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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 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Thermodynamic Modeling of the Al-Ce-Cu-Mg-Si System and Its Application to Aluminum-Cerium Alloy Design

Recently discovered AlCe alloys have shown promise in a number of applications, but the propensity of Ce to react with Al and other alloying elements can complicate the phase equilibria and design approach. To solve this, the CALPHAD method is used to explore an alloy within the quinary Al-Ce-Cu-Mg-Si system by developing a thermodynamic database with self-consistent parameters. The database includes a description of all 10 binary systems and 8 ternary systems consisting of: (i) 6 Al-containing ternaries (Al-Ce-Cu, Al-Ce-Mg, Al-Ce-Si, Al-Cu-Mg, Al-Cu-Si and Al-Mg-Si); and (ii) 2 additional ternaries that include Mg and Si (i.e., Ce-Mg-Si and Cu-Mg-Si). The thermodynamic description for the Al-Ce-Mg and Al-Mg-Si systems were reassessed to ensure consistency with the binary systems and the Ce-Mg-Si system is presented for the first time and compared to theoretical data from DFT (Density Functional Theory). In addition to the ternary interactions, the quaternary compound Al3Cu2Mg9Si7 and solid solution extending from the ternary Al2CuMg phase (Al,Si)2CuMg are incorporated. The CALPHAD method is employed and leveraged through the use of a Materials Design Simulator (MDS) to accelerate the design of novel aluminum-cerium-based alloys. The combination of a CALPHAD-based framework with experimental efforts and industrial insight permits the development of three new Al-Ce alloys: Al-3.5Ce-0.4Mg-7Si (Ce-modified A356), Al-5Ce-1Cu-0.5Mg-10Si and Al-19Ce-0.9Mg-1.1Si.

36 MATERIALS SCIENCE↗
NASA NTRS2001

Molecular motors and their functions in plants

Molecular motors that hydrolyze ATP and use the derived energy to generate force are involved in a variety of diverse cellular functions. Genetic, biochemical, and cellular localization data have implicated motors in a variety of functions such as vesicle and organelle transport, cytoskeleton dynamics, morphogenesis, polarized growth, cell movements, spindle formation, chromosome movement, nuclear fusion, and signal transduction. In non-plant systems three families of molecular motors (kinesins, dyneins, and myosins) have been well characterized. These motors use microtubules (in the case of kinesines and dyneins) or actin filaments (in the case of myosins) as tracks to transport cargo materials intracellularly. During the last decade tremendous progress has been made in understanding the structure and function of various motors in animals. These studies are yielding interesting insights into the functions of molecular motors and the origin of different families of motors. Furthermore, the paradigm that motors bind cargo and move along cytoskeletal tracks does not explain the functions of some of the motors. Relatively little is known about the molecular motors and their roles in plants. In recent years, by using biochemical, cell biological, molecular, and genetic approaches a few molecular motors have been isolated and characterized from plants. These studies indicate that some of the motors in plants have novel features and regulatory mechanisms. The role of molecular motors in plant cell division, cell expansion, cytoplasmic streaming, cell-to-cell communication, membrane trafficking, and morphogenesis is beginning to be understood. Analyses of the Arabidopsis genome sequence database (51% of genome) with conserved motor domains of kinesin and myosin families indicates the presence of a large number (about 40) of molecular motors and the functions of many of these motors remain to be discovered. It is likely that many more motors with novel regulatory mechanisms that perform plant-specific functions are yet to be discovered. Although the identification of motors in plants, especially in Arabidopsis, is progressing at a rapid pace because of the ongoing plant genome sequencing projects, only a few plant motors have been characterized in any detail. Elucidation of function and regulation of this multitude of motors in a given species is going to be a challenging and exciting area of research in plant cell biology. Structural features of some plant motors suggest calcium, through calmodulin, is likely to play a key role in regulating the function of both microtubule- and actin-based motors in plants.

