Application of a Parallel Genetic Algorithm to the Global Optimization of Gas-Phase and Supported Gold-Iridium Sub-Nanoalloys

Jack B A Davis; Sarah L. Horswell; Roy L. Johnston

doi:10.1021/acs.jpcc.5b10226

Application of a Parallel Genetic Algorithm to the Global Optimization of Gas-Phase and Supported Gold-Iridium Sub-Nanoalloys

Jack B A Davis, Sarah L. Horswell, Roy L. Johnston^*

^*Corresponding author for this work

Chemistry

Research output: Contribution to journal › Article › peer-review

24 Citations (Scopus)

273 Downloads (Pure)

Abstract

The direct density functional theory global optimization of MgO(100)-supported AuIr sub-nanoalloys is performed using the Birmingham parallel genetic algorithm (BPGA). The BPGA is a pool-based genetic algorithm for the structural characterization of nanoalloys. The parallel pool methodology utilized within the BPGA allows the code to characterize the structures of N = 4-6 Au_nIr_N-n clusters in the presence of the MgO(100) surface. The use of density functional theory allows the code to capture quantum size effects in the systems, which determine their structures. The searches reveal significant differences in structure and chemical ordering between the surface-supported and gas-phase global minimum structures.

Original language	English
Pages (from-to)	3759-3765
Number of pages	7
Journal	Journal of Physical Chemistry C
Volume	120
Issue number	7
Early online date	2 Feb 2016
DOIs	https://doi.org/10.1021/acs.jpcc.5b10226
Publication status	Published - 25 Feb 2016

ASJC Scopus subject areas

Physical and Theoretical Chemistry
Electronic, Optical and Magnetic Materials
Surfaces, Coatings and Films
General Energy

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10.1021/acs.jpcc.5b10226

Davis_et_al_Application_Parallel_Genetic_Algorithm_Journal_Physical_Chemistry_C
Final Version of record available at: http://dx.doi.org/10.1021/acs.jpcc.5b10226 Checked May 2016
Accepted author manuscript, 11.3 MBLicence: None: All rights reserved

TOUCAN: Towards an Understanding of Catalysis on Nanialloys
Johnston, R.
Engineering & Physical Science Research Council
1/09/12 → 31/05/18
Project: Research Councils

Cite this

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title = "Application of a Parallel Genetic Algorithm to the Global Optimization of Gas-Phase and Supported Gold-Iridium Sub-Nanoalloys",

abstract = "The direct density functional theory global optimization of MgO(100)-supported AuIr sub-nanoalloys is performed using the Birmingham parallel genetic algorithm (BPGA). The BPGA is a pool-based genetic algorithm for the structural characterization of nanoalloys. The parallel pool methodology utilized within the BPGA allows the code to characterize the structures of N = 4-6 AunIrN-n clusters in the presence of the MgO(100) surface. The use of density functional theory allows the code to capture quantum size effects in the systems, which determine their structures. The searches reveal significant differences in structure and chemical ordering between the surface-supported and gas-phase global minimum structures.",

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N2 - The direct density functional theory global optimization of MgO(100)-supported AuIr sub-nanoalloys is performed using the Birmingham parallel genetic algorithm (BPGA). The BPGA is a pool-based genetic algorithm for the structural characterization of nanoalloys. The parallel pool methodology utilized within the BPGA allows the code to characterize the structures of N = 4-6 AunIrN-n clusters in the presence of the MgO(100) surface. The use of density functional theory allows the code to capture quantum size effects in the systems, which determine their structures. The searches reveal significant differences in structure and chemical ordering between the surface-supported and gas-phase global minimum structures.

AB - The direct density functional theory global optimization of MgO(100)-supported AuIr sub-nanoalloys is performed using the Birmingham parallel genetic algorithm (BPGA). The BPGA is a pool-based genetic algorithm for the structural characterization of nanoalloys. The parallel pool methodology utilized within the BPGA allows the code to characterize the structures of N = 4-6 AunIrN-n clusters in the presence of the MgO(100) surface. The use of density functional theory allows the code to capture quantum size effects in the systems, which determine their structures. The searches reveal significant differences in structure and chemical ordering between the surface-supported and gas-phase global minimum structures.

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Application of a Parallel Genetic Algorithm to the Global Optimization of Gas-Phase and Supported Gold-Iridium Sub-Nanoalloys

Abstract

ASJC Scopus subject areas

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TOUCAN: Towards an Understanding of Catalysis on Nanialloys

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