Physical Intelligence Article 2017

Yield prediction in parallel homogeneous assembly

Physical Intelligence
Associate Professor (Tenured) at Delft University of Technology, Netherlands
Physical Intelligence
Guest Researcher

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
Month: June
BibTeX Type: Article (article)
DOI: 10.1039/C7SM01189J
Electronic Archiving: grant_archive

BibTeX

@article{C7SM01189J,
  title = {Yield prediction in parallel homogeneous assembly},
  journal = {Soft Matter},
  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.},
  volume = {13},
  number = {41},
  pages = {7595-7608},
  month = jun,
  year = {2017},
  author = {Ipparthi, Dhananjay and Winslow, Andrew and Sitti, Metin and Dorigo, Marco and Mastrangeli, Massimo},
  doi = {10.1039/C7SM01189J},
  month_numeric = {6}
}