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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Reactions of the ˙NO 3 radical with nuclear extraction ligands in alkane solution

Here, the reactivity of the nitrate radical (NO 3 ˙) with organophosphorus and amidic actinide and lanthanide complexing agents of interest to nuclear solvent extraction applications was measured, resulting in the first-ever reported bimolecular rate constants for this radicals’ reactions in dodecane solution. The order of reactivity for neutral organophosphorus compounds showed faster rate constants with increasing electron density on the phosphoryl phosphorus atom, indicating an increasing facility for electron abstraction reactions occurring in addition to H-atom abstraction from the ligand alkane chains. The only acidic organophosphorus compound investigated, HEH[EHP], showed low reactivity with the NO 3 ˙ radical, attributed to its dimerization in this non-polar solvent. Amide ligand reaction rates were faster than for organophosphorus molecules, suggesting more facile H-atom abstraction from carbonyl activated methylene and amyl groups. While all rate constants were slower than the diffusion-limited rate they were still rapid enough to result in significant oxidation of solvent extraction ligands in dodecane solution.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2021

QuaSiMo: A composable library to program hybrid workflows for quantum simulation

Abstract A composable design scheme is presented for the development of hybrid quantum/classical algorithms and workflows for applications of quantum simulation. The proposed object‐oriented approach is based on constructing an expressive set of common data structures and methods that enables programming of a broad variety of complex hybrid quantum simulation applications. The abstract core of the scheme is distilled from the analysis of the current quantum simulation algorithms. Subsequently, it allows synthesis of new hybrid algorithms and workflows via the extension, specialisation, and dynamic customisation of the abstract core classes defined by the proposed design. The design scheme is implemented using the hardware‐agnostic programming language QCOR into the QuaSiMo library. To validate the implementation, the authors test and show its utility on commercial quantum processors from IBM and Rigetti, running some prototypical quantum simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

New reactions of diazene and related species for modelling combustion of amine fuels

Potential energy surfaces for reactions involving N 2 H 2 isomers of diazene (diimide) have been explored using density functional theory, with energies based on coupled-cluster theory. A focus is on processes that create or consume these species, and isomerisation between the E (trans) and Z (cis) forms of HNNH. Furthermore, these include isomerisation and dissociation pathways for HNNH, addition of H atoms to form N 2 H 3 , abstraction by H atoms yielding short-lived NNH, and abstraction reactions of H with N 2 H 3 . Transition state and capture theories are applied for high-pressure-limiting behaviour, while low-pressure and falloff regions are characterised via the methods of Troe and coworkers. Rate constants and thermochemistry are provided to improve models of diamine chemistry, relevant to the combustion of NH 3 especially at high concentrations, high pressures or under reducing conditions. Results indicate that amine radical recombination mainly yields the E HNNH isomer, while H-abstraction from N 2 H 3 results in E HNNH and H 2 NN. However, at elevated temperature E → Z isomerisation becomes competitive, and Z HNNH, being more reactive, acts to enhance the diazene consumption rate.

10 SYNTHETIC FUELS↗
DOE OSTI2022

Kinetics and selectivity of methane oxidation on an IrO 2 (110) film

Undercoordinated, bridging O-atoms (O br ) are highly active as H-acceptors in alkane dehydrogenation on IrO 2 (110) surfaces but transform to HO br groups that are inactive toward hydrocarbons. The low C–H activity and high stability of the HO br groups cause the kinetics and product selectivity during CH 4 oxidation on IrO 2 (110) to depend sensitively on the availability of O br atoms prior to the onset of product desorption. From temperature programmed reaction spectroscopy (TPRS) and kinetic simulations, we identified two O br -coverage regimes that distinguish the kinetics and product formation during CH 4 oxidation on IrO 2 (110). Under excess O br conditions, when the initial O br coverage is greater than that needed to oxidize all the CH 4 to CO 2 and HO br groups, complete CH 4 oxidation is dominant and produces CO 2 in a single TPRS peak between 450 and 500 K. However, under O br -limited conditions, nearly all the initial O br atoms are deactivated by conversion to HO br or abstracted after only a fraction of the initially adsorbed CH 4 oxidizes to CO 2 and CO below 500 K. Thereafter, some of the excess CH x groups abstract H and desorb as CH 4 above ~500 K while the remainder oxidize to CO 2 and CO at a rate that is controlled by the rate at which Obr atoms are regenerated from HObr during the formation of CH 4 and H 2 O products. We also show that chemisorbed O-atoms ('on-top O') on IrO 2 (110) enhance CO 2 production below 500 K by efficiently abstracting H from Obr atoms and thereby increasing the coverage of O br atoms available to completely oxidize CH x groups at low temperature. Furthermore, our results provide new insights for understanding factors which govern the kinetics and selectivity during CH 4 oxidation on IrO 2 (110) surfaces.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Data Science Infrastructure SOFTWARE

