Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “ALTERNATE REDUCTANT”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 361 records · Page 20

Direct insights into the role of epoxy groups on cobalt sites for acidic H 2 O 2 production

Hydrogen peroxide produced by electrochemical oxygen reduction reaction provides a potentially cost effective and energy efficient alternative to the industrial anthraquinone process. In this study, we demonstrate that by modulating the oxygen functional groups near the atomically dispersed cobalt sites with proper electrochemical/chemical treatments, a highly active and selective oxygen reduction process for hydrogen peroxide production can be obtained in acidic electrolyte, showing a negligible amount of onset overpotential and nearly 100% selectivity within a wide range of applied potentials. Combined spectroscopic results reveal that the exceptionally enhanced performance of hydrogen peroxide generation originates from the presence of epoxy groups near the Co–N 4 centers, which has resulted in the modification of the electronic structure of the cobalt atoms. Computational modeling demonstrates these electronically modified cobalt atoms will enhance the hydrogen peroxide productivity during oxygen reduction reaction in acid, providing insights into the design of electroactive materials for effective peroxide production.<

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Porous Carbon-Hosted Atomically Dispersed Iron-Nitrogen Moiety as Enhanced Electrocatalysts for Oxygen Reduction Reaction in a Wide Range of pH

As one of the alternatives to replace precious metal catalysts, transition-metal–nitrogen–carbon (M–N–C) electrocatalysts have attracted great research interest due to their low cost and good catalytic activities. Despite nanostructured M–N–C catalysts can achieve good electrochemical perfor-mances, they are vulnerable to aggregation and insufficient catalytic sites upon continuous catalytic reaction. In this work, metal–organic frameworks derived porous single-atom electrocatalysts (SAEs) were successfully prepared by simple pyrolysis procedure without any further posttreatment. Combining the X-ray absorption near-edge spectroscopy and electrochemical measure-ments, the SAEs have been identified with superior oxygen reduction reaction (ORR) activity and stability compared with Pt/C catalysts in alkaline condition. More impressively, the SAEs also show excellent ORR electrocatalytic perfor-mance in both acid and neutral media. This study of nonprecious catalysts provides new insights on nanoengineering catalytically active sites and porous structures for nonprecious metal ORR catalysis in a wide range of pH.

Environmental Molecular Sciences Laboratory↗

Cu-Doped Iron Oxide for the Efficient Electrocatalytic Nitrate Reduction Reaction

The electrochemical nitrate reduction reaction (NO 3 RR) is a promising alternative synthetic route for sustainable ammonia (NH 3 ) production, because it not only eliminates nitrate (NO 3 – ) from water but also produces NH 3 under mild operating conditions. However, owing to the complicated eight-electron reaction and the competition from the hydrogen evolution reaction, developing catalysts with high activities and Faradaic efficiencies (FEs) is highly imperative to improve the reaction performance. In this study, Cu-doped Fe 3 O 4 flakes are fabricated and demonstrated to be excellent catalysts for electrochemical conversion of NO 3 – to NH 3 , with a maximum FE of ~100% and an NH 3 yield of 179.55 ± 16.37 mg h –1 mg cat –1 at –0.6 V vs RHE. Here, theoretical calculations reveal that doping the catalyst surface with Cu results in a more thermodynamically facile reaction. These results highlight the feasibility of promoting the NO 3 RR activity using heteroatom doping strategies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Permanent Nanobubbles in Water: Liquefied Hollow Carbon Spheres Break the Limiting Diffusion Current of Oxygen Reduction Reaction

Porous liquids have traditionally been designed with sterically hindered solvents. Alternatively, recent efforts rely on dispersing microporous frameworks in simpler solvents like water. Here we report a unique strategy to construct macroporous water by selectively incorporating hydrophilicity on the surfaces of hydrophobic hollow carbon spheres (HCS). Specifically, we show that the stable dispersion surface ionized HCS in water while retaining the inherent porosity. The electrocatalytic conversion of small gas molecules in aqueous electrolytes is limited by the concentration and diffusion rates of gas molecules in water. In this case, macroporous water exhibited 6 times gas uptake compared to nonporous (pure) water. Furthermore, by leveraging the high gas capacity and enhanced diffusion kinetics, the limiting diffusion current of oxygen reduction reaction (ORR) in macroporous water is 2 times that in nonporous water, offering promising prospects for sustainable energy conversion technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Data-Efficient Strategies for Probabilistic Voltage Envelopes under Network Contingencies

