A micromachined Stoneley acoustic wave system for continuous flow particle manipulation in microfluidic channels

2010 ◽  
Vol 20 (3) ◽  
pp. 035031 ◽  
Author(s):  
Ventsislav Yantchev ◽  
Johannes Enlund ◽  
Ilia Katardjiev ◽  
Linda Johansson
Micromachines ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 744 ◽  
Author(s):  
Xiangchun Xuan

Magnetic field-induced particle manipulation is simple and economic as compared to other techniques (e.g., electric, acoustic, and optical) for lab-on-a-chip applications. However, traditional magnetic controls require the particles to be manipulated being magnetizable, which renders it necessary to magnetically label particles that are almost exclusively diamagnetic in nature. In the past decade, magnetic fluids including paramagnetic solutions and ferrofluids have been increasingly used in microfluidic devices to implement label-free manipulations of various types of particles (both synthetic and biological). We review herein the recent advances in this field with focus upon the continuous-flow particle manipulations. Specifically, we review the reported studies on the negative magnetophoresis-induced deflection, focusing, enrichment, separation, and medium exchange of diamagnetic particles in the continuous flow of magnetic fluids through microchannels.


2011 ◽  
Vol 14 (2) ◽  
pp. 279-289 ◽  
Author(s):  
Linda Johansson ◽  
Johannes Enlund ◽  
Stefan Johansson ◽  
Ilia Katardjiev ◽  
Ventsislav Yantchev

Author(s):  
Zhichao Ma ◽  
Adrian J. T. Teo ◽  
Say Hwa Tan ◽  
Ye Ai ◽  
Nam-Trung Nguyen

Surface acoustic wave (SAW) is effective for the manipulation of fluids and particles in microscale. The current approach of integrating interdigitated transducers (IDTs) for SAW generation into microfluidic channels involves complex and laborious microfabrication steps. These steps often require the full access to clean room facilities and hours to align the transducers to the precise location. This work presents an affordable and innovative method for fabricating SAW-based microfluidic devices without the need of clean room facilities and alignment. The IDTs and microfluidic channels are fabricated in the same process and thus precisely self-aligned in accordance with the device design. With the use of the developed fabrication approach, a few types of different SAW-based microfluidic devices have been fabricated and demonstrated for particle separation and active droplet generation.


2011 ◽  
Vol 11 (6) ◽  
pp. 743-752 ◽  
Author(s):  
Junjie Zhu ◽  
Robert Cameron Canter ◽  
Gyunay Keten ◽  
Pallavi Vedantam ◽  
Tzuen-Rong J. Tzeng ◽  
...  

Lab on a Chip ◽  
2016 ◽  
Vol 16 (19) ◽  
pp. 3756-3766 ◽  
Author(s):  
Citsabehsan Devendran ◽  
Thomas Albrecht ◽  
Jason Brenker ◽  
Tuncay Alan ◽  
Adrian Neild

The dominant forcing mechanism for particle manipulation using SSAW is shown to be spatially dependent when travelling components are considered.


2007 ◽  
Vol 79 (19) ◽  
pp. 7291-7300 ◽  
Author(s):  
Benjamin G. Hawkins ◽  
A. Ezekiel Smith ◽  
Yusef A. Syed ◽  
Brian J. Kirby

Author(s):  
Hsiu-hung Chen ◽  
Dayong Gao

The manipulation of particles and cells in micro-fluids, such as cell suspensions, is a fundamental task in Lab-on-a-Chip applications. According to their analysis purposes in either the pre- or post-processing stage, particles/cells flowing inside a microfluidic channel are handled by means of enriching, trapping, separating or sorting. In this study, we report the use of patterning flows produced by a series of grooved surfaces with different geometrical setups integrated into a microfluidic device, to continuously manipulate the flowing particles (5 to 20 μm in diameters) of comparable sizes to the depth of the channel in ways of: 1) concentrating, 2) focusing, and 3) potential separating. The device is fabricated using soft lithographic techniques and is composed of inlets, microfluidic channels, and outlets for loading, manipulating and retrieving cell suspensions, respectively. Such fabrication methods allow rapid prototyping of micron or submicron structures with multiple layers and replica molding on those fabricated features in a clear polymer. The particles are evenly distributed in the entrance of the microchannel and illustrate the enriching, focusing, or size-selective profiles after passing through the patterning grooves. We expect that the techniques of manipulating cell suspensions from this study can facilitate the development of cell-based devices on 1) the visualization of counting, 2) the visualization of sizing, and 3) the particle separating.


Author(s):  
Hing Wah Lee ◽  
Parthiban Arunasalam ◽  
Ishak A. Azid ◽  
Kankanhally N. Seetharamu

In this study, a hybridized neural-genetic optimization methodology realized by embedding finite element analysis (FEA) trained artificial neural networks (ANN) into genetic algorithms (GA) is used to optimize temperature control in a ceramic based continuous flow polymerase chain reaction (CPCR) device. The CPCR device requires three thermally isolated zones of 94°C, 65°C and 72°C for the corresponding process of denaturing, annealing and extension to complete a cycle of polymerase chain reaction. Three separately addressable heaters provide heat input to each zone, microfluidic channels allow for the transport of fluid between zones and thermal isolation between the zones is maintained by machining air-gaps into the device. The most important aspect of temperature control in the CPCR is to maintain temperature distribution at each reaction zone with a precision of ±1°C or better irrespective of changing ambient conditions. Results obtained from the FEA simulation are compared with published experimental work. Simulation results show good comparison with experimental work for the temperature control in each reaction zone of the microfluidic channels. The data is then used to train the ANN to predict the temperature distribution of the microfluidic channel for new heater input power and fluid flow rate. Using these data, optimization of temperature control in the CPCR device is achieved by embedding the trained ANN results as a fitness function into GA. The objective of the optimization is to minimize the temperature difference in each reaction zone of the microfluidic channel while satisfying the residence time requirement. Finally, the optimized results for the CPCR device are used to build a new FEA model for numerical simulation analysis. The simulation results for the neural-genetic optimized CPCR model and the initial CPCR model are then compared. The neural-genetic optimized model shows a significant improvement from the initial model establishing the optimization methods superiority.


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