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At least 883 records · Page 49

Novel Relativistic Electronic Structure Theories for Actinide-Containing Compounds

Actinides of importance to basic energy sciences contain electrons moving at speed comparable to the speed of light. Reliable computational simulation of these electrons and hence actinide chemistry requires accurate description of relativistic effects. The present project advances computational actinide chemistry with development of new methodologies, algorithms, and computer programs in relativistic quantum chemistry, as well as applications to actinide chemistry and spectroscopy. A new “electrons-only” exact two-component approach has been developed to provide efficient treatments of relativistic effects, while maintaining chemical accuracy. New computational algorithms developed here extend the applicability of relativistic electron-correlation methods to larger molecules. The method-development work in this project also features the first implementation of analytic gradient technique for relativistic electron-correlation methods, which provides significantly enhanced ability to compute properties for molecules containing actinides. The applicability and usefulness of these new methods and computer programs have been demonstrated in calculations of actinide-containing molecules to facilitate understanding of actinide chemistry and spectroscopy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Determination of Water Content in Bio-Oils by Volumetric Karl Fischer Titration: Laboratory Analytical Procedure (LAP)

The water content of bio-oils is a key metric for several reasons. Water is typically the most concentrated single component of fast pyrolysis oils, though this will be much lower in catalytic fast pyrolysis and upgraded products. Reduced water content is preferable in bio-oil as water can contribute to phase separation, corrosivity, and instability. Additionally, lower water is beneficial for physical properties such as energy density. The percentage of water can also be used to correct the calculation for organic oxygen when determining total oxygen content of bio-oils via combustion-based ultimate analysis. The procedure described here is specifically written for the analysis of bio-oils, and is based on ASTM E203, Standard Test Method for Water Using Volumetric Karl Fischer Titration. This standard test method is specified for measuring the mass % water in pyrolysis liquid biofuels in ASTM D7544, Standard Specification for Pyrolysis Liquid Biofuel. Although the standard method is prescribed for the analysis of pyrolysis liquids for use in industrial and commercial burners, the method is not specifically written for this product. The method described with this Laboratory Analytical Procedure (LAP) provides specific guidance for the analysis of bio-oils. Both organic and aqueous phases can be measured with this technique.

09 BIOMASS FUELS↗

Analysis of Ionic Mercury Species in SRR Samples Measured by SRNL and Eurofins FGS

Savannah River Remediation (SRR) requested the development of mercury speciation capabilities at the Savannah River National Laboratory (SRNL) to support the Liquid Waste Operations at SRS. As part of that method development, SRR requested that SRNL Analytical Development (AD) compare their results with those obtained from their outside contract laboratory, Eurofins Frontier Global Sciences (FGS). This document reports on this method development work performed at SRNL as well as the comparative analyses conducted between the two laboratories. Development, optimization, and validation were undertaken at SRNL to produce a method for the species-specific analysis of ionic mercury. This method was developed as a secondary step to an existing method, L16.1-ADS-1579 Purgeable Mercury Cold Vapor Atomic Fluorescence Spectrophotometry. As such, much of the development and validation were performed in service of development of L16.1-ADS-1579. Six samples, representing two consecutive quarterly Tank 50 batches, were tested for ionic mercury by SRNL-AD and Eurofins FGS. The mean values reported by each lab for ionic mercury differed by less than one standard deviation, therefore the values reported by both labs were considered to be in agreement. SRNL-AD reported values for the six samples that differed by -5.56 mean percent, relative to Eurofins FGS. Together with comparable quality control data reported by each laboratory, these data represent a high level of agreement among both laboratories. With a viable method for ionic mercury that matches the data quality provided by outside commercial laboratories, SRNL-AD has demonstrated competency in measuring methylmercury, ethylmercury, total mercury, soluble & particulate mercury, purgeable mercury, and ionic mercury species in a variety of radioactive tank samples.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Analytic model of electron transport through and over non-linear barriers

