Evolutionary Optimisation of Self Assembling Nano-Designs (ExIStENcE)

Lead Research Organisation: University of Nottingham
Department Name: School of Computer Science


The primary objective of this proposal is the development of novel evolutionary algorithms (EAs) and protocols, based on deeper principles than currently available, for the optimisation, design and exploitation of molecular self-assembly. Evolutionary algorithms are nowadays well established techniques that have shown their worth on a large variety of applications that range from timetabling and scheduling problems to robotics and space antenna design. Surprisingly, EAs have not yet been systematically analised in the context of molecular tile design. At the core of our approach lies the assumption that self-assembly can be understood as an information-driven process and hence be better exploited by directly linking it to computational phenomena. Taken as an operational hypothesis, which our research programme will analyse both theoretically and experimentally, this assumption implies that with suitable tools, desired emergent phenomena could in principle be programmed into self-assembling nanosystems. Our experimental target will be based around molecular tiles as these have been shown to be computationally complete [1,2,3]. Hence, they can potentially be programmed to perform any set of discrete information processing steps which in turn could induce a specific emergent pattern of complex behaviour. This project will seek to automate the process of programming molecular tiles using evolutionary algorithms. In an interview for Thomson Scientific's Science Watch newsletter [quoted in J.A. Pelesko, Self Assembly, The Science of Things that Put Themselves Together, Chapman & Hall/CRC, 2007], G. Whitesides, one of the most prolific and highly cited chemists in the world, noted that the holy grail of his research was To be able to make complex systems, either structurally or functionally, by self-assembly...We would like to develop a synthesis technology that would enable the making of nanometer-scale... structures on surfaces with arbitrary chosen properties . Whitesides' challenge is at the heart of our research programme. We will seeks to leverage state-of-the-art research in Computer Science and Nanoscience to meet this challenge.


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Description Self-assembly is a phenomenon observed in nature at all scales where autonomous entities build complex structures, without external influences nor centralised master plan. Modelling such entities and programming correct interactions among them is crucial for controlling the manufacture of desired complex structures at the molecular and supramolecular scale. This work focuses on a programmability model for non DNA-based molecules and complex behaviour analysis of their self-assembled conformations. In particular, we look into modelling, programming and simulation of porphyrin molecules self-assembly and apply Kolgomorov complexity-based techniques to classify and assess simulation results in terms of information content. The analysis focuses on phase transition, clustering, variability and parameter discovery which as a whole pave the way to the notion of complex systems programmability.

In the past decades many definitions of complexity have been proposed. Most of these definitions are based either on Shannon's information theory or on Kolmogorov complexity; these two are often compared, but very few studies integrate the two ideas. In this article we introduce a new measure of complexity that builds on both of these theories. As a demonstration of the concept, the technique is applied to elementary cellular automata and simulations of the self-organization of porphyrin molecules.
Exploitation Route N/A
Sectors Manufacturing, including Industrial Biotechology

URL http://www.cs.nott.ac.uk/~pszga/sipndbmsa/index.html