Search NASA⌕ Search

SEARCH · Search NASA

Results for “Kinetic Modelling”

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 829 records · Page 46

Comprehensive Model of Single Particle Pulverized Coal Combustion Extended to Oxy-Coal Conditions

Oxy-fired coal combustion is a promising potential carbon capture technology. Predictive CFD simulations are valuable tools in evaluating and deploying oxy-fuel and other carbon capture technologies either as retrofit technologies or for new construction. But, accurate predictive simulations require physically realistic submodels with low computational requirements. In particular, comprehensive char oxidation and gasification models have been developed that describe multiple reaction and diffusion processes. Our work extends a comprehensive char conversion code (CCK), which treats surface oxidation and gasification reactions as well as processes such as film diffusion, pore diffusion, ash encapsulation, and annealing. In this work several submodels in the CCK code were updated with more realistic physics or otherwise extended to function in oxy-coal conditions. Improved submodels include the annealing model, the swelling model, the mode of burning parameter, and the kinetic model, as well as the addition of the chemical percolation devolatilization (CPD) model. We compare our results of the char combustion model to oxy-coal data, and further compared to parallel data sets near conventional conditions. A potential method to apply the detailed code in CFD work is given.

01 COAL, LIGNITE, AND PEAT↗

High-pressure CO 2 dissociation with nanosecond pulsed discharges

Herein we investigate the conversion of CO 2 into CO and O 2 with nanosecond repetitively pulsed (NRP) discharges in a high-pressure batch reactor. Stable discharges are obtained at up to 12 bar. By-products are measured with gas chromatography. The energy efficiency is determined for a range of processing times, pulse energy, and fill pressures. It is only weakly sensitive to the plasma operating parameters, i.e the extent of CO 2 conversion is almost linearly-dependent on the specific energy invested. A conversion rate as high as 14% is achieved with an energy efficiency of 23%. For long processing times, saturation in the yield and a drop in efficiency are observed, due to the increasing role of three-body recombination reactions, as described by zero-dimensional detailed kinetic modeling. The modeling reveals the presence of three-stage kinetics between NRP pulses, controlled by electron-impact CO 2 dissociation, vibrational relaxation, and neutral elementary kinetics. Transport effects are shown to be important for CO 2 conversion at high pressures. For fill pressures beyond 10 bar, CO 2 may locally transit into supercritical states. The supercritical plasma kinetics may bypass atomic oxygen pathways and directly convert CO 2 into O 2 . This work provides a detailed analysis of plasma-based high-pressure CO 2 conversion, which is of great relevance to future large-scale sustainable carbon capture, utilization, and storage.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

LOKI

LOKI is a simulation code that models weakly-coupled plasma evolution using Eulerian kinetic models in four phase space dimensions. The code is useful to understand basic plasma nonlinear plasma physics phenomena - in particular, wave-particle and wave-wave resonances that occur in laser plasma interactions. LOKI can simulate fundamental physical process in low-density plasmas on a scale of hundreds of light wavelengths. It does so by solving the relativistic Vlasov and Valsov-Fokker-Planck differential transport equations describing the collision less and low-collisionality evolution of charged particles in electromagnetic fields in two configuration space and two velocity space dimensions. Two principle electromagnetic models are provided: electrostatic (Poisson's Equation) and electromagnetic (Maxwell's equations).

DIMITS, ANDRIS↗

High-Pressure Turbulent Flame Speeds and Chemical Kinetics of Syngas Blends with and without Impurities

This Topical Report documents the first year of the project, from October 1, 2013 through September 30, 2014. Efforts for this project included experiments to characterize the atmospheric-pressure turbulent flame speed vessel over a range of operating conditions (fan speeds and turbulent length scales). To this end, a new LDV system was acquired and set up for the detailed characterization of the turbulence field. Much progress was made in the area of impurity kinetics, which included a numerical study of the effect of impurities such as NO2, NO, H2S, and NH3 on ignition delay times and laminar flame speeds of syngas blends at engine conditions. Experiments included a series of laminar flame speed measurements for syngas (CO/H2) blends with various levels of CH4 and C2H6 addition, and the results were compared to the chemical kinetics model of NUI Galway. Also, a final NOx kinetics mechanism including ammonia was assembled, and a journal paper was written and is now in press. Overall, three journal papers and six conference papers related to this project were published this year. Finally, much progress was made on the design of the new high-pressure turbulent flame speed facility. An overall design that includes a venting system was decided upon, and the detailed design is in progress.

