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EP/H010432/1 - Evolutionary Optimisation of Self Assembling Nano-Designs (ExIStENcE)

Research Perspectives grant details from EPSRC portfolio

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Professor N Krasnogor EP/H010432/1 - Evolutionary Optimisation of Self Assembling Nano-Designs (ExIStENcE)

Principal Investigator - School of Computer Science, University of Nottingham

Other Investigators

Professor PH Beton, Co InvestigatorProfessor PH Beton

Professor NR Champness, Co InvestigatorProfessor NR Champness

Professor P Moriarty, Co InvestigatorProfessor P Moriarty

Scheme

Standard Research

Research Areas

Artificial Intelligence Technologies Artificial Intelligence Technologies

Complexity Science Complexity Science

Polymer Materials Polymer Materials

Surface Science Surface Science

Start Date

02/2010

End Date

04/2013

Value

£945,423

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Grant Description

Summary and Description of the grant

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.

Structured Data / Microdata


Grant Event Details:
Name: Evolutionary Optimisation of Self Assembling Nano-Designs (ExIStENcE) - EP/H010432/1
Start Date: 2010-02-01T00:00:00+00:00
End Date: 2013-04-30T00:00:00+00:00

Organization: University of Nottingham

Description: 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 algo ...