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Results for “Coefficient of performance”

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 721 records · Page 40

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DOE OSTI2025

Correlating Solvation Free Energy to Electrolyte Properties for Lithium Metal Batteries

The electrolyte plays a critical role in lithium metal batteries. In particular, ion solvation profoundly impacts key electrolyte properties and battery performance. Here, in this study, we systematically investigate solvation-property relationships in a series of electrolytes with different solvent-diluent ratios. Through potentiometric techniques that measure the relative solvation free energies of electrolytes, we find that weaker solvation correlates with larger ion clusters, lower ionic conductivity and diffusion coefficient, and superior electrochemical stability. Weaker solvation leads to the formation of a small number of Li clusters with large hydrodynamic radii, which lowers the Li + diffusivity and ionic conductivity of the electrolyte. Concurrently, weaker solvation leads to improved electrochemical stability at both the cathode and anode interfaces. Understanding these solvation-property relationships and trade-offs is important to designing electrolytes for optimized lithium metal battery performance.

25 ENERGY STORAGE↗

DOE OSTI2022

One-loop matching for quark dipole operators in a gradient-flow scheme

The quark chromoelectric dipole (qCEDM) operator is a CP-violating operator describing, at hadronic energies, beyond-the-standard-model contributions to the electric dipole moment of particles with nonzero spin. In this paper we define renormalized dipole operators in a regularization-independent scheme using the gradient flow, and we perform the matching at one loop in perturbation theory to renormalized operators of the same and lower dimension in the more familiar MS scheme. We also determine the matching coefficients for the quark chromo-magnetic dipole operator (qCMDM), which contributes for example to matrix elements relevant to CP-violating and CP-conserving kaon decays. The calculation provides a basis for future lattice QCD computations of hadronic matrix elements of the qCEDM and qCMDM operators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Effective field theory interpretation of lepton magnetic and electric dipole moments

We perform a model-independent analysis of the magnetic and electric dipole moments of the muon and electron. We give expressions for the dipole moments in terms of operator coefficients of the low-energy effective field theory (LEFT) and the Standard Model effective field theory (SMEFT). We use one-loop renormalization group improved perturbation theory, including the one-loop matching from SMEFT onto LEFT, and one-loop lepton matrix elements of the effective-theory operators. Semileptonic four-fermion operators involving light quarks give sizable non-perturbative contributions to the dipole moments, which are included in our analysis. We find that only a very limited set of the SMEFT operators is able to generate the current deviation of the magnetic moment of the muon from its Standard Model expectation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

High fidelity simulations of contaminant dispersion in an urban environment with comparison to magnetic resonance imaging measurements

The dispersion of a contaminant in an urban environment has the potential to impact a large population of people. In this work, a complex urban canopy flow based on the Oklahoma City downtown business district circa 2003 is studied using Magnetic Resonance Imaging (MRI) and high-fidelity Large Eddy Simulations (LES). MRI is a novel experimental technique that can provide high-resolution measurements in four dimensions (three spatial and temporal) for lab scale models. The experiments and simulations use the same geometry and boundary conditions providing a one-to-one comparison of the two methods. Results are presented on the time-averaged velocity and concentration fields, the temporal dynamics of the concentration plumes for a transient release, and a novel Cloud Identification Algorithm that can separate plumes produced by periodic contaminant releases used for ensemble averaging over many releases. The MRI and LES datasets both include millions of measurement voxels and the comparisons highlight the complex 3D nature of the flow including strong vertical velocities in spanwise street canyons and flow acceleration in streamwise street canyons. The concentration fields are qualitatively similar albeit the LES shows larger dispersion. A quantitative analysis with performance measures compares the datasets pointwise and demonstrates that the two 3D datasets are similar with respect to many measures including a fractional bias of 0.02 (ideal=0.0), correlation coefficient of 0.87 (ideal = 1.0), and the fraction points within a factor of 2 is 0.98 (ideal = 1.0). Plume analysis compares the arrival and residence time of contaminant and is found to vary significantly with location within the urban environment with arrival times between 0 and 1.25 and differences within the contaminant cloud less than 10% at most locations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Augmentation of pool boiling heat transfer on tube bundles using metal foam

