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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Adhesion of Titanium Coatings on Additively Manufactured Stainless Steel

The ongoing global climate change crisis has brought attention to the urgent need to reduce greenhouse gas emissions from vehicles by providing alternative zero-emission fueling technologies. Prevailing vehicles are dependent on fossil fuels and contribute to climate change by creating emissions of carbon dioxide. In 2019, transportation was the largest contributing economic sector to the U.S. greenhouse gas emissions total at 29% [1]. By converting vehicle fueling to an alternative method, major reductions in greenhouse gas emissions can be achieved. Hydrogen fuel cells are one potential alternative capable of generating electricity from hydrogen while emitting only water. Several obstacles hinder the development of hydrogen fuel cells as a viable alternative, including the manufacturability of bipolar plates.

08 HYDROGEN↗
DOE OSTI2024

Revisiting the electrochemical reduction of CO 2 on Au 25 (SR)$\overline{_{18}}$ nanocluster

Experiments show that Au25(SR)$\overline{_{18}}$ is a potential electrocatalyst for the electrochemical reduction of CO 2 , but elucidation of the reaction mechanisms remain challenging experimentally. We evaluate key steps in the active site formation, CO 2 reduction, and H 2 evolution on the nanocluster employing density functional theory coupled with an explicit solvent model of the electrochemical interface to calculate activation barriers. The predicted preferred pathway for activating the nanocluster involves dethiolation, resulting in an exposed Au site that is both active and selective for CO 2 reduction. Finally, the alternative S site is found to be kinetically prohibitive and does not facilitate CO 2 reduction.

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

CSP Systems Analysis - Final Project Report

The CSP Systems Analysis project was a three-year effort supporting the Concentrating Solar Power (CSP) Subprogram within the Solar Energy Technologies Office of the U.S. Department of Energy (DOE). The goal of the CSP Systems Analysis project was to provide timely and accurate CSP cost data to the DOE and predict performance and cost for emerging technologies that may impact research directions and industry investment. The project consisted of six, mostly independent tasks. Major accomplishments over the three-year period of performance were as follows. The NREL team maintained current cost estimates for CSP technologies by annual updates to the cost input parameters within NREL's System Advisor Model (SAM). SAM is a performance and cost simulation software that includes technology models for the primary CSP technologies. During the period from 2016 to 2018, the estimated cost within SAM's default CSP molten-salt power tower technology dropped from 13.0 to 11.1 cent/kWh (real dollars without incentives). Power cycle models for the supercritical carbon dioxide (sCO2) Brayton Cycle were developed and made an option within SAM's molten-salt power tower model. These models were subsequently used to evaluate the cost reduction potential of alternative salts. The partial-cooling model was found to provide the greatest cost-reduction potential due to its combination of efficiency and temperature differential across the turbine and thermal energy storage (TES) system. These studies were documented in two journal articles. NREL's optical modeling software SolTrace and SolarPILOT were made more versatile and released as open-source software to the CSP community. These tools help researchers and developers to model and optimize the optical performance of CSP collector systems. The new features were highlighted in a recorded webinar that can be accessed from the NREL SAM website. New models for solar-thermal systems, that is, applications for solar industrial process heat, were developed, validated, and installed within SAM. The analysis includes a 2018 review of linear collectors in the market that are tailored for solar process heat applications. In 2018 the NREL team also developed an annual simulation for a direct steam generation system integrated with a latent-heat TES system. This analysis was submitted for journal publication. The NREL team continued to support the exchange of information and development of CSP guidelines within the international CSP community of SolarPACES. Much of the work under this project was presented at SolarPACES, including the development of a modeling checklist to help CSP stakeholders standardize the models used for estimating CSP performance and cost. The CSP Systems Analysis project also supported DOE requests for tracking and reporting programmatic targets for the CSP Subprogram.

