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At least 235 records · Page 13

Collisional excitation of interstellar molecules - Linear molecules CO, CS, OCS, and HC3N

Rates for excitation of CO, CS, OCS, and HC3N by collisions with He atoms and H2 molecules are presented. These have been obtained from extensive theoretical calculations using methods of known reliability. In general, rates necessary for modeling interstellar molecular clouds with kinetic temperatures to 100 K have been included. Methods for fitting these rates in more compact form are discussed.

Green, S.

Kinetics of thermochemical gas-solid reactions important in the Venus sulfur cycle

The thermochemical net reaction CaCO3 + SO2 yields CaSO4 + CO is predicted to be an important sink for incorporation of SO2 into the Venus crust. The reaction rate law was established to understand the dependence of rate on experimental variables such as temperature and partial pressure of SO2, CO2, and O2. The experimental approach was a variant of the thermogravimetric method often employed to study the kinetics of thermochemical gas-solid reactions. Clear calcite crystals were heated at constant temperature in SO2-bearing gas streams for varying time periods. Reaction rate was determined by three independent methods. A weighted linear least squares fit to all rate data yielded a rate equation. Based on the Venera 13, 14 and Vega 2 observations of CaO content of the Venus atmosphere, SO2 at the calculated rate would be removed from the Venus atmosphere in about 1,900,00 years. The most plausible endogenic source of the sulfur needed to replenish atmospheric SO2 is volcanism. The annual amount of erupted material needed for the replenishment depends on sulfur content; three ratios are used to calculate rates ranging from 0.4 to 11 cu km/year. This geochemically derived volcanism rate can be used to test if geophysically derived rates are correct. The work also suggests that Venus is less volcanically active than the Earth.

Fegley, Bruce, Jr.

Predicting Thermoset Resin Cure Kinetics for Composite Processing

Predicting a material’s thermal properties is not only useful for designing parts but also for defining processing parameters. This is especially applicable to wet-filament winding operations and the production of composite parts using thermoset res ins. For these, the formation of cross-linking bonds is affected by time and temperature, but the degree of cross-linking can be modeled using phenomenological methods. In the current study, the Kissinger and Flynn/Wall/Ozawa methods were both used to calculate kinetic parameters and produced values that were in agreement with each other. The kinetic parameters activation energy ( E a ) and pre-exponential factor (𝐴) calculated from exothermic peak data increased between an epoxy and resole phenol resin system, with a cyanate ester having the highest. The successful application of both methods suggests applicability to future studies for developing cure recipes.

36 MATERIALS SCIENCE

Time-resolved simplified chemical kinetics modelling using computational singular perturbation

A CO-CH4-air reaction system is used to demonstrate the computational singular perturbation (CSP) method for deriving time-resolved simplified chemical kinetics models. CSP provides a programmable algorithm to group the given collection of elementary reactions into reaction groups which are ordered according to their speed. The concept of Importance Index k(m)exp s is introduced: k(m)exp s is defined to be a number between 0 and 1 which measures the importance of the m-th reaction group to the s-th reactant and can readily be computed from data generated by CSP. It is suggested that the robustness of the solutions of the reaction system can be qualitatively assessed by inspecting the Importance Index data.

Lam, S. H.

Chemical Thermodynamics and the Mathematical Integration of Reaction Kinetics

Key advances in the development of numerical methods for non-reacting compressible flows have been enabled by translating physical requirements into concrete numerical guidelines, such as the satisfaction of entropy inequalities for shock-capturing techniques [Lax, Contributions to Nonlinear Functional Analysis (1971) 603-634]. In the present work, we present nonlinear numerical analysis tools that draw from Chemical Thermodynamics , the branch of Nonequilibrium Thermodynamics that deals with chemical reactions. Through Gibbs formalism, chemical thermodynamics provides a well-known theoretical expression for the chemical equilibrium constant of a reaction in terms of reduced chemical potentials. A less-known, yet extremely valuable result, due to [Krambeck, Arch. Ration. Mech. Anal. , 38 (1970) 317], states that when this expression is implemented, mass-action kinetic models are consistent with the dynamical prescriptions of the 2nd law of thermodynamics. For fixed-temperature ordinary differential equations modeling constant-volume reacting gas mixtures, this leads to a decreasing Helmholtz free energy. If the temperature is allowed to vary in accordance with conservation of energy (1st law), this leads to the statement of increasing entropy. These nonlinear prescriptions can, and should be, used to further develop temporal integration techniques for reaction kinetics. We demonstrate that Krambeck's result holds even when the equilibrium constants are approximated from data. We prove this result by constructing the implicit free energy and the implicit entropy inherent to a given approximation. This is first done for a 5-species, 17-reaction model problem for air. With this structure established, elements of discrete entropy-stability theory [Tadmor, Acta Numer. , 12 (2003) 451] are leveraged to examine the consistency of time-integration schemes with these prescriptions. Using chemical potentials, one can compute the respective contributions of the kinetics model and of the temporal scheme to free energy/entropy variations. We introduce a nonlinear-stable version of the Discontinuous-Galerkin (DG) scheme in time which shows robustness improvements over the standard linearly-stable version. Most notably, the maximum timestep that can be resolved with the nonlinearly-stable variant tends to grow with polynomial order, in contrast to the linearly-stable variant. We generalize our constructions to arbitrary systems of reversible chemical reactions, ultimately showing that the compressible reacting Euler system admits the opposite of the implicitly constructed thermodynamic entropy as a mathematical entropy . This lays important theoretical foundations towards robust scheme development [Harten, J. Comput. Phys. 49 (1983) 151-164].

