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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 1,243 records · Page 69

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DOE OSTI2014

Rescue of mutant fitness defects using in vitro reconstituted designer transposons in Mycoplasma mycoides

With only hundreds of genes contained within their genomes, mycoplasmas have become model organisms for precise understanding of cellular processes, as well as platform organisms for predictable engineering of microbial functions for mission-critical applications. Despite the availability of “whole genome writing” in Mycoplasma mycoides, some traditional methods for genetic engineering are underdeveloped in mycoplasmas. Here we demonstrate two facile transposon-mediated approaches for introducing genes into the synthetic cell based on M. mycoides. The marker-less approach involves preparing a fragment containing only a small genomic region of interest with flanking transposase-binding sites, followed by in vitro transposase loading and introduction into the cells. The marker-driven approach involves cloning an open reading frame (ORF) of interest into a vector containing a marker for mycoplasma transformation, as well as sites for transposase loading and random genomic integration. An innovative feature of this construct is to use a single promoter to express the transformation marker and the introduced ORF. The marker-driven approach can be conveniently applied to any exogenous or synthetic gene without any information on the effect of the gene on the strain, whereas the marker-less approach requires that the fragment has a recognizable effect. Using the marker-less method, we found that a region containing the nusG gene rescues a slow growth phenotype of a strain containing a larger deletion encompassing this gene. Using the marker-driven approach, we better defined this finding, thereby establishing that nusG is required for a normal growth rate in synthetic M. mycoides. These methods are suitable for complementation tests to identify genes responsible for assorted functions lacking in deletion mutants. These approaches are also expected to facilitate rapid testing of various natural and engineered genes or gene clusters from numerous sources in M. mycoides.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Lipid Mini-On: mining and ontology tool for enrichment analysis of lipidomic data

Abstract Summary Here we introduce Lipid Mini-On, an open-source tool that performs lipid enrichment analyses and visualizations of lipidomics data. Lipid Mini-On uses a text-mining process to bin individual lipid names into multiple lipid ontology groups based on the classification (e.g. LipidMaps) and other characteristics, such as chain length. Lipid Mini-On provides users with the capability to conduct enrichment analysis of the lipid ontology terms using a Shiny app with options of five statistical approaches. Lipid classes can be added to customize the user’s database and remain updated as new lipid classes are discovered. Visualization of results is available for all classification options (e.g. lipid subclass and individual fatty acid chains). Results are also visualized through an editable network of relationships between the individual lipids and their associated lipid ontology terms. The utility of the tool is demonstrated using biological (e.g. human lung endothelial cells) and environmental (e.g. peat soil) samples. Availability and implementation Rodin (R package: https://github.com/PNNL-Comp-Mass-Spec/Rodin), Lipid Mini-On Shiny app (https://github.com/PNNL-Comp-Mass-Spec/LipidMiniOn) and Lipid Mini-On online tool (https://omicstools.pnnl.gov/shiny/lipid-mini-on/). Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Altering the substitution and cross‐linking of glucuronoarabinoxylans affects cell wall architecture in Brachypodium distachyon

Summary The Poaceae family of plants provides cereal crops that are critical for human and animal nutrition, and also, they are an important source of biomass. Interacting plant cell wall components give rise to recalcitrance to digestion; thus, understanding the wall molecular architecture is important to improve biomass properties. Xylan is the main hemicellulose in grass cell walls. Recently, we reported structural variation in grass xylans, suggesting functional specialisation and distinct interactions with cellulose and lignin. Here, we investigated the functions of these xylans by perturbing the biosynthesis of specific xylan types. We generated CRISPR/Cas9 knockout mutants in Brachypodium distachyon XAX1 and GUX2 genes involved in xylan substitution. Using carbohydrate gel electrophoresis, we identified biochemical changes in different xylan types. Saccharification, cryo‐SEM, subcritical water extraction and ssNMR were used to study wall architecture. Bd XAX1A and Bd GUX2 enzymes modify different types of grass xylan. Brachypodium mutant walls are likely more porous, suggesting the xylan substitutions directed by both Bd XAX1A and GUX2 enzymes influence xylan‐xylan and/or xylan–lignin interactions. Since xylan substitutions influence wall architecture and digestibility, our findings open new avenues to improve cereals for food and to use grass biomass for feed and the production of bioenergy and biomaterials.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Daily Snow Depth Measurements from 195 Stations in the United States (1997) (NDP-059)

