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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 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Detection of the pairwise kinematic Sunyaev-Zel’dovich effect and pairwise velocity with DESI DR1 galaxies and ACT DR6 and Planck CMB data

We present a 9.3⁢𝜎 detection of the pairwise kinematic Sunyaev-Zel’dovich (kSZ) effect by combining a sample of 913,286 Luminous Red Galaxies (LRGs) from the Dark Energy Spectroscopic Instrument Data Release 1 (DESI DR1) catalog and coadded Atacama Cosmology Telescope (ACT DR6) and Planck cosmic microwave background (CMB) temperature maps. This represents the highest-significance pairwise kSZ measurement to date. The analysis uses three ACT CMB temperature maps: coadded 150 GHz, total frequency maps, and a component separated Internal Linear Combination (ILC) map, all of which cover 19,000 square degrees of the sky from Advanced ACTPol observations conducted between 2017 and 2022. Comparison of the results of these three maps serves as a consistency check for potential foreground contamination that may depend on the observation frequency. An estimate of the best-fit mass-averaged optical depth is obtained by comparing the pairwise kSZ curve with the linear theory prediction of the pairwise velocity under the best-fit Planck cosmology and is compared with predictions from simulations. This estimate serves as a reference point for future comparisons with thermal SZ–derived optical depth measurements for the same DESI cluster samples, which will be presented in a companion paper. Finally, we employ a machine learning approach, trained on simulations to estimate the optical depth for 456,803 DESI LRG-identified clusters within the simulated mass range ( ≳ 10 13 ⁢𝑀 ⊙ ). These are combined with the measured kSZ signal to infer the individual cluster peculiar velocities, providing the opportunity to constrain the behavior of gravity and the dark sector over a range of cosmic scales and epochs.

Gong, Yulin [Cornell University] (ORCID:0000000346↗
DOE OSTI2023

Bootstrapping the String Kawai-Lewellen-Tye Kernel

We show that a generalized version of the 4-point string theory KLT double-copy map is the most general solution to the minimal-rank double-copy bootstrap in effective field theory. This follows from significant restrictions of the 4-point map resulting from the 6-point bootstrap analysis. The generalized 4-point double-copy map is defined by a function with only two parameters times a simple function that is symmetric in s,t,u. The two parameters can be interpreted as independent choices of α', one for each of the two sets of amplitudes double-copied with the map. Specifically, each of those two sets of amplitudes must obey either the string monodromy relations or the field theory KK & BCJ relations; there are no other options. We propose a closed form of the new double-copy map that interpolates between the original KLT string double-copy and the open & closed string period integrals. The construction clarifies the "single-valued projection" property of the Riemann zeta-function values for the 4-point string theory double copy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Foliar functional traits from imaging spectroscopy across biomes in eastern North America

Summary Foliar functional traits are widely used to characterize leaf and canopy properties that drive ecosystem processes and to infer physiological processes in Earth system models. Imaging spectroscopy provides great potential to map foliar traits to characterize continuous functional variation and diversity, but few studies have demonstrated consistent methods for mapping multiple traits across biomes. With airborne imaging spectroscopy data and field data from 19 sites, we developed trait models using partial least squares regression, and mapped 26 foliar traits in seven NEON (National Ecological Observatory Network) ecoregions (domains) including temperate and subtropical forests and grasslands of eastern North America. Model validation accuracy varied among traits (normalized root mean squared error, 9.1–19.4%; coefficient of determination, 0.28–0.82), with phenolic concentration, leaf mass per area and equivalent water thickness performing best across domains. Across all trait maps, 90% of vegetated pixels had reasonable values for one trait, and 28–81% provided high confidence for multiple traits concurrently. Maps of 26 traits and their uncertainties for eastern US NEON sites are available for download, and are being expanded to the western United States and tundra/boreal zone. These data enable better understanding of trait variations and relationships over large areas, calibration of ecosystem models, and assessment of continental‐scale functional diversity.

