Rare-earth metal–organic frameworks: from structure to applications
Bibliographic record
Abstract
In the past 30 years, metal-organic frameworks (MOFs) have garnered widespread attention owing to their diverse chemical structures, and tunable properties. As a result, MOFs are of interest for a wide variety of potential applications spanning multiple scientific and engineering disciplines. MOFs have been synthesized using several elements from the periodic table, including those with metal nodes containing s-, p-, d-, and f-block elements. MOFs synthesized with rare-earth (RE) elements, which include scandium, yttrium and the series of fifteen lanthanides are an intriguing family of MOFs from the standpoint of both structure and function. While RE-MOFs can possess many of the same properties common to all MOF families (i.e., permanent porosity, tunable pore size/shape, accessible Lewis acidic sites), they can also display unique structures and properties owing to the high coordination numbers and distinct optical properties of RE-elements. In this review, we present the progress, and highlight several discoveries from research conducted on the topic of RE-MOFs. First, diverse structures of RE-MOFs are presented, divided into classes based on the composition of the RE-metal node being RE(iii)-ions, RE(iii)-chains, or RE(iii)-clusters. Then, several potential applications of RE-MOFs are presented, highlighting examples in the areas of chemical sensing, white light emission, biological imaging, drug delivery, near infrared emission, catalysis, gas adsorption, and chemical separations.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".