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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 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Aggregation of solutes in bosonic versus fermionic quantum fluids

Quantum fluid droplets made of helium-3 ( 3 He) or helium-4 ( 4 He) isotopes have long been considered as ideal cryogenic nanolabs, enabling unique ultracold chemistry and spectroscopy applications. The droplets were believed to provide a homogeneous environment in which dopant atoms and molecules could move and react almost as in free space but at temperatures close to absolute zero. Here, we report ultrafast x-ray diffraction experiments on xenon-doped 3 He and 4 He nanodroplets, demonstrating that the unavoidable rotational excitation of isolated droplets leads to highly anisotropic and inhomogeneous interactions between the host matrix and enclosed dopants. Superfluid 4 He droplets are laced with quantum vortices that trap the embedded particles, leading to the formation of filament-shaped clusters. In comparison, dopants in 3 He droplets gather in diffuse, ring-shaped structures along the equator. The shapes of droplets carrying filaments or rings are direct evidence that rotational excitation is the root cause for the inhomogeneous dopant distributions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2017

Sensitivity Analysis Method to Address User Disparities in the Analytic Hierarchy Process

Decision makers often face complex problems, which can seldom be addressed well without the use of structured analytical models. Mathematical models have been developed to streamline and facilitate decision making activities, and among these, the Analytic Hierarchy Process (AHP) constitutes one of the most utilized multi-criteria decision analysis methods. While AHP has been thoroughly researched and applied, the method still shows limitations in terms of addressing user profile disparities. A novel sensitivity analysis method based on local partial derivatives is presented here to address these limitations. This new methodology informs AHP users of which pairwise comparisons most impact the derived weights and the ranking of alternatives. The method can also be applied to decision processes that require the aggregation of results obtained by several users, as it highlights which individuals most critically impact the aggregated group results while also enabling to focus on inputs that drive the final ordering of alternatives. An aerospace design and engineering example that requires group decision making is presented to demonstrate and validate the proposed methodology.

Marie Ivanco↗
DOE OSTI2018

Evaluation of thermodynamic equations of state across chemistry and structure in the materials project

Thermodynamic equations of state (EOS) for crystalline solids describe material behaviors under changes in pressure, volume, entropy and temperature, making them fundamental to scientific research in a wide range of fields including geophysics, energy storage and development of novel materials. Despite over a century of theoretical development and experimental testing of energy–volume (E–V) EOS for solids, there is still a lack of consensus with regard to which equation is indeed optimal, as well as to what metric is most appropriate for making this judgment. In this study, several metrics were used to evaluate quality of fit for 8 different EOS across 87 elements and over 100 compounds which appear in the literature. Our findings do not indicate a clear “best” EOS, but we identify three which consistently perform well relative to the rest of the set. Furthermore, we find that for the aggregate data set, the RMSrD is not strongly correlated with the nature of the compound, e.g., whether it is a metal, insulator, or semiconductor, nor the bulk modulus for any of the EOS, indicating that a single equation can be used across a broad range of classes of materials.

36 MATERIALS SCIENCE↗
NASA NTRS2013

Uncertainty of Passive Imager Cloud Optical Property Retrievals to Instrument Radiometry and Model Assumptions: Examples from MODIS