This work presents an efficient data-driven method to construct probabilistic voltage envelopes (PVE) using power flow learning in grids with network contingencies. First, a network-aware Gaussian process (GP) termed Vertex-Degree Kernel (VDK-GP), developed in prior work, is used to estimate voltage–power functions for a few network configurations. The paper introduces a novel multi-task vertex degree kernel (MT-VDK) that amalgamates the learned VDK-GPs to determine power flows for unseen networks, with a significant reduction in the computational complexity and hyperparameter requirements compared to alternate approaches. Simulations on the IEEE 30-Bus network demonstrate the retention and transfer of power flow knowledge in both N-1 and N-2 contingency scenarios. The MT-VDK-GP approach achieves over 50 % reduction in mean prediction error for novel N-1 contingency network configurations in low training data regimes (50–250 samples) over VDK-GP. Additionally, MT-VDK-GP outperforms a hyper-parameter based transfer learning approach in over 75 % of N-2 contingency network structures, even without historical N-2 outage data. Furthermore, the proposed method demonstrates the ability to achieve PVEs using sixteen times fewer power flow solutions compared to Monte-Carlo sampling-based methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Implications of Sustainability for the United States Light-Duty Transportation Sector

Climate change is a problem that must be solved. The primary cause of this problem is burning of fossil fuels to generate energy. A dramatic reduction in carbon emissions must happen soon, and a significant fraction of this reduction must come from the transportation sector. This paper reviews existing literature to assess the consensus of the scientific and engineering communities concerning the potential for the United States' light-duty transportation sector to meet a goal of 80 percent reduction in vehicle emissions and examine what it will take to meet this target. It is unlikely that reducing energy consumption in just vehicles with gasoline-based internal combustion drivetrains will be sufficient to meet GHG emission-reduction targets. This paper explores what additional benefits are possible through the adoption of alternative energy sources, looking at three possible on-vehicle energy carriers: carbon-based fuels, hydrogen, and batteries. potential for the United States' light-duty transportation sector to meet a goal of 80 percent reduction in vehicle emissions and examine what it will take to meet this target. It is unlikely that reducing energy consumption in just vehicles with gasoline-based internal combustion drivetrains will be sufficient to meet GHG emission-reduction targets. This paper explores what additional benefits are possible through the adoption of alternative energy sources, looking at three possible on-vehicle energy carriers: carbon-based fuels, hydrogen, and batteries.

33 ADVANCED PROPULSION SYSTEMS↗

Implementation of a High-Speed FPGA and DSP Based FFT Processor for Improving Strain Demodulation Performance in a Fiber-Optic-Based Sensing System

NASA's Aviation Safety and Security Program is pursuing research in on-board Structural Health Management (SHM) technologies for purposes of reducing or eliminating aircraft accidents due to system and component failures. Under this program, NASA Langley Research Center (LaRC) is developing a strain-based structural health-monitoring concept that incorporates a fiber optic-based measuring system for acquiring strain values. This fiber optic-based measuring system provides for the distribution of thousands of strain sensors embedded in a network of fiber optic cables. The resolution of strain value at each discrete sensor point requires a computationally demanding data reduction software process that, when hosted on a conventional processor, is not suitable for near real-time measurement. This report describes the development and integration of an alternative computing environment using dedicated computing hardware for performing the data reduction. Performance comparison between the existing and the hardware-based system is presented.

Farley, Douglas L.↗

The Triple Catalytic Action of Tertiary Nitrogen Catalysts in Recyclable Epoxy-Anhydride Thermosets

The thermosetting polymer matrix in fiber reinforced composites is an important component for energy related applications, such as the lightweighting of vehicles or their use in wind and waterpower turbine blades, due to their ability to provide superior adhesion, stiffness, and applicability to a wide range of manufacturing processes. Despite these benefits, today's thermosets are widely considered to be unrecyclable; thus, there is a large interest in redesigning these materials to be inherently recyclable so that energy intensive production of fibers and monomers can be circumvented, bolstering composite manufacture supply chains. Polyester covalent adaptable networks (PECANs) are one such promising alternative to the incumbent, nonrecyclable epoxy-amine thermosets. PECANs can be formed from the ring-opening co-polymerization (ROCOP) of epoxy-anhydride monomer mixtures and subsequent curing at mild temperatures to exhibit similar performance to conventional epoxies while also possessing unique dynamic chemistries along the ester-hydroxyl backbone that are capable of transesterification and thus reprocessability. While significant advancements have been made in formulating these materials for improved mechanical properties or optimizing solvolysis and reprocessing strategies, less attention has been placed on the impact of the residing amine catalyst used to generate the polyester network. In this work, we evaluated the triple-catalytic efficacy of 12 tertiary amines that act as a curing (bulk ROCOP), a transesterification (internal bond exchange), and a deconstruction (methanolysis) catalyst for PECAN thermosets. Specifically, we first distinguish between chain-growth and step-growth polymerization mechanisms for epoxy-amine and epoxy-anhydride mechanisms. We also utilized density functional theory (DFT) to estimate the basicity (pKb) of each catalyst. Of the tested catalysts, the ROCOP of the studied PECAN network can be completed between 95 and 247 min (at 80 degrees C), with variable gelation phenomena. Additionally, the stress relaxation (transesterification metric) efficiency of the tested PECAN networks with alternative embedded catalysts ranged from 95% to 15% reduction in stress after 5 h at 200 degrees C, and the depolymerization efficacy ranged from 2.5% to 9.8% deconstruction after 36 h at 130 degrees C. Overall, the nitrogen-based moieties were demonstrated to influence polymerization kinetics, catalyze the dynamic transesterification exchange mechanism, and aid in the solvolysis of the thermosets at end-of-life.

