Interatomic Potential Models for Nanostructures

Over the last decade, nanoscience and nanotechnology [1–4] have emerged as two of the pillars of the research that will lead us to the next industrial revolution [5] and, together with molecular biology and information technology, will map the course of scientific and technological developments in the 21st century. This progress has been largely due to the development of sophisticated theoretical and experimental techniques, and practical tools, for understanding, characterizing, and manipulating nanoscale structures, processes, and systems. On the experimental front, the most significant developments were brought about by the invention of the scanning tunneling microscope (STM) in 1982 [6], followed by the atomic force microscope (AFM) [7] in 1986. These are tip-based devices which allow for a nanoscale manipulation of the morphology of the condensed phases and the determination of their electronic structures. These probebased techniques have been extended further and are now collectively referred to as scanning probe microscopy (SPM). The SPM-based techniques have been improved considerably, providing new tools in research in such fields of nanotechnology as nanomechanics, nanoelectronics, nanomagnetism, and nanooptics [8]. The fundamental entities of interest to nanoscience and nanotechnology are the isolated individual nanostructures and their assemblies. Nanostructures are constructed from a countable (limited) number of atoms or molecules. Their sizes are larger than individual molecules and smaller than microstructures. Nanoscale is a magical point on the dimensional scale: Structures in nanoscale (called nanostructures) are considered at the borderline of the smallest of humanmade devices and the largest molecules of living systems. One of their characteristic features is their high surfaceto-volume ratio. Their electronic and magnetic properties are often distinguished by quantum mechanical behavior, while their mechanical and thermal properties can be understood within the framework of classical statistical mechanics. Nanostructures can appear in all forms of condensed matter, be it soft or hard, organic or inorganic, and/or biological. They form the building blocks of nanotechnology, and the formation of their assemblies requires a deep understanding of the interactions between individual atoms and molecules forming the nanostructures. Accordingly, nanotechnology has been specialized into three broad areas, namely, wet, dry, and computational nanotechnology. Wet nanotechnology is mainly concerned with the study of nanostructures and nanoprocesses in biological and organic systems that exist in an aqueous environment. An important aspect of research in wet nanotechnology is the design of smart drugs for targeted delivery using such nanostructures as nanotubes and self-assembling materials 9 10 as platforms. Dry nanotechnology, on the other hand, addresses the electronic and mechanical properties of metals, ceramics, focusing on fabrication of structures in carbon (e.g., fullerenes and nanotubes), silicon, and other inorganic materials. Computational nanotechnology is based on the fields of mathematical modeling and computer-based simulation [11], which allow for computation and prediction of the underlying dynamics of nanostructures and processes in condensed matter physics, chemistry, materials science, biology, and genetics. Computational nanotechnology, therefore, covers the other domains of nanofields by employing concepts from both classical and quantum mechanical many-body theories. It can provide deep insight into the formation, evolution, and properties of nanostructures and mechanisms of