Peterson, Eric↗

LOKI

LOKI is a simulation code that models weakly-coupled plasma evolution using Eulerian kinetic models in four phase space dimensions. The code is useful to understand basic plasma nonlinear plasma physics phenomena - in particular, wave-particle and wave-wave resonances that occur in laser plasma interactions. LOKI can simulate fundamental physical process in low-density plasmas on a scale of hundreds of light wavelengths. It does so by solving the Vlasov and Valsov-Fokker-Planck differential transport equations describing the collision less and low-collisionality evolution of charged particles in electromagnetic fields in two configuration space and two velocity space dimensions. Two principle electromagnetic models are provided: electrostatic (Poisson's Equation) and electromagnetic (Maxwell's equations).

Banks, Jeffrey↗

SHOCK TUBE IGNITION STUDIES OF RENEWABLE DIESEL FUELS FOR MEDIUM AND HEAVY-DUTY TRANSPORTATION

Currently extensive research on alternative fuels is being conducted due to their increasing demand to reduce greenhouse emissions. One renewable fuel studied in this work is dimethyl ether (DME) blended with propane(C3H8) as a potential mixture for heavy-duty engines used in semi-trucks. The blend has the potential to drastically reduce particulate and greenhouse gas emissions compared to a conventional diesel engine operating under similar conditions. To develop the use of mixture, one must conduct detailed conceptual and simulation studies before progressing to detail studies in CFD, engine modifications, and live testing. For simulations, accurate high-fidelity chemical kinetic models are necessary. However, the validity of the chemical kinetic mechanism for operating conditions of a heavy-duty mixing-controlled compression (MCCI) engine was widely unknown until recent work presented here and published. In this work, we studied the ignition of DME and propane blends in a shock tube under MCCI engine conditions. Ignition delay time (IDT) gathered behind the reflected shock for DME-propane mixtures for heavy-duty compression ignition (CI) engine parameters. Testing was conducted for undiluted varieties spanning from temperatures of 700 to 1100 K at pressures ranging from 55 to 84 bar for various blends (100% CH3OCH3, 100% C3H8, 60% CH3OCH3/ 40% C3H8) of DME and propane were combusted in synthetic air (21% O2/ 79% N2). Several experiments were conducted at higher pressures (90-120 bar) to improve the model performance and accuracy. The ignition delay times (IDTs) were compared to recent mechanisms, including Aramco3.0, NUIG, and Dames et al. A common trend among the mechanisms was overpredicted experimental IDTs. Further studies were conducted by a sensitivity analysis using the Dames et al. model, and critical reactions sensitive to IDTs of DME-propane mixture near 60 bar are outlined. Chemical analysis was conducted on the NTC region to explain chemical kinetics which is critical for developing MCCI heavy duty engines.

