Proceedings of the International Conference on Colloid and Surface Science

Y. Iwasawa, N. Oyama, H. Kunieda

• Publisher: Elsevier Science
• Year: 2001
• Print ISBN: 9780444506511
• eBook ISBN: 9780080529356
• Topic: Physical Sciences
• Subtopic: Physical & Theoretical Chemistry

The purpose of this Conference was to discuss the results of recent developments and the future prospect in science and technology of the field. The field has been growing and flourishing, while indicating many problems to be uncovered and solved. The conference was structured to encourage interaction and to stimulate the exchange of ideas to accomplish the above purpose.Key issues and materials related to the Conference were included as follows: • Molecular Assemblies in Solutions;• Fine Particles and Colloidal Dispersions;• Supramolecular Organized Films;• Nanostructural Solid Surfaces;• Industrial Applications and Products.The Conference comprised 2 plenary lectures, 42 invited lectures, 150 oral presentations and 266 poster presentations.

Nanostructuaral solid surfaces

Improved Molecular Models for Porous Carbons

J. Pikunic^a; R. J.-M. Pellenq^b; K.T. Thomson^a,+; J.-N. Rouzaud^b; P. Levitz^b; K.E. Gubbins^{a a} Department of Chemical Engineering, North Carolina State University, 113 Riddick Labs, Raleigh, NC 27695-7905, USA
^b Centre de Recherche sur la Matière Divisée (UMR 131 CNRS), IB rue de la Ferollerie, 45071 Orléans Cédex 02, France
⁺ Present address: Purdue University, School of Chemical Engineering, West Lafayette, IN 47907-1283, USA

We describe two approaches based on Reverse Monte Carlo to model porous carbons. We use these approaches to model two different porous carbons and highlight the features of the resulting structures. In the first approach, RMC moves are applied to a configuration of basic carbon units that resemble the structure of graphene plates. In the second approach, RMC moves are applied at the atomic level, allowing the creation of defects in the carbon plates.

1 INTRODUCTION

The widespread interest in porous carbons stems from their high surface activity and consequent adsorption capacity, and from the fact that they are relatively cheap to produce. Activated carbons are the most widely used of all general purpose adsorbents in industry [1]. Industrial uses of activated carbons include sugar refining, purification of drinking water, solvent recovery, deodorization, and purification of air and other gas streams. They have also been used extensively as catalyst supports in chemical processing applications.

Porous carbons are disordered materials, and as yet cannot be fully characterized from experiment. Techniques such as X-ray and neutron scattering, and high resolution transmission electron microscopy, give useful partial information about the molecular structure, but are not yet able to provide a complete picture at the atomic level. In order to interpret experimental data on the carbons themselves, and on the behavior of adsorbates in carbons, we must resort to structural models of the pore morphology and topology, in addition to models or the intermolecular forces involved.

There are two general approaches to the problem of constructing a molecular model of a porous material. The first, which we term mimetic simulation, involves the development of a simulation strategy that mimics the synthetic process used to fabricate the material in the laboratory (see for example ref. 2). The second, termed the reconstruction method, seeks to build a molecular model whose structure matches the available experimental structure data. In the case of most porous carbons, the synthesis process is so poorly understood that mimetic simulation is not feasible.

2 REVERSE MONTE CARLO METHOD

The Reverse Monte Carlo (RMC) method was originally proposed by McGreevy and Putszai [3]. The goal of this method is to produce an atomic configuration that is consistent with a set of experimental data. The method consists of changing the atomic positions of some initial atomic configuration through a stochastic procedure. The initial configuration may have either some random structure or a structure generated with some previous knowledge about the material that is being modeled. Using the Metropolis algorithm [4], changes in the atomic configuration, or moves, are accepted or rejected based on the agreement between some simulated structural property and a corresponding target. Throughout the simulation, the differences between the simulated and the target functions are minimized. The most commonly used structural properties in RMC methods are the structure factor, S(q) and the radial distribution function, g(r). If the experimental g(r) is used as the target function, then the quantity to be minimized is:

${\chi }^2={\displaystyle \sum _{i=1}^{n_{\text{exp}}}{\left[g_{sim}\left(r_i\right)-g_{\text{exp}}\left(r_i\right)\right]}^2}$

(1)

where n_exp is the number of experimental points, g_sim (r_i) is the simulated g(r) and g_exp(r_i) is the experimental g(r) evaluated at r_i. Similarly, if the S(q) is used as the target function, then the quantity to be minimized is:

${\chi }^2={\displaystyle \sum _{i=1}^{n_{\text{exp}}}{\left[S_{sim}\left(q_i\right)-S_{\text{exp}}\left(q_i\right)\right]}^2}$

(2)

where S_sim(q_i) is the simulated S(q) and S_exp(q_i) is the experimental S(q) evaluated at q_i. After each move, the quantity χ² is calculated. The move is accepted with a probability P_acc (eq. 3). In eq. 3, P_χ is a weighting parameter. The number of accepted moves will be a function of this parameter. Note that when P_χ is set to infinity, the moves are only accepted if χ²_new < χ _old.

$P_{acc}=min\left[1,exp\left\{-P_{\chi }\left({{\chi }^2}_{\mathit{new}}-{{\chi }^2}_{\mathit{old}}\right)\right\}\right]$

(3)

It has been pointed out that different structures can be found by RMC with the same set of structural data [5,6]. Moreover, some of the models generated by RMC may have unphysical features. In order to overcome this problem,...

Table of contents

• Cover image
• Title page
• Table of Contents
• Copyright page
• Preface
• Plenary session
• Molecular assemblies in solutions
• Fine particles and colloidal dispersions
• Supramolecular organized films
• Nanostructuaral solid surfaces
• Industrial applications and products
• Author Index
• Advisory Editors