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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.

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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Investigation of Rare Earth Elements Mobility Using Molecular Dynamics

Rare Earth Elements (REE) are critical many applications such as electronics, permanent magnets, agricultural etc. Effective separation of REEs is a challenge due to their similarities in chemical and physical properties. Current separation processes are costly and environmentally detrimental. Therefore, research on REEs mobility in water-based solvents is necessary to design effective separation processes. In this research, the key kinetic and thermodynamic parameters, including diffusion coefficient and hydration shell are determined under the influence of external electric field. The diffusion coefficient of metal ions increases due to electric field in pure water.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Sensitivity Analysis and Effective Parametrization of PEM Fuel Cell Models

The cost of proton-exchange-membrane fuel cells (PEMFCs) remains a major hurdle in large-scale commercialization of this technology. To improve their performance and reduce cost, novel materials and electrode designs are continuously envisioned, e.g., non-PGM catalyst layers, ultra-thin Pt/Pt-Ni based catalyst layers, structured ionomer arrays or NSTF catalyst layers.1 Understanding the impact of these improvement strategies can be extremely time and cost intensive due to complex physical phenomena and large design space. We have previously developed a PEMFC modeling framework2 which has been a time and cost effective tool for understanding and optimizing the complex multi-physics phenomena within PEMFCs; however, several of the cell parameters used in the modeling have large spread in measured data.3 Furthermore, several transport parameters such as water adsorption kinetics have not been accurately measured and the approximations are spread over several orders of magnitude. These uncertainties cause problems in ascertaining accuracy of the modeling approach and they reduce the predictive power of the numerical models. The aim of this work is to identify the sensitivity of PEFC numerical model outputs to various input parameters. The previously in-house developed MEA modeling framework2 is used for PEMFC modeling. The sensitivity of the model outputs with respect to inputs parameters is obtained by analyzing the condition numbers for different output-input pairs at varying operating conditions. An example of the sensitivity analysis is shown in Figure 1. The condition numbers are obtained for the entire possible range of input parameters at varying operating conditions to identify the most crucial parameters of the PEMFC model. Based on our preliminary analysis, parameters related to kinetics (exchange current density and ECSA) and heat/water management in electrodes and ionomer (ionomer fraction, thermal conductivity) are most crucial. One of the major goals of this work is to identify the most crucial set of parameters towards which the model shows maximum sensitivity. This will guide future experimentalists to measure these properties with higher accuracy. Furthermore, the sensitivity analysis will also enable us to optimize the PEMFC performance by selectively targeting the most sensitive parameters and thereby making the largest impact. Acknowledgements The work is funded under the Fuel Cell Performance and Durability Consortium (FC-PAD), by the Fuel Cell Technologies Office (FCTO), Office of Energy Efficiency and Renewable Energy (EERE), of the U.S. Department of Energy under contract number DE-AC02-05CH11231. The authors would like to thank Nathan Craig at Robert Bosch LLC for his valuable input in designing the sensitivity analysis. The authors would also like to thank Giovanna Bucci and Matthias Hanauer at Robert Bosch for their valuable inputs and discussion. References P. K. Sinha, W. Gu, A. Kongkanand and E. Thompson, J. Electrochem. Soc., 158, B831 (2011). L. M. Pant, M. R. Gerhardt, N. Macauley, R. Mukundan, R. L. Borup and A. Z. Weber, Electrochim. Acta, 326, 134963 (2019). R. Vetter and J. O. Schumacher, ArXiv181110091 Phys. (2018). Figure 1

Pant, Lalit↗
DOE OSTI2020

Probing the low-temperature chemistry of methyl hexanoate: Insights from oxygenate intermediates

