First-order parallel and consecutive reaction mechanisms — Isosbestic points criterium
Bibliographic record
Abstract
A criterium for the selection of reaction mechanism derived from a condition for isosbestic points occurrence is presented. Analytical relationships involving the molar absorption coefficients of the species, which participate in a mechanism of parallel first-order reactions and the corresponding rate coefficients, are also reported. A model system of four species that present overlapping absorption spectra may correspond to the reactant and products of a system of parallel or consecutive first-order reactions. In the first case, under experimental conditions in which the absorbances are additive, the presence of an isosbestic point in the spectrum of the reaction mixture at a given wavelength leads to a time-independent ratio of the degree of advancement of reaction variables. From this, relevant kinetic information may be extracted, namely, the ratio of the reaction rate coefficients. Moreover, the occurrence of isosbestic points allows discarding the second mechanism. This conclusion is independent of the number of absorbing species. Model calculated examples show the application of the equations here derived. The resolution for the general case of mechanisms of N first-order reactions is provided.Key words: chemical kinetics, time-resolved absorption spectra, reaction mechanism.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".