Computational Fluid Dynamics: Optimize Microfluidic Mixing Efficiency

Our team works to design hydrogels that mimic biological tissues. These tissue mimics seek to copy the mechanical and chemical properties of living tissues while also recapitulating their architecture. While these materials are often prepared by hand, additive manufacturing is becoming an increasingly important way of fabricating synthetic tissues and biomaterials from fluid bioinks. Bioprinters typically perfuse bioinks through simple nozzles (usually just a needle) to deposit materials for printing. By substituting these needles with intentionally-engineered passive microfluidic mixing nozzles, bioprinters can be designed to produce increasingly complex materials with property gradients that more accurately mimic the properties of biological tissues.

Fluid mixing at the microscale often operates in suppressed Reynolds number regimes. In these flows, viscous forces dominate, thus attenuating advection and resulting in slow, inefficient, diffusion-limited mixing. Achieving efficient microfluidic mixing through passive approaches requires designs that circumvent this limitation by leveraging geometry, operating conditions, and fluid properties to achieve enhanced mixing performance. Our goal is to mix materials across a range of properties to form biomaterials that mimic the properties of biological tissues. To accomplish this work, you will learn and use computational fluid dynamics (CFD) by using ANSYS Fluent on the NSF’s Extreme Science and Engineering Discovery Environment (XSEDE). Through this work, you will join a team that will evaluate and design microfluidic mixers with performance optimized for bioink material properties. This work extends work initiated by prior Mudders with the possibility for collaboration with students external to HMC.

Check out our recent work: 

Name of research group, project, or lab
Microfluidics and Biomaterials Laboratory
Why join this research group or lab?

As a member of this group, you would work on projects that collectively build knowledge at the intersection of fluid mechanics, bioengineering, and material engineering. Together, our work seeks to build tools and materials for evaluating biological function in benchtop models to uncover biological function.

Logistics Information:
Project categories
Computer Science
Fluid Mechanics
Mechanical Engineering
Student ranks applicable
Student qualifications

Students with a keen interest in fluid mechanics or who have taken Materials Engineering and/or fluid mechanics (or those planning to take these or related courses during the Fall 2021 semester) are encouraged to apply. Furthermore, students with experience in parallel, high-performance computing, linux systems, and/or ANSYS fluent are also encouraged to apply.

Time commitment
Fall - Part Time
Spring - Part Time
Academic Credit
Number of openings
Techniques learned

high-performance computing, computational fluid dynamics, microfluidic device design, experimental design, data analysis

Contact Information:
Mentor name
Mentor email
Mentor position
Name of project director or principal investigator
Steven Santana
Email address of project director or principal investigator
2 sp. | 0 appl.
Hours per week
Fall - Part Time (+1)
Fall - Part TimeSpring - Part Time
Project categories
Mechanical Engineering (+2)
Computer ScienceFluid MechanicsMechanical Engineering