Research and Development of Popcorn-Shaped Co<sub>3</sub>O<sub>4</sub>@CoCO<sub>3</sub> Zinc Ion Battery Composite Cathode Material Prepared by Hydrothermal Method
Bibliographic record
Abstract
Co3O4 and CoCO3 materials have broad development prospects as zinc ion battery materials in water systems. In this paper, Co3O4@CoCO3 composite material for water zinc ion battery cathode was synthesized by hydrothermal method, and the best raw material was selected by screening the cobalt source. Then the temperature and time of hydrothermal reaction were optimized, as well as the temperature and time of calcination, so as to discover the best experimental route for the synthesis of Co3O4@CoCO3 composite materials. The capacity of the Co3O4@CoCO3 composite material rises to 124.89[Formula: see text]mAh/g after 10 cycles of charge and discharge at 50[Formula: see text]mA/g current density, indicating its electrochemical performance is good. The XRD analysis of the material shows that the composite is mainly composed of Co3O4@CoCO3 crystal structure, and no obvious impurity is found. As can be seen from the SEM image of synthesized composite material, the main morphology of the material is a round block structure covered with folds, similar to the popcorn shape. The EDS test and element analysis show that all elements are evenly distributed in microscale. Through the analysis of infrared spectra, it can be seen that Co3O4 and CoCO3 are composited together, forming a stable structure, and enhancing the electrochemical performance of the material.
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.
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".