Tunneling barriers are an essential component of electron sources, sensors, detectors, and vacuum nanoelectronics, and a pivotal factor in their performance, but the barriers themselves routinely depart from the analytic models used to model their behavior. Here, a new formalism is developed to analytically and accurately model emission through and over barriers associated with depletion layers, nanotip barriers, and MIM structures. The transmission probability for depletion layer and metal-insulator-metal (MIM) and metaloxide-semiconductor (MOS) barriers is accurately modeled as the electron energy exceeds the barrier height using approaches designed for rapid implementation demanded by simulation codes, and extensible to general barriers. The models supersede conventional thermal and field models in depletion and MIM/MOS barrier studies. Thermal-field methods are used to treat the transmission probability, and shape factor methods to treat the tunneling factor. Analytic formulae for current density are obtained. The methods ease device simulation and characterization of current-voltage relations for emerging technologically interesting barriers with better accuracy.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The ellipticity parameterization for an NFW profile: An overlooked angular structure in strong lens modeling

Galaxy-scale gravitational lenses are often modeled with two-component mass profiles where one component represents the stellar mass and the second is a Navarro Frenk White (NFW) profile representing the dark matter. Outside of the spherical case, the NFW profile is costly to implement, and so it is approximated via two different methods; ellipticity can be introduced via the lensing potential (NFWp) or via the mass by approximating the NFW profile as a sum of analytical profiles (NFWm). While the NFWp method has been the default for lensing applications, it gives a different prescription of the azimuthal structure, which we show introduces ubiquitous gradients in ellipticity and boxiness in the mass distribution rather than having a constant elliptical shape. Because an unmodeled azimuthal structure has been shown to be able to bias lens model results, we explored the degree to which this azimuthal structure that was introduced can affect the model accuracy. We constructed input profiles using composite models using both the NFWp and NFWm methods and fit these mocks with a power-law elliptical mass distribution (PEMD) model with external shear. As a measure of the accuracy of the recovered lensing potential, we calculated the value of the Hubble parameter H 0 one would determine from the lensing fit. We found that the fits to the NFWp input return H 0 values that are systematically biased by about 3% lower than the NFWm counterparts. We explored whether such an effect is attributable to the mass sheet transformation (MST) by using an MST-independent quantity, ξ 2 . We show that, as expected, the NFWm mocks are degenerate with PEMD through an MST. For the NFWp, an additional bias was found beyond the MST due to the azimuthal structure exterior to the Einstein radius. We recommend modelers use an NFWm prescription in the future, such that the azimuthal structure can be introduced explicitly rather than implicitly.

79 ASTRONOMY AND ASTROPHYSICS↗

Applications of Alternate Actinide Calibration on Inductively Coupled Plasma Mass Spectrometry (ICPMS) Analysis of H-Canyon Highly Enriched Uranium Legacy Material at the Savannah River Site (SRS)

The Savannah River National Laboratory (SRNL) uses Inductively Coupled Plasma Mass Spectrometry (ICPMS) to support numerous programs at the Savannah River Site (SRS). As part of an objective to prepare high assay low enriched uranium (HALEU), the SRS H-Canyon needed analysis of legacy uranyl nitrate that is stored at its Outside Facilities (HOF). With the application of a standard practice for alternate actinide calibration on ICP-MS, SRNL has successfully demonstrated its capability to characterize the uranium/actinide composition of the HOF tanks that are intended for consolidation prior to preparation of the HALEU. A comparison of the uranium analytical results between recently upgraded SRNL ICP-MS and Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES) instrumentation shows the alternate actinide calibration is a valid complementary method when used in conjunction with other analytical techniques (Davies-Gray Potentiometric Titration). The methods, instrumentation, and ongoing developments on ICP-MS at SRNL will be discussed.

Jones, Mark A.↗

Raman Spectroscopy Coupled with Chemometric Analysis for Speciation and Quantitative Analysis of Aqueous Phosphoric Acid Systems

Complex chemical systems that exhibit varied and matrix-dependent speciation are notoriously difficult to monitor and characterize on-line and in real-time. Optical spectroscopy is an ideal tool for in situ characterization of chemical species that can enable quantification as well as species identification. Chemometric modeling, a multivariate method, has been successfully paired with optical spectroscopy to enable measurement of analyte concentrations even in complex solutions where univariate methods such as Beer’s law analysis fail. Here, Raman spectroscopy is used to quantify the concentration of phosphoric acid and its three deprotonated forms during a titration. In this system, univariate approaches would be difficult to apply due to multiple species being present simultaneously within the solution as pH is varied. Locally Weighted Regression (LWR) modeling was used to determine phosphate concentration from spectral signature. LWR results, in tandem with Multivariate Curve Resolution modeling, provide direct measurement of the concentration of each phosphate species using only the Raman signal. Furthermore, results are presented within the context of fundamental solution chemistry, including Pitzer equations to compensate for activity coefficients and non-idealities associated with high ionic strength systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

