AUTHOR=Khatun Maya , Majumdar Rajat Shubhro , Anoop Anakuthil 

TITLE=A Global Optimizer for Nanoclusters

JOURNAL=Frontiers in Chemistry

VOLUME=Volume 7 - 2019

YEAR=2019

URL=https://www.frontiersin.org/journals/chemistry/articles/10.3389/fchem.2019.00644

DOI=10.3389/fchem.2019.00644

ISSN=2296-2646

ABSTRACT=We have developed a method to automatically build the global minimum and
other low-energy minima of nanoclusters. This method is implemented in PyAR
(https://github.com/anooplab/pyar/tree/development). The global optimization in PyAR involves
two parts, generation of several trial geometries and gradient-based local optimization of the trial
geometries. The generation of trial geometries uses the Tabu list to store the information of the
already used trial geometries and avoids using the similar geometries. In this recursive algorithm,
n-sized cluster is built from the geometries of n − 1 clusters. The overall procedure automatically
generates the several unique minimum energy geometries of clusters with size 2 upto n using this
evolutionary growth strategy. We have used the above mentioned strategy on some well studied
clusters such as Pd, Pt, Au, Al, binary clusters Ru-Pt and Au-Pt, and ternary clustery Ag-Au-Pt.
We have analyzed some of the popular parameters used to characterise the clusters, relative
energy, singlet-triplet energy difference, binding energy, second order energy difference, and
mixing energy and compared with the reported properties.