This data package provides daily measurements of snow depth at 195 National Weather Service (NWS) first-order climatological stations in the United States. The data have been assembled and made available by the National Climatic Data Center (NCDC) in Asheville, North Carolina. The 195 stations encompass 388 unique sampling locations in 48 of the 50 states; no observations from Delaware or Hawaii are included in the database. Station selection criteria emphasized the quality and length of station records while seeking to provide a network with good geographic coverage. Snow depth at the 388 locations was measured once per day on ground open to the sky. The daily snow depth is the total depth of the snow on the ground at measurement time. The time period covered by the database is 1893-1992; however, not all station records encompass the complete period. While a station record ideally should contain daily data for at least the seven winter months (January through April and October through December), not all stations have complete records. Each logical record in the snow depth database contains one station's daily data values for a period of one month, including data source, measurement, and quality flags. The snow depth data have undergone extensive manual and automated quality assurance checks by NCDC and the Carbon Dioxide Information Analysis Center (CDIAC). These reviews involved examining the data for completeness, reasonableness, and accuracy, and included comparison of some data records with records in NCDC's Summary of the Day First Order online database. Since the snow depth measurements have been taken at NWS first-order stations that have long periods of record, they should prove useful in monitoring climate change.For access to the data files, click this link to the CDIAC data transition website: http://cdiac.ess-dive.lbl.gov/ndps/ndp059.html

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

An Open‐Source, Physics‐Based, Tropical Cyclone Downscaling Model With Intensity‐Dependent Steering

Abstract An open‐source, physics‐based tropical cyclone (TC) downscaling model is developed, in order to generate a large climatology of TCs. The model is composed of three primary components: (a) a random seeding process that determines genesis, (b) an intensity‐dependent beta‐advection model that determines the track, and (c) a non‐linear differential equation set that determines the intensification rate. The model is entirely forced by the large‐scale environment. Downscaling ERA5 reanalysis data shows that the model is generally able to reproduce observed TC climatology, such as the global seasonal cycle, genesis locations, track density, and lifetime maximum intensity distributions. Inter‐annual variability in TC count and power‐dissipation is also well captured, on both basin‐wide and global scales. Regional TC hazard estimated by this model is also analyzed using return period maps and curves. In particular, the model is able to reasonably capture the observed return period curves of landfall intensity in various sub‐basins around the globe. The incorporation of an intensity‐dependent steering flow is shown to lead to regionally dependent changes in power dissipation and return periods. Advantages and disadvantages of this model, compared to other downscaling models, are also discussed.

Meteorology & Atmospheric Sciences↗

DOE OSTI2014

SU-E-J-175: Proton Dose Calculation On Scatter-Corrected CBCT Image: Feasibility Study for Adaptive Proton Therapy

