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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Performance model-directed data sieving for high-performance I/O

Many scientific computing applications and engineering simulations exhibit noncontiguous I/O access patterns. Data sieving is an important technique to improve the performance of noncontiguous I/O accesses by combining small and noncontiguous requests into a large and contiguous request. It has been proven effective even though more data are potentially accessed than demanded. In this study, we propose a new data sieving approach namely performance model-directed data sieving, or PMD data sieving in short. It improves the existing data sieving approach from two aspects: (1) dynamically determines when it is beneficial to perform data sieving; and (2) dynamically determines how to perform data sieving if beneficial. It improves the performance of the existing data sieving approach considerably and reduces the memory consumption as verified by both theoretical analysis and experimental results. Given the importance of supporting noncontiguous accesses effectively and reducing the memory pressure in a large-scale system, the proposed PMD data sieving approach in this research holds a great promise and will have an impact on high-performance I/O systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Geochemical characterization of floodplain sediments from Meander C and O in the East River Watershed, CO, USA

This data package is part of the Watershed Function SFA data collection and contains geochemical characterization of sediments as a function of depth in the pumphouse vicinity, including Meander C and Meander O (oxbow). This data was used in the manuscript "Fox, P.M., Bill, M., Heckman, K., Conrad, M., Anderson, C., Keiluweit, M., and Nico, P.S.Shale as a Source of Organic Carbon in Floodplain Sediments of a Mountainous Watershed" published in Journal of Geophysical Research: Biogeosciences. Data includes sieving, total organic carbon (TOC), total inorganic carbon (TIC), total nitrogen (TN), carbon isotopes (14C and 13C) of whole sediment. Sediment density fractionation data is also included, with measurements of TOC, TN, 14C and 13C on density fractions. Metal and carbon concentrations from various sediment extractions (HCl, dithionite, oxalate, water, and pyrophosphate) are included. Characterization of extracted carbon by fourier transform infrared spectroscopy (FTIR) and UV-Visible light spectroscopy. Characterization of density fractionated (light fractions) organic carbon by FTIR. Carbon X-ray spectroscopy (C near edge X-ray absorption fine structure spectroscopy [NEXAFS] and scanning transmission X-ray microscopy [STXM]) is also included for shale samples and sediment samples.Additional acknowledgements:1. M.K. and C.A. were supported by the Department of Energy, Office of Biological and Environmental Research, Subsurface Biosphere Research program (award no. DE-SC0016544).2. STXM and NEXAFS data was collected at the Canadian Light Source, which is supported by the Canada Foundation for Innovation, Natural Sciences and Engineering Research Council of Canada, the University of Saskatchewan, the Government of Saskatchewan, Western Economic Diversification Canada, the National Research Council Canada, and the Canadian Institutes of Health Research.3. Radiocarbon analysis was supported in part by the Radiocarbon Collaborative, which is jointly sponsored by the USDA Forest Service Northern Research Station, the KCCAMS Facility at UC Irvine, and Michigan Technological University.Update 11/06/2019: An .kml file was added with the GPS locations for all the sampling sites.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Advancing river corridor science beyond disciplinary boundaries with an inductive approach to catalyse hypothesis generation

Abstract A unified conceptual framework for river corridors requires synthesis of diverse site‐, method‐ and discipline‐specific findings. The river research community has developed a substantial body of observations and process‐specific interpretations, but we are still lacking a comprehensive model to distill this knowledge into fundamental transferable concepts. We confront the challenge of how a discipline classically organized around the deductive model of systematically collecting of site‐, scale‐, and mechanism‐specific observations begins the process of synthesis. Machine learning is particularly well‐suited to inductive generation of hypotheses. In this study, we prototype an inductive approach to holistic synthesis of river corridor observations, using support vector machine regression to identify potential couplings or feedbacks that would not necessarily arise from classical approaches. This approach generated 672 relationships linking a suite of 157 variables each measured at 62 locations in a fifth order river network. Eighty four percent of these relationships have not been previously investigated, and representing potential (hypothetical) process connections. We document relationships consistent with current understanding including hydrologic exchange processes, microbial ecology, and the River Continuum Concept, supporting that the approach can identify meaningful relationships in the data. Moreover, we highlight examples of two novel research questions that stem from interpretation of inductively‐generated relationships. This study demonstrates the implementation of machine learning to sieve complex data sets and identify a small set of candidate relationships that warrant further study, including data types not commonly measured together. This structured approach complements traditional modes of inquiry, which are often limited by disciplinary perspectives and favour the careful pursuit of parsimony. Finally, we emphasize that this approach should be viewed as a complement to, rather than in place of, more traditional, deductive approaches to scientific discovery.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Root‐Pore Interactions, the Underestimated Driver for Rhizosphere Structure and Rhizosheath Development

