Publications

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This report summarizes the work performed as part of a one-year LDRD project, 'Evolutionary Complexity for Protection of Critical Assets.' A brief introduction is given to the topics of genetic algorithms and genetic programming, followed by a discussion of relevant results obtained during the project's research, and finally the conclusions drawn from those results. The focus is on using genetic programming to evolve solutions for relatively simple algebraic equations as a prototype application for evolving complexity in computer codes. The results were obtained using the lil-gp genetic program, a C code for evolving solutions to user-defined problems and functions. These results suggest that genetic programs are not well-suited to evolving complexity for critical asset protection because they cannot efficiently evolve solutions to complex problems, and introduce unacceptable performance penalties into solutions for simple ones.

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Thermionic energy conversion in a miniature format shows potential as a viable, high efficiency, micro to macro-scale power source. A microminiature thermionic converter (MTC) with inter-electrode spacings on the order of microns has been prototyped and evaluated at Sandia. The remaining enabling technology is the development of low work function materials and processes that can be integrated into these converters to increase power production at modest temperatures (800 - 1300 K). The electrode materials are not well understood and the electrode thermionic properties are highly sensitive to manufacturing processes. Advanced theoretical, modeling, and fabrication capabilities are required to achieve optimum performance for MTC diodes. This report describes the modeling and fabrication efforts performed to develop micro dispenser cathodes for use in the MTC.

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The purpose of microstructural control is to optimize materials properties. To that end, they have developed sophisticated and successful computational models of both microstructural evolution and mechanical response. However, coupling these models to quantitatively predict the properties of a given microstructure poses a challenge. This problem arises because most continuum response models, such as finite element, finite volume, or material point methods, do not incorporate a real length scale. Thus, two self-similar polycrystals have identical mechanical properties regardless of grain size, in conflict with theory and observations. In this project, they took a tiered risk approach to incorporate microstructure and its resultant length scales in mechanical response simulations. Techniques considered include low-risk, low-benefit methods, as well as higher-payoff, higher-risk methods. Methods studied include a constitutive response model with a local length-scale parameter, a power-law hardening rate gradient near grain boundaries, a local Voce hardening law, and strain-gradient polycrystal plasticity. These techniques were validated on a variety of systems for which theoretical analyses and/or experimental data exist. The results may be used to generate improved constitutive models that explicitly depend upon microstructure and to provide insight into microstructural deformation and failure processes. Furthermore, because mechanical state drives microstructural evolution, a strain-enhanced grain growth model was coupled with the mechanical response simulations. The coupled model predicts both properties as a function of microstructure and microstructural development as a function of processing conditions.

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This report summarizes materials issues associated with advanced micromachines development at Sandia. The intent of this report is to provide a perspective on the scope of the issues and suggest future technical directions, with a focus on computational materials science. Materials issues in surface micromachining (SMM), Lithographic-Galvanoformung-Abformung (LIGA: lithography, electrodeposition, and molding), and meso-machining technologies were identified. Each individual issue was assessed in four categories: degree of basic understanding; amount of existing experimental data capability of existing models; and, based on the perspective of component developers, the importance of the issue to be resolved. Three broad requirements for micromachines emerged from this process. They are: (1) tribological behavior, including stiction, friction, wear, and the use of surface treatments to control these, (2) mechanical behavior at microscale, including elasticity, plasticity, and the effect of microstructural features on mechanical strength, and (3) degradation of tribological and mechanical properties in normal (including aging), abnormal and hostile environments. Resolving all the identified critical issues requires a significant cooperative and complementary effort between computational and experimental programs. The breadth of this work is greater than any single program is likely to support. This report should serve as a guide to plan micromachines development at Sandia.

Computational materials simulations have traditionally focused on individual phenomena: grain growth, crack propagation, plastic flow, etc. However, real materials behavior results from a complex interplay between phenomena. In this project, the authors explored methods for coupling mesoscale simulations of microstructural evolution and micromechanical response. In one case, massively parallel (MP) simulations for grain evolution and microcracking in alumina stronglink materials were dynamically coupled. In the other, codes for domain coarsening and plastic deformation in CuSi braze alloys were iteratively linked. this program provided the first comparison of two promising ways to integrate mesoscale computer codes. Coupled microstructural/micromechanical codes were applied to experimentally observed microstructures for the first time. In addition to the coupled codes, this project developed a suite of new computational capabilities (PARGRAIN, GLAD, OOF, MPM, polycrystal plasticity, front tracking). The problem of plasticity length scale in continuum calculations was recognized and a solution strategy was developed. The simulations were experimentally validated on stockpile materials.

The incorporation of vacancies, H atoms, and sp{sup 2} bond defects into single-crystal homoepitaxial (100)(2x1)- and(111)-oriented CVD diamond was simulated by atomic-scale kinetic Monte Carlo. Simulations were performed for substrate temperatures from 600 C to 1200 C with 0.4% CH{sub 4} in the feed gas, and for 0.4% to 7% CH{sub 4} feeds with a substrate temperature of 800 C. The concentrations of incorporated H atoms increase with increasing substrate temperature and feed gas composition, and sp{sup 2} bond trapping increases with increasing feed gas composition. Vacancy concentrations are low under all conditions. The ratio of growth rate to H atom concentration is highest around 800-900 C, and the growth rate to sp{sup 2} ratio is maximum around 1% CH{sub 4}, suggesting that these conditions are ideal for economical diamond growth under the simulated conditions.

The microstructural evolution of heavily deformed polycrystalline Cu is simulated by coupling a constitutive model for polycrystal plasticity with the Monte Carlo Potts model for grain growth. The effects of deformation on boundary topology and grain growth kinetics are presented. Heavy deformation leads to dramatic strain-induced boundary migration and subsequent grain fragmentation. Grain growth is accelerated in heavily deformed microstructures. The implications of these results for the thermomechanical fatigue failure of eutectic solder joints are discussed.

Diamond films were grown by chemical deposition of hydrocarbon species in a vapor composed predominantly of hydrogen. The rate constants of the surface reactions and the concentrations of the gas-phase species were used as input to a variable time step Monte Carlo algorithm, which simulates the evolution of the diamond growth surface by tracking the occupancies of surface sites. The results of the combined tight binding and density functional theory quantum mechanical calculations are presented, suggesting that the etching of isolated, monomolecular moieties occurred at an appreciable rate, while etching from larger carbon islands was nor favorable.

Grain growth experiments and simulations exhibit self-similar grain size distributions quite different from that derived via a mean field approach by Hillert [ 1]. To test whether this discrepancy is due to insufficient anneal times, two different two-dimensional grain structures with realistic topologies and Hillert grain size distributions are generated and subjected to grain growth via the Monte Carlo Potts Model (MCPM). In both cases, the observed self-similar grain size distributions deviate from the initial Hillert form and conform instead to that observed in MCPM grain growth simulations that start from a random microstructure. This suggests that the Hillert grain size distribution is not an attractor.