Yttrium Doped Copper (II) Oxide Hole Transport Material as Efficient Thin Film Transistor
Bibliographic record
Abstract
Abstract This work reports development of yttrium doped copper oxide (Y−CuO) as a new hole transport material with supplemented optoelectronic character. The pure and Y‐doped CuO thin films are developed through a solid‐state method at 200 °C and recognized as high performance p‐channel inorganic thin‐film transistors (TFTs). CuO is formed by oxidative decomposition of copper acetylacetonate, yielding 100 nm thick and conductive (40.9 S cm−1) compact films with a band gap of 2.47 eV and charge carrier density of ∼1.44×1019 cm−3. Yttrium doping generates denser films, Cu2Y2O5 phase in the lattice, with a wide band gap of 2.63 eV. The electrical conductivity increases nine‐fold on 2 % Y addition to CuO, and the carrier density increases to 2.97×1021 cm−3, the highest reported so far. The TFT devices perform remarkably with high field‐effect mobility (μsat) of 3.45 cm2 V−1 s−1 and 5.3 cm2 V−1 s−1, and considerably high current‐on/off ratios of 0.11×104 and 9.21×104, for CuO and Y−CuO films, respectively (at −1 V operating voltage). A very small width hysteresis, 0.01 V for CuO and 1.92 V for 1 % Y−CuO, depict good bias stability. Both the devices work in enhancement mode with stable output characteristics for multiple forward sweeps (5 to −60 V) at −1Vg.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".