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At least 325 records · Page 18

Minimal Impacts of Microplastics on Soil Physical Properties under Environmentally Relevant Concentrations

Agricultural soils are a major reservoir of microplastics, and concerns have arisen about the impacts of microplastics on soil properties and functioning. In this report we measured the physical properties of a silt loam in response to the incorporation of polyester fibers and polypropylene granules over a wide range of concentrations. We further elucidated the underlying mechanisms through determining the role of microplastic shape and the baseline effects from the amendment of soil particles. The incorporation of microplastics into soil tended to increase contact angle and saturated hydraulic conductivity, decrease bulk density and water holding capacity, while did not affect aggregate stability. Polyester fibers affected soil physical properties more profoundly than polypropylene granules, due to the vastly different shape of fibers from that of soil particles. However, changes in soil properties were gradual, and significant changes did not occur until a high concentration of microplastics was reached (i.e., 0.5% w/w for polyester fibers and 2% w/w for polypropylene granules). Currently, microplastic concentrations in soils not heavily polluted with plastics are far below these concentrations, and results from this study suggest that microplastics at environmentally relevant concentrations have no significant effects on soil physical properties.

54 ENVIRONMENTAL SCIENCES↗

Thiol–ene Click Chemistry Incorporates Hydroxyl Functionality on Polycyclooctene to Tune Properties

Polyolefins compose the majority of plastic waste, but conventional mechanical recycling degrades their properties, thereby reducing their value. We report the functionalization of a model for dehydrogenated polyethylene, polycyclooctene (PCOE), with thiol–ene click chemistry to install pendant hydroxyl ethyl thioethers. Functionalization of PCOE using mercaptoethanol via thiol–ene click chemistry yielded functionalization between 1.4 and 22.9% based on ethylene monomeric units. Reactions were well-controlled by varying the reagent stoichiometry and reaction time. Crystallinity and melting temperature decreased, and glass transition temperature increased with greater functionalization. Contact angle measurements reveal an increase in surface polarity with functionalization. Here, comparisons with poly(ethylene-co-vinyl alcohol) (EVOH) show comparable surface polarity at similar levels of alcohol functionalization. At 12% functionalization, the ultimate shear stress (USS) of functionalized PCOE in an adhesive configuration is 4.10 ± 0.48 MPa, comparable to EVOH. At >12% functionalization, the failure mode changed from adhesive to mixed adhesive–cohesive, and the USS decreased.

36 MATERIALS SCIENCE↗

A Bayesian analysis of nuclear deformation properties with Skyrme energy functionals

In spite of numerous scientific and practical applications, there is still no comprehensive theoretical description of the nuclear fission process based solely on protons, neutrons and their interactions. Furthermore, the most advanced simulations of fission are currently carried out within nuclear density functional theory (DFT). In spite of being fully quantum-mechanical and rooted in the theory of nuclear forces, DFT still depends on a dozen or so parameters characterizing the energy functional. Calibrating these parameters on experimental data results in uncertainties that must be quantified for applications. This task is very challenging because of the high computational cost of DFT calculations for fission. In this paper, we use Gaussian processes to build emulators of DFT models in order to quantify and propagate statistical uncertainties of theoretical predictions for a range of nuclear deformations relevant to describing the fission process.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Temperature-Dependent Molecular Diffusional Properties in Deep Eutectic Solvents and Eutectogels

Eutectogels (ETGs) prepared from deep eutectic solvents (DESs), a gelator, and water have many uses in separations, catalysis, and energy storage systems. In these applications, temperature-dependent molecular diffusional properties and intermolecular interactions play a critical role in their function. Diffusional properties of Alexa Fluor 633 and ATTO 647N were measured across a range of temperatures in choline chloride:2glycerol DESs comprised of one molar equivalent of choline chloride and two molar equivalents of glycerol (also known as glyceline) as well as ETGs made from this DES, a xanthan gum gelator, and 10% w/w water or 20% w/w water. Fluorescence recovery after photobleaching (FRAP) was employed to evaluate potential changes in molecular diffusion within DESs and ETGs from 20 to 100 °C. Surprisingly, the ETGs have a larger sample viscosity but also exhibit faster molecular diffusion when compared to the dry DES. This is attributed to macroscopic properties of the ETGs (e.g., pores, three-dimensional structure). The FRAP data also show an irreversible temperature-dependent decrease in the diffusion coefficient of both fluorophores in the ETGs. This is consistent with differential scanning calorimetry data of the ETG, which shows a shift to a more negative glass transition temperature (−36 °C to −47 °C) after the first cooling/heating cycle. Raman data reveal no detectable changes in the intermolecular interactions in either the DESs or ETGs as a function of temperature or water content. Finally, the findings on temperature- and water-dependent diffusional properties of DESs and ETGs provide a foundation for optimizing the use of these materials across various applications, particularly where repeated heating/cooling cycles may be used.

