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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Selectivity Control in Catalytic Reductive Amination of Furfural to Furfurylamine on Supported Catalysts

Abstract Amines are widely used in the manufacture of pharmaceuticals, agricultural chemicals, polymers, and surfactants. However, amines are mostly produced via petrochemical means, which motivates amine production from renewable resources, such as biomass. However, biomass compounds present added challenges involving poor carbon balances. We show that furfural reacts homogeneously with ammonia to produce reactive primary imines, which form large side products and leads to significant carbon losses. The carbon balance is improved by mixing furfural with furfurylamine prior to reaction to form a secondary imine for use as the reaction substrate. While controlling the primary to secondary amine selectivity is a common challenge in reductive amination, supported metal catalysts, including Ni/SiO 2 , Co/SiO 2 , and Ru/SiO 2 optimize the primary amine yield to 90 to 94 % by using the secondary imine as the reaction substrate. A qualitative correlation between the primary to secondary amine selectivity with the nitrogen binding energy of metals is identified.

Gould, Nicholas S.↗
DOE OSTI2024

Mechanistic Studies of Continuous Partial Methane Oxidation on Cu−Zeolites Using Kinetic and Spectroscopic Methods

Abstract Over the past few decades, a significant amount of research effort has focused on investigating the active site requirements and reaction mechanisms for partial methane oxidation (PMO) to methanol over copper–exchanged zeolites during stoichiometric and stepwise chemical looping routes. More recently, research efforts have expanded to include investigating the PMO reaction in a continuous catalytic regime, primarily focusing on determining the influence of catalyst composition on Cu speciation and structure and, in turn, on PMO rate and selectivity. The structures of candidate Cu active sites are commonly studied using a combination of ex situ and in situ spectroscopic approaches. In this perspective, we critically examine the prior literature on catalytic PMO over Cu–zeolites to identify key knowledge gaps that remain in our understanding as motivation for future research efforts. We identify opportunities for future research to address these gaps by adapting analogous interrogation techniques that have been successfully used to elucidate the active site requirements and mechanistic details of another catalytic redox reaction cycle on Cu–zeolites, the selective catalytic reduction (SCR) of nitrogen oxides (NO x ).

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

Room‐Temperature Phosphorescent Platinum(II) Alkynyls with Microsecond Lifetimes Bearing a Strong‐Field Pincer Ligand

Abstract The use of organometallic triplet emitters in organic light emitting diodes (OLEDs) is motivated by the premise of efficient intersystem crossing leading to unit internal quantum efficiencies. However, since most devices are based on solid‐state components, an inherent limitation to square‐planar platinum(II) phosphors is their tendency toward aggregation‐based quenching. Here, a new class of emissive, four‐coordinate Pt II species based on the bisimidazolyl carbazolide (BIMCA) ligand is introduced, which displays highly efficient, long‐lived solid‐state phosphorescence at room temperature. A set of four BIMCAPt phenyl acetylides were synthesized that emit in the green ( λ max =507–540 nm) with >60 % quantum yield and millisecond lifetimes. The structures of the resulting species reveal a non‐planar structure imposed by steric clashes between BIMCA and the iodo or alkynyl co‐ligand. Ground‐state and photophysical characterization are presented. Density functional theory calculations indicate that the BIMCA ligand dominates the frontier orbitals along with the first Franck–Condon singlet and triplet excited states.

Liska, Tadeas↗
DOE OSTI2022

Likelihood Maximization and Moment Matching in Low SNR Gaussian Mixture Models

We derive an asymptotic expansion for the log-likelihood of Gaussian mixture models (GMMs) with equal covariance matrices in the low signal-to-noise regime. The expansion reveals an intimate connection between two types of algorithms for parameter estimation: the method of moments and likelihood optimizing algorithms such as Expectation-Maximization (EM). We show that likelihood optimization in the low SNR regime reduces to a sequence of least squares optimization problems that match the moments of the estimate to the ground truth moments one by one. This connection is a stepping stone towards the analysis of EM and maximum likelihood estimation in a wide range of models. A motivating application for the study of low SNR mixture models is cryo-electron microscopy data, which can be modeled as a GMM with algebraic constraints imposed on the mixture centers. We discuss the application of our expansion to algebraically constrained GMMs, among other example models of interest. © 2022 The Authors. Communications on Pure and Applied Mathematics published by Wiley Periodicals LLC.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Instruction Roofline: An insightful visual performance model for GPUs

