Designing conducting polymers using bioinspired ant algorithms

Martins, Bianca; Brunetto, Gustavo; Sato, F.; Coluci, V. R.; Galvão, Douglas S.

doi:10.1016/j.cplett.2008.01.037

Cited by 14 publications

(6 citation statements)

References 21 publications

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“…34 Another paradigm that can also be applied to search and optimization problems is the Swarm intelligence. [35][36][37] Here, the aim of the GA still being the minimization of the quality factor V /J 0 5 , but now the investigated devices have 2, 3, 4 and 5 Graded Layers (GL), where this later was included for comparison reasons. Figure 2 shows the schematic representation of the multilayer devices with the graded region in gray scale.…”

Section: Genetic Algorithm Optimizationmentioning

confidence: 99%

Optimization of the Electrical Efficiency of Graded Multilayer Organic Light-Emitting Diodes Supported by Genetic Algorithm

Costa¹,

Pacheco²,

Neto³

et al. 2014

Jnl of Comp & Theo Nano

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In this study the electrical properties of organic light-emitting diodes with multiple graded layers were simulated and optimized. The simulations were accomplished through an analytical model presented in the literature and the optimization methodology consisted of applying a Genetic Algorithm, using the model result to calculate the fitness function, in order to systematically evaluate and evolve distinct device architectures in four case studies, with the number of graded layers ranging from two to five layers. For each case study the concentration profiles of electron transport material were varied so as to enhance their electrical efficiency. This objective was achieved through the minimization of a quality factor that is a function of both voltage and current density f V J = V /J 0 5 . The best structures were those containing two and four graded layers, in which the quality factor was smaller than the previous optimization presented in the literature.

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Section: Genetic Algorithm Optimizationmentioning

confidence: 99%

Optimization of the Electrical Efficiency of Graded Multilayer Organic Light-Emitting Diodes Supported by Genetic Algorithm

Costa¹,

Pacheco²,

Neto³

et al. 2014

Jnl of Comp & Theo Nano

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“…Ants search for the best possible solution by walking from vertex to vertex on the potential surface grid. The movement of an ant from an initial point (x 1 , y 1 ) to the final point (x 2 , y 2 ) is guided by the evaluation function [23] E(x 1 , y 1 , x 2 , y 2 )…”

Section: Ant Algorithmmentioning

confidence: 99%

Designing Type-II staggered model ternary copolymers using ant algorithm

Garg

Bakhshi

2010

Chemical Physics

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“…Combinatorial libraries allow for an exhaustive and systematic exploration of well-defined chemical spaces, but the number of generated molecules grows exponentially. At a later stage we plan to use a genetic algorithm − as a complement to the current approach . Its fitness function will be based on the information gathered from the screening of the primary library.…”

mentioning

confidence: 99%

The Harvard Clean Energy Project: Large-Scale Computational Screening and Design of Organic Photovoltaics on the World Community Grid

Hachmann

Olivares‐Amaya

Atahan-Evrenk

et al. 2011

J. Phys. Chem. Lett.

604

565

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This perspective article introduces the Harvard Clean Energy Project (CEP), a theory-driven search for the next generation of organic solar cell materials. We give a broad overview of its setup and infrastructure, present first results, and outline upcoming developments.CEP has established an automated, high-throughput, in silico framework to study potential candidate structures for organic photovoltaics. The current project phase is concerned with the characterization of millions of molecular motifs using first-principles quantum chemistry. The scale of this study requires a correspondingly large computational resource which is provided by distributed volunteer computing on IBM's World Community Grid. The results are compiled and analyzed in a reference database and will be made available for public use. In addition to finding specific candidates with certain properties, it is the goal of CEP to illuminate and understand the structure-property relations in the domain of organic electronics. Such insights can open the door to a rational and systematic design of future high-performance materials. The computational work in CEP is tightly embedded in a collaboration with experimentalists, who provide valuable input and feedback to the project.

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Designing conducting polymers using bioinspired ant algorithms

Cited by 14 publications

References 21 publications

Optimization of the Electrical Efficiency of Graded Multilayer Organic Light-Emitting Diodes Supported by Genetic Algorithm

Optimization of the Electrical Efficiency of Graded Multilayer Organic Light-Emitting Diodes Supported by Genetic Algorithm

Designing Type-II staggered model ternary copolymers using ant algorithm

The Harvard Clean Energy Project: Large-Scale Computational Screening and Design of Organic Photovoltaics on the World Community Grid

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