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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

2018 LDRD Annual Report (Argonne National Laboratory)

Argonne National Laboratory’s Laboratory Directed Research and Development (LDRD) program encourages the development of novel technical concepts, enhances the Laboratory’s research and development (R&D) capabilities, and enables pursuit of strategic laboratory goals. Argonne’s LDRD projects are proposal based and peer reviewed, supporting ideas that require advanced exploration so they can be sufficiently developed to pursue support through normal programmatic channels. Among the aims of the projects supported by the LDRD program are the establishment of engineering proofs of principle, assessment of design feasibility for prospective facilities, development of instrumentation or computational methods or systems, and discoveries in fundamental science and exploratory development. All LDRD projects have demonstrable ties to one or more of the science, energy, environment, and national security missions of the U.S. Department of Energy (DOE) and its National Nuclear Security Administration (NNSA), and many are also relevant to the missions of other federal agencies that sponsor work at Argonne. A natural consequence of the more “applied” type projects is their concurrent relevance to industry. The LDRD program is managed in overarching portfolios, each containing multiple projects each fiscal year. The LDRD Prime portfolio is further divided into strategic focus areas aligned with Argonne’s strategic plan. The largest component of Argonne’s program is LDRD Prime, which emphasizes R&D explicitly aligned with Laboratory major initiatives in support of Argonne’s strategic plan. The choice of Focus Areas under the LDRD Prime component reflects the major initiatives; the state of development of relevant technical fields; the potential value of advancing those fields to DOE/NNSA and the nation; and the compatibility of the fields with existing facilities, capabilities, and staff expertise at Argonne. Focus Areas with projects that ended in FY18 are: Advanced Computing, Biological and Environmental Science Capability Development, Energy Manufacturing Science and Engineering, Hard X-ray Sciences, Materials and Chemistry, Securing Energy and Critical Resources, and The Universe as Our Laboratory (ULab).

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Carbon flux estimates are sensitive to data source: a comparison of field and lab temperature sensitivity data

Abstract A large literature exists on mechanisms driving soil production of the greenhouse gases CO 2 and CH 4 . Although it is common knowledge that measurements obtained through field studies vs. laboratory incubations can diverge because of the vastly different conditions of these environments, few studies have systematically examined these patterns. These data are used to parameterize and benchmark ecosystem- to global-scale models, which are then susceptible to the biases of the source data. Here, we examine how greenhouse gas measurements may be influenced by whether the measurement/incubation was conducted in the field vs. laboratory, focusing on CO 2 and CH 4 measurements. We use Q 10 of greenhouse gas flux (temperature sensitivity) for our analyses because this metric is commonly used in biological and Earth system sciences and is an important parameter in many modeling frameworks. We predicted that laboratory measurements would be less variable, but also less representative of true field conditions. However, there was greater variability in the Q 10 values calculated from lab-based measurements of CO 2 fluxes, because lab experiments explore extremes rarely seen in situ , and reflect the physical and chemical disturbances occurring during sampling, transport, and incubation. Overall, respiration Q 10 values were significantly greater in laboratory incubations (mean = 4.19) than field measurements (mean = 3.05), with strong influences of incubation temperature and climate region/biome. However, this was in part because field measurements typically represent total respiration (Rs), whereas lab incubations typically represent heterotrophic respiration (Rh), making direct comparisons difficult to interpret. Focusing only on Rh-derived Q 10 , these values showed almost identical distributions across laboratory ( n = 1110) and field ( n = 581) experiments, providing strong support for using the former as an experimental proxy for the latter, although we caution that geographic biases in the extant data make this conclusion tentative. Due to a smaller sample size of CH 4 Q 10 data, we were unable to perform a comparable robust analysis, but we expect similar interactions with soil temperature, moisture, and environmental/climatic variables. Our results here suggest the need for more concerted efforts to document and standardize these data, including sample and site metadata.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

[Re] Drivers of evapotranspiration from boreal wildfires

Computational reproducibility is a difficult challenge across science. I attempted to use R 3.6.1 to reproduce linear model fits, done originally using v2.6.0 for a 2009 paper on the drivers of large-scale forest evapotranspiration after wildfire. Model outputs were largely identical, aside from minor formatting changes, except for one–out of 12 total– regression in which the median residual value changed very slightly (in the sixth decimal place). I suggest that this essentially successful reproducibility is due to the relative simplicity of the script, its use of only base R functions, and R’s historically conservative approach to breaking changes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Exact reaction coordinates for flap opening in HIV-1 protease

