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At least 523 records · Page 29

Aliphatic Amines from Waste Polyolefins by Tandem Pyrolysis, Hydroformylation, and Reductive Amination

Pyrolysis of waste plastics can produce a product mixture with a high concentration of olefins (>50 wt%). The olefins, as building blocks in the petroleum industry, are potential precursors for valuable commodity chemicals with higher values (>$2000 per ton). In this work, we produce aldehydes by hydroformylation of the olefins present in pyrolysis oil from colored post-consumer recycled high-density polyethylene (PCR-HDPE). The obtained aldehydes in the oil are then converted into aliphatic amines via reductive amination with a Ru/C catalyst. The aminated oil was characterized by multiple analytical chemistry techniques including elemental analysis, nuclear magnetic resonance spectroscopy, high-resolution liquid chromatography-mass spectrometry, and gas chromatography-mass spectrometry with a Polyarc flame ionization detector. The concentration of metals in the PCR-HDPE and oil changes during the tandem processes, showing limited effects of these elements (e.g., Al, Ca, Fe, Mg, Ti, Zn) on hydroformylation and reductive amination. Additionally, we demonstrated that reductive amination of aldehydes with varied carbon numbers and branching properties can be achieved in the presence of a complex mixture, including paraffins and aromatics. The results indicate that waste plastics have the potential to serve as a renewable source for mono and di aliphatic amines, thereby diminishing reliance on fossil feedstocks as the current primary amine source.

aliphatic amines↗

Fracture mechanics validity limits

Fracture behavior is characteristics of a dramatic loss of strength compared to elastic deformation behavior. Fracture parameters have been developed and exhibit a range within which each is valid for predicting growth. Each is limited by the assumptions made in its development: all are defined within a specific context. For example, the stress intensity parameters, K, and the crack driving force, G, are derived using an assumption of linear elasticity. To use K or G, the zone of plasticity must be small as compared to the physical dimensions of the object being loaded. This insures an elastic response, and in this context, K and G will work well. Rice's J-integral has been used beyond the limits imposed on K and G. J requires an assumption of nonlinear elasticity, which is not characteristic of real material behavior, but is thought to be a reasonable approximation if unloading is kept to a minimum. As well, the constraint cannot change dramatically (typically, the crack extension is limited to ten-percent of the initial remaining ligament length). Rice, et al investigated the properties required of J-type parameters, J(sub x), and showed that the time rate, dJ(sub x)/dt, must not be a function of the crack extension rate, da/dt. Ernst devised the modified-J parameter, J(sub M), that meets this criterion. J(sub M) correlates fracture data to much higher crack growth than does J. Ultimately, a limit of the validity of J(sub M) is anticipated, and this has been estimated to be at a crack extension of about 40-percent of the initial remaining ligament length. None of the various parameters can be expected to describe fracture in an environment of gross plasticity, in which case the process is better described by deformation parameters, e.g., stress and strain. In the current study, various schemes to identify the onset of the plasticity-dominated behavior, i.e., the end of fracture mechanics validity, are presented. Each validity limit parameter is developed in detail, and then data is presented and the various schemes for establishing a limit of the validity are compared. The selected limiting parameter is applied to a set of fracture data showing the improvement of correlation gained.

Lambert, Dennis M.↗

Small-scale yielding analysis of mixed mode plane-strain crack problems

The small-scale yielding analysis of an elastic-plastic body with a line crack under plane-strain conditions subject to combinations of Mode I and II loadings is examined. The analysis of the near-tip field follows the works of Hutchinson and Rice and Rosengren. Dominant singularity solutions governing the asymptotic behavior of the stresses and strains at the crack tip are obtained for the complete range of loadings between Mode I and II. The results of an accurate finite element technique, which imbeds the dominant singularity solutions, directly relates the near-tip behavior to the elastic stress intensity factors K(I) and K(II). Implications of this study to mixed mode fracture mechanics is also discussed, particularly with respect to the direction of crack initiation and the relation of fracture toughness under mixed modes to that in Mode I. Details of the mixed mode plastic zone sizes and shapes are also given.

