The Library
An artificial intelligence approach for modeling molecular self-assembly : agent-based simulations of rigid molecules
Tools
Tools
Tools
Fortuna, S. (Sara) and Troisi, Alessandro. (2009) An artificial intelligence approach for modeling molecular self-assembly : agent-based simulations of rigid molecules. Journal of Physical Chemistry B, Vol.113 (No.29). pp. 9877-9885. ISSN 1520-6106
Full text not available from this repository.
Official URL: http://dx.doi.org/10.1021/jp9030442
Abstract
Agent-based simulations are rule-based models traditionally used for the simulations of complex systems. In this paper, an algorithm based on the concept of agent-based simulations is developed to predict the lowest energy packing of a set of identical rigid molecules. The agents are identified with rigid portions of the system under investigation, and they evolve following a set of rules designed to drive the system toward the lowest energy minimum. The algorithm is compared with a conventional Metropolis Monte Carlo algorithm, and it is applied on a large set of representative models of molecules. For all the systems studied, the agent-based method consistently finds a significantly lower energy minima than the Monte Carlo algorithm because the system evolution includes elements of adaptation (new configurations induce new types of moves) and learning (past successful choices are repeated).
| Item Type: | Journal Article |
|---|---|
| Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software Q Science > QC Physics Q Science > QD Chemistry |
| Divisions: | Faculty of Science > Chemistry Faculty of Science > Centre for Scientific Computing |
| Library of Congress Subject Headings (LCSH): | Genetic algorithms, Nanoparticles, Multiagent systems, Molecules -- Models, Self-assembly (Chemistry), Crystals -- Structure |
| Journal or Publication Title: | Journal of Physical Chemistry B |
| Publisher: | American Chemical Society |
| ISSN: | 1520-6106 |
| Date: | 23 July 2009 |
| Volume: | Vol.113 |
| Number: | No.29 |
| Number of Pages: | 9 |
| Page Range: | pp. 9877-9885 |
| Identification Number: | 10.1021/jp9030442 |
| Status: | Peer Reviewed |
| Publication Status: | Published |
| Access rights to Published version: | Restricted or Subscription Access |
| Funder: | Leverhulme Trust (LT) |
| URI: | http://wrap.warwick.ac.uk/id/eprint/27592 |
Data sourced from Thomson Reuters' Web of Knowledge
Actions (login required)
 |
View Item |
