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At least 1,621 records · Page 90

Improved Crystal Quality by Detached Solidification in Microgravity

The goals of our work on detached solidification have been to: Develop a complete understanding of all of the phenomena of detached solidification; Make it possible to achieve detached solidification reproducibly; Increase crystallographic perfection through detached solidification. Specifically, we aimed in this project to: Identify a system and develop methods that would allow viewing of the melt surface and convection in the melt during detached solidification in microgravity; Improve understanding of the origination and evolution of detachment through experiments and theoretical treatments; Achieve detachment on earth. The project resulted in 14 publications, 15 presentations, completion of 2 Ph.D. theses, and completion of 2 M.S. theses. Two additional papers are currently being reviewed for publication. Copies of most of the papers are attached as appendices. Among the accomplishments are: Achievement of detached solidification of InSb on earth and determination of the conditions favoring detachment on earth. Development of a new method for coating the interior of silica growth ampoules with transparent boron nitride, which yields the high contact angles for semiconductor melts that favor detachment. Development of a new coating for the interior of Pyrex ampoules yielding very high contact angles for water and molten organic compounds. Development of a material-balance model for steady detached solidification that provides greatly improved insight into the process, both in microgravity and on earth. Dimensionless parameters were found that clarify the role of operating conditions and physical properties. The reason for the occurrence of two steady states was clarified, along with their relative stability. Observation of periodic gas tubes during directional solidification of water and organic compounds. Gas bubbles did not propagate around the periphery to yield full detachment. Failure to obtain detachment is attributed to the ready plastic deformation of these materials, so that the frozen material continues to adhere to the ampoule wall during cooling.

Regel, Liya L.↗

GVIPS Models and Software

Two reports discuss, respectively, (1) the generalized viscoplasticity with potential structure (GVIPS) class of mathematical models and (2) the Constitutive Material Parameter Estimator (COMPARE) computer program. GVIPS models are constructed within a thermodynamics- and potential-based theoretical framework, wherein one uses internal state variables and derives constitutive equations for both the reversible (elastic) and the irreversible (viscoplastic) behaviors of materials. Because of the underlying potential structure, GVIPS models not only capture a variety of material behaviors but also are very computationally efficient. COMPARE comprises (1) an analysis core and (2) a C++-language subprogram that implements a Windows-based graphical user interface (GUI) for controlling the core. The GUI relieves the user of the sometimes tedious task of preparing data for the analysis core, freeing the user to concentrate on the task of fitting experimental data and ultimately obtaining a set of material parameters. The analysis core consists of three modules: one for GVIPS material models, an analysis module containing a specialized finite-element solution algorithm, and an optimization module. COMPARE solves the problem of finding GVIPS material parameters in the manner of a design-optimization problem in which the parameters are the design variables.

Arnold, Steven M.↗

304L Can Crush Validation Studies

Accurate prediction of ductile behavior of structural alloys up to and including failure is essential in component or system failure assessment, which is necessary for nuclear weapons alteration and life extensions programs of Sandia National Laboratories. Modeling such behavior requires computational capabilities to robustly capture strong nonlinearities (geometric and material), rate- dependent and temperature-dependent properties, and ductile failure mechanisms. This study's objective is to validate numerical simulations of a high-deformation crush of a stainless steel can. The process consists of identifying a suitable can geometry and loading conditions, conducting the laboratory testing, developing a high-quality Sierra/SM simulation, and then drawing comparisons between model and measurement to assess the fitness of the simulation in regards to material model (plasticity), finite element model construction, and failure model. Following previous material model calibration, a J 2 plasticity model with a microstructural BCJ failure model is employed to model the test specimen made of 304L stainless steel. Simulated results are verified and validated through mesh and mass-scaling convergence studies, parameter sensitivity studies, and a comparison to experimental data. The converged mesh and degree of mass-scaling are the mesh discretization with 140,372 elements, and a mass scaling with a target time increment of 1.0e-6 seconds and time step scale factor of 0.5, respectively. Results from the coupled thermal-mechanical explicit dynamic analysis are comparable to the experimental data. Simulated global force vs displacement (F/D) response predicts key points such as yield, ultimate, and kinks of the experimental F/D response. Furthermore, the final deformed shape of the can and field data predicted from the analysis are similar to that of the deformed can, as measured by 3D optical CMM scans and DIC data from the experiment.