Wang, Zhihui↗
DOE OSTI2024

Topography and Functional Traits Control the Distribution of Key Shrub Plant Functional Types in Low-Arctic Tundra: Supporting Data

High-resolution classification maps derived from occupied aerial systems (UASs). The UAS data were collected in August 2021 using a Skydio 2+ drone equipped with a 4K resolution red-green-blue (RGB) camera (2024 Skydio Inc) and a 3DR SOLO Quadcopter carried a Parrot Sequoia+ Multispectral Sensor (2023 Parrot Drone SAS). This package includes vegetation classification maps at four locations around Next Generation Ecosystem Experiment Arctic (NGEE Arctic) Council watershed study site on the Seward Peninsula, Alaska. The classification maps were generated using a combination of RGB and canopy height information. The map data and metadata are provided as ENVI image (.dat) and text (.txt, *hdr) formats. Additional map quicklooks are provided as GIS *.kml files. These datasets are provided in support of Yang et al., (In review), “Topography and Functional Traits Control the Distribution of Key Shrub Plant Functional Types in Low-Arctic Tundra”.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Denudation, solute export, landscape evolution modeling, and geographic information system data for the East River watershed, Colorado, USA (2020-2024)

This data package contains geographic information system (GIS) layers and tabular datasets associated with the study of lithologic controls on denudation, solute export, carbon-scaling relationships, and transient landscape evolution in the East River watershed near Crested Butte, Colorado, USA. The package includes GIS layers used to produce the Figure 2 map, including drainage, hillshade, lithology, sample locations, and basin polygons, together with comma-separated value (CSV) tables and matching CSV data dictionaries. One group of tables reports sample-level and catchment-level information for river-sediment samples analyzed for in situ-produced cosmogenic beryllium-10 (10Be), including sample names, outlet elevations, geographic coordinates, upstream drainage area, rock-type classes, production-rate scaling scheme, analyzed nuclide, catchment-averaged denudation rates, and associated lower and upper analytical uncertainties. Sample and catchment attributes provide the basis for comparing denudation rates across intrusive, shale, sedimentary, and mixed-lithology settings. A second group of tables reports supporting information for landscape-evolution modeling and the mapped geologic framework of the study area. Included files list parameter values and definitions for the two-phase landscape-evolution simulations, summarize full-domain model erosion fluxes and topographic metrics for different simulation configurations, provide a fixed-area carbon-model scaling table, and summarize mapped geologic units within the East River study domain, including geologic code, formation name, lithologic description, mapped area, and lithologic class grouping. Model outputs and geologic summaries support interpretation of transient landscape behavior and its relation to the mapped distribution of shale, intrusive, sedimentary, and surficial units. A third group of tables reports hydrologic and hydrochemical information used to quantify dissolved export from the watershed. Included files provide site-level values for drainage area, mean annual solute export, standard error of annual export, area-normalized solute yield, and equivalent weathering rate for five East River monitoring sites, along with metadata describing the number, sampling cadence, and date range of discharge records and partial and full total dissolved solids observations used in the solute-yield analyses. The package also contains a supplementary daily ion-load time series with daily mean discharge, discharge observation counts, dissolved concentrations, and daily loads for calcium, magnesium, sodium, potassium, chloride, sulfate, nitrate, fluoride, dissolved silica, charge-balance bicarbonate, and total dissolved solids. The package contains GIS files, comma-separated value files (.csv), CSV data dictionaries, a file-level metadata table, a package-tree text file, and a readme text file.

