g Lieksa is ~80% metal and ~20% silicate and oxide inclusions by volume, with the inclusions consisting primarily of Fe-rich olivine. Due to Lieksa's silicate content, coupled with a texture characterized by metal enclosing the silicates, it has been classified as a pallasite. Lieksa's olivine and bulk chemical characteristics are distinct from those of the known pallasite and iron meteorite groups, consistent with its classification as ungrouped. The meteorite exhibits a flat, chondrite-normalized highly siderophile element pattern, consistent with an origin as an early crystallization product from a metallic melt with chondritic relative abundances. Molybdenum, Ru, and 183 W isotopic data indicate that Lieksa formed in the non-carbonaceous (NC) domain of the solar nebula. Radiogenic 182 W abundances for Lieksa yield a model metal–silicate segregation age of 1.5 ± 0.8 Myr after calcium-aluminum-rich inclusion formation, which is within the range established for other NC-type pallasite and iron meteorite parent bodies.

58 GEOSCIENCES↗

DOE OSTI2015

Toxic Endpoint Analysis

The purpose of this analysis is to compare the toxic endpoints (e.g., ERPG-2, ERPG-3, AEGL-2 AEGL-3, PAC-2, and PAC-3) at both the 15-minute and the 60-minute release periods against the existing Industrial Facilities Safety Basis (IFSB) Guidance Protocol for classifying facilities at Sandia National Laboratories (SNL). In this analysis, specific toxic chemicals are modeled with exposure limits at 100 meters (m) to understand the impacts on facility hazard classification.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2016

Toxic Endpoint Analysis PowerPoint Presentation [Slides]

This presentation, developed in Microsoft PowerPoint©, communicates the results of a Toxic Endpoint Analysis undertaken by the Safety Basis Department (01426) at Sandia National Laboratories/New Mexico. The purpose of the analysis is to compare the toxic endpoints (e.g., ERPG-2, ERPG-3, AEGL-2 AEGL-3, PAC-2, and PAC-3) at both the 15-minute and the 60-minute release periods against the existing Industrial Facilities Safety Basis (IFSB) Guidance Protocol for classifying facilities at Sandia National Laboratories (SNL). In this analysis, specific toxic chemicals are modeled with exposure limits at 100 meters (m) to understand the impacts on facility hazard classification.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS1967

Tektite Sculpturing

Tektite classification by type based on external form, attributing surface sculpturing of type B to aerodynamic and not chemical processes

AERODYNAMIC HEATING↗

NASA NTRS2005

Correlation of Rock Spectra with Quantitative Morphologic Indices: Evidence for a Single Rock Type at the Mars Pathfinder Landing Site

The Mars Pathfinder (MPF) landing site was predicted to contain a broad sampling of rock types varying in mineralogical, physical, mechanical and geochemical characteristics. Although rocks have been divided into several spectral categories based on Imager for Mars Pathfinder (IMP) visible/near-infrared data, efforts in isolating and classifying spectral units among MPF rocks and soils have met with varying degrees of success, as many factors influencing spectral signatures cannot be quantified to a sufficient level to be removed. It has not been fully determined which spectral categories stem from intrinsic mineralogical differences between rocks or rock surfaces, and which result from factors such as physical or chemical weathering. This has made isolation of unique rock mineralogies difficult. Morphology, like composition, is a characteristic tied to the intrinsic properties and geologic and weathering history of rocks. Rock morphologies can be assessed quantitatively and compared with spectral data, to identify and classify rock types at the MPF landing site. They can also isolate actual rock spectra from spectral types that are surficial in origin, as compositions associated with mantling dust or chemical coatings would presumably not influence rock morphology during weathering events. We previously reported on an initial classification of rocks using the quantitative morphologic indices of size, roundness, sphericity and elongation. Here, we compare this database of rock characteristics with associated rock surface spectra to improve our ability to discriminate between spectra associated with rock types and those from other sources.

