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At least 1,387 records · Page 77

Isentropic Analysis of Convective Motions

This paper analyzes the convective mass transport by sorting air parcels in terms of their equivalent potential temperature to determine an isentropic streamfunction. By averaging the vertical mass flux at a constant value of the equivalent potential temperature, one can compute an isentropic mass transport that filters out reversible oscillatory motions such as gravity waves. This novel approach emphasizes the fact that the vertical energy and entropy transports by convection are due to the combination of ascending air parcels with high energy and entropy and subsiding air parcels with lower energy and entropy. Such conditional averaging can be extended to other dynamic and thermodynamic variables such as vertical velocity, temperature, or relative humidity to obtain a comprehensive description of convective motions. It is also shown how this approach can be used to determine the mean diabatic tendencies from the three-dimensional dynamic and thermodynamic fields. A two-stream approximation that partitions the isentropic circulation into a mean updraft and a mean downdraft is also introduced. This offers a straightforward way to identify the mean properties of rising and subsiding air parcels. The results from the two-stream approximation are compared with two other definitions of the cloud mass flux. It is argued that the isentropic analysis offers a robust definition of the convective mass transport that is not tainted by the need to arbitrarily distinguish between convection and its environment, and that separates the irreversible convective overturning fromoscillations associated with gravity waves.

Lagrangian circulation↗

Defying Thermodynamics: Stabilization of Alane Within Covalent Triazine Frameworks for Reversible Hydrogen Storage

The highly unfavorable thermodynamics of direct aluminum hydrogenation can be overcome by stabilizing alane within a nanoporous bipyridine-functionalized covalent triazine framework (AlH 3 @CTF-bipyridine). This material and the counterpart AlH 3 @CTF-biphenyl rapidly desorb H 2 between 95 and 154°C, with desorption complete at 250°C. Sieverts measurements, 27 Al MAS NMR and 27 Al{ 1 H} REDOR experiments, and computational spectroscopy reveal that AlH 3 @CTF-bipyridine dehydrogenation is reversible at 60°C under 700 bar hydrogen, >10 times lower pressure than that required to hydrogenate bulk aluminum. DFT calculations and EPR measurements support an unconventional mechanism whereby strong AlH 3 binding to bipyridine results in single-electron transfer to form AlH 2 (AlH 3 ) n clusters. Here the resulting size-dependent charge redistribution alters the dehydrogenation/rehydrogenation thermochemistry, suggesting a novel strategy to enable reversibility in high-capacity metal hydrides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Defying Thermodynamics: Stabilization of Alane Within Covalent Triazine Frameworks for Reversible Hydrogen Storage

Metastable metal hydrides such as AlH 3 have many attractive features as hydrogen storage media, but generally require complex reaction schemes for regeneration following H 2 release. Here in this paper, we demonstrate that the highly unfavorable thermodynamics of direct aluminum hydrogenation can be overcome by stabilizing alane within a nanoporous bipyridine-functionalized Covalent Triazine Framework (AlH 3 @CTF-bipyridine). This material and the counterpart AlH 3 @CTF-biphenyl rapidly desorb H 2 between 95 and 154 °C, with desorption complete at 250 °C. Sieverts measurements, 27 Al MAS NMR and 27 Al{ 1 H} REDOR experiments, and computational spectroscopy reveal that AlH 3 @CTF-bipyridine dehydrogenation is reversible at 60 °C under 700 bar hydrogen, >10 times lower pressure than that required to hydrogenate bulk aluminum. DFT calculations and EPR measurements support an unconventional mechanism whereby strong AlH 3 binding to bipyridine results in single-electron transfer to form AlH 2 (AlH 3 ) n clusters. The resulting size-dependent charge redistribution alters the dehydrogenation/rehydrogenation thermochemistry, suggesting a novel strategy to enable reversibility in high-capacity metal hydrides.

