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Controlling fragment competition on pathways to addressable self-assembly [dataset] Open Access

Addressable self-assembly is the formation of a target structure from a set of unique molecular or colloidal building-blocks, each of which occupies a defined location in the target. The requirement that each type of building-block appears exactly once in each copy of the target introduces severe restrictions on the combinations of particles and on the pathways that lead to successful self-assembly. These restrictions can limit the efficiency of self-assembly and the final yield of the product. In particular, partially formed fragments may compete with each other if their compositions overlap, since they cannot be combined. Here, we introduce a "completability" algorithm to quantify competition between self-assembling fragments and use it to deduce general principles for suppressing the effects of fragment incompatibility in the self-assembly of small addressable clusters. Competition originates from loops in the bonding network of the target structure, but loops may be needed to provide structural rigidity and thermodynamic stability. An optimal compromise can be achieved by careful choice of bonding networks and by promoting semi-hierarchical pathways that rule out competition between early fragments. These concepts are illustrated in simulations of self-assembly in two contrasting addressable targets of 20 unique components each.

Descriptions

Resource type
Dataset
Contributors
Creator: Madge, Jim 1
Creator: Miller, Mark A. 1
Creator: Bourne, David 2
1 Durham University, Department of Chemistry, UK
2 Durham University, Department of Mathematical Sciences, UK
Funder
Research methods
Other description
Keyword
Self assembly (Chemistry)
Monte Carlo simulation
Soft matter
Subject
Monte Carlo method
Self-assembly (Chemistry)
Location
Language
Cited in
https://doi.org/10.1021/acs.jpcb.8b08096
Identifier
ark:/32150/r1br86b360m
doi:10.15128/r1br86b360m
Rights
Affero General Public Licence 3 (AGPL-3.0)

Publisher
Durham University
Date Created
1 October 2018

File Details

Depositor
M.A. Miller
Date Uploaded
Date Modified
3 October 2018, 11:10:04
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Characterization
File format: zip (ZIP Format)
Mime type: application/zip
File size: 6685
Last modified: 2018:10:01 11:40:49+01:00
Filename: data.zip
Original checksum: c3993fc39da40c52a5858368c87036c2
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