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Resonance Energy Transfer-Based Molecular Switch Designed Using a Systematic Design Process Based on Monte Carlo Methods and Markov ChainsRallapalli, Arjun January 2016 (has links)
<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
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[en] EVOLUTIONARY SYNTHESIS IN NANOTECHNOLOGY / [pt] SÍNTESE EVOLUCIONÁRIA EM NANOTECNOLOGIALEONE PEREIRA MASIERO 22 August 2006 (has links)
[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.
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