Advanced machine learning based global optimizations for Pt nanoclusters

• Published in: Journal of the Indian Chemical Society 2023-05, Vol.100 (5), p.100978, Article 100978
• Main Authors: Gedam, Sai Prasad, Chiriki, Siva, Padmavathi, D.A.
• Format: Article
• Language: English
• Subjects: Bayesian optimizations approach; Gaussian regression process (GPR) potentials; Global optimizations (GO); Pt-nanoclusters
• ISSN: 0019-4522
• DOI: 10.1016/j.jics.2023.100978

Pt-nanoclusters have attracted attention due to their extensive use as catalysts in various sectors and their catalytic capabilities, instigating a theoretical investigation to correlate structure and property. On the other hand, it is challenging to find stable and reliable structures to support experimental results at the nanoscale due to their fluxional nature at ambient temperature. The major objective of this work is to test the capability of stable and reliable structure findings at the nanocluster region by Gaussian Process Regression (GPR) model potentials on-the-fly within the evolutionary framework using the Bayesian optimization approach. The entire algorithm is called Global Optimizations by GPR (GO-GPR) learning. In this regard, the GO-GPR algorithm examined the potential energy surfaces of bare Ptn-nanoclusters of sizes (n = 3–6, 7, 8, 10, 13). GO-GPR identified new low-lying isomers and global minimum structures are in correlation with earlier studies. In the case of Pt13 and Pt8 nano-clusters, the global minimum structure is close to the second lowest energy structure, implying that these clusters can have fluxional nature. In fact, a few experimental studies have shown that Pt8 and Pt13 are effective in catalyzing reactions. [Display omitted] •An effective global structural optimization technique for Pt-nanoclusters (Ptn) has been used, which employs active learning.•Three main basic arrangements were observed: triangular planar, square planar, and hexagonal.•In case of Pt8, both 2D and 3D structures are competitive and 2D to 3D structural transition occurs at Pt8 nanocluster.•Results indicates that, Pt8 and Pt13 nanoclusters exhibits fluxional nature and hence may be best suitable for catalysis as in accordance with experimental studies.