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At least 595 records · Page 33

PyJMAK: An Open-Source Python Toolkit for Modeling Solid-State Metallurgical Phase Transformations

Accurate prediction of metallurgical phase transformations is an essential basis for autonomous optimization and rapid part qualification. Several methods can be used to estimate the evolution of phase fractions such as JMAK kinetics-based models, phase-field models, thermodynamic models, and data-driven machine learning models. Thermodynamic and phase-field-based methodologies solve multiphysics equations requiring numerous calibration parameters and significant computational resources. As a result, the computation domain is limited to a point or on order of micron-meters. The data-driven models rely on large datasets from experiments and simulations. While the JMAK model only provides information about phase fraction evolution, it can predict this evolution in near real-time using thermal history and thermodynamic data without restriction on the domain. JMAK models have been popularly used by researchers to model phase transformations occuring during additive manufacturing or over arbitrary temperature profiles. Commercial proprietary software such as Abaqus and Ansys or closed-source in-house implementations offer the ability to model JMAK based kinetics to predict phase transformation. However, these software packages are not open-source or freely available for use and development in conjunction with manufacturing machines, sensors, and machine learning algorithms. In addition, the use of the model is restricted by a license token. In contrast, given temperature profiles at multiple points in the domain, this Python-based PyJMAK model can compute phase evolution in parallel due to its stand-alone modular, voxel-based structure, and it can be executed on high-performance computing resources without any license restrictions.

Prabhune, Bhagya [Oak Ridge National Laboratory (O↗

Generating Skeletal Chemical Reaction Mechanisms for Post-Detonation Flows

This report documents the generation of a skeletal chemical reaction mechanism for use with hemispherical pentaerythritol tetranitrate charges. Skeletal mechanisms can substantially reduce computation time while maintaining accuracy. The methodology within uses faster running sample simulations to build a representative thermodynamic state space. These thermodynamic states are used with a constant-volume reactor analysis and a reaction flow analysis to remove unimportant species and reactions from a full chemical reaction mechanism. For the given test case, this results in a 6x speedup in computation time for directly comparable simulations in 2D axisymmetric simulations. We see a 30x speedup in simulations in 3D Cartesian coordainates when compared to a prior full kinetics simulation. There is strong agreement between temperature and species mass fraction profiles between the full and skeletal chemical reaction mechanisms. These methodologies can be applied to any explosive, given the availability of sample simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Higher-derivative corrections to entropy and the weak gravity conjecture in Anti-de Sitter space

We compute the four-derivative corrections to the geometry, extremality bound, and thermodynamic quantities of AdS-Reissner-Nordström black holes for general dimensions and horizon geometries. We confirm the universal relationship between the extremality shift at fixed charge and the shift of the microcanonical entropy, and discuss the consequences of this relation for the Weak Gravity Conjecture in AdS. The thermodynamic corrections are calculated using two different methods: first by explicitly solving the higher-derivative equations of motion and second, by evaluating the higher-derivative Euclidean on-shell action on the leading-order solution. In both cases we find agreement, up to the addition of a Casimir energy in odd dimensions. We derive the bounds on the four-derivative Wilson coefficients implied by the conjectured positivity of the leading corrections to the microcanonical entropy of thermodynamically stable black holes. These include the requirement that the coefficient of Riemann-squared is positive, meaning that the positivity of the entropy shift is related to the condition that c – a is positive in the dual CFT. We discuss implications for the deviation of η/s from its universal value and a potential lower bound.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A graph-based network for predicting chemical reaction pathways in solid-state materials synthesis

Abstract Accelerated inorganic synthesis remains a significant challenge in the search for novel, functional materials. Many of the principles which enable “synthesis by design” in synthetic organic chemistry do not exist in solid-state chemistry, despite the availability of extensive computed/experimental thermochemistry data. In this work, we present a chemical reaction network model for solid-state synthesis constructed from available thermochemistry data and devise a computationally tractable approach for suggesting likely reaction pathways via the application of pathfinding algorithms and linear combination of lowest-cost paths in the network. We demonstrate initial success of the network in predicting complex reaction pathways comparable to those reported in the literature for YMnO 3 , Y 2 Mn 2 O 7 , Fe 2 SiS 4 , and YBa 2 Cu 3 O 6.5 . The reaction network presents opportunities for enabling reaction pathway prediction, rapid iteration between experimental/theoretical results, and ultimately, control of the synthesis of solid-state materials.

