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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Quantification of Organic Porosity and Water Accessibility in Marcellus Shale Using Neutron Scattering

Pores within organic matter (OM) are a significant contributor to the total pore system in gas shales. These pores contribute most of the storage capacity in gas shales. Here we present a novel approach to characterize the OM pore structure (including the porosity, specific surface area, pore size distribution, and water accessibility) in Marcellus shale. By using ultrasmall and small-angle neutron scattering, and by exploiting the contrast matching of the shale matrix with suitable mixtures of deuterated and protonated water, both total and water-accessible porosity were measured on centimeter-sized samples from two boreholes from the nanometer to micrometer scale with good statistical coverage. Samples were also measured after combustion at 450 °C. Analysis of scattering data from these procedures allowed quantification of OM porosity and water accessibility. OM hosts 24–47% of the total porosity for both organic-rich and -poor samples. This porosity occupies as much as 29% of the OM volume. In contrast to the current paradigm in the literature that OM porosity is organophilic and therefore not likely to contain water, our results demonstrate that OM pores with widths >20 nm exhibit the characteristics of water accessibility. In conclusion, our approach reveals the complex structure and wetting behavior of the OM porosity at scales that are hard to interrogate using other techniques.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Derivation of Multiple Covarying Material and Process Parameters Using Physics-Based Modeling of X-ray Data

There is considerable interest in developing multimodal characterization frameworks capable of probing critical properties of complex materials by relying on distinct, complementary methods or tools. Any such framework should maximize the amount of information that is extracted from any given experiment and should be sufficiently powerful and efficient to enable on-the-fly analysis of multiple measurements in a self-consistent manner. Such a framework is demonstrated in this work in the context of self-assembling polymeric materials, where theory and simulations provide the language to seamlessly mesh experimental data from two different scattering measurements. Specifically, the samples considered here consist of diblock copolymers (BCP) that are self-assembled on chemically nanopatterned surfaces. The copolymers microphase separate into ordered lamellae with characteristic dimensions on the scale of tens of nanometers that are perfectly aligned by the substrate over macroscopic areas. These aligned lamellar samples provide ideal standards with which to develop the formalism introduced in this work and, more generally, the concept of high-information-content, multimodal experimentation. In conclusion, the outcomes of the proposed analysis are then compared to images generated by 3D scanning electron microscopy tomography, serving to validate the merit of the framework and ideas proposed here.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Atomic Resolution Cryogenic 4D-STEM Imaging via Robust Distortion Correction

Cryogenic four-dimensional scanning transmission electron microscopy (4D-STEM) imaging is a useful technique for studying quantum materials and their interfaces by simultaneously probing charge, lattice, spin, and chemistry on the atomic scale with the sample held at temperatures ranging from room to cryogenic. However, its applications are currently limited by the instabilities of cryo-stages and electronics. To overcome this challenge, we develop an algorithm to effectively correct the complex distortions present in atomic resolution cryogenic 4D-STEM data sets. This method uses nonrigid registration to identify localized distortions in a 4D-STEM and relate them to an undistorted experimental STEM image, followed by a series of affine transformations for distortion corrections. This method allows a minimum loss of information in both reciprocal and real spaces, enabling the reconstruction of sample information from 4D-STEM data sets. This method is computationally cheap, fast, and applicable for on-the-fly data analysis in future in situ cryogenic 4D-STEM experiments.

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

One-step lignocellulose depolymerization and saccharification to high sugar yield and less condensed isolated lignin

The cost of sugar production remains a key challenge in future lignocellulosic biorefineries. We demonstrate that ZnBr 2 , an inexpensive inorganic salt, provides nearly theoretical yields of glucose and xylose in one-step from poplar wood at 85 °C and short reaction times at molten salt hydrate (MSH) conditions without an acid. Catalytic depolymerization of the isolated MSH lignin, using a CoS 2 catalyst, yields 17% phenol-like monomers compared to only 1% produced from the acidified MSH lignin. Reductive catalytic fractionation of MSH lignin over Ru/C resulted in two times higher total monomer yield compared to the AMSH lignin. Both the lignin samples were characterized using 2D HSQC NMR and the thioacidolysis method. Thioacidolysis studies reveal 8.4% and 1.8% of β-O-4 linkages in MSH and acidified MSH lignin, respectively. Thermodynamic modeling and 13 C NMR spectroscopy indicate that the effectiveness of this catalyst arises from the strong interaction of the Lewis acidic zinc cation (Zn 2+ ) with the coordinated water molecules resulting in hydrolysis of the metal aquo complex and to the salt-driven increase in the H + activity coefficient. Techno-economic analysis demonstrates that despite being slower, the ZnBr 2 MSH media has cost advantages, compared to conventional hydrolysis and even to the LiBr and ZnBr 2 AMSH, due to the higher quality of lignin.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