Purpose: To demonstrate feasibility of proton dose calculation on scattercorrected CBCT images for the purpose of adaptive proton therapy. Methods: Two CBCT image sets were acquired from a prostate cancer patient and a thorax phantom using an on-board imaging system of an Elekta infinity linear accelerator. 2-D scatter maps were estimated using a previously introduced CT-based technique, and were subtracted from each raw projection image. A CBCT image set was then reconstructed with an open source reconstruction toolkit (RTK). Conversion from the CBCT number to HU was performed by soft tissue-based shifting with reference to the plan CT. Passively scattered proton plans were simulated on the plan CT and corrected/uncorrected CBCT images using the XiO treatment planning system. For quantitative evaluation, water equivalent path length (WEPL) was compared in those treatment plans. Results: The scatter correction method significantly improved image quality and HU accuracy in the prostate case where large scatter artifacts were obvious. However, the correction technique showed limited effects on the thorax case that was associated with fewer scatter artifacts. Mean absolute WEPL errors from the plans with the uncorrected and corrected images were 1.3 mm and 5.1 mm in the thorax case and 13.5 mm and 3.1 mm in the prostate case. The prostate plan dose distribution of the corrected image demonstrated better agreement with the reference one than that of the uncorrected image. Conclusion: A priori CT-based CBCT scatter correction can reduce the proton dose calculation error when large scatter artifacts are involved. If scatter artifacts are low, an uncorrected CBCT image is also promising for proton dose calculation when it is calibrated with the soft-tissue based shifting.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Simulated effects of sample size and grain neighborhood on the modeling of extreme value fatigue response

Assessing the size of representative volume elements (RVEs) for fatigue-related applications is challenging. A RVE relevant to random microstructure requires a volume of material that is sufficiently large to capture the grain/phase heterogeneity that captures all statistical moments of the distribution of the driving force for fatigue crack formation at “hot spot” grains. Consequently, the large size of a microstructure RVE required to study fatigue phenomena is largely computationally intractable and difficult to explore. A more realistic objective in this work is to systematically study, as a function of the size of a statistical sample of microstructure, trends towards convergence of the simulated distribution of driving force for fatigue crack formation. Our present work accordingly leverages the recently developed open-source PRISMS-Fatigue framework to examine the trends in convergence of extreme value distributions (EVD) of Fatigue Indicator Parameters (FIPs) in progressively larger polycrystalline microstructure realizations of FCC Al alloy 7075-T6 using crystal plasticity finite element method simulations. The results are compared to the traditional method in which ensembles of statistical volume elements (SVEs) are simulated to build up statistics intended to approximate those associated with a larger volume of material. The convergence of EVDs with increase of size of a SVE of microstructure is closely related to the extent of grain nearest neighbor (NN) interactions. Accordingly, the sensitivity of the local micromechanical response at hot spot grains is quantitatively investigated by systematically varying the orientations of NN grains. Results indicate that SVEs with cubic crystallographic texture tend towards convergence of the EVD of FIPs with tens of thousands of grains while the random and rolled textures require larger volumes. Simple relationships based on microstructure parameters (e.g., Schmid Factor, grain size, NN misorientation) do not completely correlate to fatigue hot spot grains. Finally, the sensitivity of the extreme value fatigue response at hot spot grains extends to the 3rd NN when a single neighborhood grain orientation is altered.

36 MATERIALS SCIENCE↗

DOE OSTI2024

In-Situ Species Concentration Measurements In Ammonia-Mix Flames Using Ftir Spectroscopy

Hydrogen and ammonia represent two carbon-free fuel sources that could be used in place of current fossil energy sources in combustion systems. To develop optimized ammonia combustion systems, validated modeling tools are needed. In the open literature, it has been shown that the complex chemistry associated with fuel-bound nitrogen contained in ammonia differs greatly from natural gas or hydrogen combustion. As a result, several new chemical kinetic mechanisms have been developed. Many of these mechanisms have been validated experimentally, however this has primarily focused on bulk parameters such as laminar flame speed and ignition delay time. Critically, high quality measurements of species concentrations are needed under controlled conditions which are easily represented by simple models. In this paper, direct, in-situ measurements of species concentrations and gas temperature are performed in a laminar flat-flame burner. This arrangement enables comparison with 1D model predictions, better isolating chemical kinetics from the fluid dynamics. Quantitative species concentrations are determined by absorption spectroscopy using an FTIR spectrometer. Fuel compositions representative of cracked ammonia (NH 3 /H 2 ) and ammonia-natural gas (NH 3 /CH 4 ) are considered for rich and lean equivalence ratios. A major focus of the paper is on the selection of spectral features for nitric oxide and ammonia and correcting for large amounts of baseline H 2 O absorption.

