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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Automated Energy-Dispersive X-ray Spectroscopy Analysis for Multi-Modal Few-Shot Learning

Scanning transmission electron microscopy (STEM) is a powerful tool that allows for the atomic-scale analysis of a materials’ structure, chemistry, and defect domains (Akers et al. 2021). The current generation of microscopes generate vast amounts of data, surpassing the limits of effective manual analysis traditionally performed by domain experts (Spurgeon et al. 2021). While recent strides in machine learning have significantly enhanced the processing of large and intricate datasets acquired through electron microscopy, the prevalent use of proprietary software packages for initial data collection poses a challenge. In many cases, these software packages act as a ‘black box’, constraining user functionality and hindering the output of data in a format that is conducive to seamless integration into machine learning models. This work addresses these challenges by adapting HyperSpy, an open-source Python library, for the analysis and quantification of raw energy dispersive spectroscopy (EDS) data acquired through STEM. The modified HyperSpy code successfully facilitates user-defined segmentation of the data, enabling the integration of atomic %, weight %, and raw EDS spectra for each segmented region into an existing few-shot machine learning model. While initial results reveal discrepancies in quantified atomic and weight percentages when compared to proprietary software, ongoing efforts aim to rectify this issue by refining the fit of the HyperSpy model to the EDS spectra. Overall, this research underscores the potential of open-source tools like HyperSpy to enhance the accessibility of analytical tools, fostering a transparent and user-friendly environment for seamlessly incorporating electron microscopy data into machine learning models.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Towards a Verifiable Domain-Specific Language for Hardware-Accelerated Stencils

Defining a domain-specific language (DSL) that supports vector-calculus abstractions eases the porting of partial differential equation (PDE) solvers to specialized architectures. Sufficiently high-level abstractions empower users to express universal laws with sufficient generality that the laws must always hold true within their domain of validity. A broad class of PDE solvers employs stencil-based algorithms, the target domain of Berkeley Lab's stencil accelerator chip co-design project. First released as open-source in January 2026, the Formal software framework lays a foundation for defining an embedded DSL based on composable operators that implement mimetic numerical methods -- stencil algorithms that guarantee satisfaction of discrete versions of important vector calculus theorems. The Formal DSL will be the frontend to a new class of stencil-PDE accelerators developed jointly by LBNL, UHCL, and UC Berkeley through the DOE Competitive Portfolios for Computer Science Project. This offers the potential of an order of magnitude acceleration for this important category of computational methods to serve the DOE mission. Future work on the Formal DSL will facilitate software verification via type-safe templates that enable problem-specific correctness proofs relying upon generic function theory and carefully crafted unit tests.

Rouson, Damian↗
DOE OSTI2023

Multiscale Development and Validation of the Stainless Steel Alloy Corrosion (SStAC) Tool for High Temperature Engine Materials

The goal of this project was to create a simulation tool to assist in part design, reducing costs by eliminating the need for conservative material selection, and enabling alloy optimization to improve corrosion resistance. Thus, it helps decrease costs for existing engines and assists in the material and engine design for the engines of the future. To meet our stated goal, we developed the Stainless-Steel Alloy Corrosion (SStAC) tool, which: (1) Models corrosion of engine valves fabricated from 21-2N valve steel in an engine environment at temperatures up to 800 °C. (2) Runs in 1D for a fast estimate of the corrosion rate, and in 2D or 3D for more detailed simulations that represent any part geometry and predict the precise location and rate of corrosion and its impact on the mechanical and thermal behavior. (3) Was implemented using the open-source Multiphysics Object Oriented Simulation Environment (MOOSE). (4) Couples the corrosion model with mechanics and thermal transport models. The SStAC tool can predict the corrosion rate of 21-2N engine valves with less than 10% error.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Five reasons why the US should not withdraw from the Open Skies Treaty

In October 2019, reports emerged that the Trump administration was considering a withdrawal from the Open Skies Treaty. According to media sources, President Trump has already signed a memorandum to leave the treaty, but the United States has not yet officially initiated the six-month withdrawal process. This article discusses 5 reasons why the U.S. should not withdraw.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Target–decoy false discovery rate estimation using Crema

