SEARCH · Search NASA
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.
Evaluated sets of rate constants and photochemical cross sections compiled by the Panel are presented. The primary application of the data is in the modelling of stratospheric processes, with particular emphasis on the ozone layer and its possible perturbation by anthropogenic and natural phenomena.
Sets of rate constants and photochemical cross sections compiled which were evaluated. The primary application of the data is in the modeling of stratospheric processes on the ozone layer and its possible perturbation by anthropogenic and natural phenomena are emphasized.
Evaluated sets of rate constants and photochemical cross sections are presented. The primary application of the data is in the modeling of stratospheric processes, with particular emphasis on the ozone layer and its possible perturbation by anthropogenic and natural phenomena.
Rate constants and photochemical cross sections are presented. The primary application of the data is for modeling of the stratospheric processes, with particular emphasis on the ozone layer and its possible perturbation by anthropogenic and natural phenomena.
This is the eighth in a series of evaluated sets of rate constants and photochemical cross sections compiled by the NASA Panel for Data Evaluation. The primary application of the data is in the modeling of stratospheric processes, with particular emphasis on the ozone layer and its possible perturbation by anthropogenic and natural phenomena. Copies of this evaluation are available from the Jet Propulsion Laboratory, Documentation Section, 111-116B, California Institute of Technology, Pasadena, California, 91109.
As part of a series of evaluated sets, rate constants and photochemical cross sections compiled by the NASA Panel for Data Evaluation are provided. The primary application of the data is in the modeling of stratospheric processes, with particular emphasis on the ozone layer and its possible perturbation by anthropogenic and natural phenomena. Copies of this evaluation are available from the Jet Propulsion Laboratory.
This is the eleventh in a series of evaluated sets of rate constants and photochemical cross sections compiled by the NASA Panel for Data Evaluation. The primary application of the data is in the modeling of stratospheric processes, with special emphasis on the ozone layer and its possible perturbation by anthropogenic and natural phenomena.
This is the twelfth in a series of evaluated sets of rate constants and photochemical cross sections compiled by the NASA Panel for Data Evaluation. The primary application of the data is in the modeling of stratospheric processes, with special emphasis on the ozone layer and its possible perturbation by anthropogenic and natural phenomena.
Hydride vapor phase epitaxy (HVPE) is a promising technology that can aid in the cost reduction of III-V materials and devices manufacturing, particularly high-efficiency solar cells for space and terrestrial applications. However, recent demonstrations of ultrafast growth rates (~500 µm/h) via uncracked hydrides are not well described by present models for the growth. Therefore, it is necessary to understand the kinetics of the growth process and its coupling with transport phenomena, so as to enable fast and uniform epitaxial growth. In this work, we derive a kinetic model using experimental data and integrate it into a computational fluid dynamics simulation of an HVPE growth reactor. We also modify an existing hydride cracking model that we validate against numerical simulations and experimental data. Here, we show that the developed growth model and the improved cracking model are able to reproduce experimental growth measurements of GaAs in an existing HVPE system.
Our recent success in exploiting graphical processing units (GPUs) to accelerate quantum chemistry computations led to the development of the ab initio nanoreactor, a computational framework for automatic reaction discovery and kinetic model construction. In this work, we apply the ab initio nanoreactor to methane pyrolysis, from automatic reaction discovery to path refinement and kinetic modeling. Elementary reactions occurring during methane pyrolysis are revealed using GPU-accelerated ab initio molecular dynamics simulations. Subsequently, these reaction paths are refined at a higher level of theory with optimized reactant, product, and transition state geometries. Reaction rate coefficients are calculated by transition state theory based on the optimized reaction paths. The discovered reactions lead to a kinetic model with 53 species and 134 reactions, which is validated against experimental data and simulations using literature kinetic models. We highlight the advantage of leveraging local brute force and Monte Carlo sensitivity analysis approaches for efficient identification of important reactions. Both sensitivity approaches can further improve the accuracy of the methane pyrolysis kinetic model. The results in this work demonstrate the power of the ab initio nanoreactor framework for computationally affordable systematic reaction discovery and accurate kinetic modeling.
Organic materials are an attractive choice for structural components due to their light weight and versatility. However, because they decompose at low temperatures relative to tradiational materials they pose a safety risk due to fire and loss of structural integrity. To quantify this risk, analysts use chemical kinetics models to describe the material pyrolysis and oxidation using thermogravimetric analysis. This process requires the calibration of many model parameters to closely match experimental data. Previous efforts in this field have largely been limited to finding a single best-fit set of parameters even though the experimental data may be very noisy. Furthermore the chemical kinetics models are often simplified representations of the true de- composition process. The simplification induces model-form errors that the fitting process cannot capture. In this work we propose a methodology for calibrating decomposition models to thermogravimetric analysis data that accounts for uncertainty in the model-form and experimental data simultaneously. The methodology is applied to the decomposition of a carbon fiber epoxy composite with a three-stage reaction network and Arrhenius kinetics. The results show a good overlap between the model predictions and thermogravimetric analysis data. Uncertainty bounds capture devia- tions of the model from the data. The calibrated parameter distributions are also presented. In conclusion, the distributions may be used in forward propagation of uncertainty in models that leverage this material.
