Bioinspired Synthesis of Hierarchical Porous Graphitic Carbon Spheres with Outstanding High-Rate Performance in Lithium-Ion Batteries
Bibliographic record
Abstract
Inspired by the biomineralization of unicellular diatoms, a biomimetic approach based on template (pluronic F127 micelle cluster)-induced self-assembly of α-cyclodextrin is developed to create hierarchical porous graphitic carbon spheres via hydrothermal treatment followed by pyrolysis. The as-obtained carbon spheres combine the features required for high-power electrode materials in lithium-ion batteries (LIBs), such as high degree of graphitization, large surface area with hierarchically distributed pore sizes as well as doping with heteroatoms, which synergistically contribute to their impressive electrochemical properties. When applied as an anode for LIBs, the carbon spheres exhibit high reversible capacity (ca. 700 mA h g –1 at 50 mA g –1 ), good cycling stability, and remarkably outstanding high-rate performance (ca. 600, 450, and 290 mA h g –1 obtained at a current density of 1, 10, and 30 A g –1, respectively), which is among the best of present pure carbon materials for LIBs applications. The fabrication process is straightforward and cost-effective, providing a new methodology for the tailored design of carbon materials with enhanced power densities for energy storage applications.
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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 | 0.000 | 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 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".