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Record W2990181299 · doi:10.1021/acs.analchem.9b04152

In Situ pH Measurements of Individual Levitated Microdroplets Using Aerosol Optical Tweezers

2019· article· en· W2990181299 on OpenAlexaff
Hallie C. Boyer, Kyle Gorkowski, Ryan C. Sullivan

Bibliographic record

VenueAnalytical Chemistry · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsMcGill University
FundersDivision of ChemistryCamille and Henry Dreyfus Foundation
KeywordsChemistryIn situOptical tweezersAerosolTweezersChromatographyNanotechnologyOpticsOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.207
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.036
GPT teacher head0.252
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations75
Published2019
Admission routes1
Has abstractyes

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