Coordination Chemistry↗

Gradient-informed Hamiltonian Monte Carlo for multicomponent CALPHAD model optimization and uncertainty quantification

CALPHAD model parameter optimization is inherently challenging due to non-smooth objective functions, high-dimensional parameter spaces, and the need for uncertainty quantification (UQ). Traditional weighted nonlinear least squares approaches are computationally efficient but local, whereas black-box global optimizers and ensemble Markov Chain Monte Carlo (MCMC) methods provide broader exploration at substantial computational cost. The objective of this work is to combine the global exploration capability of gradient-informed Hamiltonian Monte Carlo – specifically the No-U-Turn Sampler (NUTS) – with local deterministic refinement using BFGS to efficiently optimize multicomponent CALPHAD models with minimal manual intervention. Analytic gradients are computed via the Jansson derivative framework. The methodology is demonstrated on the Cr—Fe binary system and extended to the Cr—Fe—Ni ternary system with 32 degrees of freedom. For Cr—Fe, NUTS achieves comparable or superior optimality relative to ensemble MCMC while requiring over an order-of-magnitude fewer likelihood evaluations. Parameter uncertainties are quantified through NUTS sampling and propagated to thermodynamic observables using local expansion, demonstrating a novel modular approach that combines binary and ternary parameter subsets without requiring global relaxation. These results establish gradient-informed exploration as a scalable strategy for multicomponent CALPHAD optimization and provide a practical route towards efficient higher-order database development with quantified uncertainty.

36 MATERIALS SCIENCE↗

Photochemistry of Hypervalent Iodoazide Derivatives

The photochemical properties and reaction mechanisms of a series of hypervalent iodoazide compounds (R–IN3) were investigated, with substituents (−CH 3 , −H, −CF 3 ) tuning the electronic density of the phenyl ring. With the help of UV irradiation, ultrafast time-resolved spectroscopy, and density functional theory (DFT) calculations, we elucidated the mechanisms of azide radical (N 3 • ) release and its subsequent reactivity. UV–vis spectroscopy reveals that the photoconversion rates follow the trend CH3 > H > CF3, aligning with DFT-calculated ΔG values for ring-opening transitions. Homolytic cleavage of the I–N bond is identified as the dominant pathway for N3• generation upon UV irradiation, occurring within 400 fs. The released azide radicals react with the solvent molecules, while the iodo radical R–I C • fragments undergo a thermodynamically uphill lactone ring-opening (RO) reaction and subsequent hydrogen atom abstraction from the solvent to form carboxylic acids R–I–COOH, as validated by NMR and IR spectroscopy. The study also highlights the role of substituents in influencing reaction kinetics and intermediate stability, with electron-donating groups accelerating the release of the N 3 • species. This work bridges experimental observations with computational predictions, offering a foundation for future advancements in azide-based reactions and materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Neural network representations of multiphase Equations of State

Abstract Equations of State model relations between thermodynamic variables and are ubiquitous in scientific modelling, appearing in modern day applications ranging from Astrophysics to Climate Science. The three desired properties of a general Equation of State model are adherence to the Laws of Thermodynamics, incorporation of phase transitions, and multiscale accuracy. Analytic models that adhere to all three are hard to develop and cumbersome to work with, often resulting in sacrificing one of these elements for the sake of efficiency. In this work, two deep-learning methods are proposed that provably satisfy the first and second conditions on a large-enough region of thermodynamic variable space. The first is based on learning the generating function (thermodynamic potential) while the second is based on structure-preserving, symplectic neural networks, respectively allowing modifications near or on phase transition regions. They can be used either “from scratch” to learn a full Equation of State, or in conjunction with a pre-existing consistent model, functioning as a modification that better adheres to experimental data. We formulate the theory and provide several computational examples to justify both approaches, highlighting their advantages and shortcomings.

Science & Technology - Other Topics↗

Ba 1−x Sr x FeO 3−δ as an improved oxygen storage material for chemical looping air separation: a computational and experimental study

