Search NASA⌕ Search

SEARCH · Search NASA

Results for “Compiler”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Simulating nonlinear optical processes on a superconducting quantum device

Simulating plasma physics on quantum computers is difficult because most problems of interest are nonlinear, but quantum computers are not naturally suitable for nonlinear operations. In weakly nonlinear regimes, plasma problems can be modelled as wave–wave interactions. In this paper, we develop a quantization approach to convert nonlinear wave–wave interaction problems to Hamiltonian simulation problems. We demonstrate our approach using two qubits on a superconducting device. Unlike a photonic device, a superconducting device does not naturally have the desired interactions in its native Hamiltonian. Nevertheless, Hamiltonian simulations can still be performed by decomposing required unitary operations into native gates. To improve experimental results, we employ a range of error-mitigation techniques. Apart from readout error mitigation, we use randomized compilation to transform undiagnosed coherent errors into well-behaved stochastic Pauli channels. Moreover, to compensate for stochastic noise, we rescale exponentially decaying probability amplitudes using rates measured from cycle benchmarking. We carefully consider how different choices of product-formula algorithms affect the overall error and show how a trade-off can be made to best utilize limited quantum resources. This study provides an example of how plasma problems may be solved on near-term quantum computing platforms.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Performing fully parallel constraint logic programming on a quantum annealer

A quantum annealer exploits quantum effects to solve a particular type of optimization problem. The advantage of this specialized hardware is that it effectively considers all possible solutions in parallel, thereby potentially outperforming classical computing systems. However, despite quantum annealers having recently become commercially available, there are relatively few high-level programming models that target these devices. In this article, we show how to compile a subset of Prolog enhanced with support for constraint logic programming into a two-local Ising-model Hamiltonian suitable for execution on a quantum annealer. In particular, we describe the series of transformations one can apply to convert constraint logic programs expressed in Prolog into an executable form that bears virtually no resemblance to a classical machine model yet that evaluates the specified constraints in a fully parallel manner. We evaluate our efforts on a 1,095-qubit D-Wave 2X quantum annealer and describe the approach's associated capabilities and shortcomings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Single Quadrupole Multiple Fragment Ion Monitoring Quantitative Mass Spectrometry

Single quadrupole mass spectrometry (MS) with enhanced in-source multiple fragment ion monitoring was designed to perform high sensitivity quantitative mass analyses. Enhanced in-source fragmentation amplifies fragmentation from traditional soft electrospray ionization producing fragment ions that have been found to be identical to those generated in tandem MS. We have combined enhanced in-source fragmentation data with criteria established by the European Union Commission Directive 2002/657/EC for electron ionization single quadrupole quantitative analysis to perform quantitative analyses. These experiments were performed on multiple types of complex samples that included a mixture of 50 standards, as well as cell and plasma extracts. The dynamic range for these quantitative analyses was comparable to triple quadrupole multiple reaction monitoring (MRM) analyses at up to 5 orders of magnitude with the cell and plasma extracts showing similar matrix effects across both platforms. Amino acid and fatty acid measurements performed from certified NIST 1950 plasma with isotopically labeled standards demonstrated accuracy in the range of 91–110% for the amino acids, 76–129% for the fatty acids, and good precision (coefficient of variation <10%). To enhance specificity, a newly developed correlated ion monitoring algorithm was designed to facilitate these analyses. This algorithm autonomously processes, aligns, filters, and compiles multiple ions within one chromatogram enabling both precursor and in-source fragment ions to be correlated within a single chromatogram, also enabling the detection of coeluting species based on precursor and fragment ion ratios. Single quadrupole instrumentation can provide MRM level quantitative performance by monitoring/correlating precursor and fragment ions facilitating high sensitivity analysis on existing single quadrupole instrumentation that are generally inexpensive, easy to operate, and technically less complex.