36 MATERIALS SCIENCE↗

Ab initio ground states of strongly-correlated materials on quantum computers

The accurate first-principles description of strongly-correlated materials is an important and challenging problem in condensed matter physics. Ab initio downfolding has emerged as a way of deriving accurate many-body Hamiltonians including strong correlations, representing a subspace of interest of a material, using density functional theory calculations as a starting point. However, the solution of these material-specific models can scale exponentially on classical computers, constituting a challenge. Here we propose that utilizing quantum computers for obtaining the properties of downfolded Hamiltonians yields an accurate description of the ground state properties of strongly-correlated systems, while circumventing the exponential scaling problem. We benchmark the solution of Hubbard-like models obtained through downfolding by utilizing a classical tensor network implementation of variational quantum eigensolvers (VQE), and we reveal a strategy for driving the optimization through a hybrid minimization of the energy and maximization of the overlap with an approximate solution obtained through low-cost computational methods. This results in a reduction of the energy error by orders of magnitude compared to conventional VQE approaches, and allows us to reproduce long-range correlations for the first time. We demonstrate our first-principles approach for diverse strongly-correlated materials, correctly predicting the antiferromagnetic state of one-dimensional cuprate Ca 2 CuO 3 , the excitonic ground state of monolayer WTe2, and the charge-ordered state of correlated metal SrVO 3 . Our efficient computational implementation allows us to simulate large systems with up to 54 qubits and encompassing up to four correlated bands, which is indicative of the complexity that our framework can address.

Antonios M Alvertis↗

Guidelines to Achieving High Selectivity for the Hydrogenation of α,β-Unsaturated Aldehydes with Bimetallic and Dilute Alloy Catalysts: A Review

Selective hydrogenation of unsaturated aldehydes to unsaturated alcohols is a challenging class of reactions, yielding valuable intermediates for the production of pharmaceuticals, perfumes, and flavorings. On monometallic heterogeneous catalysts, the formation of the unsaturated alcohols is thermodynamically disfavored over the saturated aldehydes. Hence, new catalysts are required to achieve the desired selectivity. In this work, the literature of three major research areas in catalysis is integrated as a step toward establishing the guidelines for enhancing the selectivity: reactor studies of complex catalyst materials at operating temperature and pressure, surface science studies of crystalline surfaces in ultrahigh vacuum, and first-principles modeling using density functional theory calculations. Aggregate analysis shows that bimetallic and dilute alloy catalysts significantly enhance the selectivity to the unsaturated alcohols compared to monometallic catalysts. This comprehensive review focuses primarily on the role of different metal surfaces as well as the factors that promote the adsorption of the unsaturated aldehyde via its C=O bond, most notably by electronic modification of the surface and formation of the electrophilic sites. Furthermore, challenges, gaps, and opportunities are identified to advance the rational design of efficient catalysts for this class of reactions, including the need for systematic studies of catalytic processes, theoretical modeling of complex materials, and model studies under ambient pressure and temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

ExtremeMETA: High-speed Lightweight Image Segmentation Model by Remodeling Multi-channel Metamaterial Imagers

Deep neural networks (DNNs) have heavily relied on traditional computational units, such as CPUs and GPUs. However, this conventional approach brings significant computational burden, latency issues, and high power consumption, limiting their effectiveness. This has sparked the need for lightweight networks such as ExtremeC3Net. Meanwhile, there have been notable advancements in optical computational units, particularly with metamaterials, offering the exciting prospect of energy-efficient neural networks operating at the speed of light. Yet, the digital design of metamaterial neural networks (MNNs) faces precision, noise, and bandwidth challenges, limiting their application to intuitive tasks and low-resolution images. In this study, we proposed a large kernel lightweight segmentation model, ExtremeMETA. Based on ExtremeC3Net, our proposed model, ExtremeMETA maximized the ability of the first convolution layer by exploring a larger convolution kernel and multiple processing paths. With the large kernel convolution model, we extended the optic neural network application boundary to the segmentation task. To further lighten the computation burden of the digital processing part, a set of model compression methods was applied to improve model efficiency in the inference stage. The experimental results on three publicly available datasets demonstrated that the optimized efficient design improved segmentation performance from 92.45 to 95.97 on mIoU while reducing computational FLOPs from 461.07 MMacs to 166.03 MMacs. The large kernel lightweight model ExtremeMETA showcased the hybrid design’s ability on complex tasks.