Understanding the combustion of methyl esters is crucial to elucidate kinetic pathways and predict combustion parameters, soot yields, and fuel performance of biodiesel, however most kinetic studies of methyl esters have focused on smaller, surrogate model esters. Methyl hexanoate is a larger methyl ester approaching the chain length of methyl esters found in biodiesel and has not received as much research attention as other smaller esters. The purpose of this work is to present the first atmospheric pressure combustion data of methyl hexanoate, CH 3 CH 2 CH 2 CH 2 CH 2 COOCH 3 . Mixtures of 2% methyl hexanoate in O 2 and N 2 are studied using a plug flow reactor at atmospheric pressure, wall temperatures from 573 to 973 K, residence times from roughly 1-2 s., and fuel equivalence ratios of 1, 1.5, and 2. Exhaust gases are analyzed by a gas chromatograph-mass spectrometer system and species mole fractions are presented. Here, the literature model shows satisfactory agreement with the experimental species profiles and improvements for future mechanistic studies are suggested. In particular, this work proposes new unimolecular decomposition pathways of methyl hexanoate to form methanol or methyl acetate. Furthermore, the experiment detected three unsaturated esters that are direct products of the low temperature oxidation chemistry and it provides more insight into branching ratios for the formation of methyl hexanoate radicals and for the decomposition of hydroperoxyalkyl radicals.

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

Bayesian inference of Stochastic reaction networks using Multifidelity Sequential Tempered Markov Chain Monte Carlo

Stochastic reaction network models are often used to explain and predict the dynamics of gene regulation in single cells.These models usually involve several parameters, such as the kinetic rates of chemical reactions, that are not directly measurable and must be inferred from experimental data. Bayesian inference provides a rigorous probabilistic frame-work for identifying these parameters by finding a posterior parameter distribution that captures their uncertainty.Traditional computational methods for solving inference problems such as Markov Chain Monte Carlo methods based on classical Metropolis-Hastings algorithm involve numerous serial evaluations of the likelihood function, which in turn requires expensive forward solutions of the chemical master equation (CME). We propose an alternate approach based on a multifidelity extension of the Sequential Tempered Markov Chain Monte Carlo (ST-MCMC) sampler. This algorithm is built upon Sequential Monte Carlo and solves the Bayesian inference problem by decomposing it into a sequence of efficiently solved subproblems that gradually increase both model fidelity and the influence of the observed data. We reformulate the finite state projection (FSP) algorithm, a well-known method for solving the CME, to produce a hierarchy of surrogate master equations to be used in this multifidelity scheme. To determine the appropriate fidelity, we introduce a novel information-theoretic criteria that seeks to extract the most information about the ultimate Bayesian posterior from each model in the hierarchy without inducing significant bias. This novel sampling scheme is tested with high performance computing resources using biologically relevant problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Predicting encapsulant delamination in photovoltaic modules bridging photochemical reaction kinetics and fracture mechanics

Abstract Photovoltaic (PV) modules are subjected to environmental stressors (UV exposure, temperature, and humidity) that cause degradation within the encapsulant and its interfaces with adjacent glass and cell substrates. To save experimental time and to enable long‐term assessment with intensive degradation only taking place after many years, the development of predictive models is indispensable. Previous works have modeled the delamination of the ethylene vinyl acetate (EVA) encapsulant/glass and encapsulant/cell interfaces under field aging conditions with fundamental photochemical degradation reactions that lead to molecular scission and loss of interfacial adhesion, characterized by the fracture resistance, G c . However, these models were fundamentally limited in that the following aspects were not incorporated: (i) molecular crosslinking in the field, (ii) synergistic autocatalytic interactions of degradation mechanisms, (iii) connection between degraded encapsulant structure and its mechanical properties, and (iv) rigorous treatment of the plasticity contribution to G c with finite element models. Here, we present a time‐dependent multiscale model that addresses these limitations and is applicable to a wide range of encapsulants and interfaces. For the reference EVA encapsulant and its interfaces with the glass and cell, the presented model predicts an initial rise in G c in the first 3 years of field aging from crosslinking, then a subsequent sharp decline from degradation mechanisms. We used nanoindentation to measure the changes in EVA mechanical properties over exposure time to tune the model parameters. The model predictions of G c and mechanical properties match with experimental data and show an improvement compared to previous models. The model can even predict switches in failure interfaces, such as the observed EVA/cell to EVA/glass transition. We also conducted a sensitivity analysis study by varying the degradation and crosslinking kinetic parameters to demonstrate their effects on G c . Model extensions to polyolefin elastomer‐ and silicone‐encapsulants and their interfaces are also demonstrated.

