A digital microfluidic chip with programmable open system actuation and enhanced optical annealing with near‐infrared light
Bibliographic record
Abstract
Abstract This work investigates a digital microfluidic chip and presents an advancement to microfluidic optical annealing methods through the application of whispering gallery mode (WGM) with near infrared excitation. Establishing a microfluidic chip with point‐of‐care capabilities, including actuation and annealing, has proven to be important. Unfortunately, poor heat absorption due to the long optical penetration depth of near infrared light creates scaling limitations for applications in optical‐based microfluidics. Through the application of WGM, the interaction length between the droplet and light is increased beyond the droplet diameter to improve heating and optical absorption. This is supported by finite‐difference time‐domain electromagnetic simulations and experimental results showing a greatly improved temperature change. Such a system is implemented in an open system digital microfluidic chip, to facilitate annealing via side illumination of droplets. The open system digital microfluidic chip is programmable for droplet actuation. The fundamental experiment of preprogrammed actuation of microdroplets is demonstrated in a 36 electrode grid. The results of annealing and actuation show potential for implementation in point‐of‐care microfluidic 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 | 0.000 |
| 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 | 0.001 | 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".