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At least 343 records · Page 19

Catalyzed Combustion of Bipropellants for Micro-Spacecraft Propulsion

This paper addresses the need to understand the physics and chemistry involved in propellant combustion processes in micro-scale combustors for propulsion systems on micro-spacecraft. These spacecraft are planned to have a mass less than 50 kilograms with attitude control estimated to be in the 10 milli-Newton thrust class. These combustors are anticipated to be manufactured using Micro Electrical Mechanical Systems (MEMS) technology and are expected to have diameters approaching the quenching diameter of the propellants. Combustors of this size are expected to benefit significantly from surface catalysis processes. Miniature flame tube apparatus is chosen for this study because microtubes can be easily fabricated from known catalyst materials and their simplicity in geometry can be used in fundamental simulations for validation purposes. Experimentally, we investigated the role of catalytically active surfaces within 0.4 and 0.8 mm internal diameter microtubes, with special emphases on ignition processes in fuel rich gaseous hydrogen and gaseous oxygen. Flame thickness and reaction zone thickness calculations predict that the diameters of our test apparatus are below the quenching diameter of the propellants in sub-atmospheric tests. Temperature and pressure rise in resistively heated platinum and palladium microtubes was used as an indication of exothermic reactions. Specific data on mass flow versus preheat temperature required to achieve ignition are presented. With a plug flow model, the experimental conditions were simulated with detailed gas-phase chemistry, thermodynamic properties, and surface kinetics. Computational results generally support the experimental findings, but suggest an experimental mapping of the exit temperature and composition is needed.

Schneider, Steven J.↗

Ab Initio Simulations of Temperature Dependent Phase Stability and Martensitic Transitions in NiTi

For NiTi based alloys, the shape memory effect is governed by a transition from a low-temperature martensite phase to a high-temperature austenite phase. Despite considerable experimental and computational work, basic questions regarding the stability of the phases and the martensitic phase transition remain unclear even for the simple case of binary, equiatomic NiTi. We perform ab initio molecular dynamics simulations to describe the temperature-dependent behavior of NiTi and resolve several of these outstanding issues. Structural correlation functions and finite temperature phonon spectra are evaluated to determine phase stability. In particular, we show that finite temperature, entropic effects stabilize the experimentally observed martensite (B19') and austenite (B2) phases while destabilizing the theoretically predicted (B33) phase. Free energy computations based on ab initio thermodynamic integration confirm these results and permit estimates of the transition temperature between the phases. In addition to the martensitic phase transition, we predict a new transition between the B33 and B19' phases. The role of defects in suppressing these phase transformations is discussed.

nickel titanium↗

Ab Initio Simulations of Phase Stability and Martensitic Transitions in NiTi

For NiTi based alloys, the shape memory effect is governed by a transition from a low-temperature martensite phase to a high-temperature austenite phase. Despite considerable experimental and computational work, basic questions regarding the stability of the phases and the martensitic phase transition remain unclear even for the simple case of binary, equiatomic NiTi. We perform ab initio molecular dynamics simulations to describe the temperature-dependent behavior of NiTi and resolve several of these outstanding issues. Structural correlation functions and finite temperature phonon spectra are evaluated to determine phase stability. We show that finite temperature, entropic effects stabilize the experimentally observed martensite (B19') and austenite (B2) phases while destabilizing the theoretically predicted (B33) phase. Free energy computations based on ab initio thermodynamic integration confirm these results and permit estimates of the transition temperature between the phases. In addition to the martensitic phase transition, we predict a new transition between the B33 and B19' phases. The role of defects in suppressing phase transformation temperatures is discussed.

Simulations↗

Towards Accurate and Efficient Predictions of Martensitic Transition Temperatures for Shape Memory Alloys from First Principles

Recent rapid progresses in physics theory and computational power have made it possible to predict the martensitic transition temperatures (MTTs) in shape memory alloys (SMAs) from first principles [1-3]. In particular, rigorous while time-consuming thermodynamic integration has been employed to compute the anharmonic phonon free energies, which play a crucial role in determining martensitic phase transitions in SMAs. However, this approach has only been applied to simple binaries, and its accuracy is unsatisfying for certain SMAs such as the most commonly used NiTi. In this work, we report on several new developments to our method that bring first-principles theory and experiment much closer into agreement including the MTT of NiTi, and that improve the computational efficiency significantly. We have applied our refined approach to investigate the Ni0.5Ti0.5-xHfx and PdxNi0.5-xTi0.5 ternaries, and the predicted MTT for each composition is within 100K compared with experiment. We will address various techniques to overcome the difficulty encountered in studying ternaries. Our theoretical approach is expected to be a broadly applicable and predictive theory for designing complex SMAs with desirable properties. [1] J.B. Haskins, A.E. Thompson,and J.W. Lawson, Phys. Rev B 94, 214110 (2016). [2] J.B. HaskinsandJ.W. Lawson, J. App. Phys. 121, 205103 (2017). [3] J.B. Haskins, H. Malmir, S. J. Honrao, L. A. Sandoval, and J.W. Lawson, Acta Materialia 212, 116872 (2017).