SQMBox: Interfacing a semiempirical integral library to modular ab initio electronic structure enables new semiempirical methods

Ab initio and semiempirical electronic structure methods are usually implemented in separate software packages or use entirely different code paths. As a result, it can be time-consuming to transfer an established ab initio electronic structure scheme to a semiempirical Hamiltonian. Here we present an approach to unify ab initio and semiempirical electronic structure code paths based on a separation of the wavefunction ansatz and the needed matrix representations of operators. With this separation, the Hamiltonian can refer to either an ab initio or semiempirical treatment of the resulting integrals. We built a semiempirical integral library and interfaced it to the GPU-accelerated electronic structure code TeraChem. Equivalency between ab initio and semiempirical tight-binding Hamiltonian terms is assigned according to their dependence on the one-electron density matrix. The new library provides semiempirical equivalents of the Hamiltonian matrix and gradient intermediates, corresponding to those provided by the ab initio integral library. This enables the straightforward combination of semiempirical Hamiltonians with the full pre-existing ground and excited state functionality of the ab initio electronic structure code. We demonstrate the capability of this approach by combining the extended tight-binding method GFN1-xTB with both spin-restricted ensemble-referenced Kohn–Sham and complete active space methods. We also present a highly efficient GPU implementation of the semiempirical Mulliken-approximated Fock exchange. The additional computational cost for this term becomes negligible even on consumer-grade GPUs, enabling Mulliken-approximated exchange in tight-binding methods for essentially no additional cost.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Decomposition of multi-particle azimuthal correlations in Q-cumulant analysis*

Abstract The method of Q -cumulants is a powerful tool for studying the fine details of azimuthal anisotropies in high energy nuclear collisions. This paper presents a new method, based on mathematical induction, to evaluate the analytical form of high-order Q -cumulants. The capability of this method is demonstrated via a toy model that uses the elliptic power distribution to simulate the anisotropic emission of particles, quantified in terms of Fourier flow harmonics . The method can help in studying the large amount of event statistics that can be collected in the future and allow measurements of the very high central moments of the distribution. This can, in turn, facilitate progress in understanding the initial geometry, the input to the hydrodynamic calculations of medium expansion in high energy nuclear collisions, and the constraints on it.

Physics↗

Systematic characterization of unknown compounds via dimensionality reduction of time series

Analysis of ambient aerosols provides valuable insight into particle sources and formation chemistry. However, due to the complexity of atmospheric data and the dynamic nature of aerosol composition, a substantial fraction of data often become discarded by conventional analysis methods. Furthermore, a large fraction of chemical species within those data are unidentifiable due to a lack of matching spectral information, resulting in suboptimal characterization of chemical composition. Previous work has demonstrated techniques for cataloging analytes in a chromatographic dataset by deconvolution of mass spectra, but integration of these analytes throughout a large dataset remains time consuming. Here, we present a method to automatically identify an ion for quantitation for single-ion chromatogram based peak fitting and integration, enabling comprehensive integration of analytes with minimal user interaction. The resulting time series are clustered with a machine-learning based dimensionality reduction technique to systematically investigate the underlying characteristics of the categorized analytes and gain new insights into the chemical composition and physicochemical properties of the unidentifiable analytes. We apply these methods to existing atmospheric datasets collected in Manacapuru, Brazil during the GoAmazon2014/5 campaign to identify new analytes and interpret their variability and transformations in the atmosphere. The analysis results generate 408 time series from cataloged analytes of interest, and the clustering of those time series with spherical k-means results in 8 distinct clusters. We find the analytes form clusters based on their distinct physicochemical properties, demonstrating the method’s ability to systematically identify and selectively filter contaminants and instrumental analytes and characterize the unidentifiable analytes.