PageRank as a Collective Variable to Study Complex Chemical Transformations and Their Energy Landscapes

A reduced set of reaction coordinates are often employed in chemistry to describe the collective change between reactants and products within the context of rare event theories and in the exploration of energy landscapes. While incredibly powerful, use of these collective variables becomes increasingly challenging as the systems under study become more complex. Recent advancement of new descriptions of collective molecular coordinates have included PageRank (PR) analysis of the network of interactions about molecules and atoms within a system. Herein, PR is developed as a continuous variable that not only captures chemical transformations but can also be employed as a collective variable for a process that could span a highly dimensional energy surface. The derivatives of PR with respect to atomic coordinates are presented, and subsequently combined with forces during a chemical transformation within biased molecular dynamics sampling simulations to create the potential of mean force (PMF). This technique is demonstrated for two reactions: 1) the transformation of tetrahedral [Al(OH)4]-(aq) to octahedral [Al(OH)4(H2O)2]-(aq), and 2) the formation of contact ion pairs (CIPs) and solvent separated ion pairs (SSIPs) of Na+ and OH- in bulk water. Comparison of the behavior of the PR collective variable in both examples reveals that the ability of the PR to resolve local versus extended configurational attributes is tuned by the size of the network employed. This is a unique feature of PageRank that enables control over the resolution of the PMF that is produced.

chemistry, theories, PageRank↗
DOE OSTI2024

Identification of Distorted Gamma-Ray Signature Patterns Using Digital Filtering and Auto-Associative Memory Implemented with a Hopfield Neural Network

The detection and identification of radioactive sources in search applications involve analyzing passive gamma-ray emissions from high-level radioactive materials. This process uses a mobile detector-spectrometer in a complex field test environment. Recently, the use of artificial intelligence for gamma-ray spectrum analysis has shown promising results. However, challenges persist in identifying isotopic signatures from spectral measurements that may be distorted due to source shielding, random variations in natural radioactive background, or insufficient measurement time to obtain clear spectral lines. Here, this paper presents a novel intelligent signature recognition method that combines digital filtering techniques with an artificial Hopfield Neural Network (HNN). The HNN leverages auto-associative memory to store training sample patterns and match them with incoming gamma spectra from distorted sources. It restores the testing sources’ measurements by finding the closest matching signature patterns in the spectral library. Before HNN recognition, the measured spectrum undergoes preprocessing with a digital image filter to reduce fluctuations. Performance of the proposed method is evaluated using a set of gamma-ray spectra measured with a sodium iodide detector. The data collected include measurements from six pure samples: 241 Am, 60 Co, 137 Cs, 192 Ir, 239 Pu, and 235 U, which are used for training and validation (i.e. six cases). Additionally, the data set contains 24 distorted synthesized sources with various fluctuating backgrounds. Test results demonstrate the potential of the proposed method to accurately recognize the correct isotope with high precision, achieving an accuracy rate exceeding 85%. Furthermore, the proposed method exhibits superior performance compared to the conventional multiple regression fitting and simple feedforward neural network methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

The cosmology dependence of galaxy clustering and lensing from a hybrid N -body–perturbation theory model

ABSTRACT We implement a model for the two-point statistics of biased tracers that combines dark matter dynamics from N-body simulations with an analytic Lagrangian bias expansion. Using Aemulus, a suite of N-body simulations built for emulation of cosmological observables, we emulate the cosmology dependence of these non-linear spectra from redshifts z = 0 to z = 2. We quantify the accuracy of our emulation procedure, which is sub-per cent at $k=1\, h \,{\rm Mpc}^{-1}$ for the redshifts probed by upcoming surveys and improves at higher redshifts. We demonstrate its ability to describe the statistics of complex tracer samples, including those with assembly bias and baryonic effects, reliably fitting the clustering and lensing statistics of such samples at redshift z ≃ 0.4 to scales of $k_{\rm max} \approx 0.6\, h\,\mathrm{Mpc}^{-1}$. We show that the emulator can be used for unbiased cosmological parameter inference in simulated joint clustering and galaxy–galaxy lensing analyses with data drawn from an independent N-body simulation. These results indicate that our emulator is a promising tool that can be readily applied to the analysis of current and upcoming data sets from galaxy surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