36 MATERIALS SCIENCE↗

DOE OSTI2014

Using Natural Selection to Explore the Adaptive Potential of Chlamydomonas reinhardtii

Improving feedstock is critical to facilitate the commercial utilization of algae, in particular in open pond systems where, due to the presence of competitors and pests, high algal growth rates and stress tolerance are beneficial. Here we raised laboratory cultures of the model alga Chlamydomonas reinhardtii under serial dilution to explore the potential of crop improvement using natural selection. The alga was evolved for 1,880 generations in liquid medium under continuous light (EL population). At the end of the experiment, EL cells had a growth rate that was 35% greater than the progenitor population (PL). The removal of acetate from the medium demonstrated that EL growth enhancement largely relied on efficient usage of this organic carbon source. Genome re-sequencing uncovered 1,937 polymorphic DNA regions in the EL population with 149 single nucleotide polymorphisms resulting in amino acid substitutions. Transcriptome analysis showed, in the EL population, significant up regulation of genes involved in protein synthesis, the cell cycle and cellular respiration, whereas the DNA repair pathway and photosynthesis were down regulated. Like other algae, EL cells accumulated neutral lipids under nitrogen depletion. Our work demonstrates transcriptome and genome-wide impacts of natural selection on algal cells and points to a useful strategy for strain improvement.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

AdditiveFOAM: A Continuum Multiphysics Code for Additive Manufacturing

AdditiveFOAM is a computational framework that simulates transport phenomena in Additive Manufacturing (AM) processes. It is built on OpenFOAM (Weller et al., 1998), the leading free, open-source software package for computational fluid dynamics (CFD). OpenFOAM offers an extensible platform for solving complex multiphysics problems using state-of-the-art finite volume methods. AdditiveFOAM leverages these capabilities to develop specialized tools aimed at addressing challenges in AM processing. Metal additive manufacturing, also known as metal 3D printing, is an advanced manufacturing technique that creates physical parts from a three-dimensional (3D) digital model by melting metal powder or wire feedstock. A significant area of research in metal AM focuses on process planning to mitigate anomalous features during printing that are deleterious to part performance (e.g., porosity and cracking), as well as controlling localized microstructure and material properties. Given the high costs and substantial time requirements associated with experimental methods for qualifying new materials and processes, there is a compelling incentive for researchers to utilize advanced computational simulations. In this context, AdditiveFOAM offers a simulation framework to better understand undesirable features in printing, thereby enhancing process planning and reducing the reliance on labor-intensive experimental campaigns.

Coleman, John [Oak Ridge National Laboratory (ORNL↗

DOE OSTI2024

Measurement report: A comparison of ground-level ice-nucleating-particle abundance and aerosol properties during autumn at contrasting marine and terrestrial locations

