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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Extraction chromatography of 225 Ac and lanthanides on N,N-dioctyldiglycolamic acid /1-butyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide solvent impregnated resin

The alpha-emitter 225 Ac (t 1/2 = 9.92 d) is currently under development for targeted alpha-particle therapy of cancer, and accelerator production of 225 Ac via proton irradiation of thorium targets requires robust separations of 225 Ac from chemically similar fission product lanthanides. Additionally, the lanthanide elements represent critical components in modern technologies, and radiolanthanides such as 140 Nd (t 1/2 = 3.37 d) also have potential application in the field of nuclear medicine. The ionic liquid, 1-butyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([Bmim][NTf 2 ]), combined with the diglycolamide extractant, N,N-dioctyldiglycolamic acid (DODGAA), was adsorbed on macroporous resin support to produce a solvent impregnated resin (SIR) that was investigated for separations of 225 Ac and lanthanides. The equilibrium distribution coefficients (Kd) of the rare earth elements (Sc(III), Y(III), Ln(III)), 225 Ac(III), Th(IV), and U(VI) on the prepared DODGAA/[Bmim][NTf 2 ]-SIR were determined from batch adsorption experiments in HCl and HNO 3 media. The DODGAA/[Bmim][NTf2]-SIR exhibited preferential uptake of the heavier lanthanide elements while allowing for the separation of the lighter lanthanides. Column separations utilizing the DODGAA/[Bmim][NTf 2 ]-SIR were effective at separating the lighter lanthanides from each other, and separating 225 Ac from a mixture of lanthanides, 213 Bi, and 225 Ra without the need for additional complexing agents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

A volatile fluid assisted thermo-pneumatic liquid metal energy harvester

A close-cycle self-driving thermal energy harvester using liquid metal as energy carrier fluid has been proposed. The driving force that pushes the liquid metal against flow resistance and gravity is provided by a resistively heated volatile fluid based on thermo-pneumatic principle. The tested harvester prototype demonstrated its capability to extract thermal energy between small temperature gradient, at a scale of 10 °C. During a 5-h operation, it further demonstrated robust liquid metal recirculating performance at a time-average volume flow rate of 14 ml/min with a 12.25 W heating load. The prototype also managed to self-adjust to variable working conditions which indicated the reliability of this method. Advantages of this method include simple-structural design, rigid-motion free operation, and low-temperature actuation. These advantages make it uniquely suited for solar energy and low-grade heat harvesting, high heat flux electronics cooling, as well as autonomous machines actuating.

42 ENGINEERING↗
NASA NTRS2022

Non-Protein Amino Acids Identified in Carbon-Rich Hayabusa Particles

Amino acid abundances in acid-hydrolyzed hot water extracts of gold foils containing five Category 3 (carbon-rich) Hayabusa particles were studied using liquid chromatography with tandem fluorescence and accurate mass detection. Initial particle analyses using field emission scanning electron microscopy with energy-dispersive X-ray spectrometry indicated that the particles were composed mainly of carbon. Prior to amino acid analysis, infrared and Raman microspectroscopy showed some grains possessed primitive organic carbon. Although trace terrestrial contamination, namely L-protein amino acids, was observed in all Hayabusa extracts, several terrestrially uncommon non-protein amino acids were also identified. Some Hayabusa particles contained racemic (D≈L) mixtures of the non-protein amino acids β-aminoisobutyric acid (β-AIB) and β-amino-n-butyric acid (β-ABA) at low abundances ranging from 0.09 to 0.31 nmol g −1 . Larger abundances of the non-protein amino acid β-alanine (9.2 nmol g −1 , ≈4.5 times greater than background levels) were measured in an extract of three Hayabusa particles. This β-alanine abundance was ≈6 times higher than that measured in an extract of a CM2 Murchison grain processed in parallel. The comparatively high β-alanine abundance is surprising as asteroid Itokawa is similar to amino acid-poor LL ordinary chondrites. Elevated β-alanine abundances and racemic β-AIB and β-ABA in Hayabusa grains suggested these compounds have non-biological and plausibly non-terrestrial origins. These results are the first evidence of plausibly extraterrestrial amino acids in asteroid material from a sample-return mission and demonstrate the capabilities of the analytical protocols used to study asteroid Ryugu and Bennu samples returned by the JAXA Hayabusa2 and NASA OSIRIS-REx missions, respectively.