Non-NASA Center↗
NASA NTRS2024

Dynamic Orbital Slingshot for Rendezvous with Interstellar Objects

The solar sail “statite” concept presents a potential means to study interstellar objects (ISOs). A new class of asteroids and comets, ISOs offer a unique scientific opportunity to answer fundamental scientific questions about the origin of solar system volatiles, the compositions of exo-solar systems, and the transfer rates of material between solar systems. Unfortunately, they are also challenging to study due to their high excess energies and the short lead time offered by present detection infrastructure. By using its solar sail to “hover” in place, a statite is able to await the discovery of an ISO and, when called upon, convert the enormous potential energy of its stationary state into the velocity necessary to rendezvous with the targeted comet or asteroid. The investigation completed in Phase I focused on establishing the viability of the proposed mission concept. To do so, optimal trajectories to the two known ISOs were demonstrated and the relationship between statite placement and the resulting trajectory was explored. Post-launch trajectories from the Earth to strategic statite states were also shown to be feasible. Concurrently with these efforts, a thorough review of published ISO population estimates was conducted and preliminary steps towards creating a database of synthetic ISO ephemerides were completed. If renewed for a Phase II, this will be used to characterize the capabilities of the statite concept.

NIAC Phase I↗
DOE OSTI2024

TRUST Contact Thermal Conductance (TRUST-CTC) Report: FY24

The objective of the Delivery Environments (DE) Testbeds to Reduce Uncertainties in Simulations and Tests (TRUST) project is to quantify and help increase confidence in specific areas of computational and experimental capabilities that are applicable to current and future delivery environments. More complete quantification of confidence in experimental and computational capabilities and the sufficient increase of confidence in those capabilities is critical to improving weapons engineering design, qualification, and assessment efforts that are critical to the current and future stockpile. Staff development will include cross-discipline collaboration to provide engineers with experience in both numerical simulations and experimental methods. This work uses and provides feedback on analysis tools and experimental results databases for efficient and responsive engineering which are currently under development. TRUST currently includes five testbeds and their associated engineering analysis baseline models (EABMs): 1. contact thermal conductivity, (CTC) 2. nonlinear dynamics, (ND) 3. sensors in environments for accelerometers, (SEA) 4. sensors in environments for fiber optic displacement gages, and (SEFOD) 5. sensors in environments for thermocouples (SETC). The TRUST project uses single-feature testbeds to quantify uncertainties in specific models and experiments and to identify capability development needs that can help to reduce these uncertainties. Each testbed is designed, configured, and tested in collaboration with groups with design and experimental capability: E-14 and MPA-CINT. The complementary simulations are conducted using W-13 analysis tools and stored in model repositories with plans for incremental progress toward EABM requirements. W-13 extends and exercises the testbed simulations in collaboration with experimentalists for uncertainty quantification of current and future materials, geometries, and environments. Additionally, TRUST is intended to provide engineers in W-13 and E-14 with experience in both numerical simulations and experimental methods through cross-discipline collaborations. Following the introduction to the TRUST project, the remainder of this report focuses on experimental and analytical efforts conducted in Fiscal Year (FY) 2024 relevant to the TRUST Contact Thermal Conductance (CTC) testbed.

42 ENGINEERING↗
NASA NTRS1990

Design and development of a space station hazardous material system for assessing chemical compatibility

As the Space Station nears reality in funding support from Congress, NASA plans to perform over a hundred different missions in the coming decade. Incrementally deployed, the Space Station will evolve into modules linked to an integral structure. Each module will have characteristic functions, such as logistics, habitation, and materials processing. Because the Space Station is to be user friendly for experimenters, NASA is anticipating that a variety of different chemicals will be taken on-board. Accidental release of these potentially toxic chemicals and their chemical compatibility is the focus of this discourse. The Microgravity Manufacturing Processing Facility (MMPF) will contain the various facilities within the U.S. Laboratory (USL). Each facility will have a characteristic purpose, such as alloy solidification or vapor crystal growth. By examining the proposed experiments for each facility, identifying the chemical constituents, their physical state and/or changes, byproducts and effluents, those payloads can be identified which may contain toxic, explosive, or reactive compounds that require processing or containment in mission peculiar waste management systems. Synergistic reactions from mixed effluent streams is of major concern. Each experiment will have it own data file, complete with schematic, chemical listing, physical data, etc. Chemical compatibility information from various databases will provide assistance in the analysis of alternate disposal techniques (pretreatment, separate storage, etc.). Along with data from the Risk Analysis of the Proposed USL Waste Management System, accidental release of potentially toxic and catastrophic chemicals would be eliminated or reduced.

