Search NASA⌕ Search

SEARCH · Search NASA

Results for “Decomposition kinetics”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A chemical kinetic mechanism for combustion and flame propagation of CH 2 F 2 /O 2 /N 2 mixtures

Here in this work, we compiled and evaluated rate expressions for reactions relevant to the decomposition and combustion of CH 2 F 2 (difluoromethane, refrigerant R-32) in CH 2 F 2 /O 2 /N 2 flames. The recommended values have been used in premixed flame calculations, reported elsewhere, to model experimentally derived burning velocities determined using a constant volume spherical flame method. In this work, we also provide a detailed description of the reaction pathways for decomposition and combustion of CH 2 F 2 . This work is part of a larger effort at NIST to characterize and predict the flammability of new refrigerant working fluids and their blends for consideration as replacements of current refrigerants with high global warming potentials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Kinetic Probes of the Origin of Activity in MOF-Based C–H Oxidation Catalysis

The development of homogeneous catalysis is enabled by the availability of a rich toolkit of kinetics experiments, such as the Hgdrop test, that differentiate catalytic activity at ligand-supported metal complexes from potential heterogeneous catalysts derived from decomposition of molecular species. Metal-organic frameworks (MOFs) have garnered significant attention as platforms for catalysis at site-isolated, interstitial catalyst sites. Unlike homogeneous catalysis, relatively few strategies have been advanced to evaluate the origin of catalytic activity in MOF-promoted reactions. Many of the MOFs that have been examined as potential catalysts are comprised of molecular constituents that represent viable catalysts in the absence of the extended MOF lattice, and thus interfacial sites and leached homogeneous species represent potential sources of catalyst activity. Here, we demonstrate that analysis of deuterium kinetic isotope effects (KIEs) and olefin epoxidation diastereoselectivity provides probes of the origin of catalytic activity in MOF-promoted oxidation reactions. These analyses support involvement of lattice-based Fe sites in the turnover-limiting step of C–H activation with Fe-MOF-74-based materials (i.e., the MOF functions as a bona fide catalyst) and evidence that Cu 2 -based MOF MIL-125-Cu 2 O 2 functions as a solid-state initiator for solution-phase oxidation chemistry and is not involved in the turnover limiting step (i.e., the MOF does not function as a catalyst for substrate functionalization). furthermore, we anticipate that the simple experiments described here will provide a valuable tool for clarifying the role of MOFs in C–H oxidation reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Computational Aspects of Single-Molecule Kinetics for Coupled Catalytic Cycles: A Spectral Analysis

Catalysis from single active sites is analyzed using methods developed from single molecule kinetics. Using a stochastic Markov state description, the observable properties of general catalytic networks of reactions are expressed using an eigenvalue decomposition of the transition matrix for the Markov process. By the use of a sensitivity analysis, the necessary eigenvalues and eigenvectors are related to the energies of controlling barriers and wells located along the reaction routes. A generalization of the energetic span theory allows the eigenvalues to be computed from several activation energies corresponding to distinct barrier-well pairings. The formalism is demonstrated accurately for model problems for a physically realistic mechanism for an alkene hydrogenation reaction on a single atom catalyst.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Kinetic Properties of Microbial Exoenzymes Vary With Soil Depth but Have Similar Temperature Sensitivities Through the Soil Profile

