A Study of Microfluidic Nozzle Array for Tuanble Physico-chemically Coding of Microfibers

Abstract

Microfibers have been shown their importance in biological and medical applications [1-4]. Microfibers are common in nature, but the controlled synthesis of fibers at microscale remains challenging. Microfluidic approach has recently shown a great promise for producing microstructures with various shapes, such as particles, fibers, and tubes. This approach also facilitates the production of tunable physicochemical coding of microfibers. Physicochemically coded microfibers are microfibers that are loaded with functional groups of chemical molecules or biological cells.In this study, we aim to fabricate physicochemically coded microfibers as simple as 3D-printing. The main objective is to investigate designs of a microfluidic nozzle that incorporates with a commercial liquid-based 3D printer to fabricate physicochemically coded microfibers. To our best of knowledge, such a platform has not been reported. We use COMSOL Multiphysics Livelink with MATLAB for modeling and simulating every design of microfluidic nozzle. COMSOL Multiphysics is a powerful platform to model various physics-based problems, and MATLAB is a high-level technical computing language and interactive environment for algorithm development, data visualization, data analysis, and numerical calculation. By linking COMSOL Multiphysics and MATLAB together, we can easily perform parametric study of our designs. We can also easily implement advanced optimization algorithms (e.g. Differential Evolution, or Genetic Algorithm, etc.) to find the best optimized design.

Document Details

Document Type
DoD Grant Award
Publication Date
Apr 09, 2018
Source ID
FA23861714018

Entities

People

  • Quoc Bao Ta

Organizations

  • Air Force Office of Scientific Research
  • Tôn Đức Thắng University
  • United States Air Force

Tags

Readers

  • Computational Fluid Dynamics (CFD)
  • Database Systems and Applications
  • Nanocomposite Materials Science

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • Biotechnology