10Be↗
DOE OSTI2023

Energy Community Atlas

The Energy Community Atlas provides efficient access to authoritative, curated, and relevant data that is vital to supporting energy planning, development, and economic growth across the U.S. In this effort, researchers at the National Energy Technology Laboratory (NETL) are utilizing advanced data visualization and transformation capabilities to develop an integrated, data atlas and resource focused on supporting energy community transitions to new manufacturing opportunities. Specifically, this project is working to find, acquire, integrate, and virtually host in a user-friendly, public and private solution from available resources, relevant to understanding and characterizing fossil energy communities themselves and inform energy planning, development, and economic growth opportunities, including opportunities for co-development to support manufacturing, critical materials, and more. This Atlas when complete is to offer a one-stop-shop for stakeholders to derive new insights to accelerate energy investments and strategic decision support needs. These are following datasets that are available as part of this ongoing project • Energy Community Atlas Map Package - This is ArcPro Map package and it contains all of the symbolized layers along with ArcPro map and geodatabase • Energy Community Atlas ArcGIS REST service - https://www.arcgis.com/apps/mapviewer/index.html?panel=gallery&suggestField=true&layers=537ced69bd88440380a62c2ec8aca30c • README Energy Community Atlas - Read me word document that has details about feature classes in Map package, ArcPro map and ArcGIS Rest Service

Bipartisan Infrastructure Law↗
DOE OSTI2024

Carbon Management Projects (CONNECT) Database and Explorer

Overview The Carbon Management Projects (CONNECT) Toolkit is an online exploratory visualization tool developed by the U.S. Department of Energy's (DOE) Office of Fossil Energy and Carbon Management (FECM) with support from other federal agencies such as the U.S. Environmental Protection Agency (EPA) and the U.S. Department of Transportation (DOT). It provides a single point of access to authoritative information on federal agency investment in a portfolio of research, development, and demonstration (RD&D) projects that have been publicly announced to advance technologies for point source carbon capture, carbon dioxide removal, transport, storage, and conversion, collectively referred to as carbon management. The RD&D programs covered in this tool are authorized by annual congressional appropriations ("Base Program") and the 2021 Infrastructure Investment and Jobs Act (IIJA). The tool also incorporates public information on other federal initiatives, such as the Regional Clean Hydrogen Hubs, and public information released by other government agencies, such as the Environmental Protection Agency's (EPA) and Primacy States’ Underground Injection Control Class VI permits and EPA’s facility level greenhouse gas (GHG) emissions. Developed in a geographic information system, the tool organizes carbon management projects into five groups based on the primary technology that a project aims to advance, each visually represented as a digital layer ("carbon management project layer"). Only federally funded projects are included, which can be awarded projects that are completed or ongoing, or projects that have been selected but are currently under negotiation. Project information can be viewed in the map or in the attribute table below it when turned on. In the map view, each project is displayed at either its host site (for field work), where available, or its performer site (project lead's location, further explained in the table below). Host sites and performer sites are represented in distinct icons. Several reference layers offer additional public information on infrastructural and natural resource environment for carbon management. These reference layers, combined with multiple geographical basemaps, enable users to visualize the carbon management project layers in context. Carbon management project information will be updated monthly based on feedback and information availability. Carbon management project layers Point Source Carbon Capture (PSC) This layer contains DOE-funded projects focused on capturing carbon dioxide (CO2) from power plants or industrial facilities. Carbon Dioxide Removal (CDR) This layer contains DOE-funded projects focused on capturing CO2 from the atmosphere, including direct air capture (DAC) and DAC hubs, direct ocean capture, enhanced mineralization, and biomass carbon removal and storage. For projects with multiple host sites, each of the sites are displayed individually with the project cost and cost sharing information representing the total for the entire project. Carbon Transport This layer contains DOE- and DOT-funded projects focused on CO2 transport. The Transport Research and Development sublayer contains projects that do not involve physical infrastructure; the Proposed Transport Corridor sublayer contains projects for which either a route for the transport infrastructure has been proposed or a general area for the transport infrastructure has been identified. Carbon Storage This layer contains DOE-funded key projects focused on CO2 storage. For projects with multiple field-work sites, each of the sites are displayed individually on the map with the project cost and cost sharing information representing the overall total for the entire project. Carbon Conversion This layer contains DOE-funded projects focused on converting CO2 into economically valuable products. Reference layers The following layers provide additional information in the geographic proximity of carbon management projects. Users should reference the original sources for more details (weblinks provided below and in pop-up windows on the map). Regional Clean Hydrogen Hub and Facility These layers illustrate the approximate areas of the Regional Clean Hydrogen Hubs announced by DOE's Office of Clean Energy Demonstrations (OCED) and the approximate locations of individual facilities that constitute the hubs (see "Where are the H2Hubs located?" on the webpage linked above). EPA Facility Level GHG Emissions (direct emitter) This layer shows direct CO2 emissions from stationary sources in 2022, using data extracted from EPA's Facility Level Information on GreenHouse gases Tool (FLIGHT). Captured and injected CO2 are not deducted from direct emitters’ total emissions. Contact EPA for additional details. Underground Injection Control Class VI permit/permit application This layer shows the locations of CO2 injection wells that are granted or in the process of applying for an Underground Injection Control Class VI permit by EPA or a Primacy State (currently Louisiana, North Dakota, and Wyoming). The URLs for the permits or permit applications are provided in the pop-up windows associated with the well locations. Contact EPA for additional details. Carbon Storage Resource This layer contains information on prospective CO2 storage resources in saline formations and oil and gas reservoirs provided by the National Carbon Sequestration Database and Geographic Information System (NATCARB) spatial database. Contact NETL for additional details. Existing CO2 pipeline This layer shows active CO2 pipelines based on information digitized from the map issued by the Pipeline and Hazardous Materials Safety Administration (PHMSA). Contact PHMSA for additional details.