Current knowledge of the mechanisms driving soil organic matter (SOM) turnover and responses to warming is mainly limited to surface soils, although over 50% of global soil carbon is contained in subsoils. Deep soils have different physicochemical properties, nutrient inputs, and microbiomes, which may harbor distinct functional traits and lead to different SOM dynamics and temperature responses. We hypothesized that kinetic and thermal properties of soil exoenzymes, which mediate SOM depolymerization, vary with soil depth, reflecting microbial adaptation to distinct substrate and temperature regimes. We determined the Michaelis-Menten (MM) kinetics of three ubiquitous enzymes involved in carbon (C), nitrogen (N) and phosphorus (P) acquisition at six soil depths down to 90 cm at a temperate forest, and their temperature sensitivity based on Arrhenius/ Q 10 and Macromolecular Rate Theory (MMRT) models over six temperatures between 4–50°C. Maximal enzyme velocity ( V max ) decreased strongly with depth for all enzymes, both on a dry soil mass and a microbial biomass C basis, whereas their affinities increased, indicating adaptation to lower substrate availability. Surprisingly, microbial biomass-specific catalytic efficiencies also decreased with depth, except for the P-acquiring enzyme, indicating distinct nutrient demands at depth relative to microbial abundance. These results suggested that deep soil microbiomes encode enzymes with intrinsically lower turnover and/or produce less enzymes per cell, reflecting distinct life strategies. The relative kinetics between different enzymes also varied with depth, suggesting an increase in relative P demand with depth, or that phosphatases may be involved in C acquisition. V max and catalytic efficiency increased consistently with temperature for all enzymes, leading to overall higher SOM-decomposition potential, but enzyme temperature sensitivity was similar at all depths and between enzymes, based on both Arrhenius/ Q 10 and MMRT models. In a few cases, however, temperature affected differently the kinetic properties of distinct enzymes at discrete depths, suggesting that it may alter the relative depolymerization of different compounds. We show that soil exoenzyme kinetics may reflect intrinsic traits of microbiomes adapted to distinct soil depths, although their temperature sensitivity is remarkably uniform. These results improve our understanding of critical mechanisms underlying SOM dynamics and responses to changing temperatures through the soil profile.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Investigation of Cycle-to-Cycle Variations in Internal Combustion Engine Using Proper Orthogonal Decomposition

The understanding, modeling and control of the cycle-to-cycle variation (CCV) in the modern internal combustion engine (ICE) is a key scientific challenge to achieve stable engine operation. High CCV in the engine combustion chamber may contribute to partial burn, misfire and knock, which adversely affects the engine performance and may potentially damage the engine. The objective of the current study is to leverage high-fidelity numerical simulations to improve the understanding of the causes of CCV. Using the massively parallel code, Nek5000, multi-cycle, wall-resolved large-eddy simulations (LES) were performed for the General Motors (GM), Transparent Combustion Chamber (TCC-III) optical engine under motored operating conditions. Further, the large-scale structures of the in-cylinder flow were investigated using a triple proper orthogonal decomposition (POD) technique to explore the characteristics of different parts of the flow and their contributions to CCV. The kinetic energy of the subset of flow structures were determined and correlated between the intake and compression strokes. The insights from the analysis of the large-scale flow structures will be used to assist the development of improved engine designs with reduced CCV and enhance the engine performance.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Modeling of melting and erosion in high velocity microparticle impacts

High velocity collisions can cause melting, a situation involving elasticity, plasticity, and phase transformations in tandem, which is very challenging for mechanical modeling. Here, this paper advances the use of smoothed particle hydrodynamics (SPH) simulations for this complex situation, investigating stainless steel microspheres impacting a tin substrate. After extensive validation against a range of mechanical and geometrical measurements of experimental impacts, the model provides a detailed, quantitative view of melt volume production over a broad range of impact velocities. It also enables direct decomposition of the impact energy partitioning, including analysis of the energy absorbed by plasticity in the impactor, the system kinetic energy, and the adiabatic heating of the substrate in addition to the melting itself. Since these quantities are not available experimentally, SPH modeling substantially enhances the quantitative understanding of such impacts. Finally, the model speaks to the phase characteristics of the ejecta formed during impact, confirming the experimental inference that the ejected material likely contains a significant fraction of solid material.