54 ENVIRONMENTAL SCIENCES↗

A Review of Biodegradable Plastics: Chemistry, Applications, Properties, and Future Research Needs

Environmental concerns over waste plastics’ effect on the environment are leading to the creation of biodegradable plastics. Biodegradable plastics may serve as a promising approach to manage the issue of environmental accumulation of plastic waste in the ocean and soil. Biodegradable plastics are the type of polymers that can be degraded by microorganisms into small molecules (e.g., H 2 O, CO 2 , and CH 4 ). However, there are misconceptions surrounding biodegradable plastics. For example, the term “biodegradable” on product labeling can be misconstrued by the public to imply that the product will degrade under any environmental conditions. Such misleading information leads to consumer encouragement of excessive consumption of certain goods and increased littering of products labeled as “biodegradable”. Here this review not only provides a comprehensive overview of the state-of-the-art biodegradable plastics but also clarifies the definitions and various terms associated with biodegradable plastics, including oxo-degradable plastics, enzyme-mediated plastics, and biodegradation agents. Analytical techniques and standard test methods to evaluate the biodegradability of polymeric materials in alignment with international standards are summarized. The review summarizes the properties and industrial applications of previously developed biodegradable plastics and then discusses how biomass-derived monomers can create new types of biodegradable polymers by utilizing their unique chemical properties from oxygen-containing functional groups. The terminology and methodologies covered in the paper provide a perspective on directions for the design of new biodegradable polymers that possess not only advanced performance for practical applications but also environmental benefits.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Rapid dissolution of PuO 2 analytical samples using mediated electrochemical oxidation

Current methods for quantitative dissolution of solid PuO 2 involve lengthy dissolution times. The adaptation of mediated electrochemical oxidation, which uses an electrochemically produced oxidizing agent to catalyze dissolution, has been explored for radiochemical analysis scale dissolutions of PuO 2 . The effects of temperature, electrode material, and electrocatalyst on the dissolution kinetics were explored. Under conditions examined in this study, complete dissolution of tens of milligrams of solid PuO 2 can be achieved in less than 1 h at ambient temperature. Overall, this methodology could be adapted to dissolve other metal oxides.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Estimating soil N 2 O emissions induced by organic and inorganic fertilizer inputs using a Tier-2, regression-based meta-analytic approach for U.S. agricultural lands

Consistent methods are essential for generating country and region-specific estimates of greenhouse gas (GHG) emissions used for reporting and policymaking. The estimates of direct N 2 O emissions from U.S. agricultural soils have primarily relied on the use of emission factors (EFs, Tier-1) and process-based models (Tier-3). However, Tier-1 estimates are relatively crude while Tier-3 calculations can be costly. This work addressed this gap by developing a Tier-2, regression-based approach by leveraging a meta-database containing 1883 field N 2 O observations together with environmental and management covariates from 139 studies. Our results estimated higher monthly soil N 2 O emissions (N 2 O m , kg N/ha) during the growing season (0.38) than the fallow period (0.15), highlighting the importance of considering measurement periods when utilizing meta-databases for analyzing N 2 O drivers. Significantly different N 2 O m were found for tillage practices (conventional > no-till: 0.42 > 0.27), fertilizer type (liquid > solid manure: 0.55 > 0.32), and soil texture (fine > coarse: 0.36 > 0.22). The comparisons of the influence of crop type and rotation, water management, and soil order on N 2 O emissions are complicated by regional data availability and interactions among different factors. Additionally, the finding that N 2 O emissions reported based on area (N 2 O m ), N input rate (EF), or yield can alter treatment rankings underscores the need to establish transparent criteria for rewarding or discouraging regionally-based management practices using N 2 O metrics. Finally, we show how General Linear Models (GLMs) can be used to estimate country and regional Tier-2 N 2 O m using a suite of covariates. Our GLMs identified tillage, water management, N input type and rate, soil properties, and elevation as the most influential covariates for the conterminous U.S. The limited accuracy of regional-scale GLMs, however, suggests the need to further improve the quality and availability of GHG and covariate data through concerted efforts in data collection.

