Comparison of the Compliance and Deformation Properties of PDMS and NOA Microfluidic Chips
Bibliographic record
Abstract
Microfluidic devices are often made from polydimethylsiloxane (PDMS) due to its low cost, transparency, and simplicity.However, high-pressure flow through PDMS microfluidic channels leads to an increase in channel size due to the compliance of the material.As a result, longer response times are required to reach steady flow rates, which increases the overall time required to complete experiments when using a syringe pump.Due to its excellent optical properties and increased rigidity, Norland Optical Adhesive (NOA) has been proposed as a promising material candidate for microfluidic fabrication.This study compares the compliance and deformation properties of PDMS and NOA microfluidic chips, including their Young's modulus, roughness, compliance, and chip deformation.The Young modulus for the PDMS and NOA was found using the Instron machine under tensile strength.The surface roughness for both materials was found using the Dektak XT profilometer.The compliance of the microfluidics chips is compared through the measurement of the characteristic time required for channels to achieve an output flow rate equivalent to that of the input flow rate using a syringe pump and the Fluigent S flow meter.The characteristic time of the system is extracted by fitting the data to a model derived originally from the Windkessel model.The chip deformation is found by measuring the channels width under the microscope for the PDMS and NOA chips.With the tensile strength test, the Young modulus is 2 MPa for the PDMS and 1743 MPa for the NOA 63.The surface roughness was found to be higher for the NOA than for the PDMS.Preliminary results show a reduction of time delay of 50% when using NOA chip for large channel.Therefore, the compliance is smaller for the NOA devices than the PDMS devices.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".