Mohammed, Zuhayr Pasha↗

Experimental and modeling study of the autoignition behavior of a standard oxygenated gasoline fuel

Gasoline surrogate models can be conveniently used to simulate the combustion behavior of fuels in internal combustion engines. Because of limitations in the number of robust models available and the high computational cost of running them, simple surrogates with only 2 or 3 components (namely n-heptane, iso-octane and toluene) have been long preferred to simulate the ignition behavior of gasoline in engine calculations. More recently, thanks to the development of new, well-validated kinetic models and the access to cheap high-performance computing, the scientific and engineering community is utilizing the higher fidelity provided by more complex mixture models. The added detail in composition can in fact better reproduce variation in the fuel reactivity with pressure (an important feature for downsized, boosted conditions) and blending behavior of real fuels. In this study, the ignition behavior of a research grade full blend oxygenated fuel matching the typical specification of US standard grade gasoline has been investigated by means of rapid compression experiments and detailed kinetic calculations. A multicomponent fuel surrogate model has been developed using compositional information and a surrogate optimization tool. Based on the experimental and computational results presented in this study, general considerations about guidelines in the formulation of gasoline fuel surrogates are provided.

autoignition↗

2D Reconstruction of Magnetotail Electron Diffusion Region Measured by MMS

Models for collisionless magnetic reconnection in near-Earth space are distinctly characterized as 2D or 3D. In 2D kinetic models, the frozen-in law for the electron fluid is usually broken by laminar dynamics involving structures set by the electron orbit size, while in 3D models the width of the electron diffusion region is broadened by turbulent effects. We present an analysis of in situ spacecraft observations from the Earth's magnetotail of a fortuitous encounter with an active reconnection region, mapping the observations onto a 2D spatial domain. While the event likely was perturbed by low-frequency 3D dynamics, the structure of the electron diffusion region remains consistent with results from a 2D kinetic simulation. As such, the event represents a unique validation of 2D kinetic, and laminar reconnection models.

79 ASTRONOMY AND ASTROPHYSICS↗

Autoignition study of binary blends of n- dodecane/1-methylnaphthalene and iso- cetane/1-methylnaphthalene

An experimental study on autoignition of two binary blends, n-dodecane/1-methylnaphthalene and iso-cetane/1-methylnaphthalene, has been conducted using a rapid compression machine. Specifically, the ignition delays of the stoichiometric blend+air mixtures were measured at elevated pressures of P C = 15 bar and 30 bar, compressed temperatures of T C = 626–944 K, and varying blending ratios of the constituents. For a given set of P C and T C , a nonlinear response of the blend reactivity with respect to the relative amount of the constituents was observed. Since a comprehensive chemical kinetic model for the blends investigated here is under development, the current ignition delay datasets serve as the needed targets for model validation. For selected conditions, ignition delay simulations were conducted to highlight and discuss the deficiencies of the literature models and the potential areas for model improvements, especially at low temperatures. In conclusion, further chemical kinetic analyses were conducted to gain understanding of the blending behavior predicted by the available model.

1-methylnaphthalene↗

A Kinetic Approach to Modeling the Manufacture of High Density Polyurethane Structural Foam: Foaming and Polymerization

This report details the study of PMDI structural foam and the development of a computational model to represent it. This polyurethane has a fast catalyst, such that foaming and polymerization occur simultaneously. The foam is over-packed to twice or more of its free rise density to reach the density of interest. Our approach is to combine model development closely with experiments to discover underlying physical phenomena, to parameterize models, and to validate the models once they have been developed. The model must be able to represent the expansion, filling of molds, curing, and final foam properties. PMDI is a chemically blown foam, where carbon dioxide is produced via the reaction of water and isocyanate. The isocyanate also reacts with polyol in a competing reaction, which produces the polymer. A new kinetic model is developed and implemented, which follows a simplified mathematical formalism that decouples these two reactions. The model predicts the polymerization reaction via condensation chemistry, where vitrification and glass transition temperature evolution must be included to correctly predict the temperature dependence of the kinetics. The foam gas generation kinetics are determined by tracking the molar concentration of both water and carbon dioxide. Understanding the thermal history and loads on the foam due to exothermicity and oven curing is very important to the results, since the kinetics and material properties are all sensitive to temperature. The conservation equations, including the equations of motion, an energy balance, and three rate equations are solved via a stabilized finite element method. We assume generalized-Newtonian rheology that is dependent on the extent of cure, gas fraction, and temperature. The conservation equations are combined with a level set method to determine the location of the free surface over time. Results from the model are compared to experimental flow visualization data and post-test X-ray computed tomography (CT) data for the density. Several geometries are investigated including a mock encapsulation part, two configurations of a mock structural part, and a bar geometry to specifically test the density model. We have found that the model predicts both average density and filling profiles well. However, it under predicts density gradients, especially in the gravity direction. Further model improvements are also discussed.