Liu, Kuan↗
DOE OSTI2024

Dynamic Promotion of the Oxygen Evolution Reaction via Programmable Metal Oxides

Hydrogen gas is a promising renewable energy storage medium when produced via water electrolysis, but this process is limited by the sluggish kinetics of the anodic oxygen evolution reaction (OER). Herein, we used a microkinetic model to investigate promoting the OER using programmable oxide catalysts (i.e., forced catalyst dynamics). We found that programmable catalysts could increase current density at a fixed overpotential (100–600× over static rates) or reduce the overpotential required to reach a fixed current density of 10 mA cm –2 (45–140% reduction vs static). In our kinetic parametrization, the key parameters controlling the quality of the catalytic ratchet were the O*-to-OOH* and O*-to-OH* activation barriers. Furthermore, our findings indicate that programmable catalysts may be a viable strategy for accelerating the OER or enabling lower-overpotential operation, but a more accurate kinetic parametrization is required for precise predictions of performance, ratchet quality, and resulting energy efficiency.

Catalysts↗
DOE OSTI2020

Factors Determining Selectivity of Acid- and Base-Catalyzed Self- and Cross-Condensation of Acetone and Cyclopentanone

In a combined kinetics and density functional theory (DFT) study, we have explored several factors that affect the selectivity of acid- and base-catalyzed self- and cross-aldol condensation of acetone (ACE) and cyclopentanone (CPO). These factors include competitive adsorption, molecular structure, and electron polarization of the two ketones on the catalyst surface. Here, kinetic analysis shows that on MgO, self-condensation of both ACE and CPO is limited by the initial unimolecular enolization step. Accordingly, CPO exhibits a higher self-condensation rate than ACE due to the more favorable α-C–H abstraction by the basic O site. The thermodynamic parameters derived from the kinetic analysis indicate that under cross-condensation reaction conditions, the MgO surface fraction covered by CPO is significantly higher than that covered by ACE. Therefore, the product distribution is dominated by [CPO]-activated products ([CPO]CPO + [CPO]ACE). Also, for a given enolate (indicated as [CPO] or [ACE]), the higher surface coverage of CPO leads to enhanced C–C coupling with CPO as the electrophile ([CPO]CPO > [CPO]ACE; [ACE]CPO > [ACE]ACE). By contrast, for both acid catalysts investigated, the rate-limiting step is the bimolecular C–C coupling, with aspects of this step depending on the density of acid sites. That is, on the high-acid-density MCM-41-SO 3 H catalyst, condensation follows a bimolecular dual-site mechanism (Langmuir–Hinshelwood model). On this catalyst surface, the ACE coverage is higher than that of CPO, which causes a higher selectivity for those products in which ACE is the electrophile ([CPO]ACE > [CPO]CPO; [ACE]ACE > [ACE]CPO). Steric hindrance is another factor that affects selectivity in the same way, favoring products in which the electrophile is ACE since it presents a lower steric hindrance to C–C coupling than CPO. Therefore, the same sequence of products is obtained for the low-acid-density MCM-41-SO 3 H catalyst, which proceeds on a single-acid site with the other molecule in the liquid phase (Eley–Rideal model). In this case, the electrophile coverage is not relevant, but the steric hindrance is, yielding the same trend as above ([CPO]ACE > [CPO]CPO; [ACE]ACE > [ACE]CPO).

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

Phase transformation and growth mechanism of RF sputtered ferroelectric lead scandium tantalate (PbSc 0.5 Ta 0.5 O 3 ) films

