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[资源] 首发计算化学领域牛书！2013年Wiley-VCH《纳米结构，团簇和表面的原子结构预测》

该书作为2013年Wiley-VCH出版的计算化学领域新书，重点针对当前纳米结构模拟方面的研究热点和遗传算法等做了介绍。值得各位老师、同学参考！

书籍名称：Atomic Structure Prediction of Nanostructures, Clusters and Surfaces
书籍作者：Cristian V. Ciobanu, Cai-Zhuang Wang, and Kai-Ming Ho
出版社：Wiley-VCH
出版日期：2013
页数：200 Pages
书籍图片(或封面)：

首发计算化学领域牛书！2013年Wiley-VCH《纳米结构，团簇和表面的原子结构预测》

书籍内容简介：
This work fills the gap for a comprehensive reference conveying the developments in global optimization of atomic structures using genetic algorithms. Over the last few decades, such algorithms based on mimicking the processes of natural evolution have made their way from computer science disciplines to solid states physics and chemistry, where they have demonstrated their versatility and predictive power for many materials. Following an introduction and historical perspective, the text moves on to provide an in-depth description of the algorithm before describing its applications to crystal structure prediction, atomic clusters, surface and interface reconstructions, and quasi one-dimensional nanostructures. The final chapters provide a brief account of other methods for atomic structure optimization and perspectives on the future of the field.
书籍目录：
Preface

1. The Challenge of Predicting Atomic Structure of Crystals or Nanostructures
1.1. Evolution: reality and algorithms
1.2. Genetic algorithms and some of their applications
1.3. Binary representation
1.4. Real-space representation
1.5. Organization of this book
References for Ch. 1

2. The Genetic Algorithm in Real-Space Representation
2.1. Structure determination problems
2.2. General procedure
2.3. Selection of parent structures
2.4. Crossover operations
2.5. Mutations
2.6. Updating the genetic pool: Survival of the fittest
2.7. Stopping criteria and subsequent analysis
References for Ch. 2

3. Crystal Structure Prediction
3.1. Complexity of the energy landscape
3.2. Interaction models
3.2.1. Classical potentials
3.2.2. DFT methods
3.2.3. Adaptive classical potentials
3.3. Constraints for improving the efficiency of GA
3.4. Assessing the diversity of the pool
3.4.1. Fingerprint function
3.4.2. Maintaining the diversity of the pool
3.5. GA for variable-composition
3.6. Mapping out phase diagrams
3.7. Examples
References for Ch. 3

4. Optimization of Atomic Clusters
4.1. Lennard-Jones clusters
4.2. Thompson problem for charged systems
4.3. Metal clusters
References for Ch. 4

5. Atomic Structure of Surfaces, Interfaces, and Nanowires
5.1. Reconstruction of surfaces as problem of global optimization
5.2. Interface structure: tilted grain boundaries in Silicon
5.3. Nanowires and nanotubes via GA optimization
References for Ch. 5

6. Other Methodologies for Atomic Structure Studies
6.1. Parallel-tempering Monte Carlo with geometric cooling schedule
6.2. Basin-hoping Monte Carlo
6.3. Minima-hoping method
6.4. Metadynamics approach for predicting phase transformations
References for Ch. 6

7. Perspectives and Future Directions
References for Ch. 7

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2015-06-02 02:32:47, 4.39 M