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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 OSTI2025

Postdoctoral insights on mentoring excellence: a framework for best practices at Sandia National labs

The Sandia National Laboratories Strategic Plan FY24-FY27, updated for FY25, outlines Sandia’s two Big Labs-wide Goals, Accelerate Innovation and Lead in Modern Engineering. The goal of Accelerate Innovation is that “by FY27, Sandia will be a leader in scientific, engineering and operational innovation and an employer of choice for highly innovative and creative talent.” Sandia’s postdocs are leaders in innovation, well-versed in emerging techniques and cutting-edge methods, and capable of acting as a highly agile technical force across domains at the lab. As a federally funded research and development center (FFRDC), Sandia National Laboratories attracts top doctoral talent by offering a unique opportunity for postdoctoral researchers to develop at the crossroads of government, academia, and industry, working in multi-disciplinary teams and performing cutting-edge, mission-specific research that responds to immediate needs of national interest. However, this creates unique opportunities and demands of both postdoctoral appointees and the Sandia staff who act as their mentors, making mentorship key to attract talent. Since 2007 the Sandia Postdoctoral Development (SPD) Board, originally Postdoc To Professional (PD2P), a networking group at Sandia composed of a voluntary board of current postdocs and two staff liaisons, has advocated for postdoctoral development within Sandia National Labs. In this white paper, SPD board members and the Sandia Postdoctoral Development Office, organized in 2019, have come together to develop a comprehensive overview of the postdoctoral mentoring landscape at Sandia National Labs as we currently know it. By scouring various forms of data from efforts since 2018, we’ve compiled a community-derived perspective on what makes postdoctoral mentorship at Sandia unique. First, we analyze working sessions held between mentors and mentees to develop a comprehensive map of who is involved in postdoctoral mentorship at the lab and how the responsibilities are divided amongst mentors and mentees. We then combine multiple forms of data, including exit surveys, annual surveys, and community workshops, to identify the specific challenges that mentors and mentees encounter at the national lab. Finally, we use text mining and sentiment analysis to analyze mentoring award data to develop an idea of what postdocs are self-identifying as excellent mentorship within the lab. It is our goal that this white paper act as an ongoing resource to the postdoc and postdoc mentoring communities and provide a firm foundation for further conversations on the future of postdoctoral mentorship at Sandia National Labs.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Automated electrosynthesis reaction mining with multimodal large language models (MLLMs)

Leveraging the chemical data available in legacy formats such as publications and patents is a significant challenge for the community. Automated reaction mining offers a promising solution to unleash this knowledge into a learnable digital form and therefore help expedite materials and reaction discovery. However, existing reaction mining toolkits are limited to single input modalities (text or images) and cannot effectively integrate heterogeneous data that is scattered across text, tables, and figures. In this work, we go beyond single input modalities and explore multimodal large language models (MLLMs) for the analysis of diverse data inputs for automated electrosynthesis reaction mining. We compiled a test dataset of 65 articles (MERMES-T24 set) and employed it to benchmark five prominent MLLMs against two critical tasks: (i) reaction diagram parsing and (ii) resolving cross-modality data interdependencies. The frontrunner MLLM achieved ≥96% accuracy in both tasks, with the strategic integration of single-shot visual prompts and image pre-processing techniques. We integrate this capability into a toolkit named MERMES (multimodal reaction mining pipeline for electrosynthesis). Our toolkit functions as an end-to-end MLLM-powered pipeline that integrates article retrieval, information extraction and multimodal analysis for streamlining and automating knowledge extraction. This work lays the groundwork for the increased utilization of MLLMs to accelerate the digitization of chemistry knowledge for data-driven research.

