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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Rechargeable Aluminum-Ion Batteries Based on an Open-Tunnel Framework

Rechargeable batteries based on an abundant metal such as aluminum with a three-electron transfer per atom are promising for large-scale electrochemical energy storage. Aluminum can be handled in air, thus offering superior safety, easy fabrication, and low cost. But, the development of Al-ion batteries has been challenging due to the difficulties in identifying suitable cathode materials. This study presents the use of a highly open framework Mo 2.5 + y VO 9 + z as a cathode for Al-ion batteries. The open-tunnel oxide allows a facile diffusion of the guest species and provides sufficient redox centers to help redistribute the charge within the local host lattice during the multivalent-ion insertion, thus leading to good rate capability with a specific capacity among the highest reported in the literature for Al-based batteries. Our study also presents the use of Mo 2.5 + y VO 9 + z as a model host to develop a novel ultrafast technique for chemical insertion of Al ions into host structures. The microwave-assisted method employing diethylene glycol and aluminum diacetate (Al(OH)(C 2 H 3 O 2 ) 2 ) can be performed in air in as little as 30 min, which is far superior to the traditional chemical insertion techniques involving moisture-sensitive organometallic reagents. The Al-inserted Al x Mo 2.5 + y VO 9 + z obtained by the microwave-assisted chemical insertion can be used in Al-based rechargeable batteries.

25 ENERGY STORAGE↗
DOE OSTI2015

A frozen Gaussian approximation-based multi-level particle swarm optimization for seismic inversion

In this paper, we propose a frozen Gaussian approximation (FGA)-based multi-level particle swarm optimization (MLPSO) method for seismic inversion of high-frequency wave data. The method addresses two challenges in it: First, the optimization problem is highly non-convex, which makes hard for gradient-based methods to reach global minima. This is tackled by MLPSO which can escape from undesired local minima. Second, the character of high-frequency of seismic waves requires a large number of grid points in direct computational methods, and thus renders an extremely high computational demand on the simulation of each sample in MLPSO. We overcome this difficulty by three steps: First, we use FGA to compute high-frequency wave propagation based on asymptotic analysis on phase plane; Then we design a constrained full waveform inversion problem to prevent the optimization search getting into regions of velocity where FGA is not accurate; Last, we solve the constrained optimization problem by MLPSO that employs FGA solvers with different fidelity. The performance of the proposed method is demonstrated by a two-dimensional full-waveform inversion example of the smoothed Marmousi model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Manganese-Based Molecular Electrocatalysts for Oxidation of Hydrogen

Oxidation of H2 (1 atm) is catalyzed by the manganese electrocatalysts [(P2N2)MnI(CO)(bppm)]+ and [(PNP)MnI(CO)(bppm)]+ (P2N2= 1,5-dibenzyl-3,7-diphenyl-1,5-diaza-3,7-diphosphacyclooctane; PNP = (Ph2PCH2)2NMe); bppm = (PArF2)2CH2, and ArF = 3,5-(CF3)2C6H3). In fluorobenzene solvent using 2,6-lutidine as the exogeneous base, the turnover frequency for [(P2N2)MnI(CO)(bppm)]+ is 3.5 s-1 with an estimated overpotential of 590 mV. For [(PNP)MnI(CO)(bppm)], in fluorobenzene solvent using N-methylpyrrolidine as the exogeneous base, the turnover frequency is 1.4 s-1 with an estimated overpotential of 700 mV. Density functional theory calculations suggest that the slow step in the catalytic cycle is proton transfer from the oxidized 17-electron manganese hydride, e.g., [(P2N2)MnIIH(CO)(bppm)]+ to the pendant amine. The computed activation barrier for intramolecular proton transfer from the metal to the pendant amine is 20.4 kcal/mol in [(P2N2)MnIIH(CO)(bppm)]+ and 21.3 kcal/mol in [(PNP)MnI(CO)(bppm)]. The high barrier appears to result from both the unfavorability of metal-to-nitrogen proton transfer (thermodynamically uphill by 6.6 pKa units, 9 kcal/mol), as well as the relatively long manganese-nitrogen separation in the MnIIH complexes.