Abstract. Ice-nucleating particles (INPs) are an essential class of aerosols found worldwide that have far-reaching but poorly quantified climate feedback mechanisms through interaction with clouds and impacts on precipitation. These particles can have highly variable physicochemical properties in the atmosphere, and it is crucial to continuously monitor their long-term concentration relative to total ambient aerosol populations at a wide variety of sites to comprehensively understand aerosol–cloud interactions in the atmosphere. Hence, our study applied an in situ forced expansion cooling device to measure ambient INP concentrations and test its automated continuous measurements at atmospheric observatories, where complementary aerosol instruments are heavily equipped. Using collocated aerosol size, number, and composition measurements from these sites, we analyzed the correlation between sources and abundance of INPs in different environments. Toward this aim, we have measured ground-level INP concentrations at two contrasting sites, one in the Southern Great Plains (SGP) region of the United States with a substantial terrestrially influenced aerosol population and one in the Eastern North Atlantic Ocean (ENA) region with a primarily marine-influenced aerosol population. These measurements examined INPs mainly formed through immersion freezing and were performed at a ≤ 12 min resolution and with a wide range of heterogeneous freezing temperatures (Ts above −31 °C) for at least 45 d at each site. The associated INP data analysis was conducted in a consistent manner. We also explored the additional offline characterization of ambient aerosol particle samples from both locations in comparison to in situ data. From our ENA data, on average, INP abundance ranges from ≈ 1 to ≈ 20 L−1 (−30 °C ≤ T ≤ −20 °C) during October–November 2020. Backward air mass trajectories reveal a strong marine influence at ENA with 75.7 % of air masses originating over the Atlantic Ocean and 96.6 % of air masses traveling over open water, but analysis of particle chemistry suggests an additional INP source besides maritime aerosols (e.g., sea spray aerosols) at ENA. In contrast, 90.8 % of air masses at the SGP location originated from the North American continent, and 96.1 % of the time, these air masses traveled over land. As a result, organic-rich SGP aerosols from terrestrial sources exhibited notably high INP abundance from ≈ 1 to ≈ 100 L−1 (−30 °C ≤ T ≤ −15 °C) during October–November 2019. The probability density function of aerosol surface area-scaled immersion freezing efficiency (ice nucleation active surface site density; ns) was assessed for selected freezing temperatures. While the INP concentrations measured at SGP are higher than those of ENA, the ns(T) values of SGP (≈ 105 to ≈ 107 m−2 for −30 °C ≤ T ≤ −15 °C) are reciprocally lower than ENA for approximately 2 orders of magnitude (≈ 107 to ≈ 109 m−2 for −30 °C ≤ T ≤ −15 °C). The observed difference in ns(T) mainly stems from varied available aerosol surface areas, Saer, from two sites (Saer,SGP > Saer,ENA). INP parameterizations were developed as a function of examined freezing temperatures from SGP and ENA for our study periods.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Effect of Grain Boundaries on the Performance of Thin-Film-Based Polycrystalline Silicon Solar Cells: A Numerical Modeling

Solar cells/photovoltaic, a renewable energy source, is appraised to be the most effective alternative to the conventional electrical energy generator. A cost-effective alternative of crystalline wafer-based solar cell is thin-film polycrystalline-based solar cell. This paper reports the numerical analysis of dependency of the solar cell parameters (i.e., efficiency, fill factor, open-circuit voltage and short-circuit current density) on grain size for thin-film-based polycrystalline silicon (Si) solar cells. A minority carrier lifetime model is proposed to do a correlation between the grains, grain boundaries and lifetime for thin-film-based polycrystalline Si solar cells in MATLAB environment. As observed, the increment in the grain size diameter results in increase in minority carrier lifetime in polycrystalline Si thin film. A non-equivalent series resistance double-diode model is used to find the dark as well as light (AM1.5) current–voltage (I-V) characteristics for thin-film-based polycrystalline Si solar cells. To optimize the effectiveness of the proposed model, a successive approximation method is used and the corresponding fitting parameters are obtained. The model is validated with the experimentally obtained results reported elsewhere. The experimentally reported solar cell parameters can be found using the proposed model described here.

36 MATERIALS SCIENCE↗

DOE OSTI2024

MIXv2: a long-term mosaic emission inventory for Asia (2010–2017)

