Combinatorial Optimization of Metal‐Insulator‐Insulator‐Metal (MIIM) Diodes With Thickness‐Gradient Films via Spatial Atomic Layer Deposition
Bibliographic record
Abstract
Abstract Metal‐insulator‐insulator‐metal (MIIM) diodes with thickness‐gradient films for the insulator layers are fabricated for the first time. Spatially varying atmospheric‐pressure chemical vapor deposition is used to deposit ZnO and Al 2 O 3 films with orthogonal gradient directions, producing 414 MIIM diodes with 414 different ZnO/Al 2 O 3 film‐thickness combinations on a single substrate for combinatorial and high‐throughput optimization. The nm‐scale ZnO/Al 2 O 3 films are printed in only 2 min and the entire device fabrication takes 7 h, which is much less than conventional approaches for investigating many insulator‐thickness combinations. Rapid identification of the optimal thickness combination is demonstrated; high‐performance diodes (asymmetry = 227, nonlinearity = 13.1, and responsivity = 12 A/W) are observed when a trap‐assisted tunneling mechanism is dominant for insulator thicknesses of 3.4–4.4 nm (ZnO) and 7.4 nm (Al 2 O 3 ).
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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) | 0.001 | 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".