- Email: [email protected]
Modelling and simulation
Current Opinion in Solid State and Materials Science 7 (2003) 1–2
Editorial overview
Modelling and simulation C.R.A. Catlow* Davy-Faraday Research Laboratory, Royal Institution of Great Britain, 21 Albemarle St., London W1 X 4 BS, UK
Modelling and simulation in materials science has progressed to the point where it is, in many cases, a natural complement to experimental studies. In large part this is because the huge increases in computer power have enabled major advances in both the complexity of materials that can be investigated and the sophistication of the theoretical bases for the calculations. The papers presented in this section reflect both aspects of these advances. Sayle and Johnston point out that the complexity of real systems makes their manual construction somewhat difficult, not only because of the numbers of atoms that ought to be considered, but also because some key features may be missed, especially if they are not anticipated in the first place. Using, as illustrations, the simulation of thin films and nanoparticles they discuss what they term evolutionary techniques for modeling large scale systems. One is structural, based on an amorphisation and recrystallization strategy, in which structural features, such as grain boundaries and dislocations, emerge naturally from the molecular dynamics simulations, and the other is ‘‘pseudonatural’’, using genetic algorithms to mimic the natural selection procedures found in biological evolution. A complication is the question of how to interpret the output of such large scale simulations; visualization methods are going to play an increasingly important role. Mellot-Draznieks reports on a different approach to modeling complex inorganic crystal structures, by describing advances in structure elucidation in the zeolite family of industrially important materials. Both (static lattice) energy minimization and Monte Carlo methods are now used to find the positions of extra-framework cations, whose positions are often of low symmetry and cannot be precisely located by standard diffraction techniques. This is yet another example of the complementarity now possible between simulations and experiment. Perhaps one extreme of this harmony is the use of computational tools to design not-yet-synthesised structures. In addition to providing challenges to the experimentalists, this avenue *Fax: 144-207-629-3569. E-mail address: [email protected] (C.R.A. Catlow).
also helps to put limits on the types of structure available (e.g. for a given chemistry) by exploring the relationships between structure and composition. It is not just the crystal structures themselves which are important: in many industrial applications, control of crystal shape is paramount. The ability to predict crystal morphologies clearly has as a critical underpinning, the modeling of ‘‘perfect’’ crystal structures from which surface structures can be reliably simulated. (Zeolites represent an interesting case where the chemically important surfaces are largely, if not completely, internal in nature, and are essentially characterized by the unit cell structure.) The review by Rohl shows that, although there is some maturity attached to crystal morphology prediction, as evidenced by the availability of commercial software, it is still a dynamic field. In particular, it is now recognized that the solvent, or medium in which the crystals grow, can influence the morphology because of variations in the way in which molecules in the solution interact with surfaces of different crystallographic orientation. Changing the chemistry of the surface, through additives, for example, is another well-established, but not necessarily well-understood, way to modify the morphology or growth habits of crystals. Balazs echoes one of the themes of Sayle and Johnston, in considering the morphology of composite structures, in which inorganic nanoparticles are embedded, but this time, in an organic polymer matrix. The idea is to promote self-assembly of the nanoparticles into highly ordered structures, with appropriately interesting physical properties, by taking advantage of the flexibility in polymer processing. Organic and inorganic materials have often been treated in different ways, so it should not be surprising that the approach discussed here, a combination of self-consistent field and density functional theories, stands in contrast to the atomistic approach reviewed by Sayle and Johnston. The problems associated with the different approaches traditionally taken to modeling materials with different bonding characteristics are also highlighted in the article by Weber and Corrales with respect to the simulation of
1359-0286 / 03 / $ – see front matter 2003 Elsevier Science Ltd. All rights reserved. doi:10.1016 / S1359-0286(03)00030-5
2
C.R. A. Catlow / Current Opinion in Solid State and Materials Science 7 (2003) 1–2
non-equilibrium events in oxides. They argue that it is not possible simply to transfer the codes used for the study of radiation damage metals and covalently bonded systems to oxide systems and also point out that the current state-ofthe-art of modeling and simulation at the atomic-level cannot handle elastic and inelastic processes at the same time. They suggest that the development of computational studies of defects and radiation damage processes in ionic oxides has been hindered because of limitations to the interatomic potentials being used, which are usually only valid over a small range of interatomic separations centered about equilibrium bond-lengths and may not accurately enough model the elastic and thermal diffusion properties of the materials in question. This issue is not particularly new, of course, but has resurfaced because of the complexities of both the systems and the processes being modeled. McGreevy provides a slightly different take, but essentially addresses the same point by observing that the first
thing to do is to state clearly the question that is to be answered. He points out that it is not appropriate to ask if ‘‘the model’’ is correct, but rather whether it is useful – which is particularly the case of RMC methods where one usually derives structural information from experimental data; the best one can do is obtain a model that is consistent with that data. However, he would argue that such a model structure is a stepping stone to understanding a particular property of the material and that RMC methodologies allow one to extract substantially more information than would be gleaned from traditional structural analysis tools. In summary, the collection of articles in this section highlights the continuing diversity and complexity, both structurally and chemically, of the materials that are finding themselves the subject of modeling and simulation studies. This trend is likely only to continue, given the relentless advances in affordable computational resources.