Carbon Conversion↗
DOE OSTI2023

Field Demonstration of the Brick Ontology to Scale up the Deployment of ASHRAE Guideline 36 Control Sequences

Many commercial buildings have a vast network of sensors as part of their building automation systems (BAS) that allows opportunities for energy consumption and cost savings by deploying advanced control sequences. However, this resource is often underutilized since BAS are typically programmed with simple control sequences with limited potential to deliver on these opportunities. The recent availability of ASHRAE Guideline 36 (G36) with advanced HVAC control sequences supports control retrofits in existing buildings to unlock much of the savings potential. However, barriers such as the lack of standard naming convention of building assets and data points, proprietary equipment and BAS, and the inherent uniqueness of buildings and their systems prevent building stakeholders from adopting any “plug-and-play” implementation of G36. Instead, control vendors must often undertake the manual and labor-intensive point mapping process to identify a data stream’s functional and spatial relationship within the HVAC system along with other relevant contexts and map it to the new control sequences. The vendor must carry out the point mapping process in each individual building since the mapping is unlikely to port over to another building. Even for the same building, the point mapping process can occur multiple times if various control vendors implement different control retrofits and/or multiple control retrofits happen over the lifecycle of the building. Then, there is the likelihood that G36 control sequences are programmed uniquely to the building, preventing the same implementation from being reused in another. Therefore, this paper presents a field demonstration of how we leveraged the Brick ontology with BACnet, OpenBuildingControl’s Control Description Language (CDL), and open-source support tools to implement scalable and portable advanced building controls. These tools provide standardized semantic descriptions and relationships of the building’s assets and data points (Brick), standardized communication protocol to read from and write to the building’s BAS (BACnet), and standardized code implementations (CDL) of standardized advanced control strategies (G36). We implemented G36’s hot water supply temperature setpoint reset in a Berkeley, CA building for this field demonstration. This field demonstration aims to show how integrating these tools may streamline the deployment of advanced control sequences such as G36 in a consistent manner regardless of differences found across buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Toward Discovering the Structure and Dynamics of the Sun-Interstellar Medium System (Los Alamos LDRD Report)

