Residence Time Effect on Iron Perturbation of Taranakite Formation
Bibliographic record
Abstract
Taranakite is an important reaction product in the immediate vicinity of phosphate fertilizer bands. The residence time effect on taranakite formation at pH 4.0 and on the iron perturbation of its formation at a Fe(II)/Al molar ratio of 1.2 ( and ) was investigated in this study. The crystallization of NH 4 ‐taranakite involved a phase transformation from irregularly shaped x‐ray noncrystalline materials to taranakite. The incorporation of NH + 4 ions into taranakite structure was a relatively slow process. The presence of Fe(II) in the solution of the reaction system perturbed the incorporation of NH + 4 ions into taranakite structure, especially in the early aging period. Furthermore, the coating or coprecipitation of x‐ray noncrystalline iron phosphates with aluminum phosphates appeared to reduce the dissolution of aluminum phosphates, thus, affecting the phase transformation to taranakite. The presence of Fe(II) greatly decreased the rate of taranakite formation and retarded its formation. This is attributed to iron phosphate coatings as impurities on taranakite particles and the subsequent retardation of its crystal growth by interfering the integration of growth units. The impact of the residence time of Fe perturbation of the formation of taranakite in the immediate vicinity of fertilizer zones in soils, especially under reduced conditions, on the transformation and dynamics of P and N in the terrestrial system merits close attention.
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 | 0.000 | 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) | 0.001 | 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".