Yingst, R. A.↗

NASA NTRS1993

Roosevelt County 075: A petrologic chemical and isotopic study of the most unequilibrated known H chondrite

Roosevelt County (RC) 075 was recovered in 1990 as a single 258-gram stone. Classification of this meteorite is complicated by its highly unequilibrated nature and its severe terrestrial weathering, but we favor H classification. This is supported by O isotopes and estimates of the original Fe, Ni metal content. The O isotopic composition is similar to that of a number of reduced ordinary chondrites (e.g., Cerro los Calvos, Willaroy), although RC 075 exhibits no evidence of reduced mineral compositions. Chondrule diameters are consistent with classification as an L chondrite, but large uncertainties in chondrule diameters of RC 075 and poorly constrained means of H, L and LL chondrites prevent use of this parameter for reliable classification. Other parameters are compromised by severe weathering (e.g., siderophile element abundances) or unsuitable for discrimination between unequilibrated H, L and LL chondrites (e.g., Co in kamacite delta C-13). Petrologic subtype 3.2 +/- 0.1 is suggested by the degree of olivine heterogeneity, the compositions of chondrule olivines, the thermoluminescence sensitivity, the abundances and types of chondrules mapped on cathodoluminescence mosaics, and the amount of presolar SiC. The meteorite is very weakly shocked (S2), with some chondrules essentially unshocked and, thus, is classified as an H3.2(S2) chondrite. Weathering is evident by a LREE enrichment due to clay contamination, reduced levels of many siderophile elements, the almost total loss of Fe, Ni metal and troilite, and the reduced concentrations of noble gases. Some components of the meteorite (e.g., type IA chondrules, SiC) appear to preserve their nebular states, with little modification from thermal metamorphism. We conclude that RC 075 is the most equilibrated H chondrite yet recovered and may provide additional insights into the origin of primitive materials in the solar nebula.

Mccoy, T. J.↗

NASA NTRS1976

The Apollo 16 drill core - Modal petrology and characterization of the mineral and lithic component

A string of 59 polished thin sections covering the length of the Apollo 16 deep drill core has been examined. A modal analysis, involving the optical classification of 116,000 points was made, and over 500 mineral and lithic fragments from the core were chemically analyzed using an electron microprobe. These data were used to identify and characterize the source areas of the core material and to reconstruct the accumulation history of the core.

Vaniman, D. T.↗

NASA NTRS1972

Differentiating elements of the soil-vegetation complex

The application of remote sensing to study soil-vegetation systems requires quantification and precise location of ground observation data such that they can be correlated with multispectral aerial acquired data. Griddling and sampling of an area for exact identification in a known address on magnetic tape containing multispectral scanner data produces quantitative physico-chemical parameters and the energy which is radiating from within the soil-vegetation complex of an area. Example classifications and spectral mappings of soils made from multispectral scanner data are included.

Baumgardner, M. F.↗

DOE OSTI2025

Emergence of deep eutectic solvents (DES): chemistry, preparation, properties, and applications in biorefineries and critical materials

The emergence of renewable deep eutectic solvents (DES) as clean and efficient catalysts and solvents has created new opportunities for lignocellulosic biorefineries and critical material sectors, including chemical, energy, pharmaceutical, textile, and hydrometallurgical industries. This review provides an in-depth overview of DES, covering their chemistry, classifications, preparation methods, processing characteristics, and recyclability, while highlighting their unique attributes and industry relevant applications. Emphasis is placed on the integration of DES into advanced biorefinery systems, focusing on their tunable physicochemical and thermodynamic properties for biomass pretreatment and the production of value-added products. The review explores how DES can be tuned for selective dissolution of biomass components and evaluates production and valorization of DES-derived biochemicals, with attention to lignin extraction mechanisms and conversion of biomass into bioproducts and biofuels. Beyond biorefineries, the scope extends to DES applications in electrochemical energy devices, where they serve as electrolytes, synthesis media for electrode materials, and leaching agents in battery recycling. The multifunctional roles of DES in pharmaceutical, hydrometallurgical, and textile sectors are also explored for contributions to sustainable processing. Finally, the review identifies future research directions, outlining benefits, challenges, and knowledge gaps, for continued industrial development.

