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At least 505 records · Page 28

Water-Oil Displacement in Shale: New Insights from a Comparative Study Integrating Imbibition Tests and Multiscale Imaging

Water-oil displacement is an important process that occurs in a shale matrix after hydraulic fracturing and in water-based enhanced oil recovery. Current understanding of this displacement process is limited because of the complicated pore structure and surface properties in shale. In this work, this process and its controlling factors are investigated through a comparative study of three shale samples that have different types of pore systems and wettability. Here, an integrated method of imbibition and multiscale imaging was applied, and a modified oleic tracer that can better represent oil flow was used in imbibition testing and micro-computed tomography (CT) imaging. Scanning electron microscope (SEM) pore characterization was then performed under high magnification with guidance from the micro-CT images showing the changes caused by oil or water imbibition. New insights were obtained on the importance of both wettability and pore size effect on oil recovery and the distribution of residual oil after water-oil displacement. Connectivity of pores with different wettability is also discussed based on 3D analysis and SEM pore characterization. Collectively, these new findings improve the understanding of the complicated process of water-oil displacement and the role of influencing factors. Important implications for improved oil recovery strategy in shale are discussed for different types of reservoir rocks. The integrated imaging and imbibition technique provides a new path for further investigation of improved oil recovery in shale.

04 OIL SHALES AND TAR SANDS↗

Small to Full Height Scale Comparisons of Cesium Ion Exchange Performance with Crystalline Silicotitanate

The U.S. Department of Energy’s (DOE) Hanford Site houses 56 million gallons of high-level radioactive waste generated from plutonium production from 1944 to 1988. The supernatant waste, currently stored in underground tanks, is intended to be vitrified following filtration and 137 Cs removal at the Hanford Waste Treatment and Immobilization Plant (WTP) Low-Activity Waste (LAW) Vitrification Facility. The WTP Pretreatment Facility will not be operational for several years. The Tank Side Cesium Removal (TSCR) system is a technology demonstration that will remove cesium from tank waste supernate to support directly feeding LAW to the vitrification facility. The 137 Cs removal is important to meet the WTP LAW contract specification and ultimately for creating a contact-handled waste form. The waste acceptance criteria (WAC) limit for the WTP LAW Facility is <3.18E-5 Ci 137 Cs per mole Na. The TSCR system is skid mounted and employs two key technologies: dead end filtration for solids removal and ion exchange (IX) for cesium removal. Filtration is necessary to protect the functionality of the IX columns. The IX process utilizes sodium form crystalline silicotitanate (CST) IX media produced by UOP Honeywell, LLC (Des Plaines, IL) under the product name IONSIV R9140-B, 18 x 50 mesh, in a lead-lag-polish column configuration. Each column contains a CST bed height of 92 inches and a volume of approximately 157 gallons of CST IX media. The full-scale TSCR operation will run at a residence time of 1.9 bed volumes (BV)/h, which results in a superficial velocity of 7.3 cm/min and a flowrate of ~5 gal/min. Column testing at small (2.5% of the full bed height), medium (12% of the full bed height), and full-height scales has been previously conducted to evaluate process variables and scale up performance of Cs exchange onto the CST. Cesium load performances from various sieve cuts at the small scale indicated that a 30-mesh sieve cut be tested to determine if it better reflects the 12% and full-height column performances at the small scale. Two process flowrates were tested in the small-column configuration with <30-mesh CST and simulant solutions. These tests were compared to full-height column tests at the same residence times to assess CST particle size effect on column scaling. Table S.1 summarizes the observed column performance determined for the two flowrates juxtaposed to the previous work with 5.6 M Na simulant at higher scales (used as benchmarks). The WAC breakthroughs between the small and full-height tests at 1.3 BV/h differed by ~59 BVs. The WAC breakthroughs for small, medium, and full-height tests at 1.8 BV/h were consistent at 240 BVs. The 50% Cs breakthroughs were nominally equivalent for all column tests. The common transition zones and onsets of Cs breakthrough at the 1.8 BV/h tests indicated that the Cs mass transfers were equivalent and thus the <30-mesh CST Cs load performance at the small scale successfully modeled that of the full-height system. It is recommended that the <30-mesh CST be used in subsequent 10-mL CST bed tests.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Update to the Finite Cloud Dose Correction Factors in MACCS