Shih, C. F.↗

Reducing Antisolvent Use in the STRAP Process by Enabling a Temperature–Controlled Polymer Dissolution and Precipitation for the Recycling of Multilayer Plastic Films

The recently reported processing strategy called solvent-targeted recovery and precipitation (STRAP) enables deconstruction of multilayer plastic packaging films into their constituent resins by selective dissolution. It uses a series of solvent washes that are guided by thermodynamic calculations of polymer solubility. In this work, the use of antisolvents in the STRAP process was reduced and solvent mixtures were considered to enable the temperature-controlled dissolution and precipitation of the target polymers in multilayer films. This was considered as a means to further improve the STRAP process and its estimated costs. Two STRAP approaches were compared based on different polymer precipitation techniques: precipitation by the addition of an antisolvent (STRAP-A) and precipitation by decreasing the solvent temperature (STRAP-B). Both approaches were able to separate the constituent polymers in a post-industrial film composed primarily of polyethylene (PE), ethylene vinyl alcohol (EVOH), and polyethylene terephthalate (PET) with near 100 % material efficiency. Technoeconomic analysis indicates that the minimum selling price (MSP) of the recycled resins with STRAP-B is 21.0 % lower than that achieved with STRAP-A. This provides evidence that thermally driven polymer precipitation is an option to reduce the use of antisolvents, making the STRAP process more economically and environmentally attractive. A third process, STRAP-C, was demonstrated with another post-industrial multilayer film of a different composition. Here, the results demonstrate that this process can also recover polymers at similar costs to those of virgin resins, indicating that the STRAP technology is flexible and can remain economically competitive as the plastic feed complexity is increased.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Application of Thermo-Mechanical Measurements of Plastic Packages for Reliability Evaluation of PEMS

Thermo-mechanical analysis (TMA) is typically employed for measurements of the glass transition temperature (Tg) and coefficients of thermal expansion (CTE) in molding compounds used in plastic encapsulated microcircuits (PEMs). Application of TMA measurements directly to PEMs allows anomalies to be revealed in deformation of packages with temperature, and thus indicates possible reliability concerns related to thermo-mechanical integrity and stability of the devices. In this work, temperature dependencies of package deformation were measured in several types of PEMs that failed environmental stress testing including temperature cycling, highly accelerated stress testing (HAST) in humid environments, and bum-in (BI) testing. Comparison of thermo-mechanical characteristics of packages and molding compounds in the failed parts allowed for explanation of the observed failures. The results indicate that TMA of plastic packages might be used for quality evaluation of PEMs intended for high-reliability applications.

Sharma, Ashok K.↗

3D mapping of residual stresses in growing grains of partially recrystallized Gum Metal

The crystallographic orientations and residual stresses within recrystallizing grains in partially recrystallized beta titanium-Gum Metal-were examined non-destructively in 3D using synchrotron Differential Aperture X-ray Microscopy. Contrary to common assumptions, significant local stresses and stress variations are observed within the recrystallizing grains. The results reveal that the development of these local residual stresses depends on the plastic deformation mode and material's elastic constants, rather than grain properties such as size and orientation, or even the material's yield stress. This work provides insights valuable for the design of advanced materials with heterogeneous microstructures.

36 MATERIALS SCIENCE↗

{beta}- and {gamma}-spectroscopy study of {sup 119}Pd and {sup 119}Ag

Neutron-rich Pd-119 nuclei were produced in fission of natural uranium, induced by 25-MeV protons. Fission fragments swiftly extracted with the Ion Guide Isotope Separation On-Line method were mass separated using a dipole magnet and a Penning trap, providing mono-isotopic samples of Pd-119. Their beta(-) decay was measured with gamma gamma- and beta gamma-spectroscopy methods using low-energy germanium detectors and a thin plastic scintillator. Two distinct nuclear-level structures were observed in Ag-119, based on the 1/2(-) and 7/2(+) isomers reported previously. The beta(-)decay work was complemented by a prompt-gamma study of levels in Ag-119 populated in spontaneous fission of (252)cf, performed using the Gammasphere array of germanium detectors. Contrary to previous suggestions, our data show that the 1/2(-) isomer is located below the 7/2(+) isomer and is proposed as a new ground state of Ag-119 with the 7/2(+) isomer excitation energy determined to be 33.4 keV. Our data indicate that there are two beta unstable isomers in Pd-119, a proposed ground state of Pd-119 with tentative spin 1/2(-) or 3/2(+) and a half-life of 0.88 s and the other one about 350 keV above, having spin (11/2(-)) and a half-life of 0.85 s. The higher-energy isomer probably decays to the 1/2(-) or 3/2(+) ground state via a gamma cascade comprising 18.7-219.8-X-keV transitions. The unobserved isomeric transition with energy X approximate to 100 keV probably has an E3 multipolarity. Its hindrance factor is significantly lower than for analogous E3 isomeric transitions in lighter Pd isotopes, suggesting an oblate deformation of levels in Pd-119. Oblate configurations in Ag-119 are discussed also.

