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DOE OSTI2024

Summary of Gas Generation Behavior Observed in 3013 Surveillance and Monitoring Program Shelf-Life Experiments

Gas generation experiments have been conducted in small- and full-scale test containers at Los Alamos National Laboratory on samples of plutonium oxide material collected from plutonium processes across the DOE complex and tested at the bounding conditions for the Department of Energy 3013 Standard. The gas composition and pressures in the sealed experimental containers were measured over periods of months to years. These experiments have provided results for the formation and consumption of hydrogen and other gases. The conditions supporting the formation of flammable gas mixtures of hydrogen and oxygen in flammable gas mixtures were also determined. Different behaviors were observed between the materials tested based on their compositions, the stabilization performed on the material, and the post stabilization handling of the material. Many of the experiments are still ongoing. This report summarizes the results obtained for the gas generation behavior for high-purity plutonium oxides and salt-bearing impure plutonium oxides in sealed containers.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Establishing robust correction schemes for improved and reliable ARM-AOS aerosol optical data products

Aerosol light absorption and scattering of solar radiation play an important role in the earth’s atmosphere in terms of direct and semi-direct radiative forcing. Optical parameters of importance to the US Department of Energy (DOE) climate models include absorption and scattering coefficients, single scattering albedo (SSA), absorption Angstrom exponents (AAE), and the asymmetry parameter (g). These parameters depend on aerosol size, shape and composition (refractive index), and are spectrally sensitive in the shortwave region. Additionally, these parameters have a complex dependency on the emission source, especially for carbonaceous aerosols. The DOE Atmospheric Radiation Measurement (ARM) user facility has deployed aerosol observing systems (AOS) containing several filter-based instruments to measure and constrain aerosol optical properties and related parameters at multiple sites worldwide. For measurement of aerosol light absorption, the AOS includes filter-based instruments (particle soot absorption photometer and tricolor absorption photometer) that infer particle-phase aerosol absorption coefficients at nominal red, green, and blue wavelength bands from the attenuation (ATN) of light passing through a particulate filter on which aerosols are deposited. Measurement of aerosol scattering is done in situ using nephelometers. By combining inferred absorption coefficients from filter-based ATN measurements and in situ scattering coefficients, value-added products (VAPs) such as SSA, AAE, and g are derived.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

The Art of Automation: Translating Electron Microscopy Workflows Into Automated Processes

Acquiring data using a scanning transmission electron microscope (STEM) is a complex, multi-step process. The intricacy of the process depends on the type of sample, composition of the material, desired results of the experiment, resolution requirement and other experimental factors. Each experiment presents unique complications, such as sample drift and contamination, that the microscopist must consider when acquiring data. All these challenges are handled fluidly and expertly by experienced microscopists, but to reach new levels of innovation in material development, including greater reproducibility, throughput, and precision, the automation of these workflows is essential. The initial phase of this work involved translating intuition-based workflows into discrete, programmable steps. Some common key stages in STEM workflows are the initial tuning, scanning the sample for areas of interest, and then acquiring the data. Each stage can be broken further into specific parameter adjustments, such as aberration correction and dwell time optimization, depending on the experiment. When deconstructing various experiments each step was assessed for automation feasibility based on the amount of real time operator decisions. There are steps that lend themselves to automation more readily than others, such as course focusing and sample screening, but there is potential for full automation of all stages with time. As an initial step, an automated montage routine was developed, allowing for the efficient acquisition of large portions of the sample without requiring continuous intervention from the operator. The automation of this small process of the procedure demonstrates the value of this capability. A major challenge in automation arises from discrepancies between commanded, reported and actual stage movements. Using systematic tests, stage movement was quantified. This error can be corrected algorithmically for more accurate workflows in the future. Expanding automation capabilities would result in larger, more efficient data acquisition which allows for more robust statistical analysis. Additionally, this work lays the groundwork for a closed loop system where machine learning algorithms would intake automatically acquired data and make real time decisions. By progressively automating this instrument, this work establishes the foundation for fully automated experimentation in transmission electron microscopy.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Analytical Modeling of Exoplanet Transit Spectroscopy with Dimensional Analysis and Symbolic Regression