Assigning statistical confidence estimates to discoveries produced by a tandem mass spectrometry proteomics experiment is critical to enabling principled interpretation of the results and assessing the cost/benefit ratio of experimental follow-up. The most common technique for computing such estimates is to use target-decoy competition (TDC), in which observed spectra are searched against a database of real (target) peptides and a database of shuffled or reversed (decoy) peptides. TDC procedures for estimating the false discovery rate (FDR) at a given score threshold have been developed for application at the level of spectra, peptides, or proteins. Although these techniques are relatively straightforward to implement, it is common in the literature to skip over the implementation details or even to make mistakes in how the TDC procedures are applied in practice. Here we present Crema, an open-source Python tool that implements several TDC methods of spectrum-, peptide- and protein-level FDR estimation. Crema is compatible with a variety of existing database search tools and provides a straightforward way to obtain robust FDR estimates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Use of an ion mobility spectrometer for detecting uranium compounds

The safeguards community currently lacks a method to rapidly determine the chemical form of radioactive and non-radioactive compounds in real time during inspection activities. Chemical speciation identification can provide important information on both the types of materials that are collected during environmental sampling and can inform inspectors as to where to focus efforts during inspections or complementary access visits. Ion Mobility Spectrometry (IMS) is an established field technique for the detection of explosives, narcotics, and other organic compounds. More recently, electrospray ionization (ESI) has been used to introduce inorganic compounds to IMS instruments for analysis. These techniques have shown the ability to supply chemical information about the compounds being analyzed. Although these laboratory based instruments use a liquid-based injection system, there is evidence in the literature of unaltered and intact pharmaceutical tablets being volatilized and ionized in open atmosphere using heat and a Ni-63 source. Lastly, this work determined that a commercial-off-the-shelf (COTS) IMS could be used for the identification of solid uranium compounds directly after sampling using a COTS sample swipe.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Extracting Knowledge from Data through Catalysis Informatics

Catalysis informatics is a distinct sub-field that lies at the intersection of cheminformatics and materials informatics, but with unique challenges arising from the dynamic, surface-sensitive, multi-scale nature of heterogeneous catalysis. The ideas behind catalysis informatics can be traced back decades, but the field is only recently emerging due to advances in data infrastructure, statistics, machine learning, and computational methods. In this work we review the field from early works on expert systems and knowledge engines to more recent approaches utilizing machine-learning and uncertainty quantification. The data-information-knowledge hierarchy is introduced and used to classify various developments. The chemical master equation and micro-kinetic models are proposed as a quantitative representation of catalysis knowledge, which can be used to generate explanative and predictive hypotheses for the understanding and discovery of catalytic materials. We discuss future prospects for the field, including improved quantitative coupling of experiment/theory, advanced micro-kinetic models, and the development of open-source software tools. As a result, integration of existing chemical and physical models with emerging statistical and computational tools presents a promising route toward the automated design, discovery, and optimization of heterogeneous catalytic processes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Design of an epithermal neutron velocity selection system for the Penn State Breazeale Reactor

A series of mechanical neutron choppers to operate as a velocity selection system have been developed for the Pennsylvania State Breazeal Reactor (PSBR). This chopper system will provide pulsed epithermal neutrons in the energy range of 0.5–40 eV with 2% or better energy resolution, and with a transmission of 1E-6 or better. Four different chopper geometries have been evaluated for their utility as mechanical neutron choppers. Specifically, Fermi, ring, piston, and disc choppers have been evaluated to assess their potential neutronics performance and mechanical constructability. A series of high-speed disc choppers were selected for the final design, and optimization work was performed to maximize the neutron pulse intensity. It is estimated that the optimized system will produce an epithermal neutron intensity of approximately 96 n/s. This system can also be operated in a time of flight (TOF) configuration such that the neutrons arriving at the source have a white spectrum. This operation can be accomplished by leaving the second stage of choppers in the open position, or by removing it from the beam completely. Such unique source of epithermal neutrons produced by this chopper system will have applications in both prompt and delayed epithermal neutron activation analysis (ENAA), as well as in neutron resonance transmission analysis (NRTA).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Conserved HA-peptide NG34 formulated in pCMV-CTLA4-Ig reduces viral shedding in pigs after a heterosubtypic influenza virus SwH3N2 challenge