large convolution kernel↗

Residual Stresses Affect Cell Fragment Movement

Predictive modeling tools such as the finite element method can be of tremendous help in assessing the reliability and long-term performance of photovoltaic modules. In order to obtain accurate results, the proper modeling of materials and manufacturing processes are of utmost importance. Module fabrication introduces thermo-mechanical stresses inside the module laminate, which need to be accounted for as residual stresses in finite element simulations. We found that cell fragment movement and crack opening displacements of fractured silicon cells within modules are affected by those residual stresses. Cell cracking remains a challenging topic in assessing the reliability and durability of damaged modules. Hence, accurately quantifying the separation and movement between cell fragments creates the foundation for establishing reliable lifetime and performance assessments of fractured silicon modules. Here, we present a modeling approach that uses upper and lower bounds to accurately account for the residual stresses introduced by the module lamination process. We designed a four-point flexure coupon test of a laminated, fractured silicon strip to validate our numerical results and found good agreement between our modeling methodology and the experimental data. Finally, we discuss the implications of the residual stresses on the normal crack opening and metallization wear-out of fractured silicon cells.

14 SOLAR ENERGY↗

Liners and Low Luminosity AGN in the ROSAT Database

This program has led to a series of papers being written and published in the Astrophysical Journal. Together these papers try to explain major parts of the LINER and low luminosity AGN puzzle. One paper ('Accretion Disk Instabilities, Cold Dark Matter Models, and Their Role in Quasar Evolution', Hatziminaoglou E., Siemiginowska A., & Elvis M., 2001, ApJ, 547, 90) describes an analytical model for the evolution of the quasar luminosity function. By combining the Press-Schechter formalism for the masses of initial structures with the luminosity distribution for a population of single mass black holes given by an unstable accretion disk an almost complete end-to-end physics-based model of quasar evolution is produced. In this model black holes spend 75% of their time in a low accretion state (at L(Edd)). This low state population of black holes is likely to be observed as the LINER and low luminosity AGNs in the local universe. Another paper ('Broad Emission Line Regions in AGN: the Link with the Accretion Power', Nicastro F., 2000, ApJ Letters, 530, L65) gives a physical basis for why low state black holes appear as LINERS. By linking the Lightman-Eardley instability in an accretion disk to the ori.gin of a wind that contains the broad emission line cloud material this model explains the large widths seen in these lines as being the Keplerian velocity of the disk at the instability radius. For LINERS the key is that below an accretion rate of 10(exp -3)M(sub Edd)the Lightman-Eardley instability falls within the innermost stable orbit of the disk, and so leaves the entire disk stable. No wind occurs, and so no broad emission lines are seen. Most LINERS are likely to be black holes in this low state. Tests of this model are being considered.

Elvis, Martin↗

Comparing Parallel Plastic‐to‐X Pathways and Their Role in a Circular Economy for PET Bottles

Abstract The United States generates the most plastic waste of any country and is a top contributor to global plastic pollution. Multiple end‐of‐life strategies must be implemented to minimize environmental impacts and retain valuable plastic material, but it is challenging to compare options that generate products with different lifetimes and utilities. Herein, they present a material flow model equipped with consequential life cycle assessment, cost analysis, and a plastic circularity indicator that considers product quality and lifetime. The model is used to estimate the greenhouse gas (GHG) emissions, circularity, and cost of polyethylene terephthalate (PET) bottle mechanical downcycling to lower‐quality resin, closed‐loop glycolysis to food‐grade PET, upcycling to glass fiber‐reinforced plastic, and conversion to non‐plastic products (electricity, oil) on a United States economy‐wide basis for the year 2020. A brute force algorithm suggests that a combination of 68% glycolysis, 11% mechanical recycling, 6% upcycling, 9% landfilling, and 5% incineration can minimize the cost and GHG emissions and maximize the circularity of the current PET economy. However, uncertainty around transportation distances, materials recovery facility efficiencies, and recycling yields can result in different “optimal” pathway mixes. This flexible framework enables informed decision‐making to move toward a cost‐ and environment‐conscious circular economy for plastic.

