Application of the central composite design and response surface methodology to remove arsenic from industrial phosphorus by oxidation
Bibliographic record
Abstract
Abstract Oxidation is applied to remove arsenic from industrial phosphorus, and nitric acid is chosen as the main oxidant and molysite (Fe3+) as the oxidation intensifier to oxidise arsenic selectively prior to oxidise phosphorus. The central composite design (CCD) and response surface methodology (RSM) are applied to this purification process. The factors considered for experimental design are the concentration of nitric acid, stirring rate, the mass ratio of iron to arsenic, and the volume ratio of nitric acid to phosphorus. The significant factors are optimised using a 24 full factorial CCD of orthogonal type. The quadratic models between the responses and the independent parameters are built. The response surface models are tested with analysis of variance (ANOVA) and the optimal conditions are found: 12.5% for the concentration of nitric acid, 80 for the mass ratio of iron to arsenic, 319 rpm for stirring rate, and 3.14 for the volume ratio of nitric acid to phosphorus with the prediction of 99.9996% of the arsenic removal ratio (ARR) and 74.64% of phosphorus yield (PY). The experimental results indicate that oxidation could remove almost all arsenic from industrial phosphorus, which could prepare low arsenic phosphoric products. L'oxydation est utilisée pour éliminer l'arsenic des phosphores industriels. On choisit l'acide nitrique comme oxydant principal et le molysite (Fe3+) comme promoteur d'oxydation afin d'oxyder sélectivement l'arsenic avant d'oxyder le phosphore. Le plan central composite (PCC) et la méthode de surface de réponse (MSP) sont appliqués à ce processus de purification. Les facteurs pris en compte dans le plan expérimental sont la concentration d'acide nitrique, la vitesse d'agitation, le rapport de masse du fer par rapport à l'arsenic et le rapport de volume entre l'acide nitrique et le phosphore. Les facteurs importants sont optimisés grâce à un plan central composite de type orthogonal à 24 facteurs entiers. Les modèles quadratiques sont établis entre les réponses et les paramètres indépendants. Les modèles de surface de réponse ont été évalués grâce à l'analyse de la variance (ANOVA) et les conditions optimales suivantes ont été trouvées: une concentration d'acide nitrique de 12,5%, un rapport de masse du fer par rapport à l'arsenic de 80, une vitesse d'agitation de 319 rotations par minute et un rapport de volume de l'acide nitrique par rapport au phosphore de 3,14 avec un taux d'élimination de l'arsenic (TEA) estimé à 99,9996% et une production de phosphore de 74,64% (PP). Les résultats expérimentaux indiquent que l'oxydation peut éliminer presque tout l'arsenic contenu dans les phosphores industriels, ce qui permettrait d'obtenir des produits phosphoriques pauvres en arsenic. © 2010 Canadian Society for Chemical Engineering
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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 | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".