Physical characteristics of rhizosphere and rhizosheath, that is, root-adhering soil, are crucial for plant performance. Yet, the drivers of the rhizosphere's structural properties and their relationships with rhizosheath development remain unclear. We used X-ray computed micro-tomography (i) to explore two drivers of rhizosphere porosity: root-induced changes vs. preferential root growth into soil with certain pore characteristics and (ii) to estimate their contributions to rhizosphere macroporosity gradients and rhizosheath formation. Rhizosheath development was assessed in relation to rhizosphere macroporosity and rhizodeposition after ¹⁴C labeling. Our results confirmed that both root-induced changes and growth preferences shape rhizosphere structure, with their relative significance depending on the inherent macropore availability. In intact soils, growth preferences were the dominant factor, while in sieved soils the root-induced changes became equally important. Rhizosheath formation was associated with roots compacting their surrounding and releasing carbon. However, no correlation was found between rhizosheath formation and the actual rhizosphere, that is, the volume of soil adjacent to the roots. The study offers new process-level understanding of rhizosphere porosity gradients, while emphasizing caution in interpreting root growth data from sieved soil studies. Similarly, traditional destructively sampled rhizosheath may not fully capture the true characteristics of the actual rhizosphere, underscoring importance of intact-soil analyses.

macroporosity gradients↗
DOE OSTI2019

biodataganache/SIEVE-Ub

Code and data for the SIEVE-Ub prediction algorithm for prediction of E3 ubiquitin ligase mimics The SIEVEUb approach is a novel approach to determination of sequence similarity that retains flexibility in sequence via a reduced amino acid alphabet and does not require sequence alignment, a prohibitive step for many applications.

McDermott, Jason↗
DOE OSTI2017

Assessment of the Idaho National Laboratory Remote Handled Low Level Waste Disposal Facility Hydraulic Performance

This document provides a summary of the expected hydraulic performance of the vault drainage system installed at Idaho National Laboratory’s Remote Handled Low-Level Waste disposal facility. Hydraulic performance was assessed through analysis of the mechanical properties of the drainage system and backfill materials, including material gradation and proctor data; laboratory data, including bulk density, porosity, unsaturated hydraulic conductivity, moisture-retention data, and van Genuchten parameters; and field-data collected using in-situ instrumentation with data collected during a vault-scale infiltration characterization test. Hydraulic performance of the vault drainage system was designed to promote a greater than 500-year vault concrete longevity. The predicted hydraulic performance is, in part, a function of the materials used in construction, sequencing of the hydraulic drainage materials, and the as-built condition of the materials following compaction necessary to ensure vault stability. Specifying specific as-built hydraulic properties is exceedingly difficult at the facility specification/design phase. Instead, material mechanical properties were specified and confirmed early during the construction process. As the drainage materials were installed, samples were sent to a laboratory for hydraulic property testing and, after drainage system installation was complete around the performance assessment vaults, a field-scale infiltration test was conducted with data collection to verify the as-built hydraulic performance. This report provides summary data for the measured mechanical properties, laboratory data, and field infiltration characterization test data. Mechanical data have relatively little variability because of the sieve system used when the materials were crushed onsite. Laboratory data were obtained for a relatively small number of material samples, but the data obtained for each sample are extensive. However, laboratory data provide the moisture retention relationships and relative hydraulic conductivity-moisture content relationships for uninstalled materials. Conducting field-scale infiltration tests with collection of moisture retention data and wetting front propagation data allows extension of laboratory data to the as-installed conditions of the vault drainage system. These combined data types are integrated using a numerical simulation of the infiltration characterization test to refine model parameters. The infiltration characterization model will be used to support the hydraulic and concrete performance of the vault system provided in the facility performance assessment.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Flux Equations for Osmotically Moderated Sorption–Diffusion Transport in Rigid Microporous Membranes

