Modelling the nano-scale phenomena in condensed matter physics via computer-based numerical simulations

A review of the atomistic modelling of the behaviour of nano-scale structures and processes via molecular dynamics (MD) simulation method of a canonical ensemble is presented. Three areas of application in condensed matter physics are considered. We focus on the adhesive and indentation properties of the solid surfaces in nano-contacts, the nucleation and growth of nano-phase metallic and semi-conducting atomic and molecular films on supporting substrates, and the nano- and multi-scale crack propagation properties of metallic lattices. A set of simulations selected from these fields are discussed, together with a brief introduction to the methodology of the MD simulation. The pertinent inter-atomic potentials that model the energetics of the metallic and semi-conducting systems are also given.

Surface physics at the nano-scale via scanning probe microscopy and molecular dynamics simulations

Probe-based scanning microscopes, such as the STM and the AFM, are used to obtain the topographical and electronic structure maps of material surfaces, and to modify their morphologies on nanoscopic scales. They have generated new areas of research in condensed matter physics and materials science. We will review some examples from the fields of experimental nano-mechanics, nano-electronics and nano-magnetism. These now form the basis of the emerging field of Nano-technology. A parallel development has been brought about in the field of Computational Nano-science, using quantum-mechanical techniques and computer-based numerical modelling, such as the Molecular Dynamics (MD) simulation method. We will report on the simulation of nucleation and growth of nano-phase films on supporting substrates. Furthermore, a theoretical modelling of the formation of STM images of metallic clusters on metallic substrates will also be discussed within the non-equilibrium Keldysh Green function method to study the effects of coherent tunnelling through different atomic orbitals in a tip-sample geometry.

An ontological characterization of time-series and state-sequences for data mining

Time-series and sequences are important patterns in data mining. Based on an ontology of time-elements, this paper presents a formal characterization of time-series and state-sequences, where a state denotes a collection of data whose validation is dependent on time. While a time-series is formalized as a vector of time-elements temporally ordered one after another, a state-sequence is denoted as a list of states correspondingly ordered by a time-series. In general, a time-series and a state-sequence can be incomplete in various ways. This leads to the distinction between complete and incomplete time-series, and between complete and incomplete state-sequences, which allows the expression of both absolute and relative temporal knowledge in data mining.

Minimising the risk of defects in nano-imprint forming

Nano-imprint forming (NIF) is among the most attractive manufacturing technologies offering high yield and low-cost fabrication of three-dimensional fine structures and patterns with resolution of few nanometres. Optimising NIF process is critical for achieving high quality products and minimising the risk of commonly observed defects. Using finite element analysis, the effect of various process parameters is evaluated and design rules for safe and reliable NIF fabrication formulated. This work is part of a major UK Grand Challenge project - 3D-Mintegration - for design, simulation, fabrication, assembly and test of next generation 3D-miniaturised systems.

Modelling of nano-imprint forming process for the production of miniaturised 3D structures

Nano-imprint forming (NIF) as manufacturing technology is ideally placed to enable high resolution, low-cost and high-throughput fabrication of three-dimensional fine structures and the packaging of heterogeneous micro-systems (S.Y. Chou and P.R. Krauss, 1997). This paper details a thermo-mechanical modelling methodology for optimising this process for different materials used in components such as mini-fluidics and bio-chemical systems, optoelectronics, photonics and health usage monitoring systems (HUMS). This work is part of a major UK Grand Challenge project - 3D-Mintegration - which is aiming to develop modelling and design technologies for the next generation of fabrication, assembly and test processes for 3D-miniaturised systems.