Pool boiling on a tube bundle is one of the most important heat transfer modes in several industrial applications, including steam generators, shell and tube heat exchangers for waste heat recovery, and desalination. Although several enhanced tubes (e.g., external micro-finned tubes) have been extensively studied and commercialized, the studies that pertain to the metal foam enhanced tube bundles are limited in the open literature. The objective of the present study is to perform an experimental study to analyze the pool boiling heat transfer characteristics of a metal foam tube bundle and compare its performance with that of a tube bundle with no enhancement. The performance of the metal foam tube bundles with different porosities (81%, 75%, and 62%) is compared against the conventional bare tube bundle. The results showed that the heat transfer coefficients of the metal foam tube bundles are 100–212% higher than those of the bare tube bundle. Among the different porosities, metal foam with 75% porosity showed a higher heat transfer coefficient. Furthermore, the wall temperature of the metal foam tubes is nearly 5–14⁰C lower than that of the bare tubes. In conclusion, when compared with a tube pitch of 25.4 mm, a tube pitch of 19.05 mm showed a maximum of 9% and 14% enhancement in bare and metal foam tube bundles, respectively.

42 ENGINEERING↗

DOE OSTI2024

3D multi-system Bayesian calibration with energy conservation to study rapidity-dependent dynamics of nuclear collisions

Considerable information about the early-stage dynamics of heavy ion collisions is encoded in the rapidity dependence of measurements. To leverage the large amount of experimental data, we perform a systematic analysis using three-dimensional hydrodynamic simulations of multiple collision systems — large and small, symmetric and asymmetric. Specifically, we perform fully 3D multi-stage hydrodynamic simulations initialized by a parameterized model for rapidity-dependent energy deposition, which we calibrate on the hadron multiplicity and anisotropic flow coefficients. We utilize Bayesian inference to constrain properties of the early- and late-time dynamics of the system, and highlight the impact of enforcing global energy conservation in our 3D model.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Neural network potential from bispectrum components: A case study on crystalline silicon

In this article, we present a systematic study on developing machine learning force fields (MLFFs) for crystalline silicon. While the main-stream approach of fitting a MLFF is to use a small and localized training set from molecular dynamics simulations, it is unlikely to cover the global features of the potential energy surface. Additionally, to remedy this issue, we used randomly generated symmetrical crystal structures to train a more general Si-MLFF. Furthermore, we performed substantial benchmarks among different choices of material descriptors and regression techniques on two different sets of silicon data. Our results show that neural network potential fitting with bispectrum coefficients as descriptors is a feasible method for obtaining accurate and transferable MLFFs.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Measurement of elliptic flow of 𝐽/𝜓 in $\sqrt{s_{NN}}$ = 200 GeV ⁢Au + Au collisions at forward rapidity

Here, we report the first measurement of the azimuthal anisotropy of 𝐽/𝜓 at forward rapidity (1.2 < |𝜂| < 2.2) in Au + Au collisions at $\sqrt{s_{NN}}$ = 200 GeV at the BNL Relativistic Heavy Ion Collider. The data were collected by the PHENIX experiment in 2014 and 2016 with integrated luminosity of 14.5 nb −1 . The second Fourier coefficient (𝑣 2 ) of the azimuthal distribution of 𝐽/𝜓 is determined as a function of the transverse momentum (𝑝𝑇) using the event-plane method. The measurements were performed for several selections of collision centrality: 0%–50%, 10%–60%, and 10%–40%. We find that in all cases the values of 𝑣 2 ⁡(𝑝 𝑇 ), which quantify the elliptic flow of 𝐽/𝜓, are consistent with zero. Within uncertainties, the results are consistent with measurements at midrapidity, indicating no significant elliptic flow of the 𝐽/𝜓 within the quark-gluon-plasma medium at collision energies of $\sqrt{s_{NN}}$ = 200 GeV.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

