Yield prediction in parallel homogeneous assembly
2017
Article
pi
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} } |