Kurpeta, J↗

Rapid detection of rare events from in situ X-ray diffraction data using machine learning

High-energy X-ray diffraction methods can non-destructively map the 3D microstructure and associated attributes of metallic polycrystalline engineering materials in their bulk form. These methods are often combined with external stimuli such as thermo-mechanical loading to take snapshots of the evolving microstructure and attributes over time. However, the extreme data volumes and the high costs of traditional data acquisition and reduction approaches pose a barrier to quickly extracting actionable insights and improving the temporal resolution of these snapshots. This article presents a fully automated technique capable of rapidly detecting the onset of plasticity in high-energy X-ray microscopy data. The technique is computationally faster by at least 50 times than the traditional approaches and works for data sets that are up to nine times sparser than a full data set. This new technique leverages self-supervised image representation learning and clustering to transform massive data sets into compact, semantic-rich representations of visually salient characteristics ( e.g. peak shapes). These characteristics can rapidly indicate anomalous events, such as changes in diffraction peak shapes. It is anticipated that this technique will provide just-in-time actionable information to drive smarter experiments that effectively deploy multi-modal X-ray diffraction methods spanning many decades of length scales.

Zheng, Weijian↗

Predicting Rupture Pressure and Leak Rate of Alloy 600 U-bend Tubes with PWSCC and Comparing with Test Results (Technical Letter Report)

This report summarizes structural integrity work performed for the US NRC that predicts the structural integrity of steam generator (SG) tubes with flaws in the U-bend. The work covers model development and validation for U-bend tubes containing lab-induced primary water stress corrosion cracks (PWSCC). Limit load models for plastic collapse predicting ligament rupture pressure and leak rate of cracked U-bend tubes were developed and validated with pressure tests and finite element analyses (FEAs). Failure pressure and leak rate tests were conducted at room temperature on Alloy 600 U-bend tubes containing flaws located at various locations around the U-bend. Existing models for predicting structural integrity of straight tubes with well defined, rectangular, electro-discharge-machined (EDM) flaws were modified and used to predict the ligament rupture and unstable burst pressures as well as leak rates for the PWSCC flaws in the U-bend section.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

The line spring model for surface flaws.

A model is discussed for the analysis of long part-through surface cracks in the walls of plate or shell structures. Such problems are formulated within the context of two dimensional plate and shell theory with the part-cracked section represented as a line-spring in the middle surface. The spring allows relative separations and rotations of the middle surface, and constitutive laws relating these discontinuities to the prevailing force and moment per unit length at any point are taken from the plane strain solution for a strip in combined tension and bending, which contains an edge crack of a corresponding depth. Prior work is reviewed and further line spring constitutive laws are discussed as appropriate to elastic analysis with thermal or residual stresses and to elastic-plastic analysis, with yielding in the ligament between the crack front and far wall in the latter case.

Rice, J. R.↗

Evaluation of U10Mo Fuel Plate Performance Modeling Over Hot Isostatic Press and Hydraulic Bending for MURR DDE Plates

The United States High Performance Research Reactor Program’s objective is to reduce the amount of highly enriched uranium currently implemented in research reactors. The conversion of these research reactors requires designing a monolithic U10Mo plate fuel, with the fuel plate geometry being dependent on each research reactor. The process of forming the plates includes a hot isostatic pressing (HIP) to manufacture a prototypic plate. In the case of the Missouri University Research Reactor (MURR) design demonstration element (DDE) plate manufacture, plates that have been through HIP are then curved using dies and a hydraulic press to impart the desired curvature. Both fabrication processes impart residual stresses into each fuel plate region, with the curvature of the plates taking some regions of the fuel plate up to their material yield stresses, accompanied by plastic strain. The amount of plastic strain and stress imparted onto each MURR DDE plate is determined by the radius of curvature, thickness of each region, and overall width of the fuel plates. Furthermore, this work aims to predict the yield stresses and strain using ABAQUS to simulate the proposed fabrication process of the MURR DDE plates, accompanied by discussion over the stresses and strains as to their relation to nuclear fuel performance and the impact they will have during early irradiation.