Leong, Shi Xuan↗
DOE OSTI2024

Informing forest carbon inventories under the Paris Agreement using ground-based forest monitoring data

Human interactions with forests have shaped Earth's climate for millennia and will continue to do so as we target net-zero emission goals. Accurately characterizing these climate impacts requires making reliable forest carbon data available for forest monitoring and planning. Here, we develop a semi-automated process for submitting forest carbon measurements from the largest relevant scientific database to the International Panel on Climate Change's Emission Factor Database, which currently has sparse forest carbon data. Building this bridge from scientific research to international policy is an important step towards managing forests in a net-zero motivated future. Humans have been influencing Earth's climate via transformative impacts on forests for millennia, and forests are now recognized as critical to climate change mitigation under the Paris Agreement. The efficacy of climate change mitigation planning and reporting depends on quality data on forest carbon (C) stocks and changes. The Emission Factor Database (EFDB) of the International Panel on Climate Change (IPCC) is intended to be a definitive source for such data, but needs comprehensive and well-documented data to be so. To facilitate submission of forest C estimates from scientific studies to EFDB, we develop and document a process for semi-automated data submission from the Global Forest C database (ForC v4.0), which is the largest compilation of ground-based forest C estimates. We then assess the data currently available through ForC and provide recommendations for improving forest data collection, analysis, and reporting. As of September 2024, ForC contained ~19,286 records potentially relevant to EFDB, 1068 of which had been submitted and posted to EFDB. These represented 19% of the total EFDB records for forest land. Records were unevenly distributed across variables and geographic regions. ForC records (37%) reviewed could not be submitted because the original publication lacked required information. In the future, ground-based forest C estimates should target gaps in the record, and studies should ensure that they report all information necessary for inclusion in EFDB. Given that climate change is rapidly impacting the world's forests, timely reporting of recent estimates will be critical to accurate forest C inventories.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Compilation and Evaluation of Isomeric Fission Yield Ratios

Fission yields are essential data for reactor physics, forensics, and astrophysics. In some cases, the fission yield of a fragment is divided between the ground state and a long-lived excited state, and the relative population of the two states is referred to as the isomeric ratio. In this work, we present a comprehensive compilation of experimental isomeric fission yield ratios for all target and projectile combinations. When possible, these data are combined to provide recommended isomeric fission yield ratios for low energy neutron-induced fission and spontaneous fission. The recommended ratios are compared to the traditional Madland-England model, which attempts to describe the isomeric ratios with a single parameter relating to the angular momentum of the fragment. It is found that the model does not reliably reproduce isomeric ratios outside the few nuclei it was fitted to, and its simplified treatment of the statistical process following population in fission results in average spin values, which are neither constant nor follow a recently observed saw-tooth pattern.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Developing Ultrahigh-Resolution E3SM Land Model for GPU Systems

Designing and refactoring complex scientific code, such as the E3SM land model (ELM), for new computing architectures is challenging. This paper presents design strategies and technical approaches to develop a data-oriented, GPU-ready ELM model using compiler directives (OpenACC/OpenMP). We first analyze the datatypes and processes in the original ELM code. Then we present design considerations for ultrahigh-resolution ELM (uELM) development for massive GPU systems. These techniques include the global data-oriented simulation workflow, domain partition, code porting and data copy, memory reduction, parallel loop restructure and flattening, and race condition detection. We implemented the first version of uELM using OpenACC targeting the NVidia GPUs in the Summit supercomputer at Oak Ridge National Laboratory. During the implementation, we developed a software tool (named SPEL) to facilitate code generation, verification, and performance tuning using these techniques. The first uELM implementation for Nvidia GPUs on Summit delivered promising results: 1) over 98% of the ELM code was automatically generated and tuned by scripts. Most ELM modules had better computational performances than the original ELM code for CPUs. The GPU-ready uELM is more scalable than the CPU code on fully-loaded Summit nodes. Example profiling results from several modules are also presented to illustrate the performance improvements and race condition detection. The lessons learned and toolkit developed in the study are also suitable for further uELM deployment using OpenMP on the first US exascale computer, Frontier, equipped with AMD CPUs and GPUs.

