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Stopped-flow electrospray ionization mass spectrometry: a new method for studying chemical reaction kinetics in solution

2000· article· en· W2107542836 on OpenAlexafffund
Beata M. Kolakowski, Douglas A. Simmons, Lars Konermann

Bibliographic record

VenueRapid Communications in Mass Spectrometry · 2000
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryMass spectrometryElectrospray ionizationKineticsAnalytical Chemistry (journal)Chemical kineticsMixing (physics)IonizationChemical reactionIonReaction rate constantElectrosprayChemical ionizationChromatographyOrganic chemistry

Abstract

fetched live from OpenAlex

In this work a new mass spectrometry based method for monitoring the kinetics of chemical reactions in solution is described. A stopped-flow mixing instrument is coupled to an electrospray ionization (ESI) mass spectrometer via a novel type of interface. Chemical reactions are initiated by rapid mixing of two reactant solutions. The mixture is instantaneously transferred to a reaction tube where the kinetics can be monitored in real-time by ESI mass spectrometry. With the current setup, a time window from 2.5 to 36 seconds after mixing of the reactants can be monitored. The experimental setup is used to study the kinetics of acetylcholine hydrolysis under alkaline conditions as a function of pH. The intensities of reactant (acetylcholine) and product (choline) ions are monitored simultaneously as a function of time. The reaction is carried out under pseudo-first-order conditions and the intensity-time curves are well described by single exponentials. The rate constants determined from these fits compare favorably with previous data from the literature.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient 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: Methods · Consensus signal: Methods
Teacher disagreement score0.407
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.028
GPT teacher head0.321
Teacher spread0.293 · 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
GenreMethods

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

Citations45
Published2000
Admission routes2
Has abstractyes

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