ABAQUS↗

Integration of CeO 2 -Based Memristor with Vertically Aligned Nanocomposite Thin Film: Enabling Selective Conductive Filament Formation for High-Performance Electronic Synapses

The CeO 2 -based memristor has attracted significant attention due to its intrinsic resistive switching (RS) properties, large on/off ratio, and great plasticity, making it a promising candidate for artificial synapses. However, significant challenges such as high power consumption and poor device reliability hinder its broad application in neuromorphic microchips. To tackle these issues, in this work, we design a novel bilayer (BL) memristor by integrating a CeO 2 -based memristor with a Co-CeO 2 vertically aligned nanocomposite (VAN) layer and compare it with the single layer (SL) memristor. Preliminary electrical testing reveals that the BL memristor offers a reduced set/reset voltage (~67% lower), a higher on/off ratio (~5 × 10 2 ), enhanced device reliability, and improved device-to-device variation compared to the SL memristor. Insight from COMSOL simulation, coupled with microstructural analysis, provides a comprehensive elucidation on how the VAN layer facilitates the selective conductive filament (CF) formation. Subsequently, the plasticity of the BL memristor is evaluated through long-term potentiation/depression (LTP/LTD), paired-pulse facilitation (PPF), and spike-time-dependent plasticity (STDP). The spiking neural network (SNN) built upon the BL memristor achieves remarkable accuracy (~94%) after only 12 iterations, underscoring its potential for high-performance neural networks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hydrophobins from Aspergillus Mediate Fungal Interactions with Microplastics

Microplastics cause negative environmental consequences such as the release of toxic additive leachates, increased greenhouse gas emissions during degradation, and threaten food chains . Microplastic particles are known to serve as a vector for transport of microbes (fungi and bacteria) to new environments, threatening biodiversity. Robust biofilm formation makes fungi a candidate to collect and remediate environmental microplastics. However, fungal-microplastic colonization mechanisms have yet to be explored. In this work, we aim to understand which fungal molecules mediate microplastics binding. We examine common fungal genus Aspergillus , which we found binds microplastics tightly, removing particles from suspension. Upon inoculation of Aspergilli with microplastics particles, up to 3.85 ± 1.48 g of microplastics were flocculated per gram of dry fungal biomass; this phenomenon was observed across various plastics ranging in size from 0.05 to 5 mm. Gene knockouts revealed that hydrophobins drive microplastic-fungi binding, evidenced by a decrease in flocculation relative to wild-type Aspergillus fumigatus. Moreover, purified hydrophobins flocculated microplastics independently of the fungus, validating their ability to bind to microplastics. Furthermore, our work elucidates a role for hydrophobins in fungal colonization of microplastics and highlights a target for mitigating the harm of microplastics through engineered fungal-microplastic interactions.

biofilms↗

Lower length scale informed improvements to Bison U-Pu-Zr fuel swelling model

Due to renewed interest in metallic fuels from the U-(Pu)-Zr material system, significant improvements have recently been made to BISON's capability to simulate metallic fuel, particularly in the area of swelling. In this report, lower length scale simulations that have been conducted to inform the engineering-scale models in BISON during FY20 are described. For the high-temperature regions of the fuel that are dominated by the $\gamma$ phase of U-(Pu)-Zr, two new models for swelling have implemented in BISON. Phase-field simulations were conducted to calculate parameters for these and other BISON models that control when gaseous swelling ceases and fission gas release begins. For the low-temperature regions of the fuel dominated by the phase of uranium, microstructurally resolved simulations of pore growth and crystal deformation were performed to understand the effect of irradiation-generated crystal shape changes. Conformally meshed microstructures with pores were simulated with a crystal plasticity model and with a burnup eigenstrain model. Plastic deformation will not cause pore size to increase; burnup eigenstrain (irradiation-induced crystal shape changes) will increase the volume of existing porosity and cause it to become anisotropic in shape. Additional model development work for early-stage fission gas cluster/bubble formation in the $\gamma$ phase were performed, by coupling with defect clustering within cluster dynamics framework. Sensitivity analysis were conducted to identify the critical thermo-kinetic parameters needed for rigorous assessment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Quantum Simulations of Radiation Damage in a Molecular Polyethylene Analog