36 MATERIALS SCIENCE↗

Modelling of silicon oxynitridation by nitrous oxide using the reaction rate approach

Large technological progress in oxynitridation processing leads to the introduction of silicon oxynitride as ultra-thin gate oxide. On the theoretical side, few studies have been dedicated to the process modelling of oxynitridation. Such an objective is a considerable challenge regarding the various atomistic mechanisms occurring during this fabrication step. In this article, some progress performed to adapt the reaction rate approach for the modelling of oxynitride growth by a nitrous ambient are reported. The Ellis and Buhrman's approach is used for the gas phase decomposition modelling. Taking into account the mass balance of the species at the interface between the oxynitride and silicon, a minimal kinetic model describing the oxide growth has been calibrated and implemented. The influence of nitrogen on the reaction rate has been introduced in an empirical way. The oxidation kinetics predicted with this minimal model compares well with several experiments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Conversion of Nuclear Waste into Nuclear Waste Glass: Experimental Investigation and Mathematical Modeling

The melter feed, slurry, or calcine charged on the top of a pool of molten glass forms a floating layer of reacting material called the cold cap. Between the cold-cap top, which is covered with boiling slurry, and its bottom, where bubbles separate it from molten glass, the temperature changes by up to 1000 K. The processes that occur over this temperature interval within the cold cap include liberation of gases, conduction and consumption of heat, dissolution of quartz particles, formation and dissolution of intermediate crystalline phases, and generation of foam and gas cavities. These processes have been investigated using thermal analyses, optical and electronic microscopies, x-ray diffraction, as well as other techniques. Properties of the reacting feed, such as heat conductivity and density, were measured as functions of temperature. Investigating the structure of quenched cold caps produced in a laboratory-scale melter complemented the crucible studies. The cold cap consists of two main layers. The top layer contains solid particles dissolving in the glass-forming melt and open pores through which gases are escaping. The bottom layer contains bubbly melt or foam where bubbles coalesce into larger cavities that move sideways and release the gas to the atmosphere. The feed-to-glass conversion became sufficiently understood for representing the cold-cap processes via mathematical models. These models, which comprise heat transfer, mass transfer, and reaction kinetics models, have been developed with the final goal to relate feed parameters to the rate of glass melting.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Investigating the Adsorption–Desorption Kinetics of a Molecular Water Oxidation Catalyst at an Electrode Interface

Probing the dynamics of molecular catalysts at electrode–electrolyte interfaces is essential for understanding catalytic mechanisms. Structure-specific spectroscopic methods are particularly powerful for examining electrocatalytic interfaces but are mostly used under steady-state conditions. Herein, we combined surface-enhanced infrared absorption spectroscopy (SEIRAS) with phase-sensitive detection (PSD) to investigate the dynamics of a molecular Ir-based water oxidation catalyst at the Au–electrolyte interface. We found that the amplitude of the absorbance of the catalyst is anticorrelated to that of interfacial water. This anticorrelation can be understood by the adsorption of the electrooxidized catalyst on the electrode and concurrent displacement of interfacial water. The infrared signals from the interface exhibit an increasing phase lag with respect to the electrode potential with an increasing scan rate of the potential. Kinetic modeling suggests that the potential-dependent adsorption–desorption kinetics of the molecular catalyst on the electrode gives rise to this phase lag. Furthermore, this study shows that PSD-SEIRAS is a powerful tool for investigating the interfacial dynamics of electrocatalytic systems.