alcohols↗

Finite-range pairing in nuclear density functional theory

Pairing correlations are ubiquitous in low-energy states of atomic nuclei. To incorporate them within nuclear density functional theory, often used for global computations of nuclear properties, pairing functionals that generate nucleonic pair densities and pairing fields are introduced. Many pairing functionals currently used can be traced back to zero-range nucleon-nucleon interactions. Unfortunately, such functionals are plagued by deficiencies that become apparent in large model spaces that contain unbound single-particle (continuum) states. In particular, the underlying computational schemes diverge as the single-particle space increases, and the results depend on how marginally occupied states are incorporated. These problems become more pronounced for pairing functionals that contain gradient-density dependence, such as in the Fayans functional. To remedy this, finite-range pairing functionals are introduced. In this study, this is done by folding the pair density with Gaussians. Here, we show that a folding radius of about 1 fm offers the best compromise between quality and stability, and substantially reduces the pathological behavior in different numerical applications.

Nuclear density functional theory↗

Review of Graphite Properties Relevant to Micro-Reactor Design

Microreactors are advanced reactors that are designed to be small, scalable, and portable with up to 20 MW power. These reactors could operate independently, or as part of a microgrid, without need of a frequent refueling. Micro-reactors are designed to be deployable to provide electric power in remote locations, therefore providing greater flexibility. Several micro-reactors are under development in the US. These reactors are based on advanced gas-cooled or heat-pipe concepts. While Graphite can be found in various applications, some high-temperature reactors plan to employ Graphite in their core components due to its role as a moderator and its ability to maintain its structural integrity when subjected to elevated temperatures and high neutron fluence. Although there is significant experience with use of Graphite in nuclear applications, there are still unknowns that should be addressed. Graphite properties depend on the graphite type and affected by the fabrication procedures. Material properties are functions of the temperature and irradiation dose. The fundamental properties also affected by the oxidation environment. Therefore, in-depth understanding of graphite properties, including the effect of irradiation, oxidation and other influencing parameters are required to evaluate the design accurately. This draft aims to provide a comprehensive review of material properties for Graphite relevant to micro reactor design. For this work, two distinct grades of graphite were considered, namely IG-110 and Mersen-2114. Physical, thermal, and mechanical properties for these grades were comparatively evaluated. The properties that are discussed in this draft aim to serve as a basis for design and safety analysis.

42 ENGINEERING↗

Best practices for first-principles simulations of epitaxial inorganic interfaces

Abstract At an interface between two materials physical properties and functionalities may be achieved, which would not exist in either material alone. Epitaxial inorganic interfaces are at the heart of semiconductor, spintronic, and quantum devices. First principles simulations based on density functional theory (DFT) can help elucidate the electronic and magnetic properties of interfaces and relate them to the structure and composition at the atomistic scale. Furthermore, DFT simulations can predict the structure and properties of candidate interfaces and guide experimental efforts in promising directions. However, DFT simulations of interfaces can be technically elaborate and computationally expensive. To help researchers embarking on such simulations, this review covers best practices for first principles simulations of epitaxial inorganic interfaces, including DFT methods, interface model construction, interface structure prediction, and analysis and visualization tools.

Physics↗

Fluid Properties for MOOSE

The Multiphysics Object-Oriented Simulation Environment (MOOSE) enables a wide range of advanced nuclear reactor simulations. Under the guidance of MOOSE's Finite Volume Team, we worked on the fluid properties module. Significant contributions include enabling Tabulated Fluid Properties (TFP) for systems thermal hydraulics analysis, Temperature and Pressure functionalized Fluid Properties, and Lead & Lead-Bismuth properties. Along with improving the capabilities of the fluid properties module, we also improved the documentation to allow for future users and developers to understand how the module works.

