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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Development of a modulator to measure water vapor selectively in a gaseous mixture

Selective thermal modulation (STM) is a technique which produces a concentration-dependent pulse by selectively modulating a sample in a gas stream. Several types of modulation techniques, both chemical and physical, using adsorption, decomposition, and catalytic and mechanical methods have been developed for use with multiplex gas chromatography. Two of these applications involve selective modulation of the components present in the sample gas stream. The selective modulation of the concentration of specific sample molecules or classes of molecules provides additional analytical selectivity which can lead to selective detection. For some specific applications, the column may even be eliminated. Chemical modulation by absorption of a substance from the sample stream by a stationary phase will also produce a change in the signal intensity. Removal of a substance from the sample stream results in a signal containing a vacancy peak. In the work reported here, a selective thermal modulation technique has been developed as a method for determination of water vapor for possible use in Mars' atmosphere.

NASA Center ARC↗
NASA NTRS2005

XMM-Newton Observations of the DLS Shear-Selected Cluster Survey

The goal of this project continues to be to test the selection effects in cluster surveys by investigating the X-ray properties of the first shear-selected sample of galaxy clusters, the Deep Lens Survey (DLS). Because lensing signal is only sensitive to mass (albeit with projection effects), lensing signal can be used to select a sample that is independent of its X-ray properties. If a lensing-selected sample has very different X-ray properties from an X-ray selected sample, it would have important consequences for evolutionary studies based on existing cluster samples was aimed at refining the lensing-selected sample as part of this continuing study The grant supported a KPNO run to obtain data on another region of the sky to extend the cluster sample, and also the purchase of a disk array for archiving the optical mosaic data (Two terabytes worth) from which the lensing maps are derived As a result of the grant, we have extended the lensing cluster sample to another 4-square degree patch of the sky, adding another three clusters to our sample to be observed While the sample of X-ray observed clusters is too small to derive a firm conclusion yet, our preliminary finding is that the X-ray properties of the observed sample do not differ from those of X-ray selected surveys A paper discussing the first results has been published, and a second paper on the mass differences is still in preparation (with J Hughes as first author)

DellAntonio, Ian↗
NASA NTRS2005

Identifying or measuring selected substances or toxins in a subject using resonant raman signals

Methods and systems of the present invention identify the presence of and/or the concentration of a selected analyte in a subject by: (a) illuminating a selected region of the eye of a subject with an optical excitation beam, wherein the excitation beam wavelength is selected to generate a resonant Raman spectrum of the selected analyte with a signal strength that is at least 100 times greater than Raman spectrums generated by non-resonant wavelengths and/or relative to signals of normal constituents present in the selected region of the eye; (b) detecting a resonant Raman spectrum corresponding to the selected illuminated region of the eye; and (c) identifying the presence, absence and/or the concentration of the selected analyte in the subject based on said detecting step. The apparatus may also be configured to be able to obtain biometric data of the eye to identify (confirm the identity of) the subject.

Lambert, James L.↗
DOE OSTI2021

Process for selectively recovering a phenolic compound from feedstock comprising bio-crude and/or bio-oil

A process for selectively recovering a phenolic compound from feedstock comprising bio-crude and/or bio-oil is described. The recovery efficiency of the selected phenolic compound is greater than 70 wt % and the purity of the recovered selected phenolic compound is higher than 80 wt %. The process comprises distilling the feedstock to isolate the selected phenolic compound in a first distillate fraction comprising the selected phenolic compound, concentrating the selected phenolic compound from the first distillate fraction in a concentrated mixture, and purifying the concentrated mixture to recover the selected phenolic compound.

Mante, Ofei D.↗
DOE OSTI2022

Selective Removal of Barium and Hardness Ions from Brackish Water with Chemically Enhanced Electrodialysis