Congo, Richard T.↗
NASA NTRS1994

Chronology of chrondrule and CAI formation: Mg-Al isotopic evidence

Details of the chondrule and Ca-Al-rich inclusion (CAI) formation during the earliest history of the solar system are imperfectly known. Because CAI's are more 'refractory' than ferromagnesian chondrules and have the lowest recorded initial Sr-87/Sr-86 ratios of any solar system materials, the expectation is that CAI's formed earlier than chondrules. But it is not known, for example, if CAI formation had stopped by the time chondrule formation began. Conventional (absolute) age-dating techniques cannot adequately resolve small age differences (less than 10(exp 6) years) between objects of such antiquity. One approach has been to look at systematic differences in the daughter products of short-lived radionuclides such as Al-26 and I-129. Unfortunately, neither system appears to be 'well-behaved.' One possible reason for this circumstance is that later secondary events have partially reset the isotopic systems, but a viable alternative continues to be large-scale (nebular) heterogeneity in initial isotopic abundances, which would of course render the systems nearly useless as chronometers. In the past two years the nature of this problem has been redefined somewhat. Examination of the Al-Mg isotopic database for all CAI's suggests that the vast majority of inclusions originally had the same initial Al-26/Al-27 abundance ratio, and that the ill-behaved isotopic systematics now observed are the results of later partial reequilibration due to thermal processing. Isotopic heterogeneities did exist in the nebula, as demonstrated by the existence of so-called FUN inclusions in CV3 chondrites and isotopically anomalous hibonite grains in CM2 chondrites, which had little or no live Al-26 at the time of their formation. But, among the population of CV3 inclusions at least, FUN inclusions appear to have been a relatively minor nebular component.

Macpherson, G. J.↗
DOE OSTI2020

First-principles study on structural mechanical and thermodynamic properties of HfMoTaTiZr

This study calculates the phase diagram of HfMoTaTiZr using the TCHEA1 database in Thermo-Calc software. Furthermore, it also investigates the structural and mechanical properties of HfMoTaTiZr by applying first-principles calculations. The elastic and other mechanical properties such as Young’s modulus, pugh ratio, hardness, bulk modulus was derived and discussed. These parameters were found to be in good harmony with previously available experimental reports. Vickers hardness of HfMoTaTiZr predicted from the Tians model agrees with the available experimental result. This study also investigates the thermal coefficient of linear expansion and vibrational heat capacity of the HfMoTaTiZr using the Debye–Grüneisen theory.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Progress Report on SFR Metallic Fuel Data Qualification

This report summarizes the progress of SFR metallic fuel qualification related activities, which are focused on providing quality assurance relevant information applicable to experiments irradiated during the Integral Fast Reactor (IFR) program. A background of metallic fuel performance data and the associated databases, including the EBR-II Fuels Irradiation & Physics Database (FIPD) and Out-of-Pile Transient Database (OPTD), is included. The legacy data in the databases, including as-built, post-irradiation examination (PIE), operating parameters, and out-of-pile experiment data are introduced. The SFR metallic fuel Quality Assurance Program Plan (QAPP) and its implementation to qualify these legacy data is described in detail. Important PIE data QA documents and the specifications of four types of PIE measurements (contact profilometry, laser profilometry, neutron radiography and gamma scan) are provided. Examples of the implementation of the QAPP to qualify each of those types of PIE data are provided.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2003

