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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Advancing Insights into Electrochemical Pre‐Treatments of Supported Nanoparticle Electrocatalysts by Combining a Design of Experiments Strategy with In Situ Characterization

Activation, break-in, and/or pre-treatment protocols are generally applied to energy conversion devices before regular operation to reach stable performance. There remains much to understand about the relationships among physical properties, performance, and electrochemical pre-treatments. Here, a design-of-experiments (DoE) strategy is employed to address this gap by demonstrating the influence of five pre-treatment parameters for carbon-supported Pt-nanoparticle catalysts on the electrocatalytic oxygen reduction reaction (ORR). A subset of pre-treatments, developed using a central composite design, are tested in a flow cell combined with an inductively-coupled plasma mass spectrometer (on-line ICP-MS). The DoE-based approach facilitates comprehensive insights from two orders of magnitude fewer experiments than a conventional grid search. The coupled on-line ICP-MS setup enables effective catalysis and real-time catalyst dissolution data. Leveraging insights from DoE for on-line ICP-MS and additional characterization, a model is built between the degradation of a multi-dimensional supported Pt surface, its performance, and applied electrochemical parameters. These investigations identify surface modifications, such as oxidation, and subsequent restructuring of Pt during pre-treatment as a primary cause of performance deterioration during ORR. By combining DoE with advanced characterization techniques, a powerful approach is demonstrated to gain a mechanistic understanding of pre-treatment protocols that can be broadly adapted to various reaction chemistries.

Platinum↗
DOE OSTI2021

Structural Changes during the Growth of Atomically Precise Metal Oxido Nanoclusters from Combined Pair Distribution Function and Small-Angle X-ray Scattering Analysis

The combination of in situ pair distribution function (PDF) analysis and small-angle X-ray scattering (SAXS) enables analysis of the formation mechanism of metal oxido nanoclusters and cluster–solvent interactions as they take place. Herein, we demonstrate the method for the formation of clusters with a [Bi 38 O 45 ] core. Upon dissolution of crystalline [Bi 6 O 5 (OH) 3 (NO 3 ) 5 ]∙3 H 2 O in DMSO, an intermediate rapidly forms, which slowly grows to stable [Bi 38 O 45 ] clusters. To identify the intermediate, we developed an automated modeling method, where smaller [Bi x O y ] structures based on the [Bi 38 O 45 ] framework are tested against the data. [Bi 22 O 26 ] was identified as the main intermediate species, illustrating how combined PDF and SAXS analysis is a powerful tool to gain insight into nucleation on an atomic scale. PDF also provides information on the interaction between nanoclusters and solvent, which is shown to depend on the nature of the ligands on the cluster surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Renewable hydrogen and ammonia for combined heat and power systems in remote locations: Optimal design and scheduling

Abstract Using hydrogen (H ) and ammonia (NH ) for renewable energy storage has the potential to enable economical power and heat supply with high renewable penetrations, especially in remote locations which are characterized by high energy costs. In this work we assess the economic competitiveness of renewable combined heat and power (CHP) systems in Mahaka HI, Nantucket MA, and Northwest Arctic Borough (NWAB) AK by optimally designing these systems for scenarios in which power and heat can be purchased over a range of historical energy prices as well as when 100% renewable supply is required. We use a combined optimal design and scheduling model which minimizes annualized net present cost by determining optimal technology selection and size simultaneously with optimal schedules for each period of a system operating horizon aggregated from full year hourly resolution data via a consecutive temporal clustering algorithm. We find that renewable generation meets at least 85% of power demands and 75% of heat demands under the lowest energy prices investigated. Higher conventional energy prices lead to increased renewable penetration which is facilitated by renewable NH as a seasonal energy storage medium, as are 100% renewable CHP systems. NH is used for power generation with heat cogeneration in all three locations, as well as directly for heating in NWAB. On an annual cost basis, NH ‐enabled 100% renewable CHP is only 3% more expensive in Mahaka and NWAB than systems which can purchase energy at the lowest prices, while it is 15% more expensive in Nantucket.