36 MATERIALS SCIENCE↗

Quadrupolar interactions between acceptor pairs in $\mathcal{p}$-doped semiconductors

Here, we consider the interaction between acceptor pairs in doped semiconductors in the limit of large interacceptor separation relevant for low doping densities. Modeling individual acceptors via the spherical model of Baldereschi and Lipari, we calculate matrix elements of the quadrupole tensor between the four degenerate ground states and show that the acceptor has a nonzero quadrupole moment. As a result, the dominant contribution to the large-separation acceptor-acceptor interaction comes from direct (charge-density) terms rather than exchange terms. The quadrupole is the leading nonzero moment, so the electric quadrupole-quadrupole interaction dominates for large separation. We calculate the matrix elements of the quadrupole-quadrupole interaction Hamiltonian in a product-state basis and diagonalize, obtaining a closed-form expression for the energies and degeneracies of the sixteen-state energy spectrum. All dependence on material parameters enters via an overall prefactor, resulting in surprisingly simple and universal results. This simplicity is due, in part, to a mathematical happenstance, the nontrivial vanishing of a particular Wigner 6-$\mathcal{j}$ symbol, $^\{\frac{^2_3}{\small2} \frac{^2_3}{\small2} \frac{^2_3}{\small2}$$^\}$ = 0. Results are relevant to the control of two-qubit interactions in quantum computing implementations based on acceptor spins, as well as calculations of the thermodynamic properties of insulating $\mathcal{p}$-type semiconductors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Low-energy physics of isotropic spin-1 chains in the critical and Haldane phases

Using a matrix product state algorithm with infinite boundary conditions, we compute high-resolution dynamic spin and quadrupolar structure factors in the thermodynamic limit to explore the low-energy excitations of isotropic bilinear-biquadratic spin-1 chains. Haldane mapped the spin-1 Heisenberg antiferromagnet to a continuum field theory, the nonlinear sigma model (NLσM). In this work, we find that the NLσM fails to capture the influence of the biquadratic term and provides only an unsatisfactory description of the Haldane phase physics. But several features in the Haldane phase can be explained by noninteracting multimagnon states. The physics at the Uimin-Lai-Sutherland point is characterized by multisoliton continua. Moving into the extended critical phase, we find that these excitation continua contract, which we explain using a field-theoretic description. New excitations emerge at higher energies and, in the vicinity of the purely biquadratic point, they show simple cosine dispersions. Using block fidelities, we identify them as elementary one-particle excitations and relate them to the integrable Temperley-Lieb chain.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Improving Predictive Capability in REHEDS Simulations with Fast, Accurate, and Consistent Non-Equilibrium Material Properties

Predictive design of REHEDS experiments with radiation-hydrodynamic simulations requires knowledge of material properties (e.g. equations of state (EOS), transport coefficients, and radiation physics). Interpreting experimental results requires accurate models of diagnostic observables (e.g. detailed emission, absorption, and scattering spectra). In conditions of Local Thermodynamic Equilibrium (LTE), these material properties and observables can be pre-computed with relatively high accuracy and subsequently tabulated on simple temperature-density grids for fast look-up by simulations. When radiation and electron temperatures fall out of equilibrium, however, non-LTE effects can profoundly change material properties and diagnostic signatures. Accurately and efficiently incorporating these non-LTE effects has been a longstanding challenge for simulations. At present, most simulations include non-LTE effects by invoking highly simplified inline models. These inline non-LTE models are both much slower than table look-up and significantly less accurate than the detailed models used to populate LTE tables and diagnose experimental data through post-processing or inversion. Because inline non-LTE models are slow, designers avoid them whenever possible, which leads to known inaccuracies from using tabular LTE. Because inline models are simple, they are inconsistent with tabular data from detailed models, leading to ill-known inaccuracies, and they cannot generate detailed synthetic diagnostics suitable for direct comparisons with experimental data. This project addresses the challenge of generating and utilizing efficient, accurate, and consistent non-equilibrium material data along three complementary but relatively independent research lines. First, we have developed a relatively fast and accurate non-LTE average-atom model based on density functional theory (DFT) that provides a complete set of EOS, transport, and radiative data, and have rigorously tested it against more sophisticated first-principles multi-atom DFT models, including time-dependent DFT. Next, we have developed a tabular scheme and interpolation methods that compactly capture non-LTE effects for use in simulations and have implemented these tables in the GORGON magneto-hydrodynamic (MHD) code. Finally, we have developed post-processing tools that use detailed tabulated non-LTE data to directly predict experimental observables from simulation output.