Swine influenza viruses (SIVs), the causal agents of swine influenza, are not only important to control due to the economic losses in the swine industry, but also can be pandemic pathogens. Vaccination is one of the most relevant strategies to control and prevent influenza infection. Current human vaccines against influenza induce strain-specific immunity and annual update is required due to the virus antigenic shift phenomena. Previously, our group has reported the use of conserved hemagglutinin peptides (HA-peptides) derived from H1-influenza virus as a potential multivalent vaccine candidate. Immunization of swine with these HA-peptides elicited antibodies that recognized and neutralized heterologous influenza viruses in vitro and demonstrated strong hemagglutination-inhibiting activity. In the present work, we cloned one HA-peptide (named NG34) into a plasmid fused with cytotoxic T lymphocyte-associated antigen (CTLA4) which is a molecule that modifies T cell activation and with an adjuvant activity interfering with the adaptive immune response. The resulting plasmid, named pCMV-CTLA4-Ig-NG34, was administered twice to animals employing a needle-free delivery approach. Two studies were carried out to test the efficacy of pCMV-CTLA4-Ig-NG34 as a potential swine influenza vaccine, one in seronegative and another in seropositive pigs against SIV. The second one was aimed to evaluate whether pCMV-CTLA4-Ig-NG34 vaccination would overcome maternally derived antibodies (MDA). After immunization, all animals were intranasally challenged with an H3N2 influenza strain. A complete elimination or significant reduction in the viral shedding was observed within the first week after the challenge in the vaccinated animals from both studies. In addition, no challenged heterologous virus load was detected in the airways of vaccinated pigs. Overall, it is suggested that the pCMV-CTLA4-Ig-NG34 vaccine formulation could potentially be used as a multivalent vaccine against influenza viruses. © 2019 Sisteré-Oró et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

A scaling law of the neutral penetration length and Balmer- α wing shape in high-temperature plasmas

Hydrogen atoms penetrating deep inside high-temperature magnetically confined plasmas by repetitive charge-exchange collisions result in a particle source of the plasma, which affects the plasma transport significantly. In this paper, we present an approximate solution of the fluid equations for neutral transport and an analytical representation of the neutral penetration length, in a simplified plasma geometry. This analysis predicts a power-law decay in the Balmer-α line wings which reflects the velocity distribution of the neutral atoms, with the power-law exponent analytically represented as well. These scaling laws are compared with a simple Monte–Carlo simulation and spectroscopic observations of Large Helical Device plasmas. Since the Balmer-α line wings are experimentally accessible, our formulation opens the possibility to quickly estimate the neutral penetration length from spectroscopic observations.

neutral opacity↗
DOE OSTI2020

Exploring MDSplus data-acquisition software and custom devices

MDSplus is a software tool designed for data acquisition, storage, and analysis of complex scientific experiments. Over the years, MDSplus has primarily been used for data management for fusion experiments. This paper demonstrates that MDSplus can be used for a much wider variety of systems and experiments. We present a step-by-step tutorial describing how to create a simple experiment, manage the data, and analyze it using MDSplus and Python. To this end, a custom example device was developed to be used as the data source. This device was built on an open-source electronic hardware platform, and it consists of a microcontroller and two sensors. Finally, we read data from these sensors, store it in MDSplus, and use JupyterLab to visualize and process it.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

The ATLAS multi-user upgrade and potential applications

With the recent integration of the CARIBU-EBIS charge breeder into the ATLAS accelerator system to provide for more pure and efficient charge breeding of radioactive beams, a multi-user upgrade of the ATLAS facility is being proposed to serve multiple users simultaneously. ATLAS was the first superconducting ion linac in the world and is the US DOE low-energy Nuclear Physics National User Facility. The proposed upgrade will take advantage of the continuous-wave nature of ATLAS and the pulsed nature of the EBIS charge breeder in order to simultaneously accelerate two beams with very close mass-to-charge ratios; one stable from the existing ECR ion source and one radioactive from the newly commissioned EBIS charge breeder. In addition to enhancing the nuclear physics program, beam extraction at different points along the linac will open up the opportunity for other potential applications; for instance, material irradiation studies at ~ 1 MeV/u and isotope production at ~ 6 MeV/u or at the full ATLAS energy of ~ 15 MeV/u. Furthermore, the concept and proposed implementation of the ATLAS multi-user upgrade will be presented. Future plans to enhance the flexibility of this upgrade will also be presented.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