Schwartz, Peter↗
DOE OSTI2026

Leafweb: Leaf Gas Exchange and Pulse-Amplitude Modulated Fluorometry for C4 Species, June 2026 Release

This dataset contains leaf gas exchange and Pulse-Amplitude Modulated (PAM) fluorometry for 98 C4 species. The C4 photosynthetic pathway employs specialized CO2 concentration mechanisms and Kranz anatomy to enrich CO2 concentration around Rubisco, the enzyme that catalyzes carbon fixation in the Calvin-Benson cycle to suppress photorespiration and increase the use efficiencies of light, nitrogen, and water as compared to the C3 photosynthetic pathways. Large-scale C4 photosynthetic datasets are relatively scarce, which has affected C4 photosynthesis research. To improve C4 photosynthetic data availability, Leafweb organized an effort to systematically collect, compile, standardize, and organize measurements of leaf gas exchange and/or Pulse-Amplitude Modulated (PAM) fluorometry of C4 species. This derived a C4 photosynthetic dataset containing measurements made by independent researchers in multiple countries in various environments (field, garden, or greenhouse). It covers three biochemical subtypes – the nicotinamide adenine dinucleotide phosphate-malic enzyme (NADP-ME), nicotinamide adenine dinucleotide-malic enzyme (NAD-ME), and phosphoenolpyruvate carboxykinase (PEP-CK) subtypes. This dataset is useful for using Artificial Intelligence / Machine Learning and mechanistic models to study C4 photosynthesis and compare across different biochemical subtypes. This dataset contains 3 compressed (*.zip) folders containing 1,892 data files in comma-separate values (*.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma-separate values (*.csv) format and a user guide in PDF (*.pdf) format.

Zhou, Haoran [Tianjin University, China]↗
DOE OSTI2026

RTN-124: Photometric Redshifts for the Vera C. Rubin Observatory Data Preview

We present the photometric redshifts (photo-z) inferred using algorithms implemented in the Redshift Assessment Infrastructure Layers (RAIL) for the NSF-DOE Vera C. Rubin Observatory Data Preview 2 (DP2). We produce a compilation of reference redshift catalog using spectroscopic, grism and many band photometric redshift dataset hosted on the LIneA Photo-z Server. We curate training and testing set for assessing the scientific and technical performance of Rubin photo-z. The algorithm applied to the object catalog are FlexZBoost, BPZ, kNN, GPz, DNF and TPz; with a combination of 6-band and 4-band photo-z depending on availability of u and y photometry. The redshift point estimates and uncertainty estimation in tabular format through the Large Survey DataBase (LSDB).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

X-ray diffraction under grazing incidence conditions

Material properties frequently relate to structures at or near surfaces, particularly in thin films. As a result, it is essential to understand these structures at the molecular and atomistic levels. The most accurate and widely used techniques for characterizing crystallographic order are based on X-ray diffraction. When dealing with thin films or interfaces, standard approaches, such as single crystal or powder diffraction, are not suitable. However, X-ray diffraction under grazing incidence conditions can provide the required information. Here, in this Primer, grazing incidence X-ray diffraction (GIXD) is comprehensively introduced, starting from basic considerations on X-ray diffraction at crystals with reduced dimensionality and the optical properties of X-rays, followed by a more in-depth description of an experimental performance, including X-ray sources, goniometers and detectors. Experimental errors, limitations and reproducibility are discussed. Various applications, from highly ordered inorganic single crystal surfaces to weakly ordered polymer thin films, are presented to illustrate the potential of GIXD. Data visualizations, representations and evaluation strategies are summarized, based on the example of anthracene thin films. The Primer compiles information relevant to perform high-quality GIXD experiments, evaluate data and interpret results, to extend knowledge about X-ray diffraction from surfaces, interfaces and thin films.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Review of Wind–Wave Coupling Models for Large-Eddy Simulation of the Marine Atmospheric Boundary Layer

