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Related papers: Reverse Monte Carlo modeling in confined systems

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We investigate the radiolysis of liquid water confined in a porous silica matrix by means of an event-by-event Monte Carlo simulation of electron penetration in this composite system. We focus on the physical and physicochemical effects…

Materials Science · Physics 2016-12-28 H. Ouerdane , B. Gervais , H. Zhou , M. Beuve , J. -Ph. Renault

Understanding interfacial phenomena in confined systems is important for optimizing CO2 capture technologies. Here, we present a comprehensive investigation of CO2 adsorption in hydrated amorphous silica nanopores through an integrated…

Materials Science · Physics 2025-02-12 Jihong Shi , Tao Zhang , Shuyu Sun , Liang Gong

Past research has conclusively shown that confined pockets of water exhibit properties that differ from those of unconfined ("bulk") water. The differences between confined water and bulk, as well as between different types of confined…

Materials Science · Physics 2024-01-29 Alec A. Beaton , Alexandria Guinness , John M. Franck

The choice of appropriate interaction models is among the major disadvantages of conventional methods such as molecular dynamics and Monte Carlo simulations. On the other hand, the so-called reverse Monte Carlo (RMC) method, based on…

Soft Condensed Matter · Physics 2013-03-26 S. M. Mesli , M. Habchi , M. Kotbi , H. Xu

Dynamic Monte Carlo simulations for the open coarse-grained model of MFI type zeolite were used to study the dynamics of adsorption and diffusion of n-butane in silicalite-1. We demonstrated the influence of the confinement of the structure…

Materials Science · Physics 2009-11-11 Barbara Jagoda-Cwiklik , Lukasz Cwiklik , Marek Frankowicz

A novel a priori Monte Carlo (APMC) algorithm is proposed to accurately simulate the molecules absorbed at spherical receiver(s) with low computational complexity in diffusion-based molecular communication (MC) systems. It is demonstrated…

Emerging Technologies · Computer Science 2018-12-18 Yiran Wang , Adam Noel , Nan Yang

Bayesian models have become very popular over the last years in several fields such as signal processing, statistics, and machine learning. Bayesian inference requires the approximation of complicated integrals involving posterior…

Computation · Statistics 2021-07-20 Luca Martino , Víctor Elvira

We investigate thermal rectification in nanoporous silicon using a semi-classical Monte Carlo (MC) simulation method. We consider geometrically asymmetric nanoporous structures, and investigate the combined effects of porosity, inter-pore…

Materials Science · Physics 2019-11-18 Dhritiman Chakraborty , Joshua Brooke , Nick C S Hulse , Neophytos Neophytou

The structure of water confined in MCM41 silica cylindrical pores is studied to determine if confined water really is simply a version of the bulk liquid which can be substantially supercooled without crystallisation. A combination of total…

Soft Condensed Matter · Physics 2013-09-27 A K Soper

Reverse Monte Carlo (RMC) is an algorithm that incorporates stochastic modification of the action as part of the process that updates the fields in a Monte Carlo simulation. Such update moves have the potential of lowering or eliminating…

High Energy Physics - Lattice · Physics 2015-06-22 Arjun Singh Gambhir , Kostas Orginos

Colloids may be treated as `big atoms' so that they are good models for atomic and molecular systems. Colloidal hard disks are therefore good models for 2d materials and although their phase behavior is well characterized, rheology has…

Soft Condensed Matter · Physics 2024-06-19 Ian Williams , Erdal C. Oğuz , Hartmut Löwen , Wilson C. K. Poon , C. Patrick Royall

We present a grand canonical Monte Carlo simulation study of the phase diagram of a Lennard-Jones fluid adsorbed in a fractal and highly porous aerogel. The gel environment is generated from an off-lattice diffusion limited cluster-cluster…

Soft Condensed Matter · Physics 2007-05-23 V. De Grandis , P. Gallo , M. Rovere

Sequential Monte Carlo (SMC) methods are a class of Monte Carlo methods that are used to obtain random samples of a high dimensional random variable in a sequential fashion. Many problems encountered in applications often involve different…

Methodology · Statistics 2018-12-20 Chencheng Cai , Rong Chen , Ming Lin

Systems under external confinement and constraints often show interesting properties. In this thesis, we study some systems under external confinement. We begin by finding out the probability distribution of end-to-end separation of a Worm…

Soft Condensed Matter · Physics 2007-05-23 Debasish Chaudhuri

We present a promising coarse-graining strategy for linking micro- and mesoscales of soft matter systems. The approach is based on effective pairwise interaction potentials obtained from detailed atomistic molecular dynamics (MD)…

Soft Condensed Matter · Physics 2007-05-23 A. P. Lyubartsev , M. Karttunen , I. Vattulainen , A. Laaksonen

Random-walk Monte Carlo simulations are widely used to predict the optical properties of complex, disordered materials. In presence of large heterogeneities (e.g., spatially-extended nonscattering regions in a turbid environment), an…

Optics · Physics 2025-04-10 Loïc Tran , Benjamin Askenazi , Kevin Vynck

The simulation of diffusion-based molecular communication systems with absorbing receivers often requires a high computational complexity to produce accurate results. In this work, a new a priori Monte Carlo (APMC) algorithm is proposed to…

Emerging Technologies · Computer Science 2018-03-14 Yiran Wang , Adam Noel , Nan Yang

Computational codes based on the Diffusion Monte Carlo method can be used to determine the quantum state of two-electron systems confined by external potentials of various nature and geometry. In this work, we show how the application of…

Chemical Physics · Physics 2021-02-24 Gaia Micca Longo , Carla Maria Coppola , Domenico Giordano , Savino Longo

Motivated by recent developments in conformal field theory (CFT), we devise a Quantum Monte Carlo (QMC) method to calculate the moments of the partially transposed reduced density matrix at finite temperature. These are used to construct…

Strongly Correlated Electrons · Physics 2014-08-08 Chia-Min Chung , Vincenzo Alba , Lars Bonnes , Pochung Chen , Andreas M. Läuchli

Monte Carlo simulations of neutronic systems are computationally intensive and demand significant memory resources for high-fidelity modeling. Compressed sensing enables accurate reconstruction of signals from significantly fewer samples…

Computational Physics · Physics 2026-02-10 Ethan Lame , Camille Palmer , Todd Palmer , Ilham Variansyah