Tunable Resins with PDMS-like Elastic Modulus for Stereolithographic 3D-printing of Multimaterial Microfluidic Actuators

Stereolithographic 3D-printing (SLA) permits facile fabrication of high-precision microfluidic and lab-on-a-chip devices. SLA photopolymers often yield parts with low mechanical compliancy in sharp contrast to elastomers such as poly (dimethyl siloxane) (PDMS). On the other hand, SLA-printable elastomers with soft mechanical properties do not fulfill the distinct requirements for a highly manufacturable resin in microfluidics (e.g., high-resolution printability, transparency, low-viscosity). These limitations restrict our ability to SLA-print efficient microfluidic actuators containing dynamic, movable elements. Here we introduce low-viscous photopolymer resins based on a tunable blend of poly(ethylene glycol) diacrylate (PEGDA, Mw~258) and poly (ethylene glycol methyl ether) methacrylate (PEGMEMA, Mw~300) monomers. In these blends, which we term PEGDA-co-PEGMEMA, tuning the PEGMEMA-to-PEGDA ratio alters the elastic modulus of the printed plastics by ~400-fold, reaching that of PDMS. Through the addition of PEGMEMA, moreover, PEGDA-co-PEGMEMA retains desirable properties of highly manufacturable PEGDA such as low viscosity, solvent compatibility, cytocompatibility and low drug absorptivity. With PEGDA-co-PEGMEMA, we SLA-printed drastically enhanced fluidic actuators including microvalves, micropumps, and microregulators with a hybrid structure containing a flexible PEGDA-co-PEGMEMA membrane within a rigid PEGDA housing

Microfluidic Biosensors and Biofuel Cells Integrated with Low-dimensional Carbon Nanomaterials

This thesis presents development of the next generation carbon-based biofuel cells, and biosensors that are the two important members of the large class of bio-microsystems. In our efforts, we took advantage of exotic properties of graphene and carbon nanotubes (CNTs), and combined them with emerging microfluidic tools to fabricate, analyze, and inform theories that explain the fundamental principles underlying our experimental observations. More specifically, we demonstrated studies on (i) converting enzymatic fuel cells (EFCs) into novel enzymatic biobatteries, (ii) the use of emerging graphene derivatives in enhancing the performance metrics of EFCs, and the next-generation graphene-based phononic sensors for (iii) remote flow rate measurements within microfluidics devices, and (iv) remote detection of glucose with/without the aid of enzymes