14 SOLAR ENERGY↗
DOE OSTI2015

Optimizing Federal Fleet Vehicle Acquisitions: An Eleven-Agency FY 2012 Analysis

This report focuses on the National Renewable Energy Laboratory's (NREL) fiscal year (FY) 2012 effort that used the NREL Optimal Vehicle Acquisition (NOVA) analysis to identify optimal vehicle acquisition recommendations for eleven diverse federal agencies. Results of the study show that by following a vehicle acquisition plan that maximizes the reduction in greenhouse gas (GHG) emissions, significant progress is also made toward the mandated complementary goals of acquiring alternative fuel vehicles, petroleum use reduction, and alternative fuel use increase.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2015

Two-stage atlas subset selection in multi-atlas based image segmentation

Purpose: Fast growing access to large databases and cloud stored data presents a unique opportunity for multi-atlas based image segmentation and also presents challenges in heterogeneous atlas quality and computation burden. This work aims to develop a novel two-stage method tailored to the special needs in the face of large atlas collection with varied quality, so that high-accuracy segmentation can be achieved with low computational cost. Methods: An atlas subset selection scheme is proposed to substitute a significant portion of the computationally expensive full-fledged registration in the conventional scheme with a low-cost alternative. More specifically, the authors introduce a two-stage atlas subset selection method. In the first stage, an augmented subset is obtained based on a low-cost registration configuration and a preliminary relevance metric; in the second stage, the subset is further narrowed down to a fusion set of desired size, based on full-fledged registration and a refined relevance metric. An inference model is developed to characterize the relationship between the preliminary and refined relevance metrics, and a proper augmented subset size is derived to ensure that the desired atlases survive the preliminary selection with high probability. Results: The performance of the proposed scheme has been assessed with cross validation based on two clinical datasets consisting of manually segmented prostate and brain magnetic resonance images, respectively. The proposed scheme demonstrates comparable end-to-end segmentation performance as the conventional single-stage selection method, but with significant computation reduction. Compared with the alternative computation reduction method, their scheme improves the mean and medium Dice similarity coefficient value from (0.74, 0.78) to (0.83, 0.85) and from (0.82, 0.84) to (0.95, 0.95) for prostate and corpus callosum segmentation, respectively, with statistical significance. Conclusions: The authors have developed a novel two-stage atlas subset selection scheme for multi-atlas based segmentation. It achieves good segmentation accuracy with significantly reduced computation cost, making it a suitable configuration in the presence of extensive heterogeneous atlases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Impact of nitrogen and oxygen interstitials on niobium SRF cavity performance

Superconducting radio frequency (SRF) cavities are the leading technology for highly efficient particle acceleration, and their performance can be significantly enhanced through the controlled introduction of interstitial impurities into bulk niobium. Nitrogen doping has demonstrated a substantial reduction in surface resistance, which improves the quality factor of the cavities. More recently, oxygen doping has emerged as a promising alternative, demonstrating comparable reductions in surface resistance. In this study, we combine cavity measurements on 1.3 GHz niobium SRF cavities subjected to a range of nitrogen- and oxygen-based treatments with material characterizations performed on cavity cutouts processed under identical conditions. This approach allows us to quantitatively assess the contribution of each impurity to the reduction of surface resistance. We find that nitrogen is ten times more effective than oxygen in reducing surface resistance at 16 MV/m. We also observe an additive effect of O and N impurities in reducing RT. We discuss these results in the context of field-dependent nonequilibrium superconductivity, gap enhancement, and hydrogen trapping mechanisms.

