Bulletin of the American Physical Society
2007 APS March Meeting
Volume 52, Number 1
Monday–Friday, March 5–9, 2007; Denver, Colorado
Session A6: Frontier in Computational Materials |
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Sponsoring Units: DCOMP Chair: Giulia Galli, University of California, Davis Room: Colorado Convention Center 207 |
Monday, March 5, 2007 8:00AM - 8:36AM |
A6.00001: Quantum Design of Complex Nanostructured Electronic Materials Invited Speaker: Over the last decade, our ability to predict the fundamental properties of nanoscale building blocks such as quantum dots, wires, and slabs has improved dramatically. In particular, first principles modeling techniques can now routinely predict how the structural, electronic, optical, and transport properties of these building blocks depends on their size, shape, composition, and surface structure. In this talk we present the results of three projects designed to build upon these fundamental studies to engineer novel, nanostructured materials with tailored electronic properties. These complex, nanoscale heterostructure materials utilize both the unique properties of their nanoscale building blocks and the interactions between the constituent building blocks to engineer the ideal material properties. (i) We will describe the design of a silicon/germanium nanowire based thermoelectric material whose performance is enhanced by suppressing thermal transport and enhancing electronic transport. This is achieved by engineering the nanoscale confinement and scattering of phonons and electrons. (ii) We will describe the design of a silicon based laser, constructed from silicon nanocrystals embedded in an amorphous silicon nitride matrix. Models of the electronic states in the nanocrystal, the surrounding matrix, and the interface between the two, enable us to optimize the optical efficiency of the emission and electrically pump the laser. (iii) We will describe the use of first principles models to predict the optical response of silicon nanowires. These predictions are used to interpret the results of optical scatterometry metrology which can measure the size and surface roughness of nanoscale electronic devices produced by a combination of lithography and etching. This work was performed under the auspices of the U.S. Dept. of Energy at the University of California/Lawrence Livermore National Laboratory under contract no. W-7405-Eng-48. [Preview Abstract] |
Monday, March 5, 2007 8:36AM - 9:12AM |
A6.00002: The European Theoretical Spectroscopy Facility Invited Speaker: The ETSF (www.etsf.eu) is being created as a permanent output of the EU-funded {\it Nanoquanta} Network of Excellence (www.nanoquanta.eu, 2004-8), which joins 10 groups and over 100 researchers in research on the theory and simulation of spectroscopy of electrons in matter, and related excited-state electronic properties including quantum transport. The ETSF is intended to contribute significantly to nanoscience and nanotechnology through the development and application of theoretical spectroscopy, involving close collaboration between theorists (the existing {\it Nanoquanta} groups together with further theoretical groups) and a new community of experimental and industrial researchers who wish to apply modern theories of spectroscopy. In this talk I shall review some of the scientific output of the project so far, including the development of new ideas and techniques in many-body perturbation theory and time-dependent density-functional theory, and their application to a variety of prototype and actual systems including quantum transport in nanostructures, optical absorption in biological molecules and advanced materials, optical properties of nanoclusters and nanotubes, non-linear optical response, and spectroscopies of complex surfaces. I shall also briefly describe the network's integration activities, including code interoperability and modularity, training of internal and external researchers, and the legal, financial and organizational preparations for the ETSF. [Preview Abstract] |
Monday, March 5, 2007 9:12AM - 9:48AM |
A6.00003: The prediction of crystal structure by merging knowledge methods with first principles quantum mechanics Invited Speaker: The prediction of structure is a key problem in computational materials science that forms the platform on which rational materials design can be performed. Finding structure by traditional optimization methods on quantum mechanical energy models is not possible due to the complexity and high dimensionality of the coordinate space. An unusual, but efficient solution to this problem can be obtained by merging ideas from heuristic and ab initio methods: In the same way that scientist build empirical rules by observation of experimental trends, we have developed machine learning approaches that extract knowledge from a large set of experimental information and a database of over 15,000 first principles computations, and used these to rapidly direct accurate quantum mechanical techniques to the lowest energy crystal structure of a material. \textit{Knowledge} is captured in a Bayesian probability network that relates the probability to find a particular crystal structure at a given composition to structure and energy information at other compositions. We show that this approach is highly efficient in finding the ground states of binary metallic alloys and can be easily generalized to more complex systems. [Preview Abstract] |