Abstract The physical characteristics and atmospheric chemical composition of newly discovered exoplanets are often inferred from their transit spectra, which are obtained from complex numerical models of radiative transfer. Alternatively, simple analytical expressions provide insightful physical intuition into the relevant atmospheric processes. The deep-learning revolution has opened the door for deriving such analytical results directly with a computer algorithm fitting to the data. As a proof of concept, we successfully demonstrate the use of symbolic regression on synthetic data for the transit radii of generic hot-Jupiter exoplanets to derive a corresponding analytical formula. As a preprocessing step, we use dimensional analysis to identify the relevant dimensionless combinations of variables and reduce the number of independent inputs, which improves the performance of the symbolic regression. The dimensional analysis also allowed us to mathematically derive and properly parameterize the most general family of degeneracies among the input atmospheric parameters that affect the characterization of an exoplanet atmosphere through transit spectroscopy.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Molecular molybdenum persulfide and related catalysts for generating hydrogen from water

New metal persulfido compositions of matter are described. In one embodiment the metal is molybdenum and the metal persulfido complex mimics the structure and function of the triangular active edge site fragments of MoS.sub.2, a material that is the current industry standard for petroleum hydro desulfurization, as well as a promising low-cost alternative to platinum for electrocatalytic hydrogen production. This molecular [(PY5W.sub.2)MoS.sub.2].sup.x+ containing catalyst is capable of generating hydrogen from acidic-buffered water or even seawater at very low overpotentials at a turnover frequency rate in excess of 500 moles H.sub.2 per mole catalyst per second, with a turnover number (over a 20 hour period) of at least 19,000,000 moles H.sub.2 per mole of catalyst.

08 HYDROGEN↗

DOE OSTI2016

Molecular molybdenum persulfide and related catalysts for generating hydrogen from water

36 MATERIALS SCIENCE↗

DOE OSTI2022

Understanding the Role of Cesium on Chemical Complexity in Methylammonium-Free Metal Halide Perovskites

Mixed cesium- and formamidinium-based metal halide perovskites (MHPs) are emerging as ideal photovoltaic materials due to their promising performance and improved stability. While theoretical predictions suggest that a larger composition ratio of Cs (≈30%) aids the formation of a pure photoactive α-phase, high photovoltaic performances can only be realized in MHPs with moderate Cs ratios. In fact, elemental mixing in a solution can result in chemical complexities with non-equilibrium phases, causing chemical inhomogeneities localized in the MHPs that are not traceable with global device-level measurements. Thus, the chemical origin of the complexities and understanding of their effect on stability and functionality remain elusive. Herein, through spatially resolved analyses, the fate of local chemical structures, particularly the evolution pathway of non-equilibrium phases and the resulting local inhomogeneities in MHPs is comprehensively explored. It is illustrated that Cs-rich MHPs have substantial local inhomogeneities at the initial crystallization step, which do not fully convert to the α-phase and thereby compromise the optoelectronic performance of the materials. These fundamental observations allow the authors to draw a complete chemical landscape of MHPs including nanoscale chemical mechanisms, providing indispensable insights into the realization of a functional materials platform.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Impact of Thermal Pretreatment Temperatures on Woody Biomass Chemical Composition, Physical Properties and Microstructure

Thermal pretreatment of biomass by torrefaction and low temperature pyrolysis has the potential for generating high quality and more suitable fuels. To utilize a model to describe the complex and dynamic changes taking place during these two treatments for process design, optimization and scale-up, detailed data is needed on the property evolution during treatment of well-defined individual biomass particles. The objectives of this study are to investigate the influence of thermal pretreatment temperatures on wood biomass biochemical compositions, physical properties and microstructure. Wild cherry wood was selected as a model biomass and prepared for this study. The well-defined wood particle samples were consecutively heated at 220, 260, 300, 350, 450 and 550 °C for 0.5 h under nitrogen. Untreated and treated samples were characterized for biochemical composition changes (cellulose, hemicellulose, and lignin) by thermogravimetric analyzer (TGA), physical properties (color, dimensions, weight, density and grindablity), chemical property (proximate analysis and heating value) and microstructural changes by scanning electron microscopy (SEM). Hemicellulose was mostly decomposed in the samples treated at 260 and 300 °C and resulted in the cell walls weakening resulting in improved grindability. The dimensions of the wood were reduced in all directions and shrinkage increased with increased treatment temperature and weight loss. With increased treatment temperature, losses of weight and volume increased and bulk density decreased. The low temperature pyrolyzed wood samples improved solid fuel property with high fuel ratio, which are close to lignite/bituminous coal. Morphology of the wood remained intact through the treatment range but the cell walls were thinner. Lastly, these results will improve the understanding of the property changes of the biomass during pretreatment and will help to develop models for process simulation and potential application of the treated biomass.