The optical and microphysical structure of clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of MODIS on the NASA EOS Terra and Aqua platforms, simultaneous global-daily 1 km retrievals of cloud optical thickness (COT) and effective particle radius (CER) are provided, as well as the derived water path (WP). The cloud product (MOD06/MYD06 for MODIS Terra and Aqua, respectively) provides separate retrieval datasets for various two-channel retrievals, typically a VISNIR channel paired with a 1.6, 2.1, and 3.7 m spectral channel. The MOD06 forward model is derived from on a homogeneous plane-parallel cloud. In Collection 5 processing (completed in 2007 with a modified Collection 5.1 completed in 2010), pixel-level retrieval uncertainties were calculated for the following non-3-D error sources: radiometry, surface spectral albedo, and atmospheric corrections associated with model analysis uncertainties (water vapor only). The latter error source includes error correlation across the retrieval spectral channels. Estimates of uncertainty in 1 aggregated (Level-3) means were also provided assuming unity correlation between error sources for all pixels in a grid for a single day, and zero correlation of error sources from one day to the next. I n Collection 6 (expected to begin in late summer 2013) we expanded the uncertainty analysis to include: (a) scene-dependent calibration uncertainty that depends on new band and detector-specific Level 1B uncertainties, (b) new model error sources derived from the look-up tables which includes sensitivities associated with wind direction over the ocean and uncertainties in liquid water and ice effective variance, (c) thermal emission uncertainties in the 3.7 m band associated with cloud and surface temperatures that are needed to extract reflected solar radiation from the total radiance signal, (d) uncertainty in the solar spectral irradiance at 3.7 m, and (e) addition of stratospheric ozone uncertainty in visible atmospheric corrections. A summary of the approach and example Collection 6 results will be shown.

Cloud Properties Observations↗
DOE OSTI2026

Demand response event simulator and risk-aware bidding tool for industrial customers

Incentive Based Demand Response (IBDR) program participation delivers financial benefits to the consumers and resiliency benefits to the electricity grid. Effectively participating in these programs as an industrial consumer requires bidding strategies that balance financial risk with operational constraints. Existing bidding tools tend not to fully incorporate stochastic IBDR event modeling, program specific baseline and payment/penalty calculations, or demand reduction process control schemes that account for the cascading impacts of shutdown in complex facilities. Here, this work presents an IBDR event simulator and risk-aware bidding framework tool integrating three key components: a flexible, parameterized demand response event generator that rigorously accounts for program structures and stochasticity, a demand response operational simulation model that generates explicit control strategies for load reduction, and a Monte Carlo simulator to evaluate financial risk for varied capacity bids. A case study at a wastewater treatment plant participating in PG&E's Capacity Bidding Program demonstrates the framework's utility. In the peak capacity price month of August, optimal bidding by the wastewater treatment plant nets a mean IBDR benefit of $101,000 (67% of the August electricity bill) with 0.4% probability of a financial loss. This framework enables industrial operators to make informed bidding decisions, negotiate better program terms with demand response load aggregators, and analyze energy flexibility investments at their facilities. Ultimately, this work reduces participation barriers in IBDR programs and supports the broader goal of enhancing grid reliability and renewable energy integration.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

Structure and stability of CaH 2 surfaces: on the possibility of electron-rich surfaces in metal hydrides for catalysis

Structure, thermodynamic stability, and electronic properties of CaH 2 surfaces in (001),(110), and (111) crystallographic orientations are investigated using ab initio modeling. We show that stoichiometric surfaces terminated with a hydrogen atomic plane are the most energetically favorable and discuss properties of hydrogen vacancies (VH) at these surfaces. The average calculated work function of the most stable pristine surfaces (~5.2 eV) is in agree-ment with experimental data for powder samples. Neutral hydrogen vacancies host localized electrons and induce defect states in the band gap, thereby shifting the effective work function to much lower values of ~2.7 eV. Surface VH are predicted to aggregate into dimers and form electron-rich centers (e - )Ca 2+ (e - ) stable to over 800 K. These results suggest that hydrogen-deficient surfaces of CaH 2 can host a large concentration of localized electrons and, thus, give rise to new catalytic functionalities involving electron transfer between the surface, catalysts supported on it, and reacting species.