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

Predicting Protein–Polymer Block Copolymer Self-Assembly from Protein Properties

Protein–polymer bioconjugate self-assembly has attracted a great deal of attention as a method to fabricate protein nanomaterials in solution and the solid state. To identify protein properties that affect phase behavior in protein–polymer block copolymers, a library of 15 unique protein- b -poly(N-isopropylacrylamide) (PNIPAM) copolymers comprising 11 different proteins was compiled and analyzed. Many attributes of phase behavior are found to be similar among all studied bioconjugates regardless of protein properties, such as formation of micellar phases at high temperature and low concentration, lamellar ordering with increasing temperature, and disordering at high concentration, but several key protein-dependent trends are also observed. In particular, hexagonal phases are only observed for proteins within the molar mass range 20–36 kDa, where ordering quality is also significantly enhanced. While ordering is generally found to improve with increasing molecular weight outside of this range, most large bioconjugates exhibited weaker than predicted assembly, which is attributed to chain entanglement with increasing polymer molecular weight. Additionally, order–disorder transition boundaries are found to be largely uncorrelated to protein size and quality of ordering. However, the primary finding is that bioconjugate ordering can be accurately predicted using only protein molecular weight and percentage of residues contained within β sheets. This model provides a basis for designing protein–PNIPAM bioconjugates that exhibit well-defined self-assembly and a modeling framework that can generalize to other bioconjugate chemistries.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Anion Exchange in Cationic Frameworks: Structures of Channel-Forming Triarylpyrylium Tetrafluoroborate Salts

The crystal structure of a co-crystal of 2,4,6-tris(4-methylphenyl)pyridine and 2,4,6-tris(4-methylphenyl)pyrylium revealed a pseudohexagonal motif assembled from π-stacked helices that enclose 1-D channels containing disordered tetrafluoroborate counterions and solvent molecules. Though convoluted by disorder, aperiodicity, and complex twinning patterns, further investigation was motivated by the unique packing arrangement of this material, which enables solid-state anion diffusion, while resisting dissolution in water. Such properties are ideal for the development of anion exchange materials that can be employed for the remediation of agricultural and nuclear waste. Here, to develop a more complete understanding of the intermolecular interactions that give rise to this helical motif, we have compiled and analyzed the local interactions and extended structural motifs of 19 pore- and channel-forming 2,4,6-triarylpyrylium crystal structures. Here, three conserved local interactions were identified, including C–H···X– interactions, the rhombic binding pocket, and four-ring antiparallel dimerization. Development of this library of interaction motifs rationalizes the packing arrangement of the co-crystal and contributes to the informed design of anion exchange materials.

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

Solid Electrolytes in the Spotlight

This virtual issue is targeted to students and researchers, and highlights 32 research articles published over the past 5 years (from July 2016 to July 2021) in Chemistry of Materials (CM). Here, the compilation of papers summarizes the latest advances in the field of solid-state electrolytes for lithium (Li)-, sodium (Na)-, and multivalent-ion (not among the 32 articles discussed) all-solid-state batteries (ASSBs), with a focus on inorganic materials and excluding hybrid systems, e.g., polymer/ceramic composites or systems including liquid media. A total of 125 articles reporting exciting experimental and/or theoretical findings on solid electrolytes were considered for this issue. During 2017–2019, there were about 25–30 papers published per year on this topic, but 2020 and 2021 saw a significant increase, with 26 publications in the first half of 2021 alone. Submissions came from many countries around the world, as shown in Figure 1. While most papers were led by research groups located in the United States, Germany and Japan follow closely, and Austria, the United Kingdom, Canada, and China are also well represented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Materials Synthesis Insights from Scientific Literature via Text Extraction and Machine Learning

In the past several years, Materials Genome Initiative (MGI) efforts have produced myriad examples of computationally designed materials in the fields of energy storage, catalysis, thermoelectrics, and hydrogen storage as well as large data resources that are used to screen for potentially transformative compounds. The bottleneck in high-Throughput materials design has thus shifted to materials synthesis, which motivates our development of a methodology to automatically compile materials synthesis parameters across tens of thousands of scholarly publications using natural language processing techniques. To demonstrate our framework's capabilities, we examine the synthesis conditions for various metal oxides across more than 12 thousand manuscripts. We then apply machine learning methods to predict the critical parameters needed to synthesize titania nanotubes via hydrothermal methods and verify this result against known mechanisms. Lastly, we demonstrate the capacity for transfer learning by using machine learning models to predict synthesis outcomes on materials systems not included in the training set and thereby outperform heuristic strategies.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Assessing High-Throughput Descriptors for Prediction of Transparent Conductors

