Indium oxides by reactive ion beam assisted evaporation: From material study to device application
Bibliographic record
Abstract
Indium oxides were deposited by reactive ion beam assisted e-beam evaporation at room temperature. A material study was conducted through a variety of material characterization including crystal structure, electrical properties, optical properties, and chemical composition, along with an investigation of material properties as a function of primary deposition parameters such as ion flux and deposition rate. Implementing the developed semiconducting indium oxide as a channel material, the authors further demonstrated high-performance indium oxide thin-film transistors (TFTs) with conventional silicon dioxide gate dielectric derived by plasma-enhanced chemical vapor deposition (PECVD). The n-channel TFT has a threshold voltage of ∼2.0 V, a field-effect mobility of 33 cm2/V s at a gate bias of 20 V, an ON/OFF current ratio of 108, and a subthreshold slope of 2.0 V/decade. The stability study displays a small threshold voltage shift of ∼0.6 V under a 60 h constant current stress condition. The TFT reported here has one of the best performance characteristics in terms of field-effect mobility, ON/OFF current ratio, OFF current and device stability, using conventional and large-area foundry-compatible PECVD gate dielectrics. The device performance coupled with PECVD dielectrics makes ion beam assisted e-beam evaporation derived indium oxide TFT a promising candidate for active matrix flat-panel displays.
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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".