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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↗

DOE OSTI2016

GraQL: A Query Language for High-Performance Attributed Graph Databases

Graph databases have gained increasing interest in the last few years due to the emergence of data sources which are not easily analyzable in traditional relational models or for which a graph data model is the natural representation. In order to understand the design and implementation choices for an attributed graph database backend and query language, we have started to design our infrastructure for attributed graph databases. In this paper, we describe the design considerations of our in-memory attributed graph database system with a particular focus on the data definition and query language components.

attributed graphs↗

DOE OSTI2021

The updated ITPA global H-mode confinement database: description and analysis

The multi-machine ITPA Global H-mode Confinement Database has been upgraded with new data from JET with the ITER-like wall and ASDEX Upgrade with the full tungsten wall. This paper describes the new database and presents results of regression analysis to estimate the global energy confinement scaling in H-mode plasmas using a standard power law. Various subsets of the database are considered, focusing on type of wall and divertor materials, confinement regime (all H-modes, ELMy H or ELM-free) and ITER-like constraints. Apart from ordinary least squares, two other, robust regression techniques are applied, which take into account uncertainty on all variables. Regression on data from individual devices shows that, generally, the confinement dependence on density and the power degradation are weakest in the fully metallic devices. Using the multi-machine scalings, predictions are made of the confinement time in a standard ELMy H-mode scenario in ITER. The uncertainty on the scaling parameters is discussed with a view to practically useful error bars on the parameters and predictions. One of the derived scalings for ELMy H-modes on an ITER-like subset is studied in particular and compared to the IPB98(y,2) confinement scaling in engineering and dimensionless form. Transformation of this new scaling from engineering variables to dimensionless quantities is shown to result in large error bars on the dimensionless scaling. Regression analysis in the space of dimensionless variables is therefore proposed as an alternative, yielding acceptable estimates for the dimensionless scaling. The new scaling, which is dimensionally correct within the uncertainties, suggests that some dependencies of confinement in the multi- machine database can be reconciled with parameter scans in individual devices. This includes vanishingly small dependence of confinement on line-averaged density and normalized plasma pressure (β), as well as a noticeable, positive dependence on effective atomic mass and plasma triangularity. Extrapolation of this scaling to ITER yields a somewhat lower confinement time compared to the IPB98(y, 2) prediction, possibly related to the considerably weaker dependence on major radius in the new scaling (slightly above linear). Further studies are needed to compare more flexible regression models with the power law used here. In addition, data from more devices concerning possible ‘hidden variables’ could help to determine their influence on confinement, while adding data in sparsely populated areas of the parameter space may contribute to further disentangling some of the global confinement dependencies in tokamak plasmas.

Database↗

DOE OSTI2015

Interoperability of Materials Database Systems in Support of Nuclear Energy Development and Potential Applications for Fuel Cell Material Selection

Materials database interoperability has been of great interest in recent years for information exchange in support of research and development (R&D). In response to data and knowledge sharing needs of the GenIV International Forum (GIF) for global collaboration in nuclear energy R&D, the European Commission JRC Institute for Energy and Transport (JRC-IET) and the Oak Ridge National Laboratory (ORNL) have established a materials database interoperability project that develops techniques for automated materials data exchange between systems hosted at the two institutes MatDB Online at JRC IET and the Gen IV Materials Handbook at ORNL, respectively. The work to enable automated exchange of data between the two systems leverages the XML data import and export functionalities of both systems in combination with recently developed standards for engineering materials data. The preliminary results of data communication between the two systems have demonstrated the feasibility and efficiency of materials database interoperability, which constructs an interoperation framework that can be seamlessly integrated into the high-throughput First Principles material databases and thus advance the discovery of novel materials in fuel cell applications.

36 MATERIALS SCIENCE↗

DOE OSTI2015

Materials Databases Infrastructure Constructed by First Principles Calculations: A Review

The First Principles calculations, especially the calculation based on High-Throughput Density Functional Theory, have been widely accepted as the major tools in atom scale materials design. The emerging super computers, along with the powerful First Principles calculations, have accumulated hundreds of thousands of crystal and compound records. The exponential growing of computational materials information urges the development of the materials databases, which not only provide unlimited storage for the daily increasing data, but still keep the efficiency in data storage, management, query, presentation and manipulation. This review covers the most cutting edge materials databases in materials design, and their hot applications such as in fuel cells. By comparing the advantages and drawbacks of these high-throughput First Principles materials databases, the optimized computational framework can be identified to fit the needs of fuel cell applications. The further development of high-throughput DFT materials database, which in essence accelerates the materials innovation, is discussed in the summary as well.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Data from TropiRoot 1.0 database: tropical root characteristics across environments

