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DOE OSTI2020

Database development and exploration of process–microstructure relationships using variational autoencoders

The paper demonstrates graphical representation of a large database containing process–microstructure relationships using an unsupervised machine learning algorithm. Correlating microstructural features to processing is an essential first step to answer the difficult problem of process sequence design. Here, a large database of 346,200 orientation distribution functions resulting from a variety of process sequences is constructed, where each sequence comprises up to four stages of tension, compression and rolling along different directions in various permutations. This open-source database is constructed for collaborative development of process design algorithms. The paper demonstrates a novel application of the large database: graphical representation of texture–process relationships. A variational autoencoder is used to reduce the entire database to a two dimensional latent space where variations in processes and properties can be visualized. Using proximity analysis in this latent space, we can quickly unearth multiple process solutions to the problem of texture or property design.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Applying a Template of Expected Uncertainties to Updating 239 Pu(n,f) Cross-section Covariances in the Neutron Data Standards Database

Templates of uncertainties expected in specific measurement types were recently developed. One aim of these templates is to help evaluators in identifying (1) missing or suspiciously low uncertainties and (2) missing correlations between uncertainties of the same and different experiments, when estimating covariances for experimental data employed in their evaluations. These templates also provide realistic estimates of standard deviations and correlations for a particular uncertainty source and measurement type that can be used by evaluators in situations where they are not supplied by the experimenters. This information allows for a more comprehensive uncertainty analysis across all measurements considered in an evaluation and, thus, more realistic evaluated covariances. Here, in this work, we extend a template that is applicable to uncertainties expected in neutron-induced fission, (n,f), cross-section measurements. It is applied to improving covariances of 239 Pu(n,f) cross-section measurements in the database underlying the Neutron Data Standards evaluations. This particular example was chosen since this evaluation is primarily based on experimental information. Also, some uncertainties of individual 239 Pu(n,f) cross-section experiments in this database were suspected to be underestimated. The evaluated uncertainties obtained after updating the covariances in the database by means of the template indeed do increase compared to their original values. Even more importantly, the evaluated mean values change noticeably. These modified cross sections impact application calculations significantly, as is demonstrated by employing them in simulations of the effective neutron multiplication factor for a few selected critical assemblies. However, this updated evaluated 239 Pu(n,f) cross section should not be interpreted as the final one that should replace values of the current Neutron Data Standards project. Evaluations for the Neutron Data Standards of the 239 Pu(n,f) cross section must be linked to many other observables included in the associated database, most notably to cross sections for 235 U(n,f), but also to those for 10 B(n, α ), 6 Li(n,t), 238 U(n,f), and 238 U(n, γ ), because of included measurements of the 239 Pu(n,f) cross section that appear as ratios to these reactions. Some of these other reactions are correlated to further observables in the database. Hence, updating uncertainties of data sets of any of these observables can potentially impact the 239 Pu(n,f) cross section. Uncertainties for all measurements of these linked physical observables have to be updated before a comprehensive evaluation of the 239 Pu(n,f) cross section and its corresponding uncertainties can be provided.

239Pu Neutron-induced fission cross-section↗

DOE OSTI2022

A database of refractive indices and dielectric constants auto-generated using ChemDataExtractor

The ability to auto-generate databases of optical properties holds great potential for advancing optical research, especially with regards to the data-driven discovery of optical materials. An optical property database of refractive indices and dielectric constants is presented, which comprises a total of 49,076 refractive index and 60,804 dielectric constant data records on 11,054 unique chemicals. The database was auto-generated using the state-of-the-art natural language processing software, ChemDataExtractor, using a corpus of 388,461 scientific papers. The data repository offers a representative overview of the information on linear optical properties that resides in scientific papers from the past 30 years. Public availability of these data will enable a quick search for the optical property of certain materials. The large size of this repository will accelerate data-driven research on the design and prediction of optical materials and their properties. To the best of our knowledge, this is the first auto-generated database of optical properties from a large number of scientific papers. We provide a web interface to aid the use of our database.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Perovskite- and Dye-Sensitized Solar-Cell Device Databases Auto-generated Using ChemDataExtractor