The development of non-aqueous reverse osmosis separations via the use of rigid microporous membrane materials suggests that flux equations originally developed for swellable polymeric membranes should be revisited. This paper demonstrates that the gradient of fractional occupancy of penetrant molecules within the micropores of the membrane is the driving force for permeation without requiring assumptions about pressure within the membrane. Flux equations are derived using both Fickian and Maxwell-Stefan approaches, and different behavior in the permeate flux versus upstream hydraulic pressure relationship is shown to arise as a result of differences in the loading dependence of the single component Maxwell-Stefan diffusivity. Molecular modeling results available in the literature and experimental data obtained from carbon molecular sieve (CMS) membranes showcase that these loading-dependent changes in the Maxwell-Stefan diffusivity are possible. This loading dependence is separated into three regimes: so-called “weak confinement” diffusion and “strong confinement” diffusion, both of which have been discussed at length in the literature, and a new “hybrid confinement” diffusion, which is introduced here. Furthermore, the separation mechanism of solvent molecules through a rigid bimodally microporous membrane is studied using xylene molecules passing through CMS membranes fabricated under different conditions as examples. Altogether, this study provides fundamental insight and guidance into osmotically-moderated sorption-diffusion transport of solvent molecules through rigid microporous membranes.

36 MATERIALS SCIENCE↗
DOE OSTI2023

An experiment-informed discrete element modelling study of knife milling for flexural biomass feedstocks

A discrete element method (DEM) based approach is used to study the relationships between material attributes (MAs), processing parameters (PPs), and quality attributes (QAs) for the knife milling of maize stalks. An approximate DEM shape model was conceptualized based on real maize stalks and calibrated based on experimental bending test data for flexural properties (elastic bending stiffness, elastic bending angle limit, elastoplastic ratio, etc.). DEM simulations of maize stalk comminution in a Jordan Reduction Solutions (“JRS”) knife mill were performed to investigate the relationships between the MAs (maize stalk size and breakage stress limit), PPs (impeller rotational speed), and QAs (mass throughput and output particle size distribution (PSD)). The DEM results suggest that stalk length has little influence on mass throughput and PSD, whilst stalks with larger cross sections tend to generate larger sizes of milled particles given the same breakage stress limit. Both the DEM and experimental results show that faster impeller rotation (or higher power) does not necessarily generate higher throughput or smaller output PSD, especially for maize stalks of higher breakage stress limit. The correlations between these MAs, PPs and QAs are found highly stochastic, though breakage stress limit dictates mass throughput, regardless of stalk size. The DEM-predicted output particle size tended to match the experimental data with coarse PSDs based on sieve size but showed weakened fidelity with finer material, indicating the potential for further model improvement.

09 BIOMASS FUELS↗
DOE OSTI2015

Isotherms for Water Adsorption on Molecular Sieve 3A: Influence of Cation Composition

This study is part of our continuing efforts to address engineering issues related to the removal of tritiated water from off-gases produced in used nuclear fuel reprocessing facilities. In the current study, adsorption equilibrium of water on molecular sieve 3A beads was investigated. Adsorption isotherms for water on the UOP molecular sieve 3A were measured by a continuous-flow adsorption system at 298, 313, 333, and 353 K. Experimental data collected were analyzed by the Generalized Statistical Thermodynamic Adsorption (GSTA) isotherm model. The K + /Na + molar ratio of this particular type of molecular sieve 3A was ~4:6. Our results showed that the GSTA isotherm model worked very well to describe the equilibrium behavior of water adsorption on molecular sieve 3A. The optimum number of parameters for the current experimental data was determined to be a set of four equilibrium parameters. This result suggests that the adsorbent crystals contain four energetically distinct adsorption sites. In addition, it was found that water adsorption on molecular sieve 3A follows a three-stage adsorption process. This three-stage adsorption process confirmed different water adsorption sites in molecular sieve crystals. In addition, the second adsorption stage is significantly affected by the K + /Na + molar ratio. In this stage, the equilibrium adsorption capacity at a given water vapor pressure increases as the K + /Na + molar ratio increases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Further Investigations of Racemic and Chiral Molecular Sieves of the STW Topology

Large single crystals of pure-silica STW-type molecular sieves are prepared using 1,2,3,4,5-pentamethylimidazolium (12345PMI) and 2-ethyl-1,3,4-trimethylimidazolium (2E134TMI) as organic structure-directing agents (OSDAs) and α-amino acid additives. The effects of the amount and type of amino acid on the crystallization of pure-silica STW materials are investigated. Room-temperature single-crystal X-ray diffractometry shows that 12345PMI better fits the STW cage than 2E134TMI and is fully consistent with computed simulations. The synthesis of an enantioenriched R-STW-type molecular sieve having a Si/Ge ratio of 2.2 is achieved using a chiral, dicationic OSDA that contains two stereocenters. Furthermore, the conformation of the chiral OSDA in the chiral framework has been obtained from a Rietveld refinement using synchrotron powder diffraction data and is the first structure refinement of an enantioenriched, inorganic molecular sieve prepared from a pure, asymmetric OSDA.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Unified Medical Language System resources improve sieve-based generation and Bidirectional Encoder Representations from Transformers (BERT)–based ranking for concept normalization