36 MATERIALS SCIENCE↗

Incremental k-core decomposition: Algorithms and evaluation

A k-core of a graph is a maximal connected subgraph in which every vertex is connected to at least k vertices in the subgraph. k-core decomposition is often used in large-scale network analysis, such as community detection, protein function prediction, visualization, and solving NP-hard problems on real networks efficiently, like maximal clique finding. In many real-world applications, networks change over time. As a result, it is essential to develop efficient incremental algorithms for dynamic graph data. In this paper, we propose a suite of incremental k-core decomposition algorithms for dynamic graph data. These algorithms locate a small subgraph that is guaranteed to contain the list of vertices whose maximum k-core values have changed and efficiently process this subgraph to update the k-core decomposition. We present incremental algorithms for both insertion and deletion operations, and propose auxiliary vertex state maintenance techniques that can further accelerate these operations. Our results show a significant reduction in runtime compared to non-incremental alternatives. We illustrate the efficiency of our algorithms on different types of real and synthetic graphs, at varying scales. Furthermore, for a graph of 16 million vertices, we observe relative throughputs reaching a million times, relative to the non-incremental algorithms.

97 MATHEMATICS AND COMPUTING↗

Technoeconomic assessment of hydrogen cogeneration via high temperature steam electrolysis with a light-water reactor

Increased electricity production from renewable energy resources, coupled with low natural gas (NG) prices, has caused existing light-water reactors (LWRs) to experience diminishing returns from the electricity market. This reduction in revenue is forcing LWRs to consider alternative revenue streams, such as introduction hydrogen production or desalination, to remain profitable. This paper performs a technoeconomic assessment (TEA) regarding the viability of retrofitting existing pressurized-water reactors (PWRs) to produce green hydrogen (H 2 ) via high-temperature steam electrolysis (HTSE). Such an integration would allow nuclear facilities to expand into additional markets that may be more profitable in the long term and eliminate CO 2 emissions from the hydrogen production process. Here, to accommodate such an integration, a detailed single market levelized cost of hydrogen (LCOH) and multimarket analyses were conducted of HTSE process operation, requirements, costing, and flexibility. Alongside this costing analysis, market analyses were conducted on the electric and hydrogen markets in the PJM interconnect. Utilizing a novel stochastic, dispatch optimization approach results suggest that a positive gain is achievable, and by operating in multiple markets, the nuclear facility can avoid the sale of electricity during times of low electricity market pricing, while maintaining the ability to capitalize on the high electricity market pricing. It should be noted that the analysis conducted is a differential cash flow analysis and, as such, does not present profit levels. LCOH analysis results demonstrate the potential exists to produce hydrogen at a cost as low as $1.20/kg. This price is lower than traditional steam methane reforming (SMR) allowing nuclear based hydrogen production to disrupt the existing hydrogen production market.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Tailoring activity of iron phthalocyanine by edge-nitrogen sites induced electronic delocalization