The number of scientific publications reporting cutting-edge third-generation photovoltaic devices is increasing rapidly, owing to the pressing need to develop renewable-energy technologies that address the climate-change crisis. Consequently, the field could benefit from a central repository where photovoltaic-performance metrics, such as the power-conversion efficiency (η) are recorded. We present two automatically generated databases that contain photovoltaic properties and device material data for dye-sensitized solar cells (DSCs) and perovskite solar cells (PSCs), totalling 660,881 data entries representing 57,678 photovoltaic devices. The databases were generated by applying the text-mining toolkit ChemDataExtractor on a corpus of 25,720 articles. A multi-faceted evaluation, incorporating manual and automatic methods, was applied to ensure that the data contained therein were of the highest quality, with precision metrics ranging from 73.1% to 95.8%. The DSC database contains 475,045 entries representing 41,680 devices, and the PSC database contains 185,836 entries representing 15,818 devices. The databases are available in MongoDB and JSON formats, which can be queried in Python, R, Java and MATLAB for data-driven photovoltaic materials discovery.

14 SOLAR ENERGY↗

DOE OSTI2024

DUNE Database Development

The DUNE experiment will produce vast amounts of metadata, which describe the data coming from the read-out of the primary DUNE detectors. Various databases will make up the overall DB architecture for this metadata. ProtoDUNE at CERN is the largest existing prototype for DUNE and serves as a testing ground for - among other things - possible database solutions for DUNE. The subset of all metadata that is accessed during offline data reconstruction and analysis is referred to as ‘conditions data’ and it is stored in a dedicated database. As offline data reconstruction and analysis will be deployed on HTC and HPC resources, conditions data is expected to be accessed at very high rates. It is therefore crucial to store it in a granularity that matches the expected access patterns allowing for extensive caching. This requires a good understanding of the sources and use cases of conditions data. This contribution will briefly summarize the database architecture deployed at ProtoDUNE and explain the various sources of conditions data. We will present how the conditions data is retrieved and streamed from the databases and how it is handled to match expected access patterns.

Vizcaya Hernandez, Ana Paula↗

DOE OSTI2020

RNAcentral 2021: secondary structure integration, improved sequence search and new member databases

RNAcentral is a comprehensive database of non-coding RNA (ncRNA) sequences that provides a single access point to 44 RNA resources and >18 million ncRNA sequences from a wide range of organisms and RNA types. RNAcentral now also includes secondary (2D) structure information for >13 million sequences, making RNAcentral the world’s largest RNA 2D structure database. The 2D diagrams are displayed using R2DT, a new 2D structure visualization method that uses consistent, reproducible and recognizable layouts for related RNAs. The sequence similarity search has been updated with a faster interface featuring facets for filtering search results by RNA type, organism, source database or any keyword. This sequence search tool is available as a reusable web component, and has been integrated into several RNAcentral member databases, including Rfam, miRBase and snoDB. To allow for a more fine-grained assignment of RNA types and subtypes, all RNAcentral sequences have been annotated with Sequence Ontology terms. The RNAcentral database continues to grow and provide a central data resource for the RNA community. RNAcentral is freely available at https://rnacentral.org.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Mapping Inquiry Tool (MapIT) Database

The Mapping Inquiry Tool (MapIT) database consists of a geodatabase and data catalog of geologic, geophysical, structural, hydrologic, and contextual data, based on the data types to support geologic carbon storage activities and other subsurface energy systems resource assessments. The database was aggregated from publicly available data across the USA from state and federal entities. The database is structured by categories including rock unit geology, boundaries, national CS datasets, geophysical data, faults and structural data, infrastructure, surface hydrology, groundwater, and more. The data described in the data catalog is also available in the Mapping Inquiry Tool (https://edx.netl.doe.gov/dataset/mapping-inquiry-tool). Version 3 of the geodatabase and data catalog have been updated as of 5/17/2024. The database was published with a limited number of layers. The Catalog V3 contains many more resources than the geodatabase, documenting all layers that will be included in MapIT, and includes links to the original sources of the data. Within the catalog, in the final column, there is information about if the file is included in the geodatabase or not. Use the links provided in the catalog to download data directly from the original source if not included in the geodatabase. Four resources are included in this submission: 1. Geodatabase 2. ReadMe file 3. Catalog of data layers and additional data resources 4. Web link to a resource describing the motivation and reviewing the content of the geodatabase - DOE NETL Carbon Storage Site Mapping Inquiry Tool Database

