Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “reduction”

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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Surprisingly big linker-dependence of activity and selectivity in CO 2 reduction by an iridium(I) pincer complex

In this work, we report the quantitative electroreduction of CO 2 to CO by a PNP-pincer iridium(I) complex bearing amino linkers in DMF/water. The activity and selectivity of the reduction greatly depend on the choice of linker within the ligand. The complex 3-N is far superior to the analogues with methylene and oxygen linkers, showing higher activity and better selectivity for CO 2 over proton reduction.

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

Characterization of the Alkali Metal Oxalates (MC2O4-) and their formation by CO2 reduction via the Alkali Metal Carbonites (MCO2-)

The reduction of carbon dioxide to oxalate has been studied by experimental Collisionally Induced Dissociation (CID) and vibrational characterization of the alkali metal oxalates, supplemented by theoretical electronic structure calculations. The critical step in the reductive process is the coordination of the heterocumulene CO2 to an alkali metal anion, forming a metal carbonite MCO2 ablt to subsequently add a second CO2 molecule. While the energetic demand for these reactions is generally low, we find that the degree of activation of CO2 in terms of charge transfer and transition state energies is the highest for lithium and systematically decreases down the group (M - Li - Cs).

Jestila, Joakim S.↗
DOE OSTI2017

A Preconditioned Low-Rank Projection Method with a Rank-Reduction Scheme for Stochastic Partial Differential Equations

Herein, we consider the numerical solution of large systems of linear equations obtained from the stochastic Galerkin formulation of stochastic partial differential equations. We propose an iterative algorithm that exploits the Kronecker product structure of the linear systems. The proposed algorithm efficiently approximates the solutions in low-rank tensor format. Using standard Krylov subspace methods for the data in tensor format is computationally prohibitive due to the rapid growth of tensor ranks during the iterations. To keep tensor ranks low over the entire iteration process, we devise a rank-reduction scheme that can be combined with the iterative algorithm. The proposed rank-reduction scheme identifies an important subspace in the stochastic domain and compresses tensors of high rank on-the-fly during the iterations. The proposed reduction scheme is a coarse-grid method in that the important subspace can be identified inexpensively in a coarse spatial grid setting. The efficiency of the present method is displayed by numerical experiments on benchmark problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

An error reduction algorithm to improve lidar turbulence estimates for wind energy

Abstract. Remote-sensing devices such as lidars are currently being investigated as alternatives to cup anemometers on meteorological towers for the measurement of wind speed and direction. Although lidars can measure mean wind speeds at heights spanning an entire turbine rotor disk and can be easily moved from one location to another, they measure different values of turbulence than an instrument on a tower. Current methods for improving lidar turbulence estimates include the use of analytical turbulence models and expensive scanning lidars. While these methods provide accurate results in a research setting, they cannot be easily applied to smaller, vertically profiling lidars in locations where high-resolution sonic anemometer data are not available. Thus, there is clearly a need for a turbulence error reduction model that is simpler and more easily applicable to lidars that are used in the wind energy industry. In this work, a new turbulence error reduction algorithm for lidars is described. The Lidar Turbulence Error Reduction Algorithm, L-TERRA, can be applied using only data from a stand-alone vertically profiling lidar and requires minimal training with meteorological tower data. The basis of L-TERRA is a series of physics-based corrections that are applied to the lidar data to mitigate errors from instrument noise, volume averaging, and variance contamination. These corrections are applied in conjunction with a trained machine-learning model to improve turbulence estimates from a vertically profiling WINDCUBE v2 lidar. The lessons learned from creating the L-TERRA model for a WINDCUBE v2 lidar can also be applied to other lidar devices. L-TERRA was tested on data from two sites in the Southern Plains region of the United States. The physics-based corrections in L-TERRA brought regression line slopes much closer to 1 at both sites and significantly reduced the sensitivity of lidar turbulence errors to atmospheric stability. The accuracy of machine-learning methods in L-TERRA was highly dependent on the input variables and training dataset used, suggesting that machine learning may not be the best technique for reducing lidar turbulence intensity (TI) error. Future work will include the use of a lidar simulator to better understand how different factors affect lidar turbulence error and to determine how these errors can be reduced using information from a stand-alone lidar.