09 BIOMASS FUELS↗

DOE OSTI2023

Snekmer: a scalable pipeline for protein sequence fingerprinting based on amino acid recoding

Abstract Motivation The vast expansion of sequence data generated from single organisms and microbiomes has precipitated the need for faster and more sensitive methods to assess evolutionary and functional relationships between proteins. Representing proteins as sets of short peptide sequences (kmers) has been used for rapid, accurate classification of proteins into functional categories; however, this approach employs an exact-match methodology and thus may be limited in terms of sensitivity and coverage. We have previously used similarity groupings, based on the chemical properties of amino acids, to form reduced character sets and recode proteins. This amino acid recoding (AAR) approach simplifies the construction of protein representations in the form of kmer vectors, which can link sequences with distant sequence similarity and provide accurate classification of problematic protein families. Results Here, we describe Snekmer, a software tool for recoding proteins into AAR kmer vectors and performing either (i) construction of supervised classification models trained on input protein families or (ii) clustering for de novo determination of protein families. We provide examples of the operation of the tool against a set of nitrogen cycling families originally collected using both standard hidden Markov models and a larger set of proteins from Uniprot and demonstrate that our method accurately differentiates these sequences in both operation modes. Availability and implementation Snekmer is written in Python using Snakemake. Code and data used in this article, along with tutorial notebooks, are available at http://github.com/PNNL-CompBio/Snekmer under an open-source BSD-3 license. Supplementary information Supplementary data are available at Bioinformatics Advances online.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2013

High-Resolution Infrared Spectroscopic Measurements of Comet 2PlEncke: Unusual Organic Composition and Low Rotational Temperatures

We present high-resolution infrared spectroscopic measurements of the ecliptic comet 2P/Encke, observed on 4-6 Nov. 2003 during its close approach to the Earth, using the Near Infrared Echelle Spectrograph on the Keck II telescope. We present flux-calibrated spectra, production rates, and mixing ratios for H2O, CH3OH, HCN, H2CO, C2H2, C2H6, CH4 and CO. Comet 2P/Encke is a dynamical end-member among comets because of its short period of 3.3 years. Relative to "organics-normal" comets, we determined that 2PlEncke is depleted in HCN, H2CO, C2H2, C2H6, CH4 and CO, but it is enriched in CH3OH. We compared mixing ratios of these organic species measured on separate dates, and we see no evidence of macroscopic chemical heterogeneity in the nucleus of 2P/Encke, however, this conclusion is limited by sparse temporal sampling. The depleted abundances of most measured species suggest that 2P/Encke may have formed closer to the young Sun, before its insertion to the Kuiper belt, compared with "organics-normal" comets - as was previously suggested for other depleted comets (e.g. C/1999 S4 (LINEAR)). We measured very low rotational temperatures of 20 - 30 K for H2O, CH3OH and HCN in the near nucleus region of 2P/Encke, which correlate with one of the lowest cometary gas production rates (approx. 2.6 x 10(exp 27) molecules/s) measured thus far in the infrared. This suggests that we are seeing the effects of more efficient radiative cooling, insufficient collisional excitation, and/or inefficient heating by fast H-atoms (and icy grains) in the observed region of the coma. Its extremely short orbital period, very low gas production rate, and classification as an ecliptic comet, make 2PlEncke an important addition to our growing database, and contribute significantly to the establishment of a chemical taxonomy of comets.

Radeva, Yana L.↗

DOE OSTI2013

Relating Aerosol Absorption due to Soot, Organic Carbon, and Dust to Emission Sources Determined from In-situ Chemical Measurements

Estimating the aerosol contribution to the global or regional radiative forcing can take advantage of the relationship between the spectral aerosol optical properties and the size and chemical composition of aerosol. Long term global optical measurements from observational networks or satellites can be used in such studies, and using in-situ chemical mixing state measurements can help us to constrain the limitations of such an estimation. In this study, the Absorption Ångström Exponent (AAE) and the Scattering Ångström Exponent (SAE) are used to develop a new methodology for deducing chemical speciation based on wavelength dependence of the optical properties. In addition, in-situ optical properties and single particle chemical composition measured during three aircraft field campaigns are combined in order to validate the methodology for the estimation of aerosol composition using spectral optical properties. Results indicate a dominance of mixed types in the classification leading to an underestimation of the primary sources, however secondary sources are better classified. The distinction between carbonaceous aerosols from fossil fuel and biomass burning origins is not clear. On the other hand, the knowledge of the aerosol sources in California from chemical studies help to identify other misclassification such as the dust contribution.

