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Record W2049901699 · doi:10.1115/imece2007-42170

Exploration of the Feasibility of Using Electroosmotic Pumps in Cell Culture

2007· article· en· W2049901699 on OpenAlexaff
Tomasz Glawdel, Carolyn L. Ren

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectrohydrodynamics and Fluid Dynamics
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMicrofluidicsMicropumpElectro-osmosisVolumetric flow rateJoule heatingElectrolysisElectrodeLab-on-a-chipFlow (mathematics)Materials scienceChemistryMechanicsNanotechnologyChromatographyPhysicsElectrolyteComposite material

Abstract

fetched live from OpenAlex

A new continuous perfusion cell culture chip is studied that utilizes electroosmotic pumping to control fluid flow. Electroosmotic flow is not typically used for living cells due to the inherently high electric fields that may harm cells. Problems associated with EOF and cells are solved by incorporating electroosmotic pumps (EO pumps) which generate an induced pressure driven flow in regions with cells. Several advantages of EO pumps include pulse free flow, quick flow control and precise movement of minute volumes of fluid. An ion exchange system consisting of photopolymerized salt bridges are used to separate the media from the electrode reservoirs. However, the high salt concentration in cell culture medium creates significant problems for EO pumps such as decreased flow rate due to low zeta potential, increased electrolysis due to high current draw, significant joule heating, bubble formation and polarization. Attempts to solve these problems with the proposed microfluidic chip are discussed. The pumps are characterized to determine the flow rate for applied currents. Preliminary results with rainbow trout gill cells show that pump can be operated for 5hrs without harming the cells. The work presented here discusses the design and development of the system to this point.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.664
Threshold uncertainty score0.198

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.240
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2007
Admission routes1
Has abstractyes

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