Evidencing Fast, Massive, and Reversible H<sup>+</sup> Insertion in Nanostructured TiO<sub>2</sub> Electrodes at Neutral pH. Where Do Protons Come From?
Bibliographic record
Abstract
Ongoing developments of sustainable energy technologies based on high-surface-area semiconductive metal oxide electrodes operating under mild and safe aqueous conditions require deep understanding of proton and electron transfer/transport throughout their porous structure. To address this issue, we investigated the electrochemical reductive protonation of high surface area nanostructured amorphous TiO 2 electrodes (produced by glancing angle deposition) in both buffered and unbuffered aqueous solutions. Quantitative analysis of the two charge storage mechanisms was achieved, allowing proper deconvolution of the electrical double-layer capacitive charge storage from the reversible faradaic one resulting from the proton-coupled reduction of bulk TiO 2 . We evidence that this latter process occurs reversibly and extensively (up to an intercalation ratio of 20%) not only under strongly acidic pH conditions but also, more interestingly, under neutral pH with the intercalated proton arising from the buffer rather than water. Moreover, we show that in comparison with reductive Li + intercalation the proton-coupled electron charge storage occurs more rapidly (in a few seconds). This important finding suggests that a high-rate and high-power charge storage device could potentially be achieved with the reversible H + -coupled charge/discharge process in TiO 2 at neutral pH, opening thus new opportunities to the development of eco-friendly batteries for electrical energy storage.
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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".