Chemical looping air separation (CLAS) is a promising technology to generate oxygen-rich gas streams to enable efficient carbon dioxide capture during fossil fuel combustion or gasification. CLAS relies on the capture and release of oxygen from the atmosphere using the redox properties of an oxygen-selective solid oxide carrier. This study investigates the redox characteristics of Ba 1−x Sr x FeO 3−δ (0.0 ≤ x ≤ 0.417, 0.0 ≤ δ ≤ 0.5) using a combination of density functional theory (DFT) calculations and experimental verification using X-ray diffraction, thermogravimetric analysis, and oxygen-temperature-programmed desorption. The DFT computed energies of the Ba 1−x Sr x FeO 3−δ perovskites reveal a composition-dependent transition from hexagonal to cubic phases as the Sr-concentration or oxygen vacancy concentration increases. Oxygen vacancy formation energies of the cubic perovskites are found to be lower than those of their hexagonal counterparts. A low oxygen diffusion barrier of ∼1 eV combined with the thermodynamic preference of Ba 1−x Sr x FeO 3−δ compositions that form in a cubic phase suggests them as promising candidates for oxygen storage applications. The experimental results corroborate this finding by identifying Ba 0.75 Sr 0.25 FeO 3−δ in the cubic phase as an optimal composition offering low-temperature oxygen storage capacities comparable to that of the state-of-the-art Sr 0.75 Ca 0.25 FeO 3−δ perovskite oxygen storage material at 325 °C and 350 °C.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Descriptors for Cu facets for CO2 reduction reaction activity

Computation screening is crucial for designing efficient electrochemical catalysts for carbon dioxide (CO2R) reduction to valuable hydrocarbons and oxygenates. Herein, leveraging density functional theory calculations of the CO adsorption energy ΔE_CO on seventeen Cu terminations, we discover a strong linear correlation between ΔE_CO and the recently experimentally measured CO2R electrochemical currents (ACS Catal. 2022, 12, 11, 6578–6588). Examining the ab initio thermodynamics of the early critical intermediates CO*, COH*, and CHO*, we find that CO* → CHO* is the thermodynamically preferred step, and notably shows a volcano trend with the experimental currents where the maximum CO2R current corresponds to the moderate CHO* formation energy. Importantly, we show that increasing the step and kink density of the Cu termination not only enhances CO adsorption strength but also modulates the CO* → CHO* pathway, as respectively exemplified in the (941) and (741) facets. We also explain why (741) is exceptional with high CO2R activity as measured experimentally due to its relatively low activity toward the hydrogen evolution reaction compared with the other Cu surfaces. Beyond the general CO adsorption energy that only shows a linear trend with CO2R activity, we show that the reaction CO* → CHO* free energy is a descriptor that displays a volcano relationship with the overall CO2R activity on Cu facets.

machine learning↗

Ab Initio Many Body Quantum Embedding and Local Correlation in Crystalline Materials using Interpolative Separable Density Fitting

We present an efficient implementation of ab initio many-body quantum embedding and local correlation methods for infinite periodic systems through translational symmetry adapted interpolative separable density fitting, an approach which reduces the scaling of the calculations to only linear with the number of k-points. Employing this methodology, we compute correlated ground-state coupled cluster energies within density matrix embedding and local natural orbital correlation frameworks for both weakly and strongly correlated solids, using up to 1000 k-points. By extrapolating the local correlation domains and k-point sampling we further obtain estimates of the full coupled cluster with singles, doubles, and perturbative triples ground-state energies in the thermodynamic limit.

Chemical Physics (physics.chem-ph)↗

Numerical Study of Contaminant Effects on Combustion of Hydrogen, Ethane, and Methane in Air

A numerical study was performed to assess the effects of vitiated air on the chemical kinetics of hydrogen, ethane, and methane combustion with air. A series of calculations in static reacting systems was performed, where the initial temperature was specified and reactions occurred at constant pressure. Three different types of test flow contaminants were considered: NP, H2O, and a combustion of H2O and CO2. These contaminants are present in the test flows of facilities used for hypersonic propulsion testing. The results were computed using a detailed reaction mechanism and are presented in terms of ignition and reaction times. Calculations were made for a wide range of contaminant concentrations, temperatures and pressures. The results indicate a pronounced kinetic effect over a range of temperatures, especially with NO contamination and, to a lesser degree, with H2O contamination. In all cases studied, CO2 remained kinetically inert, but had a thermodynamic effect on results by acting as a third body. The largest effect is observed with combustion using hydrogen fuel, less effect is seen with combustion of ethane, and little effect of contaminants is shown with methane combustion.

