Scale-up modeling for manufacturing nanoparticles using microfluidic T-junction

ABSTRACT

Nanoparticles have great potential to revolutionize industry and improve our lives in various fields such as energy, security, medicine, food, and environmental science. Droplet-based microfluidic reactors serve as an important tool to facilitate monodisperse nanoparticles with a high yield. Depending on process settings, droplet formation in a typical microfluidic T-junction is explained by different mechanisms, squeezing, dripping, or squeezing-to-dripping. Therefore, the manufacturing process can potentially operate under multiple physical domains due to uncertainties. Although mechanistic models have been developed for individual domains, a modeling approach for the scale-up manufacturing of droplet formation across multiple domains does not exist. Establishing an integrated and scalable droplet formation model, which is vital for scaling up microfluidic reactors for large-scale production, faces two critical challenges: the high dimensionality of the modeling space; and ambiguity among the boundaries of physical domains. This work establishes a novel and generic formulation for the scale-up of multiple-domain manufacturing processes and provides a scalable modeling approach for the quality control of products, which enables and supports the scale-up of manufacturing processes that can potentially operate under multiple physical domains due to uncertainties.

Keywords:

• Scale-up modeling
• nanomanufacturing
• quality engineering

Additional information

Funding

Huang’s work is supported by National Science Foundation (NSF) with CAREER grant number CMMI-1055394. Malmstadt’s work is supported by NSF grant CMMI-1068212.

Notes on contributors

Yanqing Duanmu

Yanqing Duanmu received her B.S. in physics from the University of Science and Technology of China in 2012. She earned her Ph.D. degree in industrial and systems engineering and an M.S. in statistics from the University of Southern California in 2017 under the guidance of Professor Qiang Huang. She is a member of INFORMS. Currently, she is a senior analyst for statistics and operations research at United Airlines.

Carson T. Riche

Carson T. Riche received his B.S. in chemical and biomolecular engineering from Johns Hopkins University in 2010. He earned his Ph.D. from the University of Southern California in chemical engineering in 2015 under the guidance of Professors Noah Malmstadt and Malancha Gupta. He was a postdoctoral scholar in the lab of Professor Dino Di Carlo at the University of California, Los Angeles. Currently, he is an R&D Engineer at Labcyte Inc.

Malancha Gupta

Malancha Gupta is the Jack Munushian Early Career Chair Associate Professor in the Mork Family Department of Chemical Engineering and Materials Science at the University of Southern California. She received her B.S. in chemical engineering from the Cooper Union in 2002. She received her Ph.D. in chemical engineering from the Massachusetts Institute of Technology in 2007 under the guidance of Professor Karen Gleason. From 2007-2009, she was a postdoctoral fellow in the Department of Chemistry and Chemical Biology at Harvard University working under the guidance of Professor George Whitesides. She has received several awards including the ACS PRF Doctoral New Investigator Award in 2012, the NSF CAREER Award in 2013, and the USC Viterbi School of Engineering Junior Faculty Research Award in 2014.

Noah Malmstadt

Noah Malmstadt is an associate professor at the University of Southern California. He received a B.S. in chemical engineering from Caltech and a Ph.D. in bioengineering from the University of Washington. Following postdoctoral work at UCLA, he joined the Mork Family Department of Chemical Engineering and Materials Science at USC in 2007. He is the recipient of a 2012 Office of Naval Research Young Investigator award and is a 2017 Association of Laboratory Automation JALA 10 Honoree. His research focuses on microfluidic strategies to facilitate material fabrication and biophysical analysis. He has pioneered the integration of ionic liquids as solvents in droplet microreactors and the application of microfluidic systems to synthesizing biomimetic cell membranes. Microfluidic analytical techniques he has developed include methods for measuring the permeability of cell membranes to druglike molecules and techniques for measuring ionic currents through membrane proteins.

Qiang Huang

Qiang Huang received his Ph.D. degree in industrial and operations engineering from the University of Michigan-Ann Arbor. He is currently an associate professor at the Daniel J. Epstein Department of Industrial and Systems Engineering, University of Southern California (USC), Los Angeles. He was the holder of Gordon S. Marshall Early Career Chair in Engineering at USC from 2012 to 2016. He received a National Science Foundation CAREER award in 2011 and IEEE Transactions on Automation Science and Engineering Best Paper Award from IEEE Robotics and Automation Society in 2014. He is department editor for IISE Transactions, associate editor for ASME Transactions, Journal of Manufacturing Science and Engineering, and a member of the editorial board for Journal of Quality Technology. He also served an associate editor for IEEE Transactions on Automation Science and Engineering and for IEEE Robotics and Automation Letters. He is a senior member of IEEE and a member of INFORMS, ASME and IISE.