A new adaptive mutation simulated annealing algorithm: application to the study of pure and mixed Pt–Pd clusters

An Improved Self-Adaptive Differential Evolution with the Neighborhood Search Algorithm for Global Optimization of Bimetallic Clusters

Global optimization of multicomponent cluster structures is considerably time-consuming due to the existence of a vast number of isomers. In this work, we proposed an improved self-adaptive differential evolution with the neighborhood search (SaNSDE) algorithm and applied it to the global optimization of bimetallic cluster structures. The cross operation was optimized, and an improved basin hopping module was introduced to enhance the searching efficiency of SaNSDE optimization. Taking (PtNi)_N (N = 38 or 55) bimetallic clusters as examples, their structures were predicted by using this algorithm. The traditional SaNSDE algorithm was carried out for comparison with the improved SaNSDE algorithm. For all the optimized clusters, the excess energy and the second difference of the energy were calculated to examine their relative stabilities. Meanwhile, the bond order parameters were adopted to quantitatively characterize the cluster structures. The results reveal that the improved SaNSDE algorithm possessed significantly higher searching capability and faster convergence speed than the traditional SaNSDE algorithm. Furthermore, the lowest-energy configurations of (PtNi)₃₈ clusters could be classified as the truncated octahedral and disordered structures. In contrast, all the optimal (PtNi)₅₅ clusters were approximately icosahedral. Our work fully demonstrates the high efficiency of the improved algorithm and advances the development of global optimization algorithms and the structural prediction of multicomponent clusters.

Structure elucidation and construction of isomerisation pathways in small to moderate-sized (6-27) MgO nanoclusters: an adaptive mutation simulated annealing based analysis with quantum chemical calculations

Determination of global minimum structures and elucidation of reaction paths or minimum energy paths between low-lying minima are of great chemical importance. To that end, we have used our own Adaptive Mutation Simulated Annealing method to determine the global minimum and the minimum energy paths for various isomerisation reactions for small to moderate-sized (MgO)n (n = 6-27) clusters, using the Born-Mayer potential with suitable parameter values. The minimum energy structures obtained by us match well with previously reported data and are used as guess structures for further optimisation at the DFT level (using the B3LYP functional and DGDZVP basis set). Our optimised structures are found to match very well with the further DFT optimised structures, where the comparison is done by determining the root mean square deviation values as well as the radial distribution function profiles. A scheme is proposed to determine the minimum energy paths for isomerisation reactions for some cluster sizes where the transition state/s obtained by us, at very low computational cost, match well with those obtained from further optimisation using DFT calculations. We have shown the efficacy of our method in determining the reaction pathways, even for cases that involve multi-step reactions.

An adaptive mutation simulated annealing based investigation of Coulombic explosion and identification of dissociation patterns in (CO2)n2+ clusters

In this communication, we would like to discuss the advantages of adaptive mutation simulated annealing (AMSA) over standard simulated annealing (SA) in studying the Coulombic explosion of (CO₂)_n²⁺ clusters for n = 20–68, where ‘n’ is the size of the cluster.

An investigation on the structure, spectroscopy and thermodynamic aspects of Br2((-))(H2O)n clusters using a conjunction of stochastic and quantum chemical methods

In this work we obtained global as well as local structures of Br2((-))(H2O)n clusters for n = 2 to 6 followed by the study of IR-spectral features and thermochemistry for the structures. The way adopted by us to obtain structures is not the conventional one used in most cases. Here we at first generated excellent quality pre-optimized structures by exploring the suitable empirical potential energy surface using stochastic optimizer simulated annealing. These structures are then further refined using quantum chemical calculations to obtain the final structures, and spectral and thermodynamic features. We clearly showed that our approach results in very quick and better convergence which reduces the computational cost and obviously using the strategy we are able to get one [i.e. global] or more than one [i.e. global and local(s)] energetically lower structures than those which are already reported for a given cluster size. Moreover, IR-spectral results and the evolutionary trends in interaction energy, solvation energy and vertical detachment energy for global structures of each size have also been presented to establish the utility of the procedure employed.

Structural and spectroscopic studies of iodine dimer radical anion hydrated clusters: an approach using a combination of stochastic and quantum chemical methods

Structures of I₂⁽⁻⁾(H₂O)₅ clusters after evaluation by simulated annealing and subsequent DFT calculation respectively.