Lai, H. T.↗

Numerical study of contaminant effects on combustion of hydrogen, ethane, and methane in air

A numerical study was performed to assess the effects of vitiated air on the chemical kinetics of hydrogen, ethane, and methane combustion with air. A series of calculations in static reacting systems was performed, where the initial temperature was specified and reactions occurred at constant pressure. Three different types of test flow contaminants were considered: NO, H2O, and a combination of H2O and CO2. These contaminants are present in the test flows of facilities used for hypersonic propulsion testing. The results were computed using a detailed reaction mechanism and are presented in terms of ignition and reaction times. Calculations were made for a wide range of contaminant concentrations, temperatures and pressures. The results indicate a pronounced kinetic effect over a range of temperatures, especially with NO contamination and, to a lesser degree, with H2O contamination. In all cases studied, CO2 remained kinetically inert, but had a thermodynamically effect on results by acting as a third body. The largest effect is observed with combustion using hydrogen fuel, less effect is seen with combustion of ethane, and little effect of contaminants is shown with methane combustion.

Lai, H. T.↗

Thermophysics Characterization of Kerosene Combustion

A one-formula surrogate fuel formulation and its quasi-global combustion kinetics model are developed to support the design of injectors and thrust chambers of kerosene-fueled rocket engines. This surrogate fuel model depicts a fuel blend that properly represents the general physical and chemical properties of kerosene. The accompanying gaseous-phase thermodynamics of the surrogate fuel is anchored with the heat of formation of kerosene and verified by comparing a series of one-dimensional rocket thrust chamber calculations. The quasi-global combustion kinetics model consists of several global steps for parent fuel decomposition, soot formation, and soot oxidation, and a detailed wet-CO mechanism. The final thermophysics formulations are incorporated with a computational fluid dynamics model for prediction of the combustor efficiency of an uni-element, tri-propellant combustor and the radiation of a kerosene-fueled thruster plume. The model predictions agreed reasonably well with those of the tests.

Wang, Ten-See↗

Understanding the Flow Physics of Shock Boundary-Layer Interactions Using CFD and Numerical Analyses

Computational fluid dynamic (CFD) analyses of the University of Michigan (UM) Shock/Boundary-Layer Interaction (SBLI) experiments were performed as an extension of the CFD SBLI Workshop held at the 48th AIAA Aerospace Sciences Meeting in 2010. In particular, the UM Mach 2.75 Glass Tunnel with a semi-spanning 7.75deg wedge was analyzed in attempts to explore key physics pertinent to SBLI's, including thermodynamic and viscous boundary conditions as well as turbulence modeling. Most of the analyses were 3D CFD simulations using the OVERFLOW flow solver, with additional quasi-1D simulations performed with an in house MATLAB code interfacing with the NIST REFPROP code to explore perfect verses non-ideal air. A fundamental exploration pertaining to the effects of particle image velocimetry (PIV) on post-processing data is also shown. Results from the CFD simulations showed an improvement in agreement with experimental data with key contributions including adding a laminar zone upstream of the wedge and the necessity of mimicking PIV particle lag for comparisons. Results from the quasi-1D simulation showed that there was little difference between perfect and non-ideal air for the configuration presented.

Friedlander, David J.↗

Modeling of Supercritical CO2 Shell-and-Tube Heat Exchangers Under Extreme Conditions: Part II: Heat Exchanger Model

Abstract Heat exchangers play a critical role in supercritical CO2 Brayton cycles by providing necessary waste heat recovery. Supercritical CO2 thermal cycles potentially achieve higher energy density and thermal efficiency operating at elevated temperatures and pressures. Accurate and computationally efficient estimation of heat exchanger performance metrics at these conditions is important for the design and optimization of sCO2 systems and thermal cycles. In this paper (Part II), a computationally efficient and accurate numerical model is developed to predict the performance of shell-and-tube heat exchangers (STHXs). Highly accurate correlations reported in Part I of this study are utilized to improve the accuracy of performance predictions, and the concept of volume averaging is used to abstract the geometry and reduce computation time. The numerical model is validated by comparison with computational fluid dynamics (CFD) simulations and provides high accuracy and significantly lower computation time compared to existing numerical models. A preliminary optimization study is conducted and the advantage of using supercritical CO2 as a working fluid for energy systems is demonstrated.

