High‐Performance Reversible Oxygen Reduction/Evolution Gas Diffusion Electrodes with Multivalent Cation Doped Core‐Shell Mn/Mn<sub>3</sub>O<sub>4</sub> Catalysts
Bibliographic record
Abstract
Abstract The development of precious‐metal‐free catalysts with bifunctional activities for both oxygen reduction and evolution reactions (ORR/OER) is crucial for the advancement of regenerative fuel cells and rechargeable metal−air batteries. Manganese oxides (MnOx) have emerged as promising bifunctional catalysts. However, MnOx electrodes typically exhibit poor ORR/OER cycling stability owing to polarization‐induced MnOx redox reactions and phase transition. To address this issue, we developed metallic cation (i. e., Co2+, Ni2+, Cu2+, or Bi3+) doped MnOx/carbon electrodes using potentiodynamic, potentiostatic and galvanostatic methods. Among the explored dopant cations Ni2+ intercalated into MnOx under acidic conditions using a slow‐scan cyclic voltammetry method, significantly enhanced the ORR/OER activity and stability of MnOx. Alongside electrochemical doping, MnOx also underwent redox reactions leading to changes in Mn valence and phase transitions. The Ni‐incorporated MnOx gas diffusion electrode (GDE) demonstrated exceptional stability for over 120 accelerated OER and ORR cycles at ±10 mA cm−2 in 5 M KOH, surpassing the performance of the Pt/C−IrO2 benchmark. Furthermore, it achieved OER current densities of approximately 22 mA cm−2 at 1.65 VRHE, which was twice as high as that of Pt/C−IrO2.
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 | 0.001 | 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".