Gain scheduling PID control for directed self‐assembly of colloidal particles in microfluidic devices

Gao, Yu; Lakerveld, Richard

doi:10.1002/aic.16582

Cited by 8 publications

(8 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…PID control, an engineering tool commonly used to fix system behavior at a previously-identified set point, was applied to control the electric field voltage and frequency needed to keep particle density constant in microfluidic colloidal self-assembly. 93 DoE has also been used to identify optimal conditions for liposome production. 94 Integration with ML can significantly increase the breadth and complexity of intelligent microfluidic operation, streamlining the operation of expert devices.…”

Section: Microfluidic Controlmentioning

confidence: 99%

Machine learning for microfluidic design and control

et al. 2022

View full text Add to dashboard Cite

show abstract

Section: Microfluidic Controlmentioning

confidence: 99%

Machine learning for microfluidic design and control

et al. 2022

View full text Add to dashboard Cite

show abstract

“…A fundamental understanding obtained through modeling would be a pathway towards achieving specific microstructures with targeted properties. Such process control strategies could be developed using real-time field actuation to direct particle assembly [ 224 , 225 , 226 ], gain-scheduling policies that maximize particle packing [ 227 , 228 , 229 ], or the identification of an open-loop strategy that would achieve a desired order parameter, such as the degree of hexagonal close-packing [ 230 , 231 ].…”

Section: Future Directions and Conclusionmentioning

confidence: 99%

Directed Assembly of Particles for Additive Manufacturing of Particle-Polymer Composites

Shabaniverki

Juárez

2021

Micromachines

View full text Add to dashboard Cite

Particle-polymer dispersions are ubiquitous in additive manufacturing (AM), where they are used as inks to create composite materials with applications to wearable sensors, energy storage materials, and actuation elements. It has been observed that directional alignment of the particle phase in the polymer dispersion can imbue the resulting composite material with enhanced mechanical, electrical, thermal or optical properties. Thus, external field-driven particle alignment during the AM process is one approach to tailoring the properties of composites for end-use applications. This review article provides an overview of externally directed field mechanisms (e.g., electric, magnetic, and acoustic) that are used for particle alignment. Illustrative examples from the AM literature show how these mechanisms are used to create structured composites with unique properties that can only be achieved through alignment. This article closes with a discussion of how particle distribution (i.e., microstructure) affects mechanical properties. A fundamental description of particle phase transport in polymers could lead to the development of AM process control for particle-polymer composite fabrication. This would ultimately create opportunities to explore the fundamental impact that alignment has on particle-polymer composite properties, which opens up the possibility of tailoring these materials for specific applications.

show abstract

“…The overall PID control function is where K c is the proportional term, τ I is the integral time, and τ D is the derivative time.…”

Section: Proposed Experimental Setup Mathematical Modeling and Controlmentioning

confidence: 99%

Theoretical Feedback Control Scheme for the Ultrasound-Assisted Continuous Antisolvent Crystallization of Aspirin in a Tubular Crystallizer

Savvopoulos

Voutetakis

Kuhn

et al. 2021

Ind. Eng. Chem. Res.

View full text Add to dashboard Cite

Ultrasound-assisted crystallization is a promising process for the production of crystals within a size distribution width. Toward the direction of attaining high-quality crystals, this article proposes and assesses a theoretical feedback control scheme that can be applied in a continuous tubular crystallizer. In this crystallizer, the antisolvent crystallization of aspirin (a pharmaceutical ingredient) in water (an antisolvent) and ethanol (a solvent) takes place under ultrasound. Initially, a dynamic model is developed and includes the aspirin concentration variations while also taking into account temperature modifications in the inlet. After model validation, a PI control scheme is finely tuned, implemented theoretically, and critically assessed at the (i) trajectory control of the crystal length (average size), (ii) alleviation of suddenly emerged disturbances (e.g., solvent flow rate, inlet temperature), and (iii) a combination of worst-case operating scenarios. As identified, the proposed controller can offer a practical platform that can be readily applied to different scales and geometries in continuous tubular crystallizers operating with ultrasound. During all simulations, the produced crystals maintained high quality.

show abstract

Gain scheduling PID control for directed self‐assembly of colloidal particles in microfluidic devices

Cited by 8 publications

References 38 publications

Machine learning for microfluidic design and control

Machine learning for microfluidic design and control

Directed Assembly of Particles for Additive Manufacturing of Particle-Polymer Composites

Theoretical Feedback Control Scheme for the Ultrasound-Assisted Continuous Antisolvent Crystallization of Aspirin in a Tubular Crystallizer

Contact Info

Product

Resources

About