We have taken major steps toward developing the tools necessary to explore with unprecedented resolution the plasma structure and dynamics of the Sun-interstellar medium (ISM) interaction region, known as the heliosheath. We have applied a rigorous imaging technique known as Generalized Ridge Regression (GRR) to construct statistically robust sky maps of hydrogen energetic neutral atoms (ENAs) emanating from this region and detected by the Los Alamos-led IBEX-Hi ENA imager [1] on NASA’s Interstellar Boundary Explorer (IBEX) mission [2]. Our methods go far beyond the map reconstruction process currently applied by the IBEX Science Operations Center (ISOC), opening up the possibility of new discovery science with the IBEX data set and positioning LANL for a lead science role for the upcoming Interstellar Mapping and Acceleration Probe (IMAP) mission [3] for which LANL is providing two key experiments. We have successfully demonstrated that the new maps are higher resolution and are capable of revealing structures that are not presently resolveable in standard ISOC maps

58 GEOSCIENCES↗
DOE OSTI2024

Self-Organized Stress Distributions in Polycrystalline Materials [Dissertation]

Understanding stress distributions in solid materials is complicated by the fact that most materials are polycrystalline in nature, with each crystal having an elastically anisotropic reaction to force. This study is to gain a better understanding on how external forces placed on a polycrystal are related to internal reactions within and between the grains. The hypothesis is that the stress distribution in porous to fully dense materials are self-organized based on strong contacts between and within the individual grains created by force chains. Force chains, commonly known in loaded granular materials, and could be the phenomenon that connect micro to macro deformation. Scale bridging measurements conducted through Raman spectroscopy, Atomic Force Microscopy, and Digital Image Correlation will be used to create stress maps, modulus maps, and elastic strain maps across a variety of geological and pharmaceutical polycrystals. When possible, the resulting maps will be compared to current homogenization schemes and a full field models. Finite element modeling will be used to assess whether the patterning seen in the experimental map is a reasonable approximation based on the orientation data of the samples used. A minimum of three publications is projected to be accomplished focusing each on a different method to experimentally test and analyze stress distributions.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Radiological Scouting, Monitoring and Inspection Using Drones

Human populations and natural ecosystems are bound to be exposed to ionizing radiation from the deposition of artificial radionuclides resulting from nuclear accidents, nuclear devices or radiological dispersive devices (“dirty bombs”). On the other hand, Naturally Occurring Radioactive Material industries such as phosphate production or uranium mining, contribute to the on site storage of residuals with enhanced concentrations of natural radionuclides. Therefore, in the context of the European agreements concerning nuclear energy, namely the European Atomic Energy Community Treaty, monitoring is an essential feature of the environmental radiological surveillance. In this work, we obtain 3D maps from outdoor scenarios, and complete such maps with measured radiation levels and with its radionuclide signature. In such scenarios, we face challenges such as unknown and rough terrain, limited number of sampled locations and the need for different sensors and therefore different tasks. We propose a radiological solution for scouting, monitoring and inspecting an area of interest, using a fleet of drones and a controlling ground station. First, we scout an area with a Light Detection and Ranging sensor onboard a drone to accurately 3D-map the area. Then, we monitor that area with a Geiger–Müller Counter at a low-vertical distance from the ground to produce a radiological (heat)map that is overlaid on the 3D map of the scenario. Next, we identify the hotspots of radiation, and inspect them in detail using a drone by landing on them, to reveal its radionuclide signature using a Cadmium–Zinc–Telluride detector. We present the algorithms used to implement such tasks both at the ground station and on the drones. The three mission phases were validated using actual experiments in three different outdoor scenarios. We conclude that drones can not only perform the mission efficiently, but in general they are faster and as reliable as personnel on the ground.