09 BIOMASS FUELS↗

Magnetic field frustration of the metal-insulator transition in V 2 O 3

Despite decades of efforts, the origin of metal-insulator transitions (MITs) in strongly correlated materials remains one of the main long-standing problems in condensed-matter physics. An archetypal example is V 2 O 3 , which undergoes simultaneous electronic, structural, and magnetic phase transitions. This remarkable feature highlights the many degrees of freedom at play in this material. In this work, acting solely on the magnetic degree of freedom, we reveal an anomalous feature in the electronic transport of V 2 O 3 : On cooling, the magnetoresistance changes from positive to negative values well above the MIT temperature, and shows divergent behavior at the transition. In this work, the effects are attributed to the magnetic field quenching antiferromagnetic fluctuations above the Néel temperature $T_N$, and preventing long-range antiferromagnetic ordering below $T_N$. In both cases, suppressing the antiferromagnetic ordering prevents the opening of the incipient electronic gap. This interpretation is supported by Hubbard model calculations which fully reproduce the experimental behavior. Our study sheds light on this classic problem providing a clear and physical interpretation of the nature of the metal-insulator transition.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Advances in Modeling Capabilities for Critical Mineral Separation Technologies: A PrOMMiS Overview

This is an oral presentation at the TechConnect conference on the work developed by PrOMMiS. PrOMMiS builds on and extends capabilities developed within the Department of Energy’s (DOE) Institute for the Design of Advanced Energy Systems (IDAES), Integrated Platform, and Water Treatment Technoeconomic Assessment Platform (WaterTAP), which have been successfully leveraged by other Department of Energy research areas. The open-source toolkit facilitates validation, reproducibility, and accountability, allowing for easy extension of the framework to other systems. This talk presents an overview of the PrOMMiS capabilities, including unit model library, advances in thermophysical properties models, and capital cost libraries for simulation and optimization of mineral processing technologies. The PrOMMiS applications include (1) conceptual design and superstructure optimization for screening different process configurations and identifying promising technologies; (2) dynamic modeling and optimization to enable the creation of digital twins; (3) surrogate modeling tools to leverage data when predictive thermodynamic models are not currently available; (4) technical risk reduction via uncertainty quantification and robust optimization to identify process designs that are robust to process variability and uncertainties; and (5) deployment of uncertainty quantification tools to maximize knowledge gained from experimental campaigns, while reducing the number of experiments required

critical minerals and materials↗

Microstructural Characterization and Modeling of SLM Superalloy 718

Superalloy 718 is an excellent candidate for selective laser melting (SLM) fabrication due to a combination of excellent mechanical properties and workability. Predicting and validating the microstructure of SLM-fabricated Superalloy 718 after potential post heat-treatment paths is an important step towards producing components comparable to those made using conventional methods. At present, obtaining accurate volume fraction and size measurements of gamma-double-prime, gamma-prime and delta precipitates has been challenging due to their size, low volume fractions, and similar chemistries. A technique combining high resolution distortion corrected SEM imaging and with x-ray energy dispersive spectroscopy has been developed to accurately and independently measure the size and volume fractions of the three precipitates. These results were further validated using x-ray diffraction and phase extraction methods and compared to the precipitation kinetics predicted by PANDAT and JMatPro. Discrepancies are discussed in context of materials properties, model assumptions, sampling, and experimental errors.

SEM↗

Decoupling between Shockley partials and stacking faults strengthens multiprincipal element alloys

We report that mechanical properties are fundamental to structural materials, where dislocations play a decisive role in describing their mechanical behavior. Although the high-yield stresses of multiprincipal element alloys (MPEAs) have received extensive attention in the last decade, the relation between their mechanistic origins remains elusive. Our multiscale study of density functional theory, atomistic simulations, and high-resolution microscopy shows that the excellent mechanical properties of MPEAs have diverse origins. The strengthening effects through Shockley partials and stacking faults can be decoupled in MPEAs, breaking the conventional wisdom that low stacking fault energies are coupled with wide partial dislocations. This study clarifies the mechanistic origins for the strengthening effects, laying the foundation for physics-informed predictive models for materials design.

36 MATERIALS SCIENCE↗

On the inference of viscoelastic constants from stress relaxation experiments

Several constitutive theories have been proposed in the literature to model the viscoelastic response of materials, including widely used rheological constitutive models. These models are characterized by certain parameters ("time constants") that define the time scales over which the material relaxes. These parameters are primarily obtained from stress relaxation experiments using curve-fitting techniques. However, the question of how best to estimate these time constants remains open. As a step towards answering this question, we propose an optimal experimental design approach based on ideas from information geometry, namely Fisher information and Kullback-Leibler divergence. The material is modeled as a spring element in parallel with multiple Maxwell elements and described using a one- or two-term Prony series. Treating the time constants as unknowns, we develop expressions for the Fisher information and Kullback-Leibler divergence that allow us to maximize information gain from experimental data. Based on the results of this study, we propose that the largest time constant estimated from a stress relaxation experiment for a linear viscoelastic material should be at most one-fifth of the total time of the experiment in order to maximize information gain. Our results also provide confirmation that the equilibrium modulus of the material cannot be reliably determined from curve-fitting to data from a stress relaxation experiment.

