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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Pareto Optimization of Oligomer Polarizability and Dipole Moment Using a Genetic Algorithm

High-performance electronic components are highly sought after in order to produce increasingly smaller and cheaper electronic devices. Drawing inspiration from inorganic dielectric materials, in which both polarizability and polarization contribute, organic materials can also maximize both. For a large set of small molecules drawn from PubChem, a Pareto-like front appears between the polarizability and dipole moment, indicating the presence of an apparent trade-off between these two properties. We tested this balance in π-conjugated materials by searching for novel conjugated hexamers with simultaneously large polar- izabilities and dipole moments with potential use for dielectric materials. Using a genetic algorithm (GA) screening technique in conjunction with an approximate density functional tight-binding method for property calculations, we were able to efficiently search chemical space for optimal hexamers. Given the scope of chemical space, using the GA technique saves considerable time and resources by speeding up molecular searches compared to a systematic search. Here, we also explored the underlying structure–function relationships, including sequence and monomer properties, that characterize large polarizability and dipole moment regimes.

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

Ethanol Upgrading to n -Butanol Using Transition-Metal-Incorporated Poly(triazine)imide Frameworks

The upgrading of ethanol to n-butanol was performed using a molecular catalyst integrated into a carbon nitride support, one of the first examples of a supported molecular catalyst performing the Guerbet process. Initial studies using crystalline poly(triazine)imide (PTI) with lithium or transition-metal cations imbedded in the support together with a base as the catalyst system did not produce any significant amounts of n-butanol. However, when using the catalyst material formed by treatment of PTI-LiCl with [(Cp*)IrCl 2 ] 2 (Cp* = pentamethylcyclopentadienyl) along with sodium hydroxide, a 59% selectivity for butanol (13% yield) was obtained at 145 °C. This PTI-(Cp*)Ir material exhibited distinct UV–vis absorption features and powder X-ray diffractions which differ from those of the parent PTI-LiCl and [(Cp*)IrCl 2 ] 2 . Here, the PTI-(Cp*)Ir material was found to have a metal loading of 27% iridium per empirical unit of the framework. Along with the formation of n-butanol from the Guerbet reaction, the presence of higher chain alcohols was also observed.

Guerbet↗
DOE OSTI2020

Fabrication of UN-Mo CERMET Nuclear Fuel Using Advanced Manufacturing Techniques

Ceramic-metallic nuclear fuels are a candidate fuel for nuclear thermal propulsion systems due to their high heat transport properties, which are necessary in very high-temperature environments. The conventional fabrication of uranium nitride–molybdenum fuel has been thoroughly studied in the past, but modern manufacturing techniques have presented a unique opportunity for further development within this field. This work demonstrates the use of advanced manufacturing techniques to produce nuclear fuel pellets composed of uranium nitride microspheres encased in a molybdenum matrix. Binder jetting is used to print molybdenum disks that are filled with uranium nitride microspheres and afterward sintered using spark plasma sintering. Two fuel pellets were fabricated to demonstrate the methodology and to provide a baseline analysis of the effects of temperature and pressure processing conditions. Characterization of the sintered fuel pellets includes detailed microstructural analysis and thermal conductivity measurements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Modeling freight mode choice using machine learning classifiers: a comparative study using Commodity Flow Survey (CFS) data

This study explores the usefulness of machine learning classifiers for modeling freight mode choice. We investigate eight commonly used machine learning classifiers, namely Naïve Bayes, Support Vector Machine, Artificial Neural Network, K-Nearest Neighbors, Classification and Regression Tree, Random Forest, Boosting and Bagging, along with the classical Multinomial Logit model. US 2012 Commodity Flow Survey data are used as the primary data source; we augment it with spatial attributes from secondary data sources. The performance of the classifiers is compared based on prediction accuracy results. The current research also examines the role of sample size and training-testing data split ratios on the predictive ability of the various approaches. In addition, the importance of variables is estimated to determine how the variables influence freight mode choice. The results show that the tree-based ensemble classifiers perform the best. Specifically, Random Forest produces the most accurate predictions, closely followed by Boosting and Bagging. With regard to variable importance, shipment characteristics, such as shipment distance, industry classification of the shipper and shipment size, are the most significant factors for freight mode choice decisions.