Liners and Low Luminosity AGN in the ROSAT Database

This program has led to a series of papers being written and published in the Astrophysical Journal. Together these papers try to explain major parts of the LINER and low luminosity AGN puzzle. One paper ('Accretion Disk Instabilities, Cold Dark Matter Models, and Their Role in Quasar Evolution', Hatziminaoglou E., Siemiginowska A., & Elvis M., 2001, ApJ, 547, 90) describes an analytical model for the evolution of the quasar luminosity function. By combining the Press-Schechter formalism for the masses of initial structures with the luminosity distribution for a population of single mass black holes given by an unstable accretion disk an almost complete end-to-end physics-based model of quasar evolution is produced. In this model black holes spend 75% of their time in a low accretion state (at L(Edd)). This low state population of black holes is likely to be observed as the LINER and low luminosity AGNs in the local universe. Another paper ('Broad Emission Line Regions in AGN: the Link with the Accretion Power', Nicastro F., 2000, ApJ Letters, 530, L65) gives a physical basis for why low state black holes appear as LINERS. By linking the Lightman-Eardley instability in an accretion disk to the ori.gin of a wind that contains the broad emission line cloud material this model explains the large widths seen in these lines as being the Keplerian velocity of the disk at the instability radius. For LINERS the key is that below an accretion rate of 10(exp -3)M(sub Edd)the Lightman-Eardley instability falls within the innermost stable orbit of the disk, and so leaves the entire disk stable. No wind occurs, and so no broad emission lines are seen. Most LINERS are likely to be black holes in this low state. Tests of this model are being considered.

Elvis, Martin↗
DOE OSTI2026

M3SF-25LL010302052 - Radionuclide Interaction with Hydrothermally Altered Repository Materials

This progress report (Level 3 Milestone Number M3SF-25LL010302052) summarizes research conducted at Lawrence Livermore National Laboratory (LLNL) within the Crystalline Host Rock Properties & Processes - LLNL Number SF-25LL01030205. Observed changes in radionuclide sorption after bentonite/clay heating have implications for radionuclide diffusive transport through engineered barriers and must be considered when designing waste disposal repositories. Recent research performed at Los Alamos National Laboratory (LANL) has provided key insights regarding the hydrothermal alteration behavior of bentonite backfill in the presence of repository materials (steel, concrete, etc.). We are examining how this mineral alteration affects retardation behavior of a suite of radionuclides of interest to repository performance assessment. Sorption experiments and data analysis for 233 U were initiated in FY24 following earlier experiments performed on 243 Am, 90 Sr, 137 Cs. In FY25, we completed the 233 U study and initiated and completed a study of 237 Np sorption. Below, we summarize the results and potential impacts of hydrothermal alteration on radionuclide retardation and assess the importance of this process to radionuclide migration from a GHRDC. We also use statistical tools (i.e. PCA) to help us determine the major drivers in affecting changes in measured Kd values induced by hydrothermal alteration. These experiments also allow us to test the predictive ability of our component additivity approach to surface complexation and ion exchange. Our guiding hypothesis is that a robust surface complexation/ion exchange model and associated database can effectively predict changes in radionuclide sorption behavior resulting from the hydrothermal alteration of mineralogy in a repository near field. In November 2024 the paper “Selenium interaction with iron minerals: Quantitative comparison of sorption and coprecipitation impacts on mobility” was published in Applied Geochemistry. A short update of results to date is presented below. In FY25, we also actively supported the DITUSC project, which is part of the EURADII initiative, as associate partners. We are executing the Migration2025 conference and support associated the NEA-TDB and Thermochimie workshops that will provide critical international engagements and develop consensus and synergy in thermodynamics as it relates to supporting the US nuclear waste repository program.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Performance of Pulsed Thermal Tomography Imaging with Machine Learning-Based Classification of Defects in Additively Manufactured Structures

