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1. Crystal-structure prediction via the Floppy-Box Monte Carlo algorithm: Method and application to hard (non)convex particles.

Author

de Graaf, Joost, Filion, Laura, Marechal, Matthieu, van Roij, René, and Dijkstra, Marjolein

Subjects
*CRYSTAL structure, *LOGICAL prediction, *MONTE Carlo method, *ALGORITHMS, *PARTICLES (Nuclear physics), *ANISOTROPY, *SIMULATION methods & models
Abstract

In this paper, we describe the way to set up the floppy-box Monte Carlo (FBMC) method [L. Filion, M. Marechal, B. van Oorschot, D. Pelt, F. Smallenburg, and M. Dijkstra, Phys. Rev. Lett. 103, 188302 (2009)] to predict crystal-structure candidates for colloidal particles. The algorithm is explained in detail to ensure that it can be straightforwardly implemented on the basis of this text. The handling of hard-particle interactions in the FBMC algorithm is given special attention, as (soft) short-range and semi-long-range interactions can be treated in an analogous way. We also discuss two types of algorithms for checking for overlaps between polyhedra, the method of separating axes and a triangular-tessellation based technique. These can be combined with the FBMC method to enable crystal-structure prediction for systems composed of highly shape-anisotropic particles. Moreover, we present the results for the dense crystal structures predicted using the FBMC method for 159 (non)convex faceted particles, on which the findings in [J. de Graaf, R. van Roij, and M. Dijkstra, Phys. Rev. Lett. 107, 155501 (2011)] were based. Finally, we comment on the process of crystal-structure prediction itself and the choices that can be made in these simulations. [ABSTRACT FROM AUTHOR]

Published
2012
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2. Autofocus imaging: Experimental results in an anisotropic austenitic weld.

Author

Zhang, J., Drinkwater, B. W., Wilcox, P. D., and Hunter, A.

Subjects
*IMAGING systems, *ANISOTROPY, *AUSTENITIC steel, *STEEL welding, *MONTE Carlo method, *ALGORITHMS
Abstract

The quality of an ultrasonic array image, especially for anisotropic material, depends on accurate information about acoustic properties. Inaccuracy of acoustic properties causes image degradation, e.g., blurring, errors in locating of reflectors and introduction of artifacts. In this paper, for an anisotropic austenitic steel weld, an autofocus imaging technique is presented. The array data from a series of beacons is captured and then used to statistically extract anisotropic weld properties by using a Monte-Carlo inversion approach. The beacon and imaging systems are realized using two separated arrays; one acts as a series of beacons and the other images these beacons. Key to the Monte-Carlo inversion scheme is a fast forward model of wave propagation in the anisotropic weld and this is based on the Dijkstra algorithm. Using this autofocus approach a measured weld map was extracted from an austenitic weld and used to reduce location errors, initially greater than 6mm, to less than 1mm. [ABSTRACT FROM AUTHOR]

Published
2012
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