Hu, H. [Chicago U.; Fermilab] (ORCID:0009000330621↗
DOE OSTI2019

Progress in the Development of Fe-Based PGM-Free Electrocatalysts for the Oxygen Reduction Reaction

Development of alternative energy sources is crucial to tackle challenges encountered by the growing global energy demand. Hydrogen fuel, a promising way to store energy produced from renewable power sources, can be converted into electrical energy at high efficiency via direct electrochemical conversion in fuel cells, releasing water as the sole byproduct. One important drawback to current fuel-cell technology is the high content of platinum-group-metal (PGM) electrocatalysts required to perform the sluggish oxygen reduction reaction (ORR). Addressing this challenge, remarkable progress has been made in the development of low-cost PGM-free electrocatalysts synthesized from inexpensive, earth-abundant, and easily sourced materials such as iron, nitrogen, and carbon (Fe–N–C). PGM-free Fe–N–C electrocatalysts now exhibit ORR activities approaching that of PGM electrocatalysts but at a fraction of the cost, promising to significantly reduce overall fuel-cell technology costs. Here in this paper, recent developments in PGM-free electrocatalysis, demonstrating increased fuel-cell performance, as well as efforts aimed at understanding the key limiting factor, i.e., the nature of the PGM-free active site, are summarized. Further improvements will be accomplished through the controlled and/or rationally designed synthesis of materials with higher active-site densities, while at the same time establishing methods to mitigate catalyst degradation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

CO 2 hydrogenation to formate and methanol as an alternative to photo- and electrochemical CO 2 reduction

In this study, carbon dioxide is one of the end products of combustion, and is not a benign component of the atmosphere. The concentration of CO 2 in the atmosphere has reached unprecedented levels and continues to increase owing to an escalating rate of fossil fuel combustion, causing concern about climate change and rising sea levels. In view of the inevitable depletion of fossil fuels, a possible solution to this problem is the recycling of carbon dioxide, possibly captured at its point of generation, to fuels. Researchers in this field are using solar energy for CO 2 activation and utilization in several ways: (i) so-called artificial photosynthesis using photo-induced electrons; (ii) bulk electrolysis of a CO 2 saturated solution using electricity produced by photovoltaics; (iii) CO 2 hydrogenation using solar-produced H 2 ; and (iv) the thermochemical reaction of metal oxides at extremely high temperature reached by solar collectors. Since the thermodynamics of CO 2 at high temperature (> 1000 ºC) are quite different from those near room temperature, only chemistry below 200 ºC is discussed in this review.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Impact of Component Sizing in Plug-In Hybrid Electric Vehicles for Energy Resource and Greenhouse Emissions Reduction

Widespread use of alternative hybrid powertrains currently appears inevitable and many opportunities for substantial progress remain. The necessity for environmentally friendly vehicles, in conjunction with increasing concerns regarding U.S. dependency on foreign oil and climate change, has led to significant investment in enhancing the propulsion portfolio with new technologies. Recently, plug-in hybrid electric vehicles (PHEVs) have attracted considerable attention due to their potential to reduce petroleum consumption and greenhouse gas (GHG) emissions in the transportation sector. PHEVs are especially appealing for short daily commutes with excessive stop-and-go driving. However, the high costs associated with their components, and in particular, with their energy storage systems have been significant barriers to extensive market penetration of PEVs. In the research reported here, we investigated the implications of motor/generator and battery size on fuel economy and GHG emissions in a medium duty PHEV. An optimization framework is proposed and applied to two different parallel powertrain configurations, pre-transmission and post-transmission, to derive the Pareto frontier with respect to motor/generator and battery size. The optimization and modeling approach adopted here facilitates better understanding of the potential benefits from proper selection of motor/generator and battery size on fuel economy and GHG emissions. This understanding can help us identify the appropriate sizing of these components and thus reducing the PHEV cost. Addressing optimal sizing of PHEV components could aim at an extensive market penetration of PHEVs.

design optimization↗
DOE OSTI2016

SU-F-T-147: An Alternative Parameterization of Scatter Behavior Allows Significant Reduction of Beam Characterization for Pencil Beam Proton Therapy