LANL science workflows generate complex data sets and ensembles of data requiring significant compute and storage resources. The Data Science Infrastructure (DSI) project focuses on data-driven approaches to make data more readily available to LANL projects. DSI workflows leverage metadata stored in data-agnostic databases, supported by an abstraction layer API to simplify searching and accessing data across simulation runs, experimental runs, filesystems and environments. The abstraction layer API allows the user to query a range of data types: raw output, processed data, configuration data, machine learning models, performance data, etc. In addition to the abstraction backend API, the DSI project is developing client-driven query APIs and UIs to support specific user workflows.

Turton, Terece↗
DOE OSTI2024

Exploring the impact of vibrational cavity coupling strength on ultrafast CN + c -C 6 H 12 reaction dynamics

Abstract Molecular polaritons, hybrid light-matter states resulting from strong cavity coupling of optical transitions, may provide a new route to guide chemical reactions. However, demonstrations of cavity-modified reactivity in clean benchmark systems are still needed to clarify the mechanisms and scope of polariton chemistry. Here, we use transient absorption to observe the ultrafast dynamics of CN radicals interacting with a cyclohexane ( c -C 6 H 12 ) and chloroform (CHCl 3 ) solvent mixture under vibrational strong coupling of a C–H stretching mode of c- C 6 H 12 . By modulating the c -C 6 H 12 :CHCl 3 ratio, we explore how solvent complexation and hydrogen (H)-abstraction processes proceed under collective cavity coupling strengths ranging from 55 to 85 cm −1 . Reaction rates remain unchanged for all extracavity, on-resonance, and off-resonance cavity coupling conditions, regardless of coupling strength. These results suggest that insufficient vibrational cavity coupling strength may not be the determining factor for the negligible cavity effects observed previously in H-abstraction reactions of CN with CHCl 3 .

Chen, Liying↗
DOE OSTI2022

Developing a low-cost renewable supply of hydrogen with high-temperature electrochemistry

Abstract Producing inexpensive hydrogen using electricity to split water or to extract hydrogen from hydrocarbon compounds is a two-sided coin: one side is obtaining and exploiting low-cost, emissions-free energy sources while the opposite side is establishing low-cost robust, durable, and efficient materials for the conversion processes. This article explores the materials needed for water splitting electrolysis, electrochemical abstraction of hydrogen from light alkanes, and looping thermal-chemical reaction processes that typically form and then dissociate an acid compound in a two- or three-step process. The focus is on the R&D needs of materials that are used for high-temperature electrochemistry, focusing on solid-oxide, ion-conducting cell materials sets (SOECs). To exploit the availability of low-cost electricity, these materials must stand up to cyclic operations. They also must be durable for years of service to reduce operating and maintenance costs, and they must achieve high conversion efficiencies to avoid large, energy-intensive recycle loops. Graphical abstract

Boardman, Richard D.↗
DOE OSTI2024

Chamber studies of OH + dimethyl sulfoxide and dimethyl disulfide: insights into the dimethyl sulfide oxidation mechanism