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

Reducing Memory Consumption in Calico with Shared Memory

This document details the work to reduce memory consumption in Calico. Calico is SimTools’ Constructive Solid Geometry (CSG) and geometry painting library. It is primarily used to paint material volume fractions in the Eulerian meshes of the physics codes. Calico provides point-in-body checks for the geometry supplied by an Oso model, which are then aggregated by the host codes. In addition, Calico can be used to build Oso models and is used by Ingen for that purpose. Oso models, and thus Calico, provide support for various CSG primitives such as spheres, cylinders, surfaces generated by rotating tabular curve data, and STL files as well as binary combinations of those primitives. Prior to refactoring Calico will run out of memory on CTS-1 machines when 36 MPI ranks are used per node when reading STL models on the order of 1.5 GB. This limitation is a bottleneck in designer workflow. This problem has been alleviated through the use of data structures to both reduce memory consumption and to leverage MPI-3 shared memory. This report details the data structures targeted for refactoring in Calico, the methods and implementation details for reducing memory consumption and leveraging shared memory, and results for one test problem. Results show a memory reduction when loading a 1 GB STL file by a factor of 27.5, from 93.4 to 3.4 GB.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

The C-terminal region of alpha-crystallin: involvement in protection against heat-induced denaturation

Recent studies have demonstrated that the alpha-crystallins can protect other proteins against heat-induced denaturation and aggregation. To determine the possible involvement of the C-terminal region in this activity, the alpha-crystallins were subjected to limited tryptic digestion, and the amount of cleavage from the N-terminal and C-terminal regions of the alpha-A and alpha-B crystallin chains was assessed using antisera specific for these regions. Limited tryptic digestion resulted in cleavage only from the C-terminal region of alpha-A crystallin. This trypsin-treated alpha-A crystallin preparation showed a decreased ability to protect proteins from heat-induced aggregation using an in vitro assay. Together, these results demonstrate that the C-terminal region of alpha-A crystallin is important for its ability to protect against heat-induced aggregation, which is consistent with the hypothesis that post-translational changes that are known to occur at the C-terminal region may have significant effects on the ability of alpha-A crystallin to protect against protein denaturation in vivo.

NASA Discipline Cell Biology↗
DOE OSTI2019

Synthesis and in silico and in vitro evaluation of trimethoxy-benzamides designed as anti-prion derivatives

Transmissible spongiform encephalopathies (TSEs), also known as prion diseases, are neurodegenerative disorders which affect mammals, including the human species, and arise after the conversion of the monomeric cellular prion protein (PrP{sup C}) into the aggregated scrapie form (PrP{sup Sc}). There is no therapy to treat TSEs and the identification of compounds that bind PrP{sup C}, preventing its conversion into PrP{sup Sc}, is a viable therapeutic strategy. We designed and synthesized six novel trimethoxy-benzamide compounds as anti-prion drug candidates. Molecular docking analyses predicted that all the derivatives bind to a hotspot region located in the PrP globular domain with very similar spatial orientation and interaction mode. Although none of the analogs inhibited in vitro-aggregation of recombinant PrP (rPrP) in a cell-free conversion assay, the RT-QuIC, compound 8a accelerated rPrP conversion into PrP{sup Sc}-like species. STD-NMR and ITC analyses indicated that both 8a and 8b bind to rPrP{sup 90–231}. These analogs were toxic to PrP{sup Sc}-infected cell lines, hence we could not assess their anti-prion activity by using this cellular approach, although this toxicity was cell line-dependent. These results point out that the 4-amino-quinoline trimethoxy-benzamide scaffold described herein represents a novel chemical pattern useful as a starting point for future structural optimization in the design of PrP ligands with improved affinity and safety profiles.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Rationalizing the suitability of rhodamines as chromophores in dye-sensitized solar cells: A systematic molecular design study