The growth of materials databases has offered significant quantities of data to mine for new energy materials using high-throughput screening methodologies. One application of interest to energy and optoelectronics is the prediction of new high performing p-type transparent conductors (TCs). Yet, screening methods for such materials have never been validated over the breadth of computed materials properties. In this study, we compile an experimental data set of 74 bulk crystal structures corresponding to known state-of-the-art n-type and p-type TCs and compute a series of corresponding computational descriptor properties. Our goals are to (1) compare computational descriptors to experimentally demonstrated properties of real materials in the data set, (2) determine the ability of ground state, density functional theory (DFT)-based computational screening methodologies to identify these experimentally realized TCs, and (3) use this understanding to estimate reasonable screening cutoffs for four commonly used descriptors. First, stability calculations demonstrate that most materials in the data set have an energy above the convex hull ( E hull ) of <100 meV/atom, and we also propose a Pourbaix analysis technique to estimate moisture stability. Second, we find a lenient cutoff for the DFT PBE band gap of 0.5 eV is sufficient to include a majority of the wide gap candidates and exclude narrow gap compounds. Next, the effective mass, m *, is found to correlate weakly to conductivity in the p-type materials as compared with n-type materials, which may motivate an increase in the m * cutoff as well. Lastly, we perform an uncertainty analysis and literature comparison for the branch point energy (BPE), a qualitative descriptor for dopability. We discover the BPEs of most n-type materials to lie near the conduction band and those of most p-type materials to lie at midgap; this is a significant distinction, implying BPE to be a more definitive descriptor for n-type TC materials. By assessing the validity of this simple screening methodology via comparing experimental data to computational descriptors, we aim to motivate and strengthen future materials discovery efforts in the field of transparent conductors and beyond.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Localized Conduction Channels in Memristors

Since the early 2000s, the impending end of Moore’s scaling, as the physical limits to shrinking transistors have been approached, has fueled interest in improving the functionality and efficiency of integrated circuits by employing memristors or two-terminal resistive switches. Formation (or avoidance) of localized conducting channels in many memristors, often called “filaments”, has been established as the basis for their operation. While we understand some qualitative aspects of the physical and thermodynamic origins of conduction localization, there are not yet quantitative models that allow us to predict when they will form or how large they will be. Here, in this work, we compile observations and explanations of channel formation that have appeared in the literature since the 1930s, show how many of these seemingly unrelated pieces fit together, and outline what is needed to complete the puzzle. This understanding will be a necessary predictive component for the design and fabrication of post-Moore’s-era electronics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Hydrogen Sulfide Capture: From Absorption in Polar Liquids to Oxide, Zeolite, and Metal–Organic Framework Adsorbents and Membranes

We present that hydrogen sulfide removal is a long-standing economic and environmental challenge faced by the oil and gas industries. H 2 S separation using reactive and non-reactive absorption and adsorption, membranes, and cryogenic distillation are reviewed. A detailed discussion on new developments in adsorbents, such as metal oxides, metals, metal–organic frameworks, zeolites, carbon-based materials, and composite materials, absorbents, such as ionic liquids, and membrane technologies for H 2 S removal, is presented. Here, this review attempts to exhaustively compile the existing literature on sour gas sweetening and to identify promising areas for future developments in the field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Elucidation of Structure and Physical Properties of Pyrolytic Sugar Oligomers Derived from Cellulose Depolymerization/Dehydration Reactions: A Density Functional Theory Study

Fast pyrolysis of lignocellulosic materials is a promising research area to produce renewable fuels and chemicals. Dehydration is known to be among the most important reaction families during cellulose pyrolysis; water is the most important product. Together with water, dehydration reactions also form a range of poorly known oligomer species of varying molecular sizes, often collected as part of bio-oil water-soluble (WS) fraction. In this work, we used electronic structure calculations to evaluate the relative thermodynamic stabilities of several oligomer species resulting from up to three consecutive dehydration events from cellulose depolymerization intermediates. A library of the thermodynamically favored candidate molecular structures was compiled. Results revealed that most of the water molecules are eliminated from the non-reducing end, forming thermodynamically more stable conjugated compounds. This is consistent with results reported by other researchers in literature where dehydration reactions occur preferably at the non-reducing ends of oligomers. The physical-chemical properties of the proposed structures were estimated using quantitative structure-property relationships (QSPRs) and quantitative property-property relationships (QPPRs). The anhydro-sugars derived from cellulose are often blamed for coke formation during bio-oil hydrotreatment. Understanding their chemical structure could help to develop rational strategies to mitigate coke formation. Furthermore, the thermo-physical properties reported (boiling point, melting point, Gibb’s free energy of formation, enthalpy of formation, and solubility parameters among others) are also fundamental to conducting first principle engineering calculations to design and analyze new pyrolysis reactors and bio-oil up-grading units.

