Spinel to Rock-Salt Transformation in High Entropy Oxides with Li Incorporation
Bibliographic record
Abstract
High entropy oxides (HEOs) constitute a promising class of materials with possibly new and largely unexplored properties. The virtually infinite variety of compositions (multi-element approach) for a single-phase structure allows the tailoring of their physical properties and enables unprecedented materials design. Nevertheless, this level of versatility renders their characterization as well as the study of specific processes or reaction mechanisms challenging. In the present work, we report the structural and electrochemical behavior of different multi-cationic HEOs. Phase transformation from spinel to rock-salt was observed upon incorporation of monovalent Li+ ions, accompanied by partial oxidation of certain elements in the lattice. This transition was studied by X-ray diffraction, inductively coupled plasma-optical emission spectroscopy, X-ray photoelectron spectroscopy, transmission electron microscopy, and attenuated total reflection infrared spectroscopy. In addition, the redox behavior was probed using cyclic voltammetry. Especially, the lithiated rock-salt structure HEOs were found to exhibit potential for usage as negative and positive electrode materials in rechargeable lithium-ion batteries.
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) | 0.000 | 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".