STMD

Recovery and separation of precious metals from space

During the past year a viable procedure centered around centrifugal partition chromatography (CPC), a multistage liquid-liquid partitioning technique for the separation of precious metals (Pt, Pd, Rh, Ir, Os, Ru), was developed. Stable and inexpensive ligands that can be readily recycled to achieve the separations of the precious metals were identified. The separation methods developed so far yield three separate fractions: Pt, Pd, and Rh-Ir. The Rh-Ir pair can be separated in a subsequent run. The total amount of precious metals separated in a single experiment varied from 1 to 50 mg. The factors affecting the efficiencies of these separations were studied. The kinetics of the decomposition of the complex and the ion pair have a major bearing on these efficiencies, with slow kinetics resulting in poor efficiencies. The methods for the improvement of the efficiencies were also investigated. For example, significant improvement in the efficiencies and separation times for Pt and Pd were achieved by the use of chloride gradient in the mobile phase. Two papers were published and talks were presented on our work at the FACSS meeting in Anaheim, Oct. 1991, and at the Pittsburgh Conference in New Orleans, Mar. 1992.

Freiser, H.

Rotating cylinder electrode in reactive CO 2 capture: Identifying active C species via transport, VLE models and kinetics

Here, this article explores technical challenges and potential methodologies for understanding electrochemical Reactive CO 2 Capture (RCC) mechanisms. RCC offers potential energy cost advantages by directly converting captured CO 2 into fuels and chemicals, unlike traditional carbon capture and utilization (CCU) processes that require sequential capture, concentration, and compression. However, direct conversion of captured CO 2 introduces complexity due to additional equilibrium buffer reactions, making it challenging to identify active species for reduction in electrochemical studies. This article discusses methods to integrate transport, thermodynamics, and kinetics concepts to identify active carbon sources in RCC. Vapor‐Liquid Equilibrium (VLE) and transport models are validated against experimental results obtained in a gastight rotating cylinder electrode reactor and are shown as useful tools for studying RCC in heterogeneous electrocatalysts across different capture agents, solvents, and temperatures. This article establishes an experimental framework for advancing research in electrochemical RCC.

Electrocatalysis

A method for screening of plant species for space use

A cost-effective methodology which monitors numerous dynamic aspects of carbon assimilation and allocation kinetics in live, intact plants is discussed. Analogous methods can apply to nitrogen uptake and allocation. This methodology capitalizes on the special properties of the short-lived, positron-gamma emitting isotope C-11 especially when applied as CO2-11 in a special extended square wave (ESW) pattern. The 20.4 minute half-life allows for repeated or continuous experiments on the same plant over periods of minutes, hours, days, or weeks. The steady-state isotope equilibrium approached during the ESW experiments, and the parameters which can be analyzed by this technique are also direct results of that short half-life. Additionally, the paired .511 MeV gamma rays penetrate any amount of tissue and their 180 deg opposite orientation provides good collimation and allows coincidence counting which nearly eliminates background.

Goeschl, J. D.

Automated Simplification of Full Chemical Mechanisms

A code has been developed to automatically simplify full chemical mechanisms. The method employed is based on the Intrinsic Low Dimensional Manifold (ILDM) method of Maas and Pope. The ILDM method is a dynamical systems approach to the simplification of large chemical kinetic mechanisms. By identifying low-dimensional attracting manifolds, the method allows complex full mechanisms to be parameterized by just a few variables; in effect, generating reduced chemical mechanisms by an automatic procedure. These resulting mechanisms however, still retain all the species used in the full mechanism. Full and skeletal mechanisms for various fuels are simplified to a two dimensional manifold, and the resulting mechanisms are found to compare well with the full mechanisms, and show significant improvement over global one step mechanisms, such as those by Westbrook and Dryer. In addition, by using an ILDM reaction mechanism in a CID code, a considerable improvement in turn-around time can be achieved.

