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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 55 records · Page 3

Validation of standardized data formats and tools for ground-level particle-based gamma-ray observatories

Context. Ground-based γ-ray astronomy is still a rather young field of research, with strong historical connections to particle physics. This is why most observations are conducted by experiments with proprietary data and analysis software, as is usual in the particle physics field. However, in recent years, this paradigm has been slowly shifting toward the development and use of open-source data formats and tools, driven by upcoming observatories such as the Cherenkov Telescope Array (CTA). In this context, a community-driven, shared data format (the gamma-astro-data-format, or GADF) and analysis tools such as Gammapy and ctools have been developed. So far, these efforts have been led by the Imaging Atmospheric Cherenkov Telescope community, leaving out other types of ground-based γ-ray instruments. Aims. We aim to show that the data from ground particle arrays, such as the High-Altitude Water Cherenkov (HAWC) observatory, are also compatible with the GADF and can thus be fully analyzed using the related tools, in this case, Gammapy. Methods. We reproduced several published HAWC results using Gammapy and data products compliant with GADF standard. We also illustrate the capabilities of the shared format and tools by producing a joint fit of the Crab spectrum including data from six different γ-ray experiments. Results. We find excellent agreement with the reference results, a powerful confirmation of both the published results and the tools involved. Conclusions. The data from particle detector arrays such as the HAWC observatory can be adapted to the GADF and thus analyzed with Gammapy. A common data format and shared analysis tools allow multi-instrument joint analysis and effective data sharing. To emphasize this, a sample of Crab nebula event lists is made public with this paper. Because of the complementary nature of pointing and wide-field instruments, this synergy will be distinctly beneficial for the joint scientific exploitation of future observatories such as the Southern Wide-field Gamma-ray Observatory and CTA.

79 ASTRONOMY AND ASTROPHYSICS↗

WETO Stack [SWR-24-81]

The WETO Stack software is a collection of data, data analysis scripts, and website content produced through the Holistic Modeling Project’s Portfolio Coordination task. The purpose of the software is to characterize the collection of wind energy software projects supported by the U.S. Department of Energy’s Wind Energy Technologies Office. The included data contains characteristics of the actively funded software projects, and the data analysis scripts provide insights into the breadth, depth, and maturity of the collection of software projects. The website content presents the results of the analyses as well as reports from workshops and other events. It can be viewed at https://nrel.github.io/WETOStack/index.html.

Mudafort, Rafael↗

Picometer-Precision Atomic Position Tracking through Electron Microscopy

The modern aberration-corrected scanning electron microscopes have successfully achieved direct visualization of atomic columns with sub-angstrom resolution. With this significant progress, advanced image quantification and analysis is still at its early stages. In this work, we present the complete pathway for the metrology of atomic resolution STEM images. This includes: 1) tips for acquiring high-quality STEM images; 2) denoising and drift-correction for enhancing measurement accuracy; 3) obtaining initial atom positions; 4) indexing the atoms based on unit cell vectors; 4) quantifying the atom column positions with either 2D-gaussian single peak fitting or 5) multi-peak fitting routines for slightly overlapping atomic columns; 6) quantification of lattice distortion/strain within the crystal structures or at the defects/interfaces where the lattice periodicity is disrupted, and 7) some common methods to visualize and present the analysis. Furthermore, a simple self-developed free MATLAB app (EASY-STEM) with a graphical user interface (GUI) will be introduced that can help with the analysis of STEM images without the need for writing dedicated analysis code or software. The advanced data analysis methods presented here can be applied for the local quantification of defect relaxations, local structural distortions, local phase transformations, and non-centrosymmetry in a wide range of materials.

47 OTHER INSTRUMENTATION↗

Integrated, Interoperable Software Environment for Fusion Simulation and Data Analysis Tools SBIR Phase II

This SBIR effort was focused on developing a production ready system to address the integration and interoperability challenges with analysis and visualization in fusion simulations. Our overarching technical objective was to minimize the code development simulation scientists incur when coupling their simulation codes with different analysis frameworks. To this end, we developed an open-source software library to make data exchange between application easier and a Web application to manage and display analysis extracts from simulations. We have also augmented existing libraries funded by DOE such as ADIOS and VTK-m. When used together, these make it significantly easier to integrate simulation and analysis capability. We demonstrated the flexibility of our approach using two common simulation codes in the fusion community, XGC1 and GTC.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Exploring Ion Mobility Mass Spectrometry Data File Conversions to Leverage Existing Tools and Enable New Workflows