Zhigang Wu↗

Towards Accurate and Efficient Predictions of Martensitic Transition Temperatures for Shape Memory Alloys from First Principles

Recent rapid progresses in physics theory and computational power have made it possible to predict the martensitic transition temperatures (MTTs) in shape memory alloys (SMAs) from first principles [1-3]. In particular, rigorous while time-consuming thermodynamic integration has been employed to compute the anharmonic phonon free energies, which play a crucial role in determining martensitic phase transitions in SMAs. However, this approach has only been applied to simple binaries, and its accuracy is unsatisfying for certain SMAs such as the most commonly used NiTi. In this work, we report on several new developments to our method that bring first-principles theory and experiment much closer into agreement including the MTT of NiTi, and that improve the computational efficiency significantly. We have applied our refined approach to investigate the Ni0.5Ti0.5-xHfx and PdxNi0.5-xTi0.5 ternaries, and the predicted MTT for each composition is within 100K compared with experiment. We will address various techniques to overcome the difficulty encountered in studying ternaries. Our theoretical approach is expected to be a broadly applicable and predictive theory for designing complex SMAs with desirable properties.

Zhigang Wu↗

Computing Free Energies with Fluctuation Relations on Quantum Computers

One of the most promising applications for quantum computers is the dynamic simulation of quantum materials. Current hardware, however, sets stringent limitations on how long such simulations can run before decoherence begins to corrupt results. The Jarzynski equality, a fluctuation theorem that allows for the computation of equilibrium free energy differences from an ensemble of short, non-equilibrium dynamics simulations, can make use of such short-time simulations on quantum computers. Here, we present a quantum algorithm based on the Jarzynski equality for computing free energies of quantum materials. We demonstrate our algorithm using the transverse field Ising model on both a quantum simulator and real quantum hardware. As the free energy is a central thermodynamic property that allows one to compute virtually any equilibrium property of a physical system, the ability to perform this algorithm for larger quantum systems in the future has implications for a wide range of applications including the construction of phase diagrams, prediction of transport properties and reaction constants, and computer-aided drug design.

Bassman, Lindsay↗

From molecular to macroscopic: predicting liquid–liquid phase equilibria and small-angle scattering of mixtures of organic liquids from atomistic simulation using Kirkwood–Buff theory

Macroscopic phase equilibria between solutions define the functionality of many biological and industrial processes, yet they are challenging to predict due to the inherent complexity of liquids containing large molecules. This work introduces an approach for the purely predictive calculation of such phase equilibria in temperature-composition space from molecular dynamics (MD) simulations at one temperature in the single-phase region. We use an approach developed previously to obtain the entropic and enthalpic contributions to the free energy of mixing from the atomic-scale information given by MD simulations via Kirkwood–Buff theory. This allows us to accurately estimate the free energy of mixing as a function of temperature, and thus obtain liquid–liquid phase equilibria, including liquid–liquid critical points, associated binodal and spinodal lines, and composition fluctuations across a region of temperature and composition. Results for binary malonamide–alkane systems are validated by comparison to a direct experimental probe of the fluctuations: the small angle X-ray scattering intensity near zero wavenumber. The MDKB → Phase method demonstrated here provides a significant improvement in predicting liquid–liquid equilibria and free energy as a function of temperature for our systems of interest compared to conventional thermodynamic models. The accurate performance of this purely predictive approach lies in its preservation of atomistic details when determining thermodynamic properties. Furthermore, its inherent extensibility to multi-component systems will likely make the MDKB → Phase approach a valuable general tool for connecting molecular interactions to macroscopic phase equilibria and for the computational screening of materials for targeted thermodynamic behavior.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tuning Proton Transfer Thermodynamics in SARS-CoV-2 Main Protease: Implications for Catalysis and Inhibitor Design