Hydrogen, oxidation, electrocatalysis, proton tran↗
DOE OSTI2021

Lithium-ion battery physics and statistics-based state of health model

A pseudo-2d model using COMSOL Multiphysics® software is developed to simulate performance and performance degradation of Li-ion batteries consisting of layered and olivine cathodes with graphite anode when subjected to peak shaving grid service. Multiple degradation pathways are considered, including solid electrolyte interphase (SEI) formation and breakdown at the anode, cathode dissolution and its synergistic effect on SEI formation at the anode. The model is validated by simulating commercial cylindrical cell performance. A global model is developed to simulate performance across all chemistries, along with individual chemistry models using global model parameters as initial values. There is good agreement between these models for various optimization parameters such as SEI equilibrium potential, cathode dissolution exchange current density, solvent diffusivity in the SEI and SEI ionic conductivity. To circumvent time constraints related to the COMSOL model, a 0d global model is developed which fits data well and provides more clarity on differences in cathode dissolution exchange current density. Again, good agreement for various optimization parameters is obtained among the COMSOL global & individual chemistry models and the 0-d model. The lessons learned from the physics-based model is used to develop a top down statistics-based model using current, voltage and anode volumetric change per mole lithium intercalated, along with their interactions as degradation predictors. This model predicts out of sample degradation for multiple grid services and electric vehicle drive cycle with high accuracy and provides the pathway to develop an efficient battery management system combining machine learning and findings from physics-based computationally intensive algorithms.

Crawford, Aladsair J.↗
DOE OSTI2021

Unveiling the Stabilities of Nickel–Based Layered Oxide Cathodes at an Identical Degree of Delithiation in Lithium–Based Batteries

Bulk, surface, and interfacial instabilities that impact the cycle and thermal performances are the major challenges with high-energy-density LiNi 1–x–y Mn x Co y O 2 (NMC) cathodes with high nickel contents. It is generally believed that the instabilities and performance losses become exponentially aggravated as the nickel content increases. Disparate from this prevailing belief, it is herein demonstrated that NMC cathodes with higher Ni contents may imply better overall stability than “lower-Ni” cathodes under an identical degree of delithiation (charging) conditions. With two representative cathodes, LiNi 0.8 Mn 0.1 Co 0.1 O 2 and LiNiO 2 , a systematic investigation into their stabilities with control of the degree of delithiation is presented. Electrochemical tests indicate that LiNiO 2 displays better cyclability than LiNi 0.8 Mn 0.1 Co 0.1 O 2 at the same delithiation state. Comprehensive structural and interphase investigations unveil that the inferior cyclability of LiNi 0.8 Mn 0.1 Co 0.1 O 2 predominantly results from aggravated parasitic reactions, and the interphase stability may be more critical than lattice stability in dictating cyclability. Also, LiNiO 2 delivers similar or better thermal behavior than LiNi 0.8 Mn 0.1 Co 0.1 O 2 . Finally, the findings demonstrate a strong correlation of the stability of NMC cathodes to the degree of delithiation state rather than the Ni content itself, highlighting the importance of reassessing the true implications of Ni content and structural and interphasial tuning on the stabilities of NMC cathodes.

25 ENERGY STORAGE↗
DOE OSTI2015

Lattice Boltzmann-Based Approaches for Pore-Scale Reactive Transport

Here an important geoscience and environmental applications such as geologic carbon storage, environmental remediation, and unconventional oil and gas recovery are best understood in the context of reactive flow and multicomponent transport in the subsurface environment. The coupling of chemical and microbiological reactions with hydrological and mechanical processes can lead to complex behaviors across an enormous range of spatial and temporal scales. These coupled responses are also strongly influenced by the heterogeneity and anisotropy of the geologic formations. Reactive transport processes can change the pore morphology at the pore scale, thereby leading to nonlinear interactions with advective and diffusive transport, which can strongly influence larger-scale properties such as permeability and dispersion.