Eric T. Parker↗
DOE OSTI2019

Conversion of depolymerized sugars and aromatics from engineered feedstocks by two oleaginous red yeasts

One of the requirements for efficient biological conversion of lignocellulose to bioproducts is the compatibility of biological catalysts with the processes employed to solubilize and depolymerize the lignocellulosic components. The red yeasts Rhodosporidium toruloides and Rhodotorula mucilaginosa were evaluated for their ability to assimilate sugars and aromatic compounds extracted from two engineered lines of Arabidopsis thaliana with modified lignin or the wild-type using ionic liquid, acid or alkaline pretreatments. Differential amounts of monomeric sugars, organic acids and, in the case of the engineered lines, either 4-hydroxybenzoic or protocatechuic acid were additionally released from the biomass and found to be tolerated and consumed by both microorganisms. Genetically-engineered strains of the two red yeasts successfully converted the depolymerized products into the biofuel precursor bisabolene when cultivated on hydrolysates or synthetic media containing specific sugars, acids and aromatics found in the hydrolysates.

Rodriguez, Alberto↗
DOE OSTI2021

Extraction of Furfural and Furfural/5-Hydroxymethylfurfural from Mixed Lignocellulosic Biomass-Derived Feedstocks

We present a combined in silico and experimental study on the extraction of furfural and 5-hydroxymethylfurfural (HMF) in aqueous–organic biphasic systems. We predict the liquid–liquid equilibria and furfural/HMF partition coefficients of over 2200 water-organic biphasic systems using the multiscale COSMO-RS model and measure experimentally single-component (furfural) and mixture (furfural and HMF) partition coefficients at room and dehydration reaction-relevant temperatures in 28 solvents. We find the experimental data to be within a factor of 2 from the COSMO-RS predictions. Even though furfural and HMF have chemical similarity, the slight differences in molecular structure render the separation of furfural easier by the supply of more solvents of higher partition coefficient for extraction. We leverage this molecular difference and experimentally demonstrate that with an additional extraction step, using dichloromethane or toluene, we can selectively extract furfural from furfural-HMF mixtures, which can coexist in lignocellulosic biomass dehydration products, despite their partition coefficients being generally correlated. We complement solvent selection criteria for biphasic lignocellulosic biomass processes with a simple mass balance extraction model for determining volume ratios in multistage extraction. Lastly, the molecular nature of the preferential furfural extraction is rationalized using COSMO-RS σ-profile analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Single Stage Contactor Testing Of The Next Generation Solvent Blend

The Modular Caustic Side Solvent Extraction (CSSX) Unit (MCU) facility at the Savannah River Site (SRS) is actively pursuing the transition from the current BOBCalixC6 based solvent to the Next Generation Solvent (NGS)-MCU solvent to increase the cesium decontamination factor. To support this integration of NGS into the MCU facility the Savannah River National Laboratory (SRNL) performed testing of a blend of the NGS (MaxCalix based solvent) with the current solvent (BOBCalixC6 based solvent) for the removal of cesium (Cs) from the liquid salt waste stream. This testing utilized a blend of BOBCalixC6 based solvent and the NGS with the new extractant, MaxCalix, as well as a new suppressor, tris(3,7dimethyloctyl) guanidine. Single stage tests were conducted using the full size V-05 and V-10 liquid-to-liquid centrifugal contactors installed at SRNL. These tests were designed to determine the mass transfer and hydraulic characteristics with the NGS solvent blended with the projected heel of the BOBCalixC6 based solvent that will exist in MCU at time of transition. The test program evaluated the amount of organic carryover and the droplet size of the organic carryover phases using several analytical methods. The results indicate that hydraulically, the NGS solvent performed hydraulically similar to the current solvent which was expected. For the organic carryover 93% of the solvent is predicted to be recovered from the stripping operation and 96% from the extraction operation. As for the mass transfer, the NGS solvent significantly improved the cesium DF by at least an order of magnitude when extrapolating the One-stage results to actual Seven-stage extraction operation with a stage efficiency of 95%.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Extracting low energy signals from raw LArTPC waveforms using deep learning techniques — A proof of concept

Here, we investigate the feasibility of using deep learning techniques, in the form of a one-dimensional convolutional neural network (1D-CNN), for the extraction of signals from the raw waveforms produced by the individual channels of liquid argon time projection chamber (LArTPC) detectors. A minimal generic LArTPC detector model is developed to generate realistic noise and signal waveforms used to train and test the 1D-CNN, and evaluate its performance on low-level signals. We demonstrate that our approach overcomes the inherent shortcomings of traditional cut-based methods by extending sensitivity to signals with ADC values below their imposed thresholds. This approach exhibits great promise in enhancing the capabilities of future generation neutrino experiments like DUNE to carry out their low-energy neutrino physics programs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Rapid Quantification of 237 U Specific Activity for Nuclear Forensics

