Polymeric Materials for Rare Earth Elements Recovery
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Rare earth elements (REEs) play indispensable roles in various advanced technologies, from electronics to renewable energy. However, the heavy global REEs supply and the environmental impact of traditional mining practices have spurred the search for sustainable REEs recovery methods. Polymeric materials have emerged as promising candidates due to their selective adsorption capabilities, versatility, scalability, and regenerability. This paper provides an extensive overview of polymeric materials for REEs recovery, including polymeric resins, polymer membranes, cross-linked polymer networks, and nanocomposite polymers. Each category is examined for its advantages, challenges, and notable developments. Furthermore, we highlight the potential of polymeric materials to contribute to eco-friendly and efficient REEs recovery, while acknowledging the need to address challenges such as selectivity, stability, and scalability. The research in this field actively seeks innovative solutions to reduce reliance on hazardous chemicals and minimize waste generation. As the demand for REEs continues to rise, the development of sustainable REEs recovery technologies remains a critical area of investigation, with the collaboration between researchers and industry experts driving progress in this evolving field.
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.
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) | 0.001 | 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 | 0.001 |
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 it