Temperature-consistent clusters of argon atoms: Their role in free energy and nucleation rate calculations using Monte Carlo methods

2000 ◽  
Author(s):  
P. Pal
Keyword(s):  
Monte Carlo ◽  
Free Energy ◽  
Nucleation Rate ◽  
Monte Carlo Methods

Monte Carlo methods for the study of cation ordering in minerals

2001 ◽  
Vol 65 (2) ◽  
pp. 221-248 ◽  
Author(s):  
M. C. Warren ◽  
M. T. Dove ◽  
E. R. Myers ◽  
A. Bosenick ◽  
E. J. Palin ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Free Energy ◽  
Long Range ◽  
Monte Carlo Methods ◽  
Disordered Systems ◽  
Short Range ◽  
Short Range Order ◽  
Parallel Computers ◽  
Cation Ordering

AbstractThis paper reviews recent applications of Monte Carlo methods for the study of cation ordering in minerals. We describe the program Ossia99, designed for the simulation of complex ordering processes and for use on parallel computers. A number of applications for the study of long-range and short-range order are described, including the use of the Monte Carlo methods to compute quantities measured in an NMR experiment. The method of thermodynamic integration for the determination of the free energy is described in some detail, and several applications of the method to determine the thermodynamics of disordered systems are outlined.

scholarly journals FEASST: Free Energy and Advanced Sampling Simulation Toolkit

2018 ◽  
Vol 123 ◽  
Author(s):  
Harold W. Hatch ◽  
Nathan A. Mahynski ◽  
Vincent K. Shen
Keyword(s):  
Monte Carlo ◽  
Free Energy ◽  
Open Source ◽  
Monte Carlo Methods ◽  
Transition Matrix ◽  
Advanced Sampling ◽  
Free Open Source

The Free Energy and Advanced Sampling Simulation Toolkit (FEASST) is a free, open-source, modular program to conduct molecular and particle-based simulations with Metropolis, Wang-Landau, and Transition-Matrix Monte Carlo methods. FEASST is implemented in C++ and may be imported as a module within Python 2 or 3. This document describes the initial public release version 1.0.

Predicting low-temperature free energy landscapes with flat-histogram Monte Carlo methods

2017 ◽  
Vol 146 (7) ◽  
pp. 074101 ◽  
Author(s):  
Nathan A. Mahynski ◽  
Marco A. Blanco ◽  
Jeffrey R. Errington ◽  
Vincent K. Shen
Keyword(s):  
Monte Carlo ◽  
Free Energy ◽  
Low Temperature ◽  
Monte Carlo Methods ◽  
Energy Landscapes ◽  
Free Energy Landscapes
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