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

Review of Carbonaceous Annealing Effects on O 2 and CO 2 Coal Reactivity

Coal is, and will remain for the foreseeable future, a critical energy production resource. Advanced models of coal conversion behavior in air and oxy-coal environments enhance the boiler operational efficiency and design optimization. Although coal conversion models have continuously improved over decades of research, not all aspects of coal particle heating and conversion have received equal treatment. Coal particle annealing is one aspect of the coal conversion process that is simultaneously highly sensitive to the conversion environment, exceptionally impactful on coal chemistry, and frequently neglected in coal models. However, the current body of literature has explored numerous aspects of coal annealing and has shed much light on a complex subject. In conclusion, this review fulfills two purposes: (1) to highlight quantitative observations from the literature and (2) to compile and make conveniently available a clean collection of literature data to facilitate future annealing models.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Methane Exhaust Measurements at Gathering Compressor Stations in the United States

Unburned methane entrained in exhaust from natural gas-fired compressor engines (“combustion slip”) can account for a substantial portion of station-level methane emissions. A novel in-stack, tracer gas method was coupled with Fourier transform infrared (FTIR) species measurements to quantify combustion slip from natural gas compressor engines at 67 gathering and boosting stations owned or managed by nine “study partner” operators in 11 U.S. states. The mean methane emission rate from 63 four-stroke, lean-burn (4SLB) compressor engines was 5.62 kg/h (95% CI = 5.15–6.17 kg/h) and ranged from 0.3 to 12.6 kg/h. The mean methane emission rate from 39 fourstroke, rich-burn (4SRB) compressor engines was 0.40 kg/h (95% CI = 0.37– 0.42 kg/h) and ranged from 0.01 to 4.5 kg/h. Study results for 4SLB engines were lower than both the U.S. EPA compilation of air pollutant emission factors (AP-42) and Inventory of U.S. Greenhouse Gas Emissions and Sinks (GHGI) by 8 and 9%, respectively. Study results for 4SRB engines were 43% of the AP-42 emission factor and 8% of the GHGI emission factor, the latter of which does not distinguish between engine types. Total annual combustion slip from the U.S. natural gas gathering and boosting sector was modeled using measured emission rates and compressor unit counts from the U.S. EPA Greenhouse Gas Reporting Program. Modeled results [328 Gg/y (95% CI = 235–436 Gg/y) of unburned methane] would account for 24% (95% CI = 17–31%) of the 1391 Gg of methane emissions for “Gathering and Boosting Stations”, or 6% of the net emissions for “Natural Gas Systems” (5598 Gg) as reported in the 2020 U.S. EPA GHGI. In conclusion, gathering and boosting combustion slip emissions reported in the 2020 GHGI (374 Gg) fall within the uncertainty of this model.

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

Community Data Mining Approach for Surface Complexation Database Development

This paper presents a comprehensive data-to-model workflow, including a findable, accessible, interoperable, reusable (FAIR) community sorption database (newly developed LLNL Surface Complexation/Ion Exchange (L-SCIE) database) along with a data fitting workflow to efficiently optimize surface complexation reaction constants with multiple surface complexation model (SCM) constructs. This workflow serves as a universal framework to mine, compile, and analyze large numbers of published sorption data as well as to estimate reaction constants for parameterizing reactive transport models. Here the framework includes (1) data digitization from published papers, (2) data unification including unit conversions, and (3) data-model integration and reaction constant estimation using geochemical software PHREEQC coupled with the universal parameter estimation code PEST. We demonstrate our approach using an analysis of U(VI) sorption to quartz based on a first L-SCIE implementation, concluding that a multisite SCM construct with carbonate surface species yielded the best fit to community data. Surface complexation reaction constants extracted from this approach captured all available sorption data available in the literature and provided insight into previously published reaction constants and surface complexation model constructs. The L-SCIE sorption database presented herein allows for automating this approach across a wide range of metals and minerals and implementing novel machine learning approaches to reactive transport in the future.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2016