Lead scandium tantalate (PbSc 0.5 Ta 0.5 O 3 , PST), an order/disorder ferroelectric, is a potential candidate for electrocaloric cooling and pyroelectric infrared (IR) detector. In this work, we report the phase transformation kinetics from two series of samples containing pure amorphous and mixture of amorphous and pyrochlore to desired perovskite phase using postdeposition rapid thermal processing (RTP) as well as growth mechanism of RF sputtered PST thin films using excess lead target on platinized silicon (Pt/Ti/SiO 2 /Si) substrates. We find that small changes in the temperature ramp have a large effect on the degree of perovskite conversion (ferroelectric phase), orientation (crystallographic texture), and long-range order parameter (< S 111 >). Through isothermal annealing, we obtained optimal perovskite phase at ≥700°C temperature. The phase transformation is characterized by spontaneous formation of center-type in-plane radial rosette-like structures revealed by scanning electron microscopy. The PST perovskite crystallites were found to coexist with pyrochlore in RTP annealed films. The volume fractions for perovskite and pyrochlore phase were obtained from the analysis of “rosettes” and respective X-ray diffraction intensities which helped to determine various parameters associated with phase kinetics (n, k, and activation energy, Ea) and accompanying growth. The effective activation energies of perovskite transition and growth were found to be 332 ± 11 kJ/mol (345 ± 11 kJ/mol) and 114 ± 10 kJ/mol (122 ± 10 kJ/mol), respectively, for pure amorphous only (and mixed amorphous and pyrochlore) phase following nucleation-growth controlled Avrami's equation. A linear growth rate (n~1) for the perovskite phase indicates predominant interface-controlled process and diffusion-limited phenomena thus inhibiting rosette size owing to reactant depletion and soft impingement at the grain boundary. However, the growth behavior is isotropic in two-dimension parallel to the plane of the substrates for both sample series. Furthermore, lead loss was severe for in-situ growth and RTP combined with conventional furnace annealing than those of RTP only films, which were closer to stoichiometric albeit with excess lead and marginal oxygen vacancies (V o ).

36 MATERIALS SCIENCE↗
DOE OSTI2021

Temperature-responsive smart tracers for field-measurement of inter-well thermal evolution: Heterogeneous kinetics and field demonstration

Temperature-responsive smart tracers enable advanced warning of a “premature thermal breakthrough” and may therefore improve reservoir management and reduce financial risk. A successful calculation of inter-well fluid temperatures requires that temperature-dependent kinetics are known, which typically result from homogeneous batch reactor experiments. However, recent meso-scale field experiments at the Altona Field Laboratory involving fluid flow in a discretely-fractured reservoir suggest that silica-fluid interfaces may accelerate hydrolysis kinetics. Here, the Arrhenius parameters of phenyl acetate hydrolysis are investigated under heterogeneous reaction conditions in packed-bed column experiments. The breakthrough curve of the reaction product is compared to an inert reference tracer (carbon-cored nanoparticles). Temperatures experienced during field testing ranging from 10 to 40 °C were studied using a phosphate buffer solution to maintain a near-neutral pH, as found in the reservoir. The empirically-determined pre-exponential factor and activation energy values are subsequently used in a first-order kinetic model to improve calculations of effective reservoir temperatures for these meso-scale field tests. Here, the results suggest that hydrolysis reactions can directly monitor inter-well reservoir temperatures, but only if the influence of solid-fluid interactions are carefully accounted for.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Mechanistic Study of 1,2-Dichloroethane Hydrodechlorination on Cu-Rich Pt–Cu Alloys: Combining Reaction Kinetics Experiments with DFT Calculations and Microkinetic Modeling

Cu-rich Pt–Cu bimetallic catalysts are among the most promising candidates for actively catalyzing the hydrodechlorination of 1,2-dichloroethane (1,2-DCA) toward ethylene production. Combining reaction kinetics experiments with density functional theory (DFT) calculations and mean-field microkinetic modeling, we present a systematic mechanistic study for 1,2-DCA hydrodechlorination on Cu-rich Pt–Cu alloy catalysts. Our DFT (PBE+(TS+SCS)) results suggest that increasing Cu content in the Pt–Cu alloy destabilizes C 2 -species adsorption while stabilizing the binding of atomic chlorine. The reaction energetics of all the elementary steps in the 1,2-DCA reaction network were calculated on a Pt 1 Cu 3 (111) model surface. The DFT results were then used to construct a microkinetic model, and the model-predicted reaction rates were compared with our reaction kinetics experimental results on a Cu-rich SiO 2 -supported Pt–Cu alloy catalyst through a parameter estimation procedure. Both the reaction kinetics experiments and the microkinetic model after parameter adjustments yielded 100% selectivity to ethylene. The microkinetic model pointed to a reaction pathway involving two sequential chlorine-removal steps on the Pt–Cu alloy catalyst, a mechanism distinct from the one previously identified on pure Pt/SiO 2 catalysts, which involved an initial hydrogen-removal step. Adjustments to the DFT-derived parameters indicate the possible formation of chlorine-induced Cu-enriched surface sites during 1,2-DCA hydrodechlorination conditions, sites that are more active than those encountered in the bulk Pt 1 Cu 3 (111) alloy surface. Furthermore, our study offers valuable initial insights on the 1,2-DCA hydrodechlorination reaction mechanism and the nature of the active sites on PtCu bimetallic catalysts.