In WASH - 1400, external exposure from the finite radioactive cloud (cloudshine) is calculated by assuming that the cloud is semi-infinite, the concentration of radioactive material is uniform, and by using a correction factor to account for these approximations. This correction factor is originally based upon formulations by Healy and depends on the effective size of the plume and the distance from the plume center to the receptor. The range of the finite cloud dose correction factor table from WASH - 1400 developed using Healy formulations can be exceeded in certain situations. When the range of the table is exceeded, no extrapolation is performed; rather interpolation at the edge of the table is performed per WASH - 1400. The tabulated values of these finite cloud dose correction factors from WASH - 1400 and the interpolation at the edge of the table have been used in MACCS since its creation. An expanded table of finite cloud dose correction factors is one way to reduce the need of using interpolation at the edge of the table. The generation of an expanded finite cloud dose correction factor table for future use in MACCS is documented in this report.

54 ENVIRONMENTAL SCIENCES↗

Thermodynamic controls on the synthesis, structure and reactivity of materials for energy (Final Report)

The major objectives of this renewal proposal, now entitled “Thermodynamic Controls on the Synthesis, Structure and Reactivity of Materials for Energy,” are: (a) to advance and use unique calorimetric capabilities to determine the energetics of materials relevant to energy applications, with an emphasis on new materials, (b) to understand, in terms of both macroscopic energetics and microscopic structure and bonding, the interplay of defect chemistry, oxidation-reduction and size effects at the nanoscale in determining the properties of functional oxide materials and of new classes of non-oxide materials. Recent developments have generated great excitement in organic-inorganic hybrid materials such as the alkylammonium lead halide perovskites. Our current work has emphasized fluorite-based solid electrolytes, perovskites and lithium battery materials. The systematic trends seen enable a more holistic view of the relation of thermodynamics to materials discovery and synthesis. The proposed work more explicitly targets thermodynamic controls on metastability, energy landscapes, surface and nanoscale effects, and pathways of synthesis and decomposition. This project is leveraged by many U.S. and international collaborations that both extend the science and provide opportunities for work in a diverse global setting.

36 MATERIALS SCIENCE↗

Thermodynamic controls on the synthesis, structure and reactivity of materials for energy (Final Report)

The major objectives have been: a) to advance and use unique calorimetric capabilities to determine the energetics of oxide and other materials having possible energy applications, with an emphasis on new materials for batteries, fuel cells and solar energy conversion, b) to understand, in terms of both macroscopic energetics and microscopic structure and bonding, the interplay of defect chemistry, oxidation-reduction, and size effects at the bulk and nanoscale in determining materials properties. This project emphasizes mixed ionic-electronic conduction materials containing transition metals of variable valence, especially perovskites and lithium containing phases, with M = Mn, Fe, Co, Ni. The thermochemistry of new families of complex halide, chalcogenide, nitride and hybrid (organic-inorganic) perovskite materials were explored. The major and unique technique employed is high temperature oxide melt solution calorimetry, with careful attention given to materials synthesis and characterization. The thermochemical studies will be coupled with structural studies, especially to characterize order-disorder phenomena by in situ high temperature diffraction techniques.

