Stability of small cationic platinum clusters

Literature Information

Publication Date 2018-11-09
DOI 10.1039/C8CP06092D
Impact Factor 3.676
Authors

Piero Ferrari, Peter Lievens, Ewald Janssens


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Abstract

The relative stability of small cationic platinum clusters is investigated by photofragmentation experiments. Mass spectra show a smooth intensity distribution except for a local intensity minimum at Pt5+, revealing enhanced stability of the platinum tetramer Pt4+. The possibility that radiative cooling competes with statistical fragmentation after photoexcitation is examined and it is shown that clusters in the N = 3–8 size range do not radiate on the time scale of the experiment. In the absence of radiative cooling, the mass spectra of photofragmented clusters can be well explained by dissociation energies computed using density functional theory. The large calculated HOMO–LUMO gap for Pt4+ (∼1.2 eV) is attributed to its highly symmetric structure and provides an explanation for the surprisingly low reactivity of this cluster in different gas-phase reactions.

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Source Journal

Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
Articles per Year: 3036

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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