The primary goal of protein science is to understand how proteins function, which requires understanding the functional dynamics responsible for transitions between different functional structures of a protein. A central concept is the exact reaction coordinates that can determine the value of committor for any protein configuration, which provide the optimal description of functional dynamics. Despite intensive efforts, identifying the exact reaction coordinates (RCs) in complex molecules remains a formidable challenge. Using the recently developed generalized work functional, we report the discovery of the exact RCs for an important functional process—the flap opening of HIV-1 protease. Our results show that this process has six RCs, each one is a linear combination of ~240 backbone dihedrals, providing the precise definition of collectivity and cooperativity in the functional dynamics of a protein. Applying bias potentials along each RC can accelerate flap opening by 10 3 to 10 4 folds. The success in identifying the RCs of a protein with 198 residues represents a significant progress beyond that of the alanine dipeptide, currently the only other complex molecule for which the exact RCs for its conformational changes are known. Our results suggest that the generalized work functional (GWF) might be the fundamental operator of mechanics that controls protein dynamics.

Science & Technology - Other Topics↗
DOE OSTI2023

Chemical Recycling Processes of Waste Polyethylene Terephthalate Using Solid Catalysts

Polyethylene terephthalate (PET) is a non-degradable single-use plastic and a major component of plastic waste in landfills. Chemical recycling is one of the most widely adopted methods to transform post-consumer PET into PET's building block chemicals. Non-catalytic depolymerization of PET is very slow and requires high temperatures and/or pressures. Recent advancements in the field of material science and catalysis have delivered several innovative strategies to promote PET depolymerization under mild reaction conditions. Particularly, heterogeneous catalysts assisted depolymerization of post-consumer PET to monomers and other value-added chemicals is the most industrially compatible method. Here, this review includes current progresses on the heterogeneously catalyzed chemical recycling of PET. It describes four key pathways for PET depolymerization including, glycolysis, pyrolysis, alcoholysis, and reductive depolymerization. The catalyst function, active sites and structure-activity correlations are briefly outlined in each section. An outlook for future development is also presented.

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

HamLib: A Library of Hamiltonians for Benchmarking Quantum Algorithms and Hardware

For a considerable time, large datasets containing problem instances have proven valuable for analyzing computer hardware, software, and algorithms. One notable example of the value of large datasets is ImageNet [1], a vast repository of images that has been instrumental in testing numerous deep learning packages. Similarly, in the domain of computational chemistry and materials science, the availability of extensive datasets such as the Protein Data Bank [2], the Materials Project [3], and QM9 [4] has greatly facilitated the evaluation of new algorithms and software approaches, while also promoting standardization within the field. These well-defined datasets and problem instances, in turn, serve as the foundation for creating benchmarking suites like MLPerf [5] and LINPACK [6], [7]. These suites enable fair and rigorous comparisons of different methodologies and solutions, fostering continuous advancements in various areas of computer science and beyond.

Sawaya, Nicolas PD↗
DOE OSTI2025

Including frameworks of public health ethics in computational modelling of infectious disease interventions

Decisions on public health interventions to control infectious diseases are often informed by computational models. Interpreting the predicted outcomes of a public health decision requires not only high-quality modelling but also an ethical framework for assessing the benefits and harms associated with different options. The design and specification of ethical frameworks matured independently of computational modelling, so many values recognized as important for ethical decision-making are missing from computational models. We demonstrate a proof-of-concept approach to incorporate multiple public health values into the evaluation of a simple computational model for vaccination against a pathogen such as SARS-CoV-2. By examining a bounded space of alternative prioritizations of three values relevant to public health ethics (aggregate clinical burden, equity in clinical burden, equity in adverse effects from vaccination), we identify value trade-offs, where the outcomes of optimal strategies differ depending on the ethical framework. This work demonstrates an approach to incorporating diverse values into decision criteria used to evaluate outcomes of models of infectious disease interventions.