Here, rhodamines are chromophores that are employed in many dye applications. Their strong optical absorption in the visible region of the electromagnetic spectrum renders them attractive dye candidates for dye-sensitized solar cells (DSCs). However, they have not yet been systematically tested in DSCs as single- or co-sensitizers. Recent advances in concerted experimental and computational workflows involving molecular design protocols can afford a better understanding of the molecular origins of the optoelectronic properties in these sensitizers. Herein, we examine the suitability of rhodamines R560 (1), R575 (2), R590 (3), R610 (4), R620 (5), R640 (6), and R3B (7) as chromophores in co-sensitized DSCs. Our study follows a stepwise approach. Initially, structural and optical properties of the dyes are investigated by experimental and computational methods to reveal structure-property relationships and other useful features for DSC applications. Subsequently, 1-7 are investigated at the dye···TiO 2 interface, both by calculations of dye-adsorption onto the surface of a modeled (TiO 2 ) 9 cluster, and by experimental studies of dye-adsorption on TiO 2 . For that purpose, a selection of rhodamine dyes are paired together (1 and 5) and (1 and 7) for co-sensitization, among which 5 is also co-adsorbed with a fluorescein dye in order to explore chemical compatibility factors. The best dye candidates are identified from the findings of these adsorption studies in terms of dye aggregation, anchoring modes, and panchromatic response. Despite their promising dye…TiO 2 adsorption and optical prospects, our results show that rhodamines lack a suitable intramolecular charge transfer pathway for dye-to-TiO 2 electron injection to occur, thus precluding their photovoltaic function as DSC dyes. Our results are then assessed against ostensibly disparate reports of rhodamines performing successfully in DSC devices; this comparison necessitated the internal reproduction of previously reported co-sensitization experiments on 2 with the industrial standard reference dye, N3. We achieve reconciliation between our results and those in the literature by reasoning that while rhodamines cannot deliver photovoltaic function in DSCs in their own right, they can either act to facilitate or deplete the photovoltaic output of a DSC indirectly by affecting the TiO 2 adsorption prospects of a photovoltaic-active dye with which a rhodamine is co-sensitized.

14 SOLAR ENERGY↗
DOE OSTI2024

Effects of Neutron Irradiation on the Bond Strength of Steel Embedded in Concrete

The structural integrity of the concrete biological shield (CBS) in light water reactors (LWRs) exposed to long-term radiation raises the question of the effects of fast-neutron and gamma irradiation on the bond properties of embedded carbon-steel reinforcement in concrete, which is critical to the transfer of in-service and accidental loads. The design and execution of a first-of-a-kind irradiation experiment conducted in the LVR-15 test reactor (Czech Republic) are presented along with preliminary post-irradiation examination and testing results. Preliminary analysis shows that the fast neutron flux affects the radiation-induced volumetric of concrete aggregate, that the gamma irradiation induces shrinkage of the chemically bonded water in cementitious hydrates and that the bond strength of steel in concrete at the tested irradiation conditions decreases moderately.

Le Pape, Yann↗
DOE OSTI2020

Drivers of Water Use in the Agricultural Sector of the European Union 27

Population growth and the uncertain hazards that accompany climate change have put increasing pressure on the management and sustainability of water. It has a direct impact on agriculture and its domestic and international supply chain linkages. As one of the largest agricultural producers in the world, the European Union (EU) is particularly sensitive to changes in water availability. Therefore, here we perform a structural decomposition analysis based on the recently released EXIOBASE 3 database to examine in depth how changes in water input coefficients, in final demand and in technology have affected changes in water use across crops. Crop production consumes 99% of the direct water in agriculture. Our results show that the largest EU crop producers have experienced an increase in water use that is mostly driven by changes in technology. On the other hand, several Mediterranean countries, where water scarcity has been a problem for years, have decreased their water consumption mostly thanks to an improvement in their water intensity. Results by crop are consistent with those at the aggregated level except for vegetables of which water use changes have been primarily driven by changes in final demand and water intensity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

High-Pressure and Temperature Effects on the Clustering Ability of Monohydroxy Alcohols

This study examined the clustering behavior of monohydroxy alcohols, where hydrogen-bonded clusters of up to a hundred molecules on the nanoscale can form. By performing X-ray diffraction experiments at different temperatures and under high pressure, we investigated how these conditions affect the ability of alcohols to form clusters. The pioneering high-pressure experiment performed on liquid alcohols contributes to the emerging knowledge in this field. Implementation of molecular dynamics simulations yielded excellent agreement with the experimental results, enabling the analysis of theoretical models. Here we show that at the same global density achieved either by alteration of pressure or temperature, the local aggregation of molecules at the nanoscale may significantly differ. Surprisingly, high pressure not only promotes the formation of hydrogen-bonded clusters but also induces the serious reorganization of molecules. This research represents a milestone in understanding association under extreme thermodynamic conditions in other hydrogen bonding systems such as water.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Dictating Pt-Based Electrocatalyst Performance in Polymer Electrolyte Fuel Cells, from Formulation to Application