absorption↗

DOE OSTI2017

CHEMICAL ANALYSIS OF A CARBON-ENHANCED VERY METAL-POOR STAR: CD-27 14351

We present, for the first time, an abundance analysis of a very metal-poor carbon-enhanced star CD-27 14351 based on a high-resolution ( R ∼ 48,000) FEROS spectrum. Our abundance analysis performed using local thermodynamic equilibrium model atmospheres shows that the object is a cool star with stellar atmospheric parameters, effective temperature T {sub eff} = 4335 K, surface gravity log g = 0.5, microturbulence ξ = 2.42 km s{sup −1}, and metallicity [Fe/H] = −2.6. The star exhibits high carbon and nitrogen abundances with [C/Fe] = 2.89 and [N/Fe] = 1.89. Overabundances of neutron-capture elements are evident in Ba, La, Ce, and Nd, with estimated [X/Fe] > 1, the largest enhancement being seen in Ce with [Ce/Fe] = 2.63. While the first peak s -process elements Sr and Y are found to be enhanced with respect to Fe, ([Sr/Fe] = 1.73 and [Y/Fe] = 1.91), the third peak s -process element Pb could not be detected in our spectrum at the given resolution. Europium, primarily an r -process element also shows an enhancement with [Eu/Fe] = 1.65. With [Ba/Eu] = 0.12, the object CD-27 14351 satisfies the classification criterion for a CEMP-r/s star. The elemental abundance distributions observed in this star are discussed in light of the chemical abundances observed in other CEMP stars in the literature.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Identification of Common Types of Plastics by Vibrational Spectroscopic Techniques

Polyethylene Terephthalate (PET), High-Density Polyethylene (HDPE), Polyvinyl Chloride (PVC), Low-Density Polyethylene (LDPE), Polypropylene (PP), and Polystyrene (PS) account for most plastic use worldwide, with production nearing 380 million tons annually. A considerable portion enters municipal solid waste and landfills, creating long-term environmental concerns. Scaling recycling operations requires automated sorting technologies, with spectroscopy and machine learning offering promising solutions. In this study, a six-class convolutional neural network (CNN) was developed for plastic identification using vibrational spectroscopies. Raman Scattering (RS) spectra collected from recycling samples enabled accurate chemical differentiation while assessing the influence of visible features such as color. A CNN trained on RS data achieved 100% classification accuracy. To strengthen field applicability, Attenuated Total Reflectance–Fourier Transform Infrared (ATR-FTIR) spectroscopy was incorporated, achieving 95% accuracy with a similar CNN model. These findings demonstrate the potential of integrating spectroscopy with deep learning for reliable plastic classification, advancing development of scalable, field-ready recycling technologies.

Garcia Tovar, Maria P.↗

DOE OSTI2013

Breast density quantification using magnetic resonance imaging (MRI) with bias field correction: A postmortem study

Purpose: Quantification of breast density based on three-dimensional breast MRI may provide useful information for the early detection of breast cancer. However, the field inhomogeneity can severely challenge the computerized image segmentation process. In this work, the effect of the bias field in breast density quantification has been investigated with a postmortem study. Methods: T1-weighted images of 20 pairs of postmortem breasts were acquired on a 1.5 T breast MRI scanner. Two computer-assisted algorithms were used to quantify the volumetric breast density. First, standard fuzzy c-means (FCM) clustering was used on raw images with the bias field present. Then, the coherent local intensity clustering (CLIC) method estimated and corrected the bias field during the iterative tissue segmentation process. Finally, FCM clustering was performed on the bias-field-corrected images produced by CLIC method. The left–right correlation for breasts in the same pair was studied for both segmentation algorithms to evaluate the precision of the tissue classification. Finally, the breast densities measured with the three methods were compared to the gold standard tissue compositions obtained from chemical analysis. The linear correlation coefficient, Pearson'sr, was used to evaluate the two image segmentation algorithms and the effect of bias field. Results: The CLIC method successfully corrected the intensity inhomogeneity induced by the bias field. In left–right comparisons, the CLIC method significantly improved the slope and the correlation coefficient of the linear fitting for the glandular volume estimation. The left–right breast density correlation was also increased from 0.93 to 0.98. When compared with the percent fibroglandular volume (%FGV) from chemical analysis, results after bias field correction from both the CLIC the FCM algorithms showed improved linear correlation. As a result, the Pearson'sr increased from 0.86 to 0.92 with the bias field correction. Conclusions: The investigated CLIC method significantly increased the precision and accuracy of breast density quantification using breast MRI images by effectively correcting the bias field. It is expected that a fully automated computerized algorithm for breast density quantification may have great potential in clinical MRI applications.

62 RADIOLOGY AND NUCLEAR MEDICINE↗