Scalable properties of metal clusters: A comparative DFT study of ionic-core treatments

Extending the cluster scaling technique to ruthenium clusters with hcp structures

“…Indeed this offset turns out to be nearly constant as the decrements from the extrapolated bulk value for the hcp clusters with both treatments match within less than 1 kJ/mol; the same holds for the two fcc series where the differences are even smaller, below 384 0.4 kJ/mol. A previous cluster scaling study[20] found only a small difference in the cohesive energies between AE and PAW core-level represen-…”

Size-dependent properties of transition metal clusters: from molecules to crystals and surfaces – computational studies with the program ParaGauss

“…6,[15][16][17] The economical relevance 18 of industrial applications represents an especially strong driving force for scientific research aiming at a detailed understanding of the properties of TM clusters and NPs. 3,[38][39][40][41][42][43][44][45][46][47][48][49][50][51] Indeed, the physical and chemical properties of such systems follow scaling laws as they slowly approach their corresponding bulk limits. 16,[19][20][21][22][23][24] In such combined studies the experimentally examined systems need to be as close as possible to the models used in the corresponding computational studies.…”

“…Often enough, synergy effects resulting from joint experimental and computational studies turn out to be essential for gaining insights at the atomic level. 3,[39][40][41][42][43][44][45][46][47][48][49][50][51] The onset of this latter scaling behavior, hence the beginning of the so-called scalable regime, is smooth and the cluster sizes at which it occurs depend on the atomic element of the particles at hand and the property under study. With regard to nanocatalysis 6,[25][26][27] this requirement can impose considerable problems as the catalytically active species employed in industrial processes often are significantly larger than the computational models for which accurate calculations are feasible, 24,25 e.g., by means of Kohn-Sham (KS) density functional theory (DFT).…”

“…With regard to nanocatalysis 6,[25][26][27] this requirement can impose considerable problems as the catalytically active species employed in industrial processes often are significantly larger than the computational models for which accurate calculations are feasible, 24,25 e.g., by means of Kohn-Sham (KS) density functional theory (DFT). [39][40][41][42][43][44][45][46][47][48][49][50][51] From results for a series of such medium-sized clusters, scaling laws (Section 2.1) then can be invoked to extrapolate the properties of much larger NPs. 9,24 Modern cluster sources based on sputtering, 29 laser vaporization, 30,31 pulsed microplasma, 32 or discharge techniques 33 can generate particles in a wide range of sizes, but specific mass-selection is only guaranteed for species consisting of a few atoms.…”

“…9,24 Modern cluster sources based on sputtering, 29 laser vaporization, 30,31 pulsed microplasma, 32 or discharge techniques 33 can generate particles in a wide range of sizes, but specific mass-selection is only guaranteed for species consisting of a few atoms. 3,[39][40][41][42]44,45,[48][49][50][51] As those latter systems often are better defined in experiments than are individual clusters (see above), such comparisons are very advantageous for methodological assessments. 9,24 The properties of smaller clusters often change dramatically [3][4][5][6]14,16,17,24,34 upon addition of a single atom, hence approaches such as the ''superatom'' concept [35][36][37] are more suitable for their description.…”