carbon storage↗

DOE OSTI2021

Accessing Microsoft Access Databases Using ODBC and RODBC

ODBC (Open Database Connectivity) is an industry-standard API (Application Program Interface) that provides a standard interface, based on SQL (Structured Query Language) between applications and databases. This insulates applications from specific details of different database management systems (DBMS). Microsoft Windows TM provides an implementation of ODBC, which, along with drivers for various databases, supports the API. Windows also provides a driver for Access databases.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

PRO-X Research Reactor Database Status

The PRO-X Research Reactor Database is a functioning tool that can be used to quickly view attributes of past, current, and future research reactors. It contains all data found in the IAEA Research Reactor Database and entries generated from the M3 fuel conversion program. Additionally, it can be downloaded to any computer with the ability to run Microsoft ACCESS. Several research reactor attributes visible to the user have a limited amount of information, much of which is available and vetted for entry into the database. However, the necessary resources have not been allocated to add this information to the data tables. A change management system has also been developed to track changes to the database. This would need to be incorporated into the database program prior to data table modification in order to ensure proper management of the changes.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

An Overview of the Molten Salt Thermal Properties Database--Thermophysical, Version 3.1 (MSTDB-TP v.3.1)

This report presents the current status of the Molten Salt Thermal Properties Database–Thermophysical (MSTDB-TP). Information regarding version 3.1 is provided herein, which contains 820 individual salt entries (data from 180+ independent studies); the thermophysical properties contained in the database include density, viscosity, thermal conductivity, and heat capacity. The major updates to the database include a significant expansion of pseudobinary and higher-order chloride salt mixtures, many of which bearing actinides, and an incorporation of more recent literature data (i.e., that within the past 5 years). Also, modifications have been made to the pure compound data in the database as a consequence of an external quality assessment of duplicate datasets. The user-facing API for the MSTDB-TP, Saline, has been updated to include viscosity estimation capabilities based on the Redlich–Kister formalism; this is an advancement with respect to the existing density estimation capabilities. The graphical user interface was also updated to include a density estimation capability, backed by Saline. Finally, additional preliminary efforts to include surface tension into the database, as well as an investigation on formalisms that would be appropriate for thermal conductivity estimation, are reported herein.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Biosphere Futures: a database of social-ecological scenarios

T. Biosphere Futures (https://biospherefutures.net/) is a new online database to collect and discover scenario studies from across the world, with a specific focus on scenarios that explicitly incorporate interdependencies between humans and their supporting ecosystems. It provides access to a globally diverse collection of case studies that includes most ecosystems and regions, enabling exploration of the multifaceted ways in which the future might unfold. Together, the case studies illuminate the diversity and plurality of people’s expectations and aspirations for the future. The objective of Biosphere Futures is to promote the use of scenarios for sustainable development of the biosphere and to foster a community of practice around social-ecological scenarios. We do so by facilitating the assessment, synthesis, and comparative analysis of scenario case studies, pointing to relevant resources, and by helping practitioners and researchers to disseminate and showcase their own work. This article begins by outlining the rationale behind the creation of the database, followed by an introduction to its functionality and the criteria employed for selecting case studies. Subsequently, we present a synthesis of the first 100 case studies included in the scenarios database, highlighting emerging patterns and identifying potential avenues for further research. Finally, given that broader utilization and contributions to the database will enhance the achievement of Biosphere Futures’ objectives, we invite the creators of social-ecological scenarios to contribute additional case studies. By expanding the database’s breadth and depth, we can collectively foster a more nuanced understanding of the possible trajectories of our biosphere and enable better decision making for sustainable development.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