58 GEOSCIENCES↗
DOE OSTI2017

Hierarchical calibration and validation for modeling bench-scale solvent-based carbon capture. Part 1: Non-reactive physical mass transfer across the wetted wall column

A hierarchical model calibration and validation are proposed here for quantifying the confidence level of mass transfer prediction using a computational fluid dynamics (CFD) model, where the solvent-based carbon dioxide (CO 2 ) capture is simulated and the predicted results are compared to the corresponding bench-scale experimental data. Two unit problems with an increasing level of complexity are proposed to break down the complex physical/chemical processes of solvent-based CO 2 capture into relatively simpler problems to separate the effects of physical transport and chemical reaction. This paper focuses on the calibration and validation of the first unit problem, i.e., the CO 2 mass transfer across a falling ethanolamine (MEA) film in the absence of chemical reaction. This problem is investigated both experimentally and numerically using non-reactive nitrous oxide (N 2 O) as a surrogate for CO 2 . To capture motion of the gas-liquid interface, a volume of fluid method is employed with a one-fluid formulation to compute the mass transfer between the two phases. Parallel bench-scale experiments are designed and conducted to validate and calibrate the CFD models using a general Bayesian calibration approach. Two important transport parameters, Henry's constant and gas diffusivity, are calibrated to produce the posterior distributions, which will be used as input for the second unit problem to address the chemical absorption of CO 2 across the MEA falling film, where both mass transfer and chemical reaction are involved. Finally, mass transfer coefficients predicted by CFD are also compared with those predicted by the traditional/empirical correlations under both steady and wavy falling film conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

A stochastic wind turbine wake model based on new metrics for wake characterization

Abstract Understanding the detailed dynamics of wind turbine wakes is critical to predicting the performance and maximizing the efficiency of wind farms. This knowledge requires atmospheric data at a high spatial and temporal resolution, which are not easily obtained from direct measurements. Therefore, research is often based on numerical models, which vary in fidelity and computational cost. The simplest models produce axisymmetric wakes and are only valid beyond the near wake. Higher‐fidelity results can be obtained by solving the filtered Navier–Stokes equations at a resolution that is sufficient to resolve the relevant turbulence scales. This work addresses the gap between these two extremes by proposing a stochastic model that produces an unsteady asymmetric wake. The model is developed based on a large‐eddy simulation (LES) of an offshore wind farm. Because there are several ways of characterizing wakes, the first part of this work explores different approaches to defining global wake characteristics. From these, a model is developed that captures essential features of a LES‐generated wake at a small fraction of the cost. The synthetic wake successfully reproduces the mean characteristics of the original LES wake, including its area and stretching patterns, and statistics of the mean azimuthal radius. The mean and standard deviation of the wake width and height are also reproduced. This preliminary study focuses on reproducing the wake shape, while future work will incorporate velocity deficit and meandering, as well as different stability scenarios. Copyright © 2016 John Wiley & Sons, Ltd.

Doubrawa, Paula↗
DOE OSTI2018

Quality Control Analysis in Real-time (QC-ART): A Tool for Real-time Quality Control Assessment of Mass Spectrometry-based Proteomics Data

Liquid chromatography-mass spectrometry (LC-MS)-based proteomics studies of large sample cohorts can easily require from months to years to complete. Acquiring consistent, high-quality data in such large-scale studies is challenging because of normal variations in instrumentation performance over time, as well as artifacts introduced by the samples themselves, such as those due to collection, storage and processing. Existing quality control methods for proteomics data primarily focus on post-hoc analysis to remove low-quality data that would degrade downstream statistics; they are not designed to evaluate the data in near real-time, which would allow for interventions as soon as deviations in data quality are detected. In addition to flagging analyses that demonstrate outlier behavior, evaluating how the data structure changes over time can aide in understanding typical instrument performance or identify issues such as a degradation in data quality due to the need for instrument cleaning and/or re-calibration. To address this gap for proteomics, we developed Quality Control Analysis in Real-Time (QC-ART), a tool for evaluating data as they are acquired in order to dynamically flag potential issues with instrument performance or sample quality. QC-ART has similar accuracy as standard post-hoc analysis methods with the additional benefit of real-time analysis. We demonstrate the utility and performance of QC-ART in identifying deviations in data quality due to both instrument and sample issues in near real-time for LC-MS-based plasma proteomics analyses of a sample subset of The Environmental Determinants of Diabetes in the Young cohort. We also present a case where QC-ART facilitated the identification of oxidative modifications, which are often underappreciated in proteomic experiments.

Stanfill, Bryan A.↗