Ion mobility (IM) is often combined with LC-MS experiments to provide an additional dimension of separation for complex sample analysis. While highly complex samples are better characterized by the full dimensionality of LC-IM-MS experiments to uncover new information, downstream data analysis workflows are often not equipped to properly mine the additional IM dimension. For many samples the data acquisition benefits of including IM separations are all that is necessary to uncover sample information and the full dimensionality of the data is not required for data analysis. Post-acquisition reduction and adaptation of the dimensions of LC-IM-MS and IM-MS experiments into an LC-MS format opens the possibility to use a plethora of existing software tools. In this work, we developed data file conversion tools to reduce the complexity of IM data analysis. Three data file transformations are introduced in the PNNL PreProcessor software: 1) mapping the IM axis to the LC axis for IM-MS data, 2) converting the drift time vs. m/z space to CCS/z vs m/z space, and 3) transforming All Ions IM/MS mobility aligned fragmentation data to a standard LC-MS DDA data file format. Finally, these new data file conversions are demonstrated with corresponding lipidomics and proteomics workflows that leverage existing LC-MS data analysis software to highlight the benefits of the data transformations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Software Development for Data Visualization and Analysis of PN-Diodes & MOSFET Devices

The U.S. Department of Energy has a broad mission to ensure the nation’s security by addressing ongoing environmental challenges, developing novel energy production technologies, and mitigating nuclear security concerns. These efforts benefit from developing more effective semiconductor materials and devices. The research discussed in this report aims to further the development of these new electronics by improving implementations of vertical device structures, which offer theoretically better performance compared to lateral structures. Specifically, it reviews the background and development of a new and easy-to-use program for data processing and analysis from experiments run on vertical gallium nitride power devices. Current vertical structures fall short in critical performance metrics, such as On-Resistance and Breakdown Voltage, due to poor management of the device’s electric field. Junction termination extensions, or JTEs, are a field management technique that increases a device’s resilience to expected failure modes by controlling its surface electric fields. Each JTE design requires significant experimental validation, consisting of hundreds of tested devices, each outputting an enormous set of data points. The new software includes multiple methods of filtering large sets of device testing data to identify and remove flawed devices, automate device analyses, and provide statistical breakdowns for four metrics used to define the effectiveness of the JTE and the current carrying capacity of the device. These results can then be related back to fabrication techniques and device design, and in the future, be combined with processing simulations to further improve our understanding of the JTE mechanisms.

97 MATHEMATICS AND COMPUTING↗

LevSeq: Rapid Generation of Sequence-Function Data for Directed Evolution and Machine Learning

Sequence-function data provides valuable information about the protein functional landscape but is rarely obtained during directed evolution campaigns. Here, we present Long-read every variant Sequencing (LevSeq), a pipeline that combines a dual barcoding strategy with nanopore sequencing to rapidly generate sequence-function data for entire protein-coding genes. LevSeq integrates into existing protein engineering workflows and comes with open-source software for data analysis and visualization. The pipeline facilitates data-driven protein engineering by consolidating sequence-function data to inform directed evolution and provide the requisite data for machine learning-guided protein engineering (MLPE). LevSeq enables quality control of mutagenesis libraries prior to screening, which reduces time and resource costs. Simulation studies demonstrate LevSeq’s ability to accurately detect variants under various experimental conditions. Lastly, we show LevSeq’s utility in engineering protoglobins for new-to-nature chemistry. Widespread adoption of LevSeq and sharing of the data will enhance our understanding of protein sequence-function landscapes and empower data-driven directed evolution.

59 BASIC BIOLOGICAL SCIENCES↗

CDB-AP: An application for coincidence Doppler broadening spectroscopy analysis

Coincidence Doppler Broadening (CDB) Positron Annihilation Spectroscopy (PAS) is a material analysis technique that can be used to non-destructively measure characteristics of structural defects in samples. Analyzing and comparing large datasets obtained using this technique, however, can be complicated and time intensive. The Coincidence Doppler Broadening Analysis Program (CDB-AP) is a graphical user interface that facilitates rapid analysis of many data files while using transparent processes. It is already used in three laboratories at Idaho National Laboratory and can be used in laboratories worldwide.