Concept normalization, the task of linking phrases in text to concepts in an ontology, is useful for many downstream tasks including relation extraction, information retrieval, etc. We present a generate-and-rank concept normalization system based on our participation in the 2019 National NLP Clinical Challenges Shared Task Track 3 Concept Normalization. The shared task provided 13 609 concept mentions drawn from 100 discharge summaries. We first design a sieve-based system that uses Lucene indices over the training data, Unified Medical Language System (UMLS) preferred terms, and UMLS synonyms to generate a list of possible concepts for each mention. We then design a listwise classifier based on the BERT (Bidirectional Encoder Representations from Transformers) neural network to rank the candidate concepts, integrating UMLS semantic types through a regularizer. Our generate-and-rank system was third of 33 in the competition, outperforming the candidate generator alone (81.66% vs 79.44%) and the previous state of the art (76.35%). During postevaluation, the model’s accuracy was increased to 83.56% via improvements to how training data are generated from UMLS and incorporation of our UMLS semantic type regularizer. Analysis of the model shows that prioritizing UMLS preferred terms yields better performance, that the UMLS semantic type regularizer results in qualitatively better concept predictions, and that the model performs well even on concepts not seen during training. Our generate-and-rank framework for UMLS concept normalization integrates key UMLS features like preferred terms and semantic types with a neural network–based ranking model to accurately link phrases in text to UMLS concepts.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2023

Singleton Sieving: Overcoming the Memory/Speed Trade-Off in Exascale k-mer Analysis

Traditional filter data structures, such as Bloom filters, do not offer necessary features that modern high-performance data analytics applications need in order to efficiently perform complex data analysis tasks. For example, MetaHipMer, a de novo metagenome assembler, can use filters to weed out singleton k-mers and reduce memory usage by 30%-70%. However, the filter needs the ability to associate values with k-mers in order to perform the analysis in a single communication pass. Bloom filters do not support value associations and cause the application to perform an extra communication pass, thereby increasing the run time. Therefore, MetaHipMer faces a trade off between memory and speed due to the limited capabilities of traditional filters. In this paper, we overcome the memory and speed trade off in MetaHipMer by integrating a GPU-based feature-rich filter, the Two-Choice filter (TCF), in the MetaHipMer pipeline. The TCF uses key-value association to approximately store k-mers with extensions. This allows MetaHipMer to perform k-mer analysis on the GPUs in a single communication pass. Our empirical analysis shows a 50% reduction in memory usage in k-mer analysis on each node in MetaHipMer without any effect on the overall run time or assembly quality. The memory reduction in turn results in a 43% reduction in the number of nodes required to assemble datasets and enables MetaHipMer to scale to much larger datasets.

McCoy, Hunter↗
DOE OSTI2024

A methodology for selection of solid desiccants in energy recovery ventilators

Controlling indoor humidity levels is essential for maintaining acceptable indoor air quality in buildings. The use of energy recovery ventilators (ERVs) is an energy-efficient way to regulate indoor air humidity. Fixed-bed regenerators and rotary wheels are widely used ERVs because of their high sensible and latent effectiveness. These ERVs are made of desiccant-coated substrates, which enable them to transfer moisture between the supply and exhaust air streams. However, the moisture transfer ability of ERVs depends on the physiochemical and sorption properties of desiccants. Extensive, full-scale experiments are required to determine the best desiccant material for these systems. This paper presents a simplified method of selecting suitable desiccant materials for ERVs. The methodology involves important characterization methods, literature correlations for performance prediction, and cost-effective testing methods prior to full-scale testing, and full-scale test methods are discussed in detail. Furthermore, the performance of a few newly derived materials is evaluated and compared with that of conventional desiccants such as silica gel and molecular sieves. The highest latent effectiveness was obtained for composite of super absorbent polymer (SAP) with potassium formate (SAP-HCO2K-50 %), all-polymer porous solid desiccant (APPSD) and metal organic framework (MOF)–MIL–101 (Cr), followed by activated carbon fibre felt (ACFF) Silica sol-LiCl30, SAP, silica gel, MOF–303, and molecular sieve. Researchers and manufacturers would benefit from the proposed methodology and presented data in developing new desiccant materials for ERV applications.