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of complex topology nuclear reactor parts from high-strength corrosion resistance alloys, such as stainless steel and Inconel. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process. Some of the challenges with using LPBF method for nuclear manufacturing include the possibility of introducing pores into metallic structures. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures in high temperature nuclear reactor environment. Currently, there exist limited capabilities to evaluate actual AM structures non-destructively. Pulsed Thermal Tomography Imaging (PTT) provides a capability for non-destructive evaluation (NDE) of subsurface defects in arbitrary size structures. The PTT method is based on recording material surface temperature transients with infrared (IR) camera following thermal pulse delivered on material surface with flash light. The PTT method has advantages for NDE of actual AM structures because the method involves one-sided non-contact measurements and fast processing of large sample areas captured in one image. Following initial qualification of an AM component for deployment in a nuclear reactor, a PTT system can also be used for in-service nondestructive evaluation (NDE) applications. In this report, we describe recent progress in enhancing PTT capabilities in detecting and visualizing microscopic defects in metallic specimens. The thermal tomography (TT) algorithm obtains depth reconstructions of spatial effusivity from the data cube of sequentially recorded surface temperatures. However, interpretation of TT images is non-trivial because of blurring of images with increasing depth. To address this challenge, we have developed a deep learning convolutional neural network (CNN) to classify size and orientation subsurface defects in simulated TT images. CNN is trained on a database of TT images created for a set of simulated metallic structures with elliptical subsurface voids. Test of CNN performance demonstrate the ability to classify radii and angular orientation of subsurface defects in TT images. In addition, we have shown that CNN trained on elliptical defects is capable of classifying irregular-shaped defects obtained from scanning electron microscopy (SEM) of stainless steel sections printed with LPBF.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Data-Driven Constitutive Model for the Inelastic Response of Metals: Application to 316H Steel

Here, predictions of the mechanical response of structural elements are conditioned by the accuracy of constitutive models used at the engineering length-scale. In this regard, a prospect of mechanistic crystal-plasticity-based constitutive models is that they could be used for extrapolation beyond regimes in which they are calibrated. However, their use for assessing the performance of a component is computationally onerous. To address this limitation, a new approach is proposed whereby a surrogate constitutive model (SM) of the inelastic response of 316H steel is derived from a mechanistic crystal plasticity-based polycrystal model tracking the evolution of dislocation densities on all slip systems. The latter is used to generate a database of the expected plastic response and dislocation content evolution associated with several instances of creep loading. From the database, a SM is developed. It relies on the use of orthogonal polynomial regression to describe the evolution of the dislocation content. The SM is then validated against predictions of the dead load creep response given by the polycrystal model across a range of temperatures and stresses. When the SM is used to predict the response of 316H during complex non monotonic loading, extrapolating to new loading conditions, it is found that predictions compare particularly well against those from the physics-based polycrystal model.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Machine Learning Modeling Pipeline for Extracting Nuclear Proliferation Events of Interest from Open Data Sources (U)

In FY2020, the Savannah River National Laboratory (SRNL) and the Sanghani Center for Artificial Intelligence and Data Analytics at Virginia Polytechnic Institute and State University entered a collaboration funded by Department of Energy’s (DOE) Office of Defense Nuclear Nonproliferation Research and Development. The project’s mission was to take the first steps toward developing a demonstration prototype system that uses multiple machine learning and data analytics methods on largescale open data sources to identify new, developing, and/or undeclared nuclear programs. Given the SRNL team’s on-site perspective of events culminating in the DOE’s decision to pursue the Savannah River Plutonium Processing Facility (SRPPF), the team targeted the identification of events and indicators in retrospective datasets that pointed to the activity of “fissile core fabrication at the Savannah River Site” prior to the official announcement in May of 2018. A preliminary modeling pipeline was developed in FY20 that showed the datasets contained adequate signal for continuation of efforts. In FY21, a modular demonstration prototype modeling pipeline has continued in development for two text-based data sources: a broad internet archive (Webhose Ltd.) and a decahose Twitter database (i.e., a global sampling of one in every ten Tweets). The techniques that have been developed rely on graph theory and anomaly detection to identify contextual shifts in key words and phrases at various points in time such that indicators of events of interest could be identified and subsequently, events could be extracted from the corpuses. The foundational concept behind the approaches is that contextual shifts in key words and phrases can act as indicators of events of interest. Both datasets have proven successful in extracting events of interest related to pit production at the Savannah River Site prior to the official announcement. In addition, the pipelines have generated a wide range of events broadly summarized as: the awarding of DOE contracts at major sites, DOE investments in various programs, accidents at DOE national laboratories, speculations about the fate of pit production in the DOE complex, domestic and international shipments and receipts of nuclear materials at DOE sites, termination of non-proliferation agreements with Russia, termination of MOX, new weapons development approvals/testing, nuclear posture reviews, major DOE cleanup/production milestones, political opinions, and nuclear watch groups’ opinions, among many others.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Efficient machine-learning model for fast assessment of elastic properties of high-entropy alloys