Norris, A. T.

Application of Low Dimensional Manifolds in NO(x) Prediction

A new post-processing technique has been developed, based on the Intrinsic Low Dimensional Manifold (ILDM) method of Maas and Pope. The ILDM method is a dynamical systems approach to the simplification of large chemical kinetic mechanisms. By identifying low-dimensional attracting manifolds, the method allows complex full mechanisms to be parameterized by just a few variables: In effect, generating reduced chemical mechanisms by an automatic procedure. These resulting mechanisms however, still retain all the species used in the full mechanism. The NO(x) post-processor takes an ILDM reduced mechanism and attempts to map this mechanism to the results of a CFD calculation. This mapping allows the NO(x) concentrations at each grid node to be obtained from the ILDM reduced mechanism, as well as other trace species of interest. Because a mapping procedure is used, this method is very fast, being able to process one million node calculations in just a few minutes.

Norris, A. T.

Self-Sensing Composites via an Embedded 3D-Printed PVDF-MoS 2 Nanosensor for Structural Health Monitoring

Carbon fiber (CF)-reinforced epoxy composites are widely used in vehicle applications, where early damage detection is crucial for reliability and safety. To address this need, we developed a self-sensing epoxy/CF composite by embedding a PVDF-MoS 2 nanosensor via an embedded 3D printing method. By harnessing the intrinsic curing kinetics of epoxy, we tailored its rheological properties to optimize the embedded printing process, enabling precise and reliable support for sensor filaments without compromising the composite’s structural and functional integrity. Through comprehensive rheological and kinetic analysis, we established a quantitative relationship among curing temperature, conversion rate, and resulting yield modulus─defining a narrow processing window essential for successful sensor integration. Specifically, we identified that an epoxy yield modulus range of 180–294 Pa and a conversion rate below 10% are critical to support the PVDF-MoS 2 filament architecture. Here, this embedded 3D printing method produces complex and multimaterial PVDF-MoS 2 sensors within an epoxy matrix with minimal deformation and reduced postprocessing, which is scalable and adaptable for industrial applications. Under cyclic loading, the embedded sensors exhibited stable signals under constant loads and increased voltage signals in response to crack formation (17–35% higher) and catastrophic failure (1 order of magnitude higher), effectively capturing structural changes in real time. This study demonstrates the potential of PVDF-MoS 2 nanocomposite sensor materials for real-time structural health monitoring in epoxy–CF composite systems, enabling early detection of defects and stress anomalies, significantly reducing the risk of unexpected failures, and enhancing structural reliability.

PVDF-MoS2 sensor

Computer modeling the fatigue crack growth rate behavior of metals in corrosive environments

The objective of this task was to develop a method to digitize FCP (fatigue crack propagation) kinetics data, generally presented in terms of extensive da/dN-Delta K pairs, to produce a file for subsequent linear superposition or curve-fitting analysis. The method that was developed is specific to the Numonics 2400 Digitablet and is comparable to commercially available software products as Digimatic(sup TM 4). Experiments demonstrated that the errors introduced by the photocopying of literature data, and digitization, are small compared to those inherent in laboratory methods to characterize FCP in benign and aggressive environments. The digitizing procedure was employed to obtain fifteen crack growth rate data sets for several aerospace alloys in aggressive environments.

Richey, Edward, III

Test of Shi et al. Method to Infer the Magnetic Reconnection Geometry from Spacecraft Data: MHD Simulation with Guide Field and Antiparallel Kinetic Simulation

When analyzing data from an array of spacecraft (such as Cluster or MMS) crossing a site of magnetic reconnection, it is desirable to be able to accurately determine the orientation of the reconnection site. If the reconnection is quasi-two dimensional, there are three key directions, the direction of maximum inhomogeneity (the direction across the reconnection site), the direction of the reconnecting component of the magnetic field, and the direction of rough invariance (the "out of plane" direction). Using simulated spacecraft observations of magnetic reconnection in the geomagnetic tail, we extend our previous tests of the direction-finding method developed by Shi et al. (2005) and the method to determine the structure velocity relative to the spacecraft Vstr. These methods require data from four proximate spacecraft. We add artificial noise and calibration errors to the simulation fields, and then use the perturbed gradient of the magnetic field B and perturbed time derivative dB/dt, as described by Denton et al. (2010). Three new simulations are examined: a weakly three-dimensional, i.e., quasi-two-dimensional, MHD simulation without a guide field, a quasi-two-dimensional MHD simulation with a guide field, and a two-dimensional full dynamics kinetic simulation with inherent noise so that the apparent minimum gradient was not exactly zero, even without added artificial errors. We also examined variations of the spacecraft trajectory for the kinetic simulation. The accuracy of the directions found varied depending on the simulation and spacecraft trajectory, but all the directions could be found within about 10 for all cases. Various aspects of the method were examined, including how to choose averaging intervals and the best intervals for determining the directions and velocity. For the kinetic simulation, we also investigated in detail how the errors in the inferred gradient directions from the unmodified Shi et al. method (using the unperturbed gradient) depended on the amplitude of the calibration errors. For an accuracy of 3 for the maximum gradient direction, the calibration errors could be as large as 3% of reconnection magnetic field, while for the same accuracy for the minimum gradient direction, the calibration errors could only be as large as 0.03% of the reconnection magnetic field. These results suggest that the maximum gradient direction can normally be determined by the unmodified Shi et al. method, while the modified method or some other method must be used to accurately determine the minimum gradient direction. The structure velocity was found with magnitude accurate to 2% and direction accurate to within 5%.