Energy recovery↗
DOE OSTI2023

Modeling dust mineralogical composition: sensitivity to soil mineralogy atlases and their expected climate impacts

Soil dust aerosols are a key component of the climate system, as they interact with short- and long-wave radiation, alter cloud formation processes, affect atmospheric chemistry and play a role in biogeochemical cycles by providing nutrient inputs such as iron and phosphorus. The influence of dust on these processes depends on its physicochemical properties, which, far from being homogeneous, are shaped by its regionally varying mineral composition. The relative amount of minerals in dust depends on the source region and shows a large geographical variability. However, many state-of-the-art Earth system models (ESMs), upon which climate analyses and projections rely, still consider dust mineralogy to be invariant. The explicit representation of minerals in ESMs is more hindered by our limited knowledge of the global soil composition along with the resulting size-resolved airborne mineralogy than by computational constraints. In this work we introduce an explicit mineralogy representation within the state-of-the-art Multiscale Online Nonhydrostatic AtmospheRe CHemistry (MONARCH) model. We review and compare two existing soil mineralogy datasets, which remain a source of uncertainty for dust mineralogy modeling and provide an evaluation of multiannual simulations against available mineralogy observations. Soil mineralogy datasets are based on measurements performed after wet sieving, which breaks the aggregates found in the parent soil. Our model predicts the emitted particle size distribution (PSD) in terms of its constituent minerals based on brittle fragmentation theory (BFT), which reconstructs the emitted mineral aggregates destroyed by wet sieving. Our simulations broadly reproduce the most abundant mineral fractions independently of the soil composition data used. Feldspars and calcite are highly sensitive to the soil mineralogy map, mainly due to the different assumptions made in each soil dataset to extrapolate a handful of soil measurements to arid and semi-arid regions worldwide. For the least abundant or more difficult-to-determine minerals, such as iron oxides, uncertainties in soil mineralogy yield differences in annual mean aerosol mass fractions of up to ~ 100 %. Although BFT restores coarse aggregates including phyllosilicates that usually break during soil analysis, we still identify an overestimation of coarse quartz mass fractions (above 2 µm in diameter). In a dedicated experiment, we estimate the fraction of dust with undetermined composition as given by a soil map, which makes up ~ 10 % of the emitted dust mass at the global scale and can be regionally larger. Changes in the underlying soil mineralogy impact our estimates of climate-relevant variables, particularly affecting the regional variability of the single-scattering albedo at solar wavelengths or the total iron deposited over oceans. All in all, this assessment represents a baseline for future model experiments including new mineralogical maps constrained by high-quality spaceborne hyperspectral measurements, such as those arising from the NASA Earth Surface Mineral Dust Source Investigation (EMIT) mission.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Novel Full-Ceramic Multi-Tubular Membrane Systems for Pre-Combustion CO2 Capture with Simultaneous H2 Production: Fabrication, Performance Testing, and 3D CFD Modeling

Inorganic membranes show promise for application in pre-combustion CO2 capture with simultaneous H2 production. State-of-the-art systems for use under high temperature and pressure conditions consist of multiple membrane tube bundles prepared in a "candle-filter" configuration, in which the membrane tubes are open at one end and sealed at the other. This configuration is used for practical reasons, specifically the need to minimize potential problems due to thermal expansion mismatch, at high temperatures, between the ceramic tube bundle and the steel housing. The primary technical problem with the candle-filter configuration for use in commercial-scale installations is the inability to purge the permeate side (typically the tube side), a feature that is crucial for high H2 recovery. In this study, we fabricated dual-end open, commercial-size ceramic multiple-tube bundles made of zeolite, palladium (Pd), and carbon molecular sieve (CMS) membranes that enable permeate-side (tube-side) purge for gas separation applications. Experimental gas separation data with these membrane bundles under harsh operating conditions (temperatures up to 350 and pressures up to 800 psig), to be presented at the meeting, manifest excellent performance. Parallel to the membrane bundle construction and testing efforts, we have also developed a detailed 3D CFD modeling package using COMSOL Multiphysics software to gain more insight into the effect on the H2 purity and recovery of the detailed geometry of the multi-tubular membrane system, including the number of tubes used, their dimensions, and placement in the bundle, as well as the number, type, and positioning of internal baffles and other flow-enhancement accessories. The CFD package is validated with experimental data from different systems (1-tube, 3-tube, and 19-tube bundles), and shows high accuracy in predicting the experimental results (<5 % error in all cases). The results of our study show that the detailed internal geometry of these multi-tubular membrane systems has a considerable impact on the performance of the system as the flow maldistribution within the shell-side can substantially decrease (>40%) the H2 recovery.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2017

