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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Structure refinement and anisotropic atomic displacement parameters of 1M Illite: Rietveld and pair distribution function analysis using synchrotron X-ray radiation

Illite, a widespread clay mineral, plays a pivotal role in geological processes, notably as an indicator in diagenetic and hydrothermal alteration environments, and possesses significant industrial relevance in applications including ceramics, construction and catalysis. However, challenges including its nanoscale crystallinity, structural disorder and frequent interstratification with other clay minerals have hindered detailed structural characterization using conventional X-ray diffraction (XRD) techniques. This study employs integrated synchrotron XRD and pair distribution function (PDF) analysis to elucidate the crystal structure of the 1M illite polytype, yielding the first determination of its anisotropic atomic displacement parameters (U aniso ). TheseU aniso parameters provide critical insights into atomic dynamics and static disorder within the structure, enabling a more refined understanding of structure–property relationships. This integrated approach, combining synchrotron XRD, Rietveld refinement and PDF analysis, yields a comprehensive structural characterization, capturing both average crystallographic and local atomic arrangements. Considering illite's widespread geological occurrence and industrial importance, this high-precision structural dataset, especially the determinedU aniso values, provides a crucial benchmark for future modeling and simulation efforts targeting accurate prediction of its physicochemical behavior.

Chemistry↗
DOE OSTI2021

Transparent MgO for Back-Contact Passivation of CdTe-Based Solar Cells

The passivating effects of MgO have been studied by integrating into an existing superstrate CdTe thin film solar cell device architecture. When implemented as an emitter to replace the typical MZO, the device performance was below par, but improved PL and TRPL was detected with significant carrier lifetimes in comparison to the MZO devices. However, when integrated at the back, the PL signal was detected upon the illumination of excitation laser from the back. This has opened the possibility of probing the back of the CdTe thin film solar cells with transparent back contact with improved back passivation and a bifacial device structure. Further, the TRPL measurements suggests that the MgO shows passivating effects to a CdTe surface irrespective of method of deposition implemented.

bifacial↗
DOE OSTI2022

Fiber Uncertainty Visualization for Bivariate Data With Parametric and Nonparametric Noise Models

Visualization and analysis of multivariate data and their uncertainty are top research challenges in data visualization. Constructing fiber surfaces is a popular technique for multivariate data visualization that generalizes the idea of level-set visualization for univariate data to multivariate data. Here, in this paper, we present a statistical framework to quantify positional probabilities of fibers extracted from uncertain bivariate fields. Specifically, we extend the state-of-the-art Gaussian models of uncertainty for bivariate data to other parametric distributions (e.g., uniform and Epanechnikov) and more general nonparametric probability distributions (e.g., histograms and kernel density estimation) and derive corresponding spatial probabilities of fibers. In our proposed framework, we leverage Green's theorem for closed-form computation of fiber probabilities when bivariate data are assumed to have independent parametric and nonparametric noise. Additionally, we present a nonparametric approach combined with numerical integration to study the positional probability of fibers when bivariate data are assumed to have correlated noise. For uncertainty analysis, we visualize the derived probability volumes for fibers via volume rendering and extracting level sets based on probability thresholds. We present the utility of our proposed techniques via experiments on synthetic and simulation datasets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Assessing the accuracy of time-fraction and ductility exhaustion approaches for creep-fatigue damage prediction through feature-test validation

Determining creep-fatigue damage formation is critical for elevated temperature components integrity. This study evaluates creep-fatigue assessments with emphasis on differences between creep damage models. Evaluated are the time-fraction model and the classical and stress-modified ductility exhaustion creep damage models. This work extends the domain of stress-modified ductility exhaustion models by introducing and validating such formalism to Ni-based alloys. The fidelity of the assessments was benchmarked against uniaxial creep-fatigue and multiaxial feature tests of Alloy 617. For uniaxial specimens, best estimate predictions rank ductility exhaustion as the most accurate and precise and time-fraction as markedly conservative. For feature tests, ductility exhaustion predictions are within < 4.0 times difference, whereas time-fraction underpredicts life by factors of 7–14. The observations suggest ductility exhaustion models as alternative to time-fraction models in design codes for situations requiring characterization of the design margin. Further work in employing such models to assess other relevant phenomena (e.g., stress relaxation cracking) is discussed.