17 WIND ENERGY↗
NASA NTRS2000

AST Critical Propulsion and Noise Reduction Technologies for Future Commercial Subsonic Engines: Separate-Flow Exhaust System Noise Reduction Concept Evaluation

This report describes the work performed by General Electric Aircraft Engines (GEAE) and Allison Engine Company (AEC) on NASA Contract NAS3-27720 AoI 14.3. The objective of this contract was to generate quality jet noise acoustic data for separate-flow nozzle models and to design and verify new jet-noise-reduction concepts over a range of simulated engine cycles and flight conditions. Five baseline axisymmetric separate-flow nozzle models having bypass ratios of five and eight with internal and external plugs and 11 different mixing-enhancer model nozzles (including chevrons, vortex-generator doublets, and a tongue mixer) were designed and tested in model scale. Using available core and fan nozzle hardware in various combinations, 28 GEAE/AEC separate-flow nozzle/mixing-enhancer configurations were acoustically evaluated in the NASA Glenn Research Center Aeroacoustic and Propulsion Laboratory. This report describes model nozzle features, facility and data acquisition/reduction procedures, the test matrix, and measured acoustic data analyses. A number of tested core and fan mixing enhancer devices and combinations of devices gave significant jet noise reduction relative to separate-flow baseline nozzles. Inward-flip and alternating-flip core chevrons combined with a straight-chevron fan nozzle exceeded the NASA stretch goal of 3 EPNdB jet noise reduction at typical sideline certification conditions.

Janardan, B. A.↗
DOE OSTI2019

Shape-Controlled CO 2 Electrochemical Reduction on Nanosized Pd Hydride Cubes and Octahedra

Electrochemical CO 2 reduction reaction (CO 2 RR) provides a potential pathway to mitigate challenges related to CO 2 emissions. Pd nanoparticles have shown interesting properties as CO 2 RR electrocatalysts, while how different facets of Pd affect its performance in CO 2 reduction to synthesis gas with controlled H 2 to CO ratios has not been studied. Herein, we synthesized nano-sized Pd cubes and octahedra particles dominated by Pd(100) and Pd(111) facets, respectively. Here, the Pd octahedra particles show higher CO selectivity (up to 95%) and better activity than Pd cubes and commercial particles. For both Pd octahedra and cubes, the ratio of H 2 /CO products was tunable between 1 and 2, a desirable ratio for methanol production and the Fischer-Tropsch processes. Further studies of Pd octahedra in a 25-cm 2 flow cell showed a total CO current of 5.47 A was achieved at a potential of 3.4 V, corresponding to a CO partial current density of 220 mA/cm -2 . In situ X-ray absorption spectroscopy studies showed that regardless of facet Pd transformed into Pd hydride (PdH) under reaction conditions. DFT calculations show that the reduced binding energies of CO and HOCO intermediates on PdH(111) are key parameters to the high current density and Faradaic efficiency in CO 2 to CO conversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Low temperature dry reforming of methane using Ru-Ni-Mg/ceria-zirconia catalysts: Effect of Ru loading and reduction temperature

Dry reforming catalysts, especially those with activity at moderate temperatures, have been intensely investigated to enhance the conversion of biogas. Here, Ru is evaluated as a promoter for Ni-Mg based catalysts. Catalysts based on 1.4 wt%Ni-1.0 wt%Mg-Ce 0.6 Zr 0.4 O 2 with Ru (0.02–0.32 wt%) were prepared using incipient wetness. The reducibility of the catalysts and conversions increased with increasing Ru content. Increases in conversions with increasing Ru loading was attributed to the additional active sites and synergistic effect between Ru and Ni, which weakened Ni-Mg interactions. Samples showed dry reforming activity at low temperatures (450–510 °C). Reaction rates and activation energies of higher loading Ru samples (1.4 wt%Ni-1.0 wt%Mg/Ce 0.6 Zr 0.4 O 2 with 0.16 and 0.32 wt%Ru) decreased when the reduction temperature was raised from 300 to 400 °C. A 20 h TOS study showed stable catalytic activity with minimal coke deposition. Furthermore, the results suggest that Ru is an alternative to Pt in promoting low temperature dry reforming of methane.

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

Influence of Pt-Metal Alloy Catalysts with Various Ionomers on Oxygen Reduction Reaction in Fuel Cell Application

Pt-M/C (M = Co, Ni, Mn, etc.) alloy catalysts exhibit superior oxygen reduction reaction (ORR) activity compared to pure Pt/C, leading to a high energy efficiency in hydrogen fuel cells. However, many Pt-M/C alloy catalysts were synthesized and evaluated at the lab scale in model test-bed systems like rotating disc electrodes, which don't always correlate to performance within a fuel cell system; there is a clear need to evaluate catalysts in electrodes that can be prepared at industrially relevant scales to evaluate how factors like ink formulation can greatly affect device-level of fuel cell performance. Herein, three commercial Pt-M/C alloy catalysts (two Pt-Co/C and one Pt-Ni/C) were comprehensively characterized by various techniques. The results show that the average particle sizes of the three catalysts are close to 5 nm; the atomic ratio of Pt/M is around 4; and the M was successfully embedded into Pt lattice, resulting in the positive shift of Pt 4f in XPS spectra and XRD patterns. These catalytic materials were incorporated into 9 different cathode catalyst layers (CCLs) with three kinds of ionomers (Nafion D2020, high oxygen permeability ionomer (HOPI), and Aquivion D79-25BS), and their performance in proton exchange membrane fuel cells (PEMFCs) were investigated. The results demonstrate that the Pt-Co/C catalysts possess a higher mass activity (MA) than Pt-Ni/C; the cathodes with Nafion ionomer provide the highest MA while electrodes with Aquivion ionomer showed the lowest activity, attributed to poor H+ conductivity resulting from suboptimal ionomer incorporation. Finally, these alloys were shown to exceed DOE targets for MA and H2/Air performance reported in the recent publications at beginning of life and after 90k cycle catalyst AST protocol. This study provides valuable performance benchmarks for these materials guiding future Pt-M/C catalyst design and material integration for heavy duty PEMFC applications.

