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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

polishCLR: A Nextflow Workflow for Polishing PacBio CLR Genome Assemblies

Long-read sequencing has revolutionized genome assembly, yielding highly contiguous, chromosome-level contigs. However, assemblies from some third generation long read technologies, such as Pacific Biosciences (PacBio) continuous long reads (CLR), have a high error rate. Such errors can be corrected with short reads through a process called polishing. Although best practices for polishing non-model de novo genome assemblies were recently described by the Vertebrate Genome Project (VGP) Assembly community, there is a need for a publicly available, reproducible workflow that can be easily implemented and run on a conventional high performance computing environment. Here, we describe polishCLR (https://github.com/isugifNF/polishCLR), a reproducible Nextflow workflow that implements best practices for polishing assemblies made from CLR data. PolishCLR can be initiated from several input options that extend best practices to suboptimal cases. It also provides re-entry points throughout several key processes, including identifying duplicate haplotypes in purge_dups, allowing a break for scaffolding if data are available, and throughout multiple rounds of polishing and evaluation with Arrow and FreeBayes. PolishCLR is containerized and publicly available for the greater assembly community as a tool to complete assemblies from existing, error-prone long-read data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Accelerating data acquisition with FPGA-based edge machine learning: a case study with LCLS-II

New scientific experiments and instruments generate vast amounts of data that need to be transferred for storage or further processing, often overwhelming traditional systems. Edge machine learning (EdgeML) addresses this challenge by integrating machine learning (ML) algorithms with edge computing, enabling real-time data processing directly at the point of data generation. EdgeML is particularly beneficial for environments where immediate decisions are required, or where bandwidth and storage are limited. In this paper, we demonstrate a high-speed configurable ML model in a fully customizable EdgeML system using a field programmable gate array (FPGA). Our demonstration focuses on an angular array of electron spectrometers, referred to as the ‘CookieBox,’ developed for the Linac Coherent Light Source II project. The EdgeML system captures 51.2 Gbps from a 6.4 GS s −1 analog to digital converter and is designed to integrate data pre-processing and ML inside an FPGA. Our implementation achieves an inference latency of 0.2 µs for the ML model, and a total latency of 0.4 µs for the complete EdgeML system, which includes pre-processing, data transmission, digitization, and ML inference. The modular design of the system allows it to be adapted for other instrumentation applications requiring low-latency data processing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

IM3 Open Source Data Center Atlas

IM3 Open Source Data Center Atlas Description This dataset contains locations of existing data center facilities in the United States. Data center locations were derived from OpenStreetMap (OSM), a crowd-sourced database. Data points from OSM are processed in various ways to determine additional variables provided in the data including: facility area (square feet), associated US county, and US state. This dataset can be used to identify areas of concentrated data center development and inform government and private sector planning strategies for future buildout of data centers and the infrastructure necessary to support it. Usage Notes Validation of OSM-derived data center locations is an ongoing development under the IM3 project, and the database will be updated as new information becomes available. In some instances, both the data center area (e.g., campus) and individual data center buildings are included as overlapping areas in the database. Both values are retained. Data center points, buildings, and campus areas are provided as separate layers in the downloadable data package. Note that data items are not necessarily complete across layers. That is, a specific data center may only be present as a single point geometry in the "point" layer while other data centers are represented in both the campus and building layers. In some cases, data center campuses and/or buildings straddle a county boundary line. Mappings to both counties are retained in the database as separate rows. These data rows will have the same data center id information, but each will have different county information. Crowd-sourced data, by nature, relies on individuals and communities to provide information. As a result, some data may be missing where it has not yet been reported. As we collect information on additional data center locations and as OSM receives additional contributions, the database will be updated to capture additional data points not yet shown. Technical Information Data is available for download under the following formats: GeoPackage (GPKG) CSV Geospatial data is provided in the WGS84 (EPSG:4326) coordinate reference system. The GeoPackage download contains the following layers. See usage notes for more information. "point" "building" "campus" The "point" layer includes all data from OSM that had POINT geometry type (i.e., individual coordinates). The "building" layer includes all OSM data that did not have POINT geometry and where the building tag in the OSM export was neither equal to "no" or null. Data that did not meet the "point" or "building" qualification was assumed to be a facility campus and included in the "campus" layer. The dataset contains the following parameters. Variables provided by OSM are labeled with (OSM-provided). id - unique identification number (OSM-provided with prefix of "node/", "relation/" and similar attributes removed) state - name of US state state_abb - two letter US state abbreviation state_id - state ID number county - name of US county county_id - county ID number ref - reference numbers or codes (OSM-provided) operator - the name of the company, corporation, or person in charge facility (OSM-provided) name - name of facility (OSM-provided) sqft - surface area of facility polygon, measured in square feet. Only available for "building" and "campus" layers lat - latitude of data centroid point lon - longitude of data centroid point type – represented spatial information. One of "point", "building", or "campus". geometry – POLYGON geometry of area footprint (in "campus" and "building" layers) or POINT geometry of locations (in "point" layer). This parameter is not included in the csv download. Attribution Data center locations were derived from OpenStreetMap, which is made available at openstreetmap.org under the Open Database License (ODbL). US state and county boundary information was collected from the US Census Bureau for the year 2024, which is made publicly available at https://www.census.gov/geographies/mapping-files.html Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License The IM3 Open Source Data Center Atlas is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall [Pacific Northwest National Labor↗
DOE OSTI2026