36 MATERIALS SCIENCE↗

hpMCA: A Python-based Graphical Program for Energy Dispersive X-Ray Diffraction Data Collection and Analysis

Energy-dispersive X-ray diffraction (EDXD) at synchrotron beamlines is commonly used for the study of material properties under high pressure and/or high temperature. Experimenters typically rely on the availability of robust data collection and analysis at a beamline, but this has become increasingly difficult, especially with the introduction of multi-element detectors that generate complex, multi-dimensional data sets. These data sets have energy resolution, and they can also be resolved in relation to sample position, diffraction angle, or different external stimuli. We report a new Python-based graphical program, hpMCA, for EDXD data collection and analysis that streamlines the experimental process for the beamline users. The program features a user-friendly interface, capability for online viewing and analyzing data from multi-element energy-dispersive detectors, and includes features useful for working with samples under high pressure and/or high temperature, such as crystal phase identification, real-time unit cell lattice refinement, and pressure determination based on an equation of state.

data analysis software↗

DSPS: Differentiable stellar population synthesis

ABSTRACT Models of stellar population synthesis (SPS) are the fundamental tool that relates the physical properties of a galaxy to its spectral energy distribution (SED). In this paper, we present DSPS: a python package for SPS. All of the functionality in DSPS is implemented natively in the JAX library for automatic differentiation, and so our predictions for galaxy photometry are fully differentiable, and directly inherit the performance benefits of JAX, including portability onto GPUs. DSPS also implements several novel features, such as i) a flexible empirical model for stellar metallicity that incorporates correlations with stellar age, ii) support for the Diffstar model that provides a physically-motivated connection between the star formation history of a galaxy (SFH) and the mass assembly of its underlying dark matter halo. We detail a set of theoretical techniques for using autodiff to calculate gradients of predictions for galaxy SEDs with respect to SPS parameters that control a range of physical effects, including SFH, stellar metallicity, nebular emission, and dust attenuation. When forward modelling the colours of a synthetic galaxy population, we find that DSPS can provide a factor of 5 speed-up over standard SPS codes on a CPU, and a factor of 300-400 on a modern GPU. When coupled with gradient-based techniques for optimization and inference, DSPS makes it practical to conduct expansive likelihood analyses of simulation-based models of the galaxy–halo connection that fully forward model galaxy spectra and photometry.

79 ASTRONOMY AND ASTROPHYSICS↗

Periodicity significance testing with null-signal templates: reassessment of PTF’s SMBH binary candidates

Periodograms are widely employed for identifying periodicity in time series data, yet they often struggle to accurately quantify the statistical significance of detected periodic signals when the data complexity precludes reliable simulations. We develop a data-driven approach to address this challenge by introducing a null-signal template (NST). The NST is created by carefully randomizing the period of each cycle in the periodogram template, rendering it non-periodic. It has the same frequentist properties as a periodic signal template, and we show with simulations that the distribution of false positives is the same as with the original periodic template, regardless of the underlying data. Thus, performing a periodicity search with the NST acts as an effective simulation of the null (no-signal) hypothesis, without having to simulate the noise properties of the data. We apply the NST method to the supermassive black hole binaries (SMBHB) search in the Palomar Transient Factory (PTF), where Charisi et al. had previously proposed 33 high signal-to-noise candidates utilizing simulations to quantify their significance. Our approach reveals that these simulations do not capture the complexity of the real data. There are no statistically significant periodic signal detections above the non-periodic background. To improve the search sensitivity, we introduce a Gaussian quadrature based algorithm for the Bayes Factor with correlated noise as a test statistic. We show with simulations that this improves sensitivity to true signals by more than an order of magnitude. However, the Bayes Factor approach also results in no statistically significant detections in the PTF data.

79 ASTRONOMY AND ASTROPHYSICS↗

GeoTGo: AI/ML software for development of community geothermal resources

For effective and equitable outcomes in achieving the national goal of net-zero carbon emissions, communities must be not only included, but even lead the implementation of innovative green-energy technologies. Collaborations with communities should happen through informed decision-making, community-centered research and engagement of stakeholders at the local, state, and regional levels. Community-led research and implementation are fundamental to achieving success. These collaborations include rule makers, environmental regulators, clean energy industries, and technology researchers and developers. Unfortunately, many green infrastructure initiatives still adhere to a top-down and expert-driven process of site selection and design without awareness and acknowledgment of public engagement needs. This can lead to costly delays, including lawsuits, and ultimately less than desired or lacking outcomes as well as missed opportunities1. Geothermal, like many new technologies whose social and economic impacts are not fully understood, often cause disproportionately high adverse effects on disadvantaged communities. These effects can be related to human health, environmental, climate, and other cumulative impacts, as well as the accompanying economic challenges of these impacts. We are focusing our work on the needs of the New Mexico Native American Pueblos and Tribes (NMP&T). To address these needs, we are developing a novel web-based interactive software and user friendly interface called GeoTGO (https://geotgo.com) that provides everything that is needed for communities to better understand and develop their geothermal resources. We will bridge the gap between technology advancements and community needs by facilitating the interactions between the geothermal industry, regulators, stakeholders, and end-users. GeoTGO will merge data, software (including data analysis, text mining, artificial intelligence, and modeling tools), knowledge, expertise, and experience to provide fast processing and dissemination of the latest information about cutting-edge geothermal technologies to users and communities. More information about the project is available at https://envitrace.com/projects/geotgo.html.