Abstract. The oxidation of dimethyl sulfide (DMS) in the marine atmosphere represents an important natural source of non-sea-salt sulfate aerosol, but the chemical mechanisms underlying this process remain uncertain. While recent studies have focused on the role of the peroxy radical isomerization channel in DMS oxidation, this work revisits the impact of the other channels (OH addition and OH abstraction followed by bimolecular RO2 reaction) on aerosol formation from DMS. Due to the presence of common intermediate species, the oxidation of dimethyl sulfoxide (DMSO) and dimethyl disulfide (DMDS) can shed light on these two DMS reaction channels; they are also both atmospherically relevant species in their own right. This work examines the OH oxidation of DMSO and DMDS, using chamber experiments monitored by chemical ionization mass spectrometry and aerosol mass spectrometry to study the full range of sulfur-containing products across a range of NO concentrations. The oxidation of both compounds is found to lead to rapid aerosol formation (which does not involve the intermediate formation of SO2), with a substantial fraction (14 %–47 % S yield for DMSO and 5 %–21 % for DMDS) of reacted sulfur ending up in the particle phase and the highest yields observed under elevated NO conditions. Aerosol is observed to consist mainly of sulfate, methanesulfonic acid, and methanesulfinic acid. In the gas phase, the NOx dependence of several products, including SO2 and S2-containing organosulfur species, suggest reaction pathways not included in current mechanisms. Based on the commonalities with the DMS oxidation mechanism, DMSO and DMDS results are used to reconstruct DMS aerosol yields; these reconstructions roughly match DMS aerosol yield measurements from the literature but differ in composition, underscoring remaining uncertainties in sulfur chemistry. This work indicates that both the abstraction and addition channels contribute to rapid aerosol formation from DMS and highlights the need for more study into the fate of small sulfur radical intermediates (e.g., CH3S, CH3SO2, and CH3SO3) that are thought to play central roles in the DMS oxidation mechanism.

Goss, Matthew B. (ORCID:0000000226885463)↗
DOE OSTI2025

Supporting Information - How Can Crop Production Adapt to growing groundwater restrictions in the West?

Abstract This data plan outlines the structure and content of datasets generated and utilized in the research presented in the manuscript abstract. Groundwater overdraft has led to serious water supply issues in the US West. Most western states manage groundwater use through a permitting system, but California has only recently begun to restrict groundwater use statewide with the 2014 passage of groundwater restrictions which target the elimination of groundwater overdraft practices by 2042. With groundwater extraction curtailed, crop production in the US West (a $95 billion industry annually) will be affected, and appropriate response strategies will be needed to ensure minimal disruption to food production and the regional economy. In this paper, we explore the adoption of alternative adaptive responses: (a) deficit irrigation; (b) switching to less water-intensive crops; (c) changing the extent of irrigated land (including fallowing); and (d) geographically shifting crop production. Employing an integrated modeling approach, we explicitly capture the interactions and feedbacks between local hydrology, changes in crop yields, crop and land use decision-making, changes in crop prices, and regional shifts in crop production. We find that the optimal adaptive response is spatially heterogeneous and comprises a portfolio of strategies. Southwestern states and California will be the most impacted by groundwater restrictions. The optimal responses in these states are to both adopt deficit irrigation strategies and reduce a portion of their irrigated croplands, resulting in a shift in crop production to northwestern states with a larger supply of water. The datasets detailed in this repository represent the output from these integrated models, specifically designed to support the analysis and visualization presented in the manuscript and supplemental information. These datasets, used in conjunction with the scripts available at our associated GitHub repository (https://github.com/pches/Femeena_etal_How_can_crop_production_adapt), enable the reproduction of figures and facilitate a comprehensive understanding of the optimal adaptive strategies in agriculture for mitigating water stress under varying groundwater extraction scenarios, as outlined in the abstract.

DNDCe↗
DOE OSTI2025

Supporting Information - How Can Crop Production Adapt to growing groundwater restrictions in the West?

