Neural network–enabled, all-electronic control of non-Newtonian fluid flow
Real-time, all-electronic control of non-Newtonian fluid flow through a microscale channel is crucial for various applications in manufacturing and healthcare. However, existing methods lack the sensitivity required for accurate measurement and the real-time responsiveness necessary for effective adjustment. Here, we demonstrate an all-electronic system that enables closed-loop, real-time, high-sensitivity control of various waveforms of non-Newtonian fluid flow (0.76 <i>μ</i>l min<sup>-1</sup>) through a micro-sized outlet. Our approach combines a contactless, cuff-like flow sensor with a neural-network control program. This system offers a simple, miniaturized, versatile, yet high-performance solution for non-Newtonian fluid flow control, easily integrated into existing setups.
Authors
- Xin Hai Zhang (ORCID: https://orcid.org/0009-0009-0636-0959)
- Xiao Fan (ORCID: https://orcid.org/0000-0002-2620-3143)
- Huilu Bao (ORCID: https://orcid.org/0000-0001-9815-833X)
- Jinglei Ping (ORCID: https://orcid.org/0000-0003-0386-8828)
- J. William Boley (ORCID: https://orcid.org/0000-0003-0020-0988)
- Xiaoyu Zhang (ORCID: https://orcid.org/0000-0002-7052-6927)
Institutions
- Boston University (US)
- University of Massachusetts Amherst (US)
Publication Details
- Journal
- Applied Physics Letters
- Published
- 2024-10-14
- DOI
- https://doi.org/10.1063/5.0226525
- Citations
- 1
- Primary Topic
- Microfluidic and Capillary Electrophoresis Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.18
Funders
- National Science Foundation
- National Institutes of Health
- National Institute of General Medical Sciences
- Division of Civil, Mechanical and Manufacturing Innovation
- Air Force Office of Scientific Research