Purpose: 1) To describe the characteristics of pencil beam proton dose deposition kernels in a homogenous medium using a novel parameterization. 2) To propose a method utilizing this novel parametrization to reduce the measurements and pre-computation required in commissioning a pencil beam proton therapy system. Methods: Using beam data from a clinical, pencil beam proton therapy center, Monte Carlo simulations were performed to characterize the dose depositions at a range of energies from 100.32 to 226.08 MeV in 3.6MeV steps. At each energy, the beam is defined at the surface of the phantom by a two-dimensional Normal distribution. Using FLUKA, the in-medium dose distribution is calculated in 200×200×350 mm cube with 1 mm{sup 3} tally volumes. The calculated dose distribution in each 200×200 slice perpendicular to the beam axis is then characterized using a symmetric alpha-stable distribution centered on the beam axis. This results in two parameters, α and γ, that completely describe shape of the distribution. In addition, the total dose deposited on each slice is calculated. The alpha-stable parameters are plotted as function of the depth in-medium, providing a representation of dose deposition along the pencil beam. We observed that these graphs are isometric through a scaling of both abscissa and ordinate map the curves. Results: Using interpolation of the scaling factors of two source curves representative of different beam energies, we predicted the parameters of a third curve at an intermediate energy. The errors are quantified by the maximal difference and provide a fit better than previous methods. The maximal energy difference between the source curves generating identical curves was 21.14MeV. Conclusion: We have introduced a novel method to parameterize the in-phantom properties of pencil beam proton dose depositions. For the case of the Knoxville IBA system, no more than nine pencil beams have to be fully characterized.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

A Comparative Study of Machine Learning Algorithms for Industry-Specific Freight Generation Model

According to Bureau of Transportation Statistics, the U.S. transportation system handled 14,329 million ton-miles of freight per day in 2020. Understanding the generation of these freight shipments is crucial for transportation researchers, planners, and policymakers to design and plan for a more efficient and connected freight transportation system. Traditionally, the freight generation modeling has been based on Ordinary Least Square (OLS) regression, although more advanced Machine Learning (ML) algorithms have been evaluated and proven to have excellent performance in various transportation applications in recent years. Furthermore, one modeling approach applied for one industry might not always be applicable for another as their freight generation logics can be quite different. The objective of this study is to apply and evaluate alternative ML algorithms in the estimation of freight generation for each of 45 industry types. Seven alternative ML algorithms, along with the base OLS regression, were evaluated and compared. In addition, the study considered different combinations of variables in both the original and logarithmic form as well as hyperparameters of those ML algorithms in the model selection for each industry type. The results showed statistically significant improvements in the root mean square error reduction by the alternative ML algorithms over the OLS for over 80% of cases. The study suggests utilizing the alternative ML algorithms can reduce the root mean square error by about 30%, depending on industry types.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

High-efficiency oxygen reduction to hydrogen peroxide catalysed by oxidized carbon materials

Hydrogen peroxide (H 2 O 2 ) is a valuable chemical with a wide range of applications, but the current industrial synthesis of H 2 O 2 involves an energy-intensive anthraquinone process. The electrochemical synthesis of H 2 O 2 from oxygen reduction offers an alternative route for on-site applications; the efficiency of this process depends greatly on identifying cost-effective catalysts with high activity and selectivity. Here, we demonstrate a facile and general approach to catalyst development via the surface oxidation of abundant carbon materials to significantly enhance both the activity and selectivity (~90%) for H 2 O 2 production by electrochemical oxygen reduction. We find that both the activity and selectivity are positively correlated with the oxygen content of the catalysts. In conclusion, the density functional theory calculations demonstrate that the carbon atoms adjacent to several oxygen functional groups (–COOH and C–O–C) are the active sites for oxygen reduction reaction via the two-electron pathway, which are further supported by a series of control experiments.