Constitutive modeling↗
DOE OSTI2020

An expanded kinetics model describing injector region desorption

During the initial stages of electron beam injection, absorbed or entrained material can be released into the nascent beam pulse by thermal desorption or electron beam impact. These processes, and subsequent ionization and dissociation, are examined assuming a prototypical temporal beam pulse. An expanded set of kinetic equations that includes thermal desorption, electron-stimulated ion emission, electron impact dissociation, electron impact ionization, and thermal decomposition of adsorbed water molecules is developed. Estimates of the three most important ionized species H 2 O + , H + and OH + are provided for typical injector conditions. Electron impact dissociative ionization of neutral H 2 O is the dominant source of H + under these conditions. Since the abundance of thermally desorbed neutral H 2 O has an exponential rate, the production of H+ is likewise controlled by this exponential desorption rate. Thus thermal management of the confining walls could suppress proton production in the injector region. Thermal decomposition of H 2 O will not be a contributing physical process in the injector region on time scales less than a μs. The formalism is sufficiently flexible to include entrained hydrogen.

42 ENGINEERING↗
DOE OSTI2022

Conservative DG method for the micro-macro decomposition of the Vlasov–Poisson–Lenard–Bernstein model

The micro-macro (mM) decomposition approach is considered for the numerical solution of the Vlasov– Poisson–Lenard–Bernstein (VPLB) system, which is relevant for plasma physics applications. In the mM approach, the kinetic distribution function is decomposed as $f$ = $\mathscr{E}$[$ρ_f$] + g , where $\mathscr{E}$ is a local equilibrium distribution, depending on the macroscopic moments $ρ_f$ = $∫_{\mathbb{R}}$ $efdv$ = $\langle$$ef$$\rangle$$_{\mathbb{R}}$, where e = (1, $v$, $\frac{1}{2}$ $v^2$) T , and $g$, the microscopic distribution, is defined such that $\langle$$eg$$\rangle$$_{\mathbb{R}}$ = 0. We aim to design numerical methods for the mM decomposition of the VPLB system, which consists of coupled equations for $ρ_f$ and $g$. To this end, we use the discontinuous Galerkin (DG) method for phase-space discretization, and implicit-explicit (IMEX) time integration, where the phase-space advection terms are integrated explicitly and the collision operator is integrated implicitly. We give special consideration to ensure that the resulting mM method maintains the $\langle$$eg$$\rangle$$_{\mathbb{R}}$ = 0 constraint, which may be necessary for obtaining (i) satisfactory results in the collision dominated regime with coarse velocity resolution, and (ii) unambiguous conservation properties. The constraint-preserving property is achieved through a consistent discretization of the equations governing the micro and macro components. Here, we present numerical results that demonstrate the performance of the mM method. The mM method is also compared against a corresponding DG-IMEX method solving directly for $f$.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Supercooled liquid sulfur maintained in three-dimensional current collector for high-performance Li-S batteries

In lithium-sulfur (Li-S) chemistry, the electrically/ionically insulating nature of sulfur and Li 2 S leads to sluggish electron/ion transfer kinetics for sulfur species conversion. Sulfur and Li 2 S are recognized as solid at room temperature, and solid-liquid phase transitions are the limiting steps in Li-S batteries. Here, we visualize the distinct sulfur growth behaviors on Al, carbon, Ni current collectors and demonstrate that (i) liquid sulfur generated on Ni provides higher reversible capacity, faster kinetics, and better cycling life compared to solid sulfur; and (ii) Ni facilitates the phase transition (e.g., Li 2 S decomposition). Accordingly, light-weight, 3D Ni-based current collector is designed to control the deposition and catalytic conversion of sulfur species toward high-performance Li-S batteries. This work provides insights on the critical role of the current collector in determining the physical state of sulfur and elucidates the correlation between sulfur state and battery performance, which will advance electrode designs in high-energy Li-S batteries.

25 ENERGY STORAGE↗
DOE OSTI2024

A Local Macroscopic Conservative (LoMaC) Low Rank Tensor Method for the Vlasov Dynamics

