<p>A RET network consists of a network of photo-active molecules called chromophores that can participate in inter-molecular energy transfer called resonance energy transfer (RET). RET networks are used in a variety of applications including cryptographic devices, storage systems, light harvesting complexes, biological sensors, and molecular rulers. In this dissertation, we focus on creating a RET device called closed-diffusive exciton valve (C-DEV) in which the input to output transfer function is controlled by an external energy source, similar to a semiconductor transistor like the MOSFET. Due to their biocompatibility, molecular devices like the C-DEVs can be used to introduce computing power in biological, organic, and aqueous environments such as living cells. Furthermore, the underlying physics in RET devices are stochastic in nature, making them suitable for stochastic computing in which true random distribution generation is critical.</p><p>In order to determine a valid configuration of chromophores for the C-DEV, we developed a systematic process based on user-guided design space pruning techniques and built-in simulation tools. We show that our C-DEV is 15x better than C-DEVs designed using ad hoc methods that rely on limited data from prior experiments. We also show ways in which the C-DEV can be improved further and how different varieties of C-DEVs can be combined to form more complex logic circuits. Moreover, the systematic design process can be used to search for valid chromophore network configurations for a variety of RET applications.</p><p>We also describe a feasibility study for a technique used to control the orientation of chromophores attached to DNA. Being able to control the orientation can expand the design space for RET networks because it provides another parameter to tune their collective behavior. While results showed limited control over orientation, the analysis required the development of a mathematical model that can be used to determine the distribution of dipoles in a given sample of chromophore constructs. The model can be used to evaluate the feasibility of other potential orientation control techniques.</p> / Dissertation

[pt] A Nanotecnologia teve seus primeiros conceitos introduzidos pelo físico americano Richard Feynman em 1959, em sua famosa palestra intitulada There´s plenty of room at the bottom (Ainda há muito espaço sobrando no fundo). Já a Inteligência Computacional tem sido utilizada com sucesso em diversas áreas no meio acadêmico e industrial. Este trabalho investiga o potencial dos Algoritmos Genéticos na otimização e síntese de dispositivos e estruturas na área de Nanotecnologia, através de 3 tipos de aplicações distintas: síntese de circuitos eletrônicos moleculares, projeto de novos polímeros condutores e otimização de parâmetros de OLEDs (Organic Light-Emitting Diodes). A síntese de circuitos eletrônicos moleculares é desenvolvida com base em Hardware Evolucionário (EHW - Evolvable Hardware) e tem como principais elementos dois dispositivos moleculares simulados em SPICE: o diodo molecular e o transistor molecular. O projeto de novos polímeros condutores é baseado em uma metodologia que combina uma aproximação tight-binding (hamiltoniano de Hückel simplificado) que representa a estrutura eletrônica de uma cadeia polimérica, empregando um AG com avaliação distribuída como mecanismo de síntese. Finalmente, a otimização de parâmetros de OLEDs é desenvolvida por meio de um método que modela o comportamento elétrico do dispositivo com multicamadas, onde cada camada possui uma proporção de MTE (material transportador de elétrons) e uma proporção de MTB (material transportador de buracos). As aplicações apresentam resultados que comprovam que o apoio de técnicas de Inteligência Computacional como os Algoritmos Genéticos no mundo nanométrico pode trazer benefícios para a criação e o desenvolvimento de novas tecnologias. / [en] 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.