MetaboDirect: an analytical pipeline for the processing of FT-ICR MS-based metabolomic data

Background: Microbiomes are now recognized as the main drivers of ecosystem function ranging from the oceans and soils to humans and bioreactors. However, a grand challenge in microbiome science is to characterize and quantify the chemical currencies of organic matter (i.e., metabolites) that microbes respond to and alter. Critical to this has been the development of Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS), which has drastically increased molecular characterization of complex organic matter samples, but challenges users with hundreds of millions of data points where readily available, user-friendly, and customizable software tools are lacking. Results: Here, we build on years of analytical experience with diverse sample types to develop MetaboDirect, an open-source, command-line-based pipeline for the analysis (e.g., chemodiversity analysis, multivariate statistics), visualization (e.g., Van Krevelen diagrams, elemental and molecular class composition plots), and presentation of direct injection high-resolution FT-ICR MS data sets after molecular formula assignment has been performed. When compared to other available FT-ICR MS software, MetaboDirect is superior in that it requires a single line of code to launch a fully automated framework for the generation and visualization of a wide range of plots, with minimal coding experience required. Among the tools evaluated, MetaboDirect is also uniquely able to automatically generate biochemical transformation networks (ab initio) based on mass differences (mass difference network-based approach) that provide an experimental assessment of metabolite connections within a given sample or a complex metabolic system, thereby providing important information about the nature of the samples and the set of microbial reactions or pathways that gave rise to them. Finally, for more experienced users, MetaboDirect allows users to customize plots, outputs, and analyses. Conclusion: Application of MetaboDirect to FT-ICR MS-based metabolomic data sets from a marine phage-bacterial infection experiment and a Sphagnum leachate microbiome incubation experiment showcase the exploration capabilities of the pipeline that will enable the research community to evaluate and interpret their data in greater depth and in less time. It will further advance our knowledge of how microbial communities influence and are influenced by the chemical makeup of the surrounding system. The source code and User’s guide of MetaboDirect are freely available through (https://github.com/Coayala/MetaboDirect) and (https://metabodirect.readthedocs.io/en/latest/), respectively.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

ClimateNet: an expert-labeled open dataset and deep learning architecture for enabling high-precision analyses of extreme weather

Abstract. Identifying, detecting, and localizing extreme weather events is a crucial first step in understanding how they may vary under different climate change scenarios. Pattern recognition tasks such as classification, object detection, and segmentation (i.e., pixel-level classification) have remained challenging problems in the weather and climate sciences. While there exist many empirical heuristics for detecting extreme events, the disparities between the output of these different methods even for a single event are large and often difficult to reconcile. Given the success of deep learning (DL) in tackling similar problems in computer vision, we advocate a DL-based approach. DL, however, works best in the context of supervised learning – when labeled datasets are readily available. Reliable labeled training data for extreme weather and climate events is scarce. We create “ClimateNet” – an open, community-sourced human-expert-labeled curated dataset that captures tropical cyclones (TCs) and atmospheric rivers (ARs) in high-resolution climate model output from a simulation of a recent historical period. We use the curated ClimateNet dataset to train a state-of-the-art DL model for pixel-level identification – i.e., segmentation – of TCs and ARs. We then apply the trained DL model to historical and climate change scenarios simulated by the Community Atmospheric Model (CAM5.1) and show that the DL model accurately segments the data into TCs, ARs, or “the background” at a pixel level. Further, we show how the segmentation results can be used to conduct spatially and temporally precise analytics by quantifying distributions of extreme precipitation conditioned on event types (TC or AR) at regional scales. The key contribution of this work is that it paves the way for DL-based automated, high-fidelity, and highly precise analytics of climate data using a curated expert-labeled dataset – ClimateNet. ClimateNet and the DL-based segmentation method provide several unique capabilities: (i) they can be used to calculate a variety of TC and AR statistics at a fine-grained level; (ii) they can be applied to different climate scenarios and different datasets without tuning as they do not rely on threshold conditions; and (iii) the proposed DL method is suitable for rapidly analyzing large amounts of climate model output. While our study has been conducted for two important extreme weather patterns (TCs and ARs) in simulation datasets, we believe that this methodology can be applied to a much broader class of patterns and applied to observational and reanalysis data products via transfer learning.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Distributed quantum sensing of multiple phases with fewer photons

