Recovery and separation of phosphorus as dicalcium phosphate dihydrate for fertilizer and livestock feed additive production from a low-grade phosphate ore
Bibliographic record
Abstract
With the rapid increase in the world population, the global demand for food production has been increasing steeply. This increase has resulted in an increased demand for phosphorus crop fertilizers and livestock feed additives. Considering recent predictions that the global reserves of high-grade phosphorus resources would deplete within 15 years, new initiatives have begun to utilize low-grade resources to ensure sustainable supply of this essential nutrient. The main challenge with the use of low-grade resources is the difficulty with the efficient and economical separation of phosphorus from the other constituent elements, such as iron, aluminum, and magnesium. Most previous studies on the adoption of low-grade phosphate ores have focussed on ore beneficiation processes which are expensive, complex, and in some cases inefficient. In this study, we develop an integrated process for the direct recovery and separation of dicalcium phosphate dihydrate for fertilizer and livestock feed additive production from a low-grade (2.0 wt% P) iron-rich (19.7 wt% Fe) phosphate ore. The process combines leaching using dilute sulfuric acid (0.29 M) and selective precipitation using calcium oxide. During selective precipitation, ethylenediaminetetraacetic acid (EDTA) is used as a stabilizing agent to prevent iron and phosphorus co-precipitation. This process can be operated as a closed loop, allowing the recovery and recycling of both water and EDTA, while eliminating the production of liquid waste. The developed process achieves around 70% phosphorus recovery as an industrial-grade (19 wt% P) dicalcium phosphate dihydrate product with minimal iron, magnesium, and aluminum contamination, while also producing value-added calcium sulfate dihydrate (gypsum) and iron/magnesium byproducts. This process enables economical and sustainable recovery of phosphorus from low-grade ores, which can address the rising global demand for food production.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".