Evolutionary complexity for protection of critical assets.

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

Low work function material development for the microminiature thermionic converter.

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

Modeling pore corrosion in normally open gold- plated copper connectors.

The goal of this study is to model the electrical response of gold plated copper electrical contacts exposed to a mixed flowing gas stream consisting of air containing 10 ppb H{sub 2}S at 30 C and a relative humidity of 70%. This environment accelerates the attack normally observed in a light industrial environment (essentially a simplified version of the Battelle Class 2 environment). Corrosion rates were quantified by measuring the corrosion site density, size distribution, and the macroscopic electrical resistance of the aged surface as a function of exposure time. A pore corrosion numerical model was used to predict both the growth of copper sulfide corrosion product which blooms through defects in the gold layer and the resulting electrical contact resistance of the aged surface. Assumptions about the distribution of defects in the noble metal plating and the mechanism for how corrosion blooms affect electrical contact resistance were needed to complete the numerical model. Comparisons are made to the experimentally observed number density of corrosion sites, the size distribution of corrosion product blooms, and the cumulative probability distribution of the electrical contact resistance. Experimentally, the bloom site density increases as a function of time, whereas the bloom size distribution remains relatively independent of time. These two effects are included in the numerical model by adding a corrosion initiation probability proportional to the surface area along with a probability for bloom-growth extinction proportional to the corrosion product bloom volume. The cumulative probability distribution of electrical resistance becomes skewed as exposure time increases. While the electrical contact resistance increases as a function of time for a fraction of the bloom population, the median value remains relatively unchanged. In order to model this behavior, the resistance calculated for large blooms has been weighted more heavily

Modeling of friction-induced deformation and microstructures.

Frictional contact results in surface and subsurface damage that could influence the performance, aging, and reliability of moving mechanical assemblies. Changes in surface roughness, hardness, grain size and texture often occur during the initial run-in period, resulting in the evolution of subsurface layers with characteristic microstructural features that are different from those of the bulk. The objective of this LDRD funded research was to model friction-induced microstructures. In order to accomplish this objective, novel experimental techniques were developed to make friction measurements on single crystal surfaces along specific crystallographic surfaces. Focused ion beam techniques were used to prepare cross-sections of wear scars, and electron backscattered diffraction (EBSD) and TEM to understand the deformation, orientation changes, and recrystallization that are associated with sliding wear. The extent of subsurface deformation and the coefficient of friction were strongly dependent on the crystal orientation. These experimental observations and insights were used to develop and validate phenomenological models. A phenomenological model was developed to elucidate the relationships between deformation, microstructure formation, and friction during wear. The contact mechanics problem was described by well-known mathematical solutions for the stresses during sliding friction. Crystal plasticity theory was used to describe the evolution of dislocation content in the worn material, which in turn provided an estimate of the characteristic microstructural feature size as a function of the imposed strain. An analysis of grain boundary sliding in ultra-fine-grained material provided a mechanism for lubrication, and model predictions of the contribution of grain boundary sliding (relative to plastic deformation) to lubrication were in good qualitative agreement with experimental evidence. A nanomechanics-based approach has been developed for characterizing the mechanical response of wear surfaces. Coatings are often required to mitigate friction and wear. Amongst other factors, plastic deformation of the substrate determines the coating-substrate interface reliability. Finite element modeling has been applied to predict the plastic deformation for the specific case of diamond-like carbon (DLC) coated Ni alloy substrates

Atomic-scale kinetic Monte Carlo simulations of diamond chemical vapor deposition.

Diamond's superb mechanical, thermal, optical, and electronic properties are ideally suited for use in protective coatings, thermal management components, cold cathode emitters, and high-performance electronic devices, among others. Diamond can be chemically vapor deposited (CVD) to produce coatings and thin films, but this technique is currently expensive and difficult to control, and the details of the molecular processes that lead to diamond deposition remain unclear. The goal of this work is to construct a tool by which the nano-scale processes that lead to diamond growth, and their effects on film properties, can be examined. This is accomplished through the development of a kinetic Monte Carlo simulation method that treats diamond deposition on the atomic length scale using established chemical reaction rate data as input, while addressing deposition time scales that correspond directly to real growth experiments. The impact of the atomic-scale surface reaction processes on the growth kinetics, surface morphologies, and defect densities of single crystal CVD diamond are examined. In this way, a clearer understanding of the connection between atomic-scale deposition processes and CVD diamond film properties can be obtained. The growth kinetics and surface morphologies that develop during deposition are found to depend primarily on the details of the atomic surface features and their effects on bonding during deposition. The (110) and (111) surfaces facet under certain growth conditions. The (100) surface grows fastest and roughens, in contradiction to experimental observations. This can be rectified by the introduction of a mechanism for the preferential etching of monatomic islands on (100) facets, whereby the simulations predict slow-growing smooth (100) faces in accord with experimental observations. The trapping of H atoms is enhanced at higher substrate temperatures where the flux of larger \rm C\sb2H\sb2 molecules to the surface is high. Incorporation of sp\sp2 defects is highest for high-CH\sb4 feeds which generate less H, since H is required to convert sp2-bonded C on the surface to sp\sp3-bonded material. Vacancy incorporation is not substantial. The ratio of simulated growth rate to defect concentration is maximized around 800-950\sp\circC and 1% inlet CH\sb4, for which experiments also produce the best quality CVD diamond.Ph.D.Applied SciencesMaterials scienceUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/130901/2/9825167.pd

Quantifying uncertainty from material inhomogeneity.