Abstract We present a review of existing wind–wave coupling models and parameterizations used for large-eddy simulation of the marine atmospheric boundary layer. The models are classified into two main categories: (i) the wave-phase-averaged, sea surface–roughness models and (ii) the wave-phase-resolved models. Both categories are discussed from their implementation, validity, and computational efficiency viewpoints, with emphasis given on their applicability in offshore wind energy problems. In addition to the various models discussed, a review of laboratory-scale and field-measurement databases is presented thereafter. The majority of the presented data have been gathered over many decades of studying air–sea interaction phenomena, with the most recent ones compiled to reflect an offshore wind energy perspective. Both provide valuable data for model validation. We also discuss the modeling knowledge gaps and computational challenges ahead.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Current status of anaerobic digestion of food waste in the United States

Utilization of food waste (FW) and food processing waste streams in waste-to-energy technologies has increased over the years in United States (US). This review paper compiled information from published literature and open data sources to obtain a holistic view of the current state of FW availability and its management using anaerobic digestion (AD). The review examined the usage of FW as a feedstock for AD by considering the feedstock composition and availability of FW in the US as well as challenges and opportunities with implementing FW in mono- and co-digestion. Also presented are global trends in FW digestion and the current status of FW codigestion in the US. FW in the US was characterized with regard to volume and composition to show a need for waste management and an opportunity for valuable resource recovery. Challenges and opportunities of processing via AcoD were presented to review best practices for successful operations. Environmental standards, economic incentives, and governmental policies in the US and around the world regarding waste management and utilization were discussed to identify barriers and sources of opportunity for large-scale implementation of AcoD. Additionally, a range of facilities throughout the US was examined for information regarding digestion type, feedstock (s), biogas production and utilization, and energy self-sufficiency to better understand the current status of FW digestion. Several US facilities were outlined as case studies that co-digest FW and produce and utilize biogas for various applications. Future strategies, perspectives, and roadmaps were discussed to elucidate the shaping of future FW management practices.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Quasars with large proper motions: A selection from the LQAC-5 catalogue combined with Gaia EDR3: Focusing on astrometric and photometric properties

Thanks to the cross-identification between the Gaia EDR3 (E-Data Release 3) catalogue and the quasars’ compiled catalogue LQAC-5 (Large Quasar Astrometric Catalogue-5), accurate astrometric parameters as well as photometric measurements were available for a set of 416 113 quasars. After analysing the astrometric and photometric properties of these quasars, we concentrate our study on objects characterized by significant proper motion, which contradicts the postulate that they are fixed in the celestial sphere. We derived statistical properties of the positions, parallaxes, and proper motions of the quasars cross-matched with Gaia EDR3. We carried out a specific investigation of quasars with a proper motion larger than 10 mas yr -1 , and used colour-colour diagrams in mid-infrared to discriminate these quasars from stellar contamination. We discuss, in detail, a few cases where the abnormal proper motion could be caused by misidentifications. We note that 43% of LQAC-5 quasars were not detected by Gaia EDR3, mainly because of the cut-off magnitude at G = 21. The comparison between r(G) (Gaia) and r (SDSS) shows a normal distribution. The normalized distributions of parallaxes and proper motions are identical to that of the Gaia CRF2, as well as the distribution of the G BP -G RP colour index. We have identified 937 LQAC-5 objects (0.27% of the sample) with Gaia EDR3 proper motion which is significant at the 5σ level. We have clearly shown that below z = 0.35, the integrated magnitude G(r) obtained from SDSS spectra is smaller than G (Gaia), leading to the statement that the quasars are generally resolved under this threshold, which should lead to a bad determination of proper motion. Moreover, to discriminate quasars from stellar contamination, we have plotted them in a mid-infrared colour–colour diagram. Finally, we have made a final selection of 41 objects with μ > 10 mas yr -1 , satisfying drastic constraints, which makes them potential candidates for considering their proper motion as real. In this paper we carried out a complete analysis of the quasars of the LQAC-5 which were cross-identified with Gaia EDR3 ; this serves as an alternative and complementary study with respect to Gaia CRF2, involving a different population of quasars. We selected a set of 41 quasars with a proper motion exceeding 10 mas yr -1 , which can be considered as very high for objects which are a priori fixed in the celestial sphere.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