97 MATHEMATICS AND COMPUTING↗

Uncertainty Quantification for Smooth Functional Data with Application to Material Properties

This document outlines a method for processing functional output (i.e., curves) for the ultimate purpose of sampling curves under specified input conditions for use in modeling and simulation uncertainty quantification (UQ) studies. A set of benchmark curves sufficiently representative of the relevant scenario(s) being simulated are provided to the process and formatted as described in Section 1. Principal Component Analysis (PCA) is utilized to discover the components of uncertainty in the benchmark curves and is outlined in Section 2. Section 3 describes the application of uncertainty quantification to the PCA results for the purpose of sampling curves to be used in UQ analysis. Section 4 applies these techniques to an example benchmark dataset. Concluding remarks are provided in the final section.

36 MATERIALS SCIENCE↗

A Drift‐Kinetic Method for Obtaining Gradients in Plasma Properties From Single‐Point Distribution Function Data

Abstract In this paper, we derive a new drift‐kinetic method for estimating gradients in the plasma properties through a velocity space distribution at a single point. The gradients are intrinsically related to agyrotropic features of the distribution function. This method predicts the gradients in the magnetized distribution function and can predict gradients of arbitrary moments of the gyrotropic background distribution function. The method allows for estimates on density and pressure gradients on the scale of a Larmor radius, proving to resolve smaller scales than any method currently available to spacecraft. The model is verified with a set of fully kinetic VPIC particle‐in‐cell simulations.

Wetherton, B. A.↗

Monomer-scale design of functional protein polymers using consensus repeat sequences

Protein-based polymers possess chemically defined sequences that can encode diverse properties and functions into a new class of biopolymeric materials. However, sequence variation that emerges from evolution can obscure the sequence–function relationships of naturally derived polymers. One strategy to clarify these relationships is to identify common sequences between proteins with similar functions. These conserved sequences often emerge from repeat proteins, and “consensus repeat sequences” provide a convenient platform for systematic investigations of biopolymer sequence–property relationships. In this review, we highlight recent approaches to engineer tunable polymeric materials using monomer-scale design of consensus repeat proteins. Here, we explore established and emerging protein-based materials with mechanical resilience, thermodynamic phase behavior, chemical responsiveness, biomolecular transport, and hierarchical structure. Overall, recent advances in the monomer-scale design of repetitive protein polymers present exciting fundamental and translational opportunities for polymer scientists and engineers.

36 MATERIALS SCIENCE↗

Analysis of Waste Material Feedstocks Using Laser-Induced Breakdown Spectroscopy and Machine Learning

Predicting properties such as heating value, ash fusion temperature, and mineral ash composition from Laser-Induced Breakdown Spectroscopy (LIBS) data can make gasifiers more flexible to different feedstocks. Understanding these feedstock properties in-situ improves feedstock conversion modelling methods that allow for consistent operation, higher carbon conversion, and reduced fouling and erosion rates. The purpose of this study is to demonstrate methods for model creation that take LIBS data as predictor features and estimate higher order material properties as a function of feedstock material properties. Six samples were chosen to represent a mixture of abundant and carbon rich waste materials. LIBS measurements were performed on these samples for elemental wavelengths and intensity values. Laboratory analytical results were obtained for each sample’s heating value, proximate and ultimate analysis, mineral ash composition, ash fusion temperatures, and viscosity temperatures. Thermal conductivity was measured using a HotDisk TPS 2500S. LIBS measurements were processed and used as predictor features for machine learning (ML) models to predict the sample’s material properties. Predictor feature selection algorithms, particularly minimum redundancy maximum relevance (mRMR), reduced the dimensionality of ML models. Many modelling methods such as Gaussian process regression (GPR), regression tree, neural networks (NN), and support vector machines (SVM) were demonstrated to be effective at predicting higher order properties; however, mRMR with GPR stood out as a clear winning combination.

