A Pore‐Forming Strategy Toward Porous Carbon‐Based Substrates for High Performance Flexible Lithium Metal Full Batteries
Bibliographic record
Abstract
Self‐standing carbon‐based substrates with satisfied structural stability and property adjustability have promising applications in flexible lithium (Li) metal batteries (FLMBs). Current strategies for modifying carbon materials are normally carried out on powder carbon, and very few of them are suitable for self‐standing carbon substrates. Herein, a pore‐forming strategy based on the redox chemistry of metallic oxide nanodots is developed to prepare two porous carbon substrates for anode and cathode. Starting with cotton cloth, the resulting hollow carbon fibers substrate with nanopores effectively prevents from Li dendrites formation and large volume change in lithium metal anode (LMA). Simulations indicate that the porous structure leads to homogeneous ion flux, Li‐ion concentration, and electric field during Li deposition. Li symmetrical cell based on this substrate remains stable for 8300 h with an ultralow voltage hysteresis of 9 mV. Via a similar route, porous carbon cloth substrate is obtained for subsequently seeding V 2 O 5 nanowires to prepare the cathode. The assembled FLMBs pouch cell delivers a capacity of 8.2 mAh with a high capacity retention of ~100% even under dramatic deformation. The demonstrated strategy has far‐reaching potential in preparing free‐standing porous carbon‐based materials for flexible energy storage devices.
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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) | 0.001 | 0.001 |
| 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) | 0.005 | 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".