Water Use and Management in the Bakken Shale Oil Play in North Dakota

Oil and natural gas development in the Bakken shale play of North Dakota has grown substantially since 2008. This study provides a comprehensive overview and analysis of water quantity and management impacts from this development by (1) estimating water demand for hydraulic fracturing in the Bakken from 2008 to 2012; (2) compiling volume estimates for maintenance water, or brine dilution water; (3) calculating water intensities normalized by the amount of oil produced, or estimated ultimate recovery (EUR); (4) estimating domestic water demand associated with the large oil services population; (5) analyzing the change in wastewater volumes from 2005 to 2012; and (6) examining existing water sources used to meet demand. Water use for hydraulic fracturing in the North Dakota Bakken grew 5-fold from 770 million gallons in 2008 to 4.3 billion gallons in 2012. First-year wastewater volumes grew in parallel, from an annual average of 1 135 000 gallons per well in 2008 to 2 905 000 gallons in 2012, exceeding the mean volume of water used in hydraulic fracturing and surpassing typical 4-year wastewater totals for the Barnett, Denver, and Marcellus basins. Surprisingly, domestic water demand from the temporary oilfield services population in the region may be comparable to the regional water demand from hydraulic fracturing activities. Existing groundwater resources are inadequate to meet the demand for hydraulic fracturing, but there appear to be adequate surface water resources, provided that access is available.

Horner, R. M.↗
DOE OSTI2019

Criteria Air Pollutants and Greenhouse Gas Emissions from Hydrogen Production in U.S. Steam Methane Reforming Facilities

The global and U.S. domestic effort to develop a clean energy economy and curb environmental pollution incentivizes the use of hydrogen as a transportation fuel, owing to its zero tailpipe pollutant emissions and high fuel efficiency in fuel cell electric vehicles (FCEVs). However, the hydrogen production process is not emissions free. Conventional hydrogen production via steam methane reforming (SMR) is energy intensive, coproduces carbon dioxide, and emits air pollutants. Therefore, it is necessary to quantify the environmental impacts of SMR hydrogen production alongside the use-phase of FCEVs. This study fills the information gap, analyzing the greenhouse gas (GHG) and criteria air pollutant (CAP) emissions associated with hydrogen production in U.S. SMR facilities by compiling and matching the facility-reported GHG and CAP emissions data with facilities’ hydrogen production data. The actual amounts of hydrogen produced at U.S. SMR facilities are often confidential. Thus, we have developed four approaches to estimate the hydrogen production amounts. The resultant GHG and CAP emissions per MJ of hydrogen produced in individual facilities were aggregated to develop emission values for both a national median and a California state median. Lastly, this study also investigates the breakdown of facility emissions into combustion emissions and noncombustion emissions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

PubChemLite Plus Collision Cross Section (CCS) Values for Enhanced Interpretation of Nontarget Environmental Data

Finding relevant chemicals in the vast (known) chemical space is a major challenge for environmental and exposomics studies leveraging nontarget high resolution mass spectrometry (NT-HRMS) methods. Chemical databases now contain hundreds of millions of chemicals, yet many are not relevant. This article details an extensive collaborative, open science effort to provide a dynamic collection of chemicals for environmental, metabolomics, and exposomics research, along with supporting information about their relevance to assist researchers in the interpretation of candidate hits. The PubChemLite for Exposomics collection is compiled from ten annotation categories within PubChem, enhanced with patent, literature and annotation counts, predicted partition coefficient (logP) values, as well as predicted collision cross section (CCS) values using CCSbase. Monthly versions are archived on Zenodo under a CC-BY license, supporting reproducible research, and a new interface has been developed, including historical trends of patent and literature data, for researchers to browse the collection. This article details how PubChemLite can support researchers in environmental and exposomics studies, describes efforts to increase the availability of experimental CCS values, and explores known limitations and potential for future developments. The data and code behind these efforts are openly available.

PubChem↗
DOE OSTI2015

Sealing Shales versus Brittle Shales: A Sharp Threshold in the Material Properties and Energy Technology Uses of Fine-Grained Sedimentary Rocks

Fine-grained sedimentary rocks (shale and mudstone) play important roles in global CO 2 abatement efforts through their uses in carbon capture and storage (CCS), radioactive waste storage, and shale gas extraction. These different technologies, however, rely on seemingly conflicting premises regarding the sealing properties of shale and mudstone, suggesting that those rocks that lend themselves to hydrocarbon extraction may not be optimal seals for CCS or radioactive waste storage, and vice versa. In this paper, a compilation of experimental data on the properties of well-characterized shale and mudstone formations is used to demonstrate that clay mineral mass fraction, X clay , is a very important variable the controls key material properties of these formations and that a remarkably sharp threshold at X clay ~ 1/3 separates fine-grained rocks with very different properties. Finally, this threshold coincides with the predictions of a simple conceptual model of the microstructure of sedimentary rocks and is reflected in the uses of shale and mudstone formations for CCS, radioactive waste storage, and shale gas extraction.

58 GEOSCIENCES↗