Editorial overview
Modelling and simulation C.R.A. Catlow* Davy-Faraday Research Laboratory, Royal Institution of Great Britain, 21 Albemarle St., London W1 X 4 BS, UK
Modelling and simulation in materials science has progressed to the point where it is, in many cases, a natural complement to experimental studies. In large part this is because the huge increases in computer power have enabled major advances in both the complexity of materials that can be investigated and the sophistication of the theoretical bases for the calculations. The papers presented in this section reflect both aspects of these advances. Sayle and Johnston point out that the complexity of real systems makes their manual construction somewhat difficult, not only because of the numbers of atoms that ought to be considered, but also because some key features may be missed, especially if they are not anticipated in the first place. Using, as illustrations, the simulation of thin films and nanoparticles they discuss what they term evolutionary techniques for modeling large scale systems. One is structural, based on an amorphisation and recrystallization strategy, in which structural features, such as grain boundaries and dislocations, emerge naturally from the molecular dynamics simulations, and the other is ‘‘pseudonatural’’, using genetic algorithms to mimic the natural selection procedures found in biological evolution. A complication is the question of how to interpret the output of such large scale simulations; visualization methods are going to play an increasingly important role. Mellot-Draznieks reports on a different approach to modeling complex inorganic crystal structures, by describing advances in structure elucidation in the zeolite family of industrially important materials. Both (static lattice) energy minimization and Monte Carlo methods are now used to find the positions of extra-framework cations, whose positions are often of low symmetry and cannot be precisely located by standard diffraction techniques. This is yet another example of the complementarity now possible between simulations and experiment. Perhaps one extreme of this harmony is the use of computational tools to design not-yet-synthesised structures. In addition to providing challenges to the experimentalists, this avenue *Fax: 144-207-629-3569. E-mail address: [email protected] (C.R.A. Catlow).
also helps to put limits on the types of structure available (e.g. for a given chemistry) by exploring the relationships between structure and composition. It is not just the crystal structures themselves which are important: in many industrial applications, control of crystal shape is paramount. The ability to predict crystal morphologies clearly has as a critical underpinning, the modeling of ‘‘perfect’’ crystal structures from which surface structures can be reliably simulated. (Zeolites represent an interesting case where the chemically important surfaces are largely, if not completely, internal in nature, and are essentially characterized by the unit cell structure.) The review by Rohl shows that, although there is some maturity attached to crystal morphology prediction, as evidenced by the availability of commercial software, it is still a dynamic field. In particular, it is now recognized that the solvent, or medium in which the crystals grow, can influence the morphology because of variations in the way in which molecules in the solution interact with surfaces of different crystallographic orientation. Changing the chemistry of the surface, through additives, for example, is another well-established, but not necessarily well-understood, way to modify the morphology or growth habits of crystals. Balazs echoes one of the themes of Sayle and Johnston, in considering the morphology of composite structures, in which inorganic nanoparticles are embedded, but this time, in an organic polymer matrix. The idea is to promote self-assembly of the nanoparticles into highly ordered structures, with appropriately interesting physical properties, by taking advantage of the flexibility in polymer processing. Organic and inorganic materials have often been treated in different ways, so it should not be surprising that the approach discussed here, a combination of self-consistent field and density functional theories, stands in contrast to the atomistic approach reviewed by Sayle and Johnston. The problems associated with the different approaches traditionally taken to modeling materials with different bonding characteristics are also highlighted in the article by Weber and Corrales with respect to the simulation of
1359-0286 / 03 / $ – see front matter 2003 Elsevier Science Ltd. All rights reserved. doi:10.1016 / S1359-0286(03)00030-5
2
C.R. A. Catlow / Current Opinion in Solid State and Materials Science 7 (2003) 1–2
non-equilibrium events in oxides. They argue that it is not possible simply to transfer the codes used for the study of radiation damage metals and covalently bonded systems to oxide systems and also point out that the current state-ofthe-art of modeling and simulation at the atomic-level cannot handle elastic and inelastic processes at the same time. They suggest that the development of computational studies of defects and radiation damage processes in ionic oxides has been hindered because of limitations to the interatomic potentials being used, which are usually only valid over a small range of interatomic separations centered about equilibrium bond-lengths and may not accurately enough model the elastic and thermal diffusion properties of the materials in question. This issue is not particularly new, of course, but has resurfaced because of the complexities of both the systems and the processes being modeled. McGreevy provides a slightly different take, but essentially addresses the same point by observing that the first
thing to do is to state clearly the question that is to be answered. He points out that it is not appropriate to ask if ‘‘the model’’ is correct, but rather whether it is useful – which is particularly the case of RMC methods where one usually derives structural information from experimental data; the best one can do is obtain a model that is consistent with that data. However, he would argue that such a model structure is a stepping stone to understanding a particular property of the material and that RMC methodologies allow one to extract substantially more information than would be gleaned from traditional structural analysis tools. In summary, the collection of articles in this section highlights the continuing diversity and complexity, both structurally and chemically, of the materials that are finding themselves the subject of modeling and simulation studies. This trend is likely only to continue, given the relentless advances in affordable computational resources.