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

Alternative Vector PWM for CSI Common-Mode Voltage Reduction During Voltage-Boost Operation with Low Modulation Index

This paper proposes a new pulse-width modulation (PWM) scheme named alternative vector PWM (AVM) algorithm that reduces the common-mode voltage (vCM) generated by a 3-phase current source inverter (CSI) during operation within a portion of its voltage-boost regime when the CSI’s modulation index is below 1/3–√(=0.5774). Three different active current vector pairs (one conventional pair with adjacent active current vectors and two proposed pairs with non-adjacent active current vectors) are used to reduce vCM based on the CSI’s output voltage conditions. Experimental results confirm significant reductions in major vCM spectral components by up to approx. 85% between the 3rd harmonic of the fundamental frequency and the CSI’s PWM frequency, validating the advantages of the proposed AVM algorithm over the conventional PWM.

42 ENGINEERING↗
DOE OSTI2013

Molecular Mechanism of Microbial Technetium Reduction Final Report

Microbial Tc(VII) reduction is an attractive alternative strategy for bioremediation of technetium-contaminated subsurface environments. Traditional ex situ remediation processes (e.g., adsorption or ion exchange) are often limited by poor extraction efficiency, inhibition by competing ions and production of large volumes of produced waste. Microbial Tc(VII) reduction provides an attractive alternative in situ remediation strategy since the reduced end-product Tc(IV) precipitates as TcO2, a highly insoluble hydrous oxide. Despite its potential benefits, the molecular mechanism of microbial Tc(VII) reduction remains poorly understood. The main goal of the proposed DOENABIR research project is to determine the molecular mechanism of microbial Tc(VII) reduction. Random mutagenesis studies in our lab have resulted in generation of a set of six Tc(VII) reduction-deficient mutants of Shewanella oneidensis. The anaerobic respiratory deficiencies of each Tc(VII) reduction-deficient mutant was determined by anaerobic growth on various combinations of three electron donors and 14 terminal electron acceptors. Results indicated that the electron transport pathways to Tc(VII3 -, Mn(III) and U(VI) share common structural or regulatory components. In addition, we have recently found that wild-type Shewanella are also able to reduce Tc(IV) as electron acceptor, producing Tc(III) as an end-product. The recent genome sequencing of a variety of technetium-reducing bacteria and the anticipated release of several additional genome sequences in the coming year, provides us with an unprecedented opportunity to determine the mechanism of microbial technetium reduction across species and genus lines.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Characterization of Virgin, Re-used, and Oxygen-reduced Copper Powders processed by the Plasma Spheroidization Process

We report that fabrication of parts with high mechanical properties heavily depend on the quality of powder deployed in the fabrication process. Copper powder in three different powder types were spheroidized using radio-frequency inductively coupled plasma (ICP) spheroidization process (TekSphero-15 system). The characterized powders include virgin powder as purchased from the powder manufacturer, powder used in electron beam powder bed fusion (EB-PBF) process, and reconditioned powder, which was used powder that underwent an oxygen-reduction treatment. The goal of spheroidizing these powder types was to evaluate the change in powder morphology, the possibility of enhancing the powder properties back to their as-received conditions, and assess oxygen reduction of the powder lots given their initial oxygen contents. Also, to investigate the impact of re-spheroidization on powder properties, the second round of spheroidization was performed on the already used-spheroidized powder. The impact of powder type on powder sphericity and particle size distribution was evaluated using the image analysis of scanning electron microscope (SEM) micrographs and laser diffraction, respectively. The spheroidized powder showed higher sphericity and more uniform particle size distribution overall. Depending on the powder collection bin, second round of spheroidization affected the powder sphericity differently. The possibility of deploying the plasma spheroidization process as an alternative oxygen-reduction technique was also investigated through tracking the powders’ oxygen content using inert gas fusion method before and after the spheroidization. The plasma spheroidized powder showed less oxygen content than the hydrogen-treated powder. The second round of spheroidization caused no change in oxygen content. The correlation between oxygen-reduction and created cracks was discussed and compared between plasma spheroidization and hydrogen-treatment. The plasma spheroidization process created a powder with higher sphericity, uniform particle size, and less oxygen content.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