Chemistry, Mineralogy, and Grain Properties at Namib and High Dunes, Bagnold Dune Field, Gale Crater, Mars: A Synthesis of Curiosity Rover Observations: Bagnold Dune Sands Composition

The Mars Science Laboratory Curiosity rover performed coordinated measurements to examine the textures and compositions of aeolian sands in the active Bagnold dune field. The Bagnold sands are rounded to subrounded, very fine- to medium- sized (~45-500 µm) with ≥6 distinct grain colors. In contrast to sands examined by Curiosity in a dust-covered, inactive bedform called Rocknest and soils at other landing sites, Bagnold sands are darker, less red, better sorted, have fewer silt-sized or smaller grains, and show no evidence for cohesion. Nonetheless, Bagnold mineralogy and Rocknest mineralogy are similar with plagioclase, olivine, and pyroxenes in similar proportions comprising >90% of crystalline phases, along with a substantial amorphous component (35% ± 15%). Yet, Bagnold and Rocknest bulk chemistry differ. Bagnold sands are Si-enriched relative to other soils at Gale crater, and H 2 O, S, and Cl are lower relative to all previously measured martian soils and most Gale crater rocks. Mg, Ni, Fe, and Mn are enriched in the coarse-sieved fraction of Bagnold sands, corroborated by VNIR spectra that suggest enrichment of olivine. Together, patterns in major element chemistry and volatile release data indicate two distinctive volatile reservoirs in martian soils: (1) amorphous components in the sand-sized fraction (represented by Bagnold) that are Si-enriched, hydroxylated alteration products and/or impact or volcanic glasses; and (2) amorphous components in the fine fraction (<40 µm; represented by Rocknest and other bright soils) that are Fe-, S-, and Cl-enriched with low Si and adsorbed and structural H 2 O.

58 GEOSCIENCES↗
DOE OSTI2017

Preparation and Characterization of a Master Blend of Plutonium Oxide for the 3013 Large Scale Shelf-Life Surveillance Project

A mixture of chlorine-containing, impure plutonium oxides has been produced and has been given the name Master Blend. This large quantity of well-characterized chlorinecontaining material is available for use in the Integrated Surveillance and Monitoring Program for shelf-life experiments. It is intended to be representative of materials packaged to meet DOE-STD-3013.1 The Master Blend contains a mixture of items produced in Los Alamos National Laboratory’s (LANL) electro-refining pyrochemical process in the late 1990s. Twenty items were crushed and sieved, calcined to 800ºC for four hours, and blended multiple times. This process resulted in four batches of Master Blend. Calorimetry and density data on material from the four batches indicate homogeneity.

3013 electro-refining storagage radioactive↗
DOE OSTI2025

Quantum Sieving for Isotopic Separations of Gases Using Porous Materials─30 Years of Progress

Here, this paper reviews theoretical and experimental efforts to establish microporous materials that can be used to separate isotopologues of molecular gases such as H 2 and D 2 . Emphasis is placed on use of simplified models to highlight the quantum phenomena that make these separations possible. In equilibrium adsorption, differences in zero point energy in the adsorbed states of molecules favor binding of heaver isotopologues (e.g. D 2 relative to H 2 ). Experimental data showing this effect was reported as early as 1933, but the theoretical work of Beenakkers et al. in 1995 [Chem. Phys. Lett. 232 (1995) 379-382] spurred modern efforts to develop materials with strong so-called quantum sieving. In porous materials where the transition state for molecular diffusion is more strongly confined than the energy minima associated with equilibrium adsorption, differences in zero point energies between these two sites can lead to isotopic differences in molecular diffusivities. This effect favors diffusion of heavier species (e.g. D 2 ) relative to lighter species (e.g. H 2 ). This so-called kinetic quantum sieving has been observed experimentally in porous carbons and in porous organic cage materials. We show that quantum tunneling, which favors hopping of lighter species across energy barriers, diminishes the strength of kinetic quantum sieving but that it appears to make only a small contribution to the net molecular diffusivities in many porous materials of practical interest.

Sholl, David S. [Oak Ridge National Laboratory (OR↗