ABSTRACT
Low dimensional materials present characteristic properties that differ from those of their bulk counterpart. This is mainly due to their high surface/volume ratio and the presence of other low coordinated highly reactive sites, such as borders and kinks. For this reason, they encounter applications in several technological areas such as catalysis, optoelectronics, LEDs, voltaic cells, drug delivery. Computer simulations at an atomistic level allow an extensive study and understanding of these nanostructures. The recent development of predictive techniques (such as those based on machine learning) leads to a new form of material’s research. The materials are completely designed in silico and after showing excellent behaviour for some particular application they could be synthesized in the laboratory. In this chapter, a series of computational tools and techniques, useful in materials science research, are briefly presented.