Abstract An atomic‐level understanding of radiation‐induced damage in simple polymers like polyethylene is essential for determining how these chemical changes can alter the physical and mechanical properties of important technological materials such as plastics. Ensembles of quantum simulations of radiation damage in a polyethylene analog are performed using the Density Functional Tight Binding method to help bind its radiolysis and subsequent degradation as a function of radiation dose. Chemical degradation products are categorized with a graph theory approach, and occurrence rates of unsaturated carbon bond formation, crosslinking, cycle formation, chain scission reactions, and out‐gassing products are computed. Statistical correlations between product pairs show significant correlations between chain scission reactions, unsaturated carbon bond formation, and out‐gassing products, though these correlations decrease with increasing atom recoil energy. The results present relatively simple chemical descriptors as possible indications of network rearrangements in the middle range of excitation energies. Ultimately, the work provides a computational framework for determining the coupling between nonequilibrium chemistry in polymers and potential changes to macro‐scale properties that can aid in the interpretation of future radiation damage experiments on plastic materials.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Role of the flocculus of the cerebellum in motor learning of the vestibulo-ocular reflex

Structure-function studies at the systems level are an effective method for understanding the relationship of the central nervous system to behavior. Motor learning or adaptation of the vestibulo-ocular reflex is a clear example wherein this approach has been productive. During a vestibulo-ocular reflex the brain converts a head velocity signal, transduced through the vestibular semicircular canals, into an eye movement command delivered to the extraocular muscles. If the viewed target remains on the fovea of the retina, the reflex is compensatory, and its gain, eye velocity/head velocity, is one. When the image of the viewed object slips across the retina, visual acuity decreases, and the gain of the reflex, which is no longer one, is plastically adapted or adjusted until retinal stability is restored. The anatomic substrate for this plasticity thus involves brain structures in which visual-vestibular interaction can potentially occur, as well as vestibular and visual sensory and oculomotor motor structures. Further, it has been known for many years that removal of the flocculus of the cerebellum permanently precludes further vestibulo-ocular reflex adaptation, demonstrating the involvement of the cerebellum in this behavior. Maekawa and Simpson (J Neurophysiol 1973;36: 649-66) discovered that one visual input to the flocculus involved the accessory optic system and the inferior olive. Ensuing work has demonstrated that the visual signals used to adapt the vestibulo-ocular reflex are transmitted by this accessory optic system to the flocculus and subsequently to brain stem structures involved in vestibulo-ocular reflex plasticity. Presently the inclusive list of anatomic sites involved in vestibulo-ocular reflex circuitry and its adaptive plasticity is small. Our laboratory continues to believe that this behavior should be caused by interactions within this small class of neurons. By studying each class of identified neuron and its interactions with others within the list, we hope to ultimately understand the mechanisms used by the brain in the expression of this behavior.

Non-NASA Center↗

Digital Multiphase Composites via Additive Manufacturing

Abstract Mechanical properties of traditional engineering materials are typically coupled to each other, presenting a challenge to practitioners with multi‐dimensional material property requirements. In this work, continuous, independent control over multiple mechanical properties is demonstrated in composite materials realized using additive manufacturing. For the first time, composites additively manufactured from rigid plastic, soft elastomer, and liquid constituents are experimentally characterized, demonstrating materials which span four orders of magnitude in modulus and two orders of magnitude in toughness. By forming analytical mappings between relative concentrations of constituents at the microscale and resulting macroscale material properties, inverse material design is enabled; the method is showcased by printing artifacts with prescribed toughness and elasticity distributions. The properties of these composites are placed in the context of biological tissues, showing they have promise as mechanically plausible tissue mimics.

Smith, Lawrence T.↗

Solving Stochastic Inverse Problems for Property–Structure Linkages Using Data-Consistent Inversion and Machine Learning

Determining process–structure–property linkages is one of the key objectives in material science, and uncertainty quantification plays a critical role in understanding both process–structure and structure–property linkages. In this work, we seek to learn a distribution of microstructure parameters that are consistent in the sense that the forward propagation of this distribution through a crystal plasticity finite element model matches a target distribution on materials properties. This stochastic inversion formulation infers a distribution of acceptable/consistent microstructures, as opposed to a deterministic solution, which expands the range of feasible designs in a probabilistic manner. Furthermore, to solve this stochastic inverse problem, we employ a recently developed uncertainty quantification framework based on push-forward probability measures, which combines techniques from measure theory and Bayes’ rule to define a unique and numerically stable solution. This approach requires making an initial prediction using an initial guess for the distribution on model inputs and solving a stochastic forward problem. To reduce the computational burden in solving both stochastic forward and stochastic inverse problems, we combine this approach with a machine learning Bayesian regression model based on Gaussian processes and demonstrate the proposed methodology on two representative case studies in structure–property linkages.

36 MATERIALS SCIENCE↗