14 SOLAR ENERGY↗

AlN Base Material Development for High Temperature Application [Poster]

Polar wurtzite AlN-based alloy materials have exceptional optoelectronic and charge transport properties (e.g., Al1-xGaxN in LEDs and Al1-xScxN as a promising new ferroelectric1). Other cation substitutions include Ta 3+ , Cr 3+ , Er 3+ , Yb 3+ , and small amounts of Gd 3+ , 2-6 but ionic size effects are a serious issue, and other variables affecting solubility are underexplored in this family, hampering development of new functional AlN-based alloys.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Combustion of Butyl acetate as an alternative additive to petroleum fuels

Blending petroleum fuels with oxygenates is a common approach to stem the depletion of crude oil while also mitigating the impact of their combustion on the environment. It has recently been considered that butyl acetate (BA, C6H12O2 , boiling point of 399K) could be a viable oxygenate additive to diesel fuel. The platform used to study combustion of commercial and synthesized BA was an isolated droplet burning with spherical symmetry. The experiments were carried out in a drop tower to minimize buoyant convection. Restricting motion by supporting droplets on 14 micrometer fibers eliminated forced convection. Precise control of the initial diameter was achieved by first deploying large droplets and letting them evaporate to the size of interest, here being between 0.3 mm to 0.8 mm. The experimental results show that commercial and the newly synthesized BA burned almost identically for the evolution of droplet and flame diameters. Droplets burned slower as the initial diameter was increased and soot formation was noted for the larger sizes studied due to a residence size effect. Burning in a buoyant convective field showed higher burn rates due to the convective effect and that the asymmetric flames became nearly spherical as diameter decreased. The study illustrates the significant value that the microgravity environment brings to evaluating performance of oxygenated fuels synthesized by new production methods.

Wang, Yujie↗

SPARC-X: Quantum simulations at extreme scale - reactive dynamics from first principles

We have developed the massively parallel electronic structure code SPARC-X: a computational framework for performing Kohn-Sham Density Functional Theory (DFT) calculations that can scale linearly with the number of atoms in the system, while being able to leverage petascale and emerging exascale parallel computers to study chemical phenomena at unprecedented length and time scales. SPARC-X exploits a recent breakthrough in electronic structure methodologies: systematically improvable, strictly local, orthonormal, discontinuous real-space bases that efficiently and systematically capture the local chemistry of the system. With further adaptation using new machine-learning techniques and the use of the massively parallel Spectral Quadrature (SQ) electronic structure method, the algorithmic complexity and prefactor associated with DFT calculations involving semilocal as well as hybrid functionals are dramatically reduced. Using petascale computational resources, SPARC-X enables quantum mechanical simulations at length and time scales previously accessible only by empirical approaches, e.g., 1,000,000 atoms for a few picoseconds using semilocal functionals or 1,000 atoms for a few picoseconds using hybrid functionals. Using exascale resources, the sizes and times targeted are two orders of magnitude larger. Such a capability has applications in a wide variety of chemical sciences, including reactive interfaces where large length- and/or long time-scales are needed and traditional force fields fail. This is particularly important in dynamic catalysis, where bond breaking and formation must be understood in detail. We developed, tested, and employed the SPARC-X framework to understand the photocatalytic properties of TiO 2 nanoparticles, revealing finite size effects that cannot be captured with standard model systems or functionals. This integrated development and application strategy ensures that SPARC-X remains a robust, efficient, and scalable software package for quantum simulations on current petascale and emerging exascale computing resources.