Catalysts↗

Engineering Ralstonia eutropha for Production of Isobutanol (IBT) Motor Fuel from Carbon Dioxide, Hydrogen, and Oxygen Project Final Report

This research project is a collaboration between the Sinskey laboratory at MIT and the Worden laboratory at Michigan State University. The goal of the project is to produce Isobutanol (IBT), a branched-chain alcohol that can serve as a drop-in transportation fuel, through the engineered microbial biosynthesis of Carbon Dioxide, Hydrogen, and Oxygen using a novel bioreactor. This final technical report presents the findings of both the biological engineering work at MIT that extended the native branched-chain amino acid pathway of the wild type Ralstonia eutropha H16 to perform this biosynthesis, as well as the unique design, modeling, and construction of a bioreactor for incompatible gasses at Michigan State that enabled the operational testing of the complete system. This 105 page technical report summarizing the three years of research includes 72 figures and 11 tables of findings. Ralstonia eutropha (also known as Cupriavidus necator) is a Gram-negative, facultatively chemolithoautotrophic bacteria. It has been the principle organism used for the study of polyhydroxybutyrate (PHB) polymer biosynthesis. The wild-type Ralstonia eutropha H16 produces PHB as an intracellular carbon storage material while under nutrient stress in the presence of excess carbon. Under this stress, it can accumulate approximately 80 % of its cell dry weight (CDW) as this intracellular polymer. With the restoration of the required nutrients, the cells are then able to catabolize this polymer. If extracted from the cell, this PHB polymer can be processed into biodegradable and biocompatible plastics, however for this research, it is the efficient metabolic pathway channeling the captured carbon that is of interest. R. eutropha is further unique in that it contains two carbon-fixation Calvin–Benson–Bassham cycle operons, two oxygen-tolerant hydrogenases, and several formate dehydrogenases. It has also been much studied for its ability in the presence of oxygen, to fix carbon dioxide into complex cellular molecules using the energy from hydrogen. In this research project, engineered strains of R. eutropha redirected the excess carbon from PHB storage into the production of isobutanol and 3-methyl-1-butanol (branched-chain higher alcohols). These branched-chain higher alcohols can be used directly as substitutes for fossil-based fuels and are seen as alternative biofuels to ethanol and biodiesel. Importantly, these alcohols have approximately 98 % of the energy content of gasoline, 17 % higher than the current gasoline additive ethanol, without impacting corn market production for feed or food. Unlike ethanol, these branched-chain alcohols have low vapor pressure, hygroscopicity, and water solubility, which make them readily compatible with the existing pipelines, gasoline pumps, and engines in our transportation infrastructure. While the use of alternative energies from solar, wind, geothermal, and hydroelectric has spread for stationary power applications, these energy sources cannot be effectively or efficiently employed in current or future transportation systems. With the ongoing concerns of fossil fuel availability and price stability over the long term, alternative biofuels like branched-chain higher alcohols hold promise as a suitable transportation fuel in the future. We showed in our research that various mutant strains of R. eutropha with isobutyraldehyde dehydrogenase activity, in combination with the overexpression of plasmid-borne, native branched-chain amino acid biosynthesis pathway genes and the overexpression of heterologous ketoisovalerate decarboxylase gene, would produce isobutanol and 3-methyl-1-butanol when initiated during nitrogen or phosphorus limitation. Early on, we isolated one mutant R. eutropha strain which produced over 180 mg/L branched-chain alcohols in flask culture while being more tolerant of isobutanol toxicity. After the targeted elimination of genes encoding several potential carbon sinks (ilvE, bkdAB, and aceE), the production titer of the improved to 270 mg/L isobutanol and 40 mg/L 3-methyl-1-butanol. Semicontinuous flask cultivation supplied the cells with sufficient nutrients while minimizing the toxicity caused by isobutanol. Under this cultivation, the R. eutropha mutant grew and produced more than 14 g/L branched-chain alcohols over the duration of 50 days. These results demonstrate that R. eutropha carbon flux can be redirected from PHB to branched-chain alcohols and that engineered R. eutropha can be cultivated over prolonged periods of time for product biosynthesis. While this bioengineering work was being done at the