The first Nanotechnology concepts were introduced by the American physicist Richard Feynman in 1959, in his famous lecture entitled There´s plenty of room at the bottom. Computational Intelligence has been successfully used in various areas in the academic and industrial worlds. This work investigates the potential of Genetic Algorithms in the optimization and synthesis of devices and structures in the Nanotechnology domain, by means of 3 types of distinct applications: synthesis of molecular electronic circuits, design of new conducting polymers and optimization of OLEDs (Organic Light-Emitting Diodes) parameters. The synthesis of molecular electronic circuits is developed based on the Evolvable Hardware (EHW) paradigm and has as main elements two molecular devices simulated in SPICE: the molecular diode and the molecular transistor. The design of new conducting polymers is based on a methodology that combines an approximated tight-binding (simplified Huckel Hamiltonian) that represents the electronic structure of a polymer chain, using a GA with distributed evaluation as the synthesis mechanism. Finally, the optimization of OLEDs parameters is developed by means of a method that models the electric behavior of multi-layer devices, where each layer has a ratio of electron transport material (ETM) to hole transport material (HTM). The applications present results that demonstrate that the use of Computational Intelligence techniques, as Genetic Algorithms, in the nanometer world can bring benefits for the creation and development of new technologies.