Preferentially Orientated Li-Deficient Li<sub>4</sub>Ti<sub>5</sub>O<sub>12</sub> Nanosheet Anode and Its Excess Charge Storage Properties
Bibliographic record
Abstract
Mesoporous Li deficient Li4Ti5O12 nanosheets with major [110] preferred orientation were prepared by a novel low T (<100 °C) aqueous synthesis process. Surface relaxation due to nanosize effect in the near surface region and 10 % deficiency of lithium were found to lead to local chemical bond length extension that influences the electronic structure and Li storage capacity. Thus the lithiated material over the potential range from 1 to 2.5 V vs. Li/Li+ reaches the following over-stoichiometrical composition: Li7.92Ti5O12. As determined by XANES the excess Li-ion storage is the result of preferential crystal orientation along the (110) and (111), facets. During lithiation, it was further determined the charge compensation to occur primarily by oxygen, rather than by titanium. Finally, both the oxygen and titanium in the near surface region exhibit different electronic structure from bulk. Those results point to the importance of surface reconstruction and relaxation in accommodating excess Li storage. As a consequence, the newly prepared Li4Ti5O12 nanosheets exhibit superior Li-ion storage performance exceeding by far most of the alternatively prepared LTO anode materials.
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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".