"Mathematical Biology"↗
DOE OSTI2025

Simultaneous prediction of structural properties in epitaxially–grown GaN with quantum and conventional multi–output learning algorithms

Hundreds of GaN thin film crystal plasma–assisted molecular beam epitaxy synthesis experiment records spanning two decades were organized into a dataset correlating the growth experiment design parameters with discrete, binary determinations of crystallinity and surface morphology. Conventional data science techniques as well as both quantum and classical multi–output supervised machine learning algorithms were implemented to investigate the relationships between the operating parameter data and the structural figures of merit. Correlation coefficients, decision tree nodes, p–values, and SHAP values all support substrate temperature and gallium effusion cell conditions as being statistically significant for simultaneously influencing GaN crystallinity and surface morphology. Here, a conventional deep neural network learned best from the data, followed by a quantum–classical hybrid gradient boosting algorithm. When combined with calculations of uncertainty intervals based on VennAbers predictors, machine learning predictions of both structural properties show good agreement with results reported in published experimental literature.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Uncertainty about the Uncertainty [Slides]

A golden standard in science is to repeat an experiment a statistically significant number of times, recording data using the same set of detectors and the same data analysis methodology. In such case experimental error includes both the range of true values generated by repetitions of the experiment, and measurement uncertainty caused by the detector. They are independent. It is a huge and too frequently used simplification, to assume that one can measure multiple repetitions of an identical experiment, resulting in identical true experimental value. Repetitions, as similar is it is experimentally achievable result in a range of the true values rather than in a single value. When modern, very sensitive and well calibrated measurement systems are used, this range is not negligible, and sometimes dominates, in comparison to the measurement uncertainty. Range of true values depends on the physics of the experiment, while measurement uncertainty depends on the measurement method (properties of the detector not of the experiment). When data from one–of–a kind experiment are analyzed, only the measurement uncertainty is reported. It gives no information about the range, in which the true values of experiment would spread if the experiment was repeated. A frequently used approximation, that if a physical quantity is measured as a function of time, only measurement of this quantity, produces uncertainty is also in some real experiments fare to strong. Example: In reaction history time measurement uncertainty propagated to alpha dominated under certain conditions over the flux measurement uncertainty propagated to alpha. Reliability of a data point is in general independent from its measurement uncertainty. However, in practice reliable measurement methods frequently have high measurement uncertainty, while low reliability methods are applied to limit measurement uncertainty. Comparison of reliable data with high measurement uncertainty to not so reliable data measured with low uncertainty is discussed – in different scenarios different data analysis methods are applicable.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Data associated with “Different methods of estimating riverbed sediment grain size diverge at the basin scale ” (v2)

This data package is associated with the publication “Different methods of estimating riverbed sediment grain size diverge at the basin scale” published in Frontiers in Earth Science (Regier et al., 2025). The distribution of sediment grain size in streams and rivers is often quantified by the median grain size (d50), a key metric for understanding and predicting hydrologic and biogeochemical function of streams and rivers. Manual methods to measure d50 are time-consuming and ignore larger grains, while model-based methods to estimate d50 often over-generalize basin characteristics, and therefore cannot accurately represent site-scale heterogeneity. Here, we apply a machine learning-enabled photogrammetry methodology (You Only Look Once, or YOLO) for estimating d50 for grains > 2 mm based on images collected from streams and rivers throughout the Yakima River Basin (YRB). To understand how such methods may help bridge the gaps in resolution and accuracy between manual and catchment characteristics model-based d50 estimates, we compared YOLO d50 values to manual and model-based estimates across the YRB. We found distinct differences among methods for d50 averages and variability, and relationships between d50 estimates and basin characteristics. Source images can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1892052. This data package was originally published in May 2023. It was updated August 2025 (v2; new and modified files). File and folder names were not revised to indicate changes. See the change history section in the readme for more details. In addition to the readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) readme; (4) and subfolders containing data, figures, and scripts. The data folder contains datasets used for the analyses in the manuscript in image, text-delimited or geospatially-referenced formats. The figures folder contains the figures from the manuscript in different formats. The scripts folder contains all of the scripts used to complete the analyses in the manuscript. All files are .csv, .rds, .dbf, .prj, .shp, .shx, .jpg, .png, .R, .Rproj, or .pdf. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected some of these data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Crossbreeding Effect of Chalcogenation and Iodination on Benzene Additives Enables Optimized Morphology and 19.68% Efficiency of Organic Solar Cells

