Systematic cluster growth: a structure search method for transition metal clusters
Literature Information
Peter L. Rodríguez-Kessler, Adán R. Rodríguez-Domínguez, Alvaro Muñoz-Castro
The systematic cluster growth (SCG) method is a biased structure search strategy based on a seeding process for investigating the structural evolution and growth pattern of transition metal clusters. In SCG, a set of initial structures with size n are constructed based on the equilibrium structures of the preceding n − 1 cluster isomers by adding a single atom at all inequivalent binding sites. This strategy requires a relatively low number of evaluations for global minima localization on the potential energy surface, allowing its application in first-principles calculations. The performance of SCG is tested by using the Lennard Jones (LJ) potential energy surface. The 93.7% of the best-known solutions for Lennard Jones clusters were found for n ≤ 80 by using a relatively low number of local optimizations. Most importantly, by using SCG combined with DFT calculations (SCG-DFT), we revisit and provide the ground state structures and growth pattern for transition metal clusters TMn (where TM = Ti, Ni, Cu, Ag, Pt; and n = 6–14). The application of the code for doped clusters is also discussed. A detailed description of the present method for generating the structures of the clusters is provided.
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Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.











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