Electrochemical tuning of vertically aligned MoS <sub>2</sub> nanofilms and its application in improving hydrogen evolution reaction
Bibliographic record
Abstract
The ability to intercalate guest species into the van der Waals gap of 2D layered materials affords the opportunity to engineer the electronic structures for a variety of applications. Here we demonstrate the continuous tuning of layer vertically aligned MoS2 nanofilms through electrochemical intercalation of Li(+) ions. By scanning the Li intercalation potential from high to low, we have gained control of multiple important material properties in a continuous manner, including tuning the oxidation state of Mo, the transition of semiconducting 2H to metallic 1T phase, and expanding the van der Waals gap until exfoliation. Using such nanofilms after different degree of Li intercalation, we show the significant improvement of the hydrogen evolution reaction activity. A strong correlation between such tunable material properties and hydrogen evolution reaction activity is established. This work provides an intriguing and effective approach on tuning electronic structures for optimizing the catalytic activity.
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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".