The use of a nonconventional water resource for energy and industrial applications often requires extraction of low-level undesirable ions from matrices of benign dominant ions. In this study, the selective extraction of Ba 2+ and Mg 2+ from synthetic brine solutions was evaluated using strong acid cation-exchange membranes modified with the surface deposition of macrocyclic molecules including crown ethers and calixarenes. Compared to the bare membrane, vinylbenzo-18-crown-6 (VB18C6) and calix[4]arene-amended membranes showed increased selectivity for Ba 2+ and Mg 2+ with respect to the dominant ion (Na + ) by up to fourfolds, with the calix[4]arene-modified membrane achieving more selective separation than VB18C6. Optimal selectivity was achieved at a moderate-to-high current density (3.1–6.3 mA/cm 2 ), which was attributed to the alleviation of transport limitation in the boundary layer by the surface modification. Amendment of a calix[4]arene derivative with a crown-6 “boot strap” and two carboxylic groups resulted in reduced selectivity due to the formation of strong complexes with divalent ions. Furthermore, these results show that surface deposition of ion sequestrants can be a versatile approach to improve the membrane’s selectivity; however, the performance is sensitive to feed water salinity, current loading, and the macrocycle-ion chemistry, where there is a trade-off between ion affinity and mobility.

36 MATERIALS SCIENCE↗
DOE OSTI2016

A Parameter Subset Selection Algorithm for Mixed-Effects Models

Mixed-effects models are commonly used to statistically model phenomena that include attributes associated with a population or general underlying mechanism as well as effects specific to individuals or components of the general mechanism. This can include individual effects associated with data from multiple experiments. However, the parameterizations used to incorporate the population and individual effects are often unidentifiable in the sense that parameters are not uniquely specified by the data. As a result, the current literature focuses on model selection, by which insensitive parameters are fixed or removed from the model. Model selection methods that employ information criteria are applicable to both linear and nonlinear mixed-effects models, but such techniques are limited in that they are computationally prohibitive for large problems due to the number of possible models that must be tested. To limit the scope of possible models for model selection via information criteria, we introduce a parameter subset selection (PSS) algorithm for mixed-effects models, which orders the parameters by their significance. In conclusion, we provide examples to verify the effectiveness of the PSS algorithm and to test the performance of mixed-effects model selection that makes use of parameter subset selection.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

In Vitro Selection of Antibodies Targeting Yersinia pestis Membrane Lipids Using Nanodisc-Based Antigen Presentation

Proteins are the most common targets for antibody discovery and vaccine development, but their sequence variability can limit the breadth of resulting antigens. Lipids represent an alternative class of antigens due to their structural conservation and roles in host–pathogen interactions. Here, we describe the development and optimization of an in vitro antibody selection workflow using lipid-containing nanodiscs as antigen presentation platforms to enable phage and yeast display selections under conditions adapted for these non-protein targets. Lipopolysaccharide (LPS) nanodiscs were first used as a model system to evaluate selection strategies, including competitive and subtractive approaches to reduce non-specific binders, yielding peptide and single-chain variable fragment (scFv) binders that were affinity matured to improve binding signals. The same approach was subsequently used to select scFv antibodies that recognize lipid nanodiscs prepared from Yersinia pestis membrane lipid extracts. These antibodies show binding to lipid nanodiscs derived from Y. pestis, with evidence of selectivity relative to control nanodiscs. Overall, this work establishes a workflow for antibody selection against lipid-containing nanodisc antigens and highlights practical considerations associated with these targets. The approach may be useful for generating affinity reagents to membrane-associated lipids, although further characterization is required to define antigen specificity and functional activity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Ultraselective Carbon Molecular Sieve Membranes with Tailored Synergistic Sorption Selective Properties

Membrane-based separations can reduce the energy consumption and the CO 2 footprint of large-scale fluid separations, which are traditionally practiced by energy-intensive thermally driven processes. Here, a new type of membrane structure based on nanoporous carbon is reported, which, according to this study, is best referred to as carbon/carbon mixed-matrix (CCMM) membranes. The CCMM membranes are formed by high-temperature (up to 900 °C) pyrolysis of polyimide precursor hollow-fiber membranes. Unprecedentedly high permselectivities are seen in CCMM membranes for CO 2 /CH 4 , N 2 /CH 4 , He/CH 4 , and H 2 /CH 4 separations. Analysis of permeation data suggests that the ultrahigh selectivities result from substantially increased sorption selectivities, which is hypothetically owing to the formation of ultraselective micropores that selectively exclude the bulkier CH 4 molecules. With tunable sorption selectivities, the CCMM membranes outperform flexible polymer membranes and traditional rigid molecular-sieve membranes. The capability to increase sorption selectivities is a powerful tool to leverage diffusion selectivities, and has opened the door to many challenging and economically important fluid separations that require ultrafine differentiation of closely sized molecules.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Modifiers versus Channels: Creating Shape-Selective Catalysis of Metal Nanoparticles/Porous Nanomaterials