09 BIOMASS FUELS↗

DOE OSTI2016

Nonintrusive Uncertainty Quantification of Computational Fluid Dynamics Simulations of a Bench-Scale Fluidized-Bed Gasifier

Uncertainty quantification (UQ) analysis is increasingly becoming one of the major requirements of simulation-based engineering to assess the confidence in the results and make better-informed decisions based on the insight derived from the simulations. In an earlier study, Bayesian UQ analysis was applied to existing bench-scale fluidized-bed gasifier experiment results. In the current study, a series of simulations were carried over with the open-source computational fluid dynamics software MFiX to reproduce the experimental conditions, where three operating factors, i.e., coal flow rate, coal particle diameter, and steam-to-oxygen ratio, were systematically varied to understand their effect on the syngas composition. Bayesian UQ analysis was this time performed on the numerical results for comparison purposes. This is part of ongoing research efforts to explore the applicability of advanced UQ methods and processes such as Bayesian methods for large-scale complex multiphase flow simulations. As part of Bayesian UQ analysis, a global sensitivity analysis was performed based on the simulation results, which shows that the predicted syngas composition is strongly affected not only by the steam-to-oxygen ratio (which was observed in experiments as well) but also by variation in the coal flow rate and particle diameter (which was not observed in experiments). The carbon monoxide mole fraction is underpredicted at lower steam-to-oxygen ratios and overpredicted at higher steam-to-oxygen ratios. The opposite trend is observed for the carbon dioxide mole fraction. These discrepancies are attributed to either excessive segregation of the phases that leads to the fuel-rich or -lean regions or alternatively the selection of reaction models, where different reaction models and kinetics can lead to different syngas compositions throughout the gasifier.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2016

Cellulose-Enriched Microbial Communities from Leaf-Cutter Ant (Atta colombica) Refuse Dumps Vary in Taxonomic Composition and Degradation Ability

Deconstruction of the cellulose in plant cell walls is critical for carbon flow through ecosystems and for the production of sustainable cellulosic biofuels. Our understanding of cellulose deconstruction is largely limited to the study of microbes in isolation, but in nature, this process is driven by microbes within complex communities. In Neotropical forests, microbes in leaf-cutter ant refuse dumps are important for carbon turnover. These dumps consist of decaying plant material and a diverse bacterial community, as shown here by electron microscopy. To study the portion of the community capable of cellulose degradation, we performed enrichments on cellulose using material from five Atta colombica refuse dumps. The ability of enriched communities to degrade cellulose varied significantly across refuse dumps. 16S rRNA gene amplicon sequencing of enriched samples identified that the community structure correlated with refuse dump and with degradation ability. Overall, samples were dominated by Bacteroidetes, Gammaproteobacteria, and Betaproteobacteria. Half of abundant operational taxonomic units (OTUs) across samples were classified within general containing known cellulose degraders, including Acidovorax, the most abundant OTU detected across samples, which was positively correlated with cellulolytic ability. Lastly, a representative Acidovorax strain was isolated, but did not grow on cellulose alone. Phenotypic and compositional analyses of enrichment cultures, such as those presented here, help link community composition with cellulolytic ability and provide insight into the complexity of community-based cellulose degradation.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Biases in genome reconstruction from metagenomic data

Background Advances in sequencing, assembly, and assortment of contigs into species-specific bins has enabled the reconstruction of genomes from metagenomic data (MAGs). Though a powerful technique, it is difficult to determine whether assembly and binning techniques are accurate when applied to environmental metagenomes due to a lack of complete reference genome sequences against which to check the resulting MAGs. Methods We compared MAGs derived from an enrichment culture containing ~20 organisms to complete genome sequences of 10 organisms isolated from the enrichment culture. Factors commonly considered in binning software—nucleotide composition and sequence repetitiveness—were calculated for both the correctly binned and not-binned regions. This direct comparison revealed biases in sequence characteristics and gene content in the not-binned regions. Additionally, the composition of three public data sets representing MAGs reconstructed from the Tara Oceans metagenomic data was compared to a set of representative genomes available through NCBI RefSeq to verify that the biases identified were observable in more complex data sets and using three contemporary binning software packages. Results Repeat sequences were frequently not binned in the genome reconstruction processes, as were sequence regions with variant nucleotide composition. Genes encoded on the not-binned regions were strongly biased towards ribosomal RNAs, transfer RNAs, mobile element functions and genes of unknown function. Our results support genome reconstruction as a robust process and suggest that reconstructions determined to be >90% complete are likely to effectively represent organismal function; however, population-level genotypic heterogeneity in natural populations, such as uneven distribution of plasmids, can lead to incorrect inferences.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Investigating Core Gaps and the Development of Subcomponent Validation Methods for Wind Turbine Blades: Preprint