IM3 Open Source Data Center Atlas

IM3 Open Source Data Center Atlas Description This dataset contains locations of existing data center facilities in the United States. Data center locations were derived from OpenStreetMap (OSM), a crowd-sourced database. Data points from OSM are processed in various ways to determine additional variables provided in the data including: facility area (square feet), associated US county, and US state. This dataset can be used to identify areas of concentrated data center development and inform government and private sector planning strategies for future buildout of data centers and the infrastructure necessary to support it. Usage Notes Validation of OSM-derived data center locations is an ongoing development under the IM3 project, and the database will be updated as new information becomes available. In some instances, both the data center area (e.g., campus) and individual data center buildings are included as overlapping areas in the database. Both values are retained. Data center points, buildings, and campus areas are provided as separate layers in the downloadable data package. Note that data items are not necessarily complete across layers. That is, a specific data center may only be present as a single point geometry in the "point" layer while other data centers are represented in both the campus and building layers. In some cases, data center campuses and/or buildings straddle a county boundary line. Mappings to both counties are retained in the database as separate rows. These data rows will have the same data center id information, but each will have different county information. Crowd-sourced data, by nature, relies on individuals and communities to provide information. As a result, some data may be missing where it has not yet been reported. As we collect information on additional data center locations and as OSM receives additional contributions, the database will be updated to capture additional data points not yet shown. Data items will occasionally be removed from OSM if they are misidentified, if they no longer exist, if they are duplicates of another item, or similar. For that reason, updated versions of this database may not contain all data center locations included in previous versions. Technical Information Data is available for download under the following formats: GeoPackage (GPKG) CSV Geospatial data is provided in the WGS84 (EPSG:4326) coordinate reference system. The GeoPackage download contains the following layers. See usage notes for more information. "point" "building" "campus" The "point" layer includes all data from OSM that had POINT geometry type (i.e., individual coordinates). The "building" layer includes all OSM data that did not have POINT geometry and where the building tag in the OSM export was neither equal to "no" or null. Data that did not meet the "point" or "building" qualification was assumed to be a facility campus and included in the "campus" layer. The dataset contains the following parameters. Variables provided by OSM are labeled with (OSM-provided). id - unique identification number (OSM-provided with prefix of "node/", "relation/" and similar attributes removed) state - name of US state state_abb - two letter US state abbreviation state_id - state ID number county - name of US county county_id - county ID number ref - reference numbers or codes (OSM-provided) operator - the name of the company, corporation, or person in charge facility (OSM-provided) name - name of facility (OSM-provided) sqft - surface area of facility polygon, measured in square feet. Only available for "building" and "campus" layers lat - latitude of data centroid point lon - longitude of data centroid point type – represented spatial information. One of "point", "building", or "campus". geometry – POLYGON geometry of area footprint (in "campus" and "building" layers) or POINT geometry of locations (in "point" layer). This parameter is not included in the csv download. Attribution Data center locations were derived from OpenStreetMap, which is made available at openstreetmap.org under the Open Database License (ODbL). US state and county boundary information was collected from the US Census Bureau for the year 2024, which is made publicly available at https://www.census.gov/geographies/mapping-files.html Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License The IM3 Open Source Data Center Atlas is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall [Pacific Northwest National Labor↗
DOE OSTI2022

