| Title |
Design of optimal electrode geometries for dielectrophoresis using fitness based on simplified particle trajectories
|
|---|---|
| Published in |
Biomedical Microdevices, July 2016
|
| DOI | 10.1007/s10544-016-0085-8 |
| Pubmed ID | |
| Authors |
Steven Kinio, James K. Mills |
| Abstract |
Dielectrophoretic (DEP) forces applied to microscopic particles are highly dependent on the gradient of the electric field experienced by the particles. These DEP forces can be used to selectively capture and remove cells from fluid flows within a micro-channel above the DEP electrodes. Modification of the geometry of the electrodes that generate the electric field is the main approach available to increase the electric field gradient over a wide area, and hence increase the applied dielectrophoretic force. Optimized DEP forces increase attraction or repulsion of target cells from the electrode surface, enhancing the efficacy of electrodes for cell sorting applications. In this paper, we present a design approach, using genetic optimization techniques, to develop novel electrode geometries that effectively capture target particles. The performance of candidate electrode designs is evaluated by calculating simplified particle trajectories. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 13 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 38% |
| Researcher | 2 | 15% |
| Student > Master | 2 | 15% |
| Student > Bachelor | 1 | 8% |
| Other | 1 | 8% |
| Other | 0 | 0% |
| Unknown | 2 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 8 | 62% |
| Physics and Astronomy | 2 | 15% |
| Materials Science | 1 | 8% |
| Unknown | 2 | 15% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 August 2017.
All research outputs
#18,567,744
of 22,997,544 outputs
Outputs from Biomedical Microdevices
#613
of 754 outputs
Outputs of similar age
#279,970
of 363,851 outputs
Outputs of similar age from Biomedical Microdevices
#5
of 10 outputs
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So far Altmetric has tracked 754 research outputs from this source. They receive a mean Attention Score of 4.1. This one is in the 11th percentile – i.e., 11% of its peers scored the same or lower than it.
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