Synthesis of Li <sub>4</sub> Ti <sub>5</sub> O <sub>12</sub> negative electrode material in a fluidized bed thermogravimetric analyzer
Bibliographic record
Abstract
Abstract Spinel lithium titanate (Li 4 Ti 5 O 12 ) is the most promising negative electrode material for energy storage which can be applied in lithium‐ion batteries lithium‐sulphur batteries, and supercapacitors. However, the high cost of Li 4 Ti 5 O 12 powder and its high molecular weight limit its application due to the complicated synthesis process. In this work, a facile solid‐state reaction in a fluidized bed reactor was used for the first time to synthesize spinel Li 4 Ti 5 O 12 using lithium carbonate and titanium oxide as solid reactants. We investigated the fluidization behaviour of starting materials and studied different synthesis temperature in fluidized and fixed beds. X‐ray diffraction and scanning electron microscopy were employed to characterize the samples. The results demonstrate that the mixture of Li 2 CO 3 and TiO 2 had a complete fluidization velocity of 0.88 cm/s and showed good fluidization behaviour. Pure spinel Li 4 Ti 5 O 12 was obtained via solid‐state reaction in a fluidized bed reactor at 800°C for 30 minutes, which is much lower than a conventional solid‐state reaction in a fixed bed or muffle furnace. By this novel method, the micro‐sized Li 4 Ti 5 O 12 particles (6‐8 μm) have hollow porous structure composed of nano‐sized particles (<100 nm) synthesized. According to the experimental results, we proposed a different reaction mechanism for the synthesis of Li 4 Ti 5 O 12 in fluidized beds which explains how the Li 2 CO 3 and TiO 2 react to form hollow lithium titanate nano‐structured micro‐particles in fluidized beds. The bulk density, surface area, and bulk conductivity of the synthesized Li 4 Ti 5 O 12 are 3240 kg/m 3 , 4.6 m 2 /g, and 3.90 × 10 −6 S/cm, respectively.
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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 | 0.001 |
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".