In the event of an unattributed nuclear explosion, rapid assessment of the short-lived uranium isotope activity and mass can provide valuable information for subsequent forensic analysis. Rapid analysis in the field is enabled by using microfluidic chemistry and deployable instrumentation. Here, this work presents a flow chemistry system, controlled in LabVIEW, that integrates three functionalities: (1) selective extraction of uranium from the sample matrix via a 3D-printed supported liquid membrane module; (2) UV–visible absorbance spectrophotometry to measure the total uranium concentration in the strip flow; and (3) a portable CdTe γ-ray spectrometer coupled to a 3D-printed flow cell to measure 237 U activity concentration in the strip solution. The system was calibrated using standard solutions, and its functionality was demonstrated using a solution of depleted uranium spiked with 237 U. Uranium concentrations of 40–5000 μg/mL were directly quantified online using a 100 mm optical flow cell, while concentrations of 0.5–10 μg/mL were quantified online using a colorimetric reagent. The mass concentration measurement takes approximately 60 min while the activity concentration via γ-ray spectrometry varies depending on the activity of 237 U, with 1 kBq/mL requiring about 30 min of acquisition time to obtain <10% uncertainty at 1σ. This platform provides a fieldable approach for quantifying uranium mass and radioactivity relevant to postdetonation nuclear debris.

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

KBKit: A Python Toolkit for Kirkwood–Buff Theory from Molecular Dynamics

Thermodynamic properties of liquid mixtures govern processes that range from drug delivery to energy storage, yet extracting these properties from molecular simulations remains challenging. Kirkwood–Buff (KB) theory offers a rigorous route by linking microscopic pair distribution functions to macroscopic free energies, but practical use of the theory has been hindered by two obstacles: (i) the long simulations needed to obtain well-converged Kirkwood-Buff integrals (KBIs) and (ii) the specialized corrections required to translate finite-size data to the thermodynamic limit. $\texttt{KBKit}$ is an open-source Python package that removes these barriers. It automatically computes KBIs and derived thermodynamic quantities from GROMACS input files, applies state-of-the-art finite-size corrections, and provides built-in diagnostic tools to quantify statistical uncertainty. Written with modern software-engineering practices—continuous integration, extensive unit testing, and thorough documentation—$\texttt{KBKit}$ is both reliable and easy to extend. By condensing complex KBI analysis into a few intuitive commands, $\texttt{KBKit}$ enables researchers to incorporate KB theory into routine simulation workflows and accelerate the discovery of solution-phase thermodynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Automated “Cells-To-Peptides” Sample Preparation Workflow for High-Throughput, Quantitative Proteomic Assays of Microbes

Mass spectrometry-based quantitative proteomic analysis has proven valuable for clinical and biotechnology-related research and development. Improvements in sensitivity, resolution, and robustness of mass analyzers have also added value. However, manual sample preparation protocols are often a bottleneck for sample throughput and can lead to poor reproducibility, especially for applications where thousands of samples per month must be analyzed. To alleviate these issues, we developed a “cells-to-peptides” automated workflow for Gram-negative bacteria and fungi that includes cell lysis, protein precipitation, resuspension, quantification, normalization, and tryptic digestion. The workflow takes 2 h to process 96 samples from cell pellets to the initiation of the tryptic digestion step and can process 384 samples in parallel. We measured the efficiency of protein extraction from various amounts of cell biomass and optimized the process for standard liquid chromatography–mass spectrometry systems. The automated workflow was tested by preparing 96 Escherichia coli samples and quantifying over 600 peptides that resulted in a median coefficient of variation of 15.8%. Similar technical variance was observed for three other organisms as measured by highly multiplexed LC-MRM–MS acquisition methods. These results show that this automated sample preparation workflow provides robust, reproducible proteomic samples for high-throughput applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Alloy-assisted deposition of three-dimensional arrays of atomic gold catalyst for crystal growth studies