We combined descriptor-based analytical models for stiffness-matrix and elastic-moduli with mean-field methods to accelerate assessment of technologically useful properties of high-entropy alloys, such as strength and ductility. Model training for elastic properties uses Sure-Independence Screening (SIS) and Sparsifying Operator (SO) method yielding an optimal analytical model, constructed with meaningful atomic features to predict target properties. Computationally inexpensive analytical descriptors were trained using a database of elastic properties determined from density functional theory for binary and ternary subsets of Nb-Mo-Ta-W-V refractory alloys. The optimal Elastic-SISSO models, extracted from an exponentially large feature space, give an extremely accurate prediction of target properties, similar to or better than other models, with some verified from existing experiments. Here we also show that electronegativity variance and elastic-moduli can directly predict trends in ductility and yield strength of refractory HEAs, and reveals promising alloy concentration regions.

36 MATERIALS SCIENCE↗
NASA NTRS2003

Comparison of Acoustic Impedance Eduction Techniques for Locally-Reacting Liners

Typical acoustic liners used in current aircraft inlets and aft-fan ducts consist of some type of perforated facesheet bonded to a honeycomb core. A number of techniques for determining the acoustic impedance of these locallyreacting liners have been developed over the last five decades. In addition, a number of models have been developed to predict the acoustic impedance of locallyreacting liners in the presence of grazing flow, and to use that information together with aeroacoustic propagation codes to assess the noise absorption provided by these liners. These prediction models have incorporated the results from databases acquired with specific impedance eduction techniques. Thus, while these prediction models are acceptable for liners that are similar to those tested in these databases, their application to new liner configurations must be viewed with caution. The primary purpose of this paper is to provide a comparison of impedance eduction techniques that have been implemented at various aerospace research laboratories in the United States (NASA Langley Research Center, General Electric Aircraft Engines, B. F. Goodrich and Boeing). A secondary purpose is to provide data for liner configurations that extend the porosity range beyond that which has been previously used in common aircraft engine nacelles. Two sets of liners were designed to study the effects of three parameters: perforate hole diameter, facesheet thickness and porosity. These two sets of liners were constructed for testing in each of the laboratories listed above. The first set of liners was designed to fit into the NASA Langley and Boeing test facilities. The second set was designed to fit into the General Electric Aircraft Engines and B. F. Goodrich test facilities. By using the same parent material, both sets of liners were identical to within the limits of material and fabrication variability. Baseline data were obtained in the normal incidence impedance tubes at NASA Langley and B. F. Goodrich. The results were found to compare extremely well. The samples were then tested in the grazing flow ducts of each of the four laboratories. Perhaps the most significant result of these comparisons is that the educed acoustic resistances for the liners used in this study increase as the mean flow profile is modified from uniform to 3-D shear. This realization has demonstrated the need for an frequency-dependent impedance eduction technique that incorporates 3-D shear flow and is efficient.