Palys, Matthew J.↗
DOE OSTI2023

Combining pairwise structural similarity and deep learning interface contact prediction to estimate protein complex model accuracy in CASP15

Abstract Estimating the accuracy of quaternary structural models of protein complexes and assemblies (EMA) is important for predicting quaternary structures and applying them to studying protein function and interaction. The pairwise similarity between structural models is proven useful for estimating the quality of protein tertiary structural models, but it has been rarely applied to predicting the quality of quaternary structural models. Moreover, the pairwise similarity approach often fails when many structural models are of low quality and similar to each other. To address the gap, we developed a hybrid method (MULTICOM_qa) combining a pairwise similarity score (PSS) and an interface contact probability score (ICPS) based on the deep learning inter‐chain contact prediction for estimating protein complex model accuracy. It blindly participated in the 15th Critical Assessment of Techniques for Protein Structure Prediction (CASP15) in 2022 and performed very well in estimating the global structure accuracy of assembly models. The average per‐target correlation coefficient between the model quality scores predicted by MULTICOM_qa and the true quality scores of the models of CASP15 assembly targets is 0.66. The average per‐target ranking loss in using the predicted quality scores to rank the models is 0.14. It was able to select good models for most targets. Moreover, several key factors (i.e., target difficulty, model sampling difficulty, skewness of model quality, and similarity between good/bad models) for EMA are identified and analyzed. The results demonstrate that combining the multi‐model method (PSS) with the complementary single‐model method (ICPS) is a promising approach to EMA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Acceleration Factors for Combined‐Accelerated Stress Testing of Photovoltaic Modules

Combined‐accelerated stress testing (C‐AST) is developed to establish the durability of photovoltaic (PV) products, including for degradation modes that are not a priori known or examined in standardized tests. C‐AST aims to comprehensively represent the sample, stress factors, and their combinations using levels at the statistical tails of the natural environment. Acceleration factors for relevant climate sequences within the C‐AST cycle with respect to the Florida USA climate are estimated for selected degradation mechanisms. It is found that for degradation of the outer backsheet polymer layer, the acceleration factor of the tropical climate sequence (the longest of the climate sequences) is f ( T , G ) = 17.3 with ultraviolet photodegradation; for polyethylene terephthalate hydrolysis (backsheets), f ( T , RH ) = 426; for electrochemical corrosion (PV cell), f ( I ) = 14.1; and for PbSn solder fatigue f (Δ T , r ( T )) = 17.3. Here, T is the module temperature, G is the broadband spectrum irradiance on the plane of array of the module, RH is the relative humidity on the module surface, I is the leakage current through the module packaging, and r ( T ), the number of temperature reversals. The methods discussed herein are generally applicable for evaluating acceleration factors in other accelerated test methods.

14 SOLAR ENERGY↗
DOE OSTI2024

Combination of searches for heavy spin-1 resonances using 139 fb -1 of proton-proton collision data at $\sqrt{s}$ = 13 TeV with the ATLAS detector

A combination of searches for new heavy spin-1 resonances decaying into different pairings of W, Z, or Higgs bosons, as well as directly into leptons or quarks, is presented. The data sample used corresponds to 139 fb -1 of proton-proton collisions at $\sqrt{s}$ = 13 TeV collected during 2015–2018 with the ATLAS detector at the CERN Large Hadron Collider. Analyses selecting quark pairs (qq, bb, $t\overline{t}$, and tb) or third-generation leptons (τν and ττ) are included in this kind of combination for the first time. A simplified model predicting a spin-1 heavy vector-boson triplet is used. Cross-section limits are set at the 95% confidence level and are compared with predictions for the benchmark model. These limits are also expressed in terms of constraints on couplings of the heavy vector-boson triplet to quarks, leptons, and the Higgs boson. The complementarity of the various analyses increases the sensitivity to new physics, and the resulting constraints are stronger than those from any individual analysis considered. The data exclude a heavy vector-boson triplet with mass below 5.8 TeV in a weakly coupled scenario, below 4.4 TeV in a strongly coupled scenario, and up to 1.5 TeV in the case of production via vector-boson fusion.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Combination and interpretation of differential Higgs boson production cross sections in proton-proton collisions at $ \sqrt{s}=13 $ TeV

Precision measurements of Higgs boson differential production cross sections are a key tool to probe the properties of the Higgs boson and test the standard model. New physics can affect both Higgs boson production and decay, leading to deviations from the distributions that are expected in the standard model. In this paper, combined measurements of differential spectra in a fiducial region matching the experimental selections are performed, based on analyses of four Higgs boson decay channels (γγ, ZZ$^{(*)}$, WW$^{(*)}$, and ττ) using proton-proton collision data recorded with the CMS detector at $ \sqrt{s}=13 $ TeV, corresponding to an integrated luminosity of 138 fb$^{−1}$. The differential measurements are extrapolated to the full phase space and combined to provide the differential spectra. A measurement of the total Higgs boson production cross section is also performed using the γγ and ZZ decay channels, with a result of $ {53.4}_{-2.9}^{+2.9}{\left(\textrm{stat}\right)}_{-1.8}^{+1.9}\left(\textrm{syst}\right) $ pb, consistent with the standard model prediction of 55.6 ± 2.5 pb. The fiducial measurements are used to compute limits on Higgs boson couplings using the κ-framework and the SM effective field theory.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Combination of searches for heavy vector boson resonances in proton-proton collisions at $\sqrt{s}=13$ TeV