Abstract In this paper, we propose a novel Local Macroscopic Conservative (LoMaC) low rank tensor method for simulating the Vlasov-Poisson (VP) system. The LoMaC property refers to the exact local conservation of macroscopic mass, momentum and energy at the discrete level. This is a follow-up work of our previous development of a conservative low rank tensor approach for Vlasov dynamics ( arXiv:2201.10397 ). In that work, we applied a low rank tensor method with a conservative singular value decomposition to the high dimensional VP system to mitigate the curse of dimensionality, while maintaining the local conservation of mass and momentum. However, energy conservation is not guaranteed, which is a critical property to avoid unphysical plasma self-heating or cooling. The new ingredient in the LoMaC low rank tensor algorithm is that we simultaneously evolve the macroscopic conservation laws of mass, momentum and energy using a flux-difference form with kinetic flux vector splitting; then the LoMaC property is realized by projecting the low rank kinetic solution onto a subspace that shares the same macroscopic observables by a conservative orthogonal projection. The algorithm is extended to the high dimensional problems by hierarchical Tuck decomposition of solution tensors and a corresponding conservative projection algorithm. Extensive numerical tests on the VP system are showcased for the algorithm’s efficacy.

Guo, Wei↗
DOE OSTI2024

Association Kinetics for Perfluorinated n -Alkyl Radicals

Radical-radical reaction channels are important in the pyrolysis and oxidation chemistry of perfluoroalkyl substances (PFAS). In particular, unimolecular dissociation reactions within unbranched n-perfluoroalkyl chains, and their corresponding reverse barrierless association reactions, are expected to be significant contributors to the gas-phase thermal decomposition of families of species such as perfluorinated carboxylic acids and perfluorinated sulfonic acids. Unfortunately, experimental data for these reactions are scarce and uncertain. Furthermore, obtaining reliable theoretical predictions for such reactions is a laborious and computationally intensive task. Here, in this work, the chemical kinetics of the various association/decomposition reactions producing/decomposing the C 2 -C 4 series of unbranched n-perfluoroalkanes (C 2 F 6 , C 3 F 8 , and C 4 F 10 ) are examined using state-of-the-art ab initio transition-state-theory-based master-equation calculations. The variable-reaction-coordinate transition-state theory (VRC-TST) formalism is employed in computing the microcanonical and canonical rates for the association reactions. Reaction thermochemistry is obtained via composite quantum chemistry calculations and the laddering of error-canceling reaction schemes via a connectivity-based hierarchy approach employing ANL1/ANL0-style reference energies. Lennard-Jones collision model parameters for the considered systems were estimated by a direct dynamics approach, and collisional energy transfer parameters were obtained from analogies to systems of similar size and heavy-atom connectivity. A one-dimensional master equation approach was used to convert the microcanonical rate coefficients from the VRC-TST analysis into temperature- and pressure-dependent rate constants for the association reactions and the reverse dissociation reactions. The data are reported in standardized formats for usage in comprehensive chemical kinetic models for PFAS thermal destruction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Deep learning for in situ data compression of large turbulent flow simulations

As the size of turbulent flow simulations continues to grow, in situ data compression is becoming increasingly important for visualization, analysis, and restart checkpointing. For these applications, single-pass compression techniques with low computational and communication overhead are crucial. In this paper we present a deep-learning approach to in situ compression using an autoencoder architecture that is customized for three-dimensional turbulent flows and is well suited for contemporary heterogeneous computing resources. The autoencoder is compared against a recently introduced randomized single-pass singular value decomposition (SVD) for three different canonical turbulent flows: decaying homogeneous isotropic turbulence, a Taylor-Green vortex, and turbulent channel flow. Our proposed fully convolutional autoencoder architecture compresses turbulent flow snapshots by a factor of 64 with a single pass, allows for arbitrarily sized input fields, is cheaper to compute than the randomized single-pass SVD for typical simulation sizes, performs well on unseen flow configurations, and has been made publicly available. The results reported here show that the autoencoder dramatically outperforms a randomized single-pass SVD with similar compression ratio and yields comparable performance to a higher-rank decomposition with an order of magnitude less compression in regard to preserving a number of important statistical quantities such as turbulent kinetic energy, enstrophy, and Reynolds stresses.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

AEflow (Autoencoder fluid flow compression network) [SWR-22-29]