The catalytic reaction in SARS-CoV-2 main protease is activated by a proton transfer (PT) from Cys145 to His41. The same PT is likely also required for the covalent binding of some inhibitors. Here we use a multiscale computational approach to investigate the PT thermodynamics in the apo enzyme and in complex with two potent inhibitors, N3 and the α-ketoamide 13b. We show that with the inhibitors the free energy cost to reach the charge-separated state of the active-site dyad is lower, with N3 inducing the most significant reduction. We also show that a few key sites (including specific water molecules) significantly enhance or reduce the thermodynamic feasibility of the PT reaction, with selective desolvation of the active site playing a crucial role. The approach presented is a cost-effective procedure to identify the enzyme regions that control the activation of the catalytic reaction and is thus also useful to guide the design of inhibitors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Computerized systems analysis and optimization of aircraft engine performance, weight, and life cycle costs

The computational techniques utilized to determine the optimum propulsion systems for future aircraft applications and to identify system tradeoffs and technology requirements are described. The characteristics and use of the following computer codes are discussed: (1) NNEP - a very general cycle analysis code that can assemble an arbitrary matrix fans, turbines, ducts, shafts, etc., into a complete gas turbine engine and compute on- and off-design thermodynamic performance; (2) WATE - a preliminary design procedure for calculating engine weight using the component characteristics determined by NNEP; (3) POD DRG - a table look-up program to calculate wave and friction drag of nacelles; (4) LIFCYC - a computer code developed to calculate life cycle costs of engines based on the output from WATE; and (5) INSTAL - a computer code developed to calculate installation effects, inlet performance and inlet weight. Examples are given to illustrate how these computer techniques can be applied to analyze and optimize propulsion system fuel consumption, weight, and cost for representative types of aircraft and missions.

Fishbach, L. H.↗

Pitfalls in parameters: practical process development in chemical vapor processing of SiC

Vapor processing of high-value materials, such as silicon carbide (SiC), is of interest for many industries, including aerospace and energy production. Chemical vapor infiltration (CVI) of additively manufactured components is an especially attractive manufacturing process currently in development. Here, a novel development workflow is demonstrated with the H 2 –CH 3 SiCl 3 gas system for SiC to accelerate the process optimization of CVI SiC. A combination of calculated thermodynamics and high-throughput experimental chemical vapor deposition (CVD) coatings substantially reduced the experiments required with slow CVI processes. The computational results accurately predicted changes in the thermodynamic conditions tested, while CVD coatings – characterized by Raman spectroscopy – addressed changes in kinetic parameters. This workflow is also applicable to other vapor-processing systems, such as pyrolytic carbon, ZrC, or Si 3 N 4 .

Lamm, Benjamin W. [Oak Ridge National Laboratory (↗

Polynomial approximations of thermodynamic properties of arbitrary gas mixtures over wide pressure and density ranges

Computer programs for flow fields around planetary entry vehicles require real-gas equilibrium thermodynamic properties in a simple form which can be evaluated quickly. To fill this need, polynomial approximations were found for thermodynamic properties of air and model planetary atmospheres. A coefficient-averaging technique was used for curve fitting in lieu of the usual least-squares method. The polynomials consist of terms up to the ninth degree in each of two variables (essentially pressure and density) including all cross terms. Four of these polynomials can be joined to cover, for example, a range of about 1000 to 11000 K and 0.00001 to 1 atmosphere (1 atm = 1.0133 x 100,000 N/m sq) for a given thermodynamic property. Relative errors of less than 1 percent are found over most of the applicable range.

Allison, D. O.↗

Use of Tabulated Thermochemical Data for Pure Compounds

Thermodynamic data for inorganic compounds is found in a variety of tabulations and computer databases. An extensive listing of sources of inorganic thermodynamic data is provided. The three major tabulations are the JANAF tables. Thermodynamic Properties of Individual Substances, and the tabulation by Barin. The notation and choice of standard states is different in each of these tabulations, so combining data from the different tabulations is often a problem. By understanding the choice of standard states, it is possible to develop simple equations for conversion of the data from one form to another.

Jacobson, Nathan S.↗

Experimental and computational design tools for industrial drying processes: Challenges in process‐limit prediction

Abstract The coating and drying of inks and slurries are important steps to manufacture a plethora of products. Drying processes, particularly, comprise energy‐intensive steps that affect product cost and quality. Prior work has highlighted failures of various multicomponent diffusivity models to conserve mass in dryer modeling and challenges in predicting process limits given variability in published values of key thermodynamic parameters. Herein, we develop a computational model and benchtop drying experiments to investigate these concerns for drying polymer‐laden coatings. Model predictions of process limits in a single‐zone drying oven demonstrate that published variability in Flory–Huggins parameter yields large variations in predicted operating temperatures above which blistering occurs. This indicates that caution should be exercised when choosing approaches to obtain or predict the Flory–Huggins parameter, and that both benchtop drying experiments and a set of additional experiments, such as sorption experiments, are needed to fully characterize and optimize a given drying process.