54 ENVIRONMENTAL SCIENCES↗

Exaflops Biomedical Knowledge Graph Analytics

We are motivated by newly proposed methods for mining large-scale corpora of scholarly publications (e.g., full biomedical literature), which consists of tens of millions of papers spanning decades of research. In this setting, analysts seek to discover relationships among concepts. They construct graph representations from annotated text databases and then formulate the relationship-mining problem as an all-pairs shortest paths (APSP) and validate connective paths against curated biomedical knowledge graphs (e.g., Spoke). In this context, we present Coast (Exascale Communication-Optimized All-Pairs Shortest Path) and demonstrate 1.004 EF/s on 9,200 Frontier nodes (73,600 GCDs). We develop hyperbolic performance models (HYPERMOD), which guide optimizations and parametric tuning. The proposed Coast algorithm achieved the memory constant parallel efficiency of 99% in the single-precision tropical semiring. Looking forward, Coast will enable the integration of scholarly corpora like PubMed into the Spoke biomedical knowledge graph.

Kannan, Ramakrishnan {ramki}↗

Monitoring the Caustic Dissolution of Aluminum Alloy in a Radiochemical Hot Cell Using Raman Spectroscopy

Chemical processing of highly radioactive materials commonly takes place in heavily shielded hot cells. The remote, real-time monitoring of chemical processing streams via optical spectroscopic techniques in hot cells may be particularly useful. Here in this paper, we describe the implementation of Raman spectroscopy and chemometric analysis to monitor the dissolution of aluminum-clad targets containing irradiated aluminum–neptunium oxide cermet pellets in caustic solutions in a hot cell environment. Partial least squares regression analysis was used to generate calibration models to quantify the concentration of dissolved aluminum, nitrate, and hydroxide in solutions within the radiochemical hot cell. This work explored a systematic approach to optimize a matrix of calibration standards using a D-optimal experimental design. The Design of Experiments-based regression model, in comparison to more traditional analytical approaches, was found to be the more practical method for building calibration models, with fewer samples, to obtain informative analytical data from Raman spectra.

36 MATERIALS SCIENCE↗

Biomimetic virus-based colorimetric sensors

The present invention provides, inter alia, a device comprising a colorimetric detection layer configured to undergo a color change upon interaction with a first analyte of interest. The detection layer comprises a first plurality of self-assembled fiber bundles. At least a fraction of the fiber bundles undergo a change from a first conformation to a second conformation upon interaction with the first analyte of interest, thereby undergoing a color change. The invention also provides a method for using the system to detect an analyte of interest.

36 MATERIALS SCIENCE↗

Biomimetic virus-based colorimetric sensors

The present invention provides, inter alia, a device comprising a colorimetric detection layer configured to undergo a color change upon interaction with a first analyte of interest. The detection layer comprises a first plurality of self-assembled fiber bundles. At least a fraction of the fiber bundles undergo a change from a first conformation to a second conformation upon interaction with the first analyte of interest, thereby undergoing a color change. The invention also provides a method for using the system to detect an analyte of interest.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Model‐Based Approach to Selecting Pegfilgrastim Dose for Pharmacokinetic and Pharmacodynamic Similarity Studies in Biosimilar Development

This study applied modeling and simulation (M&S) approaches to evaluate the sensitivity of pegfilgrastim pharmacokinetics (PKs) and pharmacodynamics (PDs) to changes in dose amount, and linear or nonlinear clearance (CL) over pegfilgrastim subcutaneous dose of 2–6 mg. A previously published model was adapted to better describe pegfilgrastim PK and PD data in healthy subjects and used in simulation. Nonlinear CL accounts for 98% and 77%, respectively, of the total CL of pegfilgrastim at 2 and 6 mg. The sensitivity analyses showed: (i) PK of 2 and 6 mg doses are similarly sensitive to detect differences for a 5% change in dose; (ii) PK of 2 mg dose is more sensitive to changes in receptor binding affinity, a model parameter for nonlinear CL, and a product quality attribute characterized with orthogonal methods as part of demonstrating analytical similarity between products; (iii) PK of approved 6 mg dose is more sensitive to changes in linear CL, which has not been associated with any specific product quality attributes, and (iv) the PDs are not sensitive to changes in linear or nonlinear CL. Taken together, our analyses support that the approved pegfilgrastim dose of 6 mg is appropriate for detecting differences between a biosimilar and the reference products in pegfilgrastim PK and PD similarity studies. The described M&S approaches can be adopted to support dose selection for biosimilars with nonlinear PK and complex PK–PD interplay.

Pharmacology & Pharmacy↗