The MIXv2 Asian emission inventory is developed under the framework of the Model Inter-Comparison Study for Asia (MICS-Asia) Phase IV and produced from a mosaic of up-to-date regional emission inventories. We estimated the emissions for anthropogenic and biomass burning sources covering 23 countries and regions in East, Southeast and South Asia and aggregated emissions to a uniform spatial and temporal resolution for seven sectors: power, industry, residential, transportation, agriculture, open biomass burning and shipping. Compared to MIXv1, we extended the dataset to 2010–2017, included emissions of open biomass burning and shipping, and provided model-ready emissions of SAPRC99, SAPRC07, and CB05. A series of unit-based point source information was incorporated covering power plants in China and India. A consistent speciation framework for non-methane volatile organic compounds (NMVOCs) was applied to develop emissions by three chemical mechanisms. The total Asian emissions for anthropogenic/open biomass sectors in 2017 are estimated as follows: 41.6/1.1 Tg NO x , 33.2/0.1 Tg SO 2 , 258.2/20.6 Tg CO, 61.8/8.2 Tg NMVOC, 28.3/0.3 Tg NH 3 , 24.0/2.6 Tg PM 10 , 16.7/2.0 Tg PM 2.5 , 2.7/0.1 Tg BC (black carbon), 5.3/0.9 Tg OC (organic carbon), and 18.0/0.4 Pg CO 2 . The contributions of India and Southeast Asia were emerging in Asia during 2010–2017, especially for SO 2 , NH 3 and particulate matter. Gridded emissions at a spatial resolution of 0.1° with monthly variations are now publicly available. This updated long-term emission mosaic inventory is ready to facilitate air quality and climate model simulations, as well as policymaking and associated analyses.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Highly Crystalline and Porous Borocarbonitrides as Metal‐Free Catalysts for Boosted N‐Heterocycle Dehydrogenation

Safe and efficient hydrogen storage is pivotal for enabling a clean hydrogen economy. Liquid organic hydrogen carriers (LOHCs) offer a practical solution, but their deployment is hindered by the lack of highly active and economical dehydrogenation catalysts. In this work, we report a metal‐free catalyst design that overcomes the long‐standing trade‐off between crystallinity and surface area in two‐dimensional frameworks for highly efficient dehydrogenation of LOHCs. A flux‐assisted reconstruction strategy transforms amorphous borocarbonitrides (AM‐BCN) into highly crystalline, defect‐rich BCN nanosheets (C‐BCN) with large surface area and accessible porosity, as confirmed by complementary spectroscopic, x‐ray, and neutron analyses. C‐BCN catalyzes the acceptor‐less dehydrogenation of aza‐fused LOHCs with quantitative hydrogen release under mild conditions, outperforming AM‐BCN and previously reported metal‐free scaffolds. Mechanistic insights from x‐ray, neutron scattering, and theoretical calculations identify open C‐B‐N and N‐B‐N defect motifs as the primary active sites. This work establishes a generalizable strategy to engineer crystalline, porous, defect‐rich two‐dimensional lattices and demonstrates a highly active metal‐free platform for LOHC dehydrogenation with high‐purity H 2 generation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

SynopFrame: Multiscale time-dependent visual abstraction framework for analyzing DNA nanotechnology simulations

We present an open-source framework, SynopFrame, that allows DNA nanotechnology (DNA-nano) experts to analyze and understand molecular dynamics simulation trajectories of their designs. We use a multiscale multi-dimensional abstraction space, connect the representations to a projected conformational space plot of the structure’s temporal sequence, and thus enable experts to analyze the dynamics of their structural designs and, specifically, failure cases of the assembly. In addition, our time-dependent abstraction representation allows the biologists, for the first time in a smooth and structurally clear way, to identify and observe temporal transitions of a DNA-nano design from one configuration to another, and to highlight important periods of the simulation for further analysis. We realize SynopFrame as a dashboard of the different synchronized 3D spatial and 2D schematic visual representations, with a color overlay to show essential properties such as the status of hydrogen bonds. The linking of the spatial, schematic, and abstract views ensures that users can effectively analyze the high-frequency motion. We also categorize the status of the hydrogen bonds into a new format to allow us to color-encode it and overlay it on the representations. To demonstrate the utility of SynopFrame, we describe example usage scenarios and report user feedback.