creep-fatigue↗
DOE OSTI2024

Comprehensive characterization of extracellular vesicles produced by environmental (Neff) and clinical (T4) strains of Acanthamoeba castellanii

We conducted a comprehensive comparative analysis of extracellular vesicles (EVs) from two Acanthamoeba castellanii strains, Neff (environmental) and T4 (clinical). Morphological analysis via transmission electron microscopy revealed slightly larger Neff EVs (average = 194.5 nm) compared to more polydisperse T4 EVs (average = 168.4 nm). Nanoparticle tracking analysis (NTA) and dynamic light scattering validated these differences. Proteomic analysis of the EVs identified 1,352 proteins, with 1,107 common, 161 exclusive in Neff, and 84 exclusively in T4 EVs. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) mapping revealed distinct molecular functions and biological processes and notably, the T4 EVs enrichment in serine proteases, aligned with its pathogenicity. Lipidomic analysis revealed a prevalence of unsaturated lipid species in Neff EVs, particularly triacylglycerols, phosphatidylethanolamines (PEs), and phosphatidylserine, while T4 EVs were enriched in diacylglycerols and diacylglyceryl trimethylhomoserine, phosphatidylcholine and less unsaturated PEs, suggesting differences in lipid metabolism and membrane permeability. Metabolomic analysis indicated Neff EVs enrichment in glycerolipid metabolism, glycolysis, and nucleotide synthesis, while T4 EVs, methionine metabolism. Furthermore, RNA-seq of EVs revealed differential transcript between the strains, with Neff EVs enriched in transcripts related to gluconeogenesis and translation, suggesting gene regulation and metabolic shift, while in the T4 EVs transcripts were associated with signal transduction and protein kinase activity, indicating rapid responses to environmental changes. In this novel study, data integration highlighted the differences in enzyme profiles, metabolic processes, and potential origins of EVs in the two strains shedding light on the diversity and complexity of A. castellanii EVs and having implications for understanding host-pathogen interactions and developing targeted interventions for Acanthamoeba-related diseases.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Investigation of Membrane Chemical Degradation as a Function of Catalyst Platinum Loading

Membrane chemical degradation is one of many factors that can impact fuel cell durability. Additionally, the fuel cell’s lifetime heavily depends on the membrane and its ability to maintain chemical and mechanical integrity. Previous studies indicate that chemical degradation is due to the formation of hydroxyl radicals that attack the polymer structure resulting in membrane thinning, pinhole formation, and the release of fluoride and sulfate ions. Membrane durability was investigated using ultra-low Pt electrode loadings (≤ 0.1 mg Pt cm -2 ). Accelerated stress testing (US-DOE protocols) demonstrated that the degradation rate was found to increase with higher Pt loadings. This is most likely due to more heterogeneous sites for radical formation due to hydrogen crossover to the cathode. We also explored membrane degradation rates while varying catalyst layer thickness, ionomer to carbon ratio, and types of carbon support. All of the aforementioned variables impact the membrane degradation rates.

25 ENERGY STORAGE↗
DOE OSTI2025

Data Assimilation with Machine Learning Surrogate Models: A Case Study with FourCastNet

Modern data-driven surrogate models for weather forecasting provide accurate short-term predictions but inaccurate and nonphysical long-term forecasts. This paper investigates online weather prediction using machine learning surrogates supplemented with partial and noisy observations. We empirically demonstrate and theoretically justify that, despite the long-time instability of the surrogates and the sparsity of the observations, filtering estimates can remain accurate in the long-time horizon. As a case study, we integrate the Fourier Forecasting Neural Network (FourCastNet), a weather surrogate model, within a variational data assimilation framework using partial, noisy ERA5 global reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF). Here, our results show that filtering estimates remain accurate over a year-long assimilation window and provide effective initial conditions for forecasting tasks, including extreme event prediction.