Shape-selective catalysis is of great research interest for its key role in chemical synthesis. Porous nanomaterials with uniform pore structures, have been proven as ideal supports for metal nanoparticles (MNPs) to generate efficient shape-selective catalysis. However, many widely used commercial irregular porous nanomaterials usually face the challenge to realize satisfactory shape selectivity due to the lack of molecular sieving structures. In this work, we report a concept of creating shape selectivity in MNPs/porous-MNPs using appropriate modifiers. The remained MNPs within the porous nanomaterials can cooperate with the channels to generate selectivity. Such strategy not only applies to regular porous nanomaterials (metal-organic frameworks, zeolites, etc.), but also can be extended to irregular porous nanomaterials (active carbon, P25, etc.). Potentially, the matching among different MNPs, corresponding modifiers and porous nanomaterials makes our strategy promising for wide applications in selective catalytic systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Model validation and selection in metabolic flux analysis and flux balance analysis

13C-Metabolic Flux Analysis (13C-MFA) and Flux Balance Analysis (FBA) are widely used to investigate the operation of biochemical networks in both biological and biotechnological research. Both methods use metabolic reaction network models of metabolism operating at steady state so that reaction rates (fluxes) and the levels of metabolic intermediates are constrained to be invariant. They provide estimated (MFA) or predicted (FBA) values of the fluxes through the network in vivo, which cannot be measured directly. These fluxes can shed light on basic biology and have been successfully used to inform metabolic engineering strategies. Several approaches have been taken to test the reliability of estimates and predictions from constraint-based methods and to compare alternative model architectures. Despite advances in other areas of the statistical evaluation of metabolic models, such as the quantification of flux estimate uncertainty, validation and model selection methods have been underappreciated and underexplored. We review the history and state-of-the-art in constraint-based metabolic model validation and model selection. Applications and limitations of the χ 2 -test of goodness-of-fit, the most widely used quantitative validation and selection approach in 13C-MFA, are discussed, and complementary and alternative forms of validation and selection are proposed. A combined model validation and selection framework for 13C-MFA incorporating metabolite pool size information that leverages new developments in the field is presented and advocated for. Finally, we discuss how adopting robust validation and selection procedures can enhance confidence in constraint-based modeling as a whole and ultimately facilitate more widespread use of FBA in biotechnology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

PdCu Single Atom Alloys for the Selective Oxidation of Methanol to Methyl Formate at Low Temperatures

The selective catalytic oxidation of methanol to methyl formate (MF) has been considered as an attractive route to produce MF, an important precursor in the chemical industry. Although supported Pd nanoparticles are active for the selective oxidation of methanol to MF, the relatively low MF selectivity and yield remains an unsolved issue. Here in this paper, we show that adding a small amount of Pd into Cu forming PdCu single atom alloy (SAA) catalysts can catalyze the oxidation of methanol to MF selectively at low temperatures, with a high catalyst stability. The atomic dispersion of Pd atoms in the Cu matrix was confirmed by various in-situ characterization techniques. The activity and selectivity of PdCu SAA catalysts were compared to monometallic Cu and Pd catalysts, in a flow reactor at similar conditions. This work may guide the design of new SAA based catalysts for selective oxidation reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Promotion of catalytic selectivity on transition metal oxide through restructuring surface lattice