QSCOUT Progress Report, June 2022 [Quantum Scientific Computing Open User Testbed]

Quantum information processing has reached an inflection point, transitioning from proof-of-principle scientific experiments to small, noisy quantum processors. To accelerate this process and eventually move to fault-tolerant quantum computing, it is necessary to provide the scientific community with access to whitebox testbed systems. The Quantum Scientific Computing Open User Testbed (QSCOUT) provides scientists unique access to an innovative system to help advance quantum computing science.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A thermotropic liquid crystal enables efficient and stable perovskite solar modules

Perovskite solar cells have seen impressive progress in performance and stability, yet maintaining efficiency while scaling area remains a challenge. Here we find that additives commonly used to passivate large-area perovskite films often co-precipitate during perovskite crystallization and aggregate at interfaces, contributing to defects and to spatial inhomogeneity. Here we develop design criteria for additives to prevent their evaporative precipitation and enable uniform passivation of defects. We explored liquid crystals with melting point below the perovskite processing temperature, functionalization for defect passivation and hydrophobicity to improve device stability. We find that thermotropic liquid crystals such as 3,4,5-trifluoro-4'-(trans-4-propylcyclohexyl)biphenyl enable large-area perovskite films that are uniform, low in defects and stable against environmental stress factors. We demonstrate modules with a certified stabilized efficiency of 21.1% at an aperture area of 31 cm 2 and enhanced stability under damp-heat conditions (ISOS-D-3, 85% relative humidity, 85 °C) with T 86 (the duration for the efficiency to decay to 86% of the initial value) of 1,200 h, and reverse bias with (ISOS-V-1, negative maximum-power-point voltage) and without bypass diodes.

14 SOLAR ENERGY↗
DOE OSTI2020

Assessment Report ASMT-1033: Department 635 FY2019 Evaluate Center 600 Assessment Process

This assessment reviewed the Center 600 assessment process; gathered knowledge from 17 assessment points of contact across the Center; piloted an annual assessment planning process; and compared Center 600 Administrative Operating Procedure (AOP) 04-04, Assessments, to current practices and corporate requirements. The assessment identified two observations, three noteworthy practices, and multiple opportunities for improvement beyond the scope of the assessment.

42 ENGINEERING↗
DOE OSTI2022

Using lifetime of point defects for dislocation bias in bcc Fe

The interaction between dislocations and point defects is key to deformation processes and microstructural evolution of structural materials. In this work, we compute the lifetime of point defects to describe their interaction with dislocations. This approach can accurately account for the effects of the dislocation core and anisotropic defect dynamics to accumulatively determine the capture efficiency, sink strength, and dislocation bias at different temperatures and dislocation densities. Particularly, the absorption of point defects by straight screw and edge dislocations in a model bcc iron system is studied. The maximum swelling rates based on the obtained bias factors are in close agreement with a variety of experimental measurements, including both neutron and ion-irradiation data, especially when considering the survival fraction for point defects from displacement cascades. Further, this approach applies to many other processes and sinks, such as dislocation loops and interfaces, providing a powerful means to develop fundamental insights critical for improving radiation resistance and mechanical properties of structural materials through controlling defect interaction and evolution.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Strong spin-dephasing in a topological insulator-paramagnet heterostructure

The interface between magnetic materials and topological insulators can drive the formation of exotic phases of matter and enable functionality through the manipulation of the strong spin polarized transport. Here, we report that the transport processes that rely on strong spin-momentum locking in the topological insulator Bi 2 Se 3 are completely suppressed by scattering at a heterointerface with the kagome-lattice paramagnet, Co 7 Se 8 . Bi 2 Se 3 –Co 7 Se 8 –Bi 2 Se 3 trilayer heterostructures were grown using molecular beam epitaxy, where magnetotransport measurements revealed a substantial suppression of the weak antilocalization effect for Co 7 Se 8 at thicknesses as thin as a monolayer, indicating a strong dephasing mechanism. Bi 2- x Co x Se 3 films, in which Co is in a non-magnetic 3 + state, show weak antilocalization that survives to higher than x = 0.4, which, in comparison with the heterostructures, suggests that the unordered moments of Co 2+ act as a far stronger dephasing element. This work highlights several important points regarding coherent transport processes involving spin-momentum locking in topological insulator interfaces and how magnetic materials can be integrated with topological materials to realize both exotic phases and novel device functionality.