Sinskey laboratory at MIT, the researchers at the Worden laboratory at Michigan State were working on the design and construction of the required specialty bioreactor for incompatible gasses (BIG) that would allow the safe feeding of microbes on Carbon Dioxide, Hydrogen, and Oxygen without explosive results. The early design and assembly work in year 1 incorporated a novel microbubble generator to maximize the bioavailability of gasses within the system comprised of small scale hollow fiber reactors. The early success of the microbubble generator eliminated the need to investigate potentially toxic surfactants within the system. For operational control, the system design incorporated a Opto22-based control network. The researchers also selected the specific hollow fiber material suitable for the bioreactor application. A variety of commercially available hollow fiber membranes were compared with regard to their pore sizes, cell affinity, and potential interference to cell viability assays. The selected membrane with its spongy layer was then tested for diffusivity of O2 and CO2. The instrumented system was then fully assembled for experimentally measuring the heterotrophic growth rate of immobilized R. eutropha cells. The requisite procedures for inoculation, measurement, and cleaning were established enabling the system performance to be validated under controlled laboratory conditions. In year 2, the researchers completed the Opto22 based cross-platform control network, and the system’s communications across the Sartorius fermentation system and Bruker gas chromatograph was established via open platform communications (OPC) protocol. Using the revised system, measurements were taken of the R.eutropha cell growth rate and substrate mass transfer rate in the hollow fiber membrane. Several IBT recovery strategies were explored and resin adsorption was determined to be optimal solution for lab scale operations. The adsorption capacity of the resin column was then measured and IBT desorption using methanol has been demonstrated. With the growing body of experimental data in hand, mathematical models were constructed to demonstrate and map the cellular kinetics, mass transfer of heterotrophic and autotrophic substrates in the hollow fiber, and the adsorption process in the resin column. A structured kinetic model was constructed to describe the competition between cell mass generation and IBT production. The reactor was then scaled up from single fiber to a membrane area of 180 cm2 and then further to 1 ft2. In Year 3 of the research, the IBT mass transfer across the membrane was characterized within the system with experiments to empirically measure the IBT diffusion coefficient in the BIG spongy layer. Using the refined mathematical models, the researchers are now able to explain the experimental observations and predict bioreactor performance under a wide range of experimental conditions. The Big system is able to demonstrate continuous controlled operations with the integrated IBT recovery system. Both heterotrophic and autotrophic production have been shown during continuous operation with heterotrophic and autotrophic stages. Performance of BIG system has been measured during continuous run with alternating heterotrophic growth on fructose and autotrophic product formation on H2, CO2, and O2. Volumetric productivities of IBT at 325 mg/(L day) and of 3M1B at 50 mg/(L day) were achieved, which were comparable to that achieved under heterotrophic conditions. Using the mathematical model, researchers are able to predict system performance for scaled-up BIG system. The apparent diffusion coefficient of IBT in the spongy layer of XM-50 hollow fiber membranes has been measured at various lumen liquid flow rates. The experiment is simulated in COMSOL to validate the results. The constructed COMSOL model is able to simulate BIG system performance in both batch and continuous mode. Mathematical simulations of the system performance have been run to identify the most crucial operational conditions, identifying the rate-limiting factors in autotrophic production of IBT, and quantitating the rate of IBT catabolism. Investigations of the productivity of the production system have suggested and the modeling of the system has revealed a particular sensitivity to the catabolism of the produced IBT by the engineered R. eutropha. Experiments have been designed and executed to quantify the IBT catabolism of R. eutropha, which open up possibilities for further system improvements through future, targeted bioengineering of the strain. Finally, the researchers at Michigan State performed an economic analysis of the system, based on the collective results, and their findings are presented in full within the report.

