In Situ pH Measurements of Individual Levitated Microdroplets Using Aerosol Optical Tweezers
Bibliographic record
Abstract
The pH of microscale reaction environments controls numerous physicochemical processes, requiring a real-time pH microprobe. We present highly accurate real-time pH measurements of microdroplets using aerosol optical tweezers (AOT) and analysis of the whispering gallery modes (WGMs) contained in the cavity-enhanced Raman spectra. Uncertainties ranging from ±0.03 to 0.06 in pH for picoliter droplets are obtained through averaging Raman frames acquired at 0.5 Hz over 3.3 min. The high accuracy in pH determination is achieved by combining two independent measurements uniquely provided by the AOT approach: the anion concentration ratio from the spontaneous Raman spectra, and the total solute concentration from the refractive index retrieved from WGM analysis of the stimulated cavity-enhanced Raman spectra. pH can be determined over a range of -0.36 to 0.76 using the aqueous sodium bisulfate system. This technique enables direct measurements of pH-dependent chemical and physical changes experienced by individual microparticles and exploration of the role of pH in the chemical behavior of confined microenvironments.
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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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".