Fe-N-C catalysts have been recognized as the most satisfactory candidates alternatively to Pt-based catalysts for oxygen reduction reaction (ORR). However, fine-tailoring of their intrinsic ORR catalytic activity still remains a great challenge due to the inferior accessibility and intrinsic activity of FeN x moieties. Herein, one order of magnitude activity enhancement of pristine Fe-N-C through cooperating with nitrogen-doped carbon micro-flower is achieved. The axial coordination effect between Fe active center and nitrogen atoms in support can break the electronic distribution symmetry of FeN x moieties and induce the electron delocalization on Fe active center and the electron localization on N, respectively, which favor the adsorption behavior of *OH intermediate. As a result, the catalyst exhibits a remarkable half-wave potential of 0.9 V and a high kinetic current density of 74.04 mA cm -2 at 0.85 V. In addition, when utilized as a cathode catalyst of liquid Zn-air batteries (ZABs), it possesses excellent electrochemical performance, for example, a high open circuit voltage (OCV) and peak power density of 1.59 V and 170.09 mW cm -2 , respectively. In conclusion, this work provides a new understanding into the activity enhancement mechanism of Fe-N-C catalysts, and inspires electronic delocalization of active sites for adjusting catalytic activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Evolving Role of Radiation Therapy in the Management of Malignant Melanoma

The incidence of melanoma is rising in the United States, leading to an estimated 68,720 new diagnoses and 8,650 deaths annually. The natural history involves metastases to lymph nodes, lung, liver, brain, and often to other sites. Primary treatment for melanoma is surgical excision of the primary tumor and affected lymph nodes. The role of adjuvant or definitive radiation therapy in the treatment of melanoma remains controversial, because melanoma has traditionally been viewed as a prototypical radioresistant cancer. However, recent studies suggest that under certain clinical circumstances, there may be a significant role for radiation therapy in melanoma treatment. Stereotactic radiosurgery for brain metastases has shown effective local control. High dose per fraction radiation therapy has been associated with a lower rate of locoregional recurrence of sinonasal melanoma. Plaque brachytherapy has evolved into a promising alternative to enucleation at the expense of moderate reduction in visual acuity. Adjuvant radiation therapy following lymphadenectomy in node-positive melanoma prevents local and regional recurrence. The newer clinical data along with emerging radiobiological data indicate that radiotherapy is likely to play a greater role in melanoma management and should be considered as a treatment option.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Quantitative evaluation of common cause failures in high safety-significant safety-related digital instrumentation and control systems in nuclear power plants

Digital instrumentation and control (DI&C) systems at nuclear power plants (NPPs) have many advantages over analog systems. They are proven to be more reliable, cheaper, and easier to maintain given obsolescence of analog components. However, they also pose new engineering and technical challenges, such as possibility of common cause failures (CCFs) unique to digital systems. Here this paper proposes a Platform for Risk Assessment of DI&C (PRADIC) that is developed by Idaho National Laboratory (INL). A methodology for evaluation of software CCFs in high safety-significant safety-related DI&C systems of NPPs was developed as part of the framework. The framework integrates three stages of a typical risk assessment—qualitative hazard analysis and quantitative reliability and consequence analyses. The quantified risks compared with respective acceptance criteria provide valuable insights for system architecture alternatives allowing design optimization in terms of risk reduction and cost savings. A comprehensive case study performed to demonstrate the framework's capabilities is documented here in this paper. Results show that the PRADIC is a powerful tool capable to identify potential digital-based CCFs, estimate their probabilities, and evaluate their impacts on system and plant safety.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Coupling High-Throughput Experiments and Regression Algorithms to Optimize PGM-Free ORR Electrocatalyst Synthesis

Over the past decades, significant improvement has been achieved in the performance of platinum group metal-free (PGM-free) materials as an alternative to Pt-based electrocatalysts for oxygen reduction reaction (ORR). However, further progress in ORR activity requires evaluation of precursors and synthesis approaches. In response to this challenge, we generated a first of its kind experimental data set of 36 samples using high-throughput synthesis and activity measurements. Several control parameters (e.g., Fe precursor identity, the precursor content, and pyrolysis temperature) were varied. We then developed several state-of-the-art machine learning (ML) based regression models to predict ORR activity, dependent on selected synthesis variables. Through an iterative algorithm, higher prediction accuracy (smaller root-mean-square error) was achieved. We identified that gradient boosting regression (GBR) and support vector regression (SVR), among several methods, work best for this data set. Aided by our ML-based surrogate models, we decided to alter catalyst synthesis conditions, which resulted in a 36% increase in measured ORR activity in comparison to the maximum ORR mass activity value of 21.9 A/g catalyst in the original data set. Overall, this combined experiment and machine learning approach represents a promising path forward toward developing highly efficient next-generation ORR electrocatalysts and, more generally, functional materials.