The microbially mediated soil organic carbon loss under degenerative succession in an alpine meadow

Land-cover change has long been recognized as having marked effect on the amount of soil organic carbon (SOC). However, the microbially mediated processes and mechanisms on SOC are still unclear. In this study, the soil samples in a degenerative succession from alpine meadow to alpine steppe meadow in the Qinghai–Tibetan Plateau were analysed using high-throughput technologies, including Illumina sequencing and geochip functional gene arrays. The soil microbial community structure and diversity were significantly (p <.05) different between alpine meadow and alpine steppe meadow; the microbial α-diversity in alpine steppe meadow was significantly (p <.01) higher than in alpine meadow. Molecular ecological network analysis indicated that the microbial community structure in alpine steppe meadow was more complex and tighter than in the alpine meadow. Here, the relative abundance of soil microbial labile carbon degradation genes (e.g., pectin and hemicellulose) was significantly higher in alpine steppe meadow than in alpine meadow, but the relative abundance of soil recalcitrant carbon degradation genes (e.g., chitin and lignin) showed the opposite tendency. The Biolog Ecoplate experiment showed that microbially mediated soil carbon utilization was more active in alpine steppe meadow than in alpine meadow. Consequently, more soil labile carbon might be decomposed in alpine steppe meadow than in alpine meadow. Therefore, the degenerative succession of alpine meadow because of climate change or anthropogenic activities would most likely decrease SOC and nutrients medicated by changing soil microbial community structure and their functional potentials for carbon decomposition.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Sulfide Generation by Dominant Halanaerobium Microorganisms in Hydraulically Fractured Shales

ABSTRACT Hydraulic fracturing of black shale formations has greatly increased United States oil and natural gas recovery. However, the accumulation of biomass in subsurface reservoirs and pipelines is detrimental because of possible well souring, microbially induced corrosion, and pore clogging. Temporal sampling of produced fluids from a well in the Utica Shale revealed the dominance of Halanaerobium strains within the in situ microbial community and the potential for these microorganisms to catalyze thiosulfate-dependent sulfidogenesis. From these field data, we investigated biogenic sulfide production catalyzed by a Halanaerobium strain isolated from the produced fluids using proteogenomics and laboratory growth experiments. Analysis of Halanaerobium isolate genomes and reconstructed genomes from metagenomic data sets revealed the conserved presence of rhodanese-like proteins and anaerobic sulfite reductase complexes capable of converting thiosulfate to sulfide. Shotgun proteomics measurements using a Halanaerobium isolate verified that these proteins were more abundant when thiosulfate was present in the growth medium, and culture-based assays identified thiosulfate-dependent sulfide production by the same isolate. Increased production of sulfide and organic acids during the stationary growth phase suggests that fermentative Halanaerobium uses thiosulfate to remove excess reductant. These findings emphasize the potential detrimental effects that could arise from thiosulfate-reducing microorganisms in hydraulically fractured shales, which are undetected by current industry-wide corrosion diagnostics. IMPORTANCE Although thousands of wells in deep shale formations across the United States have been hydraulically fractured for oil and gas recovery, the impact of microbial metabolism within these environments is poorly understood. Our research demonstrates that dominant microbial populations in these subsurface ecosystems contain the conserved capacity for the reduction of thiosulfate to sulfide and that this process is likely occurring in the environment. Sulfide generation (also known as “souring”) is considered deleterious in the oil and gas industry because of both toxicity issues and impacts on corrosion of the subsurface infrastructure. Critically, the capacity for sulfide generation via reduction of sulfate was not detected in our data sets. Given that current industry wellhead tests for sulfidogenesis target canonical sulfate-reducing microorganisms, these data suggest that new approaches to the detection of sulfide-producing microorganisms may be necessary.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2019

Ultra-High Resolution Elemental/Isotopic Mass Spectrometry (m/?m> 1,000,000): Coupling of the Liquid Sampling-Atmospheric Pressure Glow Discharge with an Orbitrap Mass Spectrometer for Applications in Biological Chemistry and Environmental Analysis

