期刊
JOURNAL OF PHYSICAL CHEMISTRY C
卷 120, 期 7, 页码 3759-3765出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.jpcc.5b10226
关键词
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资金
- Engineering and Physical Sciences Research Council, U.K. (EPSRC) [EP/J010804/1]
- EPSRC [EP/L000202]
- Office of Science and Technology through EPSRC's High End Computing Programme
- EPSRC [EP/J010804/1, EP/L000202/1] Funding Source: UKRI
- Engineering and Physical Sciences Research Council [EP/L000202/1, EP/J010804/1] Funding Source: researchfish
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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