Microfluidics for real-time direct monitoring of self- and co-assembly biomolecular processes

Zohar A. Arnon, Sharon Gilead, Ehud Gazit

Research output: Contribution to journalReview articlepeer-review

9 Scopus citations


Molecular self-assembly is a major approach for the fabrication of functional supramolecular nanomaterials. This dynamic, straightforward, bottom-up procedure may result in the formation of various architectures at the nano-scale, with remarkable physical and chemical characteristics. Biological and bio-inspired building blocks are especially attractive due to their intrinsic tendency to assemble into well-organized structures, as well as their inherent biocompatibility. To further expand the morphological diversity, co-assembly methods have been developed, allowing to produce alternative unique architectures, enhanced properties, and improved structural control. However, in many cases, mechanistic understanding of the self- and co-assembly processes is still lacking. Microfluidic techniques offer a set of exclusive tools for real-time monitoring of biomolecular self-organization, which is crucial for the study of such dynamic processes. Assembled nuclei, confined by micron-scale pillars, could be subjected to controlled environments aiming to assess the effect of different conditions on the assembly process. Other microfluidics setups can produce droplets at a rate of over 100 s-1, with volumes as small as several picoliters. Under these conditions, each droplet can serve as an individual pico/nano-reactor allowing nucleation and assembly. These processes can be monitored, analyzed and imaged, by various techniques including simple bright-field microscopy. Elucidating the mechanism of such molecular events may serve as a conceptual stepping-stone for the rational control of the resulting physicochemical properties.

Original languageEnglish
Article number102001
Issue number10
StatePublished - 18 Jan 2019


FundersFunder number
Horizon 2020 Framework Programme694426


    • Microfluidics
    • mechanistic study
    • real-time monitoring
    • self-assembly


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