42 ENGINEERING↗
DOE OSTI2020

Transients using low-high pulsed power in inductively coupled plasmas

Pulsed inductively coupled plasmas (ICPs) are widely deployed in the fabrication of semi-conductor devices. Pulse repetition frequencies (PRFs) of up to tens of kHz are commonly used during plasma etching for the high power densities they generate during the pulse-on period, and for their unique chemistries during the pulse-off period. The use of highly attaching halogen gases produces low electron densities during the pulse-off period, and these low density can result in instabilities, E-H transitions and ignition delays when applying power on the next pulse. To mitigate these possibilities, a low-level power environment could be maintained during “pulse-off” to moderate the minimum plasma density, therefore reducing ignition delays and enhancing plasma stability. In this work, ICPs sustained by 5 kHz pulsed power using Ar/Cl 2 mixtures at 20 mTorr were computationally investigated. For these conditions, the computed electron temperature (T e ) reaches a quasi-steady state during both the high- and low-power excitation. The model predicts that within the electromagnetic skin-depth, T e spikes to a high value during a low-to-high power modulation, and to a low value during a high-to-low power modulation. At the same time, a few cm above the substrate, there is little modulation in T e , as electron power convected from the skin depth disperses in traversing the reactor. Finally, the positive and negative spikes, and convection of transients across the reactors, are functions of power ramping time and gas mixtures.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

The use of synchrotron X-ray fluorescent imaging to study distribution and content of elements in chemically fixed single cells: a case study using mouse pancreatic beta-cells

Synchrotron X-ray fluorescence microscopy (SXRF) presents a valuable opportunity to study the metallome of single cells because it simultaneously provides high-resolution subcellular distribution and quantitative cellular content of multiple elements. Different sample preparation techniques have been used to preserve cells for observations with SXRF, with a goal to maintain fidelity of the cellular metallome. In this case study, mouse pancreatic beta-cells have been preserved with optimized chemical fixation. We show that cell-to-cell variability is normal in the metallome of beta-cells due to heterogeneity and should be considered when interpreting SXRF data. Additionally, we determined the impact of several immunofluorescence (IF) protocols on metal distribution and quantification in chemically fixed beta-cells and found that the metallome of beta-cells was not well preserved for quantitative analysis. However, zinc and iron qualitative analysis could be performed after IF with certain limitations. To help minimize metal loss using samples that require IF, we describe a novel IF protocol that can be used with chemically fixed cells after the completion of SXRF.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Using DAPPER to extract the photon strength function of 58 Fe using the inverse Oslo and shape methods

The photon strength function of 58 Fe has been extracted using both the Oslo and Shape methods from particle–γ coincidence data measured using the Detector Array for Photons, Protons, and Exotic Residues, which probes nuclei utilizing (d,p) reactions in inverse kinematics. Four particle–γ coincidence matrices, each constructed with different treatments of the γ–ray energies, are explored in order to observe the impact on the resulting nuclear level density and photon strength. The final photon strength function reported is found to agree well with previous Oslo measurements of other iron isotopes. Systematic uncertainties are included, using different model parameters and their reported errors to perform the Oslo method normalization. The model-independent Shape method is explored and the functional form of the photon strength function obtained is in agreement with the Oslo method results. A low-energy enhancement is not reported for 58 Fe in this work given possible subtraction issues originating from strongly populated states.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Using nature’s blueprint to expand catalysis with Earth-abundant metals

Original title changed for publication from; " Using Nature's Blueprint to Enable Catalysis with Earth-Abundant Metals" A diverse array of redox transformations that are essential to life are catalyzed by metalloenzymes that feature an earth-abundant metal. In contrast, platinum-group metals have been the cornerstone of many industrial catalytic reactions for decades, providing high activity, thermal stability and tolerance to chemical poisons. We assert that Nature’s blueprint provides the fundamental principles for vastly expanding the use of abundant metals in catalysis. We highlight the key physical properties of abundant metals that distinguish them from precious metals, and we look to Nature to understand how the inherent attributes of abundant metals can be embraced, leading to unique, highly efficient catalysts, emphasizing reactions crucial to the sustainable production and transformation of fuels and chemicals.