08 HYDROGEN↗

Final Report, DOE Early Career Award: Predictive modeling of complex physical systems: new tools for statistical inference, uncertainty quantification, and experimental design

Predictive simulation of complex physical systems increasingly rests on the interplay of experimental observations with computational models. Key inputs, parameters, or structural aspects of models may be incomplete or unknown, and must be developed from indirect and limited observations. At the same time, quantified uncertainties are needed to qualify computational predictions in the support of design and decision-making. In this context, Bayesian statistics provides a foundation for inference from noisy and limited data, but at prohibitive computional expense. This project intends to make rigorous predictive modeling *feasible* in complex physical systems, via accelerated and scalable tools for uncertainty quantification, Bayesian inference, and experimental design. Specific objectives are as follows: 1. Develop adaptive posterior approximations and dimensionality reduction approaches for Bayesian inference in high-dimensional nonlinear systems. 2. Extend accelerated Bayesian methodologies to large-scale {\em sequential} data assimilation, fully treating nonlinear models and non-Gaussian state and parameter distributions. 3. Devise efficient surrogate-based methods for Bayesian model selection and the learning of model structure. 4. Develop scalable simulation/optimization approaches to nonlinear Bayesian experimental design, for both parameter inference and model selection. 5. Demonstrate these inferential tools on chemical kinetic models in reacting flow, constructing and refining thermochemical and electrochemical models from limited data. Demonstrate Bayesian filtering on canonical stochastic PDEs and in the dynamic estimation of inhomogeneous subsurface properties and flow fields.

97 MATHEMATICS AND COMPUTING↗

Understanding copper diffusion in CuInSe 2 with first-principles based atomistic and continuum models

We investigate the diffusion of copper in CuInSe 2 using thermodynamic and kinetic models based on density functional theory calculations, attempting to reconcile large differences in reported experimental diffusivities. We find that observations of rapid chemical diffusion can be explained by large thermodynamic factors, which we calculate using a compositionally constrained model of intrinsic point defect formation. We further characterize how copper diffusion coefficients depend on material synthesis conditions and exhibit their variation across the CuInSe 2 secondary phase diagram. In doing so, we identify stable off-stoichiometries that are dominated by either vacancy- or interstitial-mediated diffusion mechanisms. These results are employed in the development of a continuum reaction–diffusion model, which we use to simulate experimental depth profiles.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

High-Throughput Study of Diffusion and Phase Transformation Kinetics of Magnesium-Based Systems for Automotive Cast Magnesium Alloys

The objective of the proposed study is to establish a scientific foundation on kinetic modeling of diffusion, phase precipitation, and casting/solidification, in order to accelerate the design and optimization of cast magnesium (Mg) alloys for weight reduction of U.S. automotive fleet. The team has performed the following tasks: 1) study diffusion kinetics of various Mg-containing binary systems using high-throughput diffusion multiples to establish reliable diffusivity and mobility databases for the Mg-aluminum (Al)-zinc (Zn)-tin (Sn)-calcium (Ca)-strontium (Sr)-manganese (Mn) systems; 2) study the precipitation kinetics (nucleation, growth and coarsening) using both innovative dual-anneal diffusion multiples and cast model alloys to provide large amounts of kinetic data (including interfacial energy) and microstructure atlases to enable implementation of the Kampmann-Wagner numerical model to simulate phase transformation kinetics of non-spherical/non-cuboidal precipitates in Mg alloys; 3) implement a micromodel to take into account back diffusion in the solid phase in order to predict microstructure and microsegregation in multicomponent Mg alloys during dendritic solidification especially under high pressure die-casting (HPDC) conditions; and, 4) widely disseminate the data, knowledge and information using the Materials Genome Initiative infrastructure (http://www.mgidata.org) as well as publications and digital data sharing to enable researchers to identify new pathways/routes to better cast Mg alloys.

36 MATERIALS SCIENCE↗