Modeling study for oscillatory reaction of chlorite – iodide – ethyl acetoacetate
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.
Bibliographic record
Abstract
Chlorine dioxide based chemical oscillating behavior was modeled by a simple scheme consisting of three component reactions. Furthermore, little is known about the influence of the pH value. In this study, four component reactions were used to model the chlorite – iodide – ethyl acetoacetate oscillating reaction by dynamic analysis software. The oscillatory phenomenon is observed for concentration changes of triiodide ion, chlorite ion, and hydrogen ion. The initial concentration of ethyl acetoacetate, chlorite ion, iodide ion, and hydrogen ion has great influence on oscillations. The amplitude and number of oscillations are associated with the initial reactant concentrations. The equation of the reaction rate of triiodide ion, chlorite ion, or hydrogen ion changing with reaction time and initial concentrations in the oscillation stage was obtained. The bifurcation surface between oscillatory and nonoscillatory behavior with different pH values was obtained. The spatial zone for the occurrence of oscillation is reduced with an increase in the pH value. The range of oscillation as concentrations of chlorine dioxide, iodine, and ethyl acetoacetate is well described by an equation. There is a lower limit on ethyl acetoacetate initial concentration for oscillation. However, there is a higher limit on chlorine dioxide and iodine concentration for oscillation. The concentrations of chlorine dioxide and iodine for oscillation decrease with an increase in the pH value. The results provide new theoretical evidence of the importance of pH value, which can affect the bifurcation surface between oscillatory and nonoscillatory behavior.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it