Abstraction space↗

DOE OSTI2023

Developing a Facile Technology for Converting Domestic US Coal into High-Value Graphene

Universal Matter Ltd. was formed in July 2019 to scale-up and commercialize a breakthrough process, Flash Joule Heating (FJH), to transform different coal grades, into high-quality graphene. This graphene is made using a high-voltage electric discharge that brings the carbon source to temperatures higher than 3,000 K in less than 10 milliseconds. The short burst of electricity breaks all chemical bonds in the feedstock and reorders the carbon atoms into exceptionally thin layers of a special type of graphene, at an estimated $100 per ton in electricity cost. This process is capable of producing 1-5 layer-thick high-quality graphene (with defects of <0.05% and purity of >99%) in a green, practical, and cost-effective process. The graphene produced in the FJH process is a very special kind of graphene called “turbostratic graphene” (TG). TG offers superior physical properties compared to other graphene structures on a similar weight basis. Unlike graphene made from graphite using traditional techniques, the graphene layers in TG stack in an irregular pattern that allows the graphene powder to be exfoliated more easily and blend more evenly within other materials. The TG produced using our FJH technology is the most economical graphene product that opens up significant large volume markets for end-use applications; it would allow the use of TG made from coal for commercial applications in several market segments including energy storage, sensors, hyper-lubricants, reinforced plastics, and building materials such as concrete.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2026

Web-based Preprocessing and Visualization of 3D FIB Tomography Data for Nuclear Fuel Characterization

Three-dimensional (3D) focused ion beam (FIB) tomography enables reconstruction of internal nuclear fuel features that can't be fully evaluated through surface imaging alone. This capability supports characterization of fuel constituents and defects under thermal and irradiation conditions relevant to microreactor development. However, large tomography datasets can create data-handling, loading, and visualization challenges, especially when image-stack preparation and file conversion must be completed with separate tools. The Computational Ultraspatial Tomography Toolkit for High-Resolution Object Analysis Tools (CUTTRHOAT) is an open-source web application being developed to display FIB tomography datasets available through the Nuclear Research Data System (NRDS). The current alpha version requires prepared HDF5 datasets and has limited integrated data-preparation capabilities. This project improves CUTTHROAT by adding dataset-folder selection, automatic input detection, dataset scanning, missing-slice identification, blank-slice insertion, and image-stack-to-HDF5 conversion. Two applications will be compared: the baseline CUTTHROAT alpha workflow and the updated application containing the integrated data-handling and preprocessing functions. Evaluation will consider dataset detection accuracy, conversion success, loading time, rendering responsiveness, application stability, and user interaction. Preliminary results demonstrate successful loading of existing HDF5 files and converted image stacks, while testing also identified performance reductions caused by excessive blank-slice generation. The updated workflow reduces reliance on external preparation tools and supports more direct movement from image stacks to color-code 3D visualization. Future work includes refining missing-slice handling, integrating additional preprocessing functions, like a denoising feature, parsing TIFF metadata for automatic voxel scaling, and adding manual X, Y, and Z voxel-spacing inputs for PNG and JPEG.

36 - MATERIALS SCIENCE↗

DOE OSTI2016

Scalable Metropolis Monte Carlo for simulation of hard shapes

We design and implement a scalable hard particle Monte Carlo simulation toolkit (HPMC), and release it open source as part of HOOMD-blue. HPMC runs in parallel on many CPUs and many GPUs using domain decomposition. We employ BVH trees instead of cell lists on the CPU for fast performance, especially with large particle size disparity, and optimize inner loops with SIMD vector intrinsics on the CPU. Our GPU kernel proposes many trial moves in parallel on a checkerboard and uses a block-level queue to redistribute work among threads and avoid divergence. HPMC supports a wide variety of shape classes, including spheres/disks, unions of spheres, convex polygons, convex spheropolygons, concave polygons, ellipsoids/ellipses, convex polyhedra, convex spheropolyhedra, spheres cut by planes, and concave polyhedra. NVT and NPT ensembles can be run in 2D or 3D triclinic boxes. Additional integration schemes permit Frenkel–Ladd free energy computations and implicit depletant simulations. In a benchmark system of a fluid of 4096 pentagons, HPMC performs 10 million sweeps in 10 min on 96 CPU cores on XSEDE Comet. The same simulation would take 7.6 h in serial. HPMC also scales to large system sizes, and the same benchmark with 16.8 million particles runs in 1.4 h on 2048 GPUs on OLCF Titan.

Computer Science↗