36 MATERIALS SCIENCE↗

Sodium sulfate - Vaporization thermodynamics and role in corrosive flames

Mass spectrometer experiments were conducted to determine the thermodynamic properties of gaseous Na2SO4, and these data were used in a computer program to calculate equilibrium flame compositions and temperatures for representative turbine engine and burner rig flames. The work is important in that sodium sulfate is the major phase recovered from turbine surfaces after instances of corrosion, due to the presence of sulfur in fuels and sodium chloride in intake air.

Kohl, F. J.↗

Does metallic ammonium exist

A description is given of calculations which demonstrate that metallic ammonium, at least in the form envisaged by Ramsey (1951), is unstable at all pressures. On the basis of the computational results it is concluded that monovalent metallic ammonium is never the thermodynamically favored phase for an NH3-1/2H2 mixture.

Stevenson, D. J.↗

Computing Equilibrium Chemical Compositions

Chemical Equilibrium With Transport Properties, 1993 (CET93) computer program provides data on chemical-equilibrium compositions. Aids calculation of thermodynamic properties of chemical systems. Information essential in design and analysis of such equipment as compressors, turbines, nozzles, engines, shock tubes, heat exchangers, and chemical-processing equipment. CET93/PC is version of CET93 specifically designed to run within 640K memory limit of MS-DOS operating system. CET93/PC written in FORTRAN.

Mcbride, Bonnie J.↗

Modeling the Deterioration of Engine and Low Pressure Compressor Performance During a Roll Back Event Due to Ice Accretion

The main focus of this study is to apply a computational tool for the flow analysis of the engine that has been tested with ice crystal ingestion in the Propulsion Systems Laboratory (PSL) of NASA Glenn Research Center. A data point was selected for analysis during which the engine experienced a full roll back event due to the ice accretion on the blades and flow path of the low pressure compressor. The computational tool consists of the Numerical Propulsion System Simulation (NPSS) engine system thermodynamic cycle code, and an Euler-based compressor flow analysis code, that has an ice particle melt estimation code with the capability of determining the rate of sublimation, melting, and evaporation through the compressor blade rows. Decreasing the performance characteristics of the low pressure compressor (LPC) within the NPSS cycle analysis resulted in matching the overall engine performance parameters measured during testing at data points in short time intervals through the progression of the roll back event. Detailed analysis of the fan-core and LPC with the compressor flow analysis code simulated the effects of ice accretion by increasing the aerodynamic blockage and pressure losses through the low pressure compressor until achieving a match with the NPSS cycle analysis results, at each scan. With the additional blockages and losses in the LPC, the compressor flow analysis code results were able to numerically reproduce the performance that was determined by the NPSS cycle analysis, which was in agreement with the PSL engine test data. The compressor flow analysis indicated that the blockage due to ice accretion in the LPC exit guide vane stators caused the exit guide vane (EGV) to be nearly choked, significantly reducing the air flow rate into the core. This caused the LPC to eventually be in stall due to increasing levels of diffusion in the rotors and high incidence angles in the inlet guide vane (IGV) and EGV stators. The flow analysis indicating compressor stall is substantiated by the video images of the IGV taken during the PSL test, which showed water on the surface of the IGV flowing upstream out of the engine, indicating flow reversal, which is characteristic of a stalled compressor.

