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Record W2000567133 · doi:10.1039/b617079j

Suppression of aqueous surface hydrolysis by monolayers of short chain organic amphiphiles

2007· article· en· W2000567133 on OpenAlexafffund
Daniel Clifford, Thorsten Bartels‐Rausch, D. J. Donaldson

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSpectroscopy and Quantum Chemical Studies
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMonolayerChemistryNitric acidAqueous solutionStearic acidAmmoniaHydrolysisOrganic acidOctanolLauric acidInorganic chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Aqueous aerosols and other water surfaces in the environment may be coated with organic films, which can give rise to significant effects on gas-solution transport and surface reactivity. We have used acridine as a molecular fluorescent pH probe to examine the hydration of nitric acid and ammonia at both the uncoated and the organic-coated air-water interface. For uncoated samples, a transient decrease in pH is observed at the interface upon introduction of nitric acid vapour, followed by a relaxation to a final pH which is lower than the initial value. This long-time final change in pH is also measured in bulk pH measurements. Solutions having monolayer and sub-monolayer films of 1-octanol do not display the transient, but do show the same long-time change in pH. The degree of suppression of the surface pH transient depends directly on the amount of octanol present at the surface. Hydrolysis of ammonia at the water surface is also indicated by a surface pH transient which is also suppressed when a monolayer of octanol is present at the surface. Monolayers of butanol and of uncompressed stearic acid at the surface show little difference from the clean interface. The results are related to the concentration of available water at the interface.

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 categoriesMeta-epidemiology (narrow)
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 score0.006
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.007
GPT teacher head0.245
Teacher spread0.238 · 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

Citations44
Published2007
Admission routes2
Has abstractyes

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