TropiRoot 1.0 is a new tropical root database with root characteristics across environment gradients. It has data extracted from 104 new sources, resulting in more than 8000 rows of data (either species or community data). Most of the data in TropiRoot 1.0 includes root characteristics such as root biomass, morphology, root dynamics, mass fraction, architecture, anatomy, physiology and root chemistry. This initiative represents an approximately 30% increase in the currently available data for tropical roots in the Fine Root Ecology Database (FRED). TropiRoot 1.0, contains root characteristics from 25 different countries where seven are located in Asia, six in South America, five in Central America and the Caribbean, four in Africa, two in North America, and 1 in Oceania. Due to the volume of data, when ancillary data was available, including soil data, these data was either extracted and included in the database or their availability was recorded in an additional column. Multiple contributors checked the entries for outliers during the collation process to ensure data quality. For text-based observations, we examined all cells to ensure that their content relates to their specific categories. For numerical observations, we ordered each numerical value from least to greatest and plotted the values, checking apparent outliers against the data in their respective sources and correcting or removing incorrect or impossible values. Some data (soil and aboveground) have different columns for the same variable presented in different units, including originally published units, but root characteristics data had units converted to match the ones reported in FRED. By filling a gap from global databases, TropiRoot 1.0 expands our knowledge of otherwise so far underrepresented regions, and our ability to assess global trends. This advancement can be used to improve tropical forest representation in vegetation models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

Data Preparation Process for the Buildings Performance Database

The Buildings Performance Database (BPD) includes empirically measured data from a variety of data sources with varying degrees of data quality and data availability. The purpose of the data preparation process is to maintain data quality within the database and to ensure that all database entries have sufficient data for meaningful analysis and for the database API. Data preparation is a systematic process of mapping data into the Building Energy Data Exchange Specification (BEDES), cleansing data using a set of criteria and rules of thumb, and deriving values such as energy totals and dominant asset types. The data preparation process takes the most amount of effort and time therefore most of the cleansing process has been automated. The process also needs to adapt as more data is contributed to the BPD and as building technologies over time. The data preparation process is an essential step between data contributed by providers and data published to the public in the BPD.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2015

Enhancing Disaster Management: Development of a Spatial Database of Day Care Centers in the USA

Children under the age of five constitute around 7% of the total U.S. population and represent a segment of the population, which is totally dependent on others for day-to-day activities. A significant proportion of this population spends time in some form of day care arrangement while their parents are away from home. Accounting for those children during emergencies is of high priority, which requires a broad understanding of the locations of such day care centers. As concentrations of at risk population, the spatial location of day care centers is critical for any type of emergency preparedness and response (EPR). However, until recently, the U.S. emergency preparedness and response community did not have access to a comprehensive spatial database of day care centers at the national scale. This paper describes an approach for the development of the first comprehensive spatial database of day care center locations throughout the USA utilizing a variety of data harvesting techniques to integrate information from widely disparate data sources followed by geolocating for spatial precision. In the context of disaster management, such spatially refined demographic databases hold tremendous potential for improving high resolution population distribution and dynamics models and databases.

58 GEOSCIENCES↗

DOE OSTI2016

Polarimetric Scattering Database for Non-spherical Ice Particles at Microwave Wavelengths

A database containing polarimetric single-scattering properties of various types of ice particles at millimeter to centimeter wavelengths is presented. This database is complementary to earlier ones in that it contains complete (polarimetric) scattering property information for each ice particle - 44 plates, 30 columns, 405 branched planar crystals, 660 aggregates, and 640 conical graupel - and direction of incident radiation but is limited to four frequencies (W-, Ka-, Ku- and X-bands), does not include temperature dependencies of the single-scattering properties and does not include scattering properties averaged over randomly oriented ice particles. Rules for constructing the morphologies of ice particles from one database to the next often differ; consequently, analyses that incorporate all of the different databases will contain the most variability, while illuminating important differences between them.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

Geothermal NEPA Database on OpenEI (Poster)

The National Renewable Energy Laboratory (NREL) developed the Geothermal National Environmental Policy Act (NEPA) Database as a platform for government agencies and industry to access and maintain information related to geothermal NEPA documents. The data were collected to inform analyses of NEPA timelines, and the collected data were made publically available via this tool in case others might find the data useful. NREL staff and contractors collected documents from agency websites, during visits to the two busiest Bureau of Land Management (BLM) field offices for geothermal development, and through email and phone call requests from other BLM field offices. They then entered the information into the database, hosted by Open Energy Information (http://en.openei.org/wiki/RAPID/NEPA). The long-term success of the project will depend on the willingness of federal agencies, industry, and others to populate the database with NEPA and related documents, and to use the data for their own analyses. As the information and capabilities of the database expand, developers and agencies can save time on new NEPA reports by accessing a single location to research related activities, their potential impacts, and previously proposed and imposed mitigation measures. NREL used a wiki platform to allow industry and agencies to maintain the content in the future so that it continues to provide relevant and accurate information to users.

