Formation of Lithium Titanate Hydrate Nanosheets: Insight into a Two-Dimension Growth Mechanism by in Situ Raman
Bibliographic record
Abstract
Orthorhombic lepidocrocite-type lithium titanate hydrates (LTH), as one important member among two-dimensional (2D) materials, have drawn much attention due to their potential applications in nanoelectronics, energy conversion, and energy storage devices. However, only a few efforts have focused on an anisotropic growth mechanism that determines the formation kinetics of LTH and/or even their derivatives. In this context, in situ Raman observation was employed to the isothermal crystallization of LTH nanosheet crystals from amorphous precursor precipitates. During isothermal crystallization, the formation of monolayered LTH nuclei is controlled by oxygen diffusion with an activation energy of 0.72 eV; anisotropic growth along (010) planes induces an interblocking effect among LTH nanosheet crystals, which limits their size up to 50 nm. The nucleation–growth crystallization kinetics of LTH nanosheets were accurately interpreted by the modified Johnson–Mehl–Avrami–Kolmogorov (JMAK) model, which considered their anisotropic 2D growth. Beyond LTH, the present study that combines in situ spectroscopic monitoring with kinetic modeling paves the way toward deeper comprehension and ultimate control of the growth kinetics of 2D titanate 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 | 0.001 |
| 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".