97 MATHEMATICS AND COMPUTING↗

Predictive Indicators of the Performance of Large Language Models

In several mission contexts, it is desirable to estimate the performance of large language models (LLMs) on tasks that we cannot run directly. In light of published “scaling laws” our hypothesis is that some tasks should be consistently more challenging than others based on characteristics of the task. The goal of this project was to begin quantifying how much information about LLM performance can be gained from the features of a model and a task. Two of our statistical models struggled to converge. Pass/fail test results may provide limited information for inference beyond model quality and task difficulty, but we see no evidence at this time for significant feature interaction effect sizes, arguing for simple models. Future work extending the models to capitalize on perplexity of ground truth answers is suggested. This project also introduces “Depth of Knowledge Variant Testing” as a strategy for more finely assessing language models on open domain question and answer tasks. We developed sets of questions that ask a language model to produce similar information while demonstrating increasing depth of knowledge, and also relabeled existing Q&A test questions with their depth of knowledge. Our results suggest further consideration of Bloom’s taxonomy and further refinement of prompts to properly elicit information at varying depths. In the course of this work, we set up a basic infrastructure for standardizing tasks and testing many language models on these tasks. In addition to testing the predictive quality of model features and performance across test suites, with this project we have introduced two new task features to contextualize each test question: the Dewey Classification main category of information covered, and the Bloom’s taxonomy level that corresponds to the depth of knowledge probed by the question. Splits across these and other features produced over five hundred task subtypes with distinct feature vectors, which we tested on half a dozen models.

97 MATHEMATICS AND COMPUTING↗

Radiation Response of Low Dimensional Carbon Systems

The project is aimed at understanding the fundamentals of radiation response of low dimensional carbon systems and irradiation-induced mechanical property changes, with a focus on the unique phenomena caused by their geometry, boundary, and quantum size effects. In comparison with their bulk counterparts (graphite), radiation responses of low-dimensional carbon systems are substantially different. The differences exist at almost every stage of defect development, namely, displacement creation, damage cascade, thermal spike formation defect recombination, defect clustering, and structural reconstruction. Many traditional concepts in ion-solid interaction theory do not apply at the nanoscale or require substantial modification. Through this project, we systematically studied various aspects of radiation damage development in graphene, carbon nanotubes (CNTs), and graphite.

36 MATERIALS SCIENCE↗

Enhancing Superionic Conductivity in Cluster-Based Sodium-Rich Antiperovskites

Sodium (Na) superionic conductors are the key to developing next-generation solid-state batteries with safety and low cost. However, most of the known Na-conductors exhibit limited ionic conductivities at room temperature (RT), hindering their practical applications. To meet the challenge, a series of Li- and Na-rich antiperovskite superionic conductors based on cluster ions (e.g. BH4- and BCl4-) have been theoretically developed [e.g. Fang et al. PNAS 114, 11046, 2017; ACS App. Mat. Inter. 11, 963, 2018]. These materials exhibit superior properties as solid electrolytes with greatly enhanced ionic conductivities at RT. One cluster-based solid electrolyte of such, Na3O(BH)4, has been successfully synthesized for the first time most recently and its measured RT ionic conductivity is well above 10-3 S/cm which is four orders of magnitude higher than that of its halogen counterparts Na3OX (X = Cl, Br, I) [Sun et al. J. Am. Chem. Soc. 141, 5640, 2019]. In this work, we aim to further enhance the ionic conductivity of the Na-superionic conductor by using chemical mixing according to the size effect. The study further shows the advantage of utilizing cluster ions as building blocks, introducing additional degrees of freedom into tuning the properties of superionic conductors.

Fang, Hong↗

Discovery, Design, Synthesis and Testing of High Performance Structural Alloys (Final Technical Report)