A Step-Down Test Procedure for Wavelet Shrinkage Using Bootstrapping

Wavelet thresholding (or shrinkage) attempts to remove the noises existing in the signals while preserving inherent pattern characteristics in the reconstruction of true signals. For data-denoising purpose, we present a new wavelet thresholding procedure which employs the step-down testing idea of identifying active contrasts in unreplicated fractional factorial experiments. The proposed method employs bootstrapping methods to a step-down test for thresholding wavelet coefficients. By introducing the concept of a false discovery error rate in testing wavelet coefficients, we shrink the wavelet coefficients with p -values higher than the error rate. The error rate controls the expected proportion of wrongly accepted coefficients among chosen wavelet coefficients. Bootstrap samples are used to approximate the p -value for computational efficiency. We also present some guidelines for selecting the values of hyper-parameters which affect the performance in the step-down thresholding procedure. Based on some common testing signals and an air-conditioner sounds example, the comparison of our proposed procedure with other thresholding methods in the literature is performed. The analytical results show that the proposed procedure has a potential in data-denoising and data-reduction in a variety of signal reconstruction applications.

42 ENGINEERING↗

DOE OSTI2022

Convective Heat Transfer Potential of Particles/Airflow Through Single Cell Thick Additively Manufactured Octet-Shaped Lattice Frame Material

Abstract Particle-to-Supercritical Carbon Dioxide (sCO2) heat exchangers are one of the most critical components of the next-generation Concentrating Solar Power (CSP) plants. There have been several efforts to enhance the overall heat exchanger performance which essentially comprises of thermal resistances offered by sCO2 channel, wall (separating sCO2 with particles) thickness, particle-wall contact resistance and particle-side effective heat transfer coefficient. This study is focused towards reducing the particle side thermal resistance by incorporating single unit cell thick reticulated Octet lattice frame structures on the falling particle side to enhance the effective thermal conductivity of the particle channel and to enhance convective heat transfer between the falling particles and the solid phase of the falling particle channel (endwalls and fibers). Steady-state experiments were conducted to measure the effective thermal conductivity of lattice frame material for two cases: a) when void space was occupied by air, b) when void space was occupied with particles. Further, convective heat transfer experiments have been conducted with both air (steady-state) and particles (quasi steady-state) as “working fluid” for panels sandwiching the Octet array. Three different lattice porosities ranging from 0.75 to 0.9 have been tested for a wide range of air flow rates and a fixed particle flow rate (highest potential).

Aider, Youssef↗

DOE OSTI2022

Carbon-Binder Weight Loading Optimization for Improved Lithium-Ion Battery Rate Capability

Battery performance is strongly correlated with electrode microstructure and weight loading of the electrode components. Among them are the carbon-black and binder additives that enhance effective conductivity and provide mechanical integrity. However, these both reduce effective ionic transport in the electrolyte phase and reduce energy density. Therefore, an optimal additive loading is required to maximize performance, especially for fast charging where ionic transport is essential. Such optimization analysis is however challenging due to the nanoscale imaging limitations that prevent characterizing this additive phase and thus quantifying its impact on performance. Herein, an additive-phase generation algorithm has been developed to remedy this limitation and identify percolation threshold used to define a minimal additive loading. Improved ionic transport coefficients from reducing additive loading has been then quantified through homogenization calculation, macroscale model fitting, and experimental symmetric cell measurement, with good agreement between the methods. Rate capability test demonstrates capacity improvement at fast charge at the beginning of life, from 37% to 55%, respectively for high and low additive loading during 6C CC charging, in agreement with macroscale model, and attributed to a combination of lower cathode impedance, reduced electrode tortuosity and cathode thickness.

