2‐nm‐Thick Indium Oxide Featuring High Mobility
Bibliographic record
Abstract
Abstract Thin film transistors (TFTs) are key components for the fabrication of electronic and optoelectronic devices, resulting in a push for the wider exploration of semiconducting materials and cost‐effective synthesis processes. In this report, a simple approach is proposed to achieve 2‐nm‐thick indium oxide nanosheets from liquid metal surfaces by employing a squeeze printing technique and thermal annealing at 250 °C in air. The resulting materials exhibit a high degree of transparency (>99 %) and an excellent electron mobility of ≈96 cm 2 V −1 s −1 , surpassing that of pristine printed 2D In 2 O 3 and many other reported 2D semiconductors. UV‐detectors based on annealed 2D In 2 O 3 also benefit from this process step, with the photoresponsivity reaching 5.2 × 10 4 and 9.4 × 10 3 A W −1 at the wavelengths of 285 and 365 nm, respectively. These values are an order of magnitude higher than for as‐synthesized 2D In 2 O 3 . Utilizing transmission electron microscopy with in situ annealing, it is demonstrated that the improvement in device performances is due to nanostructural changes within the oxide layers during annealing process. This work highlights a facile and ambient air compatible method for fabricating high‐quality semiconducting oxides, which will find application in emerging transparent electronics and optoelectronics.
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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".