Single‐Phase Mixed Transition Metal Carbonate Encapsulated by Graphene: Facile Synthesis and Improved Lithium Storage Properties
Bibliographic record
Abstract
Abstract Transition metal carbonates (TMCs) with complex composition and robust hybrid structure hold great potential as high‐performance electrode materials for lithium‐ion batteries (LIBs). However, poor ionic/electronic conductivities and large volume changes of TMCs during lithiation/delithiation processes have hindered their applications. Herein, single‐phase MnCo mixed carbonate composites encapsulated by reduced graphene oxide (MnxCo1−xCO3/RGO), in which Mn and Co species are distributed randomly in one crystal structure, are successfully synthesized through a facial liquid‐state method. When evaluated as LIB anodes, the MnxCo1−xCO3/RGO composites exhibit enhanced electrochemical performance compared with the reference CoCO3/RGO and MnCO3/RGO. Specifically, the Mn0.7Co0.3CO3/RGO delivers an ultrahigh capacity of 1454 mA h g−1 after 130 cycles at 100 mA g−1 and exhibits an ultralong cycling stability (901 mA h g−1 after 1500 cycles at 2000 mA g−1). This is the best lithium storage performance among carbonate‐based anodes reported up to date. Such superb performance is attributed to the hybrid structure and enhanced electroconductivity due to the integration of Co and Mn into one crystal structure, which is complemented by electrochemical impedance spectroscopy and density functional theory calculations. The facile synthesis, promising electrochemical results, and scientific understanding of the MnxCo1−xCO3/RGO provides a design principle and encourages more research on TMCs‐based electrodes.
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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) | 0.001 | 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".