Evidence map›Paper›PMID 40099714›Full record

ArticleElectrophoresis2025

Comparing Different Light Models for Virtual Electrodes in Optoelectronic Tweezers.

Ernesto Guzman-Saleh, Victor H Perez-Gonzalez, Rodrigo Martinez-Duarte

Abstract readComparative Study
In one paragraph

Article in Electrophoresis, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Ernesto Guzman-SalehSchool of Engineering and Sciences, Tecnologico de Monterrey, Monterrey, Nuevo Leon, Mexico.
Victor H Perez-GonzalezSchool of Engineering and Sciences, Tecnologico de Monterrey, Monterrey, Nuevo Leon, Mexico.
Rodrigo Martinez-DuarteMultiscale Manufacturing Laboratory, Department of Mechanical Engineering, Clemson University, Clemson, South Carolina, USA.

Funding

Consejo Nacional de Humanidades, Ciencia y Tecnología 62382Federico Baur Endowed Chair in Nanotechnology 0020240I03Tecnologico de Monterrey through the Nano-Sensors & Devices Research Group 0020209I06TIGER grant program at Clemson University
6 · The paper itself

Abstract

Optoelectronic tweezers (OET) allow for the physical manipulation of particles of interest via dielectrophoresis (DEP) in microfluidic devices. To produce the nonuniform electric field required to enable DEP, light is used to expose a photoconductive film and create a so-called virtual electrode (VE). Several attempts have been made to model the light profile used to excite the photoconductive layer and produce the VE. However, no comparison of the models has been presented in the literature. Here, we present a comparative study among the rectangular, Gaussian, and saturated-Gaussian models in mapping to light profiles obtained experimentally. These models were then used to predict the activation of a VE and the distribution of the electric field in an OET system. From this comparison, it is possible to conclude that the saturated-Gaussian model should be the preferred choice to study these systems. Moreover, VEs were also compared numerically to conventional gold electrodes used regularly in DEP applications, concluding that very relevant differences exist between the electric fields produced by these two types of electrodes.

Indexed as

ElectrophoresisMicrofluidic Analytical TechniquesModels, TheoreticalOptical TweezersComputer SimulationElectrodesEquipment DesignLightNormal Distributionlight‐induced dielectrophoresisoptically induced dielectrophoresisoptoelectronic tweezersphotoconductivevirtual electrodes

Identifiers

PMID40099714
PMCPMC12514432

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.