Jones, M. G.↗
NASA NTRS2008

ISS Charging Hazards and Low Earth Orbit Space Weather Effects

Current collection by high voltage solar arrays on the International Space Station (ISS) drives the vehicle to negative floating potentials in the low Earth orbit daytime plasma environment. Pre-flight predictions of ISS floating potentials Phi greater than |-100 V| suggested a risk for degradation of dielectric thermal control coatings on surfaces in the U.S. sector due to arcing and an electrical shock hazard to astronauts during extravehicular activity (EVA). However, hazard studies conducted by the ISS program have demonstrated that the thermal control material degradation risk is effectively mitigated during the lifetime of the ISS vehicle by a sufficiently large ion collection area present on the vehicle to balance current collection by the solar arrays. To date, crew risk during EVA has been mitigated by operating one of two plasma contactors during EVA to control the vehicle potential within Phi less than or equal to |-40 V| with a backup process requiring reorientation of the solar arrays into a configuration which places the current collection surfaces into wake. This operation minimizes current collection by the solar arrays should the plasma contactors fail. This paper presents an analysis of F-region electron density and temperature variations at low and midlatitudes generated by space weather events to determine what range of conditions represent charging threats to ISS. We first use historical ionospheric plasma measurements from spacecraft operating at altitudes relevant to the 51.6 degree inclination ISS orbit to provide an extensive database of F-region plasma conditions over a variety of solar cycle conditions. Then, the statistical results from the historical data are compared to more recent in-situ measurements from the Floating Potential Measurement Unit (FPMU) operating on ISS in a campaign mode since its installation in August, 2006.

Minow, Joseph↗
DOE OSTI2021

Coordination environment of Si in calcium silicate hydrates, silicate minerals, and blast furnace slags: A XANES database

Understanding the silicate polymerization of calcium silicate hydrate (C-S-H) gel and its crystalline polymorphs is important in cement science. NMR can determine Si environments, but the measurement can be time-consuming and provides no spatial information. X-ray absorption near-edge structure (XANES) spectroscopy is a fast tool for probing Si coordination, possibly with spatial information. However, there lacks an understanding of Si K-edge XANES spectra of cement-related silicate phases. Here, a Si K-edge XANES spectral database of nanocrystalline C-S-H, C-S-H minerals, blast-furnace slags, and metakaolin is provided. Si K-edge of C-S-H minerals shifts to higher energies with higher polymerized Si and lower CaSi connectivity in the Si second nearest neighbor shell. Si K-edge energy shows weak correlations with Ca/Si ratio, average SiO bond length, and SiO{sub 4} distortion due to the structural complexity of silicates. The substitution of Al for Si shifts the Si K-edge of tobermorite and slags to higher energies.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A robust synthetic data generation framework for machine learning in high-resolution transmission electron microscopy (HRTEM)

Machine learning techniques are attractive options for developing highly-accurate analysis tools for nanomaterials characterization, including high-resolution transmission electron microscopy (HRTEM). However, successfully implementing such machine learning tools can be difficult due to the challenges in procuring sufficiently large, high-quality training datasets from experiments. In this work, we introduce Construction Zone, a Python package for rapid generation of complex nanoscale atomic structures which enables fast, systematic sampling of realistic nanomaterial structures and can be used as a random structure generator for large, diverse synthetic datasets. Using Construction Zone, we develop an end-to-end machine learning workflow for training neural network models to analyze experimental atomic resolution HRTEM images on the task of nanoparticle image segmentation purely with simulated databases. Further, we study the data curation process to understand how various aspects of the curated simulated data—including simulation fidelity, the distribution of atomic structures, and the distribution of imaging conditions—affect model performance across three benchmark experimental HRTEM image datasets. Using our workflow, we are able to achieve state-of-the-art segmentation performance on these experimental benchmarks and, further, we discuss robust strategies for consistently achieving high performance with machine learning in experimental settings using purely synthetic data. Construction Zone and its documentation are available at https://github.com/lerandc/construction_zone.

36 MATERIALS SCIENCE↗