As the size of turbulent flow simulations continues to grow, in situ data compression is becoming increasingly important for visualization, analysis, and restart checkpointing. For these applications, single-pass compression techniques with low computational and communication overhead are crucial. In this paper we present a deep-learning approach to in situ compression using an autoencoder architecture that is customized for three-dimensional turbulent flows and is well suited for contemporary heterogeneous computing resources. The autoencoder is compared against a recently introduced randomized single-pass singular value decomposition (SVD) for three different canonical turbulent flows: decaying homogeneous isotropic turbulence, a Taylor-Green vortex, and turbulent channel flow. Our proposed fully convolutional autoencoder architecture compresses turbulent flow snapshots by a factor of 64 with a single pass, allows for arbitrarily sized input fields, is cheaper to compute than the randomized single-pass SVD for typical simulation sizes, performs well on unseen flow configurations, and has been made publicly available. The results reported here show that the autoencoder dramatically outperforms a randomized single-pass SVD with similar compression ratio and yields comparable performance to a higher-rank decomposition with an order of magnitude less compression in regard to preserving a number of important statistical quantities such as turbulent kinetic energy, enstrophy, and Reynolds stresses.

King, Ryan↗
DOE OSTI2023

Mechanistic insights into the pyrolysis of poly (vinyl chloride)

The accumulation of unmanaged plastic waste in the environment has a devastating impact upon marine life and human health. Catalytic and thermal pyrolysis are promising technologies toward the efficient utilization of plastic waste. Yet, the processing of polymers, such as polyvinyl chloride (PVC), that decompose into corrosive compounds remains a major challenge. In this work, we employ density functional theory (DFT) and thermogravimetric analysis (TGA) to explore the elementary chemical steps that underpin the thermal decomposition of PVC. We determine that the dehydrochlorination reaction (i.e., 1 st stage of thermal decomposition) begins in tertiary chloride defects and propagates via HCl–mediated autocatalysis of internal allylic (IA) chloride groups. The latter groups, when in the vicinity of π–conjugated polymer segments, release HCl in a facile manner. We predict that other compounds, including hydrogen halides and H 2 O could also catalyze PVC’s dehydrochlorination. We suggest that hydrogen halides are the most efficient catalysts for this process, while other compounds like H 2 O may slow down the dehydrochlorination compared to purely HCl-catalyzed process, because of the dilution of the produced HCl. This result is corroborated by TGA experiments. Additionally, we study the thermochemistry and kinetics of polyene chain crosslinking and the formation of aromatics. The former reaction proceeds in parallel with the dehydrochlorination process (i.e., during the 1st stage of thermal decomposition), whilst the latter may occur at high temperatures (i.e., during the 2 nd stage of thermal decomposition). Furthermore, this work contributes to the fundamental understanding of molecular scale phenomena that take place during PVC pyrolysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Pyrolysis Modeling of PMMA decomposition studied by TGA

Data from four TGA experiments conducted at Sandia National Laboratories was used for determination of a pyrolysis model using a commercial thermokinetics program developed by Netzsch Instruments (Kinetics NEO, version 2.1). The data measured at 1 K/min and the average of three measurements at 50 K/min were used as input into Kinetics NEO. The model was developed using data in the range 373 to 773 K. An initial estimate of the energy of activation (E) and pre-exponential constant (A) were determined from the model-free Friedman approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Constraints on ion velocity distributions from fusion product spectroscopy

Abstract Recent inertial confinement fusion experiments have shown primary fusion spectral moments which are incompatible with a Maxwellian velocity distribution description. These results show that an ion kinetic description of the reacting ions is necessary. We develop a theoretical classification of non-Maxwellian ion velocity distributions using the spectral moments. At the mesoscopic level, a monoenergetic decomposition of the velocity distribution reveals there are constraints on the space of spectral moments accessible by isotropic distributions. General expressions for the directionally dependent spectral moments of anisotropic distributions are derived. At the macroscopic level, a distribution of fluid element velocities modifies the spectral moments in a constrained manner. Experimental observations can be compared to these constraints to identify the character and isotropy of the underlying reactant ion velocity distribution and determine if the plasma is hydrodynamic or kinetic.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