Data assimilation↗
DOE OSTI2020

Hessian-based multiparameter fractional viscoacoustic full-waveform inversion

Recent progress on fractional modeling enables incorporating seismic attenuation into wavefield simulation in an accurate and efficient way. But its inverse problem, i.e., the multiparameter viscoacoustic full waveform inversion (FWI), still suffers from various issues, especially the crosstalk between velocity and attenuation. In this study, we integrate the Hessian information via the Newton-CG framework and develop the multiparameter fractional viscoacoustic FWI algorithm. It significantly mitigates the crosstalk problems and sheds light upon simultaneous inversion for both velocity and Q models.

Xing, Guangchi↗
DOE OSTI2025

Dynamic Nanopeptide Assemblies for Trans-Tympanic Drug Delivery

Aim: Otitis media is a common otolaryngologic diagnosis worldwide. Invasive methods to curtail and treat frequent occurrences are undesirable, thus necessitating the identification and production of a non-invasive approach to treating the disease. Due to tympanic membrane thickness, ototopical drug delivery is challenging. In this preliminary study, formulations integrating nanopeptides and thermoresponsive polymeric hydrogels are utilized to improve the efficiency of trans-tympanic membrane drug delivery. Methods: Peptides were synthesized using standard Fmoc (fluorenylmethoxycarbonyl protecting group) based solid state peptide synthesis on an automated peptide synthesizer. Ciprofloxacin release was simulated using multiwell microplates with porous inserts. Rate of Ciprofloxacin release was measured over a 48-hour period using a 200 uL solution of peptide fibers and Ciprofloxacin at 1 wt% each, and the labeled peptide at 0.1 wt% in PBS at pH of 7.4. The cytotoxicity of the PA (peptide amphiphile, specifically c16-AHL 3 K 3 -CO 2 H) micelle and fiber with and without ciprofloxacin was investigated by examining epidermal keratinocyte viability in the presence of the material at various concentrations. Laser scanning confocal microscopy was performed with excitation of the calcein dye at 485 nm and the PA-TAMRA (rhodamine labeled peptide) at 515 nm. Results: We have demonstrated the potential viability of a self-assembled peptide amphiphile hydrogel capable of transitioning from a network of 1D nanoscale fibers to 0D micelles. This dissociative mechanism of action yields a peptide that is an effective cell penetrating peptide (CPP) while temporally controlling the release of the antibiotic ciprofloxacin. Conclusion: This work highlights the potential utility of the dynamic process of an engineered peptide hydrogel capable of dissociating into CPPs capable of facilitating drug delivery across the tympanic membrane.

cell culture↗
DOE OSTI2021

The Development of Catalysts for Upgrading of Pyrolysis Vapor for Refinery Feedstocks and Intermediates: Cooperative Research and Development, CRADA Number CRD-12-00497 (Final Report)

Fast pyrolysis of biomass with vapor phase upgrading (VPU) can produce refinery feedstocks or intermediates that can meet the Department of Energy’s goal of cost-competitive hydrocarbon fuels by 2017. A key technical barrier for this technology is the lack of selective, cost effective catalysts that can produce high yields of fuel-appropriate hydrocarbons from the pyrolysis vapors. In overcoming this barrier, it will be important to engage leading catalyst development companies to devote their resources and expertise to the development of these materials. Thus, we propose a Cooperative Research and Development Agreement (CRADA) between the National Renewable Energy Laboratory (NREL), a world leader in biomass pyrolysis research and Johnson Matthey (JM), a world leader in the production of advanced catalyst materials to develop and test novel catalysts for efficient VPU. Through its Intercat Inc. subsidiary in Savannah, Ga., Johnson Matthey is internationally recognized as a leader in zeolite-based vapor phase upgrading in refinery duties and an emerging developer of biomass conversion technologies. The research and development efforts described in the proposed work will build upon existing collaborations between NREL and JM and play to the strengths of both institutions. NREL will analyze the composition of pyrolysis vapors as an input to catalyst design, screen and test catalysts, characterize the resulting oil and conduct techno-economic analysis. Catalyst samples will be produced and funded by JM. JM will design and synthesize catalysts, characterize fresh and used catalysts and develop catalyst supports needed to achieve commercially meaningful lifetimes. The project will span catalyst development and testing from the fundamental stage using quantum mechanical modeling and chemical reaction analysis to catalyst screening to integrated pilot studies.