The Roofline performance model provides an intuitive approach to identify performance bottlenecks and guide performance optimization. However, the classic FLOP-centric approach is inappropriate for the emerging applications that perform more integer operations than floating point operations. In this article, we reintroduce our Instruction Roofline Model on NVIDIA GPUs and expand our evaluation of it. The Instruction Roofline incorporates instructions and memory transactions across all memory hierarchies together, and provides more performance insights than the FLOP-oriented Roofline Model, that is, instruction throughput, stride memory access patterns, bank conflicts, and thread predication. We use our Instruction Roofline methodology to analyze eight proxy applications: HPGMG from AMReX, Matrix Transpose benchmarks, ADEPT from MetaHipMer's sequence alignment phase, EXTENSION from MetaHipMer's local assembly phase, CUSP, cuSPARSE, cudaTensorCoreGemm, and cuBLAS. We demonstrate the ability of our methodology to understand various aspects of performance and performance bottlenecks on NVIDIA GPUs and motivate code optimizations.

Ding, N↗
DOE OSTI2024

Evaluating the potential of disaggregated memory systems for HPC applications

Summary Disaggregated memory is a promising approach that addresses the limitations of traditional memory architectures by enabling memory to be decoupled from compute nodes and shared across a data center. Cloud platforms have deployed such systems to improve overall system memory utilization, but performance can vary across workloads. High‐performance computing (HPC) is crucial in scientific and engineering applications, where HPC machines also face the issue of underutilized memory. As a result, improving system memory utilization while understanding workload performance is essential for HPC operators. Therefore, learning the potential of a disaggregated memory system before deployment is a critical step. This paper proposes a methodology for exploring the design space of a disaggregated memory system. It incorporates key metrics that affect performance on disaggregated memory systems: memory capacity, local and remote memory access ratio, injection bandwidth, and bisection bandwidth, providing an intuitive approach to guide machine configurations based on technology trends and workload characteristics. We apply our methodology to analyze thirteen diverse workloads, including AI training, data analysis, genomics, protein, fusion, atomic nuclei, and traditional HPC bookends. Our methodology demonstrates the ability to comprehend the potential and pitfalls of a disaggregated memory system and provides motivation for machine configurations. Our results show that eleven of our thirteen applications can leverage injection bandwidth disaggregated memory without affecting performance, while one pays a rack bisection bandwidth penalty and two pay the system‐wide bisection bandwidth penalty. In addition, we also show that intra‐rack memory disaggregation would meet the application's memory requirement and provide enough remote memory bandwidth.

Ding, Nan↗
DOE OSTI2024

Bulk Layering Effects of Ag and Cu for Tandem CO 2 Electrolysis

The electrochemical reduction of carbon dioxide (CO 2 ) presents an opportunity to close the carbon cycle and obtain sustainably sourced carbon compounds. In recent years, copper has received widespread attention as the only catalyst capable of meaningfully producing multi-carbon (C 2+ ) species. Notably carbon monoxide (CO) can also be reduced to C 2+ compounds on copper, motivating tandem systems that combine copper and CO-producing species, like silver, to enhance overall C 2+ selectivities. In this work, we examine the impact of layered-combinations of bulk Cu and Ag by varying the location and proportion of the CO-producing Ag layer. We report an effective increase in the C 2+ oxygenate selectivity from 23 % with a 100 nm Cu to 38 % for a 100: 15 nm Cu : Ag layer. Notably, however, for all co-catalyst cases there is an overproduction of CO vs Cu alone, even for 5 nm Ag layers. Lastly, due to restructuring and interlayer mobility of the copper layer it is clear that the stability of copper limits the locational advantages of such tandem solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Evaluation of Aliphatic Alcohols for CO 2 Capture Using the Characteristic Carbonate Frequency

Control over CO 2 capture and utilization are important scientific and technological challenges. Although a variety of amine absorbents are used for capture, releasing the captured CO 2 is often difficult and limits their recyclability. Therefore, it is crucial to control the strength of the CO 2 bond with the absorbent. Furthermore, it is desirable to use a method that can conveniently report the strength of this bond. This motivates exploring adducts of CO 2 with alcohols in the presence of a base, using vibrational spectroscopy to report on the bond strength. Although reactions of alcohols with CO 2 to form alkyl carbonates are known, a systematic study of these adducts has not been conducted. Here we show formation of alkyl carbonates by a series of alcohols spanning the pK a range 9.5 to 16.8. We show experimental and computational results for the frequency of the characteristic asymmetric stretch of the carbonate and demonstrate that it correlates inversely with the pK a of the alcohol. Based on computations of the bond lengths and previous work, we propose that this frequency also correlates inversely with the adduct strength. As a result, this work extends the scope of CO 2 capture reagents and inspires further research in tuning alcohols as reversible absorbents.