Abstract Distributed quantum metrology has drawn intense interest as it outperforms the optimal classical counterparts in estimating multiple distributed parameters. However, most schemes so far have required entangled resources consisting of photon numbers equal to or more than the parameter numbers, which is a fairly demanding requirement as the number of nodes increases. Here, we present a distributed quantum sensing scenario in which quantum-enhanced sensitivity can be achieved with fewer photons than the number of parameters. As an experimental demonstration, using a two-photon entangled state, we estimate four phases distributed 3 km away from the central node, resulting in a 2.2 dB sensitivity enhancement from the standard quantum limit. Our results show that the Heisenberg scaling can be achieved even when using fewer photons than the number of parameters. We believe our scheme will open a pathway to perform large-scale distributed quantum sensing with currently available entangled sources.

Science & Technology - Other Topics↗
DOE OSTI2024

The influence of exploration activities of a potential lithium mine to the environment in Western Serbia

The proposed exploitation of the Jadar Valley lithium/borate deposit in Serbia, by the Rio Tinto Corporation, indicates that it would become large-scale processing of boron- and lithium-containing ore. It would be one of the world’s very first lithium mines in populated and agricultural area. The company claims that the envisioned mining will be in accordance with environmental protection requirements. The Jadar Valley deposits have been claimed to cover 90% of Europe’s current lithium needs. Yet, local opposition to the mining has arisen due to potential devastating impacts on groundwater, soil, water usage, biodiversity loss, and waste accumulation. Research drilling by the mining company has already produced environmental damage, with mine water containing high levels of boron leaking from exploratory wells and causing crops to dry out. Furthermore, our investigations reveal substantially elevated downstream concentrations of boron, arsenic, and lithium in nearby rivers as compared to upstream regions. Additionally, here we show that soil samples exhibit repeated breaches of remediation limit values with environmental consequences on both surface and underground waters. With the opening of the mine, problems will be multiplied by the tailings pond, mine wastewater, noise, air pollution, and light pollution, endangering the lives of numerous local communities and destroying their freshwater sources, agricultural land, livestock, and assets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

dCache: Inter-disciplinary storage system

The dCache project provides open-source software deployed internationally to satisfy ever more demanding storage requirements. Its multifaceted approach provides an integrated way of supporting different use-cases with the same storage, from high throughput data ingest, data sharing over wide area networks, efficient access from HPC clusters and long term data persistence on a tertiary storage. Though it was originally developed for the HEP experiments, today it is used by various scientific communities, including astrophysics, biomed, life science, which have their specific requirements. In this paper we describe some of the new requirements as well as demonstrate how dCache developers are addressing them.

Mkrtchyan, Tigran↗
DOE OSTI2025

dCache project status and update

The dCache project delivers an open-source, massively scalable, distributed storage system deployed internationally to satisfy today’s scientists’ ever-demanding storage requirements. Its multifaceted approach supports different use cases with the same storage, from high throughput data ingest, data sharing over wide area networks, efficient access from HPC clusters, and longterm data persistence on tertiary storage. Even though dCache was initially developed for HEP experiments, today, it is used by various scientific communities, including astrophysics, biomed, and life science, each with their specific requirements. To match the needs of these new communities and keep up with the scaling demands of existing experiments, dCache is permanently evolving. With this contribution, we would like to highlight the recent developments in dCache regarding integration with CERN Tape Archive (CTA), advanced metadata handling, token-based authorization support, bulk API for QoS transitions, REST API to control interaction with the tape system, and future development directions.

Mkrtchyan, Tigran [DESY]↗