Monday, March 5, 2007 9:48AM - 10:24AM |
A6.00004: Quantum-Mechanical Combinatorial Design of Solids having Target Properties Invited Speaker: (1) One of the most striking aspects of solid state physics is the diversity of structural forms in which crystals appear in Nature. Not only are there many distinct crystal-types, but combinations of two or more crystalline materials (alloys) give rise to various local geometric atomic patters. The already rich repertoire of such forms has recently been significantly enhanced by the advent of artificial crystal growth techniques (MBE, STM- atom positioning, etc.) that can create desired structural forms, such as superlattices and impurity clusters even in defiance of the rules of equilibrium thermodynamics. (2) At the same time, the fields of chemistry of nanostructures and physics of structural phase-transitions have long revealed that different atomic configurations generally lead to different physical properties even without altering the chemical makeup. While the most widely - known illustration of such ``form controls function'' rule is the dramatically different color, conductivity and hardness of the allotropical forms of pure carbon (diamond,graphite, C60), the physics of semiconductor superstructures and nanostructures is full of striking examples of how optical, magnetic and transport properties depend sensitively on atomic configuration. (3) Yet, the history of material research has generally occurred via accidental discoveries of material structures having interesting physical property (semiconductivity, ferromagnetism; superconductivity etc.). This begs the question: can this discovery process be inverted, i.e. can we first articulate a desired target physical property, then search (within a class) for the configuration that has this property? (4) The number of potentially interesting atomic configurations exhibits a combinatorial explosion, so even fast synthesis or fast computations can not survey all. (5) This talk describes the recent steps made by solid state theory + computational physics to address this ``Inverse Design'' (Franceschetti {\&} Zunger, Nature, 402, 60 (1999) problem. I will show how Genetic Algorithms, in combination with efficient (``Order N'') solutions to the Pseudopotential Schrodinger equation allow us to investigate astronomical spaces of atomic configurations in search of the structure with a target physical property. Only a small fraction of all ($\sim $ 10**14 in our case) configurations need to be examined. Physical properties are either calculated on-the-fly (if it's easy), or first ``Cluster-Expanded'' (if the theory is difficult). I will illustrate this Inverse Band Structure approach for (a) Design of required band-gaps in semiconductor superlattices; (b) architecture of impurity --clusters with desired optical properties (PRL 97, 046401, 2006) (c) search for configuration of magnetic ions in semiconductors that maximize the ferromagnetic Curie temperature (PRL, 97, 047202, 2006). [Preview Abstract] |
Monday, March 5, 2007 10:24AM - 11:00AM |
A6.00005: Computational Thermoelectrics. Invited Speaker: For several decades the thermoelectric properties of materials have attracted moderate interest in the solid state physics community. It was believed that bulk materials such as Bi2Te3 have come close to the maximum attainable figure of merit ZT. The resulting efficiency for energy conversion and other applications was seen as insufficient to spur more detailed theoretical studies. In the 80's and 90's the expansion of material fabrication technologies allowing for the fabrication of nano-patterned systems and the theoretical prediction that ZT can reach values in nanostructures far larger than in bulk materials have spurred a renewed theoretical interest in thermoelectric properties. This presentation will offer a review of the computational efforts undertaken to achieve a quantitative description of the thermoelectric properties of nano-patterned materials. Evaluating ZT requires the computation of the electronic contribution to the electrical and thermal conductivities and the Seebeck coefficient, and the lattice contribution to the thermal conductivity. A brief overview of the methods mostly used in evaluating these transport properties will be given. Semiclassical approaches relying on a solution of the Boltzmann transport equation for both electrons and phonons will be described as well as Green-Kubo and non-equilibrium transport techniques. Examples will be given for bulk semiconductors such as silicon, germanium and bismuth telluride. Atomic level calculations of the thermoelectric properties for semiconductor nanostructures will also be presented. The lattice contribution to the thermal conductivity is of particular importance to maximize ZT for semiconductors. Beside the Boltzmann transport equation approach, other methods use the fluctuation-dissipation theorem or non-equilibrium molecular dynamics. Numerical results will be shown for bulk materials and nanostructures. Concluding remarks will offer an estimate of the currently achievable accuracy on the prediction of thermoelectric properties and will outline the path for improvements. [Preview Abstract] |
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