Volatile solid additives have attracted increasing attention in optimizing the morphology and improving the performance of currently dominated non-fullerene acceptor-based organic solar cells (OSCs). However, the underlying principles governing the rational design of volatile solid additives remain elusive. Herein, a series of efficient volatile solid additives are successfully developed by the crossbreeding effect of chalcogenation and iodination for optimizing the morphology and improving the photovoltaic performances of OSCs. Five benzene derivatives of 1,4-dimethoxybenzene (DOB), 1-iodo-4-methoxybenzene (OIB), 1-iodo-4-methylthiobenzene (SIB), 1,4-dimethylthiobenzene (DSB) and 1,4-diiodobenzene (DIB) are systematically studied, where the widely used DIB is used as the reference. The effect of chalcogenation and iodination on the overall property is comprehensively investigated, which indicates that the versatile functional groups provided various types of noncovalent interactions with the host materials for modulating the morphology. Among them, SIB with the combination of sulphuration and iodination enabled more appropriate interactions with the host blend, giving rise to a highly ordered molecular packing and more favorable morphology. As a result, the binary OSCs based on PM6:L8-BO and PBTz-F:L8-BO as well as the ternary OSCs based on PBTz-F:PM6:L8-BO achieved impressive high PCEs of 18.87%, 18.81% and 19.68%, respectively, which are among the highest values for OSCs.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The fluid definition of the ‘waters of the United States’: Non-uniform effects of regulation on US wetland protections

Recent revisions to the definition of the ‘waters of the United States’ (WOTUS) have considerably altered how wetlands are federally regulated under the Clean Water Act. The two most recent modifications to WOTUS, the Clean Water Rule (CWR) and the Navigable Waters Protection Rule (NWPR), represent two opposing approaches to the federal wetland policy. The impacts of these two rules on the regulation of wetlands have as of yet been poorly characterized at broad spatial scales. Using New York State (NYS) as a case study, we evaluated the jurisdictional statuses of more than 253 000 wetlands under the CWR and the NWPR to assess the landscape-scale effects of WOTUS re-definitions. Here, we found that statewide and within each of NYS's hydrologic regions, the NWPR protects fewer wetlands and less total wetland area than the CWR. The efficacy of the two regulations varied considerably in space across NYS, highlighting the need for comprehensive, nationwide assessments of wetland policy outcomes. We also observed that both rules produced non-uniform patterns in jurisdiction across a range of landscape positions and wetland sizes, preferentially protecting large wetlands close to the stream network. This effect was particularly pronounced under the NWPR, which excludes all geographically isolated wetlands from protection. Our findings in NYS emphasize the existence of unique patterns in protected wetlands across spatial scales, highlighting the value in applying geospatial analyses to evaluate environmental policy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Role of α → ε → α phase transformation on the spall behavior of iron at atomic scales

Shock compression of iron microstructures above a threshold stress results in a α (BCC) → ε (HCP) transformation and the propagation of the release wave brings the metal back to the α phase following the ε→α transformation. Predicting failure behavior under shock loading conditions (spallation) relies on understanding the evolution of defects in the microstructure as it undergoes the α→ε→α phase transformation. This study uses molecular dynamics (MD) simulations to investigate the role of defect evolution during α→ε→α phase transformation on the spall strength values of single-crystal (sc) Fe microstructures. The MD simulations aim to characterize the ε phase fraction formed during shock compression and the defects during shock release for variations in loading orientations and shock stresses. The simulations are carried out for loading along the [100], [110], [111], and [112] orientations and for impact velocities ranging from 600 m/s to 1 km/s. The ε phase fractions during compression and defects (dislocations, twins) characterized during spall failure show an orientation dependence that affects the spall strength values. Here, the lowest value for spall strength is observed for the <110> loading orientation that shows a high density of twinning at the spall plane, whereas the highest value is observed for the <100> orientation and is associated with a α (BCC) → γ (FCC) transformation at the spall plane. The correlations of the spall strength values with the strain rates and with the ε phase fractions are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2020