36 MATERIALS SCIENCE↗
DOE OSTI2025

CERF: IM3 Projected Western US Power Plant Locations

Overview The Capacity Expansion Regional Feasibility (CERF) model is an open-source geospatial python package that provides new power plant locations at a 1km resolution. The model ingests U.S. state or regional-scale electricity system capacity expansion plans, such as those produced by the Global Change Analysis Model (GCAM-USA), and identifies feasible, site-specific locations for individual new power plants (renewable and non-renewable). CERF combines high-resolution geospatial suitability analyses with an economic algorithm that selects individual plant siting locations based on grid interconnection costs and the locational marginal value of new generation. The model incorporates a wide range of dynamic constraints and opportunities, such as protected lands, population density, existing infrastructure, and water availability. This dataset provides CERF power plant siting results for IM3 Phase 2 simulations across eight different scenarios for the Western US through 2055. The scenarios include combinations of two Shared Socioeconomic Pathways (SSP3 and SSP5) with four high-resolution climate projections specific to the United States (see, https://tgw-data.msdlive.org/). These climate projections include "hotter" and "cooler" variants for two Representative Concentration Pathways (RCP4.5 and RCP8.5). The resulting eight simulations are: rcp45cooler_ssp3 rcp45cooler_ssp5 rcp45hotter_ssp3 rcp45hotter_ssp5 rcp85cooler_ssp3 rcp85cooler_ssp5 rcp85hotter_ssp3 rcp85hotter_ssp5 CERF siting results in this dataset correspond to capacity expansion plans in the GCAM-USA IM3 Phase 2 simulation data and are available for each of the above scenarios. Data Details Temporal Range: 2015-2055 in 5-year timesteps. Note that 2015 is the experiment base year and 2020 and beyond represent model simulation years. Spatial Range: Plant locations are provided for the eleven states in the Western US including Arizona, California, Colorado, Idaho, Montana, New Mexico, Nevada, Oregon, Utah, Washington, and Wyoming. Spatial Resolution: 1 km-squared, provided in x and y coordinates Geospatial Projection: Albers Equal Area Conic (ESRI:102003) File Type: csv The dataset contains subdirectories for each of the eight scenarios described in the overview. Each scenario folder contains two subfolders with the following information: 1. Power Plant Data This directory contains a single .csv file of power plant locations for both pre-existing (non-CERF sited plants in operation in 2015) and new (CERF-sited) power plants across the temporal range along with additional CERF model output parameters for CERF-sited plants. Plant with a siting year earlier than 2020 correspond to facilities that are operational leading into the first timestep CERF simulation. For a more detailed description of CERF model output parameters, see the CERF model documentation. Note that the cerf_plant_id parameter is unique within each scenario file but not across scenario files. Parameter Descriptions scenario - Name of scenario cerf_plant_id - Unique siting identifier cerf_sited - If True, indicates that plant was sited by CERF model. If False, indicates pre-existing facility region_name - Name of region (state) tech_id - Technology ID tech_name - Full generation technology name inclusive of cooling type (if applicable) and additional characteristics tech_simple - Simplified generation technology type unit_size_mw - Power plant unit size (MW) xcoord - X coordinate in the default CRS (meters) ycoord - Y coordinate in the default CRS (meters) index - Index position in the flattend 2D array buffer_in_km - Exclusion buffer around site (km) sited_year - Year of siting retirement_year - Year of retirement lmp_zone - Locational marginal price (LMP) zone ID locational_marginal_price_usd_per_mwh - Locational marginal price ($/MWh) generation_mwh_per_year - Generation output (MWh/yr) operating_cost_usd_per_year - Cost of plant operations ($/yr) net_operational_value - Net operational value based on LMP and and operating costs ($/yr) interconnection_cost - Cost of interconnection for transmission & gas pipeline (if applicable) net_locational_cost -- Difference of interconnection cost and operating value ($/yr) capacity_factor_fraction - Capacity factor (fraction) carbon_capture_rate_fraction - Carbon capture rate (fraction) fuel_co2_content_tons_per_btu - Fuel CO2 content (tons/Btu) fuel_price_usd_per_mmbtu - Fuel price ($/MMBtu) fuel_price_esc_rate_fraction - Fuel price escalation rate (fraction) heat_rate_btu_per_kWh - Heat rate (Btu/kWh) lifetime_yrs - Technology lifetime for annuity (years) operational_life_yrs - Operational lifetime for retirement (years) variable_om_usd_per_mwh - Variable operation and maintenance costs of yearly capacity use ($/MWh) variable_om_esc_rate_fraction - Variable operation and maintenance costs escalation rate (fraction) carbon_tax_usd_per_ton - Carbon tax ($/ton) carbon_tax_esc_rate_fraction - Carbon tax escalation rate (fraction) 2. Storage Data This directory contains information on new and pre-existing energy storage facilities operational in each timestep along with various storage operational parameters. The 2015 timestep provides pre-existing energy storage data and corresponds with facilities that are operational leading into the first model simulation timestep. Note that coordinates in the storage files correspond to the interconnection point on the grid (substation location), not individual energy storage locations. Energy storage is added in a cumulative process at each given interconnection point. That is, each individual file provides the total operational storage capacity interconnected to the specified substation for the given timestep, inclusive of previously installed storage at that location and new storage installed in that timestep at that location. Parameters scenario - Name of scenario timestep - Simulation timestep name - Unique storage identifier s_typ - Type of energy storage technology (battery or pumped storage hydro) s_node - Node ID of interconnecting substation xcoord - X coordinate in the default CRS (meters) ycoord - Y coordinate in the default CRS (meters) charge_rate - Maximum charge rate (power capacity) of storage system (MW) discharge_rate - Maximum discharge rate (power capacity) of storage system (MW) duration - Duration of storage system (hours) max_SoC - Allowed maximum state of charge (energy capacity) of storage system (MWh) min_SoC -Allowed minimum state of charge (energy capacity) of storage system (MWh) charge_eff - Efficiency of charge (fraction between 0 and 1) discharge_eff - Efficiency of discharge (fraction between 0 and 1) Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program.