The overarching goal of this project is to understand the phase stability and mechanical behavior of non-stoichiometric multi-principal element alloy (MPEA) materials. In order to identify suitable alloys, we plan to use a combinatorial thin film screening approach, in collaboration with scientists at Lawrence Berkeley National Laboratory who are performing computational work as well as complementary experimental work. Specific tasks within the scope of this project include the fabrication, using thin film deposition from six sputtering targets, of combinatorial samples with multi-dimensional gradients in composition and microstructure. These samples are studied to screen MPEA systems for promising candidate alloys with specific composition(s), based on characterization of composition, structure and mechanical behavior across the thin film. We want to produce single-phase MPEAs with chemical homogeneity in a given thin film region, simple grain structures, and no intermetallic phases present. Gradient films facilitate first-pass screening for desirable characteristics and inform the next stage of work that involves fabrication of bulk MPEA specimens for (tensile) mechanical testing and characterization. To make the bulk alloys, metal (elemental) pieces are melted to form MPEAs, followed by heat treatment to homogenize the composition and microstructure. A subset of alloys is also cast, using vacuum arc melting, to yield larger samples (diameter ~1 cm and length ~5-10 cm) and these allow us to assess viability of scale-up for the alloys in structural applications. Further processing plans include rolling and heat treatment to recrystallize selected bulk MPEAs and grow grains to different extents, in order to investigate size effects in the mechanical behavior of MPEAs. Microspecimen testing will be performed (primarily in tension) to assess the mechanical behavior over a range of temperatures. The deformation microstructure of mechanically tested alloys will be characterized using transmission electron microscopy (TEM) to provide a scientific basis for understanding the structure-property relationships in MPEA mechanical behavior.

36 MATERIALS SCIENCE↗

Comparison of Social Media, Syndromic Surveillance, and Microbiologic Acute Respiratory Infection Data: Observational Study

Internet data can be used to improve infectious disease models. However, the representativeness and individual-level validity of internet-derived measures are largely unexplored as this requires ground truth data for study. This study sought to identify relationships between Web-based behaviors and/or conversation topics and health status using a ground truth, survey-based dataset. This study leveraged a unique dataset of self-reported surveys, microbiological laboratory tests, and social media data from the same individuals toward understanding the validity of individual-level constructs pertaining to influenza-like illness in social media data. Logistic regression models were used to identify illness in Twitter posts using user posting behaviors and topic model features extracted from users’ tweets. Of 396 original study participants, only 81 met the inclusion criteria for this study. Of these participants’ tweets, we identified only two instances that were related to health and occurred within 2 weeks (before or after) of a survey indicating symptoms. It was not possible to predict when participants reported symptoms using features derived from topic models (area under the curve [AUC]=0.51; P=.38), though it was possible using behavior features, albeit with a very small effect size (AUC=0.53; P≤.001). Individual symptoms were also generally not predictable either. The study sample and a random sample from Twitter are predictably different on held-out data (AUC=0.67; P≤.001), meaning that the content posted by people who participated in this study was predictably different from that posted by random Twitter users. Individuals in the random sample and the GoViral sample used Twitter with similar frequencies (similar @ mentions, number of tweets, and number of retweets; AUC=0.50; P=.19). To our knowledge, this is the first instance of an attempt to use a ground truth dataset to validate infectious disease observations in social media data. The lack of signal, the lack of predictability among behaviors or topics, and the demonstrated volunteer bias in the study population are important findings for the large and growing body of disease surveillance using internet-sourced data.

59 BASIC BIOLOGICAL SCIENCES↗

Dual-unitary shadow tomography

We introduce a classical shadow tomography scheme based on dual-unitary brick-wall circuits termed "dual-unitary shadow tomography" (DUST). For this we study operator spreading and Pauli weight dynamics in one-dimensional qubit systems, evolved by random two-local dual-unitary gates arranged in a brick-wall structure, ending with a final measurement layer. We do this by deriving general constraints on the Pauli weight transfer matrix and specializing to the case of dual-unitarity. We first show that dual-unitaries must have a minimal amount of entropy production. Remarkably, we find that operator spreading in these circuits have a rich structure resembling that of relativistic quantum field theories, with massless chiral excitations that can decay or fuse into each other, which we call left- or right-movers. We develop a mean-field description of the Pauli weight in terms of $\rho(x,t)$, which represents the probability of having nontrivial support at site $x$ and depth $t$ starting from a fixed weight distribution. We develop an equation of state for $\rho(x,t)$, and simulate it numerically using Monte Carlo simulations. Lastly, we demonstrate that the fast-thermalizing properties of dual-unitary circuits make them better at predicting large operators than shallow brick-wall Clifford circuits. Our results are robust to finite-size effects due to the chirality of dual-unitary brick-wall circuits.

