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At least 487 records · Page 27

The thermal and plasma-physical evolution of laminar current sheets formed in the solar atmosphere by emerging flux

A time-dependent analysis of emerging flux is carried out, and the time evolution of both the current sheet energetics and the plasma state is calculated. This evolution is determined in two different regimes. In the first case the width of the current sheet is assumed to be independent of the sheet thermodynamics and is fixed by the initial conditions. In the second, the width of the current sheet is a function of the resistivity and is allowed to decrease to its minimum given by the electron gyroradius. In both cases the resistivity is computed according to the marginal stability hypothesis. In each case the thermodynamic evolution is found to be quite rapid, with the temperature increasing from 10,000 to 1,000,000 K in a second or less. In contrast to previous studies, it is found that the resistivity is not significantly enhanced by the current-driven plasma wave turbulence. It is concluded that a laminar current sheet cannot be responsible for the activity associated with emerging flux.

Larosa, T. N.↗

Machine Learning-Accelerated First-Principles Molecular Dynamics Reveals C–C Coupling Mechanisms toward Ethylene on Cu(100)

Here, the Cu(100) termination has been identified as the most effective facet for converting CO and CO 2 into ethylene. To enhance both the activity and selectivity of ethylene production, we perform machine-learning-accelerated, first-principles molecular dynamics simulations at 298 K in an explicit solvent at pH 7 to elucidate the C–C coupling mechanism─the critical reaction step in forming C 2+ products. Among the six potential C–C coupling pathways, the most feasible are CO* dimerization and CO – CHO* and CHO* – CHO* couplings. Using the computational hydrogen electrode method, we demonstrate that all three pathways are equally accessible at −0.6 V vs RHE. At a potential below −1.0 V vs RHE, the thermodynamic barriers for the CO – CHO* and CHO* – CHO* pathways become negligible. Our computational findings explain the experimental observations, particularly the absence of C 2+ products above −0.4 V vs RHE and the peaks in ethylene production near −0.6 and −1.0 V vs RHE. Since CHO* acts as a key intermediate common to both C–C coupling and CH 4 formation, we propose that suppressing CHO* hydrogenation would inhibit CH 4 pathways, thereby maximizing ethylene selectivity.

CO2 reduction↗

Theoretical Prediction of Thermal Expansion Anisotropy for Y 2 Si 2 O 7 Environmental Barrier Coatings Using a Deep Neural Network Potential and Comparison to Experiment

Environmental barrier coatings (EBCs) are an enabling technology for silicon carbide (SiC)-based ceramic matrix composites (CMCs) in extreme environments such as gas turbine engines. However, development of new coating systems is hindered by the large design space and difficulty in predicting properties for these materials. Density Functional Theory (DFT) has successfully been used to model and predict some thermodynamic and thermo-mechanical properties of high-temperature ceramics for EBCs, although these calculations are challenging due to their high computational costs. In this work, we use machine learning to train a deep neural network potential (DNP) for Y 2 Si 2 O 7 , which is then applied to calculate thermodynamic and thermo-mechanical properties at near-DFT accuracy much faster and using less computational resources than DFT. We use this DNP to predict phonon-based thermodynamic properties of Y 2 Si 2 O 7 with good agreement to DFT and experiments. We also utilize the DNP to calculate the anisotropic, lattice direction-dependent coefficients of thermal expansion (CTEs) for Y 2 Si 2 O 7 . Molecular dynamics trajectories using the DNP correctly demonstrate accurate prediction of the anisotropy of the CTE in good agreement with diffraction experiments. In the future, this DNP could be applied to accelerate additional property calculations for Y 2 Si 2 O 7 compared to DFT or experiments.

rare earth silicates↗

High speed inlet calculations with real gas effects

A 2-D steady-state Navier-Stokes solver has been upgraded to include the effects of frozen and equilibrium air chemistry for applications to high speed flight vehicles. To provide a computationally economical first order approximation to the high temperature physics, variable thermodynamic data is used for the chemically frozen mode to allow for a variation with temperature of the air specific heats and enthalpy. For calculations involving air in chemical equilibrium, a specially modified version of the NASA Lewis Chemical Equilibrium Code, CEC, is used to compute the chemical composition and resultant thermochemical properties. The upgraded solver is demonstrated by comparing results from calorically perfect (C sub p=constant), thermally perfect (frozen) and equilibrium air calculations for a variety of geometries, and flight Mach numbers.