CERF↗
DOE OSTI2023

Influence of oxygen on performance of multi-principal element alloy as braze filler for Ni-base alloys

In manufacturing of multi-principal element alloys (MPEAs), the casting process is often a primary point of oxygen introduction to the material system, which was demonstrated by the laboratory scale button arc-melting process. Oxygen introduction raises concerns for the mechanical performance of these alloys if employed as structural materials alone or in engineering applications, such as serving as filler materials to enable joining of similar or dissimilar alloy pairs that are conventionally considered difficult to join. In this work, oxide inclusions in an as-cast off-equiatomic MnFeCoNiCu MPEA and Ni-base alloy braze joints made with this MPEA were evaluated by synchrotron x-ray diffraction mapping and electron microscopy. MnO was found to be prevalent throughout the cast MPEA and was chemically reduced during brazing by trace Al from the base material, Ni-base Alloy 600. Incomplete reaction of the MnO with Al, and some alternative reaction with Cr, left a mixture of MnO, Al 2 O 3 , and Cr 2 O 3 in the as-brazed joint, with the oxides concentrated near the braze centerline due to directional solidification. Further, in the braze joints, the non-oxide constituent phases detected were an FCC matrix and particles of Cr 23 C 6 , Cr 7 C 3 , and TiN which are all native to Alloy 600. The evolution of oxides within the brazed joints at elevated service temperatures of 600-800°C was also evaluated. While MnO and Al 2 O 3 were stable during high-temperature service, Cr 2 O 3 particles grew to several hundred microns, with dissolved oxygen in the MPEA providing a significant source for oxide growth. Comparing tensile performance of the as-brazed condition with post-service conditions showed that the evolution of oxide particles contributed to an increase in strength and decrease in ductility of the brazed joints. Evaluating particle morphologies among fracture surfaces of individual specimens demonstrated that large Cr 2 O 3 particles and continuous cluster networks of Al 2 O 3 were the features most detrimental to total elongation. Hence, unmitigated evolution of oxygen-containing species during brazing and service conditions is detrimental to the ductility of the brazed joints, which highlights the importance of oxygen control in initial manufacturing of MPEAs for engineering applications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Engineering the formation of spin-defects from first principles