North American Lithium-Ion Battery Supply Chain Database Development - Phase II

Lithium-ion batteries (LIBs) are used in a wide range of applications, including cell phones, laptops, power tools, electric vehicles, and grid storage, and are essential for economic growth and addressing climate change. However, the significant demand for LIBs has led to supply chain issues for the United States, as China dominates the processing of battery materials and battery production. To address this concern, NAATBatt International, a trade association of North American battery companies, supported the National Renewable Energy Laboratory in developing a database of companies that mine, process, manufacture, reuse, and recycle batteries in North America. The purpose of this database was to identify strengths and gaps in the supply chain, so that private-government partnerships could develop strategies to create a competitive LIB supply chain in the US. NREL published the first version of this database in 2021 and the second version in 2022. The database includes companies that have a manufacturing facility in North America and are engaged in materials, cells, packs, end-of-life management, as well as those involved in LIB battery modeling, distribution, service and repair, and R&D. In this presentation, we will discuss our approach to collecting data and categorizing various segments and products. We will also provide a summary of the data and present various maps to illustrate the distribution of companies in the database.

ADVANCED PROPULSION SYSTEMS,ENERGY STORAGE↗

DOE OSTI2024

DUNE Database Development

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

BRE‐X Emissions Database for End‐of‐Life Scenarios of Selective Building Construction Materials to Enable Circular Economy in Construction

In the United States, construction and demolition debris predominately end up in landfills with minimal end‐of‐life Re‐X (recover, recycle, reuse, etc.) scenarios, resulting in large environmental impacts and lost opportunities for material recovery. Except for concrete and metals, which seem to have a few well‐defined end‐of‐life pathways, there seems to be a lack of well‐documented end‐of‐life scenarios for other construction materials, let alone their emissions data. Hence, there is a need for documented end‐of‐life Re‐X scenarios and end‐of‐life data of more building materials to motivate widespread use of Re‐X strategies in building design. This paper outlines the efforts of the National Renewable Energy Laboratory, Carbon Leadership Forum, Building Transparency, and Skidmore, Owings & Merrill to (a) create an open‐access BRE‐X (Building Re‐X) end‐of‐life emissions database consisting of greenhouse gas emissions data associated with various end‐of‐life scenarios for a select list of high‐impact building construction materials, and (b) integrate the BRE‐X end‐of‐life emissions database with CAD/BIM/LCA tools for evaluating various end‐of‐life scenarios. The paper also presents a few existing life cycle inventory databases that contain sparse amounts of end‐of‐life data for a few construction materials and their limitations in terms of scaling and data consolidation. Finally, a sample of how the collected data can be ingested into whole‐building LCA tools using open data formats and a public access link to the BRE‐X end‐of‐life emissions database is also included.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Large language model-driven database for thermoelectric materials

Thermoelectric materials have the ability to convert waste heat into electricity, offering a valuable solution for energy harvesting. However, their widespread use is hindered by low conversion efficiency, the reliance on expensive rare earth elements, and the environmental and regulatory concerns associated with lead-based materials. A fast and cost-effective way to identify highly efficient thermoelectric materials is through data-driven methods. These approaches rely on robust and comprehensive datasets to train models. Although there are several databases on thermoelectric materials, there is still a need to collect and integrate experimental data from peer-reviewed research articles to capture diverse compositions and properties of materials. Here, in this work, we developed a comprehensive database of 7,123 thermoelectric compounds, containing key information such as chemical composition, structural detail, seebeck coefficient, electrical and thermal conductivity, power factor, and figure of merit (ZT). We used the GPTArticleExtractor workflow, powered by large language models (LLM), to extract and curate data automatically from the scientific literature published in Elsevier journals. This process enabled the creation of a structured database that addresses the challenges of manual data collection. The open access database could stimulate data-driven research and advance thermoelectric material analysis and discovery.