15 GEOTHERMAL ENERGY↗

Plutonium Basket Counter Measurement Control Q3-Q4 2023

The Plutonium Basket Counter (PBC) is a spent fuel nuclear safeguards instrument that was developed to measure spent-fuel elements from MAGNOX-type research reactors and determine their plutonium content. The instrument is designed to measure fuel elements in spent fuel cooling pools through underwater operation, but it is also able to measure radiation sources in air. The PBC determines fuel plutonium content by detecting neutrons with an array of Helium-3 detectors. The electronics make use of a JSR-15 shift register for data collection and IAEA Neutron Coincidence Counting (INCC) software for data analysis. The PBC is used to determine the 240 Pu content in spent MAGNOX fuel elements grouped into basket-like bundles, thus the instrument’s name. Reactor burnup calculations can be used in conjunction with the data from the PBC to estimate the total plutonium content in the fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

2020 Multiscale Microbial Dynamics Modeling Course

The 2020 Multiscale Microbial Dynamics course is adapted from the virtual 2020 Mutliscale Microbial Dynamics Summer School that was hosted by Environmental Molecular Sciences Laboratory (EMSL), a U.S. Department of Energy (DOE) science user facility located on the Pacific Northwest National Laboratory (PNNL) campus, in collaboration with the Joint Genome Institute (JGI) and the DOE Systems Biology Knowledgebase (KBase). The course course covers how to incorporate microbial metagenomic and environmental metabolite data from watershed ecosystems into metabolic and community modeling using computational frameworks, such as KBase and PFLOTRAN. The curriculum includes lectures and software and data analysis tutorials. All materials are freely accessible to the community as part of the 2020 Microbial Dynamics Summer School Organization in KBase.

54 ENVIRONMENTAL SCIENCES↗

Synchrotron-based techniques for characterizing STCH water-splitting materials

Understanding the role of oxygen vacancy–induced atomic and electronic structural changes to complex metal oxides during water-splitting processes is paramount to advancing the field of solar thermochemical hydrogen production (STCH). The formulation and confirmation of a mechanism for these types of chemical reactions necessitate a multifaceted experimental approach, featuring advanced structural characterization methods. Synchrotron X-ray techniques are essential to the rapidly advancing field of STCH in part due to properties such as high brilliance, high coherence, and variable energy that provide sensitivity, resolution, and rapid data acquisition times required for the characterization of complex metal oxides during water-splitting cycles. X-ray diffraction (XRD) is commonly used for determining the structures and phase purity of new materials synthesized by solid-state techniques and monitoring the structural integrity of oxides during water-splitting processes (e.g., oxygen vacancy–induced lattice expansion). X-ray absorption spectroscopy (XAS) is an element-specific technique and is sensitive to local atomic and electronic changes encountered around metal coordination centers during redox. While in operando measurements are desirable, the experimental conditions required for such measurements (high temperatures, controlled oxygen partial pressures, and H 2 O) practically necessitate in situ measurements that do not meet all operating conditions or ex situ measurements. Here, we highlight the application of synchrotron X-ray scattering and spectroscopic techniques using both in situ and ex situ measurements, emphasizing the advantages and limitations of each method as they relate to water-splitting processes. The best practices are discussed for preparing quenched states of reduction and performing synchrotron measurements, which focus on XRD and XAS at soft (e.g., oxygen K-edge, transition metal L-edges, and lanthanide M-edges) and hard (e.g., transition metal K-edges and lanthanide L-edges) X-ray energies. The X-ray absorption spectra of these complex oxides are a convolution of multiple contributions with accurate interpretation being contingent on computational methods. The state-of-the-art methods are discussed that enable peak positions and intensities to be related to material electronic and structural properties. Through careful experimental design, these studies can elucidate complex structure–property relationships as they pertain to nonstoichiometric water splitting. A survey of modern approaches for the evaluation of water-splitting materials at synchrotron sources under various experimental conditions is provided, and available software for data analysis is discussed.

08 HYDROGEN↗

Echo: Data and Analysis Management [Slides]

Echo software capabilities are described. Echo provides a comprehensive suite of tools for data wrangling, management, and analysis. It is an object-oriented approach to data analysis designed for robust and scalable execution of complex analysis workflows written in MATLAB.

97 MATHEMATICS AND COMPUTING↗