Abstract Time-resolved CO 2 and N 2 vibrational populations and translational-rotational temperature are measured in a CO 2 –N 2 plasma sustained by a ns pulse discharge burst in plane-to-plane geometry. Time-resolved, absolute number density of CO generated in the plasma is also inferred from the experimental data. CO 2 and CO vibrational populations are measured by mid-IR, tunable quantum cascade laser absorption spectroscopy, and N 2 vibrational populations are measured by the ns broadband vibrational CARS. Transient excitation of N 2 and CO 2 asymmetric stretch vibrational energy modes is detected during the discharge burst. The time-resolved rate of CO generation does not correlate with N 2 or CO 2 ( ν 3 ) vibrational temperatures, indicating that CO 2 dissociation via the vibrational excitation is insignificant at the present conditions. The rate of CO generation decreases gradually during the discharge burst. The estimated specific energy cost of the CO product is close to that of N atoms in pure nitrogen, measured previously at similar operating conditions. Comparison of the experimental data with the kinetic modeling analysis indicates that CO 2 dissociation in collisions with electronically excited N 2 molecules is the dominant channel of CO generation at the present conditions, although the inferred CO yield in these processes is significantly lower than 1. The effect of vibrational energy transfer between N 2 and CO 2 on the plasma chemical processes is insignificant. The kinetic model underpredicts a rapid reduction of the N 2 and CO 2 ( ν 3 ) vibrational temperatures during the later half of the discharge burst and in the afterglow. V–T relaxation of N 2 by N and O atoms generated in the ns pulse discharge plasma does not affect the vibrational relaxation rate in a significant way. However, rapid V–T relaxation of CO 2 by O atoms has a significant effect on the relaxation rate. The difference between the experimental data and the modeling predictions may be due to the unknown scaling of the CO 2 –O V–T rates with the vibrational quantum number.
Pellet- and reactor-scale models for Fischer–Tropsch synthesis (FTS) with a Fe–K/silica catalyst were developed to investigate the sensitivity of the hydrocarbon products and carbon dioxide selectivity to process conditions and feed composition at high temperature (350–400 °C), moderate pressure (1–10 bar), and a range of H 2 /CO ratios (3–1). The major objective of this paper is to develop, validate, and evaluate a high-temperature FTS model that is then used to assess the feasibility of process integration with syngas production. Since there is limited kinetic data available, in literature at these conditions, bench-scale reactor tests were conducted to obtain operational data for parameter fitting of kinetic expressions used in the model. This resulting kinetic model demonstrated agreement with the experimental data with an R 2 of 0.97 to the testing data set and, thus, was feasible to apply at pellet and reactor scales. Here, multiple pellet sizes were modeled to detail the role of transport limitations as the sphere’s diameter approached and exceeded 1 mm. Application of the reactor model indicated that hydrocarbon selectivity depended strongly on temperature, whereas the ratio of olefin to paraffin products decreased with increasing temperature, pressure, and H 2 /CO ratio. Product selectivity was not sensitive to the conversion of carbon monoxide. Furthermore, the roles of the pressure and H 2 /CO ratio were closely coupled. At a H 2 /CO ratio of 3, only slight variations in selectivity occurred over a pressure range of 1–20 bar, whereas at a ratio of 1, selectivity could vary by as much as 30% over the same pressure range. At pressures below 5 bar and temperatures above 350 °C, minimal selectivity to heavy hydrocarbons (C 12+ ) is obtained, and selectivity to midrange products (C 5–11 ) rapidly declined as pressure dropped below 5 bar, which indicated that an operational pressure of at least 5 bar is needed to achieve reasonable yields in this temperature range. These results, while tentative, provide guidelines for further experimentation and evaluation of integrated FTS processes.