01 COAL, LIGNITE, AND PEAT↗

Eigenstate Entanglement: Crossover from the Ground State to Volume Laws

For the typical quantum many-body systems that obey the eigenstate thermalization hypothesis (ETH), we argue that the entanglement entropy of (almost) all energy eigenstates is described by a single crossover function. The ETH implies that the crossover functions can be deduced from subsystem entropies of thermal ensembles and have universal properties. These functions capture the full crossover from the ground-state entanglement regime at low energies and small subsystem size (area or log-area law) to the extensive volume-law regime at high energies or large subsystem size. For critical one-dimensional systems, a universal scaling function follows from conformal field theory and can be adapted for nonlinear dispersions. We use it to also deduce the crossover scaling function for Fermi liquids in d > 1 dimensions. Here, the analytical results are complemented by numerics for large noninteracting systems of fermions in d ≤ 3 dimensions and have also been confirmed for bosonic systems and nonintegrable spin chains.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Mechanical and tribological properties of anodic Al coatings as a function of anodizing conditions

Enhanced wear and corrosion resistance properties are vital for numerous functional and decorative applications. Anodizing is a process frequently used to generate stable oxide coatings on metal surfaces, including aluminium (Al). In this work, we present an evaluation of process variables for optimized anodized coating properties using existing methods and as a baseline for novel coating development. A representative relatively pure Al alloy was chosen as a model system with a goal of finding conditions to achieve high wear coatings with retained ductility. AA5052 alloy coupons were anodized in two different electrolytes (sulfuric and phosphoric acid) to study the effects of anodizing conditions on the mechanical and tribological properties of the anodic coatings. Porosity was evaluated with microscopy, coating hardness was determined via nanoindentation, and tribological properties were characterized using a pin-on-disk tribometer. These measurements were correlated and a loading evaluation was performed to assess the optimum nanoindentation parameters for the use of representative coupons without the need for special processing prior to anodizing. The porosity and coating thickness were found to depend on the anodizing time and the type of electrolyte. Thicker and harder anodic coatings were generated in sulfuric acid compared to phosphoric acid. Porosity studies of the anodic coatings generated in phosphoric acid revealed that coating porosity decreased as the anodizing time increased. Both electrolytes generated anodic coatings with improved tribological properties (friction coefficient and dimensional wear rate), and an optimum processing time was identified for best wear properties.

36 MATERIALS SCIENCE↗

Memory-efficient emulation of physical tabular data using quadtree decomposition

Computationally expensive functions are sometimes replaced in simulations with an emulator that approx-imates the true function (e.g., equations of state, wavelength-dependent opacity, or composition-dependent materials properties). For functions that have a constrained domain of interest, this can be done by discretizing the domain and performing a local interpolation on the tabulated function values of each local domain. For these so-called tabular data methods, the method of discretizing the domain and mapping the input space to each subdomain can drastically influence the memory and computational costs of the emulator. This is especially true for functions that vary drastically in different regions. We present a method for domain discretization and mapping that utilizes quadtrees, which results in significant reductions in the size of the emulator with minimal increases to computational costs or loss of global accuracy. We apply our method to the electron-positron Helmholtz free energy equation of state and show over an order of magnitude reduction in memory costs for reasonable levels of numerical accuracy.

97 MATHEMATICS AND COMPUTING↗

The Fe 2 O 3 (0001) Surface Under Electroreduction Conditions: A DFT Study of L-Cysteine Adsorption

Local catalyst surface structure and environment can play a significant role towards catalytic activity and selectivity. Surface functionalization using organic additives, such as amino acid chains or peptides, can alter surface properties. Density Functional Theory calculations are used to evaluate the potential dependent surface stability of different terminations of the Fe 2 O 3 (0001) surface. Adsorption of L-Cysteine in different redox states and through different binding modes (carboxylic: O-Fe, amine: N-Fe and thiol: S-Fe) is evaluated. At moderate electrochemical reducing conditions, Fe 2 O 3 (0001) exposes a partially reduced termination with both surface H atoms and undercoordinated Fe atoms in the outermost layer. L-Cysteine adsorption occurs most preferentially through carboxylic acid, O-Fe, binding and does not significantly alter the relative surface stability of different surface terminations. A partially reduced surface with L-Cysteine functionalization will be stable under electroreduction conditions. As a result, stable functionalization of an oxide material through amino acid chains or peptide adsorption may provide an additional design lever to develop improved catalytic systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