Alcohols↗
DOE OSTI2021

Drought legacies mediated by trait trade‐offs in soil microbiomes

Abstract Soil microbiomes play a key role in driving biogeochemical cycles of the Earth system. As drought frequency and intensity increase due to climate change, soil microbes and the processes they control will be impacted. Even after a drought ends, microbiomes and other systems take time to recover and may display a memory of previous climate conditions. Still, the mechanisms involved in these legacy effects remain unclear, making it difficult to predict climate and biogeochemical rates in the future. Here, we used a trait‐based microbiome model (DEMENTpy) to implement trade‐off‐mediated mechanisms that may lead to drought legacy effects on litter decomposition. Trade‐offs were assumed to follow the Y‐A‐S framework that defines three primary life‐history strategies of microorganisms: high growth Yield, resource Acquisition, and Stress tolerance. We represented cellular trade‐offs between osmolytes required for drought tolerance and investment in enzymes involved in litter decomposition. Simulations were run under varying levels of drought severity and dispersal. With high levels of dispersal, no legacy effects were predicted by DEMENTpy following drought. With limited dispersal, severe drought resulted in a persistent legacy of altered community‐level traits and reduced litter decomposition. Moderate drought resulted in a transient legacy that disappeared after two years, consistent with recent empirical observations in Southern California ecosystems. These results imply that greater movement along the trade‐off between enzyme investment and osmolyte production resulted in stronger legacy effects. More generally, factors that shift the position of a microbiome in YAS space may alter the legacy outcome following drought. Our trait‐based modeling study motivates additional empirical measurements to quantify YAS traits and trade‐offs that are needed to make accurate predictions of soil microbiome resilience and functioning. Also, our study illustrates an emerging approach for representing trait trade‐offs in microbiomes and vegetation that dictate ecosystem responses to drought and other environmental perturbations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Morphology‐controlled synthesis of multi‐metal‐based spinel oxide nanocatalysts and their performance for oxygen reduction

Abstract We present a one‐pot colloidal synthesis method for producing monodisperse multi‐metal (Co, Mn, and Fe) spinel nanocrystals (NCs), including nanocubes, nano‐octahedra, and concave nanocubes. This study explores the mechanism of morphology control, showcasing the pivotal roles of metal precursors and capping ligands in determining the exposed crystal planes on the NC surface. The cubic spinel NCs, terminated with exclusive {100}‐facets, demonstrate superior electrocatalytic activity for the oxygen reduction reaction (ORR) in alkaline media compared to their octahedral and concave cubic counterparts. Specifically, at 0.85 V, (CoMn)Fe 2 O 4 spinel oxide nanocubes achieve a high mass activity of 23.9 A/g and exhibit excellent stability, highlighting the promising ORR performance associated with {100}‐facets of multi‐metal spinel oxides over other low‐index and high‐index facets. Motivated by exploring the correlation between ORR performance and surface atom arrangement (active sites), surface element composition, as well as other factors, this study introduces a prospective approach for shape‐controlled synthesis of advanced spinel oxide NCs. It underscores the significance of catalyst shape control and suggests potential applications as nonprecious metal ORR electrocatalysts.

Li, Can↗
DOE OSTI2023

Engineering Redox Flow Battery Electrodes with Spatially Varying Porosity Using Non‐Solvent‐Induced Phase Separation

Redox flow batteries (RFBs) are a promising electrochemical platform for efficiently and reliably delivering electricity to the grid. Within the RFB, porous carbonaceous electrodes facilitate electrochemical reactions and distribute the flowing electrolyte. Tailoring electrode microstructure and surface area can improve RFB performance, lowering costs. Electrodes with spatially varying porosity may increase electrode utilization and provide surface area in reaction‐limited zones; however, the efficacy of such designs remains an open area of research. Herein, a non‐solvent‐induced phase‐separation (NIPS) technique that enables the reproducible synthesis of macrovoid‐free electrodes with well‐defined across‐thickness porosity gradients is described. The monotonically varying porosity profile is quantified and the physical properties and surface chemistries of porosity‐gradient electrodes are compared with macrovoid‐containing electrode, also synthesized by NIPS. Then, the electrochemical and fluid dynamic performance of the porosity‐gradient electrodes is evaluated, exploring the effect of changing the direction of the porosity gradient and benchmarking against the macrovoid‐containing electrode. Lastly, the performance is examined in a vanadium RFB, finding that the porosity‐gradient electrode outperforms the macrovoid electrode, is independent of gradient direction, and performs favorably compared to advanced electrodes in the contemporary literature. It is anticipated that the approach motivates further exploration of microstructurally tailored electrodes in electrochemical systems.