Core gaps are a common manufacturing defect observed in wind blade composite sandwich constructions, which occur when sheets of core material are not properly butted up against each other in the mold. The aim of this study was to characterize core gaps in composite sandwich constructions at the coupon scale. This was to gain an initial understanding of the defect before developing appropriate methodologies for more complex subcomponents as part of a much broader wind blade structural validation and damage tolerance program. Long beam flexure in 4-point-bending was chosen as the most appropriate loading scenario. Beam specimens were characterized with and without 10 mm core gaps in fiberglass/balsa sandwich beams. The core gaps were characterized with two separate resin systems; a Hexion epoxy and Arkema's Elium resins system (a novel, infusible thermoplastic). Results showed that the Elium beams without the core gaps were had a 15% lower static strength than their epoxy counterparts. The introduction of the core gap to the epoxy beams reduced their static strength by 35%. The Elium beams, however, exhibited negligible strength reductions with the inclusion of the core gap. Overall, this characterization study provided pertinent information with regards to core gaps as a manufacturing defect to allow for continued development of damage tolerance and subcomponent validation methodologies with the inclusion of manufacturing defects.

17 WIND ENERGY↗

DOE OSTI2016

Corrigendum to "Predicting biomass of hyperdiverse and structurally complex central Amazonian forests — a virtual approach using extensive field data" Published in Biogeosciences, 13, 1553-1570, 2016

Old-growth forests are subject to substantial changes in structure and species composition due to the intensification of human activities, gradual climate change and extreme weather events. Trees store ca. 90% of the total aboveground biomass (AGB) in tropical forests and precise tree biomass estimation models are crucial for management and conservation. In the central Amazon, predicting AGB at large spatial scales is a challenging task due to the heterogeneity of successional stages, high tree species diversity and inherent variations in tree allometry and architecture. We parameterized generic AGB estimation models applicable across species and a wide range of structural and compositional variation related to species sorting into height layers as well as frequent natural disturbances. We used 727 trees (diameter at breast height ≥5 cm) from 101 genera and at least 135 species harvested in a contiguous forest near Manaus, Brazil. Sampling from this data set we assembled six scenarios designed to span existing gradients in floristic composition and size distribution in order to select models that best predict AGB at the landscape level across successional gradients. We found that good individual tree model fits do not necessarily translate into reliable predictions of AGB at the landscape level. We observed systematic biases ranging from -31% (pantropical) to +39 %, with root-mean-square error (RMSE) values of up to 130-Mg ha -1 (pantropical), when predicting AGB (dry mass) over scenarios using our different models and an available pantropical model. Our first and second best models had both low mean biases (0.8 and 3.9 %, respectively) and RMSE (9.4 and 18.6 Mg ha -1 ) when applied over scenarios. Predicting biomass correctly at the landscape level in hyperdiverse and structurally complex tropical forests, especially allowing good performance at the margins of data availability for model construction/calibration, requires the inclusion of predictors that express inherent variations in species architecture. Furthermore, the model of interest should comprise the floristic composition and size-distribution variability of the target forest, implying that even generic global or pantropical biomass estimation models can lead to strong biases. Reliable biomass assessments for the Amazon basin (i.e., secondary forests) still depend on the collection of allometric data at the local/regional scale and forest inventories including species-specific attributes, which are often unavailable or estimated imprecisely in most regions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Feasibility study of a compact neutron resonance transmission analysis instrument

Neutron Resonance Transmission Analysis (NRTA) uses resonant absorption of neutrons to infer the absolute isotopic composition of a target object, enabling applications in a broad range of fields such as archaeology, enrichment analysis of nuclear fuel, and arms control treaty verification. In the past, NRTA involved large user facilities and complex detector systems. However, recent advances in the intensity of compact neutron sources have made compact neutron imaging designs increasingly feasible. This work describes the Monte Carlo (MC) based design of a compact epithermal NRTA radiographic instrument which uses a moderated, compact deuterium-tritium (DT) neutron source and an epithermal neutron detector. Such an instrument would have a wide range of applications, and would be especially impactful for such scenarios as nuclear inspection and arms control verification exercises, where system complexity and mobility may be of critical importance. The MC simulations presented in this work demonstrate accurate time-of-flight (TOF) reconstructions for transmitted neutron energies, capable of differentiating isotopic compositions of nuclear material with high levels of accuracy. A new generation of miniaturized and increasingly more intense neutron sources will allow this technique to achieve measurements with greater precision and speed, with significant impact on a variety of engineering and societal problems.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Cation Dynamics in Hybrid Halide Perovskites