Coirier, William J.↗

High speed inlet calculations with real gas effects

A 2-D steady-state Navier-Stokes solver has been upgraded to include the effects of frozen and equilibrium air chemistry for applications to high speed flight vehicles. To provide a computationally economical first order approximation to the high temperature physics, variable thermodynamic data is used for the chemically frozen mode to allow for a variation with temperature of the air specific heats and enthalpy. For calculations involving air in chemical equilibrium, a specially modified version of the NASA Lewis Chemical Equilibrium Code, CEC, is used to compute the chemical composition and resultant thermochemical properties. The upgraded solver is demonstrated by comparing results from calorically perfect (C sub p=constant), thermally perfect (frozen) and equilibrium air calculations for a variety of geometries, and flight Mach numbers.

Coirier, William J.↗

A simple method for obtaining heat capacity coefficients of minerals

Abstract Heat capacity data are unavailable or incomplete for many minerals at geologically relevant temperatures. Despite the availability of entropy and enthalpy values in numerous thermodynamic tables (even sometimes at elevated temperatures), there remains need for extrapolation beyond, or interpolation between, temperatures. This approach inevitably results in estimates for entropy and enthalpy values because the heat capacity coefficients required for optimal thermodynamic treatment are less frequently available. Here we propose a simple method for obtaining heat capacity coefficients of minerals. This method requires only the empirically measured temperature-specific heat capacity for calculation via a matrix algorithm. The system of equations solver is written in the Python computing language and has been made accessible in an online repository. Thermodynamically, the solution to a system of equations represents the heat capacity coefficients that satisfy the mineral-specific polynomial. Direct coefficient calculation will result in more robust thermodynamic data, which are not subject to fitting uncertainties. Using hematite as an example, this method provides results that are comparable to conventional means and is applicable to any solid material. Coefficients vary within the traditional large 950 K temperature interval, indicating that best results should instead utilize a smaller 400 K temperature interval. Examples of large-scale implications include the refinement of geothermal gradient estimation in rapidly subsiding sedimentary basins or metamorphic and hydrothermal evolution.

Geochemistry & Geophysics↗

Theoretical Prediction of Thermal Expansion Anisotropy for Y 2 Si 2 O 7 Environmental Barrier Coatings Using a Deep Neural Network Potential and Comparison to Experiment

Environmental barrier coatings (EBCs) are an enabling technology for silicon carbide (SiC)-based ceramic matrix composites (CMCs) in extreme environments such as gas turbine engines. However, the development of new coating systems is hindered by the large design space and difficulty in predicting the properties for these materials. Density Functional Theory (DFT) has successfully been used to model and predict some thermodynamic and thermo-mechanical properties of high-temperature ceramics for EBCs, although these calculations are challenging due to their high computational costs. In this work, we use machine learning to train a deep neural network potential (DNP) for Y 2 Si 2 O 7 , which is then applied to calculate the thermodynamic and thermo-mechanical properties at near-DFT accuracy much faster and using less computational resources than DFT. We use this DNP to predict the phonon-based thermodynamic properties of Y 2 Si 2 O 7 with good agreement to DFT and experiments. We also utilize the DNP to calculate the anisotropic, lattice direction-dependent coefficients of thermal expansion (CTEs) for Y 2 Si 2 O 7 . Molecular dynamics trajectories using the DNP correctly demonstrate the accurate prediction of the anisotropy of the CTE in good agreement with the diffraction experiments. In the future, this DNP could be applied to accelerate additional property calculations for Y 2 Si 2 O 7 compared to DFT or experiments.

36 MATERIALS SCIENCE↗

Additively manufactured Ni-20Cr to V functionally graded material: Computational predictions and experimental verification of phase formations

Throughout this work, a database for the Cr-Ni-V system was constructed by modeling the binary Cr-V and ternary Cr-Ni-V systems using the CALPHAD approach aided by density functional theory (DFT)-based first-principles calculations and ab initio molecular dynamics (AIMD) simulations. To validate this new database, a functionally graded material (FGM) using Ni-20Cr and elemental V was fabricated using directed energy deposition additive manufacturing (DED AM) and experimentally characterized. The deposited Ni-20Cr was pure fcc phase, while increasing the amount of V across the gradient resulted in the formation of sigma phase, followed by the bcc phase. The experimentally measured phase data was compared with computational predictions made using a Cr-Ni-V thermodynamic database from the literature as well as the database developed in the present work. The newly developed database was shown to better predict the experimentally observed phases due to its accurate modeling of binary systems within the database and the ternary liquid phase, which is critical for accurate Scheil calculations.

