A Counter Propagating Lens‐Mirror System for Ultrahigh Throughput Single Droplet Detection
Bibliographic record
Abstract
Fluorescence-based detection schemes provide for multiparameter analysis in a broad range of applications in the chemical and biological sciences. Toward the realization of fully portable analysis systems, microfluidic devices integrating diverse functional components have been implemented in a range of out-of-lab environments. That said, there still exits an unmet and recognized need for miniaturized, low-cost, and sensitive optical detection systems, which provide not only for efficient molecular excitation, but also enhanced photon collection capabilities. To this end, an optofluidic platform that is adept at enhancing fluorescence light collection from microfluidic channels is presented. The central component of the detection module is a monolithic parabolic mirror located directly above the microfluidic channel, which acts to enhance the number of emitted photons reflected toward the detector. In addition, two-photon polymerization is used to print a microscale-lens below the microfluidic flow channel and directly opposite the mirror, to enhance the delivery of excitation radiation into the channel. Using such an approach, it is demonstrated that fluorescence signals can be enhanced by over two orders of magnitude, with component parallelization enabling the detection of pL-volume droplets at rates up to 40 000 droplets per second.
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 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".