Reducing facet nucleation during algorithmic self-assembly.
Algorithmic self-assembly, a generalization of crystal growth, has been proposed as a mechanism for bottom-up fabrication of complex nanostructures and autonomous DNA computation. In principle, growth can be programmed by designing a set of molecular tiles with binding interactions that enforce assembly rules. In practice, however, errors during assembly cause undesired products, drastically reducing yields. Here we provide experimental evidence that assembly can be made more robust to errors by adding redundant tiles that "proofread" assembly. We construct DNA tile sets for two methods, uniform and snaked proofreading. While both tile sets are predicted to reduce errors during growth, the snaked proofreading tile set is also designed to reduce nucleation errors on crystal facets. Using atomic force microscopy to image growth of proofreading tiles on ribbon-like crystals presenting long facets, we show that under the physical conditions we studied the rate of facet nucleation is 4-fold smaller for snaked proofreading tile sets than for uniform proofreading tile sets.
Chen
Ho-Lin
HL
Department of Computer Science, Stanford University, Stanford, California 94305, USA.
Schulman
Rebecca
R
Goel
Ashish
A
Winfree
Erik
E
D000465:Algorithms; D003198:Computer Simulation; D003460:Crystallization / Q000379:methods*; D004247:DNA / Q000737:chemistry* / Q000648:ultrastructure*; D046911:Macromolecular Substances / Q000737:chemistry; D008422:Materials Testing; D008956:Models, Chemical; D008958:Models, Molecular; D008968:Molecular Conformation; D049329:Nanostructures / Q000737:chemistry* / Q000648:ultrastructure*; D036103:Nanotechnology / Q000379:methods; D010316:Particle Size; D013499:Surface Properties
D046911:Macromolecular Substances; D004247:DNA