Publications

Biological systems create proteins that perform tasks more efficiently and precisely than conventional chemicals. For example, many plants and animals produce proteins to control the freezing of water. Biological antifreeze proteins (AFPs) inhibit the solidification process, even below the freezing point. These molecules bond to specific sites at the ice/water interface and are theorized to suppress solidification chemically or geometrically. In this project, we investigated the theoretical and experimental data on AFPs and performed analyses to understand the unique physics of AFPs. The experimental literature was analyzed to determine chemical mechanisms and effects of protein bonding at ice surfaces, specifically thermodynamic freezing point depression, suppression of ice nucleation, decrease in dendrite growth kinetics, solute drag on the moving solid/liquid interface, and stearic pinning of the ice interface. Stearic pinning was found to be the most likely candidate to explain experimental results, including freezing point depression, growth morphologies, and thermal hysteresis. A new stearic pinning model was developed and applied to AFPs, with excellent quantitative results. Understanding biological antifreeze mechanisms could enable important medical and engineering applications, but considerable future work will be necessary.

Abstract not provided.

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.

Abstract not provided.

The Microsystems Subgrid Physics project is intended to address gaps between developing high-performance modeling and simulation capabilities and microdomain specific physics. The initial effort has focused on incorporating electrostatic excitations, adhesive surface interactions, and scale dependent material and thermal properties into existing modeling capabilities. Developments related to each of these efforts are summarized, and sample applications are presented. While detailed models of the relevant physics are still being developed, a general modeling framework is emerging that can be extended to incorporate evolving material and surface interaction modules.

A kinetic, three-dimensional Monte Carlo model for simulating grain growth in the presence of mobile pores is presented. The model was used to study grain growth and pore migration by surface diffusion in an idealized geometry that ensures constant driving force for grain growth. The driving forces, pore size, and pore mobilities were varied to study their effects on grain-boundary mobility and grain growth. The simulations captured a variety of complex behaviors, including reduced grain-boundary velocity due to pore drag that has been predicted by analytical theories. The model is capable of treating far more complex geometries, including polycrystals. We present the capabilities of this model and discuss its limitations.

Abstract not provided.

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 origin of recrystallization nuclei is reviewed with particular emphasis on materials in which well-developed cells are present in the deformed state. Nucleation is discussed in terms of coarsening of the subgrain network that develops on annealing and an analogy is made with abnormal grain growth. The results of a theoretical analysis of abnormal growth are summarized. The Monte Carlo model for grain growth is adapted for variable grain boundary energy and mobility in order to investigate the behavior of individual grains with special properties. The simulation results show that both energy and mobility affect abnormal growth as expected from the theoretical analysis. The results are discussed in terms of the stability that subgrain networks may exhibit depending on their mean misorientation.

The application of computer simulation to grain growth and recrystallization was strongly stimulated in the early 80s by the realization that Monte Carlo models could be applied to problems of grain structure evolution. By extension of the Ising model for domain modeling of magnetic domains to the Potts model (with generalized spin numbers) it was then possible to represent discretely grains (domains) by regions of similarly oriented sets of material (lattice) points. In parallel with this fascinating development, there also occured notable work on analytical models, especially by Abbruzzese and Bunge, which has been particularly useful for understanding the variation of texture (crystallographic preferred orientation) during grain growth processes. Geometric models of recrystallization, worked on most recently and productively by Nes et al., have been useful in connection with grain size prediction as a result of recrystallization. Also, mesh-based models have been developed to a high degree by Kawasaki, Fradkov and others, and, rather recently, by Humphreys to model not just grain growth but also the nucleation process in recrystallization. These models have the strength that they deal with the essential features of grains, i.e. the nodes, but have some limitations when second phases must be considered. These various approaches to modeling of recrystallization processes will be reviewed, with a special emphasis on practical approaches to implementing the Potts model. This model has been remarkably successful in modeling such diverse phenomena as dynamic recrystallization, secondary recrystallization (abnormal grain growth), particle-inhibited recrystallization, and grain structure evolution in soldering and welding. In summary, the application of mesoscopic simulation to the phenomenon of recrystallization has yielded much new insight into some longstanding deficiencies in our understanding.

This paper describes the use of computerized simulation to model microstructures of various materials.