Discipline: Technology and Engineering
Subcategory: Biomedical Engineering
Amber Camacho - Cal State Long Beach
Co-Author(s): Roger C. Lo, Cal State Long Beach
Microfluidics is the study of manipulating or processing small volumes of fluid at a microscale (typically tens of micrometers). The high surface-area-to-volume ratio of microfluidic devices leads to enhanced heat and mass transfer and interfacial phenomena that are not usually observed at a macroscale, such as the domination of surface forces instead of inertial and body forces. Microfluidic devices have potential applications, including: chemical synthesis, DNA sequencing, and drug screening, because it has many advantages, such as significant reduction in analysis time, much lower sample and reagent consumption (in the nanoliter range or less), and enhanced system performance and functionality by integrating different components onto individual devices. 3D printing has entered this discipline because it allows rapid fabrication of customized microfluidic devices without using the traditional process that requires intensive labor and unpleasant chemicals. Herein, we present our current progress in modeling, fabricating, and operating fully automated microfluidic devices for organic chemical synthesis. Our lab reproduced Lee Cronin’s results before initiating our own experiments. We utilized computer aided design programs to draft the designs of the devices and proceeded to print them. The preliminary devices were tested with nonreactive fluids to test the integrity of its structure. We also were able to characterize the fluid flow properties in the devices. Through experimentation, we have determined the properties of several thermoplastic materials and have gained more insight into the printing process. Further research will eventually lead to printing in thermoplastics capable of carrying out organic synthesis. The current plastics investigated are not well suited for this purpose but have allowed us to understand the printing process more clearly.
Funder Acknowledgement(s): This research is supported in part by the National Science Foundation Grant HRD-1402873 and College of Natural Sciences and Mathematics, CSULB
Faculty Advisor: None Listed, email@example.com