Most engineering materials are inherently inhomogeneous in their processing, internal structure, properties, and performance. Their properties are therefore statistical rather than deterministic. These inhomogeneities manifest across multiple length and time scales, leading to variabilities, i.e. statistical distributions, that are necessary to accurately describe each stage in the process-structure-properties hierarchy, and are ultimately the primary source of uncertainty in performance of the material and component. When localized events are responsible for component failure, or when component dimensions are on the order of microstructural features, this uncertainty is particularly important. For ultra-high reliability applications, the uncertainty is compounded by a lack of data describing the extremely rare events. Hands-on testing alone cannot supply sufficient data for this purpose. To date, there is no robust or coherent method to quantify this uncertainty so that it can be used in a predictive manner at the component length scale. The research presented in this report begins to address this lack of capability through a systematic study of the effects of microstructure on the strain concentration at a hole. To achieve the strain concentration, small circular holes (approximately 100 {micro}m in diameter) were machined into brass tensile specimens using a femto-second laser. The brass was annealed at 450 C, 600 C, and 800 C to produce three hole-to-grain size ratios of approximately 7, 1, and 1/7. Electron backscatter diffraction experiments were used to guide the construction of digital microstructures for finite element simulations of uniaxial tension. Digital image correlation experiments were used to qualitatively validate the numerical simulations. The simulations were performed iteratively to generate statistics describing the distribution of plastic strain at the hole in varying microstructural environments. In both the experiments and simulations, the deformation behavior was found to depend strongly on the character of the nearby microstructure

Understanding and controlling low-temperature aging of nanocrystalline materials.

Nanocrystalline copper lms were created by both repetitive high-energy pulsed power, to produce material without internal nanotwins; and pulsed laser deposition, to produce nan- otwins. Samples of these lms were indented at ambient (298K) and cryogenic temperatures by immersion in liquid nitrogen (77K) and helium (4K). The indented samples were sectioned through the indented regions and imaged in a scanning electron microscope. Extensive grain growth was observed in the lms that contained nanotwins and were indented cryogenically. The lms that either lacked twins, or were indented under ambient conditions, were found to exhibit no substantial grain growth by visual inspection. Precession transmission elec- tron microscopy was used to con rm these ndings quantitatively, and show that 3 and 7 boundaries proliferate during grain growth, implying that these interface types play a key role in governing the extensive grain growth observed here. Molecular dynamics sim- ulations of the motion of individual grain boundaries demonstrate that speci c classes of boundaries - notably 3 and 7 - exhibit anti- or a-thermal migration, meaning that their mobilities either increase or do not change signi cantly with decreasing temperature. An in-situ cryogenic indentation capability was developed and implemented in a transmission electron microscope. Preliminary results do not show extensive cryogenic grain growth in indented copper lms. This discrepancy could arise from the signi cant di erences in con g- uration and loading of the specimen between the two approaches, and further research and development of this capability is needed

Microstructure-based approach for predicting crack initiation and early growth in metals.

Fatigue cracking in metals has been and is an area of great importance to the science and technology of structural materials for quite some time. The earliest stages of fatigue crack nucleation and growth are dominated by the microstructure and yet few models are able to predict the fatigue behavior during these stages because of a lack of microstructural physics in the models. This program has developed several new simulation tools to increase the microstructural physics available for fatigue prediction. In addition, this program has extended and developed microscale experimental methods to allow the validation of new microstructural models for deformation in metals. We have applied these developments to fatigue experiments in metals where the microstructure has been intentionally varied

Crossing the mesoscale no-man<U+2019>s land via parallel kinetic Monte Carlo.

The kinetic Monte Carlo method and its variants are powerful tools for modeling materials at the mesoscale, meaning at length and time scales in between the atomic and continuum. We have completed a 3 year LDRD project with the goal of developing a parallel kinetic Monte Carlo capability and applying it to materials modeling problems of interest to Sandia. In this report we give an overview of the methods and algorithms developed, and describe our new open-source code called SPPARKS, for Stochastic Parallel PARticle Kinetic Simulator. We also highlight the development of several Monte Carlo models in SPPARKS for specific materials modeling applications, including grain growth, bubble formation, diffusion in nanoporous materials, defect formation in erbium hydrides, and surface growth and evolution