A combined statistical analysis of searches for heavy vector boson resonances decaying into pairs of W, Z, or Higgs bosons, as well as into quark pairs $\left(\mathrm{q}\overline{\mathrm{q}},\mathrm{b}\overline{\mathrm{b}},\mathrm{t}\overline{\mathrm{t}},\mathrm{t}\overline{\mathrm{b}}\right)$ or lepton pairs ℓ + ℓ – , ℓ$\bar{v}$, with ℓ = e, μ, τ, is presented. The results are based on proton-proton collision data at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 138 fb −1 , collected by the CMS experiment from 2016 to 2018. No significant deviation from the expectations of the standard model is observed. The results are interpreted in the simplified heavy vector triplet (HVT) framework, setting 95% confidence level upper limits on the production cross sections and on the coupling strengths of the HVT bosons to standard model particles. The results exclude HVT resonances with masses below 5.5 TeV in a weakly coupled scenario, below 4.8 TeV in a strongly coupled scenario, and up to 2.0 TeV in the case of production via vector boson fusion. The combination provides the most stringent constraints to date on new phenomena predicted by the HVT model.

beyond Standard Model↗
DOE OSTI2020

Combination of the W boson polarization measurements in top quark decays using ATLAS and CMS data at $\sqrt{s} =$ 8 TeV

The combination of measurements of the W boson polarization in top quark decays performed by the ATLAS and CMS collaborations is presented. The measurements are based on proton-proton collision data produced at the LHC at a centre-of-mass energy of 8 TeV, and corresponding to an integrated luminosity of about 20 fb$^{−1}$ for each experiment. The measurements used events containing one lepton and having different jet multiplicities in the final state. The results are quoted as fractions of W bosons with longitudinal (F$_{0}$), left-handed (F$_{L}$), or right-handed (F$_{R}$) polarizations. The resulting combined measurements of the polarization fractions are F$_{0}$ = 0.693 ± 0.014 and F$_{L}$ = 0.315 ± 0.011. The fraction F$_{R}$ is calculated from the unitarity constraint to be F$_{R}$ = −0.008 ± 0.007. These results are in agreement with the standard model predictions at next-to-next-to-leading order in perturbative quantum chromodynamics and represent an improvement in precision of 25 (29)% for F$_{0}$ (F$_{L}$) with respect to the most precise single measurement. A limit on anomalous right-handed vector (V$_{R}$), and left- and right-handed tensor (g$_{L}$, g$_{R}$) tWb couplings is set while fixing all others to their standard model values. The allowed regions are [−0.11, 0.16] for V$_{R}$, [−0.08, 0.05] for g$_{L}$, and [−0.04, 0.02] for g$_{R}$, at 95% confidence level. Limits on the corresponding Wilson coefficients are also derived.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

A combined experimental and numerical approach that eliminates the non-uniqueness associated with the Johnson-Cook parameters obtained using inverse methods

Abstract Johnson-Cook constitutive model is a commonly used material model for machining simulations. The model includes five parameters that capture the initial yield stress, strain-hardening, strain-rate hardening, and thermal softening behavior of the material. These parameters are difficult to determine using experiments since the conditions observed during machining (such as high strain-rates of the order of $$10^5$$ 10 5 /sec - $$10^6$$ 10 6 /sec) are challenging to recreate in the laboratory. To address this problem, several researchers have recently proposed inverse approaches where a combination of experiments and analytical models are used to predict the Johnson-Cook parameters. The errors between the measured cutting forces, chip thicknesses and temperatures and those predicted by analytical models are minimized and the parameters are determined. In this work, it is shown that only two of the five Johnson-Cook parameters can be determined uniquely using inverse approaches. Two different algorithms, namely, Adaptive Memory Programming for Global Optimization (AMPGO) and Particle Swarm Optimization (PSO), are used for this purpose. The extended Oxley’s model is used as the analytical tool for optimization. For determining a parameter’s value, a large range for each parameter is provided as an input to the algorithms. The algorithms converge to several different sets of values for the five Johnson-Cook parameters when all the five parameters are considered as unknown in the optimization algorithm. All of these sets, however, yield the same chip shape and cutting forces in FEM simulations. Further analyses show that only the strain-rate and thermal softening parameters can be determined uniquely and the three parameters present in the strain-hardening term of the Johnson-Cook model cannot be determined uniquely using the inverse method. A combined experimental and numerical approach is proposed to eliminate this determine all parameters uniquely.