08 HYDROGEN↗
DOE OSTI2022

Electrochemical CO2 Reduction over Metal-/Nitrogen-Doped Graphene Single-Atom Catalysts Modeled Using the Grand-Canonical Density Functional Theory

Renewably driven, electrochemical conversion of carbon dioxide into value-added products is expected to be a critical tool in global decarbonization. However, theoretical studies based on the computational hydrogen electrode largely ignore the nonlinear effects of the applied potential on the calculated results, leading to inaccurate predictions of catalytic behavior or mechanistic pathways. Here, we use grand canonical density functional theory (GC-DFT) to model electrochemical CO2 reduction (CO2R) over metal- and nitrogen-doped graphene catalysts (MNCs) and explicitly include the effects of the applied potential. We used GC-DFT to compute the CO2 to CO reaction intermediate energies at -0.3, -0.7, and -1.2 VSHE catalyzed by MNCs each doped with 1 of the 10 3d block metals coordinated by four pyridinic nitrogen atoms. Our results predict that Sc-, Ti-, Co-, Cu-, and Zn-N4Cs effectively catalyze CO2R at moderate to large reducing potentials (-0.7 to -1.2 VSHE). ZnN4C is a particularly promising electrocatalyst for CO2R to CO both at low and moderate applied potentials based on our thermodynamic analysis. Our findings also explain the observed pH independence of CO production over FeN4C and predict that the rate-determining step of CO2R over FeN4C is not *CO2- formation but rather *CO desorption. Additionally, the GC-DFT-computed density of states analysis illustrates how the electronic states of MNCs and adsorbates change non-uniformly with applied potential, resulting in a significantly increased *CO2- stability relative to other intermediates and demonstrating that the formation of the adsorbed *CO2- anion is critical to CO2R activation. This work demonstrates how GC-DFT paves the way for physically realistic and accurate theoretical simulations of reacting electrochemical systems.

CO2 reduction↗
DOE OSTI2019

Engineering Fe–Fe3C@Fe–N–C Active Sites and Hybrid Structures from Dual Metal–Organic Frameworks for Oxygen Reduction Reaction in H2–O2 Fuel Cell and Li–O2 Battery

Dual metal-organic frameworks (MOFs, i.e., MIL-100(Fe) and ZIF-8) are thermally converted into Fe-Fe3C-embedded Fe-N-codoped carbon as platinum group metal (PGM)-free oxygen reduction reaction (ORR) electrocatalysts. Pyrolysis enables imidazolate in ZIF-8 rearranged into highly N-doped carbon, while Fe from MIL-100(Fe) into N-ligated atomic sites concurrently with a few Fe-Fe3C nanoparticles. Upon precise control of MOF compositions, the optimal catalyst is highly active for the ORR in half-cells (0.88 V in base and 0.79 V versus RHE in acid in half-wave potential), a proton exchange membrane fuel cell (0.76 W cm(-2) in peak power density) and an aprotic Li-O-2 battery (8749 mAh g(-1) in discharge capacity), representing a state-of-the-art PGM-free ORR catalyst. In the material, amorphous carbon with partial graphitization ensures high active site exposure and fast charge transfer simultaneously. Macropores facilitate mass transport to the catalyst surface, followed by oxygen penetration in micropores to reach the infiltrated active sites. Further modeling simulations shed light on the true Fe-Fe3C contribution to the catalyst performance, suggesting Fe3C enhances oxygen affinity, while metallic Fe promotes *OH desorption as the rate-determining step at the nearby Fe-N-C sites. These findings demonstrate MOFs as model system for rational design of electrocatalyst for energy-based functional applications.

battery↗
DOE OSTI2016

Investigation of Oxygen Reduction Activity of Catalysts Derived from Co and Co/Zn Methyl-Imidazolate Frameworks in Proton Exchange Membrane Fuel Cells

We demonstrated that the oxygen reduction reaction (ORR) activity over the catalysts derived from pyrolyzed cobalt zeolitic imidazolate frameworks depends strongly on the imidazole ligand structure and cobalt content. The activity and durability of these catalysts were tested in the proton exchange membrane fuel cell for the first time. The membrane electrode assembly containing a catalyst derived from Co/Zn bimetallic ZIF at cathode achieved an open circuit voltage of 0.93 V, a current density of 28 mA cm-2 at 0.8 ViR-free and a peak power density of 374 mW cm-2.

electrocatalysts↗