Mesoscopic modeling of the uniaxial compression and recovery of vertically aligned carbon nanotube forests
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Computational materials science encompasses modeling and simulation techniques that are used to improve our understanding of materials from the atomic to macroscopic scales. This talk will focus on recent applications of computational materials science to ablative thermal protection materials, including heritage PICA and state-of-the-art woven materials like HEEET. Development of advanced molecular, microscopic, and mesoscopic models will be discussed.
A multiscale modeling methodology is developed for structurally-graded material microstructures. Molecular dynamic (MD) simulations are performed at the nanoscale to determine fundamental failure mechanisms and quantify material constitutive parameters. These parameters are used to calibrate material processes at the mesoscale using discrete dislocation dynamics (DD). Different grain boundary interactions with dislocations are analyzed using DD to predict grain-size dependent stress-strain behavior. These relationships are mapped into crystal plasticity (CP) parameters to develop a computationally efficient finite element-based DD/CP model for continuum-level simulations and complete the multiscale analysis by predicting the behavior of macroscopic physical specimens. The present analysis is focused on simulating the behavior of a graded microstructure in which grain sizes are on the order of nanometers in the exterior region and transition to larger, multi-micron size in the interior domain. This microstructural configuration has been shown to offer improved mechanical properties over homogeneous coarse-grained materials by increasing yield stress while maintaining ductility. Various mesoscopic polycrystal models of structurally-graded microstructures are generated, analyzed and used as a benchmark for comparison between multiscale DD/CP model and DD predictions. A final series of simulations utilize the DD/CP analysis method exclusively to study macroscopic models that cannot be analyzed by MD or DD methods alone due to the model size.
A discrete random medium is an object in the form of a finite volume of a vacuum or a homogeneous material medium filled with quasi-randomly and quasi-uniformly distributed discrete macroscopic impurities called small particles. Such objects are ubiquitous in natural and artificial environments. They are often characterized by analyzing theoretically the results of laboratory, in situ, or remote-sensing measurements of the scattering of light and other electromagnetic radiation. Electromagnetic scattering and absorption by particles can also affect the energy budget of a discrete random medium and hence various ambient physical and chemical processes. In either case electromagnetic scattering must be modeled in terms of appropriate optical observables, i.e., quadratic or bilinear forms in the field that quantify the reading of a relevant optical instrument or the electromagnetic energy budget. It is generally believed that time-harmonic Maxwell's equations can accurately describe elastic electromagnetic scattering by macroscopic particulate media that change in time much more slowly than the incident electromagnetic field. However, direct solutions of these equations for discrete random media had been impracticable until quite recently. This has led to a widespread use of various phenomenological approaches in situations when their very applicability can be questioned. Recently, however, a new branch of physical optics has emerged wherein electromagnetic scattering by discrete and discretely heterogeneous random media is modeled directly by using analytical or numerically exact computer solutions of the Maxwell equations. Therefore, the main objective of this Report is to formulate the general theoretical framework of electromagnetic scattering by discrete random media rooted in the Maxwell- Lorentz electromagnetics and discuss its immediate analytical and numerical consequences. Starting from the microscopic Maxwell-Lorentz equations, we trace the development of the first principles formalism enabling accurate calculations of monochromatic and quasi-monochromatic scattering by static and randomly varying multiparticle groups. We illustrate how this general framework can be coupled with state-of-the-art computer solvers of the Maxwell equations and applied to direct modeling of electromagnetic scattering by representative random multi-particle groups with arbitrary packing densities. This first-principles modeling yields general physical insights unavailable with phenomenological approaches. We discuss how the first-order-scattering approximation, the radiative transfer theory, and the theory of weak localization of electromagnetic waves can be derived as immediate corollaries of the Maxwell equations for very specific and well-defined kinds of particulate medium. These recent developments confirm the mesoscopic origin of the radiative transfer, weak localization, and effective-medium regimes and help evaluate the numerical accuracy of widely used approximate modeling methodologies.
Modeling solidification microstructures has become an area of intense study in recent years. The properties of large scale cast products, ranging from automobile engine blocks to aircraft components and other industrial applications, are strongly dependent on the physics that occur at the mesoscopic and microscopic length scales during solidification. The predominant morphology found in solidification microstructures is the dendrite, a tree-like pattern of solid around which solidification proceeds. The microscopic properties of cast products are determined by the length scales of these dendrites, and their associated segregation profiles. For this reason understanding the mechanisms for pattern selection in dendritic growth has attracted a great deal of interest from the experimental and theoretical communities. In particular, a great deal of research has been undertaken to understand such issues as dendrite morphology, shape and growth speed. Experiments on dendrite evolution in pure materials by Glicksman and coworkers on succinonitrile (SCN), and more recently pivalic acid (PVA), as well as other transparent analogs of metals, have provided tests of theories for dendritic growth, and have stimulated considerable theoretical progress. These experiments have clearly demonstrated that in certain parameter ranges the physics of the dendrite tip can be characterized by a steady value for the dendrite tip velocity, radius of curvature and shape. Away from the tip, the time-dependent dendrite exhibits a characteristic sidebranching as it propagates, which is not yet well understood. These experiments are performed by observing individual dendrites growing into an undercooled melt. The experiments are characterized by the dimensionless undercooling. Most experiments are performed at low undercooling.
Conjugated polymer/silica nanocomposites with hexagonal, cubic, or lamellar mesoscopic order were synthesized by self-assembly using polymerizable amphiphilic diacetylene molecules as both structure-directing agents and monomers. The self-assembly procedure is rapid and incorporates the organic monomers uniformly within a highly ordered, inorganic environment. By tailoring the size of the oligo(ethylene glycol) headgroup of the diacetylene-containing surfactant, we varied the resulting self-assembled mesophases of the composite material. The nanostructured inorganic host altered the diacetylene polymerization behavior, and the resulting nanocomposites show unique thermo-, mechano-, and solvatochromic properties. Polymerization of the incorporated surfactants resulted in polydiacetylene (PDA)/silica nanocomposites that were optically transparent and mechanically robust. Molecular modeling and quantum calculations and (13)C spin-lattice relaxation times (T(1)) of the PDA/silica nanocomposites indicated that the surfactant monomers can be uniformly organized into precise spatial arrangements prior to polymerization. Nanoindentation and gas transport experiments showed that these nanocomposite films have increased hardness and reduced permeability as compared to pure PDA. Our work demonstrates polymerizable surfactant/silica self-assembly to be an efficient, general approach to the formation of nanostructured conjugated polymers. The nanostructured inorganic framework serves to protect, stabilize, and orient the polymer, mediate its performance, and provide sufficient mechanical and chemical stability to enable integration of conjugated polymers into devices and microsystems.