15 GEOTHERMAL ENERGY↗

DOE OSTI2019

FY 2019 Nuclear Energy Infrastructure Database Accomplishments

The database, known as the Nuclear Energy Infrastructure Database (NEID), is accessed through a web-based application (at nsuf-infrastructure.inl.gov) and built specifically to track research and development (R&D) facilities and associated equipment throughout the DOE-NE complex. The NEID serves internal users (such as DOE personnel and national laboratory staff and researchers) and potential infrastructure users who will be able to view the inventory of DOE-NE-compatible R&D capabilities potentially available to them. NSUF utilizes the NEID to support the annual nuclear energy gap analysis process. Infrastructure needs are gathered from DOE-NE R&D programs and researchers at U.S. national laboratories, universities, and the U.S. nuclear industry. The fiscal year (FY) 2019 Nuclear Energy Infrastructure Database (NEID) Accomplishments report captures all the additions and improvements made to the database in FY 2019.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2024

Advances in Metallic Fuel Database Development and Data Qualification

The Fuels Irradiation and Physics Database (FIPD [1]) is a comprehensive repository of data and documents related to Uranium-Zirconium based metallic fuel test pins. This database stores operational conditions of these pins, calculated using a suite of Argonne National Laboratory analysis codes developed during the Integral Fast Reactor (IFR) program. Key calculated data include axial distributions of power, temperature, fluence, burnup, and isotopic densities. Additionally, the FIPD holds post-irradiation examination (PIE) data such as fission gas release, gas chemistry measurements, and axial distributions derived from profilometry, gamma scanning, and neutron radiography. Complementing these data is an extensive archive of documents related to various pins and experiments. These include raw PIE records, design details, safety analyses, and operational reports. More detail about FIPD can be found in ref. [2]. The database development is an ongoing effort covering metallic fuel experiments from the Experimental Breeder Reactor II (EBR-II) and the Fast Flux Test Facility (FFTF). The recent improvements to the database and the data QA status are summarized in this paper.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2017

Development of a Searchable Database of Cryoablation Simulations for Use in Treatment Planning

PurposeTo create and validate a planning tool for multiple-probe cryoablation, using simulations of ice ball size and shape for various ablation probe configurations, ablation times, and types of tissue ablated.Materials and MethodsIce ball size and shape was simulated using the Pennes bioheat equation. Five thousand six hundred and seventy different cryoablation procedures were simulated, using 1–6 cryoablation probes and 1–2 cm spacing between probes. The resulting ice ball was measured along three perpendicular axes and recorded in a database. Simulated ice ball sizes were compared to gel experiments (26 measurements) and clinical cryoablation cases (42 measurements). The clinical cryoablation measurements were obtained from a HIPAA-compliant retrospective review of kidney and liver cryoablation procedures between January 2015 and February 2016. Finally, we created a web-based cryoablation planning tool, which uses the cryoablation simulation database to look up the probe spacing and ablation time that produces the desired ice ball shape and dimensions.ResultsAverage absolute error between the simulated and experimentally measured ice balls was 1 mm in gel experiments and 4 mm in clinical cryoablation cases. The simulations accurately predicted the degree of synergy in multiple-probe ablations. The cryoablation simulation database covers a wide range of ice ball sizes and shapes up to 9.8 cm.ConclusionCryoablation simulations accurately predict the ice ball size in multiple-probe ablations. The cryoablation database can be used to plan ablation procedures: given the desired ice ball size and shape, it will find the number and type of probes, probe configuration and spacing, and ablation time required.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2014

An annotated database of Arabidopsis mutants of acyl lipid metabolism

Mutants have played a fundamental role in gene discovery and in understanding the function of genes involved in plant acyl lipid metabolism. The first mutant in Arabidopsis lipid metabolism ( fad4 ) was described in 1985. Since that time, characterization of mutants in more than 280 genes associated with acyl lipid metabolism has been reported. This review provides a brief background and history on identification of mutants in acyl lipid metabolism, an analysis of the distribution of mutants in different areas of acyl lipid metabolism and presents an annotated database (ARALIPmutantDB) of these mutants. The database provides information on the phenotypes of mutants, pathways and enzymes/proteins associated with the mutants, and allows rapid access via hyperlinks to summaries of information about each mutant and to literature that provides information on the lipid composition of the mutants. Mutants for at least 30 % of the genes in the database have multiple names, which have been compiled here to reduce ambiguities in searches for information. Furthermore, the database should also provide a tool for exploring the relationships between mutants in acyl lipid-related genes and their lipid phenotypes and point to opportunities for further research.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

A harmonized longitudinal biomarkers and cognition database for assessing the natural history of preclinical Alzheimer's disease from young adulthood and for designing prevention trials