Database↗

DOE OSTI2021

An uncertainty-focused database approach to extract spatiotemporal trends from qualitative and discontinuous lake-status histories

Changes in lake status are often interpreted as palaeoclimate indicators due to their dependence on precipitation and evaporation. The Global Lake Status Database (GLSDB) has since long provided a standardised synopsis of qualitative lake status over the last 30,000 14C years. Potential sources of uncertainty however are not recorded in the GLSDB. Here we present an updated and improved relational-database framework that incorporates uncertainty in both chronology and the interpretation of palaeoenvironmental data. The database uses peer-reviewed palaeolimnological studies to produce a consensus on qualitative lake-status histories, whose chronologies are revised and standardized through the recalibration of radiocarbon dates and the application of Bayesian age-depth modelling for stratigraphic archives. Quantitative information on absolute water-level elevation is preserved if available from geomorphological sources. We also propose a new probabilistic analytical framework that accounts for these uncertainties to reconstruct synoptic, integrated environmental signals. The process is based on a Monte Carlo algorithm that iteratively samples individual lake-status histories within the limits of their uncertainties to produce many possible scenarios. We then use Recursively-Subtracted Empirical Orthogonal Function analysis to extract dominant patterns of lake-status variability from these scenarios. As a proof of concept, we apply this framework to 67 sites in eastern and southern Africa whose lake-status histories cover part of the late Pleistocene and/or Holocene. We show that, despite the sometimes large temporal and interpretation uncertainties, and the inclusion of highly discontinuous lake-status time series, identifying the major known millennial-scale climatic phases during the last 20,000 years is possible. Our framework was also able to identify an antiphased response between the lake basins in eastern and interior southern Africa to these changes. Here, we propose that our new database and methodology framework serves as a template for efficient lake-status data synthesis, encourages the incorporation of lake-status data in palaeoclimate syntheses, and expands the possibilities for the use of such data in the evaluation of climate models.

58 GEOSCIENCES↗

DOE OSTI2020

Identifying Abandoned Well Sites Using Database Records and Aeromagnetic Surveys

Oil and natural gas are primary sources of energy in the United States. Improved drilling and extracting techniques have led to a renewed interest in historic oil and gas fields, but limited records of legacy wells make new drilling efforts more difficult, as abandoned wells may provide conduits for liquids and gases to migrate into groundwater reservoirs or the atmosphere. Well finding using aeromagnetic surveys pinpoints the location of steel-cased wells, detecting both active and abandoned wells, including buried casings lacking aboveground markers. Here, we present six aeromagnetic surveys conducted in Pennsylvania and Wyoming as case studies, comparing the magnetic points to locations known in databases. In all study sites, more magnetic points were detected than recorded in databases. Based on differences between theoretical database well counts and the actual number of wells detected in surveys, we estimated the total number of wells in Pennsylvania to be 395 000–466 000 and 181 000–182 000 in Wyoming. Extrapolating to the national level, in this work, we estimate the average number of wells in the continental United States is 6.04 ± 19.97 million wells with 1.16 ± 3.84 million of those designated as abandoned wells, within the range of previous abandoned well count estimations. Although aeromagnetic surveys are limited to detecting steel-cased wells and do not differentiate sites based on well status, this study nevertheless demonstrates the utility of aeromagnetic surveys in well finding efforts across the country and shows limitations in database records of oil and natural gas wells.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Reflections on one million compounds in the open quantum materials database (OQMD)

Abstract Density functional theory (DFT) has been widely applied in modern materials discovery and many materials databases, including the open quantum materials database (OQMD), contain large collections of calculated DFT properties of experimentally known crystal structures and hypothetical predicted compounds. Since the beginning of the OQMD in late 2010, over one million compounds have now been calculated and stored in the database, which is constantly used by worldwide researchers in advancing materials studies. The growth of the OQMD depends on project-based high-throughput DFT calculations, including structure-based projects, property-based projects, and most recently, machine-learning-based projects. Another major goal of the OQMD is to ensure the openness of its materials data to the public and the OQMD developers are constantly working with other materials databases to reach a universal querying protocol in support of the FAIR data principles.

08 HYDROGEN↗