Large-scale assembly of individual atoms over smooth surfaces is difficult to achieve. A configuration of an atom reservoir, in which individual atoms can be readily extracted, may successfully address this challenge. In this work, we demonstrate that a liquid gold-silicon alloy established in classical vapor-liquid-solid growth can deposit ordered and three-dimensional rings of isolated gold atoms over silicon nanowire sidewalls. Here, we perform ab initio molecular dynamics simulation and unveil a surprising single atomic gold-catalyzed chemical etching of silicon. Experimental verification of this catalytic process in silicon nanowires yields dopant-dependent, massive and ordered 3D grooves with spacing down to similar to 5 nm. Finally, we use these grooves as self-labeled and ex situ markers to resolve several complex silicon growths, including the formation of nodes, kinks, scale-like interfaces, and curved backbones.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Small-angle neutron scattering study of a dense microemulsion system formed with an ionic liquid

Mixtures of water, octane and 1-octanol with 1-tetradecyl-3-methylimidazolium chloride (C14MIM·Cl), often referred to as a surface active ionic liquid (SAIL), form water-in-oil microemulsions that have potential application as extraction media for various metal ions. Here in this work, we present a structural study by small-angle neutron scattering (SANS) of dense microemulsions formed by surfactant-rich mixtures of these four compounds to understand how the SAIL can be used to tune the structures and properties of the microemulsions. The SANS experiments revealed that the microemulsions formed are composed of two phases, a water-in-oil microemulsion and a bicontinuous microemulsion, which becomes the dominant phase at high surfactant concentration. In this concentration regime, the surfactant film becomes more rigid, having a higher bending modulus that results from the parallel stacking of the imidazolium ring of the SAIL. At lower surfactant concentrations, the molecular packing of the SAIL does not change with the water content of the microemulsion. Finally, the results presented here correlate well with previously observed changes in the interaction between the IL cation and metal ions (Y. Tong, L. Han and Y. Yang, Ind. Eng. Chem. Res., 2012, 51, 16438–16443), while the capacity of the microemulsion system for water remains high enough for using the system as an extraction medium.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Isotope effects in molecular structures and electronic properties of liquid water via deep potential molecular dynamics based on the SCAN functional

Here, Feynman path-integral deep potential molecular dynamics (PI-DPMD) calculations have been employed to study both light (H 2 O) and heavy water (D 2 O) within the isothermalisobaric ensemble. In particular, the deep neural network is trained based on ab initio data obtained from the strongly constrained and appropriately normed (SCAN) exchange-correlation functional. Because of the lighter mass of hydrogen than deuteron, the properties of light water are more influenced by nuclear quantum effect than those of heavy water. Clear isotope effects are observed and analyzed in terms of hydrogen-bond structure and electronic properties of water that are closely associated with experimental observables. The molecular structures of both liquid H 2 O and D 2 O agree well with the data extracted from scattering experiments. The delicate isotope effects on radial distribution functions and angular distribution functions are well reproduced as well. Our approach demonstrates that deep neural network combined with SCAN functional based ab initio molecular dynamics provides an accurate theoretical tool for modeling water and its isotope effects.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Validation of CTF Droplet Entrainment and Annular/Mist Closure Models using Riso Steam/Water Experiments

This report summarizes the work done to validate the droplet entrainment and de-entrainment models as well as two-phase closure models in the CTF code by comparison with experimental data obtained at Riso National Laboratory. The Riso data included a series of over 250 steam/water experiments that were performed in both tube and annulus geometries over a range of various pressures and outlet qualities. Experimental conditions were set so that the majority of cases were in the annular/mist ow regime. Measurements included liquid lm ow rate, droplet ow rate, lm thickness, and two-phase pressure drop. CTF was used to model 180 of the tubular geometry cases, matching experimental geometry, outlet pressure, and outlet ow quality to experimental values. CTF results were compared to the experimental data at the outlet of the test section in terms of vapor and entrained liquid ow fractions, pressure drop per unit length, and liquid lm thickness. The entire process of generating CTF input decks, running cases, extracting data, and generating comparison plots was scripted using Python and Matplotlib for a completely automated validation process. All test cases and scripting tools have been committed to the COBRA-TF master repository and selected cases have been added to the continuous testing system to serve as regression tests. The dierences between the CTF- and experimentally-calculated ow fraction values were con- sistent with previous calculations by Wurtz, who applied the same entrainment correlation to the same data. It has been found that CTF's entrainment/de-entrainment predictive capability in the annular/mist ow regime for this particular facility is comparable to the licensed industry code, COBRAG. While lm and droplet predictions are generally good, it has been found that accuracy is diminished at lower ow qualities. This nding is consistent with the noted deciencies in the Wurtz entrainment model employed by CTF. The CTF predicted two-phase pressure drop in the annular/mist ow regime has been found to be highly inaccurate, exhibiting a clear bias with respect to the experimental data. This inaccuracy led to an investigation that revealed deciencies in the implementation of the annular/mist interfacial friction model, which should be investigated further in the future. Looking to published COBRAG results for this same facility reveal it exhibits no bias with regard to experimental pressure drop results. In addition to the problems with pressure drop prediction, the lm thickness was also signicantly under-predicted by CTF compared to both experimental data and Wurtz's analytical calculations. Film thickness is calculated using a simple geometric relationship and lm void fraction in CTF, which is dependent on slip ratio and interfacial friction. It is possible that the issues aecting the pressure drop and lm void prediction are related.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Salts in Hot Water: Developing a Scientific Basis for Supercritical Desalination and Strategic Metal Recovery

