Atomic Structure Prediction of Nanostructures, Clusters and Surfaces (Hardcover)

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