Abstract This data plan outlines the structure and content of datasets generated and utilized in the research presented in the manuscript abstract. Groundwater overdraft has led to serious water supply issues in the US West. Most western states manage groundwater use through a permitting system, but California has only recently begun to restrict groundwater use statewide with the 2014 passage of groundwater restrictions which target the elimination of groundwater overdraft practices by 2042. With groundwater extraction curtailed, crop production in the US West (a $95 billion industry annually) will be affected, and appropriate response strategies will be needed to ensure minimal disruption to food production and the regional economy. In this paper, we explore the adoption of alternative adaptive responses: (a) deficit irrigation; (b) switching to less water-intensive crops; (c) changing the extent of irrigated land (including fallowing); and (d) geographically shifting crop production. Employing an integrated modeling approach, we explicitly capture the interactions and feedbacks between local hydrology, changes in crop yields, crop and land use decision-making, changes in crop prices, and regional shifts in crop production. We find that the optimal adaptive response is spatially heterogeneous and comprises a portfolio of strategies. Southwestern states and California will be the most impacted by groundwater restrictions. The optimal responses in these states are to both adopt deficit irrigation strategies and reduce a portion of their irrigated croplands, resulting in a shift in crop production to northwestern states with a larger supply of water. The datasets detailed in this repository represent the output from these integrated models, specifically designed to support the analysis and visualization presented in the manuscript and supplemental information. These datasets, used in conjunction with the scripts available at our associated GitHub repository (https://github.com/pches/Femeena_etal_How_can_crop_production_adapt), enable the reproduction of figures and facilitate a comprehensive understanding of the optimal adaptive strategies in agriculture for mitigating water stress under varying groundwater extraction scenarios, as outlined in the abstract.

DNDCe↗
DOE OSTI2025

Supporting Information - How Can Crop Production Adapt to growing groundwater restrictions in the West?

Abstract This data plan outlines the structure and content of datasets generated and utilized in the research presented in the manuscript abstract. Groundwater overdraft has led to serious water supply issues in the US West. Most western states manage groundwater use through a permitting system, but California has only recently begun to restrict groundwater use statewide with the 2014 passage of groundwater restrictions which target the elimination of groundwater overdraft practices by 2042. With groundwater extraction curtailed, crop production in the US West (a $95 billion industry annually) will be affected, and appropriate response strategies will be needed to ensure minimal disruption to food production and the regional economy. In this paper, we explore the adoption of alternative adaptive responses: (a) deficit irrigation; (b) switching to less water-intensive crops; (c) changing the extent of irrigated land (including fallowing); and (d) geographically shifting crop production. Employing an integrated modeling approach, we explicitly capture the interactions and feedbacks between local hydrology, changes in crop yields, crop and land use decision-making, changes in crop prices, and regional shifts in crop production. We find that the optimal adaptive response is spatially heterogeneous and comprises a portfolio of strategies. Southwestern states and California will be the most impacted by groundwater restrictions. The optimal responses in these states are to both adopt deficit irrigation strategies and reduce a portion of their irrigated croplands, resulting in a shift in crop production to northwestern states with a larger supply of water. The datasets detailed in this repository represent the output from these integrated models, specifically designed to support the analysis and visualization presented in the manuscript and supplemental information. These datasets, used in conjunction with the scripts available at our associated GitHub repository (https://github.com/pches/Femeena_etal_How_can_crop_production_adapt), enable the reproduction of figures and facilitate a comprehensive understanding of the optimal adaptive strategies in agriculture for mitigating water stress under varying groundwater extraction scenarios, as outlined in the abstract.

DNDCe↗
DOE OSTI2024

Graph-Based Representations and Applications to Process Simulation

Rapid and robust convergence of a process flowsheet is critical to enable large-scale simulations that address core scientific questions related to process design, optimization, and sustainability. However, due to the highly coupled and nonlinear nature of chemical processes, efficiently solving a flowsheet remains a challenge. In this work, we show that graph representations of the underlying physical phenomena in unit operations may help identify potential avenues to systematically reformulate the network of equations and enable more robust topology-based convergence of flowsheets. To this end, we developed graph abstractions of the governing equations of vapor-liquid and liquid-liquid equilibrium separation equipment. These graph abstractions consist of a mesh of interconnected variable nodes and equation nodes that are systematically generated through PhenomeNode, a new open-source library in Python developed in this study. We show that partitioning the graph into separate mass, energy, and equilibrium subgraphs can help decouple nonlinearities and guide decomposition algorithms. By employing the graph abstraction on an industrial separation process for separating glacial acetic acid from water, we implemented a new block decomposition scheme in BioSTEAM and demonstrated that this can accelerate convergence over a traditional sequential modular approach.