42 ENGINEERING↗
DOE OSTI2022

Combined Experimental and Computational Study of Molybdenum and Niobium for Nuclear Sensor Application

Due to their novel electromagnetic and thermal properties, molybdenum (Mo) and niobium (Nb) become optimal temperature sensor materials for nuclear energy applications. We leveraged voltage recorded during a heat ramp to tune a computational method to predict the Seebeck electromotive force (EMF) of Mo and Nb. Using a combined Density Functional Theory (DFT) and Boltzmann Transport Equations (BTE) method the voltage was predicted but did not include the effects of temperature on atomic structure. Combining Ab Initio Molecular Dynamics (AIMD) and BTE included temperature effects on structure optimization and yielded voltages in a good agreement with experiment. Lanthanum (La) and Phosphorus (P) additives in Mo and Nb, respectively, could increase the EMF compared to those of the pure metals. The presence of oxygen (O) in Mo increases the EMF while O in Nb slightly reduces the EMF. Furthermore, our studies suggested that heat treatment-induced structural changes that lead to a reduction in voltage occur not only at the mesoscale as previously understood but also at the atomic scale.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Scaling kinetic Monte-Carlo simulations of grain growth with combined convolutional and graph neural networks

Graph neural networks (GNN) have emerged as a promising machine learning method for microstructure simulations such as grain growth. However, accurate modeling of realistic grain boundary networks requires large simulation cells, which GNN has difficulty scaling up to. To alleviate the computational costs and memory footprint of GNN, we suggest a hybrid architecture combining a convolutional neural network (CNN) based bijective autoencoder to compress the spatial dimensions, and a GNN that evolves the microstructure in the latent space of reduced spatial sizes. Our results demonstrate that the new design significantly reduces computational costs with using fewer message passing layer (from 12 down to 3) compared with GNN alone. The reduction in computational cost becomes more pronounced as the spatial size increases, indicating strong computational scalability. For the largest mesh evaluated (160 3 ), our method reduces memory usage and runtime in inference by 117× and 115×, respectively, compared with GNN-only baseline. More importantly, it shows higher accuracy and stronger spatiotemporal capability than the GNN-only baseline, especially in long-term testing. Such combination of scalability and accuracy is essential for simulating realistic material microstructures over extended time scales. The improvements can be attributed to the bijective autoencoder’s ability to compress information losslessly from spatial domain into a high dimensional feature space, thereby producing more expressive latent features for the GNN to learn from, while also contributing its own spatiotemporal modeling capability. Training data are generated from stochastic grain growth simulations, providing realistic variability for learning robust microstructure evolution. Comprehensive system validation confirms that the model is accurate, robust, and scalable.

36 MATERIALS SCIENCE↗
DOE OSTI2021

On the competitive antagonism effect in combined chloride-sulfate attack: A numerical exploration

Highlights: • A chemo-physical-mechanical method based on thermodynamic modelling is implemented. • The contradicting findings from reported experiments are numerically explored. • The competitive antagonism effect is time-dependent rather than a conclusive term. • The competitive antagonism effect is quantifiable with a novel assessment criterion. It is of tremendous difficulty to draw a conclusive verdict on the complex process of mutual interference regarding the combined chloride-sulfate attack on concrete, where many have explored the topic, but contradicting results have been reported. In this paper, by taking advantages of the chemo-physical-mechanical method, based on the robust technique of thermodynamic modelling, the competitive antagonism effect in combined chloride-sulfate attack is investigated. Firstly, a range of reported tests are numerically modelled to demonstrate the effectiveness of the employed method in interpreting those opposing and diverse experimental outcomes. More importantly, a fresh conjecture incorporating a novel assessment criterion for the competitive antagonism effect is proposed and supported through a carefully designed illustrative example. Based on the numerical exploration, unique findings and implications for future engineering practices are revealed.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Combined effect of NaAlO2 and NaOH on the early age hydration of Portland cement with a high concentration of borate solution