25 ENERGY STORAGE↗

2D and 3D Characterization of PtNi Nanowire Electrode Composition and Structure

Extended surface Pt or Pt-M (M = Ni or Co) catalysts are a viable alternative to supported nanoparticle catalysts for the oxygen reduction reaction (ORR) at the cathode in proton exchange membrane fuel cells (PEMFCs). The activity and durability of these catalysts in membrane electrode assemblies (MEAs) are greatly dependent on the surface and bulk properties of the catalyst material, integration with ionomer, and the three-dimensional structure of the electrode, necessitating extensive characterization of the catalyst in the electrode at multiple scales. In this work, extended surface PtNi nanowire-based electrocatalysts derived by spontaneous galvanic displacement, and post-treated to obtain high specific and mass activities, are characterized by X-ray spectroscopies to assess catalyst composition and to determine the extent of Pt-Ni alloying. Transmission X-ray microscopy (TXM) is used to generate two- and three-dimensional images of catalyst layers with varied compositions within the electrode to show the distribution of nanowires and to study Ni dissolution and redeposition within the electrode. These techniques are complemented by electron microscopy, which is used to confirm leaching of nickel from the nanowires and its redeposition within the electrode. This process is shown to have detrimental effect on the MEA performance, which can be at least in part recovered by soaking electrodes in acid. The combination of these techniques provides unprecedented detail of the evolution of the nanowire-based extended surface catalyst and electrode structure guiding the targeted design of high performance electrodes based on this class of materials.

36 MATERIALS SCIENCE↗

Unravelling core microbial metabolisms in the hypersaline microbial mats of Shark Bay using high-throughput metagenomics

Modern microbial mats are potential analogues of some of Earth’s earliest ecosystems. Excellent examples can be found in Shark Bay, Australia, with mats of various morphologies. To further our understanding of the functional genetic potential of these complex microbial ecosystems, we conducted for the first time shotgun metagenomic analyses. We assembled metagenomic nextgeneration sequencing data to classify the taxonomic and metabolic potential across diverse morphologies of marine mats in Shark Bay. The microbial community across taxonomic classifications using protein-coding and small subunit rRNA genes directly extracted from the metagenomes suggests that three phyla Proteobacteria, Cyanobacteria and Bacteriodetes dominate all marine mats. However, the microbial community structure between Shark Bay and Highbourne Cay (Bahamas) marine systems appears to be distinct from each other. The metabolic potential (based on SEED subsystem classifications) of the Shark Bay and Highbourne Cay microbial communities were also distinct. Shark Bay metagenomes have a metabolic pathway profile consisting of both heterotrophic and photosynthetic pathways, whereas Highbourne Cay appears to be dominated almost exclusively by photosynthetic pathways. Alternative non-rubisco-based carbon metabolism including reductive TCA cycle and 3-hydroxypropionate/4-hydroxybutyrate pathways is highly represented in Shark Bay metagenomes while not represented in Highbourne Cay microbial mats or any other mat forming ecosystems investigated to date. Potentially novel aspects of nitrogen cycling were also observed, as well as putative heavy metal cycling (arsenic, mercury, copper and cadmium). Finally, archaea are highly represented in Shark Bay and may have critical roles in overall ecosystem function in these modern microbial mats.

Ruvindy, Rendy↗

Development of a high-fidelity multi-physics coupling between MCNP6.2 and CTF4.0 for VVER applications

Ensuring system safety in the design, licensing, and operation phases is a priority in the nuclear industry. Performing extensive, full-scale reactor safety experiments is often prohibitive due to the large associated costs. Computational simulations offer an alternative safety analysis method, typically with significant cost reductions. Recent high-level developments in technology and increased availability of computational resources have allowed the development of high-fidelity, high-resolution multi-physics coupled codes. Such developments may be used to generate reference models for deterministic core calculations. Under this framework, the high-fidelity continuous energy Monte Carlo-based neutron transport code MCNP6.2 was coupled externally with the state-of-the-art thermal-hydraulics subchannel code, CTF4.0 for VVER (Water-Water Energetic Reactor) applications. A VVER-1000 fuel assembly model was used to demonstrate the capability of the coupled code. The converged coupled solution is compared to initial results, consisting of the first MCNP evaluation and first CTF evaluation after initialization. The VVER-1000 type assembly results are compared to other evaluations of the same assembly model. The findings indicate good agreement with expectations and reference cases, where available. The initial results of the coupled MCNP6.2/CTF4.0 calculations at the assembly level for steady-state calculations are presented in this study, which may support future work toward high-fidelity coupled full-core modeling capabilities. The multi-physics model may be further improved, enhanced, and expanded for both cycle depletion and transient applications. Such a multi-physics system will also be applicable to the VVER-1200 and other triangular lattice designs and support their deployment and operation safely and economically. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