In this study, in situ electrochemical diagnostics designed to probe ionomer interactions with platinum and carbon were applied to relate ionomer coverage and conformation, gleaned from anion adsorption data, with O 2 transport resistance for low-loaded (0.05 mg Pt cm -2 ) platinum-supported Vulcan carbon (Pt/Vu)-based electrodes in a polymer electrolyte fuel cell. Coupling the in situ diagnostic data with ex situ characterization of catalyst inks and electrode structures, the effect of ink composition is explained by both ink-level interactions that dictate the electrode microstructure during fabrication and the resulting local ionomer distribution near catalyst sites. Electrochemical techniques (CO displacement and ac impedance) show that catalyst inks with higher water content increase ionomer (sulfonate) interactions with Pt sites without significantly affecting ionomer coverage on the carbon support. Surprisingly, the higher anion adsorption is shown to have a minor impact on specific activity, while exhibiting a complex relationship with oxygen transport. Ex situ characterization of ionomer suspensions and catalyst/ionomer inks indicates that the lower ionomer coverage can be correlated with the formation of large ionomer aggregates and weaker ionomer/catalyst interactions in low-water content inks. These larger ionomer aggregates resulted in increased local oxygen transport resistance, namely, through the ionomer film, and reduced performance at high current density. In the water-rich inks, the ionomer aggregate size decreases, while stronger ionomer/Pt interactions are observed. The reduced ionomer aggregation improves transport resistance through the ionomer film, while the increased adsorption leads to the emergence of resistance at the ionomer/Pt interface. Overall, the high current density performance is shown to be a nonmonotonic function of ink water content, scaling with the local gas (H 2 , O 2 ) transport resistance resulting from pore, thin film, and interfacial phenomena.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

Atomically Precise Single-Site Catalysts via Exsolution in a Polyoxometalate–Metal–Organic-Framework Architecture

Single-site catalysts (SSCs) achieve a high catalytic performance through atomically dispersed active sites. A challenge facing the development of SSCs is aggregation of active catalytic species. Reducing the loading of these sites to very low levels is a common strategy to mitigate aggregation and sintering; however, this limits the tools that can be used to characterize the SSCs. Here we report a sintering-resistant SSC with high loading that is achieved by incorporating Anderson–Evans polyoxometalate clusters (POMs, MMo 6 O 24 , M = Rh/Pt) within NU-1000, a Zr-based metal–organic framework (MOF). The dual confinement provided by isolating the active site within the POM, then isolating the POMs within the MOF, facilitates the formation of isolated noble metal sites with low coordination numbers via exsolution from the POM during activation. The high loading (up to 3.2 wt %) that can be achieved without sintering allowed the local structure transformation in the POM cluster and the surrounding MOF to be evaluated using in situ X-ray scattering with pair distribution function (PDF) analysis. Notably, the Rh/Pt···Mo distance in the active catalyst is shorter than the M···M bond lengths in the respective bulk metals. Furthermore, models of the active cluster structure were identified based on the PDF data with complementary computation and X-ray absorption spectroscopy analysis.

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

Distributed quantum approximate optimization algorithm on a quantum-centric supercomputing architecture

