Coefficient d'activité de l'acide sulfurique déterminé par titrage infrarouge
Bibliographic record
Abstract
The titration of sulphuric acid by infrared spectroscopy using the attenuated total reflection (ATR) technique was made in the 0 to 14 pH range for solutions ranging from 1.89 to 0.01 M. The subtraction of the water spectrum was made using acidic, neutral, and basic waters which exhibit different spectra. The results gave the spectra of mixtures of the HSO4 and SO24 ionic species in solutions. For each concentration, factor analysis (FA) sorted the spectra of the pure ionic species and gave through the multiplying factors (MF) the distribution of the species as a function of pH. This distribution is the same as that obtained from the equilibrium equations. The IR measurements gave directly the ratios of the activity coefficients of HSO4 and SO24 ions. This ratio varies with the total concentration of both ions but is independent of the relative concentration. The fitting of the experimental and theoretical volumetric titration curves in the high and low pH regions gave the mean activity coefficients of the other species present in the solutions. The values obtained are comparable to those obtained by electrochemical measurements. These results show that it is possible to use IR spectroscopy to study aqueous solutions of inorganic acids from low to high concentrations.Key words : IR spectroscopy, sulfuric acid, aqueous solutions, factor analysis, ATR, principal spectra, solvation, activity coefficients, IR titration.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".