Given the steady growth in world population and the ever-increasing fresh water demand, the only sustainable water supply option is desalination. Conceptually, desalination is very simple - just separate dissolved salts from water. While desalination research programs have existed since the 1960s and have resulted in a multitude of approaches, realizing affordable desalination has proven to be a challenge. Our goal is to meet this challenge using low cost heat sources to drive a liquid-discharge-free desalination process that can be co-mingled with the extraction of economically valuable co-products. High temperatures and pressures will be used to manipulate water’s properties, such as the dielectric constant, and hence its ability to solvate ions. Selective precipitation/recovery of valuable metal co-products creates new revenue streams (i.e., cost offsets). We will develop the scientific understanding necessary to control salt precipitation from supercritical seawater, inland brines, and water commonly co-produced with oil and gas. Atomistic simulations will be used to understand at a molecular level the changes in hydrogen bonding and ion solvation that occur as we increase the temperature and/or pressure and change the density and ion concentration. Our simulation results will also aid in the interpretation of experimental data and guide the development of applied thermodynamic models for engineering design calculations.

58 GEOSCIENCES↗
NASA NTRS1988

Determination of low molecular weight thiols using monobromobimane fluorescent labeling and high-performance liquid chromatography

Methods are described for the preparation and high-performance liquid chromatography (HPLC) analysis of monobromobimane derivatives of low molecular weight thiols in extracts of biological samples. Typical problems encountered in the development and application of these methods are discussed. Analysis of mung bean extract is used as an example.

Fahey, Robert C.↗
DOE OSTI2021

Extracting low energy signals from raw LArTPC waveforms using deep learning techniques -- A proof of concept

We investigate the feasibility of using deep learning techniques, in the form of a one-dimensional convolutional neural network (1D-CNN), for the extraction of signals from the raw waveforms produced by the individual channels of liquid argon time projection chamber (LArTPC) detectors. A minimal generic LArTPC detector model is developed to generate realistic noise and signal waveforms used to train and test the 1D-CNN, and evaluate its performance on low-level signals. We demonstrate that our approach overcomes the inherent shortcomings of traditional cut-based methods by extending sensitivity to signals with ADC values below their imposed thresholds. This approach exhibits great promise in enhancing the capabilities of future generation neutrino experiments like DUNE to carry out their low-energy neutrino physics programs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2008

[Stardust Amines]

We investigated the abundances of amino acids and amines, as well as their enantiomeric composition in water extracts of comet Wild 2 exposed aerogel and aluminum foils returned by Stardust using liquid chromatography with UV fluorescence detection and time of flight-mass spectrometry (LC-FD/ToF-MS). A suite of amino acids and amines including glycine, L-alanine, methylamine (MA), and ethylamine (EA) were identified in the Stardust bulk aerogel. With the exception of MA and EA, all other primary amines detected in comet-exposed aerogels were also present in the aerogel witness tile that was not exposed to Wild 2, suggesting that most amines are terrestrial in origin. The enhanced abundances of MA, EA, and possibly glycine in comet-exposed aerogel compared to controls, coupled with MA to EA ratios (approx.1 to 2) that are distinct from preflight aerogels (approx.7 to lo), suggest that these amines were captured from Wild 2. The presence of cometary amines in Stardust material supports the hypothesis that comets were an important source of prebiotic organics on the early Earth. To better understand their origin, a systematic study of all these species with C, N, and H compound specific isotopic analysis (CSIA) via gas chromatography quadrupole mass spectrometry in with parallel with combustion isotope ratio mass spectrometry (GC-QMS/IRMS) is being conducted. We will discuss our latest C-CSIA measurements and what they indicate about the origin of the amino acids extracted from Stardust samples.

Dworkin, Jason P.↗