Implanting CNT Forest onto Carbon Nanosheets as Multifunctional Hosts for High‐Performance Lithium Metal Batteries
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
Abstract Lithium (Li) metal anodes are considered an ideal anode for the next‐generation Li batteries with high energy density. However, some intrinsic problems, such as Li dendrite growth and tremendous volume change, inhibit their practical applications. Here, an unstacked microstructure is tailored by planting an N‐doped carbon nanotube (CNT) forest on the surface of biomass‐derived large‐aspect‐ratio N‐doped carbon sheets (CSs) (CS‐CNT), which can effectively overcome the easy aggregation properties of CSs. As the host material for Li metal anode, the N‐doping and unstacked natures of CS‐CNT offer sufficient Li nucleation sites, large surface area, and space for smooth and uniform Li deposition, effectively preventing the formation of dendritic Li. As a result, the cell with this electrode can keep high and stable Coulombic efficiency of 98.8% for over 2000 h, superior to the pure CSs and Cu foil electrodes. Additionally, the symmetric cell exhibits significantly enhanced cycle life up to 1500 h as well as lowered hysteresis. The present study sheds light on the design of unstacked porous carbon materials and offers an opportunity to develop high efficiency Li metal anode.
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) | 0.000 | 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 it