Abstract
In this work, we have investigated the scattering plasmonic resonance characteristics of silver nanospheres with a geometrical distribution that is modelled by Cellular Automata using time-domain numerical analysis. Cellular Automata are discrete mathematical structures that model different natural phenomena. Two binary one-dimensional Cellular Automata rules are considered to model the nanostructure, namely rule 30 and rule 33. The analysis produces three-dimensional scattering profiles of the entire plasmonic nanostructure. For the Cellular Automaton rule 33, the introduction of more Cellular Automata generations resulted only in slight red and blue shifts in the plasmonic modes with respect to the first generation. On the other hand, while rule 30 introduced significant red shifts in the resonance peaks at early generations, at later generations however, a peculiar effect is witnessed in the scattering profile as new peaks emerge as a feature of the overall Cellular Automata structure rather than the sum of the smaller parts that compose it. We strongly believe that these features that emerge as a result adopting the different 256 Cellular Automata rules as configuration models of nanostructures in different applications and systems might possess a great potential in enhancing their capability, sensitivity, efficiency, and power utilization.
Highlights
Cellular Automaton (CA) theory was established and developed in the second half of the last century [1]
Two Cellular Automata have been implemented as models of distribution of silver nanospheres whose scattering profiles were acquired after each generation
While Cellular Automaton rule 33 is a simple and a systematic rule, which provides simplicity and ease of implementation, it showed a scattering profile matching that of a single silver nanosphere with two resonance modes that blue and red shift as more generations are introduced
Summary
Cellular Automaton (CA) theory was established and developed in the second half of the last century [1]. A onedimensional Cellular Automaton is a discrete mathematical structure that is consisted of a sequence of ݇ number of consecutive cells where each cell can take a value between 0 and ݇ െ 1. The decimal value of each rule is represented in hexadecimal form and the binary equivalent of this hexadecimal number associates with different combinations of input values of the cells [1, 3]. Cellular Automata had been extensively used in several applications, such as image processing, traffic modelling, and music composition [2]. We believe that employing these nature-complying rules as configuration models in different artificial systems and structures, such as sensing, imaging, and energy harvesting applications, can introduce positive enhancements to their capabilities, efficiencies, and energy utilization. Thereafter, we characterize the scattering profiles of these CA configurations while observing how they evolve after each generation
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