Pinto, Luís Ramos (ORCID:0000000319975484)↗
DOE OSTI2022

Median bed-material sediment particle size across rivers in the contiguous US

Abstract. Bed-material sediment particle size data, particularly the median sediment particle size (D50), are critical for understanding and modeling riverine sediment transport. However, sediment particle size observations are primarily available at individual sites. Large-scale modeling and assessment of riverine sediment transport are limited by the lack of continuous regional maps of bed-material sediment particle size. We hence present a map of D50 over the contiguous US in a vector format that corresponds to approximately 2.7 million river segments (i.e., flowlines) in the National Hydrography Dataset Plus (NHDPlus) dataset. We develop the map in four steps: (1) collect and process the observed D50 data from 2577 U.S. Geological Survey stations or U.S. Army Corps of Engineers sampling locations; (2) collocate these data with the NHDPlus flowlines based on their geographic locations, resulting in 1691 flowlines with collocated D50 values; (3) develop a predictive model using the eXtreme Gradient Boosting (XGBoost) machine learning method based on the observed D50 data and the corresponding climate, hydrology, geology, and other attributes retrieved from the NHDPlus dataset; and (4) estimate the D50 values for flowlines without observations using the XGBoost predictive model. We expect this map to be useful for various purposes, such as research in large-scale river sediment transport using model- and data-driven approaches, teaching environmental and earth system sciences, planning and managing floodplain zones, etc. The map is available at https://doi.org/10.5281/zenodo.4921987 (Li et al., 2021a).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Bacteroides expand the functional versatility of a universal transcription factor and transcribed DNA to program capsule diversity

This record contains a list of Snakemake rules (Snakefile) to process a raw *.fastq.gz (from GEO record: GSE281607) using Cutadapt, map a processed *.fastq file using Bowtie, convert mapped reads to *.bed files using Samtools and Bedtools, and count the occurance of each Bacteriodes fragilis str NCTC 9343 genome position anywhere in a mapped read and as the 3' end of a mapped read using Bedtools. It further contains *ebwt files to assist with Bowtie mapping, *genome file to be used with Bedtools, a *.fasta file (useful to regenerate *ebwt files), and the completely processed *bed and *txt read files (generated by Snakemake and R) as references. In addition, a *.pdb file is included and represents the predicted interaction between UpeY and UpaZ.

Landick, Robert↗
DOE OSTI2021

Union: A Unified HW-SW Co-Design Ecosystem in MLIR for Evaluating Tensor Operationson Spatial Accelerators

To meet the extreme compute demands for deep learning across commercial and scientific applications, dataflow accelerators are becoming increasingly popular. While these“domain-specific” accelerators are not fully programmable like CPUs and GPUs, they retain varying levels of flexibility with respect to data orchestration, i.e., dataflow and tiling optimizations to enhance efficiency. There are several challenges when designing new algorithms and mapping approaches to execute the algorithms for a target problem on new hardware. Previous works have addressed these challenges individually. To address this challenge as a whole, in this work, we present an HW-SW co-design ecosystem for spatial accelerators called Union within the popular MLIR compiler infrastructure. Our framework allows exploring different algorithms and their mappings on several accelerator cost models. Union also includes a plug-and-play library of accelerator cost models and mappers which can easily be extended. The algorithms and accelerator cost models are connected via a novel mapping abstraction that captures the map space of spatial accelerators which can be systematically pruned based on constraints from the hardware, workload, and mapper. We demonstrate the value of Union for the community with several case studies which examine offloading different tensor operations (CONV/GEMM/Tensor Contraction) on diverse accelerator architectures using different mapping schemes.

Jeong, Geonhwa↗
DOE OSTI2022

Broad-area laser awareness sensor

A laser-strike detection system includes an imaging sensor mounted on a platform, and a computing device. The imaging sensor outputs image frames that are each representative of a portion of the platform at a different time, during which a laser may be striking the platform. The computing device receives the image frames, and computes a delay map that indicates time-of-arrival delays of the laser beam at points on the portion of the platform. The computing device converts the delay map to a path-length variation map by multiplying the delay map by the propagation speed of light. The computing device fits a plane to the path-length variation map constrained by a topological model of the platform. The computing device computes angular deflections in x- and y-directions based upon the fit, which angular deflections define a direction from the platform to an emitter of the laser beam.

