Self-Assembled Circuit Patterns

Multiscale Biofabrication: Integrating Additive Manufacturing with DNA-Programmable Self-Assembly

Structure and hierarchical organization are crucial elements of biological systems and are likely required when engineering synthetic biomaterials with life-like behavior. In this context, additive manufacturing techniques like bioprinting have become increasingly popular. However, 3D bioprinting, as well as other additive manufacturing techniques, show limited resolution, making it difficult to yield structures on the sub-cellular level. To be able to form macroscopic synthetic biological objects with structuring on this level, manufacturing techniques have to be used in conjunction with biomolecular nanotechnology. Here, a short overview of both topics and a survey of recent advances to combine additive manufacturing with microfabrication techniques and bottom-up self-assembly involving DNA, are given.

Modeling gross damage in tile-based nanomanufacturing by DNA self-assembly

This paper proposes a novel model for gross damage as occurring in tile-based nanomanufacturing by DNA self-assembly. Gross damage occurs due to exogenous agents (such as radiation and tip-sample interactions) and is modeled as a hole (with a large number of empty tile sites) in the aggregate of the self-assembly. A stochastic analysis based on Markov chains for the tile binding process is pursued for regrowth of the tiles. This analysis establishes resilience as the probability to regrow the target pattern in the area affected by the gross damage. The conditions by which regrowth of a hole is favorable (i.e., at high resilience) compared with normal growth are established by considering temperature of aggregation and bond energy. As examples, two patterns for nano interconnects are analyzed based on the proposed model.

Analysis of punctures in DNA self-assembly under forward growth

This paper deals with the characterization and analysis of intentionally induced punctures on a DNA self-assembly. Based on forward growth, punctures are utilized to remove errors in DNA tiles from the self-assembly. Initially, a Markov model is proposed by considering different types of punctures under various bonding conditions in the tiles. For different values of on and off rates (as corresponding to the parameters G(se) and G(mc)), it is shown that the proposed models can assess the types of puncture for removing mismatched tiles as errors. Subsequently, a novel model of puncturing is introduced to establish the condition by which a generic aggregate can utilize punctures for error resilience. It is proven that by using the correct puncture(s), errors as frozen mismatched tiles are moved toward the boundaries, thus ensuring the generation of the target assembly and ease in removal of the errors. As an example, the Sierpinski tile set is analyzed based on the proposed models to fully assess the appropriate type of puncture for this pattern. Simulation results are provided as evidence that the proposed models are effective.

Algorithmic self-assembly of DNA Sierpinski triangles

Algorithms and information, fundamental to technological and biological organization, are also an essential aspect of many elementary physical phenomena, such as molecular self-assembly. Here we report the molecular realization, using two-dimensional self-assembly of DNA tiles, of a cellular automaton whose update rule computes the binary function XOR and thus fabricates a fractal pattern—a Sierpinski triangle—as it grows. To achieve this, abstract tiles were translated into DNA tiles based on double-crossover motifs. Serving as input for the computation, long single-stranded DNA molecules were used to nucleate growth of tiles into algorithmic crystals. For both of two independent molecular realizations, atomic force microscopy revealed recognizable Sierpinski triangles containing 100–200 correct tiles. Error rates during assembly appear to range from 1% to 10%. Although imperfect, the growth of Sierpinski triangles demonstrates all the necessary mechanisms for the molecular implementation of arbitrary cellular automata. This shows that engineered DNA self-assembly can be treated as a Turing-universal biomolecular system, capable of implementing any desired algorithm for computation or construction tasks.

Engineered DNA self-assembly to produce a fractal pattern demonstrates all the necessary mechanisms for the molecular implementation of arbitrary cellular automata