scholarly journals Growth of nano-domains in Gd–CeO2 mixtures: hybrid Monte Carlo simulations

2016 ◽  
Vol 4 (12) ◽  
pp. 4592-4602 ◽  
Author(s):  
John A. Purton ◽  
Adam Archer ◽  
Neil L. Allan ◽  
David S. D. Gunn
Keyword(s):  
Molecular Dynamics ◽  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Hybrid Monte Carlo

Hybrid Monte Carlo (HMC) simulations are used to study the growth of Gd-rich domains in Gd doped CeO2, and we probe the conductivity of the resulting and other configurations by molecular dynamics.

Hybrid Monte Carlo simulations theory and initial comparison with molecular dynamics

Biopolymers ◽  
1993 ◽  
Vol 33 (8) ◽  
pp. 1307-1315 ◽  
Author(s):  
A. Brass ◽  
B. J. Pendleton ◽  
Y. Chen ◽  
B. Robson
Keyword(s):  
Molecular Dynamics ◽  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Hybrid Monte Carlo ◽  
Initial Comparison

scholarly journals ACCEPTANCES AND AUTOCORRELATIONS IN THE HYBRID MONTE CARLO ALGORITHM

1992 ◽  
Vol 03 (01) ◽  
pp. 43-52 ◽  
Author(s):  
SOURENDU GUPTA
Keyword(s):  
Molecular Dynamics ◽  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Critical Exponent ◽  
Quark Mass ◽  
Monte Carlo Algorithm ◽  
Xy Model ◽  
Acceptance Probability ◽  
Hybrid Monte Carlo ◽  
Lattice Size

The acceptance probability in Hybrid Monte Carlo simulations of QCD, in particular, its dependence on the lattice size, quark mass and the coupling, is discussed. Results on the tuning of parameters required in order to achieve low autocorrelations in the 2-d XY model are presented. In both phases of this model, the dynamical critical exponent is close to 2 for runs with trajectory lengths between 1 and 3 molecular dynamics units.

Molecular dynamics, Langevin and hydrid Monte Carlo simulations in a multicanonical ensemble

1996 ◽  
Vol 259 (3-4) ◽  
pp. 321-330 ◽  
Author(s):  
Ulrich H.E. Hansmann ◽  
Yuko Okamoto ◽  
Frank Eisenmenger
Keyword(s):  
Molecular Dynamics ◽  
Monte Carlo ◽  
Monte Carlo Simulations

Magnetic relaxation of xenon‐131 dissolved in benzene. A study by molecular dynamics and Monte Carlo simulations

1993 ◽  
Vol 98 (2) ◽  
pp. 1566-1578 ◽  
Author(s):  
M. Luhmer ◽  
D. van Belle ◽  
J. Reisse ◽  
M. Odelius ◽  
J. Kowalewski ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Magnetic Relaxation

scholarly journals Computational Prediction of Heteromeric Protein Complex Disassembly Order with Hybrid Monte Carlo/Molecular Dynamics Simulation

2022 ◽  
Author(s):  
Ikuo Kurisaki ◽  
Shigenori Tanaka
Keyword(s):  
Molecular Dynamics ◽  
Monte Carlo ◽  
Protein Complex ◽  
Protein Complexes ◽  
Structural Bioinformatics ◽  
Dynamics Simulation ◽  
Tryptophan Synthase ◽  
Selection Scheme ◽  
Hybrid Monte Carlo ◽  
Multimeric Protein

The physicochemical entity of biological phenomenon in the cell is a network of biochemical reactions and the activity of such a network is regulated by multimeric protein complexes. Mass spectroscopy (MS) experiments and multimeric protein docking simulations based on structural bioinformatics techniques have revealed the molecular-level stoichiometry and static configuration of subcomplexes in their bound forms, then revealing the subcomplex populations and formation orders. Meanwhile, these methodologies are not designed to straightforwardly examine temporal dynamics of multimeric protein assembly and disassembly, essential physicochemical properties to understand functional expression mechanisms of proteins in the biological environment. To address the problem, we had developed an atomistic simulation in the framework of the hybrid Monte Carlo/Molecular Dynamics (hMC/MD) method and succeeded in observing disassembly of homomeric pentamer of the serum amyloid P component protein in experimentally consistent order. In this study, we improved the hMC/MD method to examine disassembly processes of the tryptophan synthase tetramer, a paradigmatic heteromeric protein complex in MS studies. We employed the likelihood-based selection scheme to determine a dissociation-prone subunit pair at each hMC/MD simulation cycle and achieved highly reliable predictions of the disassembly orders with the success rate over 0.9 without a priori knowledge of the MS experiments and structural bioinformatics simulations. We similarly succeeded in reliable predictions for the other three tetrameric protein complexes. These achievements indicate the potential availability of our hMC/MD approach as the general purpose methodology to obtain microscopic and physicochemical insights into multimeric protein complex formation.

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