Parrish, Chance↗

A study of the optimization method used in the NAVY/NASA gas turbine engine computer code

Sources of numerical noise affecting the convergence properties of the Powell's Principal Axis Method of Optimization in the NAVY/NASA gas turbine engine computer code were investigated. The principal noise source discovered resulted from loose input tolerances used in terminating iterations performed in subroutine CALCFX to satisfy specified control functions. A minor source of noise was found to be introduced by an insufficient number of digits in stored coefficients used by subroutine THERM in polynomial expressions of thermodynamic properties. Tabular results of several computer runs are presented to show the effects on program performance of selective corrective actions taken to reduce noise.

Horsewood, J. L.↗

Structural and Mechanistic Advances in the Chemistry of Methyl-Coenzyme M Reductase (MCR)

Methane represents 34% of U.S. energy consumption and is a major greenhouse gas related to the global carbon cycle and energy production. However, current industrial practices significantly increase atmospheric methane levels, necessitating a deeper understanding of its biosynthesis and oxidation. Methyl-coenzyme M reductase (MCR) is central to biological methane metabolism, catalyzing the final step of methanogenesis and the first step in anaerobic methane oxidation. It is also a key target for strategies to capture and transform methane into value-added chemicals.The active site of MCR is a buried Ni-based cofactor only accessible by the substrates via a 50 Å long tunnel. Although the Ni(I) state is required to initiate catalysis, capturing this state remains a challenge for the current structural techniques. Recent advances in structural biology using X-ray Free-Electron Laser serial crystallography have provided insights into MCR's inactive Ni(II) state at room temperature and show promise for capturing its active Ni(I) form.Our team has established several critical aspects of the MCR mechanism using a combination of experimental and computational studies. MCR uses CH 3 -SCoM and CoBSH as substrates, producing methane and a disulfide product CoMSSCoB. Kinetic analysis showed that productive substrate binding requires CH 3 -SCoM to bind first, inducing conformational changes that optimize the active site for subsequent CoBSH binding. Following substrate binding, four proposed methane production/oxidation mechanisms were examined, establishing whether the reaction proceeds through an organometallic methyl-nickel(III), methyl anion ion, or methyl radical intermediate. Experimental measurements using CoBSH analogs successfully slowed the reaction, allowing for mechanistic insight that demonstrated the methyl radical pathway, where the initial interactions involve homolytic cleavage of the methyl-sulfur bond, generating a methyl radical that quickly abstracts the thiol hydrogen atom of CoBSH to form methane. Computational studies further confirmed that, compared to other mechanisms, the methyl radical mechanism is thermodynamically more favorable and accessible under physiological conditions.Spectroscopic and computational studies challenged the conventional understanding of substrate binding in MCR by proposing an alternative positioning of CH 3 -SCoM and CoMSSCoB in the active site pocket. The research suggested that CH 3 -SCoM (substrate) and CoMSSCoB (product) bind via their sulfonate groups to the Ni(I) center of cofactor F 430 . This binding allows for the reaction without substrate reorganization in the pocket but would require a long-range electron transfer. Altogether, the work summarized in this review reflects our current understanding of the enzyme's catalytic mechanism and structural dynamics. This is essential for developing efficient methane conversion technologies that could mitigate its environmental impact while harnessing energy-storage properties.

03 NATURAL GAS↗

Thermodynamic equilibrium-air correlations for flowfield applications

Equilibrium-air thermodynamic correlations have been developed for flowfield calculation procedures. A comparison between the postshock results computed by the correlation equations and detailed chemistry calculations is very good. The thermodynamic correlations are incorporated in an approximate inviscid flowfield code with a convective heating capability for the purpose of defining the thermodynamic environment through the shock layer. Comparisons of heating rates computed by the approximate code and a viscous-shock-layer method are good. In addition to presenting the thermodynamic correlations, the impact of several viscosity models on the convective heat transfer is demonstrated.

Zoby, E. V.↗

Equations of State in Computational Physics: What, Why, and How

Summary: 1. Equations of state furnish thermodynamic properties of a material. 2. Usually involve P, p (or V), and T, or P, r, and E 3. Necessary ingredient to solve compressible flow problems. 4. Varieties: i. Analytical expressions (ideal gas, Grüneisen) – fast, convenient for verification and test problems ii. Graphs and charts – good for hand calculations iii. Tables and databases – generally most accurate, require interpolation i. Steam tables ii. NIST database iii. SESAME EOS Library 5. Constructed by using semi-empirical models from Statistical Mechanics and fitting to available data

36 MATERIALS SCIENCE↗