Quantum approximate optimization algorithm (QAOA) has shown promise in solving combinatorial optimization problems by providing quantum speedup on near-term gate-based quantum computing systems. However, QAOA faces challenges for high-dimensional problems due to the large number of qubits required and the complexity of deep circuits, limiting its scalability for real-world applications. In this study, we present a distributed QAOA (DQAOA), which leverages distributed computing strategies to decompose a large computational workload into smaller tasks that require fewer qubits and shallower circuits than are necessary to solve the original problem. These sub-problems are processed using a combination of high-performance and quantum computing resources. The global solution is iteratively updated by aggregating sub-solutions, allowing convergence toward the optimal solution. We demonstrate that DQAOA can handle considerably large-scale optimization problems (e.g., 1000-bit problem), achieving a high solution quality and short time-to-solution, outperforming existing strategies. Furthermore, we realize DQAOA on a quantum-centric supercomputing architecture, paving the way for practical applications of gate-based quantum computers in real-world optimization tasks. To extend DQAOA’s applicability to materials science, we further develop an active learning algorithm integrated with our DQAOA (AL-DQAOA), which involves machine learning, DQAOA, and active data production in an iterative loop. We successfully optimize photonic structures using AL-DQAOA, indicating that solving real-world optimization problems using gate-based quantum computing is feasible. We expect the proposed DQAOA to be applicable to a wide range of optimization problems and AL-DQAOA to find broader applications in material design.

Kim, Seongmin [ORNL] (ORCID:0000000159063004)↗
NASA NTRS1992

A fuzzy set preference model for market share analysis

Consumer preference models are widely used in new product design, marketing management, pricing, and market segmentation. The success of new products depends on accurate market share prediction and design decisions based on consumer preferences. The vague linguistic nature of consumer preferences and product attributes, combined with the substantial differences between individuals, creates a formidable challenge to marketing models. The most widely used methodology is conjoint analysis. Conjoint models, as currently implemented, represent linguistic preferences as ratio or interval-scaled numbers, use only numeric product attributes, and require aggregation of individuals for estimation purposes. It is not surprising that these models are costly to implement, are inflexible, and have a predictive validity that is not substantially better than chance. This affects the accuracy of market share estimates. A fuzzy set preference model can easily represent linguistic variables either in consumer preferences or product attributes with minimal measurement requirements (ordinal scales), while still estimating overall preferences suitable for market share prediction. This approach results in flexible individual-level conjoint models which can provide more accurate market share estimates from a smaller number of more meaningful consumer ratings. Fuzzy sets can be incorporated within existing preference model structures, such as a linear combination, using the techniques developed for conjoint analysis and market share estimation. The purpose of this article is to develop and fully test a fuzzy set preference model which can represent linguistic variables in individual-level models implemented in parallel with existing conjoint models. The potential improvements in market share prediction and predictive validity can substantially improve management decisions about what to make (product design), for whom to make it (market segmentation), and how much to make (market share prediction).

Turksen, I. B.↗
DOE OSTI2018

Degradation Mechanisms of High Capacity 18650 Cells Containing Si-Graphite Anode and Nickel-Rich NMC Cathode

Application of advanced anode and cathode materials in commercial lithium-ion batteries is attracting attention due to their high capacity. Silicon (Si)/graphite anodes and nickel (Ni)-rich lithium nickel manganese cobalt oxide with layered structures have been paired in commercial 18650 high energy density cells (~270 Wh/kg). It is crucial to investigate the cell performance and the aging behavior of this commercial cell. In this study, we present commercial cell degradation mechanisms by comparing fresh and aged electrodes, including changes of crystal structure, morphology, elemental composition, and electrochemical properties. The quantitative analysis was done based on dV/dQ incremental capacity analysis of 18650 cells. To determine the amount of cyclable lithium ions (Li + ) and active material loss, the lithiation and delithiation capacity were compared for fresh and aged electrodes in half coin cells. Results showed that even with 5% (by mass) of Si added in the anode, cracks occurred across the anode leading to contact loss and thickening of the solid electrolyte interphase (SEI) layer. Additionally, the average fluorine (F) ratio of the aged anodes was higher compared to that of the fresh anodes. More severely, the F content on the Si aggregations on aged anodes increased to as high as 5 times that of the fresh anode, indicating SEI growth, especially on Si particles. Solid 7 Li nuclear magnetic resonance results showed no detectable Li metal deposition on the aged anode. On the cathode side, cracks on the primary particle interfaces contributed to cathode material loss, contact loss, and impedance rise. Furthermore, Li + loss into the thickened SEI layer, particle cracking, and impedance rise are the main reasons behind cell degradation.

25 ENERGY STORAGE↗