Structural Transitions in Solids: Theory, Simulations, Experiments and Visualization Techniques
- Stefano Leoni (Max-Planck Institute for Chemical Physics of Solids, Germany)
- Roman Martonak (Comenius University Bratislava, Slovakia, Slovakia)
- Michele Parrinello (Swiss Federal Institute of Technology Zurich, Lugano, Switzerland)
- Jean Favre (Swiss Supercomputing Centre (CSCS), Switzerland)
Research on novel materials is nowadays among the fastest growing fields of scientific activity, with a tremendous technological and social impact. The quest for novel materials with critical properties has boosted the developments of novel techniques to improve material fabrication. At the same time, the increasing need of a rational approach to material sciences has promoted an extensive effort on the theoretical and numerical side. The contribution and impact of theory and simulations in this field has recently grown to such an extent, that not only a reliable and firm framework can be provided, due to a large number of novel numerical methods and simulation approaches. More importantly, numerical simulations can perform truly predictively by now. This fact has opened completely new scenarios for a novel way of interaction between simulation and practice, beyond the historical dichotomy theory-experiment. Theory can not only justify experimental results, but can take on the task of guiding experiments in difficult situations, on unknown grounds. The identification of stable and metastable phases, the elucidation of reaction and transformation mechanisms, the precise and complete exploration of phase diagrams, the design of new generations of reliable potentials, are only a few of nowadays routine tasks theory can provide.
Enhanced pressure, applied to induce material transformations and to achieve distinct properties remains one of the most important experimental parameters in the search of novel materials. Most recently (Nature Material, September 2008), common ammonia, the well-known compound for producing pharmaceuticals, fertilizers and explosives and forming hydrogen-bonded solids at high pressure, has been predicted to form ionic solids of ammonium amide at even higher pressure. Already this single fact shows very clearly how the novel methods can renew established field of research, even with respect to "old", familiar compounds, providing a true rebirth even of classical fields.
This proposal moves from the awareness of this enhanced impact of simulation approaches to the understanding of complex phenomena, due to a number of novel, recent techniques and methods. It intends to bring together leading experts, practitioners and younger scientists active in all areas of this field (theory, numerical simulations, experiments, numerics of visualization, high-performance computing) to stress the truly interdisciplinary character of the field, and to further promote synergies, spread know-how and share competences. A survey of the state of the art and a close dialogue with experimentalists on the identification of novel areas of investigation will serve as input for discussions and for composing a work-flow for further methodological developments and synergies.
We intend to represent the state of the art by organizing several sessions
around central, field-shaping methods and approaches. We have identified
the following topics as particularly appealing and representative:
I) Methods from molecular dynamics: Meta-dynamics
II) Methods from molecular dynamics: Path Sampling
II) Ab initio and DFT approaches
IV) Structure Prediction Evolutionary algorithms, random search
V) High-pressure polymorphism
VI) Nucleation and Growth
VII) Geometrical and crystallographic models
VIII) New developments in classical potentials
IX) Novel methods for high-pressure experiments
X) Challenging materials
XI) Parallel visualization with millions of atoms
-Evolutionary algorithm for crystal structure prediction
Oganov, Glass - J. Chem. Phys. 124, 244704. (2006).
Simulation of structural transformations by metadynamics
Martonak, Laio and Parrinello , Phys. Rev Lett., 90, 075503 (2003).
Simulation of structural transformations by transition path sampling
Zahn, Leoni, Phys. Rev. Lett 92, 250201 (2004).
Crystal structure prediction by random search
Pickard and Needs, Phys. Rev. Lett 97, 045504. (2006)
Neural network representation of DFT potential energy surface
Behler and Parrinello, Phys. Rev. Lett., 98, 146401 (2007)