An Alternative Casting Technique to Improve the Creep Resistance of Cast INCONEL Alloy 740H

The increasing performance requirements of power plant designs, such as advanced-ultra supercritical (A-USC), require the use of Ni-based superalloys to replace high-strength, ferritic-martensitic steels for components subjected to temperatures above 898 K (625 °C) and for austenitic stainless steels components at temperatures above 973 K (700 °C). To date, commercial Ni-based superalloy INCONEL 740H has been shown to be appropriate for use in A-USC power plants as boiler components in a wrought product. However, large complex components in boilers as well as other casings in the turbine and valve chest require castings of a thick-wall nature. Using the alloy in its cast form would be significantly valuable in terms of range of component size, geometry and complexity. Previous investigations revealed short creep lives from cast INCONEL alloy 740H. Here in this investigation, an alternative casting route that utilized a melt procedure resulting in a fine-grain casting, and in conjunction with a computationally optimized homogenization heat treatment, not only controlled the grain size and grain boundary structure but minimized chemistry variability and segregation. A primarily equiaxed and homogenous grain size distribution was obtained from this approach with better repartition of M 23 C 6 carbides along the grain boundaries. Furthermore, better than 38 pct increase was obtained for this material in comparison to the creep life obtained from the best performing conventionally cast material. More importantly, the fine-grain homogenized (FGH) casting route resulted in the Larson–Miller plot for this material that coincided with that of wrought alloy 740. At low creep stresses (with a test still in progress), the FGH casting is resulting in higher values of the LMP than the wrought alloy.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Large adiabatic temperature change and magnetic frustration in triangular lattice antiferromagnet Dy 2 IrSi 3

While previous studies reveal that the formation of polycrystalline R 2 TX 3 (R = rare-earth, T = transition metal, X = p-block element) type compounds with T = Ir and Co is not achievable without deliberate introduction of atomic vacancies of Ir/Co and Si, here we report successful synthesis of Dy 2 IrSi 3 with fully stoichiometric ratio of constituent elements. An antiferromagnetic transition is manifested in the compound at 6.6 K where only about 50 % of Dy spins take part, while the rest remain in highly frustrated state due to edge-sharing triangular lattice geometry. The magnetic frustration is conclusively probed through magnetization, heat capacity and magnetocaloric study and the frustration parameter (f = |θ p |/T N , θ p , T N being Curie-Weiss and Néel temperatures, respectively) in this case is as large as ~ 3. An additional cluster-glass type transition at ~2.8 K observed in this system has likely been originated due to this magnetic frustration. The magnetocaloric effect reveals an adiabatic temperature change of ~7.5 K for 70 kOe magnetic field, which is one of the largest values reported in intermetallic compounds.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Stakeholder analysis for designing an urban air quality data governance ecosystem in smart cities

Cities, the world over, are fuelling economic growth. At the same time, rapid urbanization is a root cause of serious environmental damage. Recent WHO global air pollution guidelines highlight air pollution as a critical environmental threat along with climate change. To address these threats, smart cities and clean air programs are on a rise. In smart cities, data and Information and Communication Technologies (ICT) are major drivers of city transformations. The 4th Industrial Revolution (4IR) technologies such as the Internet of Things (IoT), big data, artificial intelligence (AI), and cloud computing have the potential to accelerate these transformations toward urban resilience. However, the success of smart cities and clean air programs depends on cohesive multi-sector stakeholder contributions. This study conducted interdisciplinary participative stakeholder analysis to understand the data, and sectorial challenges, to outline the technological opportunities to facilitate clean air programs in Indian smart cities. The research highlights gaps due to siloed stakeholder operations, lack of data calibration, non-alignment of smart city and air quality management services, non-availability of health exposure data, and difficulty in translating scientific data into implementable actions. Stakeholders expressed potential ‘fit for the purpose’ use of IoT devices, satellites, smartphones, and mobility data augmented by AI methods in bridging these gaps. In conclusion, the analysis points toward a need to develop an easily accessible and ubiquitous urban data governance ecosystem enabling seamless cross-sector data exchanges to build trusting relationships among the stakeholders across the air quality management value chain.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