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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 OpenAlexfundno aff
Takashi Amemiya, Jichang Wang

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2010
Admission routes1
Has abstractyes

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