Investigation of the Mechanism of Mg Insertion in Birnessite in Nonaqueous and Aqueous Rechargeable Mg-Ion Batteries
Bibliographic record
Abstract
Magnesium batteries are an energy storage system that potentially offers high energy density, but development of new high voltage cathode materials and understanding of their electrochemical mechanism are critical to realize its benefits. Herein, we synthesize the layered MnO 2 polymorph (the birnessite phase) as a nanostructured phase supported on conductive carbon cloth and compare its electrochemistry and structural changes when it is cycled as a positive electrode material in a Mg-ion battery under nonaqueous or aqueous conditions. X-ray photoelectron spectroscopy and transmission electron microscopy studies show that a conversion mechanism takes place during cycling in a nonaqueous electrolyte, with the formation of MnOOH, MnO, and Mg(OH) 2 upon discharge. In aqueous cells, on the other hand, intercalation of Mg 2+ ions takes place, accompanied by expulsion of interlayer water and transformation to a spinel-like phase as evidenced by X-ray diffraction. Both systems are structurally quasireversible. The sharp contrast in behavior in the two electrolytes points to the important role of the desolvation energy of the Mg 2+ cation in nonaqueous systems.
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".