New PDF release: Atomic Structure Prediction of Nanostructures, Clusters and

By Dr. Cristian V. Ciobanu, Dr. Cai?Zhuang Wang, Dr. Kai?Ming Ho(auth.)

This paintings fills the space for a finished reference conveying the advancements in international optimization of atomic buildings utilizing genetic algorithms. during the last few a long time, such algorithms in line with mimicking the strategies of normal evolution have made their means from desktop technology disciplines to strong states physics and chemistry, the place they've got verified their versatility and predictive energy for plenty of fabrics. Following an creation and historic point of view, the textual content strikes directly to offer an in-depth description of the set of rules sooner than describing its purposes to crystal constitution prediction, atomic clusters, floor and interface reconstructions, and quasi one-dimensional nanostructures. the ultimate chapters supply a short account of different equipment for atomic constitution optimization and views at the way forward for the sphere.

Chapter 1 The problem of Predicting Atomic constitution (pages 1–9):
Chapter 2 The Genetic set of rules in Real?Space illustration (pages 11–35):
Chapter three Crystal constitution Prediction (pages 37–69):
Chapter four Optimization of Atomic Clusters (pages 71–86):
Chapter five Atomic constitution of Surfaces, Interfaces, and Nanowires (pages 87–147):
Chapter 6 different Methodologies for Investigating Atomic constitution (pages 149–186):
Chapter 7 views and Outlook (pages 187–189):

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Extra resources for Atomic Structure Prediction of Nanostructures, Clusters and Surfaces

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8, 825. G. (1990) Phys. Rev. , 65, 1020. L. J. (2006) Phys. Rev. B, 65, 224104. , and Roberts, C. (2002) J. Chem. , 116, 1536. L. , 4193. Trimarchi, G. and Zunger, A. (2007) Phys. Rev. B, 75, 104113. j35 j37 3 Crystal Structure Prediction This chapter addresses in more detail the problem of crystal structure prediction using genetic algorithm (GA) within the real-space representation that we have discussed in the previous chapters. As mentioned in Chapter 1, in our view the main foundational works are as follows: i) The pioneering work by Deaven and Ho [1] in which the authors put forth the cut-and-paste operations in real space and have shown that systems with N $ 60 atoms are solved successfully.

The selection probability pi proportional to fitness F i described here is often called roulette-wheel selection for the following reason. 7. 6. Another possible way to select structures for the mating pool is the tournament selection. In this type of selection, every parent is selected as a result of a tournament between a prescribed number k of members of the genetic pool: the winner of the tournament is the structure with the highest fitness value among the k randomly chosen structures. We can define, loosely, the selection pressure as being the degree to which better fit individual structures are selected for the mating pool.

Mol. : THEOCHEM, 678, 113. Z. M. (2004) J. Comput. Theor. , 1, 3. J. (2008) Phys. Rev. E, 78, 026708. F. (1998) Nature, 392, 582. M. (2009) J. Chem. Phys, 131, 124507. M. (2000) Phys. Rev. B, 61, 2329. Kresse, G. and Furthm€ uller, J. (1996) Comput. Mater. , 6, 15. 12 Plimpton, S. (1995) J. Comput. , 117, 1. R. W. (2006) J. Chem. , 124, 244704. M. (2011) Phys. Rev. B, 124, 184102. M. (2004) Surf. Sci. , 573, L375. V. and Predescu, C. (2004) Phys. Rev. B, 70, 085321. D. (2000) Model. Simul. Mater.

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