Veres, Joseph P.↗

Modeling the Deterioration of Engine and Low Pressure Compressor Performance During a Roll Back Event Due to Ice Accretion

The main focus of this study is to apply a computational tool for the flow analysis of the engine that has been tested with ice crystal ingestion in the Propulsion Systems Laboratory (PSL) of NASA Glenn Research Center. A data point was selected for analysis during which the engine experienced a full roll back event due to the ice accretion on the blades and flow path of the low pressure compressor. The computational tool consists of the Numerical Propulsion System Simulation (NPSS) engine system thermodynamic cycle code, and an Euler-based compressor flow analysis code, that has an ice particle melt estimation code with the capability of determining the rate of sublimation, melting, and evaporation through the compressor blade rows. Decreasing the performance characteristics of the low pressure compressor (LPC) within the NPSS cycle analysis resulted in matching the overall engine performance parameters measured during testing at data points in short time intervals through the progression of the roll back event. Detailed analysis of the fan-core and LPC with the compressor flow analysis code simulated the effects of ice accretion by increasing the aerodynamic blockage and pressure losses through the low pressure compressor until achieving a match with the NPSS cycle analysis results, at each scan. With the additional blockages and losses in the LPC, the compressor flow analysis code results were able to numerically reproduce the performance that was determined by the NPSS cycle analysis, which was in agreement with the PSL engine test data. The compressor flow analysis indicated that the blockage due to ice accretion in the LPC exit guide vane stators caused the exit guide vane (EGV) to be nearly choked, significantly reducing the air flow rate into the core. This caused the LPC to eventually be in stall due to increasing levels of diffusion in the rotors and high incidence angles in the inlet guide vane (IGV) and EGV stators. The flow analysis indicating compressor stall is substantiated by the video images of the IGV taken during the PSL test, which showed water on the surface of the IGV flowing upstream out of the engine, indicating flow reversal, which is characteristic of a stalled compressor.

Jorgenson, Philip C. E.↗

Modeling of Non-Isothermal Cryogenic Fluid Sloshing

A computational fluid dynamic model was used to simulate the thermal destratification in an upright self-pressurized cryostat approximately half-filled with liquid nitrogen and subjected to forced sinusoidal lateral shaking. A full three-dimensional computational grid was used to model the tank dynamics, fluid flow and thermodynamics using the ANSYS Fluent code. A non-inertial grid was used which required the addition of momentum and energy source terms to account for the inertial forces, energy transfer and wall reaction forces produced by the shaken tank. The kinetics-based Schrage mass transfer model provided the interfacial mass transfer due to evaporation and condensation at the sloshing interface. The dynamic behavior of the sloshing interface, its amplitude and transition to different wave modes, provided insight into the fluid process at the interface. The tank pressure evolution and temperature profiles compared relatively well with the shaken cryostat experimental test data provided by the Centre National D'Etudes Spatiales.

Cryogenics↗

Accelerated Discovery of Solar Thermochemical Hydrogen Production Materials via High-Throughput Computational and Experimental Methods

In this project, combinatorial synthesis and testing methods were combined with high-throughput materials theory calculations to greatly accelerate the discovery of thermodynamically suitable candidates for green hydrogen production via a two-stage solar thermochemical water splitting (STCH) process. Over the course of the project, more than 8000 quinary and higher oxide compositions were computationally screened for STCH viability, and detailed stability calculations were performed for more than 30 of the most promising identified compositional archetypes. As a result, three new STCH capable compositional families were discovered and experimentally verified. The first, Ce x Sr 2-x MnO 4 (CSM), represents the first known Ruddlesden-Popper compound to show STCH activity, and thus demonstrates that perovskite-related structures may hold promise for this application. The second family, Sr 1-x Ce x MnO 3 (SCM), is the simple perovskite sister-analog to CSM. Sr 0.7 Ce 0.3 MnO 3 (SCM30), a member of this compositional family, was found to produce the highest hydrogen yields of any compound tested in this project, exceeding the end of project milestone target of > 150 μmol H 2 /gram oxide at a reduction temperature of 1350 °C, although only at steam-to-hydrogen ratios greater than 1000:1. Finally, we proved that a third novel Sr-and Mn-containing family, Sr 1-x Ca x Ti 1-y Mn y O 3 (SCTM), which was identified by Materials Project tools, also splits water. The behavior of the SCTM system was found to be similar to the previously discovered Sr 1-x La x Al 1-y Mn y O 3 (SLMA) family, albeit with lower H 2 yields. Across the three thrusts of the project (computational, combinatorial, and bulk testing), five journal articles were published. As part of Program End Analysis and Data Dissemination, relevant data used for the publications was uploaded to the HydroGEN Data Hub for public access, and in certain cases, results were added to public materials databases.