Pursuit of high catalytic selectivity is paramount in the design of catalysts for green chemical processes towards minimizing the production of undesired products. We demonstrated that catalytic selectivity for production of alkene through oxidative dehydrogenation of alkane on transition metal oxides can be promoted through tailoring the surface lattice of the oxide catalyst. Selectivity for production of ethylene through oxidative dehydrogenation (ODH) of ethane on Co 3 O 4 nanocrystals can be substantially increased by 30%–35% via temperature-mediated reconstruction of surface lattice of Co 3 O 4 . Co 3 O 4 nanocrystals formed at 800 °C leads to smooth, flat crystal plane with predominantly exposed (111) facet in contrast to high Miller index (311) facet of Co 3 O 4 formed at ≤700 °C, revealed by environmental transmission electron microscopy. Isotope-labelled experiments suggest that the higher catalytic selectivity on the (111) facet results from the lower activity of its surface lattice oxygen atoms. Consistent with these experimental results, DFT calculations suggest low activity of surface lattice oxygen atoms and high activation barriers for adsorption and dissociation of C—H bond on the (111) surface in contrast to (311). Upon the activation of C—H on (311), the stronger binding of ethylene on more active, under-coordinated surface lattice oxygen atoms of (311) forms a robust “deprotonated ethylene glycol”-like intermediate on (311) with a rate-limiting desorption barrier to the formation of ethylene. Compared to (311), the kinetically favorable desorption of bound ethylene species from (111) surface well rationalized the higher selectivity for production of ethylene on (111) than (311). Here these findings demonstrate that temperature-mediated tailoring of the surface lattice for a transition metal oxide nanocatalyst is a promising approach in pursuing high selectivity in oxidative dehydrogenation of hydrocarbons.

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

A systematic feature extraction and selection framework for data-driven whole-building automated fault detection and diagnostics in commercial buildings

In data-driven automated fault detection and diagnostics (AFDD) modeling for building energy systems, feature engineering is a critical process of extracting information from high-dimensional and noisy sensor measurement and turning it into informative and representative inputs or features for data-driven modeling. However, few studies specifically discuss the feature engineering, especially the interactions between feature extraction and feature selection in whole-building AFDD. We developed a systematic feature extraction and selection framework for whole-building AFDD. In this framework, features are aggressively extracted from raw sensor data using statistical feature extraction techniques with various window sizes and statistics. With many features extracted, a hybrid feature selection algorithm that combines the filter and wrapper method then selects the best feature set. The framework considers diversity in the duration of fault behavior among fault types in whole-building AFDD, thus achieving high model generalization. We implemented our developed framework in a virtual testbed calibrated with measured data from Oak Ridge National Laboratory's Flexible Research Platform designed to mimic the operation of a typical small commercial building. The AFDD model is trained by the simulation data generated from the virtual testbed. The results show that (1) the developed framework improves the generalization of the AFDD model by 10.7% compared with literature-reported feature extraction and selection methods and (2) features with diverse window sizes and statistics are selected, providing insight into physical systems beyond the current understanding of buildings and faults and improving the detection and diagnostics of multiple fault types.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Molecular dynamics study of carbon dioxide and nitrogen selectivity through poly[bis((methoxyethoxy)ethoxy)phosphazene] (MEEP) membrane

Here, a molecular dynamics simulation model was developed to comprehensively understand carbon dioxide over nitrogen (CO 2 /N 2 ) selectivity through polyphosphazene-based membrane comprising of poly[bis((methoxyethoxy)ethoxy)phosphazene] (MEEP) selective layer at the molecular level. The effects of temperature, pressure, and initial feed gas composition on the CO 2 transport on a polymer membrane were studied. The computed free energy and density profile of the permeating gas mixture exhibited that CO 2 molecules express higher interactions with the membrane than N 2 molecules, resulting in higher CO 2 /N 2 selectivity. Statistical analysis of gas molecules (CO 2 , water (H 2 O), and N 2 ) transportation suggested that hydro- and CO 2 -philic functional groups in the membrane significantly impact CO 2 permeability and CO 2 /N 2 selectivity. This study suggested that Lewis acid–base and hydrogen bonding combinations contribute to CO 2 permeation and CO 2 /N 2 selectivity. An equal CO 2 /N 2 selectivity was observed with and without water vapor in the feed gas suggesting that water does not hinder CO 2 transport through the membrane.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Breaking the trade-off between selectivity and adsorption capacity for gas separation

It is generally recognized that porous solids (sorbents) with high selectivity and high adsorption capacity offer potential for energy-efficient gas separations. Unfortunately, there is generally a trade-off between capacity and selectivity, which represents a roadblock to the utility of sorbents in key industrial processes. For example, acetylene (C 2 H 2 ), an important fuel and chemical intermediate, is produced with CO 2 as an impurity, and the similar physicochemical properties of C 2 H 2 and CO 2 mean that most sorbents are poorly selective. Hybrid ultramicroporous materials (HUMs) are candidates for gas separations as they exhibit benchmark selectivity for several key gas pairs. Unfortunately, existing HUMs are handicapped by low capacity. Here, we report a new HUM, SIFSIX-21-Ni, that addresses the trade-off between selectivity and capacity that has plagued sorbents, as its high uptake and high selectivity renders it the new benchmark for C 2 H 2 /CO 2 separation performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Selectivity mechanisms of ion intercalation in Prussian blue analogs

