Revisiting medium-sized silicon clusters: new lowest-energy structures for $$\hbox {Si}_{18}$$, $$\hbox {Si}_{20}$$, $$\hbox {Si}_{30}$$, and $$\hbox {Si}_{32}$$ and correlated correction of DFT misassignments
Year: 2026
Type: article
Abstract: Silicon clusters are prototype building blocks of nanoscale silicon materials, linking molecular chemistry with bulk semiconductor properties that underpin optoelectronics and quantum technologies. Herein, we revisit medium-sized silicon clusters through a workflow that combines machine-learned interatomic potentials (MLIPs), genetic-algorithm searches, electronic-structure geometry optimisations, and DLPNO-CCSD(T) benchmarking. The MLIPs were trained on TPSSh/def2-TZVP and $$\hbox {r}^2$$ r 2 SCAN-D3/def2-TZVP energies and forces, enabling rapid screening of candidate structures and broad exploration of the configurational landscape. Candidates within 15 kcal/mol of the lowest-energy structure identified by the genetic algorithm were reoptimised at the PBE0/def2-TZVP level, and we computed single-point energies with DLPNO-CCSD(T) in combination with the cc-pVDZ and cc-pVTZ basis sets. This workflow identifies new lowest-energy structures to date for Si 18 , Si 20 , Si 30 , and Si 32 . Across these clusters, the cc-pVDZ to cc-pVTZ shift in the relative energy difference between the new and previously reported minima ranges from 0.1 to 5.4 kcal/mol. For example, the corresponding gaps for Si 20 are 14.7 and 11.5 kcal/mol with cc-pVDZ and cc-pVTZ, respectively, without changing the energetic ordering of the isomers. In contrast, putative new minima identified by DFT for Si 17 , Si 22 , Si 23 , and Si 29 were not confirmed by correlated calculations, which placed these candidate structures up to 20 kcal/mol above the corresponding literature minima. This recurring discrepancy reveals a functional sensitivity in which compact cage-like motifs are overstabilised relative to more extended $${\mathscr {C}}_{\textrm{s}}$$ C s and $${\mathscr {C}}_{\textrm{2v}}$$ C 2v structures. We also report IR fingerprints for the identified low-energy structures to aid experimental assignment. Overall, these results show how MLIP-accelerated exploration, combined with selective high-level validation, enables efficient discovery and reliable assignment of low-energy structures in silicon clusters.
Source: Theoretical Chemistry Accounts
Language: English
Subfield: Atomic and Molecular Physics, and Optics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,590
Award: G3658768356
OpenAlex ID: W7203652655