The full realization of spin qubits for quantum technologies relies on the ability to control and design the formation processes of spin defects in semiconductors and insulators. We present a computational protocol to investigate the synthesis of point-defects at the atomistic level, and we apply it to the study of a promising spin-qubit in silicon carbide, the divacancy (VV). Our strategy combines electronic structure calculations based on density functional theory and enhanced sampling techniques coupled with first principles molecular dynamics. We predict the optimal annealing temperatures for the formation of VVs at high temperature and show how to engineer the Fermi level of the material to optimize the defect’s yield for several polytypes of silicon carbide. Our results are in excellent agreement with available experimental data and provide novel atomistic insights into point defect formation and annihilation processes as a function of temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Twenty Years of Collaborative Materials Exercises by the Nuclear Forensics International Technical Working Group

The Collaborative Materials Exercise (CMX) series are a critical mechanism used to advance the ITWG's mission of identifying, developing and promoting the best practices of nuclear forensics. These exercises are not designed to test laboratory performance, but as learning experiences that provide opportunities for participants to test and demonstrate state-of-the-practice to the global scientific and law enforcement communities. They are run as mock nuclear forensic investigations under realistic scenarios, with timelines and conditions designed to mimic actual operations. These situations provide the relatively unique opportunity for the appropriate governmental agencies to exercise their collective response to a nuclear security incident. Utilizing well-characterized materials of a known history and origin that are taken from specific process locations within the nuclear fuel cycle, these 'real world' materials are used to fully consider the potential significance of process-derived heterogeneities and characteristics that might be used by investigators to derive useful information such as intended use, point of loss of control, process history or origin. While individual laboratory results are kept confidential, a summary of the major outcomes of each exercise is published in the open literature. The ITWG has carried out six CMXs since 1999. The sixth (CMX-6) and largest (21 participants) was completed in June 2019. Each CMX has contributed demonstrably to advancements in the state of practice and the emergence of novel techniques in nuclear forensic science.

Schwantes, Jon M.↗
DOE OSTI2023

Final Report On Non-Intrusive Load Monitoring Of Welding Processes

The conventional method of weld process monitoring is to monitor the process output electrical power close to the point of welding. Non-Intrusive Load Monitoring (NILM) describes the method of monitoring primary or utility electrical power into a welding process well away from the point of welding. The objective of this project was to determine if there is sufficient information within the welding process input power to understand process output power characteristics, and, if so, determine if there is sufficient resolution within the input electrical characteristics to infer some measures of weld quality. To understand the relationship between process input and output power, both input and output power were monitored for two welding processes (GMAW and GTAW) and two different power source types (inverter and SCR). Welds were made with and without intentional disturbances. The results showed that there is a strong correlation between input and output power and that the influence of process disturbances are evident within the input power. A simple method using input power only was devised and successfully demonstrated to discriminate between a weld made with no intentional disturbance (a nominal weld) from a weld made with an intentional disturbance (off-nominal weld). The primary conclusions of this work is that NILM of process input power is sensitive to process disturbances that could influence weld quality and that the approach warrants additional study.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Comparing the effect of virtual and in-person instruction on students’ performance in a design for additive manufacturing learning activity

The goal of this work is to compare the outcome of a design for additive manufacturing (DfAM) heuristics lesson conducted in a virtual learning environment to the same in an in-person learning environment. Prior work revealed that receiving DfAM heuristics at different points in the design process impacts the quality and novelty of designs produced afterward, but this work may have been limited by the solely virtual format. In this work, an identical experiment was performed in a face-to-face learning environment. Results indicate that neither learning format presents an advantage over the other when it comes to the quality of designs produced during the intervention. Participants across all experimental groups reported an increase in self-efficacy after the intervention, with improved performance on quiz-type questions. Furthermore, the novelty and variety of the designs produced by the in-person experimental groups were significantly lower than that of the virtual experimental groups. In addition to validating the effectiveness of virtual instruction as a teaching method, these results also support the authors’ hypothesis that the priming effect is stronger in an in-person classroom than in a virtual classroom.

