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Yield prediction in parallel homogeneous assembly

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Abstract

We investigate the parallel assembly of two-dimensional, geometrically-closed modular target structures out of homogeneous sets of macroscopic components of varying anisotropy. The yield predicted by a chemical reaction network (CRN)-based model is quantitatively shown to reproduce experimental results over a large set of conditions. Scaling laws for parallel assembling systems are then derived from the model. By extending the validity of the CRN-based modelling, this work prompts analysis and solutions to the incompatible substructure problem.

Graphical abstract: Yield prediction in parallel homogeneous assembly

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Publication details

The article was received on 15 Jun 2017, accepted on 19 Sep 2017 and first published on 19 Sep 2017


Article type: Paper
DOI: 10.1039/C7SM01189J
Citation: Soft Matter, 2017, Advance Article
  • Open access: Creative Commons BY license
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    Yield prediction in parallel homogeneous assembly

    D. Ipparthi, A. Winslow, M. Sitti, M. Dorigo and M. Mastrangeli, Soft Matter, 2017, Advance Article , DOI: 10.1039/C7SM01189J

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