08 HYDROGEN↗

Acceleration of Solvation Free Energy Calculation via Thermodynamic Integration Coupled with Gaussian Process Regression and Improved Gelman–Rubin Convergence Diagnostics

The determination of the solvation free energy of ions and molecules holds profound importance across a spectrum of applications spanning chemistry, biology, energy storage, and the environment. Molecular dynamics simulations are powerful tools for computing this critical parameter. Nevertheless, the accurate and efficient calculation of the solvation free energy becomes a formidable endeavor when dealing with complex systems characterized by potent Coulombic interactions and sluggish ion dynamics and, consequently, slow transition across various metastable states. Here, in the present study, we expose limitations stemming from the conventional calculation of the statistical inefficiency g in the thermodynamic integration method, a factor that can hinder the determination of convergence of the solvation free energy and its associated uncertainty. Instead, we propose a robust scheme based on Gelman–Rubin convergence diagnostics. We leverage this improved estimation of uncertainties to introduce an innovative accelerated thermodynamic integration method based on the Gaussian Process regression. This methodology is applied to the calculation of the solvation free energy of trivalent rare-earth elements immersed in ionic liquids, a scenario in which the aforementioned challenges render standard approaches ineffective. The proposed method proves to be effective in computing solvation free energy in situations where traditional thermodynamic integration methods fall short.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Should We Conserve Entropy or Energy when Computing CAPE with Mixed-Phase Precipitation Physics?

Abstract The rapidly increasing resolution of global atmospheric reanalysis and climate model datasets necessitates finding methods for computing convective available potential energy (CAPE) both efficiently and accurately. To this end, this article compares two common methods for computing CAPE which conserve either energy or entropy. Inaccuracies in these computations arise from both physical and numerical errors. For instance, computing CAPE with entropy conserved results in physical errors from nonequilibrium phase transitions but minimizes numerical errors because solutions are analytic at each height. In contrast, computing CAPE with energy conserved avoids these physical errors, but accumulates numerical errors that are grid-resolution-dependent because the numerical integration of a differential equation is required. Analysis of CAPE computed with large databases of soundings from the tropical Amazon and midlatitude storm environments shows that physical errors from the entropy method are typically 1%–3% as large as CAPE, which is comparable to the numerical errors from conserving energy with grid spacing of 25 and 250 m using explicit first-order and second-order integration schemes, respectively. Errors in entropy-based CAPE calculations are also insensitive to vertical grid spacing, in contrast to energy-based calculations whose error strongly scales with the grid spacing. It is shown that entropy-based methods are advantageous when intercomparing datasets with differing vertical resolution because they produce accurate and reasonably fast results that are insensitive to grid resolution, whereas a second-order energy-based method is advantageous when analyzing data with a consistent vertical resolution because of its superior computational efficiency. Significance Statement Convective available potential energy (CAPE) is a measure of instability in the atmosphere that helps forecasters and researchers understand when and where thunderstorms will form. The purpose of this article is to identify the most efficient and accurate methods for computing CAPE. Two methods are considered here, one that relates to the entropy (a measure of thermodynamic disorder) of an air parcel and one that relates to the energy of an air parcel. Results indicate that the entropy method is most accurate and insensitive to the resolution of the data used for the calculation (which can vary considerably), whereas the energy method uses the least computation time.

Peters, John M.↗

Resolving the Heat Generated from ZrO 2 Atomic Layer Deposition Surface Reactions

Abstract In situ pyroelectric calorimetry and spectroscopic ellipsometry were used to investigate surface reactions in atomic layer deposition (ALD) of zirconium oxide (ZrO 2 ). Calibrated and time‐resolved in situ ALD calorimetry provides new insights into the thermodynamics and kinetics of saturating surface reactions for tetrakis(dimethylamino)zirconium(IV) (TDMAZr) and water. The net ALD reaction heat ranged from 0.197 mJ cm −2 at 76 °C to 0.155 mJ cm −2 at 158 °C, corresponding to an average of 4.0 eV/Zr at all temperatures. A temperature dependence for reaction kinetics was not resolved over the range investigated. The temperature dependence of net reaction heat and distribution among metalorganic and oxygen source exposure is attributed to factors including growth rate, equilibrium surface hydroxylation, and the extent of the reaction. ZrO 2 ‐forming surface reactions were investigated computationally using DFT methods to better understand the influence of surface hydration on reaction thermodynamics.

Bielinski, Ashley R.↗