Many fundamental questions of astrophysics, biochemistry, and geology rely on the ability to accurately and precisely measure the mass and abundance of isotopes. Taken a step further, the capacity to perform such measurements on intact molecules provides insights into processes in diverse biological systems. Described here is the coupling of a combined atomic and molecular (CAM) ionization source, the liquid sampling-atmospheric pressure glow discharge (LS-APGD) microplasma, with a commercially available ThermoScientific Fusion Lumos mass spectrometer. Demonstrated for the first time is the ionization and isotopically-resolved fingerprinting of a long-postulated, but never mass-spectrometrically observed, bi-metallic complex Hg:Se-cysteine. Such a complex has been implicated as having a role in observations of Hg detoxification by selenoproteins/amino acids. Demonstrated as well is the ability to mass spectrometrically-resolve the geochronologically important isobaric 87Sr and 87Rb species (?m ~ 0.3 mDa, mass resolution m/?m ? 1,700,000). The mass difference in this case reflects the beta-decay of the 87Rb to the stable Sr isotope. These two demonstrations highlight what may be a significant change in bioinorganic and atomic mass spectrometry, with impact expected across a broad spectrum of the physical, biological and geological sciences.

Hoegg, Edward D.↗
DOE OSTI2019

Stochastic density functional theory

Linear-scaling implementations of density functional theory (DFT) reach their intended efficiency regime only when applied to systems having a physical size larger than the range of their Kohn–Sham density matrix (DM). This causes a problem since many types of large systems of interest have a rather broad DM range and are therefore not amenable to analysis using DFT methods. For this reason, the recently proposed stochastic DFT (sDFT), avoiding exhaustive DM evaluations, is emerging as an attractive alternative linear-scaling approach. This review develops a general formulation of sDFT in terms of a (non)orthogonal basis representation and offers an analysis of the statistical errors (SEs) involved in the calculation. Using a new Gaussian-type basis-set implementation of sDFT, applied to water clusters and silicon nanocrystals, it demonstrates and explains how the standard deviation and the bias depend on the sampling rate and the system size in various types of calculations. We also develop a basis-set embedded-fragments theory, demonstrating its utility for reducing the SEs for energy, density of states and nuclear force calculations. Finally, we discuss the algorithmic complexity of sDFT, showing it has CPU wall-time linear-scaling. Lastly, the method parallelizes well over distributed processors with good scalability and therefore may find use in the upcoming exascale computing architectures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Radiochronometric discordance in cast uranium metal: a multi-laboratory intercomparison exercise

Here, the model age of a nuclear material is crucial in nuclear forensic analysis. Uranium metals with complex production histories often exhibit discordant model ages from the 230 Th– 234 U and 231 Pa– 235 U chronometers. Recent studies involving targeted uranium metal castings have enhanced our understanding of decay product behavior during casting, aiding nuclear forensic interpretation. Building on this prior work, forensics laboratories at Atomic Weapons Establishment (AWE), Lawrence Livermore National Laboratory (LLNL), and Los Alamos National Laboratory (LANL) conducted an interlaboratory comparison to investigate spatial heterogeneity in uranium metal cast under controlled conditions. Each laboratory measured samples of a mixed feedstock and its corresponding cast product. This work furthers our understanding of discordant model ages and the use of discordance as a signature to enhance confidence in interpretations of radiochronometric data for nuclear forensics.

230Th/234U↗
DOE OSTI2026

Peridynamic modeling of cementitious materials for nuclear waste management

Radioactive and hazardous waste generated from fuel processing plants, nuclear reactors, and hospitals, requires effective management strategies. Cementitious materials are widely applied for these needs, serving as structural materials, reactive barriers, or waste forms. In these applications cracking poses a significant risk to performance, driven by inconsistent shrinkage of the components and the varying strength and permeability of their interfaces. Traditional modeling approaches face challenges in representing the complex fracture behavior of cementitious materials due to the reliance on spatial derivatives and difficulties with mesh generation. Here, to overcome these limitations, we employ peridynamics, a novel continuum mechanics formulation that uses integrals to describe mechanical equilibrium, avoiding discontinuities associated with traditional methods. Through incorporation of a bi-linear softening model and quasistatics, an experimentally validated model for Portland cement concrete samples was created. Mechanical parameters, including compressive strength and elastic modulus were validated and variation due to aggregate packing was evaluated. Additionally, sensitivity analysis of the peridynamic parameters to the bulk material properties was established. The results lay the groundwork for evaluating the impact of unique conditions of cementitious waste forms that can be assessed to improve the reliability of waste management strategies.