Sandusky, John↗
DOE OSTI2024

Liquid Interfacial Electron Microscopy Identifies Nanogalvanic Corrosion in Pearlitic Steel

The nanoscale mechanisms of localized corrosion in low carbon steels have remained elusive due to the complexity of studying the degradative material behavior at nanoscale solid-liquid interfaces. We identified various steps in the nanogalvanic corrosion processes using in-situ liquid-cell scanning transmission electron microscopy (STEM) using a microfluidic holder by Hummingbird Scientific. Initial work, performed at low magnification, identified the initiation point on a 1018 low-carbon steel surface. This initiation point was determined to be a triple junction of two ferrite grains bridging a cementite grain in contact with a baseline electrolyte of 6 uM CO2 dissolved in a buffered (2.78 uM Na2SO4) aqueous solution, pH 6.1. The pre-etched low-carbon steel surface was prepared using focused ion beam lift-out procedures to extract a cross-section of the low-carbon steel surface, which then was thinned to about 150 nm and transferred to a SiN membrane microfluidic window. The transfer was made using a lift-out needle to attach the low-carbon steel lamella to the corner of the SiN window, and then Pt/C deposition held the lamella in contact with the window while it was released from the lift out needle. To identify the triple point on the low carbon steel lamella, prior to attachment on the SiN window, the sample was characterized for compositional variations with energy dispersive x-ray spectroscopy mapping, grain orientation and phase mapping with precession electron diffraction, and thickness mapping with energy filtered transmission electron microscopy. This pre-characterization prior to the in-situ experiment provided a map of the multiphase and multigrain structure, where the in-situ liquid cell imaging provided a clear understanding of the initiation point on the sample. These data were cross-correlated to paint a holistic picture of the triple junction site, enabling low electron-fluence in-situ snapshot imaging to avoid dominating the native corrosion reactions with effects from the incident electron beam. This initial result identified that localized, nanogalvanic corrosion at the phase interface was the dominant corrosion process in the low-carbon steel, so we next targeted the observation of an array of these nanogalvanic features phase boundaries in a pearlite grain. Near-surface ferrite/cementite phase interfaces that typify pearlitic low-carbon steel were extracted, pre-characterized, and imaged for the in-situ corrosion processes. The sample was a cross-section from a pearlite grain, with alternating ferrite and cementite grains that extended microns down from the pre-etched low-carbon steel pipe surface. After contact with a buffered aqueous solution, the phase boundaries between the ferrite and cementite began to dissolve, with observable material loss and thickness changes in the dark-field and bright-field STEM images. Within minutes, the corrosion front proceeded deeper into the material, claiming a thin layer of ferrite around all exposed phase boundaries before progressing laterally into the ferrite matrix, converting the ferrite to corrosion product normal to each buried cementite grain. Formation of the corrosion product causes a volumetric expansion, creating a lateral wedging force that mechanically ejects the cementite grains from their grooves and leaves behind percolation channels into the steel substructure. Rapid and deleterious, this nanogalvanic corrosion pathway represents an important target for understanding and preventing run-away degradation in this common building material. Observation of this corrosion mechanism was enabled by the combination of pre-characterization using standard structural, grain, and compositional analysis in the TEM, which provides maps for understanding the reaction propagation captured in low-dose, in-situ, liquid-cell STEM.

corrosion↗
DOE OSTI2024

Memory access statistics monitoring

Systems, apparatuses, and methods related to memory access statistics monitoring are described. A host is configured to map pages of memory for applications to a number of memory devices coupled thereto. A first memory device comprises a monitoring component configured to monitor access statistics of pages of memory mapped to the first memory device. A second memory device does not include a monitoring component capable of monitoring access statistics of pages of memory mapped thereto. The host is configured to map a portion of pages of memory for an application to the first memory device in order to obtain access statistics corresponding to the portion of pages of memory upon execution of the application despite there being space available on the second memory device and adjust mappings of the pages of memory for the application based on the obtained access statistics corresponding to the portion of pages.

Roberts, David A.↗