25 ENERGY STORAGE↗

DOE OSTI2024

Carbon-Binder Optimization for Lithium-Ion Battery Extreme Fast Charge

carbon-binder additives↗

DOE OSTI2020

An Exploratory Approach Using Regression and Machine Learning in the Analysis of Mass Absorption Cross Section of Black Carbon Aerosols: Model Development and Evaluation

Mass absorption cross-section of black carbon (MAC BC ) describes the absorptive cross-section per unit mass of black carbon, and is, thus, an essential parameter to estimate the radiative forcing of black carbon. Many studies have sought to estimate MAC BC from a theoretical perspective, but these studies require the knowledge of a set of aerosol properties, which are difficult and/or labor-intensive to measure. We therefore investigate the ability of seven data analytical approaches (including different multivariate regressions, support vector machine, and neural networks) in predicting MAC BC for both ambient and biomass burning measurements. Our model utilizes multi-wavelength light absorption and scattering as well as the aerosol size distributions as input variables to predict MAC BC across different wavelengths. We assessed the applicability of the proposed approaches in estimating MAC BC using different statistical metrics (such as coefficient of determination (R 2 ), mean square error (MSE), fractional error, and fractional bias). Overall, the approaches used in this study can estimate MAC BC appropriately, but the prediction performance varies across approaches and atmospheric environments. Based on an uncertainty evaluation of our models and the empirical and theoretical approaches to predict MAC BC , we preliminarily put forth support vector machine (SVM) as a recommended data analytical technique for use. We provide an operational tool built with the approaches presented in this paper to facilitate this procedure for future users.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

An in situ formed inorganic conductive network enables high stability and rate capability of single-crystalline nickel-rich cathodes

Single-crystalline Ni-rich cathodes are promising for the next generation of high-energy-density Li-ion batteries due to their better capacity retention than their polycrystalline counterparts. However, there is still much room for improving the electrochemical performances when considering their surface degradation and severe kinetic hindrance during cycling. Herein, we report a strategy to construct an in situ formed robust Li-conductive Li 3 PO 4 layer on the surface of cathode particles. This Li-conductive layer significantly increases the Li-ion diffusion coefficients and suppresses detrimental surface phase transformation. In situ XRD reveals that the improved kinetics alleviate the local stress at high voltage. The as-prepared single-crystalline LiNi 0.83 Co 0.12 Mn 0.05 O 2 delivers good durability (96.8% after 100 cycles at 1C) and excellent rate capability (177.08 mA h g -1 at 5C). Here, this work provides a facile and efficient strategy to improve the cycling performance and boost the rate capability of single-crystalline Ni-rich cathodes.

25 ENERGY STORAGE↗

DOE OSTI2020

Computational modelling and experimental tank testing of the multi float WaveSub under regular wave forcing

A submerged wave device generates energy from the relative motion of floating bodies. In WaveSub, three floats are joined to a reactor; each connected to a spring and generator. Electricity generated damps the orbital movements of the floats. The forces are non-linear and each float interacts with the others. Tuning to the wave climate is achieved by changing the line lengths, so there is a need to understand the performance trade-offs for a large number of configurations. This requires an efficient, large displacement, multidirectional, multi-body numerical scheme. Results from a 1/25 scale wave basin experiment are described. Here, we show that a time domain linear potential flow formulation (Nemoh, WEC-Sim) can match the tank testing provided that suitably tuned drag coefficients are employed. Inviscid linear potential models can match some wave device experiments; however, additional viscous terms generally provide better accuracy. Scale experiments are also prone to mechanical friction, and we estimate friction terms to improve the correlation further. The resulting error in mean power between numerical and physical models is approximately 10%. Predicted device movement shows a good match. Overall, drag terms in time domain wave energy modelling will improve simulation accuracy in wave renewable energy device design. to understand the performance trade-offs for a large number of configurations. This requires an efficient, large displacement, multidirectional, multi-body numerical scheme. Results from a 1/25 scale wave basin experiment are described. Here, we show that a time domain linear potential flow formulation (Nemoh, WEC-Sim) can match the tank testing provided that suitably tuned drag coefficients are employed. Inviscid linear potential models can match some wave device experiments; however, additional viscous terms generally provide better accuracy. Scale experiments are also prone to mechanical friction, and we estimate friction terms to improve the correlation further. The resulting error in mean power between numerical and physical models is approximately 10%. Predicted device movement shows a good match. Overall, drag terms in time domain wave energy modelling will improve simulation accuracy in wave renewable energy device design.