36 MATERIALS SCIENCE↗

Direct aromatization of CO 2 via combined CO 2 hydrogenation and zeolite-based acid catalysis

Aromatics, including benzene, toluene, and xylenes (BTX), are essential chemical building blocks and are widely used as solvents, fuel additives, and polymers. With the recent development in CO 2 capture technologies and the progress made in producing H 2 using renewable energy, direct hydrogenation of CO 2 to aromatics via heterogeneous catalysis has emerged as a promising pathway to accomplish the production of aromatics with simultaneous utilization of waste CO 2 . In this review, we focus on recent advances in the nascent field of direct CO 2 aromatization, whereby tandem catalysts composed of CO 2 hydrogenation and aromatization functionalities are designed and deployed. We review two categories of tandem catalysts: catalysts integrating Fe-based/H-ZSM-5 components following RWGS (reverse water-gas shift of CO 2 to CO)-FT (Fischer-Tropsch synthesis of lower olefins)-aromatization pathways, and catalysts combining metal oxide/H-ZSM-5 domains following CO 2 to methanolaromatization pathways. The key parameters that determine the catalytic performance, such as the composition and structure of the Fe-based or metal oxide-based CO 2 conversion catalysts, the properties of H-ZSM-5, and the synergy between the two components, are analyzed to provide insights for the design of efficient tandem catalysts for CO 2 aromatization. In parallel, thermodynamic analyses, mechanistic studies, and density functional theory (DFT) computations for the relevant reaction routes and pathways are discussed to offer improved understanding of CO 2 activation, reaction intermediates, and product formation. In closing, the challenges and prospects for these tandem reactions are addressed to provide suggested paths forward for future research.

10 SYNTHETIC FUELS↗

Impact of fission product inclusion on phase development in U 3 Si 2 fuel

Due to its high thermal conductivity and uranium density, U 3 S i2 has been considered as a candidate for use as an accident tolerant fuel (ATF). In order to fully assess its suitability and performance as a fuel, the impact of fission products (FPs) on the stability and performance of U 3 Si 2 must be investigated. The interactions of FPs and U 3 Si 2 have had relatively little study until now and require experimental and computational examination. U 3 Si 2 was doped with individual FPs to explore U-Si-FP interactions and phase equilibria that may impact the performance of the ATF during irradiation. Elemental Ce, Mo, Y, or Zr were used to individually dope U 3 Si 2 at a concentration of 5 wt% FP. A diffusion couple of a 1:1 Mo:Zr alloy and U 3 Si 2 was heated to 1200 °C in order to consider the impacts of multiple FPs on the stability and structure of the fuel. Samples were characterized for FP solubility and secondary phase formation using electron microscopy, energy dispersive spectroscopy, and x-ray diffraction. First principles density functional theory calculations complemented the experimental effort to understand FP behavior. Experimental and computational findings were used in the development of a thermodynamic database containing 8 major FPs and their associated silicide phases. Finally, fuel compositions generated from depletion calculations were used to thermodynamically model the equilibrium phases of the fuel undergoing burnup.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Itinerant Magnetism in Hydride-Synthesized CaCo 12 B 6

A new compound in the underexplored Ca–Co–B phase space has been discovered, validating high-throughput computations from the Open Quantum Materials Database, which predicted thermodynamic stability for CaCo 12 B 6 in the SrNi 12 B 6 structure type. The synthetic effects of different boron precursors and the advantages of using CaH 2 instead of Ca metal were demonstrated by the short synthesis duration and high purity of CaCo 12 B 6 , in contrast with traditional synthesis routes. Powder X-ray diffraction (PXRD) confirmed that CaCo 12 B 6 shares the SrNi 12 B 6 structure ( R $\bar{3}$m (#166), a = 9.469(4) Å, c = 7.468(2) Å, Z = 3) and is water- and air-stable. High-temperature in situ PXRD indicates that CaCo 12 B 6 is stable below 1050 K under vacuum in a silica capillary. CaCo 12 B 6 decomposes between 693 and 773 K during spark-plasma sintering. Density functional theory calculations indicate that CaCo 12 B 6 is metallic with a ferromagnetic ground state. X-ray absorption near-edge spectroscopy and Bader charge analysis indicate that Co atoms in CaCo 12 B 6 lack ionic character. Magnetometry reveals room-temperature paramagnetism with μ eff = 1.7(1)μ B per Co atom and a Weiss constant of +190(10)K. Ferromagnetic ordering occurs below 172(1)K, resulting in a saturation moment of 0.46 μ B per Co atom. Our findings demonstrate that the hydride route is a viable strategy for discovery of new ternary alkaline-earth-transition metal borides analogous to rare-earth-containing counterparts.

