Optimization and miniaturization of SE-ECL for potential-resolved, multi-color, multi-analyte detection
Bibliographic record
Abstract
Electrochemiluminescence (ECL) is a bioanalytical technique with numerous advantages, including the potential for high temporal and spatial resolution, a high signal-to-noise ratio, a broad dynamic range, and rapid measurement capabilities. To reduce the complexity of a multi-electrode approach, we use a single-electrode electrochemiluminescence (SE-ECL) configuration to achieve the simultaneous emission and detection of multiple colors for applications that require multiplexed detection of several analytes. This method exploits intrinsic differences in the electric potential applied along single electrodes built into electrochemical cells, enabling the achievement of distinct colors through selective excitation of ECL luminophores. We present results on the optimization of SE-ECL intensity for different channel lengths and widths, with sum intensities being 5 times larger for 6 cm vs. 2 cm channels and linearly increasing with the width of the channels. Furthermore, we demonstrated for the first time that applying Alternating Current (AC) voltage within the single electrode setup for driving the ECL reactions has a dramatic effect on the emitted light intensity, with square waveforms resulting in higher intensities vs sine waveforms. Additionally, multiplexed multicolor SE-ECL on a 6.5 mm × 3.6 mm CMOS semiconductor image sensor was demonstrated for the first time, with the ability to simultaneously distinguish four different colors, leading to the ability to measure multiple analytes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".