Revised Basin-Hopping Monte Carlo Algorithm for Structure Optimization of Clusters and Nanoparticles

2013 ◽  
Vol 53 (9) ◽  
pp. 2282-2298 ◽  
Author(s):  
Gustavo G. Rondina ◽  
Juarez L. F. Da Silva
Keyword(s):  
Monte Carlo ◽  
Structure Optimization ◽  
Monte Carlo Algorithm ◽  
Basin Hopping

scholarly journals Structural optimization of Fen-Ptm (5 n+m 24) alloy clusters based on an improved Basin-Hopping Monte Carlo algorithm

2017 ◽  
Vol 66 (5) ◽  
pp. 053601
Author(s):  
Liu Tun-Dong ◽  
Li Ze-Peng ◽  
Ji Qing-Shuang ◽  
Shao Gui-Fang ◽  
Fan Tian-E ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Structural Optimization ◽  
Monte Carlo Algorithm ◽  
Basin Hopping ◽  
Alloy Clusters

Spark-based improved Basin-Hopping Monte Carlo algorithm for structural optimization of alloy clusters

2019 ◽  
Vol 383 (5) ◽  
pp. 464-470 ◽  
Author(s):  
Yuan-Hua Yang ◽  
Jun-Fa Zhang ◽  
Jin-Bo Wang ◽  
Xian-Bin Xu ◽  
Gui-Fang Shao ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Structural Optimization ◽  
Monte Carlo Algorithm ◽  
Basin Hopping ◽  
Alloy Clusters

Structural, electronic and magnetic properties of stoichiometric cobalt oxide clusters (CoO)nq (n=3−10,q=0,+1): A modified basin-hopping Monte Carlo algorithm with spin-polarized DFT

2019 ◽  
Vol 18 (01) ◽  
pp. 1950003 ◽  
Author(s):  
Mohammad Noh Daud
Keyword(s):  
Monte Carlo ◽  
Magnetic Properties ◽  
Cobalt Oxide ◽  
Monte Carlo Algorithm ◽  
General Notion ◽  
Dissociation Pathway ◽  
Global Minima ◽  
Electronic And Magnetic Properties ◽  
Spin Polarized ◽  
Basin Hopping

The structural, electronic and magnetic properties of the neutral and cationic cobalt oxide clusters (CoO)[Formula: see text] ([Formula: see text], [Formula: see text]) have been studied using a modified basin-hopping Monte Carlo (BHMC) algorithm refined by spin-polarized DFT. A systematic search of global minimum structures predicts new global minima of (CoO)[Formula: see text] and reproduced other minima that are in excellent agreement with previous works. For most low-spin and high-spin states, the structural transition from planar-like to compact structure occurs at (CoO)[Formula: see text], which is in contrast with the general notion that the structural changes at (CoO)[Formula: see text]. Supported by the results of the binding energy, second-order total energy difference, chemical hardness, chemical potential and HOMO-LUMO gap confirms the stability of (CoO)4. Results of the spin magnetic moments for the global minima show that (CoO)4 and (CoO)8 spin configurations exhibit a fully antiferromagnetic (AFM) ordering, while (CoO)9 spin displays the highest ferromagnetic (FM) ordering. Interestingly, elongation of Co–Co bond in (CoO)4 causes O being polarized by the neighboring Co atoms that accordingly follows the Goodenough-Kanamori-Anderson rule of FM super-exchange coupling for the Co-O-Co structural rearrangement to 90∘ ([Formula: see text] structure) in order to accommodate the spin magnetic ordering changes. This rearrangement is a result of the valence band being shifted away from the Fermi level to lower energy causing high population of the spin-up density of state and leading to the asymmetrical polarization of the whole (CoO)4 structure. As far as the dissociation energy surfaces are concerned, the first ever such surfaces are constructed corresponding to [Formula: see text], which identify a complete dissociation pathway linking the cationic and neutral clusters and finally confirm (CoO)[Formula: see text] as the most stable cluster compared to the rest.

Examining sharp restart in a Monte Carlo method for the linearized Poisson–Boltzmann equation

2020 ◽  
Vol 26 (3) ◽  
pp. 223-244
Author(s):  
W. John Thrasher ◽  
Michael Mascagni
Keyword(s):  
Monte Carlo ◽  
Free Energy ◽  
Monte Carlo Algorithm ◽  
Significant Bias ◽  
Poisson Boltzmann ◽  
Electrostatic Free Energy ◽  
Poisson Boltzmann Equation ◽  
The Stability ◽  
Potential Methods ◽  
The Individual

AbstractIt has been shown that when using a Monte Carlo algorithm to estimate the electrostatic free energy of a biomolecule in a solution, individual random walks can become entrapped in the geometry. We examine a proposed solution, using a sharp restart during the Walk-on-Subdomains step, in more detail. We show that the point at which this solution introduces significant bias is related to properties intrinsic to the molecule being examined. We also examine two potential methods of generating a sharp restart point and show that they both cause no significant bias in the examined molecules and increase the stability of the run times of the individual walks.

Sign in / Sign up

Export Citation Format

Share Document