diffraction↗

Solution Chemistry to Control Boron-Containing Monolayers on Silicon: Reactions of Boric Acid and 4-Fluorophenylboronic Acid with H- and Cl-terminated Si(100)

In this work, the reactions of boric acid and 4-fluorophenylboronic acid with H- and Cl-terminated Si(100) surfaces in solution were investigated. X-ray photoelectron spectroscopy (XPS) studies reveal that both molecules react preferentially with Cl–Si(100) and not with H–Si(100) at identical conditions. On Cl–Si(100), the reactions introduce boron onto the surface, forming a Si–O–B structure. The quantification of boron surface coverage demonstrates that the 4-fluorophenylboronic acid leads to ~2.8 times higher boron coverage compared to that of boric acid on Cl–Si(100). Consistent with these observations, density functional theory studies show that the reaction of boric acid and 4-fluorophenylboronic acid is more favorable with the Cl- versus H-terminated surface and that on Cl–Si(100) the reaction with 4-fluorophenylboronic acid is ~55.3 kJ/mol more thermodynamically favorable than the reaction with boric acid. The computational studies were also used to demonstrate the propensity of the overall approach to form high-coverage monolayers on these surfaces, with implications for selective-area boron-based monolayer doping.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electrolyte-Dependent, “Microscopically Irreversible” H-Atom Transfer Kinetics of Ce-Based Metal–Organic Framework, Ce-MOF-808

Redox reactions at the interface of metal oxides and protic electrolytes almost always involve protons and electrons in equal amounts. Given the stoichiometry, these proton-coupled electron transfer (PCET) reactions are thermochemically equivalent to net H-atom transfer (HAT) reactions. The correlation between the chemical nature of solid catalysts and HAT kinetics has been employed for decades as the design principle for energy-relevant reactions (e.g., reactions of 2H + /H 2 ). More recently, chemists have experimentally determined that a change in liquid electrolytes that alters the microenvironment at the redox-active sites has an equally profound impact on electrocatalysis involving PCET/HAT. Yet, precise correlations between the chemical nature of electrolytes and the PCET kinetics are, to date, rare in the literature. Herein, we report our findings using the Ce-based metal−organic framework, Ce-MOF-808, as a model system. Each Ce 6 (μ 3 −O) 4 (μ 3 − OH) 4 (OH) 6 (H 2 O) 6 node of this MOF undergoes a 1H + /1e − redox reaction. Using chronoamperometry and the Cottrell analysis, we have determined that the PCET hopping kinetics within the pores of Ce-MOF-808 can change by orders of magnitude by altering the buffer species and the proton activity of the electrolyte. Furthermore, in all buffers, reductive reactions were ∼3−10 times faster in kinetics than the reverse oxidative reaction with the same electrochemical driving force, suggesting that the system, at first glance, violates the principle of microscopic reversibility. Isothermal titration calorimetry (ITC) and computational simulations corroborated that the buffer-node binding thermodynamics are quite distinct, depending on the chemical nature of the buffer and the oxidation state of the node. Together, these results suggest that the substrate and the product during the oxidative vs reductive reaction of Ce-MOF-808 are chemically different species, which explains the apparent ‘microscopic irreversibility.’ Thus, the rational modulation of electrolytes can dramatically enhance PCET kinetics, even though the solid electrodes remain identical. Implications of these findings are contrasted with the electrochemical/electrocatalytic behavior of other redox-active MOFs, heterogeneous catalysts, and enzymatic systems at the solid−liquid interface.

Ce-based MOF↗

Two-dimensional ruthenium boride: a Dirac nodal loop quantum electrocatalyst for efficient hydrogen evolution reaction

Catalysts with high carrier mobility, high activity, and an active basal plane have been highly sought for the hydrogen evolution reaction (HER). However, combining these advantages into one single material is a grand challenge. Herein, using first principles computations, we predicted that a two-dimensional (2D) Dirac nodal loop semimetal, namely the RuB 4 monolayer, is promising as a superior catalyst for the HER. Our systematic computations showed that the single layer RuB 4 is thermodynamically, dynamically, mechanically, and thermally stable and presents multiple Ru and B sites for the HER on the basal plane. The estimated Gibbs free energy for hydrogen adsorption at a Ru site is approaching zero (–8.8 meV), suggesting its excellent HER performance. The RuB 4 monolayer is a Dirac nodal loop semimetal with high Fermi velocities, which can accelerate charge transfer between catalysts and reaction intermediates. The RuB 4 monolayer is an auxetic material with an out-of-plane negative Poisson's ratio, implying its novel mechanical properties. Finally, this work provides an example of using a Dirac nodal loop semimetal for high-performance HER catalysts, which is a promising alternative to the known catalysts with trivial metallic properties.