Prussian blue analogs (PBAs) are a family of materials with facile, reversible, and selective ion transport capability for various ions via electrochemical intercalation, owing to their vacancy structure. The large tunable compositional space of PBAs allows for manipulation of intercalation behavior and selectivity by controlling structural vacancy level through choice of transition metal centers and modifications to the synthesis process. However, a lack of understanding of the mechanisms of ion selectivity hinders the material’s design process. Here, for this work, we investigated the origins of ion selectivity using a model PBA, copper hexacyanoferrate, and focused on eight technologically and biologically prominent ions, for which we determined a sequence of selectivity: Rb + > K + > Na + > Ba 2+ > Sr 2+ ≈ Ca 2+ > Mg 2+ > Li + . We provide electrochemical, structural, and redox evidence of strong correlation between the ion identity, the dominant charge-compensating redox, and preferred occupancy site. Specifically, using synchrotron anomalous X-ray diffraction (AXRD), we reveal that monovalent ions exhibit significant association with the corner sites of the unit cell and iron redox, whereas divalent ions display affinity toward the center site with higher ratios of copper redox. Informed by selectivity results, we applied CuHCFe to Li purification and achieved 99.9% purity. Our findings demonstrate an approach to elucidating ion intercalation behavior in order to distinguish and manipulate material properties to optimize separation performance.

Prussian blue analog↗
DOE OSTI2021

Highly selective ion separations based on counter-flow electromigration in nanoporous membranes

Highly selective ion separations are vital for recovering important salts, and membrane-based techniques may enable environmentally friendly ion separations that operate continuously. This study demonstrates that simply opposing convective flow with electromigration in track-etched membranes leads to remarkable selectivities among monovalent ions. Because the membrane-pore diameters are orders of magnitude larger than the ion diameters, advection moves all ions at the same velocity, whereas electrophoretic velocities are proportional to ion mobilities. Thus during counter-flow cation electromigration, less mobile cations have lower electromigration velocity components and pass through porous membranes more rapidly than more mobile cations. Using membranes with 400 nm pores, counter-flow electromigration gives Li + /K + selectivities of 100 and Li + /Na + selectivities around 30 in mixed-salt studies. In this work, numerical simulations based on the extended Nernst-Planck equation agree with trends in experimental data and highlight the importance of high Péclet numbers, high current-to-flow ratios, and uniform current distributions for achieving high selectivities. Importantly, experimental separations give high selectivities at 0.3 M ionic strength and low Li + /K + ratios, which suggest these methods may also work in brine solutions. Nevertheless, energy costs for such separations are high.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Cellulose acetate membranes exhibit exceptional monovalent to divalent cation selectivities

Salt transport properties of cellulose acetate membranes are reported for a series of chloride salts with mono- valent and divalent cations (LiCl, NaCl, MgCl 2 , CaCl 2 ). Measurements include salt permeability and sorption, with diffusivity values calculated from the permeability and sorption results. We report an exceptionally high LiCl/MgCl 2 selectivity of 750:1. Salts with similar valence (LiCl and NaCl; MgCl 2 and CaCl 2 ) have similar transport properties. The high monovalent/divalent selectivity arises from differences in both sorption and diffusion, with a LiCl/MgCl 2 solubility selectivity of about 11 and a diffusivity selectivity of about 70. Atomistic molecular dynamics simulations show that ions tend to reside in isolated clusters of water. Increasing ion charge strengthens ion–water interactions relative to ion–polymer interactions, explaining the reduced sorption of divalent ions. Diffusion of ions through the membrane occurs via hop-like motion between water clusters. Lithium diffuses faster than magnesium due to weaker ion–water coordination for lithium, which allows for greater mobility within water clusters and more frequent hopping. Altogether, our atomistic simulations suggest that the high LiCl/MgCl 2 selectivity is linked to cellulose acetate’s high water/salt selectivity and is a consequence of low water content and relatively uniform water distribution.

36 MATERIALS SCIENCE↗