Denton, R.

Machine Learning-Assisted Recovery of Delicate Kinetic Information from Transient Reactor Experiments

Identifying active sites and their roles in chemical reaction steps remains a vital challenge in heterogeneous catalysis. Transient experiments offer a unique way to probe active sites and distinguish subtle kinetic features. Although physics-based analysis methods may be well-developed, they can be highly susceptible to experimental noise, and smoothing methods may erase or even distort important features; a smooth curve is not always the best curve. We demonstrate a new workflow for the direct interpretation of intrinsic kinetic information from exit flux curves measured in transient reactor experiments. This workflow contains three artificial neural networks (ANNs), including a noise reducer, a concentration predictor, and a rate predictor to analyze experimental data, followed by the virtual TAP (VTAP) physics-based reactor model and density functional theory (DFT) calculations of adsorption energies on specific sites. We use this workflow to analyze the data from experiments titrating Pt/Al 2 O 3 and Pt/SiO 2 catalysts with carbon monoxide (CO) in the temporal analysis of products (TAP) reactor. Our workflow separates the time-evolving chemical reaction and mass transfer information contained in the TAP pulse response. The existence of strong- and weak-binding sites on the Pt/Al 2 O 3 catalyst is observed in the catalyst titration experiment in the transient reactor. The structures of the strong- and weak-binding sites are then identified by using DFT calculations. We find that the Pt/SiO 2 catalyst has only strong-binding sites, which aligns with the inactive support effect of SiO 2 . We demonstrate how machine learning methods provide unique insights with high-resolution data analysis that cannot be achieved by using state-of-the-art physics-based methods.

Adsorption

Particle collisionality in scaled kinetic plasma simulations

Kinetic plasma processes, such as magnetic reconnection, collisionless shocks, and turbulence, are fundamental to the dynamics of astrophysical and laboratory plasmas. Simulating these processes often requires particle-in-cell (PIC) methods, but the computational cost of fully kinetic simulations can necessitate the use of artificial parameters, such as a reduced speed of light and ion-to-electron mass ratio, to decrease expense. While these approximations can preserve overall dynamics under specific conditions, they introduce nontrivial impacts on particle collisionality that are not yet well understood. In this work, we develop a method to scale particle collisionality in simulations employing an artificial speed of light and/or an artificial ion-to-electron mass ratio. By introducing species-dependent scaling factors, we independently adjust inter- and intra-species collision rates to better replicate the collisional properties of the physical system. Our approach maintains the fidelity of electron and ion transport properties while preserving critical relaxation rates, such as energy exchange timescales, within the limits of weakly collisional plasma theory. Furthermore, we demonstrate the accuracy of this scaling method through benchmarking tests against theoretical relaxation rates and connecting to fluid theory, highlighting its ability to retain key transport properties. Existing collisional PIC implementations can be easily modified to include this scaling, which will enable deeper insights into the behavior of marginally collisional plasmas across various contexts.

Totorica, S. R. [Princeton Univ., NJ (United State

Dissolution of quartz in aqueous basic solution, 106-236 C - Surface kinetics of 'perfect' crystallographic faces

A highly accurate method, called the negative crystal method, for determining the rate of dissolution on specific crystallographic faces of crystals was developed, in which the dissolution rates of nominally perfect crystal faces are obtained by measuring the size of individual negative crystals during a sequence of dissolution steps. The method was applied to determine the apparent activation energy and rate constants for the dissolution of quartz in 0.01 M KOH solutions at temperatures from 106 to 236 C. Also investigated were the effects of hydroxyl activity and ionic strength. The apparent activation energies for the dissolution of the prism and of the rhomb were determined.

Gratz, Andrew J.