Investigating Metal–Tributyl Phosphate Complexes during Supercritical Fluid Extraction of the NdFeB Magnet Using Density Functional Theory and X-ray Absorption Spectroscopy
Bibliographic record
Abstract
Supercritical fluid extraction (SCFE) is gaining significant interest as a green technology for the recycling of end-of-life waste electrical and electronic equipment (WEEE). Neodymium iron boron (NdFeB) magnets, which contain large quantities of critical rare-earth elements such as neodymium, praseodymium, and dysprosium, are widely used in wind turbines and electric/hybrid vehicles. Hence, they are considered a promising secondary resource for these elements when they reach their end-of-life. Previously, the SCFE process was developed for recycling WEEE, including NdFeB; however, the process mechanism remains unexplored. Here, density functional theory, followed by extended X-ray absorption fine structure and X-ray absorption near-edge structure analyses, are utilized to determine the structural coordination and interatomic interactions of complexes formed during the SCFE of the NdFeB magnet. The results indicate that Fe(II), Fe(III), and Nd(III) form Fe(NO 3 ) 2 (TBP) 2, Fe(NO 3 ) 3 (TBP) 2, and Nd(NO 3 ) 3 (TBP) 3 complexes, respectively. This theory-guided investigation elucidates the complexation chemistry and mechanism during the SCFE process by rigorously determining the structural models.
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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 | 0.000 | 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".