The early age hydration of ordinary Portland cement in 5 M borate solution, with or without the addition of NaAlO{sub 2} and/or NaOH, was investigated. Hydration was measured using calorimetry, X-ray diffraction, thermogravimetric analysis, {sup 11}B and {sup 27}Al magic angle spinning NMR analysis, and scanning transmission electron microscopy. The purpose of this study was to reveal the mechanisms behind the retardation caused by a high concentration borate solution and the restoration of hydration through the combined addition of NaOH and NaAlO{sub 2}. Amorphous ulexite, which formed on the surface of the cement particles and prevented the further dissolution of anhydrous phases, was identified as the retardation product. The mechanism of the combined addition of NaAlO{sub 2} and NaOH in overcoming retardation was to transform amorphous ulexite into B-AFt and gowerite (CaB{sub 6}O{sub 10}·5H{sub 2}O). Formation of gowerite is favorable because of the much higher boron immobilization capacity in weight percentage, comparing to usual boron-containing phases reported previously.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Influence of polycarboxylate superplasticizer, citric acid and their combination on the hydration and workability of calcium sulfoaluminate cement

Highlights: • The dispersion efficiency of polycarboxylate superplasticizers drops quickly over time. • Citric acid maintains the dispersion efficiency of PCE over time. • Competitive adsorption between citric acid and PCE occurs. • The combination of citric acid with PCE decreases the initial dispersion efficiency of PCE. PCEs are well known to improve the initial fluidity of CSA. However, their dispersion efficiency drops quickly over time. This issue can be solved by incorporating retarders. In this context, this paper deals with the influence of citric acid, used as a retarder, PCE and their combination on the hydration and workability of CSA. Isothermal calorimetry, XRD and TG analysis were used to describe the hydration process, while workability was characterized with the mini-cone test. Adsorption behavior was investigated using total organic carbon analyzer coupled with ion chromatography. Results show that the introduction of citric acid retained the dispersion efficiency of PCE over time. However, the initial dispersion efficiency of PCE was decreased by citric acid as the latter tend to adsorb first on the surface of cement grains, inhibiting the adsorption of PCE. A dispersion model was proposed to describe the acting mechanism of these admixtures on CSA.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Mechanistic insights into Cr(VI) removal by a combination of zero-valent iron and pyrite

Recent studies have revealed that a combination of zero-valent iron (ZVI) and pyrite (FeS 2 ) can effectively remove (Cr(VI)) from water, but the reasons behind this synergistic effect are still unclear. Our batch experiments showed that dissolved oxygen (DO) is a critical factor in the improved removal of Cr(VI) by ZVI and pyrite. When 0.08 g/L pyrite was combined with 0.5 g/L ZVI in the presence of DO, total Cr was reduced from 10 mg/L to 0.02 mg/L within 6 h. Conversely, in the absence of DO, total Cr was only reduced to 5.6 mg/L. DO oxidation of pyrite produced protons that promote ZVI corrosion, and mixing pyrite with water creates dissolved sulfide, which also contributes to the improved removal of Cr(VI). Here, electron microscopy images and X-ray absorption near edge structure analyses revealed that the presence of dissolved sulfide led to the formation of ferrous sulfide precipitates on the ZVI surface, preventing the formation of a passivating layer.

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

A Combination of Human Broadly Neutralizing Antibodies against Hepatitis B Virus HBsAg with Distinct Epitopes Suppresses Escape Mutations

Although there is no effective cure for chronic hepatitis B virus (HBV) infection, antibodies are protective and correlate with recovery from infection. To examine the human antibody response to HBV, we screened 124 vaccinated and 20 infected, spontaneously recovered individuals. The selected individuals produced shared clones of broadly neutralizing antibodies (bNAbs) that targeted 3 non-overlapping epitopes on the HBV S antigen (HBsAg). Single bNAbs protected humanized mice against infection but selected for resistance mutations in mice with prior established infection. In contrast, infection was controlled by a combination of bNAbs targeting non-overlapping epitopes with complementary sensitivity to mutations that commonly emerge during human infection. The co-crystal structure of one of the bNAbs with an HBsAg peptide epitope revealed a stabilized hairpin loop. This structure, which contains residues frequently mutated in clinical immune escape variants, provides a molecular explanation for why immunotherapy for HBV infection may require combinations of complementary bNAbs.

59 BASIC BIOLOGICAL SCIENCES↗