97 MATHEMATICS AND COMPUTING↗

The microbiome structure of decomposing plant leaves in soil depends on plant species, soil pore sizes, and soil moisture content

Microbial communities are known as the primary decomposers of all the carbon accumulated in the soil. However, how important soil structure and its conventional or organic management, moisture content, and how different plant species impact this process are less understood. To answer these questions, we generated a soil microcosm with decomposing corn and soy leaves, as well as soil adjacent to the leaves, and compared it to control samples. We then used high-throughput amplicon sequencing of the ITS and 16S rDNA regions to characterize these microbiomes. Leaf microbiomes were the least diverse and the most even in terms of OTU richness and abundance compared to near soil and far soil, especially in their bacterial component. Microbial composition was significantly and primarily affected by niche (leaves vs. soil) but also by soil management type and plant species in the fungal microbiome, while moisture content and pore sizes were more important drivers for the bacterial communities. The pore size effect was significantly dependent on moisture content, but only in the organic management type. Overall, our results refine our understanding of the decomposition of carbon residues in the soil and the factors that influence it, which are key for environmental sustainability and for evaluating changes in ecosystem functions.

16S rDNA↗

Low-Energy Electron Elastic Collisions with Actinide Atoms Am, Cm, Bk, Es, No and Lr: Negative-Ion Formation

The rigorous Regge-pole method is used to investigate negative-ion formation in actinide atoms through electron elastic total cross sections (TCSs) calculation. The TCSs are found to be characterized generally by negative-ion formations, shape resonances and Ramsauer-Townsend(R-T) minima, and they exhibit both atomic and fullerene molecular behavior near the threshold. Additionally, a polarization-induced metastable cross section with a deep R-T minimum is identified near the threshold in the Am, Cm and Bk TCSs, which flips over to a shape resonance appearing very close to the threshold in the TCSs for Es, No and Lr. We attribute these new manifestations to size effects and orbital collapse significantly impacting the polarization interaction. From the TCSs unambiguous and reliable ground, metastable and excited states negative-ion binding energies (BEs) for Am−, Cm−, Bk−, Es−, No− and Lr− anions formed during the collisions are extracted and compared with existing electron affinities (EAs) of the atoms. The novelty of the Regge-pole approach is in the extraction of the negative-ion BEs from the TCSs. We conclude that the existing theoretical EAs of the actinide atoms and the recently measured EA of Th correspond to excited anionic BEs.

Msezane, Alfred Z. (ORCID:0000000212485661)↗

The 1 S 0 Pairing Gap in Neutron Matter

We report ab initio calculations of the S wave pairing gap in neutron matter calculated using realistic nuclear Hamiltonians that include two- and three-body interactions. We use a trial state, properly optimized to capture the essential pairing correlations, from which we extract ground state properties by means of auxiliary field diffusion Monte Carlo simulations. We extrapolate our results to the thermodynamic limit by studying the finite-size effects in the symmetry-restored projected Bardeen-Cooper-Schrieffer (PBCS) theory and compare our results to other ab initio studies done in the past. Our quantum Monte Carlo results for the pairing gap show a modest suppression with respect to the mean-field BCS values. These results can be connected to cold atom experiments, via the unitarity regime where fermionic superfluidity assumes a unified description, and they are important in the prediction of thermal properties and the cooling of neutron stars.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Spin Susceptibility in Neutron Matter from Quantum Monte Carlo Calculations

The spin susceptibility in pure neutron matter is computed from auxiliary field diffusion Monte Carlo calculations over a wide range of densities. The calculations are performed for different spin asymmetries, while using twist-averaged boundary conditions to reduce finite-size effects. The employed nuclear interactions include both the phenomenological Argonne AV8′ + UIX potential and local interactions that are derived from chiral effective field theory up to next-to-next-to-leading order.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