Fisher information↗

Cluster-Spin-Glass Magnetic Behavior and Morphology in the Coordination Polymer Alloys Fe y Co 1– y BTT

We report the synthesis of a series of pseudo-1D coordination polymer (CP) materials with the formula Fe y Co 1–y BTT (BTT = 1,3,5-benzenetrithiolate). These materials were structurally characterized by PXRD Rietveld, EXAFS, and PDF analyses, revealing that the CP superstructure enables a continuous and isomorphous alloy between the two homometallic compounds. Lower Fe loadings exhibit emergent spin glass magnetic behavior, such as memory effects and composition-dependent spin glass response time constants ranging from 6.9 × 10 –9 s to 1.8 × 10 –6 s. These data are consistent with the formation of spin clusters within the lattice. The magnetic behavior in these materials was modeled via replica exchange Monte Carlo simulation, which provides a good match for the experimentally measured spin glassing and magnetic phase transitions. Furthermore, these findings underscore how the rigid superstructure of CP and MOF scaffolds can enable the systematic tuning of physical properties, such as the spin glass behavior described here.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Inelastic Neutron Scattering Study of Magnetic Exchange Pathways in MnS

We report an investigation of the magnetic structure and magnetic exchange pathways in MnS via neutron scattering methods, aided by density functional theory (DFT) modeling. The material has been confirmed to undergo antiferromagnetic (AFM) ordering at 152 K, with the magnetic structure representing AFM stacking of ferromagnetic (FM) (111) planes of Mn magnetic moments. Correspondingly, the magnetic structure is described by a propagation vector k = (1/2, 1/2, 1/2), with the volume of the magnetic unit cell being 8 times larger than the volume of the nuclear unit cell. Analysis of inelastic neutron scattering (INS) data collected on a powder sample of MnS revealed that the next-nearest-neighbor magnetic exchange constant (J 2 ) exceeds the nearest-neighbor exchange constant (J 1 ) by more than 3 times, while in the case of MnO, which exhibits the same nuclear and magnetic structures as MnS, the J 2 /J 1 ratio was reported to be below 1.5. Although for MnO the signs of both J 1 and J 2 indicated AFM exchange interactions, machine-learning INS data analysis in combination with DFT calculations suggests that the INS data collected on MnS are best described with J 1 < 0 and J 2 > 0, corresponding to FM and AFM exchange couplings, respectively. To achieve a satisfactory fit to the experimentally observed data, the Hamiltonian used to model the INS spectra also included the next-next-nearest-neighbor magnetic exchange constant (J 3 ). The best-fit model has been obtained with the values of the exchange constants J 1 = -0.27 meV, J 2 = 1.05 meV, and J 3 = -0.19 meV.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Topology optimization of compliant mechanisms under transient thermal conditions

This work considers multi-material topology optimization of compliant mechanisms under transient thermal and quasi-static mechanical conditions wherein thermally actuated devices are optimized for different operating conditions. The materials are modeled using finite strain thermo-hyperelasticity and a two way coupling between the energy balance and equilibrium equations is investigated. The design updates are generated from the gradient-based method of moving asymptotes optimizer and the sensitivities are computed using the time dependent adjoint sensitivity analysis. Results show the impact of designing for short versus long actuation times.

42 ENGINEERING↗

Computationally efficient method for determining limiting velocities of edge dislocations in anisotropic crystals

The continuum-limit theory of dislocations in crystals predicts divergences in the elastic energy at crystal-geometry dependent limiting velocities vL, which separate subsonic, transsonic, and supersonic dislocation glide regimes and are therefore import for material strength models at high strain rates. Although it is known how to calculate those limiting velocities, there is one special case - edge dislocations with reflection symmetry, but non-vanishing elastic constants c16 or c26 - where previous methods have been notoriously slow. In this letter, we address this deficiency by deriving a computationally efficient method for determining the limiting velocities of edge dislocations with reflection symmetry which is two orders of magnitude faster than the previous method.

36 MATERIALS SCIENCE↗