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Yield prediction in parallel homogeneous assembly

2017

Article

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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.

Author(s): Ipparthi, Dhananjay and Winslow, Andrew and Sitti, Metin and Dorigo, Marco and Mastrangeli, Massimo
Journal: Soft Matter
Volume: 13
Number (issue): 41
Pages: 7595-7608
Year: 2017

Department(s): Physical Intelligence
Bibtex Type: Article (article)
Paper Type: Journal

DOI: 10.1039/C7SM01189J

BibTex

@article{C7SM01189J,
  title = {Yield prediction in parallel homogeneous assembly},
  author = {Ipparthi, Dhananjay and Winslow, Andrew and Sitti, Metin and Dorigo, Marco and Mastrangeli, Massimo},
  journal = {Soft Matter},
  volume = {13},
  number = {41},
  pages = {7595-7608},
  year = {2017},
  doi = {10.1039/C7SM01189J}
}