Deposition of N-Heterocyclic Carbenes on Reactive Metal Substrates─Applications in Area-Selective Atomic Layer Deposition
Bibliographic record
Abstract
Integrated circuits are presently constructed using top-down strategies composed of multiple etching and lithographic steps. As the feature sizes of these devices approach single-digit nm scales, existing fabrication methods introduce defects which require further corrective steps and are rapidly becoming ineffective for industry needs. To meet future scaling requirements, bottom-up fabrication methods which leverage differences in the local surface environment such as area-selective atomic layer deposition (AS-ALD) are promising but have been limited by the surface-binding energies of adsorbates. N-heterocyclic carbenes (NHCs) have shown excellent bonding to metal surfaces and are presented herein as next-generation carbon-based small molecule inhibitors (SMIs) for use in AS-ALD processes. NHCs demonstrate a preference for adsorbing onto metal surfaces over dielectric materials and enable the selective deposition of ZnO onto SiO 2 bands. NHC-based SMIs can be effectively removed by either thermal annealing at 350 °C or plasma treatment using hydrogen at 800 W for 60 s.
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".