3 papers
physics.flu-dyn2024
Predicting Performance of Microfluidic-Based Alginate Microfibers with Feature-Supplemented Deep Neural Networks
Nicholus R. Clinkinbeard, Justin Sehlin, Meharpal Singh Bhatti +3
Selection of solution concentrations and flow rates for the fabrication of microfibers using a microfluidic device is a largely empirical endeavor of trial-and-error, largely due t…
cs.CE2024
Accelerating Hydrodynamic Fabrication of Microstructures using Deep Neural Networks
Nicholus R. Clinkinbeard, Reza Montazami, Nicole N. Hashemi
Manufacturing of microstructures using a microfluidic device is a largely empirical effort due to the multi-physical nature of the fabrication process. As such, models are desired…
cs.LG2021
Machine Learning-Assisted E-jet Printing of Organic Flexible Biosensors
Mehran Abbasi Shirsavar, Mehrnoosh Taghavimehr, Lionel J. Ouedraogo +4
Electrohydrodynamic-jet (e-jet) printing technique enables the high-resolution printing of complex soft electronic devices. As such, it has an unmatched potential for becoming the…