16 TIDAL AND WAVE POWER↗

DOE OSTI2024

Comprehensive Study of Carrier Recombination in High‐Efficiency CdTe Solar Cells Using Transient Photovoltage

Cadmium telluride (CdTe) solar cells represent a commercially successful photovoltaic technology, with an annual production capacity approaching 20 GW. However, improving the open-circuit voltage (V OC ) remains challenging. This study aims to deepen the understanding of charge carrier recombination in CdTe solar cells and to explore alternative dynamical characterization methods that address the limitations found in conventionally used time-resolved photoluminescence for CdTe solar cells. Transient photovoltage and transient photocurrent techniques are utilized to investigate charge carrier dynamics under conditions resembling real-world solar cell operation. The results reveal that an effective nonradiative recombination lifetime of 580 ns dominates the charge dynamics at VOC values below 850 mV. Above this threshold, radiative recombination becomes significant, with a radiative recombination coefficient of 1.1 × 10 −9 cm 3 s −1 . Additionally, the stationary charge carrier density at 1 sun is determined to be around 1 × 10 14 cm −3 . By accurately determining both radiative and nonradiative recombination, this work provides a comprehensive understanding of carrier dynamics in high-performing CdTe devices and paves the way for improving the V OC and performance of CdTe solar cells.

CdTe solar cells↗

DOE OSTI2022

Chemical kinetic interactions and sensitivity analyses for 2-ethylhexyl nitrate-doped PRF91 using a reduced mechanism

A numerical and experimental investigation about the chemical kinetic interactions between 2-ethylhexylnitrate (EHN) and PRF91 was performed in this study. Rapid compression machine experiments were conducted to investigate the effect of EHN on the autoignition reactivity of the fuel, and a reduced chemical kinetic mechanism was developed including an EHN sub-model. Experiments showed that the ignition delay decreases as the fuel is doped with EHN, but the effect of the doping level of EHN on the ignition is highly non-linear. Moreover, experiments showed that the EHN effectiveness is lowest during the transition between the low-temperature regime and the negative temperature coefficient (NTC) regime, and it rapidly increases as the temperature increases. Both detailed and (developed) reduced mechanisms were validated against the experimental results, allowing a more in-depth EHN-fuel chemistry study. Additionally, ignition delay sensitivity and EHN effectiveness sensitivity analyses were performed with the reduced mechanism to identify the reactions that control the interaction between EHN and the fuel. As the result, EHN thermal decomposition is only relevant for very low temperatures. The chemistry of EHN-doped fuel is more sensitive to intermediate temperature reactions than that of straight fuel, especially at lower temperatures, due to the effect of EHN on the NTC behavior of the fuel. Finally, the chemistry of EHN-doped fuel is very sensitive to NO 2 -to-NO reactions, especially at high temperatures, because these reactions transform the NO 2 generated by EHN into NO, which is a very effective fuel reactivity enhancer.

2-ethylhexyl nitrate↗

DOE OSTI2020

Cloud based tool for analysis of chemical kinetic mechanisms

The size and complexity of chemical kinetic models used to simulate combustion of hydrocarbon fuels continue to increase with our improved understanding of the underlying physical mechanisms, along with the improved ability to utilize such models as the result of increased computational power and efficiency. As mechanisms grow beyond thousands of species and tens of thousands of reactions, it becomes increasingly difficult to manually check for errors and physical inconsistencies. In this work, we present several automated methods to check for such issues in the specification of chemical reaction models. First, we demonstrate how discontinuities in thermodynamic data can cause simulation difficulties manifested as long wall-clock times and convergence failures. To correct this type of problem, we describe an automated method for refitting thermodynamic parameters. We also outline several methods to check the timescales of reaction rate coefficients to ensure physical consistency. All the methods are made available through a web-based tool (https://combustiontools.llnl.gov) intended to aid mechanism developers and users to improve the accuracy and performance of fuel models used by the combustion community.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