Design for additive manufacturing↗
DOE OSTI2020

Effects of transition metals on the evolution of polymer-derived SiOC ceramics

This work focuses on catalytic graphitization from different metals, iron (Fe), cobalt (Co), and nickel (Ni), for inducing carbon growth in silicon oxycarbides (SiOCs) during the pyrolysis. Fe, Co, and Ni-modified SiOCs were synthesized by pyrolysis to 900, 1100, and 1300 °C respectively in Ar. The transition metals induced the formation of the corresponding metal silicides, β-SiC, and graphitic carbon with the catalytic activity in the order of Fe > Co > Ni, in agreement with the activation energy calculation based on the carbon types and amounts. Lateral growth of turbostratic carbon followed a 2D grain growth process and its point-like defect density decreased based on the catalytic order of the transition metals, with SiOC/Fe having the lowest defect density. Quantitative analysis of the XPS results with Rietveld refinement illustrated that the phase separation of SiOC is more dominant than local carbothermal reduction between SiO 2 and C in the SiOC/M (M = Ni, Co, or Fe) systems. Understanding the catalytic graphitization effect of Ni, Co, and Fe on polymer derived ceramics offers new strategies in increasing high-temperature phase amounts and thus creating novel materials for heterogeneous catalysis, magnetic, and other applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Optoelectronic and material properties of solution-processed Earth-abundant Cu 2 BaSn(S, Se) 4 films for solar cell applications

Copper barium thioselenostannate, Cu 2 BaSnS 4-x Se x (CBTSSe), absorbers employ low-toxicity and abundant metals while offering low-cost manufacturing options, controllable stoichiometry and band gap tunability (from 2 eV at x = 0 to 1.55 eV at x = 3). CBTSSe can therefore be considered a prospective candidate for maintaining or improving upon the advantages of already commercialized Cu(In,Ga)(S,Se) 2 (CIGSSe) and CdTe absorbers. Here, we focus on solution-deposited stoichiometric CBTSSe films with band gap of 1.59 eV (x ≈ 3) and explore the fundamental film properties. Temperature- and excitation-dependent photoluminescence studies reveal a dominant defect emission at ~1.5 eV and a second deep defect feature at 1.15 eV. From time-resolved terahertz measurements, we find a charge carrier (electron and hole sum) mobility of ~140 cm 2 /Vs—i.e., comparable to values in CIGSSe or Cu 2 ZnSnS 4-x Se x (CZTSSe)—as well as a two-component minority carrier lifetime. A longer-lived lifetime component (~2 ns) arises from bulk recombination. However, strong recombination at the (bare) surface leads to a ~50 ps lifetime, inferior to state-of-the-art CIGSSe or CZTSSe absorbers. This recombination issue may worsen for CBTSSe/CdS interfaces, due to a cliff-like band alignment with 0.6 eV band offset, as revealed by ultraviolet photoemission spectroscopy. A low number of charge carriers within the absorber further contributes to a high series resistance. Employing these films, we also report the highest performance achieved from solution-processed trigonal CBTSSe thin-film photovoltaic devices, with open circuit voltage, short-circuit current density, fill factor and efficiency of 470 mV, 14.3 mA/cm 2 , 43.6% and 2.9%, respectively. The physical measurements provided on the stoichiometric solution-processed CBTSSe absorber further point to critical areas for future improvement of CBTSSe and related photovoltaic cells in the quest for higher efficiency devices based on earth abundant metals.

14 SOLAR ENERGY↗
DOE OSTI2026

Imaging Three-Dimensional Molecular Structure and Dynamics with Multiparticle Covariance and Cumulant Coulomb Explosion Analysis

Coulomb explosion imaging (CEI) provides a direct means of imaging molecular geometry by correlating fragment ion momenta following the fragmentation of a molecular polycation. Here, we demonstrate the use of three-body covariance and four-body cumulant analysis to extract three-dimensional (3D) structural information from the X-ray-induced Coulomb explosion of tert-butyl iodide (C4H9I). Site-selective ionization at the iodine 4d edge with intense femtosecond soft X-ray pulses from an X-ray free-electron laser (XFEL) enables rapid charge buildup and molecular breakup. By correlating ionic fragments in the molecular frame, we isolate complete dissociation channels and reveal subtle structural changes, such as umbrella-type motion of the branched alkyl chain, during the ionization process. Comparison with point-charge simulations of the Coulomb explosion shows close agreement, validating the approach. Furthermore, these results establish covariance/cumulant mapping as a powerful strategy for imaging complex three-dimensional molecular structures and point the way toward time-resolved CEI using both XFEL and tabletop sources for capturing ultrafast structural dynamics.

Imaging↗