Disposable spectrofluidic devices for attenuated total reflection infrared spectroscopy: characterization sensitivity, spatial resolution and generally applicable to multiple device types
Bibliographic record
Abstract
In this paper, we present a generalizable method for the fabrication of disposable spectrofluidic devices for solution characterization by attenuated total reflectance (ATR) Fourier transform infrared (FTIR) spectroscopy. A major design feature is the integration of an ATR element into the device rather than the fabrication of the microchannels on its sensing surface. This alleviates spatial limitations, due to small element footprint and dominance of edge-beading, enabling arbitrarily complex microfluidic circuitry and complex world-to-chip interfaces while leaving the entire ATR element available for sensing. An optimized optical interface maximizes light transfer into the on-chip sensing chamber. This promotes low limits of detection, fast measurements and/or designs featuring multiple sensing sub regions. To demonstrate the approach, we conducted measurements on complex flow profiles generated from four separate proof-of-concept spectrofluidic devices. A high sensitivity device detected glucose and sodium phosphate dibasic(Na2HPO4) at concentrations as low as 3 mM and 1 mM, respectively or and for time-lapse results with second-scale time resolution from single-scan measurements. We also demonstrated spatial selectivity for assays in parallel channels, measurements of concentration gradients in a multi-laminar co-flow device, and monitored fast kinetics of the protonation of a pH buffer in a microfluidic reactor.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".