1,2-Dichloroethane↗
DOE OSTI2025

Mechanistic Insights into Molecular Copper Hydride Catalysis: the Kinetic Stability of CuH Monomers toward Aggregation is a Critical Parameter for Catalyst Performance

The activity of molecular copper hydride (CuH) complexes towards the selective insertion of unsaturated hydrocarbons under mild conditions has contributed significantly to versatile methodologies for upgrading these feedstocks. However, these catalysts are particularly susceptible to deleterious aggregation, leading to the depletion of active CuH species. Little is known about the mechanisms of CuH aggregation, how it influences overall catalyst performance, and how it can be controlled. We address these challenges with mechanistic studies on a model reaction of unactivated alkene hydroboration catalyzed by (IPr*CPh 3 )CuH (LCuH). Here, we report a comprehensive mechanistic investigation of this system, identifying an aggregation pathway that continuously depletes catalytically active LCuH to form inactive CuH clusters during turnover. Deactivation of LCuH is controlled primarily by the competition between the kinetics of the initial LCuH dimerization step and that of alkene insertion. We therefore propose that a more comprehensive understanding of CuH catalyst performance must account for the kinetics of the initial LCuH dimerization step, revising a previously explored thermodynamic understanding of CuH aggregation, where the concentration of active species is controlled by equilibria established between CuH dimers and monomers. With a series of (NHC)CuH congeners (NHC = N-heterocyclic carbene), we demonstrate that ostensibly minor structural modifications to the ligand peripheries can drastically affect the LCuH dimerization kinetics, while maintaining reactivity towards on–cycle alkene insertion. We employed a computational approach based on molecular dynamics simulations to provide an in-depth understanding of how specific structural ligand modifications can substantially increase the kinetic stability of monomeric CuH catalysts. Our combined experimental and computational studies suggest strategies for rational ligand design that can be broadly applied to molecular catalyst systems that are susceptible to deactivation via aggregation pathways.

Ryan, David E. [Pacific Northwest National Laborat↗
DOE OSTI2021

Experimental and computational kinetics study of the liquid-phase hydrogenation of C=C and C=O bonds

Solvent effects on adsorption equilibrium and reaction kinetics are evaluated for hydrogenation reactions catalyzed by Pd/alumina in a series of different solvents. Three reactants – cyclohexene, benzene and benzaldehyde – and three solvents – n-heptane (HEP), methylcyclohexane (MCHA), decalin (DL) – have been investigated. Kinetic analysis of hydrogenation of cyclohexene reveals that hydrogen adsorbs on different sites from those where cyclohexene and the solvents adsorb; however, the presence of hydrogen on these separate sites affects the heats of adsorption of the hydrocarbons. When the solvent is a weakly interacting linear alkane (HEP), the rate determining step of the reaction is the first hydrogenation of adsorbed cyclohexene. Furthermore, this conclusion is supported by DFT calculations that show a higher enthalpy barrier for the first hydrogenation than for the second, while statistical thermodynamics analysis validates the physical significance of the entropy of adsorption parameters derived from the kinetic fitting of experimental data. By contrast, with solvents such as MCHA and DL, which interact more strongly with the metal surface and compete for active sites with the reactant and the surface intermediate, the rate limiting step seems to shift to the second hydrogenation step.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Observation and Modeling of the Thermal Runaway of High-Capacity Pouch Cells Due to an Internal Short Induced by an Indenter

Owing to the complexity of coupling mechanical and electrical solvers for finite element analysis (FEA) of mechanical abuse of a battery, the simulation should be performed by incorporating a local short circuit model activated based on the status of battery elements. However, the approach should also consider various other conditions of the battery simulated, such as the initial state of charge (SOC), for precise simulations of the internal short. This study proposes an approach developed with a mechanical model and single-particle battery model, along with a reaction kinetics model for thermal abuse using LS-DYNA. Several key parameters were selected, such as the activation criteria, kinetic abuse and element integration points during the internal short circuit induced by the indenter. The impact of these key parameters in the FEA on thermal runaway response for various initial SOCs from 25 to 100 % were analyzed. The FEA results obtained were compared against experimental results with various parameters such as activation criterion of internal short, kinetic abuse based on accelerating rate calorimetry (ARC) data. Finally, the root causes of the discrepancy between the FEA and experimental results are discussed regarding integration point what solver can make difference during calculation.