30 DIRECT ENERGY CONVERSION↗

A Note on the Effects of Linear Topology Preservation in Monte Carlo Simulations of Knotted Proteins

Monte Carlo simulations are a powerful technique and are widely used in different fields. When applied to complex molecular systems with long chains, such as those in synthetic polymers and proteins, they have the advantage of providing a fast and computationally efficient way to sample equilibrium ensembles and calculate thermodynamic and structural properties under desired conditions. Conformational Monte Carlo techniques employ a move set to perform the transitions in the simulation Markov chain. While accepted conformations must preserve the sequential bonding of the protein chain model and excluded volume among its units, the moves themselves may take the chain across itself. We call this a break in linear topology preservation. In this manuscript, we show, using simple protein models, that there is no difference in equilibrium properties calculated with a move set that preserves linear topology and one that does not. However, for complex structures, such as those of deeply knotted proteins, the preservation of linear topology provides correct equilibrium results but only after long relaxation. In any case, to analyze folding pathways, knotting mechanisms and folding kinetics, the preservation of linear topology may be an unavoidable requirement.

Especial, João N. C. (ORCID:0000000254765370)↗

Overview of heat transfer and fluid flow problem areas encountered in Stirling engine modeling

NASA Lewis Research Center has been managing Stirling engine development programs for over a decade. In addition to contractual programs, this work has included in-house engine testing and development of engine computer models. Attempts to validate Stirling engine computer models with test data have demonstrated that engine thermodynamic losses need better characterization. Various Stirling engine thermodynamic losses and efforts that are underway to characterize these losses are discussed.

Tew, Roy C., Jr.↗

DSMC simulation of ionized rarefied flows

Recently a renewed interest has been exhibited in understanding contamination and space environmental effect in the LEO range of 200 to 600 km as well as in low density microelectronics manufacturing technologies. Realistic simulations must model the physics of the highly coupled effects of neutral and charged particle flows, thermodynamic nonequilibrium, surface charging, and electromagnetic field effects. The computational requirements are enormous for this level of modeling and are almost impossible on current single processor supercomputers. An effort was initiated to develop this capability on a massively parallel MIMD supercomputers. The Wake Shield Facility experiment will be used for test case calculations. Preliminary results indicate that parallel supercomputers may be the only computers capable of simulating the required level of physics and spatial resolution. Calculations which contain from 1 to 8 million simulation particles are presented.

Bartel, Timothy J.↗

GMS-based"Future Time" Rainfall Data Assimilation for Mesoscale Weather Prediction over Korean Peninsula and Future Prospects with GPM Satellite Measurements

This study examines the use of satellite-derived nowcasted (short-term forecasted) rainfall over 3-hour time periods to gain an equivalent time increment in initializing a nonhydrostatic mesoscale model used for predicting convective rainfall events over the Korean peninsula. Infrared (IR) window measurements from the Japanese Geostationary Meteorological Satellite (GMS) are used to specify latent heating for a spinup period of the model - but in future time -- thus initializing in advance of actual time in the framework of a prediction scenario. The main scientific objective of the study is to investigate the strengths and weaknesses of this approach insofar as data assimilation, in which the nowcasted assimilation data are derived independently of the prognostic model itself. Although there have been various recent improvements in formulating the dynamics, thermodynamics, and microphysics of mesoscale models, as well as computer advances which allow the use of high resolution cloud-resolving grids and explicit latent heating over regional domains, spinup remains at the forefront of unresolved mesoscale modeling problems. In general, non-realistic spinup limits the skill in predicting the spatial-temporal distribution of convection and precipitation, primarily in the early hours of a. forecast, stemming from standard prognostic variables not representing the initial diabatic heating field produced by the ambient convection and cloud fields. The long-term goal of this research is to improve short-range (12-hour) quantitative precipitation forecasting (QPF) over the Korean peninsula through the use of innovative data assimilation methods based on geosynchronous satellite measurements. As a step in th~s direction, a non-standard data assimilation experiment in conjunction with GMS-retrieved nowcasted rainfall information introduced to the mesoscale model is conducted. The 3-hourly precipitation forecast information is assimilated through nudging the associated diabatic heating during the early stages of a forecast period. This procedure is expected to enhance details in the moisture field during model integration, and thus improve spinup performance, assuming the errors in the future time latent heating data ate less than intrinsic model background errors.

Smith, Eric A.↗