2, Departamento de Mecatrónica e Ingeniería Eléctrica, Tecnológico de Monterrey, Nuevo León, , Mexico
3, Imperial College London, London, , United Kingdom
4, School of Mechanical Engineering, College of Engineering, University of Tehran, Tehran, , Iran (the Islamic Republic of)
5, Department of Engineering in Medicine, Brigham and Women's Hospital, Harvard Medical School, Cambridge, Massachusetts, United States
Nature generates densely packed micro- and nanostructures to enable key functionalities in cells, tissues, and other materials. Current fabrication techniques, due to limitations in resolution and speed, are far less effective at creating microstructure. Yet, the development of extensive amounts of surface area per unit of volume will enable applications and manufacturing strategies not possible today. Here, we introduce chaotic printing—the use of chaotic flows for rapid generation of complex, high-resolution microstructures.
Here we use two clasic mixing systems as models, the Journal Bearing (JB) Flow and the Kenics mixer, to demontrate the use of chaotic printing. In a miniaturized JB flow (miniJB) we induced deterministic chaotic flows in viscous liquids. These flows deform an “ink” (i.e., a drop of a miscible liquid, fluorescent beads, or cells) at an exponential rate to render a densely packed lamellar microstructure that is then preserved by curing or photocrosslinking. In a continuous version of chaotic printing, we created chaotic flows by coextruding two streams of alginate (two inks) through a printing head that contains an on-line miniaturized Kenics static mixer with multiple mixing elements (or sections). In this way, we continuously 3D-print multi-material lamellar structures with different degrees of surface area (as a function of th enumber of elements used) and full spatial control of the internal microstructure. The combined outlet stream is then submerged in a calcium chloride solution in order to crosslink the emerging alginate fibers and preserve the microstructure.
We show that the exponentially fast creation of fine microstructure achievable through chaotic printing exceeds the limits of resolution and speed of the currently available 3D printing techniques. Moreover, we show that the architecture of the microstructure to be created with chaotic printing can be predicted using computational fluid dynamic (CFD) techniques.
We present diferent proof-of-principle applications for this technology, including the development of densely packed biocatalytic surfaces and highly complex multi-lamellar and multi-component tissue-like structures for biomedical applications.