ENERGY STORAGE↗
DOE OSTI2022

Early stage growth of amorphous thin film: Average kinetics, nanoscale dynamics, and pressure dependence

We used the coherent grazing incidence small angle x-ray scattering technique to study the average kinetics and nanoscale dynamics during early-stage a-WSi 2 sputter deposition. The kinetic and dynamic properties are examined as a function of pressure, which is known to be a critical factor in determining final surface roughness. Surface growth kinetics and dynamics are characterized by time parameters extracted from the height-height structure factor and correlation functions. The roughness at a given length scale reaches a maximum before relaxing down to a steady state. The lateral length scale dependence and pressure dependence are then compared among the measured kinetics and dynamics time parameters. Surfaces grown at lower pressures are smoother, leading to longer correlation times. The time parameters to reach a dynamic steady state and a kinetic steady state show contrasting pressure dependence. A dynamic steady state is reached earlier than the kinetic steady state at high pressure. A more random deposition direction and lower kinetic energy at higher pressures can explain these phenomena, along with the hypothesis that larger nanoclusters form in vapor before arriving at the surface. Here, a continuum model is applied to simulate the overall behavior with mixed success.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Rapid Construction of Validated Chemistry Models for Advanced Biofuels (Co-Optima Final Report)

Computer methods were developed and demonstrated that make it possible to predict the combustion and pyrolysis chemistry of proposed biofuels, even before the biofuels are ever manufactured or experimentally tested. The methods are based on first-principles calculations of reaction rates and equilibria. A large number of complicated calculations are required, so we developed a computer workflow that automates many of the steps. With the chemical structure of the biofuel and the system conditions (temperature, pressure, compositions, etc.) as the input, the computer methods can construct a detailed kinetic model with refined parameters without intense human intervention. The automation of model construction makes it practical for a single engineer to make the predictions in a reasonable time period. The accuracy of the computer predictions was tested by measuring the time-profiles of various reaction intermediates (carbon monoxide, carbon dioxide, water, formaldehyde, methane, and ethylene) formed as the biofuels pyrolyze or ignite using sophisticated laser shock tube methods. Several biofuels, including methyl propyl ether, cyclopentanone, butyl acetate isomers, etc., were carefully studied to demonstrate the validity of the proposed computational and experimental methodology. This research project opens up the possibility for assessing some proposed biofuels on the computer without expensive experimental campaigns. The new computer methods are open source and well-documented, allowing a knowledgeable modeler to easily access the developed methods and implement them in their work routine. Moreover, they are also convenient and powerful, promising for developing the fuel chemistry models needed for use in engine simulators, facilitating co-optimization of new engine designs with new fuels.

09 BIOMASS FUELS↗
DOE OSTI2021

Kinetics of Carbon Condensation in Detonation of High Explosives: First-Order Phase Transition Theory Perspective

We report the kinetics of carbon condensation, or carbon clustering, in detonation of carbon-rich high explosives is modeled by solving a system of rate equations for concentrations of carbon particles. Unlike previous efforts, the rate equations account not only for the aggregation of particles but also for their fragmentation in a thermodynamically consistent manner. Numerical simulations are performed, yielding the distribution of particle concentrations as a function of time. In addition to that, analytical expressions are obtained for all the distinct steps and regimes of the condensation kinetics, which facilitates the analysis of the numerical results and allows one to study the sensitivity of the kinetic behavior to the variation of system parameters. The latter is important because the numerical values of many parameters are not reliably known at present. The theory of the kinetics of first-order phase transitions is found adequate to describe the general kinetic trends of carbon condensation, as described by the rate equations. Such physical phenomena and processes as the coagulation, nucleation, growth, and Ostwald ripening are observed, and their dependence on various system parameters is studied and reported. It is believed that the present work will become useful when analyzing the present and future results for the kinetics of carbon condensation, obtained from experiments or atomistic simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