09 BIOMASS FUELS↗
DOE OSTI2023

WAVES [Slides]

WAVES (LANL code C23004) is a computational engineering workflow tool that integrates parametric studies with traditional software build systems.

42 ENGINEERING↗
DOE OSTI2025

First-Principles Thermodynamic Assessments of Sr-Containing Secondary Phase Formation in La1-xSrxMnO3±δ Perovskites for Solid Oxide Cell Applications

Sr-secondary phase formation is a potentially significant degradation mode threatening solid-oxide cell (SOC) commercial viability. A first-principles thermodynamic study was performed for rhombohedral perovskite (La1-xSrx) MnO3±δ (LSM) to assess its stability against Sr secondary phase formation in SOC applications. In this work, the Sr secondary phase formation reaction free energies were determined by combining ab initio lattice dynamics calculations for the solid phases and an ab initio thermodynamics approach for the gas phases. Furthermore, this approach goes beyond previous thermodynamic modeling studies by integrating first-principles based point-defect equilibria into the analyses. The modeling results indicate an increased tendency to form SrO oxide from LSM upon decreasing the oxygen partial pressure. Additionally, enhancing factors to form the Sr-related secondary phase from the associated SrO activity in LSM are further quantified by considering the equilibrium of SrO reacting with contaminant gas species as a function of temperature and gas pressure.

Defect and phase stability↗
DOE OSTI2025

Nuclear data sensitivity and uncertainty study of copper-reflected integral experiments [Slides]

This presentation touches on reducing uncertainties in intermediate-energy actinide nuclear data and this continues to be a high priority for many applications. The goal of PARADIGM (PARallel Approach of Differential and InteGral Measurements): accelerate efforts to reduce biases and uncertainties in nuclear data through improvements to the nuclear data pipeline. This presentation includes integral experiments and a summarization of existing copper nuclear data.

Cu63↗
DOE OSTI2026

Development of an Unbiased Future Solar Dataset for Solar Resource Adequacy Research Over CONUS

A high-resolution, long-term solar dataset is essential for capturing the variability of solar energy resources and informing strategies to ensure grid reliability and resilience in systems with high levels of solar energy integration. This study focuses on generating unbiased, high-resolution projections of solar irradiance through a statistical downscaling framework, using Earth system model (ESM) simulations obtained from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX). The National Solar Radiation Database (NSRDB) is used to calibrate statistical downscaling models. The newly developed dataset provides solar irradiance, surface air temperature, and surface wind speed at 4-km and hourly resolutions across the contiguous United States (CONUS), based on two future scenarios (RCP4.5 and RCP8.5). This study outlines key steps in developing the high-resolution future solar dataset, including (1) regridding ESM data to a common 20-km resolution grid, (2) correcting ESM biases using the NSRDB, and (3) applying temporal and spatial downscaling methods to generate high-resolution (4-km, hourly) solar projections. Preliminary results indicate that downscaled projections (4-km) captured reasonable spatial patterns when compared to observations across CONUS for four variables. On average across all pixels, 4-km daily-total GHI and DNI projections showed normalized bias (nBias) less than 1% and 6% for GHI and DNI against NSRDB, respectively (nBias less than 1% and 5% for daily-average surface air temperature and surface wind speed). In terms of long-term trend for GHI and DNI, there was no strong increasing or decreasing trend (when compared to surface air temperature), but it showed a very weak decreasing trend.