CATMoS: Collaborative Acute Toxicity Modeling Suite

Background: Humans are exposed to tens of thousands of chemical substances that need to be assessed for their potential toxicity. Acute systemic toxicity testing serves as the basis for regulatory hazard classification, labeling, and risk management. However, it is cost- and time-prohibitive to evaluate all new and existing chemicals using traditional rodent acute toxicity tests. In silico models built using existing data facilitate rapid acute toxicity predictions without using animals. Objectives: The U.S. Interagency Coordinating Committee on the Validation of Alternative Methods Acute Toxicity Workgroup organized an international collaboration to develop in silico models for predicting acute oral toxicity based on five different endpoints: LD50 value, U.S. Environmental Protection Agency hazard categories, Globally Harmonized System for Classification and Labelling hazard categories, very toxic chemicals (LD50 =50 mg/kg), and non-toxic chemicals (LD50 >2000 mg/kg). Methods: An acute oral toxicity data inventory for 11,992 chemicals was compiled, split into training and evaluation sets, and made available to 35 participating international research groups that submitted a total of 139 predictive models. Predictions that fell within the applicability domains of the submitted models were evaluated using external validation sets. These were then combined into consensus models to leverage strengths of individual approaches. Results: The resulting consensus predictions, which leverage the collective strengths of each individual model, form the Collaborative Acute Toxicity Modeling Suite (CATMoS). CATMoS demonstrated high performance in terms of accuracy and robustness when compared to in vivo results. Discussion: CATMoS is being evaluated by regulatory agencies for its utility and applicability as a potential replacement for in vivo rat acute oral toxicity studies. CATMoS predictions for over 800,000 chemicals have been made available via the NTP’s Integrated Chemical Environment. The models are also implemented in a free, standalone open-source tool, OPERA, which allows predictions of new and untested chemicals to be made.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2021

Leaf gas exchange data, Nov 2018 and May 2019, Daintree Rainforest, Australia

This data package contains leaf gas exchange data for 11 canopy tree species in the control and drought treatments at the Daintree Rainforest Observatory in Queensland, Australia (AU-DRO) with the purpose of testing for differences in gas exchange between treatments. Data were collected at the end of the dry season (November 2018) and end of the wet season (May 2019). Using a canopy crane, large branches (>1 m) were collected from the top of the canopy and immediately placed in a bucket of water, upon which the LI-6800 leaf chamber was clamped onto a recently mature leaf with minimal herbivory. Measurements were recorded every 3 seconds for 3 minutes total. The species included in the dataset are: Castanospermum australe, Cleistanthus myrianthus, Cryptocarya mackinnoniana, Dysoxylum papuanum, Elaeocarpus angustifolius (Elaeocarpus grandis), Endiandra microneura, Mallotus paniculatus, Myristica globosa, Rockinghamia angustifolia, Synima cordierorum, Syzygium spp. The two data files included are: 1. LICOR_Data_AU_DRO_2019_GasEx.csv (a compilation of individual LICOR output files, with correction of user input errors such as incorrect species spelling) 2. ESS_DIVE_Data_AU_DRO_2019_GasEx.csv (selected variables and converted units from LICOR_Data_AU_DRO_2019_GasEx.csv to follow the standard gas exchange reporting format from Ely et al. 2021 Ecological Informatics). The metadata files included are: (3) ESS_DIVE_Metadata_AU_DRO_2019_GasEx.xlsx (4) File_Submission_Metadata_AU_DRP_2019_GasEx.xlsx (5) E-Field_Log_AU_DRO_2019_GasEx.xlsx (6) Data_Column_Description_AU_DRO_2019_GasEx.xlsx.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Chemical Blast Standard (1 kg)

