AUTHOR=Khatun Maya , Majumdar Rajat Shubhro , Anoop Anakuthil 

TITLE=A Global Optimizer for Nanoclusters

JOURNAL=Frontiers in Chemistry

VOLUME=7

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=<p>We have developed an algorithm to automatically build the global minimum and other low-energy minima of nanoclusters. This method is implemented in PyAR (<ext-link ext-link-type="uri" xlink:href="https://github.com/anooplab/pyar" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/anooplab/pyar</ext-link>) program. The global optimization in PyAR involves two parts, generation of several trial geometries and gradient-based local optimization of the trial geometries. While generating the trial geometries, a Tabu list is used for storing the information of the already used trial geometries to avoid using the similar trial geometries. In this recursive algorithm, an <italic>n</italic>-sized cluster is built from the geometries of <italic>n</italic>−1 clusters. The overall procedure automatically generates many unique minimum energy geometries of clusters with size from 2 up to <italic>n</italic> using this evolutionary growth strategy. We have used our strategy on some of the well-studied clusters such as Pd, Pt, Au, and Al homometallic clusters, Ru-Pt and Au-Pt binary clusters, and Ag-Au-Pt ternary cluster. We have analyzed some of the popular parameters to characterize the clusters, such as relative energy, singlet-triplet energy difference, binding energy, second-order energy difference, and mixing energy, and compared with the reported properties.</p>