Study on the structures and properties of praseodymium-doped silicon clusters PrSi n (n = 3–9) and their anions with density functional schemes

Structure and Chemical Bonding in Medium-Size Boron Clusters Doped with Praseodymium

After reports of unusually low oxidation states of lanthanide elements in Ln-B clusters and their inverse sandwich geometrical topologies, the interest shifted from boride clusters doped with transition metal (TM) elements to the boride clusters doped with lanthanide atoms. In this work, the results obtained by a combined approach consisting of CALYPSO structure predictions and density functional theory (DFT) calculations for the neutral and anionic PrB_n series, n = 7-16, are reported. A close agreement between our calculated vertical detachment energies and experimental data supports the accuracy of the results obtained. Contrary to the medium-size TM-doped medium boron clusters, which prefer three types of structural configurations, all lowest-energy states of the medium-size Pr-doped boron clusters have half-sandwich geometries. An interesting structural evolution pattern was found for both neutral and anionic PrB_n clusters at n = 7, 10, 13, and 16, which includes quasi-planar B₇ units half-sandwiching the Pr atom. Unusual oxidation numbers of +2 and +1 were found for the Pr atom in the PrB₇^- and PrB₈^- anions, respectively. Chemical bonding analysis for the neutral PrB₇ and PrB₁₃ clusters revealed that their high stability stems from interactions between Pr 5d and B 2p orbitals. A stable tubular-shaped PrB₃₀ cluster is proposed as a promising building block for boron-based nanotubes.

NWPEsSe: An Adaptive-Learning Global Optimization Algorithm for Nanosized Cluster Systems

Global optimization constitutes an important and fundamental problem in theoretical studies in many chemical fields, such as catalysis, materials, or separations problems. In this paper, a novel algorithm has been developed for the global optimization of large systems including neat and ligated clusters in the gas phase and supported clusters in periodic boundary conditions. The method is based on an updated artificial bee colony (ABC) algorithm method, that allows for adaptive-learning during the search process. The new algorithm is tested against four classes of systems of diverse chemical nature: gas phase Au₅₅, ligated Au₈²⁺, Au₈ supported on graphene oxide and defected rutile, and a large cluster assembly [Co₆Te₈(PEt₃)₆][C₆₀]_n, with sizes ranging between 1 and 3 nm and containing up to 1300 atoms. Reliable global minima (GMs) are obtained for all cases, either confirming published data or reporting new lower energy structures. The algorithm and interface to other codes in the form of an independent program, Northwest Potential Energy Search Engine (NWPEsSe), is freely available, and it provides a powerful and efficient approach for global optimization of nanosized cluster systems.

Structural growth pattern of neutral and negatively charged yttrium-doped silicon clusters YSin0/− (n=6–20): from linked to encapsulated structures

Superatom YSi₂₀⁻, with an ideal thermodynamic stability and chemical reactivity, is the most suitable building block for novel optical, optoelectronic photosensitive or catalytic nanomaterials.