Self-Supported Single Crystalline H<sub>2</sub>Ti<sub>8</sub>O<sub>17</sub> Nanoarrays as Integrated Three-Dimensional Anodes for Lithium-Ion Microbatteries
Bibliographic record
Abstract
Well-ordered, one-dimensional H2Ti2O5, H2Ti8O17, TiO2-B, and anatase TiO2/TiO2-B nanowire arrays were innovatively designed and directly grown on current collectors as high performance three dimensional (3D) anodes for binder and carbon free lithium ion batteries (LIBs). The prepared thin nanowires exhibited a single crystalline phase with highly uniform morphologies, diameters ranging from 70-80 nm, and lengths of around 15 μm. Specifically, reversible Li insertion and extraction reactions around 1.6-1.8 V with initial intercalation capacities of 326 and 271 mA h g(-1) at a cycling rate of 0.1 C (where 1 C = 335 mA g(-1)) were observed for H2Ti8O17 and TiO2-B nanowire arrays, respectively. Among the four compounds investigated, the H2Ti8O17 nanowire electrode demonstrated optimal cycling stability, delivering a high specific discharge capacity of 157.8 mA h g(-1) with a coulombic efficiency of 100%, even after the 500th cycle at a current rate of 1 C. Furthermore, the H2Ti8O17 nanowire electrode displayed superior rate performance with rechargeable discharge capacities of 127.2, 111.4, 87.2, and 73.5 mA h g(-1) at 5 C, 10 C, 20 C, and 30 C, respectively. These results present the potential opportunity for the development of high-performance LIBs based on nanostructured Ti-based anode materials in terms of high stability and high rate capability.
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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".