Aggregates↗
DOE OSTI2020

An approach for broad molecular imaging of the root-soil interface via indirect matrix-assisted laser desorption/ionization mass spectrometry

Understanding of rhizospheric processes is limited by the need for imaging complex molecular transformations at relevant spatial scales within the root soil continuum. In this work, we demonstrate a method to enable this analysis by first extracting organic compounds from the rhizosphere onto a PVDF membrane while maintaining their 2D distribution. We then image the distribution of chemical compounds using matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). This approach permitted us to visualize and identify compounds on the root surface and presumed root exudates in the rhizosphere. Within a 1.8 cm x 0.6 cm sampling area of a switchgrass rhizosphere, we could observe at least four chemically distinct zones. Using high performance Fourier transform ion cyclotron MS, we were able to accurately annotate numerous molecules co-localized to each of these zones.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Unveiling Morphology and Crystallinity Dynamics in Ni x Mn 1– x CO 3 Cathode Precursors through Batch-Mode Coprecipitation

This study delves into the synthesis and control of Ni x Mn 1–x CO 3 , a critical class of Mn-rich, Co-free precursors vital for cathode-oxide materials in energy storage and conversion technologies. Employing batch-mode coprecipitation, we systematically generated samples with varying Ni concentrations (x = 0, 0.1, 0.3, 0.5, 0.7, and 0.9) and conducted a comprehensive analysis of their compositions, crystallinities, transition-metal distributions, and particle morphologies through both experimental and computational methods. A significant variation in particle size and crystallinity was observed, contingent on the Ni content. Further, a pivotal transition emerged at Ni concentrations above x = ~0.5, transforming uniform morphologies, such as spherical, monodisperse, pseudo-single-crystalline particles, into bimodal, polycrystalline structures. Furthermore, the study highlights the role of Ni–ammonia complexes leading to Ni-deficient precipitates and underscores the importance of ammonia concentration in achieving precise Ni content control. This study unveils critical reaction conditions governing Mn-rich precursor properties that are vital for cathode-oxides, emphasizing the need for meticulous synthetic control and offering the potential for practical applications in advanced energy storage and conversion systems.

25 ENERGY STORAGE↗
DOE OSTI2020

Phase diagrams of single-layer two-dimensional transition metal dichalcogenides: Landau theory

We report single layer (SL) two-dimensional transition metal dichalcogenides (TMDs), such as MoS 2 , ReS 2 , WSe 2 , and MoTe 2 have now become the focus of intensive fundamental and applied research due to their intriguing and tunable physical properties. These materials exhibit a broad range of structural phases that can be induced via elastic strain, chemical doping, and electrostatic field effect. These transformations, in turn, can open and close the band gap of SL-TMDs, leading to metal-insulator transitions, and lead to emergence of more complex quantum phenomena. These considerations necessitate detailed understanding of the mesoscopic mechanisms of these structural phase transitions. Here we develop a Landau-type thermodynamic description of SL-TMDs on a sample of the SL-(MoS 2 ) 1-x -(ReS 2 ) x system and analyze the free energy surfaces, phase diagrams, and order parameter behavior. Our results predict the existence of multiple structural phases with two-, six- and 12-fold degenerated energy minima for in-plane and out-of-plane order parameters. This analysis suggests that out-of-plane ferroelectricity can exist in many of these phases, with the switchable polarization being proportional to the out-of-plane order parameter. We further predict that the domain walls in SL-(MoS 2 ) 1-x -(ReS 2 ) x should become conductive above a certain strain threshold.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Anomalous Behavior in the Atomic Structure of Nb$^{3}$Sn under High Pressure

In the present study, the local atomic structure of a Nb3Sn superconductor sample has been probed by X-ray absorption fine structure (XAFS) as a function of hydrostatic pressure (from ambient up to 26 GPa) using a diamond anvil cell set-up. The analysis of the Nb-K edge extended X-ray absorption fine structure (EXAFS) data was carried out combining standard multi shell structural refinement and reverse Monte Carlo method to provide detailed in situ characterization of the pressure-induced evolution of the Nb local structure in Nb3Sn. The results highlight a complex evolution of Nb chains at the local atomic scale, with a peculiar correlated displacement of Nb–Nb and Nb–Nb–Nb configurations. Such a local effect appears related to anomalies evidenced by X-ray diffraction in other superconductors belonging to the same A15 crystallographic structure.

36 MATERIALS SCIENCE↗