Critical Investigation of Metal–Organic-Frameworks to Improve the Silicon Anode of Lithium-Ion Batteries
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The poor capacity retention of the silicon (Si) anode has hindered its widespread use in lithium-ion batteries. Metal–organic-frameworks (MOF) may offer the structural and functional tunability needed to alleviate some of the longstanding problems associated with silicon pulverization. Herein, MOF-74 (Co-based) and MOF-199 (Cu-based) were implemented in different design configurations for high-Si loading electrodes. Multilayer sandwich configurations provided a modest improvement in capacity retention. However, greatest improvements in capacity retention were observed when the MOF was in situ synthesized onto the silicon surface (Si@MOF) and subsequently pyrolyzed. The best performing high-loading 0.5Si@MOF-c sample delivered a high capacity of 1000 mAh/g and retained 60% capacity after 100 cycles, surpassing a standard silicon-graphite composite.
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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 | 0.000 |
| 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".