25 ENERGY STORAGE↗
DOE OSTI2023

Comparing emulation methods for a high‐resolution storm surge model

Abstract Realistic simulations of complex systems are fundamental for climate and environmental studies. Large computer systems are often not sufficient to run sophisticated computational models for large numbers of different input settings. Statistical surrogate models, or emulators, are key tools enabling fast exploration of the simulator input space. Gaussian processes have become standard for computer simulator emulation. However, they require careful implementation to scale appropriately, motivating alternative methods more recently introduced. We present a comparison study of surrogates of the Sea, Lake, and Overland Surges from Hurricanes (SLOSH) simulator—the simulator of choice for government agencies—using four emulation approaches: BASS; BART; SEPIA; and RobustGaSP. SEPIA and RobustGaSP use Gaussian processes, BASS implements adaptive splines, and BART is based on ensembles of regression trees. We describe the four models and compare them in terms of computation time and predictive metrics. These surrogates use proven and distinct methodologies, are available through accessible software, and quantify prediction uncertainty. Our data cover millions of response values. We find that SEPIA and RobustGaSP provide exceptional predictive power, but cannot scale to emulate experiments as large as the one considered in this paper as effectively as BASS and BART.

Hutchings, Grant↗
DOE OSTI2021

Radial storage efficiency for CO 2 injection: Quantifying effectiveness of local flow control methods

Basin-scale geologic carbon sequestration will require hundreds of injection wells, each of which has costs related to property rights and regulatory requirements that correlate with the areal size of the carbon dioxide plume. These surface-footprint-related issues motivate maximizing storage efficiency radially away from each well. Radial storage efficiency (RSE) is defined here as the ratio of the volumetrically weighted carbon dioxide free-phase saturation within a given radius away from the injection well to the available pore space within that same radius. Maximizing RSE effectively minimizes the radial extent of the CO 2 plume. Optimizing RSE around individual wells requires local flow control injection strategies that can increase the uniformity of the filling of pore space around the well over the entire length of the perforated injection interval despite differences in local formation transmissivity. The goal of uniform filling of the storage reservoir starting from the well outward is to maximize carbon dioxide sweep and trapping locally outward from the well in all of the layers of the storage region before buoyancy forces predominate and drive carbon dioxide upward where it will spread laterally under lower-permeability layers. Example simulations of carbon dioxide injection into a layered storage system with and without local flow control are presented to show the advantage of uniformly filling all layers and how RSE can be used to quantify storage efficiency for the two different injection approaches. Published 2021. This article is a U.S. Government work and is in the public domain in the USA.

03 NATURAL GAS↗
DOE OSTI2022

Downwind dispersion of CO 2 from a major subsea blowout in shallow offshore waters

Growing interest in offshore geologic carbon sequestration (GCS) motivates risk assessment of large-scale subsea CO 2 well blowouts or pipeline ruptures. For major leaks of CO 2 from wells or pipelines, significant fluxes of CO 2 may occur from the sea surface depending on water depth. In the context of risk assessment of human health and safety, we have used previously simulated coupled well-reservoir and water column model results as a source term for dense gas dispersion of CO 2 above the sea surface. The models are linked together by one-way coupling, that is, output of one model is used as input to the next model. These first-of-their-kind coupled flow results are applicable to assessing the hazard of CO 2 to people at and downwind of the sea surface location of emission. Hazard is quantified by plotting the downwind dispersion length (DDL), which we define in the study as the distances from the emission source to the point at which the emitted CO 2 has been diluted to 5% and 1.5% in air by volume. Here results suggest that large-scale blowouts in shallow water (10 m) may cause hazardous CO 2 plumes extending on the order of several hundred meters downwind. Details of the modeling show DDL has a maximum for windspeed (at an elevation of 10 m) of approximately 5 m/s, with smaller DDL for both weaker and stronger winds. This is explained by the fact that wind favors transport but also causes dispersion; therefore there is a certain wind speed that maximizes DDL.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Case studies of robots and automation as health/safety interventions in small manufacturing enterprises

