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Title:An artificial intelligence approach for modeling molecular self-assembly: Agent Based simulations of rigid molecules
Authors:ID Fortuna, Sara, Department of Chemistry and Centre for Scientific Computing, University of Warwick, CV4 7AL, Coventry (U.K.) (Author)
ID Troisi, Alessandro, Department of Chemistry and Centre for Scientific Computing, University of Warwick, CV4 7AL, Coventry (U.K.) (Author)
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Work type:Not categorized
Typology:1.01 - Original Scientific Article
Organization:UNG - University of Nova Gorica
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).
Keywords:Self-assembly, self-organisation, agent based, Monte Carlo, rigid molecules, simulation
Year of publishing:2009
Number of pages:9877-9885
Numbering:113, 29
PID:20.500.12556/RUNG-2655 New window
COBISS.SI-ID:4530171 New window
DOI:10.1021/jp9030442 New window
Publication date in RUNG:10.10.2016
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Record is a part of a journal

Title:Journal of Physical Chemistry B
Shortened title:J. Phys. Chem. B
Publisher:American Chemical Society
Year of publishing:2009