Hybrid halide perovskite semiconductors exhibit complex, dynamical disorder while also harboring properties ideal for optoelectronic applications that include photovoltaics. However, these materials are structurally and compositionally distinct from traditional compound semiconductors composed of tetrahedrally coordinated elements with an average valence electron count of silicon. The additional dynamic degrees of freedom of hybrid halide perovskites underlie many of their potentially transformative physical properties. Neutron scattering and spectroscopy studies of the atomic dynamics of these materials have yielded significant insights into their functional properties. Specifically, inelastic neutron scattering has been used to elucidate the phonon band structure, and quasi-elastic neutron scattering has revealed the nature of the uncorrelated dynamics pertaining to molecular reorientations. Understanding the dynamics of these complex semiconductors has elucidated the temperature-dependent phase stability and origins of defect-tolerant electronic transport from the highly polarizable dielectric response. Furthermore, the dynamic degrees of freedom of the hybrid perovskites provide additional opportunities for application engineering and innovation.

Materials Science↗

DOE OSTI2023

Cocontinuous Nanostructures by Microphase Separation of Statistically Cross-Linked Polystyrene/Poly(2-vinylpyridine) Networks

Cocontinuous polymeric nanostructures have drawn considerable attention due to their ability to combine distinct, percolation-dependent properties of two different polymer domains. Randomly end-linked copolymer networks (RECNs) have previously been shown to support the formation of disordered cocontinuous nanostructures across wide composition windows in a robust way. However, achieving highly efficient linking of telechelic polymers with excellent end-group fidelity often requires complex synthetic routes. As an alternative, we study here statistically cross-linked copolymer networks (SCCNs) composed of polystyrene and poly(2-vinylpyridine) (PS and P2VP) with cross-linkable allyl pendent groups that are conveniently synthesized by controlled radical copolymerization. Via selective extraction of P2VP, coupled with gravimetry, small-angle X-ray scattering, and electron microscopy, we find disordered cocontinuous phases across wide composition ranges (up to ≈ 35 wt %), approaching values previously determined for RECNs. Remarkably, even for samples that appear to exhibit full percolation, a substantial fraction of P2VP (≈ 20–30 wt %) cannot be removed, which we ascribe to short strands between nearby cross-linkers that are physically embedded within PS domains. Here, the resulting PS porous monoliths with residual surface P2VP layers enable facile surface modification to resist protein adsorption and templating of porous gold nanostructures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

Comment on “A model for phosphate glass topology considering the modifying ion sub-network” [J. Chem. Phys. 140, 154501 (2014)]

In a recent paper, Hermansen, Mauro, and Yue [J. Chem. Phys. 140, 154501 (2014)] applied the temperature-dependent constraint theory to model both the glass transition temperature, T{sub g}, and fragility, m, of a series of binary alkali phosphate glasses of the form (R{sub 2}O){sub x}(P{sub 2}O{sub 5}){sub 1−x}, where R represents an alkali species. Key to their success seems to be the retention of linear constraints between the alkali ion (R{sup +}) and the non-bridging oxygens near T{sub g}, which allows the model to mimic a supposed minimum for both T{sub g}(x) and m(x) located near x = 0.2. However, the authors have overlooked several recent studies that clearly show there is no minimum in m(x). We argue that the retention of the alkali ion constraints at these temperatures is unjustified and question whether the model calculations can be revised to meet the actual experimental data. We also discuss alternative interpretations for the fragility based on two-state thermodynamics that can accurately account for its compositional dependence.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Correlations of the Elemental Compositions of Primary Coal Tar and Char

We report that simulations of large-scale coal combustors rely on accurate submodels to describe the chemical and physical changes in coal during reaction. Typically, researchers use simplified empirical submodels tuned to experimental data to reduce the computational complexity. When data are not readily available, researchers use simplifying assumptions, which can create inaccuracies and biases in a large simulation. One such simplifying assumption in coal research is how to describe the elemental composition of primary pyrolysis products. This paper explores several different empirical model forms to predict the dry, ash-free fractions of C, H, O, N, and S in both the char and the tar, using variables such as parent coal composition, reaction conditions (temperatures and particle residence times), and key coal structural parameters derived from NMR measurements. These model forms were correlated to existing data using a wide range of experimental data using a cross-validation procedure. Since coal structural values can be expensive to measure, several correlations from the literature were used to estimate these values based on information from the proximate and ultimate analyses of the parent coal, including a new correlation for the coal aromaticity. These model forms were tested against a set of measured elemental compositions of tar and char to find the best fit to use in the cross-validation process. Lastly, the best empirical models are presented that predict elemental composition of the coal char and tar after devolatilization.

01 COAL, LIGNITE, AND PEAT↗