This article reviews the experiences of 63 case studies of small businesses (<250 employees) with manufacturing automation equipment acquired through a health/safety intervention grant program. The review scope included equipment technologies classified as industrial robots (n = 17), computer numerical control (CNC) machining (n = 29), or other programmable automation systems (n = 17). Descriptions of workers' compensation (WC) claim injuries and identified risk factors that motivated the acquisition of the equipment were extracted from grant applications. Other aspects of the employer experiences, including qualitative and quantitative assessment of effects on risk factors for musculoskeletal disorders (MSD), effects on productivity, and employee acceptance of the intervention were summarized from the case study reports. Case studies associated with a combination of large reduction in risk factors, lower cost per affected employee, and reported increases in productivity were CNC stone cutting system, CNC/vertical machining system, automated system for bottling, CNC/routing system for plastics products manufacturing, and a CNC/Cutting system for vinyl/carpet. Six case studies of industrial robots reported quantitative reductions in MSD risk factors in these diverse manufacturing industries: snack foods; photographic film, paper, plate, and chemical; machine shops; leather goods and allied products; plastic products; and iron and steel forging. Furthermore, this review of health/safety intervention case studies indicates that advanced (programmable) manufacturing automation, including industrial robots, reduced workplace musculoskeletal risk factors, and improved process productivity in most cases.

42 ENGINEERING↗
DOE OSTI2025

Positive Co‐Degree Density of Hypergraphs

The minimum positive co-degree of a nonempty r-graph H, denoted $δ^+_{r-1}$ (H), is the maximum k such that if S is an (r-1)-set contained in a hyperedge of H, then is contained in at least distinct hyperedges of H. Given an r-graph F, we introduce the positive co-degree Turán number co + ex(n, F) as the maximum positive co-degree $δ^+_{r-1}$ (H) over all n-vertex r-graphs H that do not contain F as a subhypergraph. In this paper, we concentrate on the behavior of co + ex(n, F) for 3-graphs F. In particular, we determine asymptotics and bounds for several well-known concrete 3-graphs F (e.g. $K^-_4$ and the Fano plane). Here, we also show that, for r-graphs, the limit γ + (F)≔ lim$_{n→∞}$ $\frac{co^+ex(n, F)}{n}$ exists, and “jumps” from 0 to 1/r, that is, it never takes on values in the interval . Moreover, we characterize which r-graphs F have γ + (F) = 0. Our motivation comes primarily from the study of (ordinary) co-degree Turán numbers where a number of results have been proved that inspire our results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

MacroSheds: A synthesis of long-term biogeochemical, hydroclimatic, and geospatial data from small watershed ecosystem studies

The US Federal Government supports hundreds of watershed monitoring efforts from which solute fluxes can be calculated. Although instrumentation and methods vary between studies, the data collected and their motivating questions are remarkably similar. Nevertheless, little effort toward their compilation has previously been made. The MacroSheds project has developed a future-friendly system for harmonizing daily time series of streamflow, precipitation, and solute chemistry from 169+ watersheds, and supplementing each with watershed attributes. Here, we describe the breadth of MacroSheds data, and detail the steps involved in rendering each data product. We provide recommendations for usage and discuss when other datasets might be more suitable. The MacroSheds dataset is an unprecedented resource for watershed science, and for hydrology, as a small-watershed supplement to existing collections of streamflow predictors, like CAMELS and GAGES-II. The MacroSheds platform includes a web dashboard for visualization and an R package for data access and analysis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Oxides and Nitrides with Asymmetric Pore Structure from Block Copolymer Co–Assembly and Non–Solvent Induced Phase Separation

Materials combining an asymmetric pore structure with mesopores everywhere enable high surface area accessibility and fast transport, making them attractive for e.g., energy conversion and storage applications. Block copolymer (BCP)/inorganic precursor co-assembly combined with non-solvent induced phase separation (NIPS) provides a route to materials in which a mesoporous top surface layer merges into an asymmetric support with graded porosity along the film normal and mesopores throughout. Here, the co-assembly and non-solvent-induced phase separation (CNIPS) of poly(isoprene)-b-poly(styrene)-b-poly(4-vinylpyridine) (ISV) triblock terpolymer and titanium dioxide (TiO 2 ) sol-gel nanoparticlesare reported. Heat-treatment in air results in free-standing asymmetric porous TiO 2 . Further thermal processing in ammonia results in free-standing asymmetric porous titanium nitride (TiN). processing changes alter structural membrane characteristics is demonstrated. Changing the CNIPS evaporation time results in various membrane cross-sections ( finger-like to sponge-like). Further, oxide and nitride material composition, crystallinity, and porosity are tuned by varying thermal processing conditions. Finally, thermal processing condition effects are probed on phase-pure asymmetric nitride membrane behavior using cyclic voltammetry to elucidate their influence, e.g., on specific capacitance. Results provide further insights into improving asymmetric and porous materials for applications including energy conversion and storage, separation, and catalysis and motivate a further expansion of CNIPS to other (in)organic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