Distillation↗
DOE OSTI2021

Productive Programming of Distributed Systems with the SHAD C++ Library

High-performance computing (HPC) is often perceived as a matter of making large-scale systems (e.g., clusters) run as fast as possible, regardless the required programming effort. However, the idea of "bringing HPC to the masses" has recently emerged. Inspired by this vision, we have designed SHAD, the Scalable High-performance Algorithms and Data-structures library. SHAD is open source software, written in C++, for C++ developers. Unlike other HPC libraries for distributed systems, which rely on SPMD models, SHAD adopts a shared-memory programming abstraction, to make C++ programmers feel at home. Underneath, SHAD manages tasking and data-movements, moving the computation where data resides and taking advantage of asynchrony to tolerate network latency. At the bottom of his stack, SHAD can interface with multiple runtime systems: this not only improves developer’s productivity, by hiding the complexity of such software and of the underlying hardware, but also greatly enhance code portability. Thanks to its abstraction layers, SHAD can indeed target different systems, ranging from laptops to HPC clusters, without any need for modifying the user-level code. We have prototyped and open-sourced the implementation of (a subset of) the C++ standard library (STL) targeting multi-node HPC clusters. Our work allows plain STL-based C++ code to scale on HPC systems, with no need for rewriting the code to exploit the complex hardware. SHAD is available under Apache v2 License at https://github.com/pnnl/SHAD. In this paper we overview the design of the SHAD library, depicting its main components: runtime systems abstractions for tasking; parallel and distributed data-structures; STL-compliant interfaces and algorithms.

Castellana, Vito G.↗
DOE OSTI2021

Reusability First: Toward FAIR Workflows

The FAIR principles of open science (Findable, Accessible, Interoperable, and Reusable) have had transformative effects on modern large-scale computational science. In particular, they have encouraged more open access to and use of data, an important consideration as collaboration among teams of researchers accelerates and the use of workflows by those teams to solve problems increases. How best to apply the FAIR principles to workflows themselves, and software more generally, is not yet well understood. We argue that the software engineering concept of technical debt management provides a useful guide for application of those principles to workflows, and in particular that it implies reusability should be considered as ‘first among equals’. Moreover, our approach recognizes a continuum of reusability where we can make explicit and selectable the tradeoffs required in workflows for both their users and developers.To this end, we propose a new abstraction approach for reusable workflows, with demonstrations for both synthetic workloads and real-world computational biology workflows. Through application of novel systems and tools that are based on this abstraction, these experimental workflows are refactored to rightsize the granularity of workflow components to efficiently fill the gap between end-user simplicity and general customizability. Our work makes it easier to selectively reason about and automate the connections between trade-offs across user and developer concerns when exposing degrees of freedom for reuse. Additionally, by exposing fine-grained reusability abstractions we enable performance optimizations, as we demonstrate on both institutional-scale and leadership-class HPC resources.

Wolf, Matthew↗
DOE OSTI2023

System and method for adaptive object-oriented sensor fusion for environmental mapping

The present disclosure relates to a mapping system adapted for detecting objects in an environmental scene, by scanning an environmental scene with propagating energy, and receiving reflected energy back from objects present in the environmental scene, in a prioritized manner, for later use. The system may comprise an imaging subsystem which includes a detection and ranging subsystem for initially identifying primitive objects in the environmental scene. The imaging subsystem may also include an identification and mapping subsystem for prioritizing the primitive objects for further scanning and analysis, to ultimately identify one or more of the primitive objects as one or more abstract objects. An environmental model, updated in real time, is used to maintain a map of the primitive objects and the known abstract objects within the environmental scene, as new primitive objects and new abstract objects are obtained with repeated scans of the environmental scene.

Panas, Robert Matthew↗