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 (Mn x Co 1− x CO 3 /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 Mn x Co 1− x CO 3 /RGO composites exhibit enhanced electrochemical performance compared with the reference CoCO 3 /RGO and MnCO 3 /RGO. Specifically, the Mn 0.7 Co 0.3 CO 3 /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 Mn x Co 1− x CO 3 /RGO provides a design principle and encourages more research on TMCs‐based electrodes.
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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 | 0.001 |
| 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 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".