Abstract Introduction Large longitudinal biomarkers database focusing on middle age is needed for Alzheimer's disease (AD) prevention. Methods Data for cerebrospinal fluid analytes, molecular imaging of cerebral fibrillar β‐amyloid with positron emission tomography, magnetic resonance imaging–based brain structures, and clinical/cognitive outcomes were harmonized across eight AD biomarker studies. Statistical power was estimated. Results The harmonized database included 7779 participants with clinical/cognitive data: 3542 were 18∼65 years at the baseline, 5865 had longitudinal cognitive data for a median of 4.7 years, 2473 participated in the cerebrospinal fluid studies (906 had longitudinal data), 2496 participated in the magnetic resonance imaging studies (1283 had longitudinal data), and 1498 participated in the positron emission tomography amyloid studies (849 had longitudinal data). The database provides adequate power for detecting early biomarker changes, and demonstrates the feasibility of AD prevention trials on middle‐aged individuals. Discussion The harmonized database is an optimum resource to design AD prevention trials decades before symptomatic onset.

Xiong, Chengjie↗

DOE OSTI2023

A database of ultrastable MOFs reassembled from stable fragments with machine learning models

High-throughput screening of hypothetical metal-organic framework (MOF) databases can uncover new materials, but their stability in real-world applications is often unknown. We leverage community knowledge and machine learning (ML) models to identify MOFs that are thermally stable and stable upon activation. We separate these MOFs into their building blocks and recombine them to make a new hypothetical MOF database of over 50,000 structures with orders of magnitude more (1) connectivity nets and (2) inorganic building blocks than were present in prior databases. Further, this database shows a 10-fold enrichment of ultrastable MOF structures that are stable upon activation and more than 1 standard deviation more thermally stable than the average experimentally characterized MOF. For nearly 10,000 ultrastable MOFs, we compute elastic moduli to confirm that these materials have good mechanical stability, and we report methane deliverable capacities. We identify privileged metal nodes in ultrastable MOFs that optimize gas storage and mechanical stability simultaneously.

36 MATERIALS SCIENCE↗

DOE OSTI2021

FIPD: The SFR metallic fuels irradiation & physics database

The DOE Advanced Reactor Technology (ART) program has supported efforts to recover and preserve metallic fuel data generated throughout the US sodium-cooled fast reactor (SFR) program. Those efforts have been focused on establishing databases of the experimental data that were mainly generated during the Integral Fast Reactor (IFR) program including data generated at Experimental Breeder Reactor-II (EBR-II), Fast Flux Test Facility (FFTF), and Transient Reactor Test Facility (TREAT) reactors, as well as out of pile data. The data is essential for future licensing activities of metallic fuel based advanced fast reactors. This paper describes the development of the SFR Metallic Fuels Irradiation & Physics Database (FIPD) and covers the scientific knowledge available in the database. Furthermore, the architecture of the FIPD is described by showing the available reactor operation data, fabrication, and post-irradiation examination (PIE) data, and other documents. The applications of the fuel database are also discussed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Initial demonstration of automated fuel performance modeling with 1977 EBR-II metallic fuel pins using BISON code with FIPD and IMIS databases

Using the BISON fuel performance code, simulations were conducted using an automated process to read initial and operating conditions from the Fuels Irradiation and Physics Database (FIPD) and Integral Fast Reactor materials information system (IMIS) database, which contains metallic fuel data from the Experimental Breeder Reactor-II (EBR-II). This work demonstrates use of an integrated framework to access the vast majority of EBR-II experimental fuel pin data to support rapid development of fuel performance models for next-generation metallic fuel systems. With this capability, validation for fuel qualification can be performed rapidly. Between IMIS and FIPD, there is enough information to conduct 1977 unique EBR-II metallic fuel pin histories from 24 different experiments, at varying levels of detail between the two databases. Each of these histories includes a high-resolution power history, flux history, coolant channel flow rates, and coolant channel temperatures. Fission gas release (FGR), cumulative damage fraction (CDF), fuel axial swelling, cladding profilometry, and burnup were all simulated in BISON. The results were compared to post-irradiation examination (PIE) results for the initial demonstration of automated BISON modeling. BISON simulations conducted with IMIS and FIPD were in rough agreement with PIE measurements and calculations. Cladding profilometry, FGR, and fuel axial swelling were found to be in rough agreement with PIE measurements, depending on the physics used within the BISON input files. Here, the mechanical contact solver chosen was found to significantly impact axial fuel swelling and cladding strain predictions. CDF values were assessed to see whether pin failure may have been predicted (CDF ≥ 1). This work suggests that continued development of an automated tool for BISON should focus on inclusion of the Fast Flux Test Facility (FFTF) experimental data for a larger database for metallic fuel, improved physical models to better capture fuel performance, such as fuel-cladding interactions, and a more detailed comparison with available PIE data to further the BISON model development.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