Bullock, Ronald M.↗
DOE OSTI2021

Quantitative 2D thermometry in turbulent sooting non-premixed flames using filtered Rayleigh scattering

This paper demonstrates the application of a thermometry method in turbulent sooting non-premixed flames using filtered Rayleigh scattering (FRS). Fuel tailoring is used to establish a specific C 2 H 2 -based fuel mixture such that temperature can be determined accurately by a single FRS measurement over the entirety of mixture fraction space, or equivalently, for all relevant thermo-chemical states. Evaluation is performed in a hierarchy of flows to establish measurement precision and accuracy. Initial assessments in a series of heated fuel mixtures; non-sooting, near-adiabatic flat flames; and laminar non-premixed sooting flames show accuracy of the approach over a full range of expected temperatures and high single-shot measurement precision (e.g., 65 < <#comment/> S N R < <#comment/> 80 ) for temperatures between 1900 and 2200 K. Subsequently, 2D temperature measurements are evaluated in a turbulent non-premixed sooting flame. For the current fuel mixture, the local mixture-averaged Rayleigh scattering cross section is nearly constant over all composition space, and thus traditional laser Rayleigh scattering (LRS) is used as a measurement standard in the absence of soot. The results show excellent agreement between the proposed FRS thermometry approach and LRS in non-sooting regions. In the presence of soot, the proposed FRS-based approach shows no signs of interference. In addition, 2D temperature imaging shows high SNR (60–74) over all temperature conditions. Thus, we believe the proposed methodology successfully provides a high-resolution 2D temperature method under turbulent sooting flame conditions.

Pu, Jinpeng↗
DOE OSTI2024

Using DAPPER to extract the photon strength function of 58Fe using the inverse Oslo and shape methods

The photon strength function of 58 Fe has been extracted using both the Oslo and Shape methods from particle-γ coincidence data measured using the Detector Array for Photons, Protons, and Exotic Residues, which probes nuclei utilizing (d,p) reactions in inverse kinematics. Four particle-γ coincidence matrices, each constructed with different treatments of the γ-ray energies, are explored in order to observe the impact on the resulting nuclear level density and photon strength. The final photon strength function reported is found to agree well with previous Oslo measurements of other iron isotopes. Systematic uncertainties are included, using different model parameters and their reported errors to perform the Oslo method normalization. The model-independent Shape method is explored and the functional form of the photon strength function obtained is in agreement with the Oslo method results. A low-energy enhancement is not reported for 58 Fe in this work given possible subtraction issues originating from strongly populated states.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Intracardiac Electrical Imaging using the 12-lead ECG: A Machine Learning Approach using Synthetic Data

Current state-of-the-art techniques for non-invasive imaging of cardiac electrical phenomena require voltage recordings from dozens of different torso locations and anatomical models built from expensive medical diagnostic imaging procedures. Here this study aimed to assess if recent machine learning advances could alternatively reconstruct electroanatomical maps at clinically relevant resolutions using only the standard 12-lead electrocardiogram (ECG) as input. To that end, a computational study was conducted to generate a dataset of over 16000 detailed cardiac simulations, which was then used to train neural network (NN) architectures designed to exploit both spatial and temporal correlations in the ECG signal. Analysis over a validation set showed average errors in activation map reconstruction below 1.7 msec over 75 intracardiac locations. Furthermore, phenotypical patterns of activation and the morphology of the activation potential were correctly reconstructed. The approach offers opportunities to stratify patients non-invasively, both retrospectively and prospectively, using metrics otherwise only available through invasive clinical procedures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

NdFeB Permanent Magnet Uses, Projected Growth Rates and Nd Plus Dy Demands across End-Use Sectors through 2050: A Review

Rare earth element (REE) permanent magnets (NdFeB) are a critical element in a vast and growing number of industrial applications. In consumer electronics, a broad category encompassing computer, CD, and DVD hard drives, in addition to the ubiquitous cell phones, the nominal NdFeB magnet content may be small, but the global market share for this sector accounts for almost 30% of NdFeB demand, due to a large and continually increasing consumer base. It is estimated that wind turbines that primarily employ permanent magnets will add roughly 110 GW annually of on- and off-shore capability over the next few years. Electric vehicles (EVs) and E-bicycles (EBs) equipped with permanent magnet motors comprise the transportation contribution. Permanent magnet motors have garnered nearly 100% of the market share among EV manufacturers worldwide. Industrial, professional service, and personal robots, most using permanent magnets, are also included in the projected global need for rare earths, particularly Nd and Dy. The sector projects significant growth of approximately 10% across robotic categories. In this paper, we calculate the future demand for Nd and Dy through 2050 across these sectors using a compounded annual growth rate coupled with magnet weight and rare earth content. Uncertainties in the estimates, such as the true global production of Nd, a range of end-product scales and/or unit types in each sector, varied magnet compositions, and the variety of uses within a sector, are all considered.

Geochemistry & Geophysics↗