14 SOLAR ENERGY↗
DOE OSTI2020

A Comprehensive Analysis of Energy and Daylighting Impact of Window Shading Systems and Control Strategies on Commercial Buildings in the United States

Commercial buildings consume approximately 1.9 EJ of energy in the United States, 50% of which is for heating, cooling, and lighting applications. It is estimated that windows contribute up to 34% of the energy used for heating and cooling. However, window retrofits are not often undertaken to increase energy efficiency because of the high cost and disruptive nature of window installation. Highly efficient window technologies would also need shading devices for glare prevention and visual comfort. An automated window shading system with an appropriate control strategy is a technology that can reduce energy demand, maintain occupant comfort, and enhance the aesthetics and privacy of the built environment. However, the benefits of the automated shades currently used by the shading industry are not well studied. The topic merits an analysis that will help building owners, designers and engineers, and utilities make informed decisions using knowledge of the impact of this technology on energy consumption, peak demand, daylighting, and occupant comfort. This study uses integrated daylight and whole-building energy simulation to evaluate the performance of various control strategies that the shading industry uses in commercial office buildings. The analysis was performed for three different vintages of medium office buildings at six different locations in United States. The results obtained show the control strategies enabled cooling energy savings of up to 40% using exterior shading, and lighting energy savings of up to 25%. The control strategies described can help building engineers and researchers explore different control methods used to control shading in actual buildings but rarely discussed in the literature. This information will give researchers the opportunity to investigate potential improvements in current technologies and their performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Higher education institutions can do more to lead society toward resilience and sustainability

Higher education institutions (HEIs) are beginning to recognize their role as leading societal institutions in the movement toward resilience and sustainability by empowering their students as sustainability stakeholders and leaders and recognizing the value of faculty and staff as facilitators in this mobilization toward a more sustainable future. This chapter identifies seven goals derived from academic research that can be used to foster student leadership in sustainability and support faculty and staff in facilitatory roles. To date, however, most research has focused on sustainability in the classroom environment or the establishment of living labs. To illuminate how these seven goals can be achieved, the chapter adopts stakeholder theory and conducts an integrated case study assessment. Overall, the chapter helps to (i) develop a stronger understanding of sustainability and resilience, (ii) identify best practices for empowering student leaders and to better understand the facilitatory role played by faculty and staff in achieving the seven goals, and (ii) offer further insights through a reflective case study.

Sustainability and Resilience, Sustainability Syst↗
DOE OSTI2025

Data Assimilation with Machine Learning Surrogate Models: A Case Study with FourCastNet

Modern data-driven surrogate models for weather forecasting provide accurate short-term predictions but inaccurate and nonphysical long-term forecasts. This paper investigates online weather prediction using machine learning surrogates supplemented with partial and noisy observations. We empirically demonstrate and theoretically justify that, despite the long-time instability of the surrogates and the sparsity of the observations, filtering estimates can remain accurate in the long-time horizon. As a case study, we integrate FourCastNet, a weather surrogate model, within a variational data assimilation framework using partial, noisy ERA5 data. Our results show that filtering estimates remain accurate over a year-long assimilation window and provide effective initial conditions for forecasting tasks, including extreme event prediction.

Adrian, Melissa [Univ. of Chicago, IL (United Stat↗
DOE OSTI2025

Kinematic flow from the flow of cuts

The wavefunction coefficients of conformally coupled scalars in power-law FRW cosmologies satisfy differential equations governed by a set of simple combinatorial rules known as the kinematic flow. In this paper we derive the kinematic flow, expressed using a set of differential forms referred to as the cut basis, from a geometric perspective, relying solely on the cosmological hyperplane arrangement and without invoking bulk physics. Each element of the cut basis corresponds to the positive geometry associated to an independent cut of the physical FRW-form and can be labeled by decorating (minors of) the truncated Feynman graph with an acyclic orientation. We provide a straightforward prescription to associate a logarithmic differential form to each element of the cut basis by considering its corresponding decorated graph. Moreover, we show that the residues of the physical FRW-form are canonical forms of certain graphical zonotopes labeled by the same set of decorated graphs. These zonotopes control the cut combinatorics -- flow of cuts -- of the physical FRW-form and the cut basis (by construction). Using the theory of relative twisted cohomology and intersection theory, we derive a closed form formula for the differential equations of the cut basis. We also introduce combinatorial rules that compute the kinematic differential of any basis element without explicit calculation. The combinatorics of our differential equations is a natural consequence of the flow of cuts and is equivalent (up to rescaling) to the kinematic flow for the recently studied time integral basis. In particular, our differential equations decouple into exponentially many sectors, one for each way of cutting a subset of edges of the graph.

General Relativity and Quantum Cosmology↗