Molecular Information Technology

Abstract

ABSTRACT:Molecular materials are endowed with unique properties of unrivaled potential for high density integration of computing systems. Present applications of molecules range from organic semiconductor materials for low-cost circuits to genetically modified proteins for commercial imaging equipment. To fully realize the potential of molecules in computation, information processing concepts that relinquish narrow prescriptive control over elementary structures and functions are needed, and self-organizing architectures have to be developed. Investigations into qualitatively new concepts of information processing are underway in the areas of reaction-diffusion computing, self-assembly computing, and conformation-based computing. Molecular computing is best considered not as competitor for conventional computing, but as an opportunity for new applications. Microrobotics and bioimmersive computing are among the domains likely to benefit from advances in molecular computing. Progress will depend on both novel computing concepts and innovations in materials. This article reviews current directions in the use of bulk and single molecules for information processing. KEY WORDS:polymer electronics, molecular switches, self-assembly computing, conformation-based computation, self-organizing materials, bioimmersive computing

The Phi-Bot: A Robot Controlled by a Slime Mould

“…The formidable gap between artificial and natural systems in terms of information processing capability [1] motivates research into biological modes of information processing. Hybrid artifacts, for example, try to overcome the theoretic and physical limits of information processing in solid-state realisations of digital von Neumann machines by exploiting the self-organisation of naturally evolved systems in engineered environments [2,3].…”

Enabling the discovery of computational characteristics of enzyme dynamics

“…An example of these are given for a 1-dimensional parameter space first considered in Fig. 5, where one behaviour is similar to Michaelis-Menton kinetics [47] and the others provide non-monotonic behaviours that could be of use within enzymatic computation [38]. In the simulation observations were calculated from the behaviour using the requested experiment parameter, then all were adjusted with Gaussian noise (N (0, 0.5 2 )) and 25% of the observations had shock noise applied to them to provide erroneous observations.…”

“…Therefore a third assumption we made that not all observations are valid, where some observations will be unrepresentative of the actual behaviour that should be observed, which we refer to as erroneous observations produced through shock noise. Finally we assumed that the response characteristics of the enzymes under investigation and of potential usefulness in enzymatic computation, will be both monotonic and non-monotonic [38]. Using these assumptions we developed a set of algorithms, collectively named an artificial experimenter, for performing automated discovery.…”

Robot Control: From Silicon Circuitry to Cells

“…In examining what is known about nature's molecular level computing it becomes evident that matter is used in a markedly different way than in conventional computing architectures. Information processing mechanisms are tightly coupled to physiochemical properties of the materials rather than being narrowly constraint to enact a rigid formalism [13].…”