Publications

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II-VI quantum dots, such as CdSe and CdTe, are attractive as downconversion materials for solid-state lighting, because of their narrow linewidth, tunable emission. However, for these materials to have acceptable quantum yields (QYs) requires that they be coated with a II-VI shell material whose valence band offset serves to confine the hole to the core. Confinement prevents the hole from accessing surface traps that lead to nonradiative decay of the exciton. Examples of such hole-confined core/shell QDs include CdTe/CdSe and CdSe/CdS. Unfortunately, the shell can also cause problems due to lattice mismatch, which ranges from 4-6% for systems of interest. This lattice mismatch can create significant interface energies at the heterojunction and places the core under radial compression and the shell under tangential tension. At elevated temperatures (~240°C) interfacial diffusion can relax these stresses, as can surface reconstruction, which can expose the core, creating hole traps. But such high temperatures favor the hexagonal Wurtzite structure, which has lower QY than the cubic zinc blende structure, which can be synthesized at lower temperatures, ~140°C. In the absence of alloying the core/shell structure can become metastable, or even unstable, if the shell is too thick. This can cause result in an irregular shell or even island growth. But if the shell is too thin thermallyactivated transport of the hole to surface traps can occur. In our LDRD we have developed a fundamental atomistic modeling capability, based on Stillinger-Weber and Bond-Order potentials we developed for the entire II-VI class. These pseudo-potentials have enabled us to conduct large-scale atomistic simulations that have led to the computation of phase diagrams of II-VI QDs. These phase diagrams demonstrate that at elevated temperatures the zinc blende phase of CdTe with CdSe grown on it epitaxially becomes thermodynamically unstable due to alloying. This is accompanied by a loss of hole confinement and a severe drop in the QY and emission lifetime, which is confirmed experimentally for the zinc blende core/shell QDs prepared at low temperatures. These QDs have QYs as high as 95%, which makes them very attractive for lighting. Finally, to address strain relaxation in these materials we developed a model for misfit dislocation formation that we have validated through atomistic simulations.

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Certain details of the additive manufacturing process known as selective laser melting (SLM) affect the performance of the final metal part. To unleash the full potential of SLM it is crucial that the process engineer in the field receives guidance about how to select values for a multitude of process variables employed in the building process. These include, for example, the type of powder (e.g., size distribution, shape, type of alloy), orientation of the build axis, the beam scan rate, the beam power density, the scan pattern and scan rate. The science-based selection of these settings con- stitutes an intrinsically challenging multi-physics problem involving heating and melting a metal alloy, reactive, dynamic wetting followed by re-solidification. In addition, inherent to the process is its considerable variability that stems from the powder packing. Each time a limited number of powder particles are placed, the stacking is intrinsically different from the previous, possessing a different geometry, and having a different set of contact areas with the surrounding particles. As a result, even if all other process parameters (scan rate, etc) are exactly the same, the shape and contact geometry and area of the final melt pool will be unique to that particular configuration. This report identifies the most important issues facing SLM, discusses the fundamental physics associated with it and points out how modeling can support the additive manufacturing efforts.

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The subject of this work is the development of models for the numerical simulation of matter, momentum, and energy balance in heterogeneous materials. These are materials that consist of multiple phases or species or that are structured on some (perhaps many) scale(s). By computational mechanics we mean to refer generally to the standard type of modeling that is done at the level of macroscopic balance laws (mass, momentum, energy). We will refer to the flow or flux of these quantities in a generalized sense as transport. At issue here are the forms of the governing equations in these complex materials which are potentially strongly inhomogeneous below some correlation length scale and are yet homogeneous on larger length scales. The question then becomes one of how to model this behavior and what are the proper multi-scale equations to capture the transport mechanisms across scales. To address this we look to the area of generalized stochastic process that underlie the transport processes in homogeneous materials. The archetypal example being the relationship between a random walk or Brownian motion stochastic processes and the associated Fokker-Planck or diffusion equation. Here we are interested in how this classical setting changes when inhomogeneities or correlations in structure are introduced into the problem. Aspects of non-classical behavior need to be addressed, such as non-Fickian behavior of the mean-squared-displacement (MSD) and non-Gaussian behavior of the underlying probability distribution of jumps. We present an experimental technique and apparatus built to investigate some of these issues. We also discuss diffusive processes in inhomogeneous systems, and the role of the chemical potential in diffusion of hard spheres is considered. Also, the relevance to liquid metal solutions is considered. Finally we present an example of how inhomogeneities in material microstructure introduce fluctuations at the meso-scale for a thermal conduction problem. These fluctuations due to random microstructures also provide a means of characterizing the aleatory uncertainty in material properties at the mesoscale.

The performance, reproducibility and reliability of metal joints are complex functions of the detailed history of physical processes involved in their creation. Prediction and control of these processes constitutes an intrinsically challenging multi-physics problem involving heating and melting a metal alloy and reactive wetting. Understanding this process requires coupling strong molecularscale chemistry at the interface with microscopic (diffusion) and macroscopic mass transport (flow) inside the liquid followed by subsequent cooling and solidification of the new metal mixture. The final joint displays compositional heterogeneity and its resulting microstructure largely determines the success or failure of the entire component. At present there exists no computational tool at Sandia that can predict the formation and success of a braze joint, as current capabilities lack the ability to capture surface/interface reactions and their effect on interface properties. This situation precludes us from implementing a proactive strategy to deal with joining problems. Here, we describe what is needed to arrive at a predictive modeling and simulation capability for multicomponent metals with complicated phase diagrams for melting and solidification, incorporating dissolutive and composition-dependent wetting.

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The integration and stability of electrocatalytic nanostructures, which represent one level of porosity in a hierarchical structural scheme when combined with a three-dimensional support scaffold, has been studied using a combination of synthetic processes, characterization techniques, and computational methods. Dendritic platinum nanostructures have been covalently linked to common electrode surfaces using a newly developed chemical route; a chemical route equally applicable to a range of metals, oxides, and semiconductive materials. Characterization of the resulting bound nanostructure system confirms successful binding, while electrochemistry and microscopy demonstrate the viability of these electroactive particles. Scanning tunneling microscopy has been used to image and validate the short-term stability of several electrode-bound platinum dendritic sheet structures toward Oswald ripening. Kinetic Monte Carlo methods have been applied to develop an understanding of the stability of the basic nano-scale porous platinum sheets as they transform from an initial dendrite to hole containing sheets. Alternate synthetic strategies were pursued to grow dendritic platinum structures directly onto subunits (graphitic particles) of the electrode scaffold. A two-step photocatalytic seeding process proved successful at generating desirable nano-scale porous structures. Growth in-place is an alternate strategy to the covalent linking of the electrocatalytic nanostructures.

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Recent research at Sandia has discovered a new class of organic binary ionic solids with tunable optical, electronic, and photochemical properties. These nanomaterials, consisting of a novel class of organic binary ionic solids, are currently being developed at Sandia for applications in batteries, supercapacitors, and solar energy technologies. They are composed of self-assembled oligomeric arrays of very large anions and large cations, but their crucial internal arrangement is thus far unknown. This report describes (a) the development of a relevant model of nonconvex particles decorated with ions interacting through short-ranged Yukawa potentials, and (b) the results of initial Monte Carlo simulations of the self-assembly binary ionic solids.

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