Order from Disorder: Measuring Reversibility and Local Equilibration in Self-Assembly

Abstract

We illustrate self-assembly with several systems which aim to harness the process of assembly to create new functional structures. The concept of kinetic trapping preventing assembly and the importance of reversibility, breaking as well as making bonds, for avoiding such traps are introduced. We aim to identifyhow reversible systems are, with the aim of aecting the prediction, control anddesign of new systems.In four systems a lattice gas model, and three models based upon patchy particleschemes, a yield is dened and used to identify optimal assembly at a giventime. Three measurements relevant to reversibility are described, applied, andcompared with the results of similar studies. The rst simply counts the bondingand un-bonding events, or kinks, over the whole assembly process and comparesthe total number of events with the net bonding events. We measure values of100 􀀀 1000kinks per bond in crystal systems, and 60 􀀀 200 for closed structures.In analogy with a toy model the values can be related to a `forgivingness', a ratioof bad bonding sites, to good ones.We then turn to measurements at early times which allow for the predictionof when assembly will occur. These include rate measurements of kinks whichprovide an instant measure of reversibility and comparison of correlation andresponse functions with the equilibrium uctuation dissipation theory. Thesemethods examine the dynamics of the assembly process while our third approachexamines the structures during assembly. We examine how each of the measurementsprovide information about the assembly process and how it relates tothe particles, their interactions and the nal structure. The possibility of usingthe methods in combination is shown to be relevant to the prediction of assemblyand how they might be used to implement design and control schemes to improveassembly.

Date of Award	17 Oct 2012
Original language	English
Awarding Institution	University of Bath
Supervisor	Robert Jack (Supervisor)