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Record W1589828252 · doi:10.5772/6946

Nonlinear Phenomena during the Oxidation and Bromination of Pyrocatechol

2010· book-chapter· en· W1589828252 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueNonlinear Dynamics · 2010
Typebook-chapter
Languageen
FieldComputer Science
TopicNonlinear Dynamics and Pattern Formation
Canadian institutionsnot available
FundersJapan Society for the Promotion of ScienceNatural Sciences and Engineering Research Council of Canada
KeywordsNonlinear systemPattern formationBromateBelousov–Zhabotinsky reactionChemistryPhysicsChemical physicsPhysical chemistryInorganic chemistryQuantum mechanicsBromide

Abstract

fetched live from OpenAlex

This chapter reviewed recent studies on the nonlinear dynamics in the bromatepyrocatechol reaction (Harati & Wang, 2008a and 2008b), which showed that spontaneous oscillations could be obtained under broad range of reaction conditions. However, when the concentration of bromate, the oxidant in this chemical oscillator, is fixed, the concentration of pyrocatechol within which the system could exhibit spontaneous oscillations is quite narrow. This accounts for the reason why earlier attempt of finding spontaneous oscillations in the bromate-pyrocatechol system had failed. As illustrated by phase diagrams in the concentration space, it is critical to keep the ratio of bromate/pyrocatechol within a proper range. From the viewpoint of nonlinear dynamics, bromate is a parameter which has a positive impact on the nonlinear feedback loop, where increasing bromate concentration enhances the autocatalytic cycle (i.e. nonlinear feedback). On the other hand, pyrocatechol involves in the production of bromide ions, a reagent which inhibits the autocatalytic process, where an increase of pyrocatechol concentration accelerates the production of bromide ions through reacting with such reagents as bromine molecules. The requirement of having a proper ratio of bromate/pyrocatechol reflects the need of having a balanced interaction between the activation cycle and inhibition process for the onset of oscillatory behaviour in this chemical system. If the above conclusion is rational, one can expect that the role that pyrocatechol reacts with bromine dioxide radicals to accomplish the autocatalytic cycle is less important than its involvement in bromide production in this uncatalyzed bromate oscillator, and therefore when a reagent such as metal catalyst is used to replace pyrocatechol to react with bromine dioxide radicals for completing the autocatalytic cycle, oscillations are still expected to be achievable. This is indeed the case. Experiments have shown spontaneous oscillations when cerium, ferroin or manganese ions were introduced into the bromate-pyrocatechol system. Numerical simulations performed in this research show that the observed oscillatory phenomena could be qualitatively reproduced with a generic model proposed for noncatalyzed bromate oscillators. The simulation further indicates that while either two reaction steps K12 and K13 or K12 and K14 together with ten steps K1 ­ K10 in Scheme I in the OKN mechanism are sufficient to qualitatively reproduce oscillations, three steps K12, K13, and K14 with ten steps K1 ­ K10 are more realistic for representing the chemistry involving the oscillatory reactions, and also for reproducing oscillatory behaviors observed experimentally. The ratio of the rate constants for the equilibrium reaction K13 was a key reference to eliminate reaction step K11 from the original model. Although the present model still needs to be improved to reproduce the experimental results quantitatively, it has

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.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.979
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.206
Teacher spread0.199 · 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