Mafic and ultramafic rocks present an intriguing pathway for CO 2 capture through strategic enhancements to the natural silicate weathering cycle. Simultaneously, these rock types are often hosts to appreciable amounts of metals critical to U.S. energy independence, particularly in the context of alkaline mine tailings from historical metal mining. The research and scientific prerogative, then, is to identify promising mafic and ultramafic feedstocks and conduct exploratory studies to effectively recover these critical minerals while preserving the potential for mineral carbonation. The Keweenaw Peninsula of Michigan hosts the largest native Cu reservoir within basalt in the world and experienced a rich history of Cu production spanning from pre-historic times to the mid-1900s. Today, much of the Cu mining legacy remains as mine waste tailings. In this study, we examined the Cu extractability from Keweenaw Basalt tailings using a sodium glycinate solution, in comparison with acid and sodium hydroxide leaching. Experimental results showed an 85 % Cu extraction rate using sodium glycinate as the extraction solution with negligible release of other cations from the basalt. The kinetic and extraction mechanisms of Cu selective recovery using glycinate solution were discussed using time-resolved experimental data and kinetic geochemical modeling. Theoretical estimation of carbon mineralization potential of all the existing basalt waste tailings (∼500 million tons) can reach 85.5 MMT CO 2 . A total of 0.786 MMT Cu can be recovered with sodium glycinate, with a value of 7.7 billion USD. In conclusion, this novel application of alkaline glycinate for selective Cu recovery from basalt mine tailings demonstrates the viability of selective metal recovery using a non-hazardous chemical while preserving CO 2 capture potential and presents a potential pathway toward reducing energy-related emissions and providing an unconventional domestic source of critical minerals.
The antiparasitic drug niclosamide (NCL) is notable for its ability to crystallize in multiple 1:1 channel solvate forms, none of which are isostructural. Here, using a combination of time-resolved synchrotron powder X-ray diffraction and thermogravimetry, the process-induced desolvation mechanisms of methanol and acetonitrile solvates are investigated. Structural changes in both solvates follow a complicated molecular-level trajectory characterized by a sudden shift in lattice parameters several degrees below the temperature where the desolvated phase first appears. Model fitting of kinetic data obtained under isothermal heating conditions suggests that the desolvation is rate-limited by the nucleation of the solvent-free product. The desolvation pathways identified in these systems stand in contrast to previous investigations of the NCL channel hydrate, where water loss by diffusion initially yields an anhydrous isomorph that converts to the thermodynamic polymorph at significantly higher temperatures. Taking the view that each solvate lattice is a unique “pre-organized” precursor, a comparison of the pathways from different starting topologies to the same final product provides the opportunity to reevaluate assumptions of how various factors (e.g., solvent binding strength, density) influence solid-state desolvation processes.
Over the award period we made progress on all three objectives. We completed our goal of understanding the impact of cofactor recycling on pathway performance for a propanediol-related pathway (Objective 1) and coupled this data with kinetic metabolic models developed in Objective 3, resulting in several products (4 published research articles, 1 review and 3 other research manuscripts in preparation). We completed half of Objective 2 but found the pathway was incompatible with compartmentalization, which is an important but unexpected result. The details are relayed in the following sections, grouped by objective and task as applicable.
How does one take a molecule, strongly asymmetric in both shape and charge distribution, and assemble it into a crystal? We propose a model for the nucleation and crystal growth process for tetragonal lysozyme, based upon fluorescence, light, neutron, and X-ray scattering data, size exclusion chromatography experiments, dialysis kinetics, AFM, and modeling of growth rate data, from this and other laboratories. The first species formed is postulated to be a 'head to side' dimer. Through repeating associations involving the same intermolecular interactions this grows to a 4(sub 3) helix structure, that in turn serves as the basic unit for nucleation and subsequent crystal growth. High salt attenuates surface charges while promoting hydrophobic interactions. Symmetry facilitates subsequent helix-helix self-association. Assembly stability is enhanced when a four helix structure is obtained, with each bound to two neighbors. Only two unique interactions are required. The first are those for helix formation, where the dominant interaction is the intermolecular bridging anion. The second is the anti-parallel side-by-side helix-helix interaction, guided by alternating pairs of symmetry related salt bridges along each side. At this stage all eight unique positions of the P4(sub3)2(sub 1),2(sub 1) unit cell are filled. The process is one of a) attenuating the most strongly interacting groups, such that b) the molecules begin to self-associate in defined patterns, so that c) symmetry is obtained, which d) propagates as a growing crystal. Simple and conceptually obvious in hindsight, this tells much about what we are empirically doing when we crystallize macromolecules. By adjusting the growth parameters we are empirically balancing the intermolecular interactions, preferentially attenuating the dominant strong (for lysozyme the charged groups) while strengthening the lesser strong (hydrophobic) interactions. In the general case for proteins the lack of a singularly defined association pathway may lead to formation of multiple species, i.e., amorphous precipitation. Weak interactions, such as hydrogen bonds, are promiscuous, serving to strengthen rather than define specific interactions. Participation in an interaction sequesters that surface from subsequent interactions, and we expect the strongest bonds to form first. This model, its basis, how it fits into the currently understood osmotic second virial coefficient approach to crystallization, and what it suggests will be discussed.
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.