Engineering↗

$\mathrm{DRAGON}$: A multi-GPU orbital-free density functional theory molecular dynamics simulation package for modeling of warm dense matter

As progress in electronic structure theoretical methods is made, ab initio molecular dynamics (MD) based on orbital-free density functional theory (OF-DFT) is becoming increasingly more successful at substituting the traditional, very accurate but computationally costly Kohn–Sham (KS) approach for simulations of matter at the challenging warm dense matter (WDM) regime. However, despite the significant cost alleviation of eliminating the dependence on the KS orbitals, OF-DFT MD runs require ~10 2 to 10 3 CPU cores running for days, or even weeks, for simulations of systems comprised of 10 2 to 10 3 atoms, depending on thermodynamic conditions. Here we present DRAGON, a multi-GPU OF-DFT MD code for fast and efficient simulations of WDM. With a relatively small allocation of resources (4 to 8 GPU devices) it can provide an order of magnitude speedup for simulations containing $\mathscr{O}$(10 4 ) atoms and target systems composed of $\mathscr{O}$(10 5 ) atoms at conditions within the WDM regime, which is currently outside the capabilities of CPU codes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Toward more environmentally resistant gas turbines: Progress in NASA-Lewis programs

A wide range of programs are being conducted for improving the environmental resistance to oxidation and hot corrosion of gas turbine and power system materials. They range from fundamental efforts to delineate attack mechanisms, allow attack modeling and permit life prediction, to more applied efforts to develop potentially more resistant alloys and coatings. Oxidation life prediction efforts have resulted in a computer program which provides an initial method for predicting long time metal loss using short time oxidation data by means of a paralinear attack model. Efforts in alloy development have centered on oxide-dispersion strengthened alloys based on the Ni-Cr-Al system. Compositions have been identified which are compromises between oxidation and thermal fatigue resistance. Fundamental studies of hot corrosion mechanisms include thermodynamic studies of sodium sulfate formation during turbine combustion. Information concerning species formed during the vaporization of Na2SO4 has been developed using high temperature mass spectrometry.

Lowell, C. E.↗

The structure of evaporating and combusting sprays: Measurements and predictions

The structure of particle-laden jets and nonevaporating and evaporating sprays was measured in order to evaluate models of these processes. Three models are being evaluated: (1) a locally homogeneous flow model, where slip between the phases is neglected and the flow is assumed to be in local thermodynamic equilibrium; (2) a deterministic separated flow model, where slip and finite interphase transport rates are considered but effects of particle/drop dispersion by turbulence and effects of turbulence on interphase transport rates are ignored; and (3) a stochastic separated flow model, where effects of interphase slip, turbulent dispersion and turbulent fluctuations are considered using random sampling for turbulence properties in conjunction with random-walk computations for particle motion. All three models use a k-e-g turbulence model. All testing and data reduction are completed for the particle laden jets. Mean and fluctuating velocities of the continuous phase and mean mixture fraction were measured in the evaporating sprays.

Shuen, J. S.↗

Dependence of predicted bulk properties of hexagonal hydroxyapatite on exchange-correlation functional

Hydroxyapatite (HA) is the main component of human bones and teeth. HA has also been widely applied in various technological fields due to its unique properties. Reliable computational simulations for this critical material often require input parameters obtained from the first-principles density functional theory (DFT) calculations with appropriate exchange–correlation functionals. Previous DFT calculations are insufficient to verify the reliabilities of various functionals, particularly as they fail to assess predictions for multiple properties of the material. In this paper, we first select 18 different functionals to calculate geometric, elastic, electronic, and thermodynamic properties of hexagonal HA bulk crystal. We find that the results from optB86b-vdW and optB88-vdW functionals with dispersion corrections have the overall best agreement with available experimental data. Then, we choose optB88-vdW functional, as well as PBE functional without dispersion corrections as a comparison, to perform extensive first-principles DFT phonon calculations under the quasiharmonic approximation. Various thermodynamic properties (including phonon contributions to internal energy, entropy, and Helmholtz free energy) and thermal parameters (including thermal expansions of volume, thermal expansion coefficients, heat capacities, isothermal bulk moduli, etc.) versus temperature are consequently obtained. By comparing these quantities, we report that the results from optB88-vdW functional have significantly better agreement with available experimental data than those from PBE functional although the latter has been widely used in previous DFT calculations for HA-based material systems.

36 MATERIALS SCIENCE↗