A new perspective of lanthanide metal–organic frameworks: tailoring Dy-BTC nanospheres for rechargeable Li–O<sub>2</sub> batteries
Bibliographic record
Abstract
Nanoscaled lanthanide metal-organic frameworks (NLn-MOFs) have emerged as attractive nanomaterials for photofunctional applications. To enhance the inherent properties and endow NLn-MOF materials with desired electrochemical performance for rechargeable Li-O2 batteries, rational design and synthesis of NLn-MOFs with tailored morphologies for high O2 accessibility and rich open metal sites to bind O2 molecules is highly desired and remains a grand challenge. Herein, we prepare Dy-BTC nanospheres, which are explored for the first time as an O2 cathode in Li-O2 batteries. Interestingly, the specific capacity and electrochemical stability of the Dy-BTC nanosphere-based electrode outperform significantly those of the bulk crystalline Dy-BTC. A full discharge capacity of 7618 mA h g-1 at 50 mA g-1 has been achieved by the Dy-BTC nanospheres. Furthermore, the Dy-BTC nanospheres stably deliver a discharge capacity of 1000 mA h g-1 at 200 mA g-1 for 76 cycles, which is remarkably longer than that of the bulk crystalline Dy-BTC with a cycling life of 26 cycles.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".