Chemical explosions create blast waves with large overpressure disturbances. It is important to develop a standard blast model based on data to accurately predict acoustic blast-wave amplitudes near detonations and invert for explosion energy from distant observations of blast-wave signals. However, open data from large, controlled chemical explosions with reliable ground truth can be challenging to find. The lack of access to such data could limit the number of contributions to related research and potentially stifle the rate of discoveries or validation of existing models. Here, to address these data scarcity problem, we have curated and compiled a standardized set of 817 blast-wave waveforms from 19 distinct high-explosive events. The blast-wave waveforms are standardized to a 1 kg trinitrotoluene explosion using scaling laws and corrections for location effects. A brief overview of the dataset is presented along with explosion feature models as well as recommendations for extracting explosion features. The resulting dataset is distributed to an open repository in both Seismic Analysis Code and pandas DataFrame formats containing the waveforms, the scaled distances, and the sample rates.

58 GEOSCIENCES↗
DOE OSTI2023

NEWTS Well Summary by Hydrologic Regions and Subbasins in the U.S.

Oil and gas well production data (2000-2022), including water production and injection, as well as summary information (e.g., well count by status, total vertical depth statistics, etc.) spatially summarized by Watershed Boundary Dataset's (WBD) region (Hydrologic Unit Code (HUC) 2) and subbasin (HUC8). Energy-related produced waters data were acquired and summarized in support of the development of the National Energy Technology Laboratory's NEWTS (National Energy Water Treatment and Speciation Database). Due to the proprietary nature of the wellbore data, this derived product has been spatially compiled by key areas to support research and stakeholder needs.

Energy Infrastructure↗
DOE OSTI2023

Seven open problems in applied combinatorics

We present and discuss seven different open problems in applied combinatorics. Additionally, the application areas relevant to this compilation include quantum computing, algorithmic differentiation, topological data analysis, iterative methods, hypergraph cut algorithms, and power systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Modeling Streamflow and Sediment Transport Under Current and Future Climates at the West Valley Site - 20231

Performance Assessment models often require inputs representing specific hydrologic processes such as streamflow and sediment flux. This paper details the development of a process-level hydrologic model and its use in a Probabilistic Performance Assessment (PPA) system-level model for the West Valley Site in western New York. For this PPA model, a watershed model was developed using SWAT (Soil and Water Assessment Tool) and used to evaluate water and sediment fluxes in nearby streams draining the Site. A particular challenge of probabilistic modeling over long periods of time is scaling parameters appropriately so that outcomes are not grossly over- or underestimated. This challenge is especially important when the spatial and temporal scales of process and system level models differ. In this instance, the SWAT watershed model and GoldSim PPA model have similar spatial scales of stream reaches and sub-catchments within a single watershed (approximately hundreds to tens of thousands of square meters, but the temporal scales differ considerably. The SWAT model calculates streamflow and sediment transport rates at the daily scale, while the PPA model requires long-term average values that are applied over hundreds to thousands of year-long periods. As such, distributions of daily climatic parameters such as average precipitation rate, temperature, wind speed, and relative humidity were developed to force a transient SWAT model that captures the dynamic behavior of the watershed in response to daily changes in the weather. Output from the model, which includes stream flow (m{sup 3}/y) and sediment transport rate (Mg/y) is then averaged over a 100-year period as an approximation for the long-term average values which can be applied in GoldSim. A single SWAT model was run 5000 times with varying climatic inputs and deterministic soil, land use, and elevation data, and the range of outputs were compiled into a distribution which can be implemented stochastically into the PPA Model. Additionally, this paper includes a high-level discussion of how changes in future climate affect weather input distributions, and a summary of how those changes in weather affect the outcomes from the SWAT model and the inputs into the PPA model. In this analysis, future climate distributions were developed based on climate research documenting the expected changes to precipitation and temperature in western New York. The 5,000 SWAT simulations were then repeated with these future climate distributions, and the resulting output was implemented into the PPA Model as hydrologic conditions under a future climate. In the current version of the PPA Model, hydrologic parameters change linearly from the 'current climate' conditions to the 'future climate' conditions over a period of 100 years, after which they remain constant. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