Self-Assembled Monolayers of Triazolylidenes on Gold and Mixed Gold/Dielectric Substrates
Bibliographic record
Abstract
N -Heterocyclic carbenes (NHCs) have emerged as valuable ligands for surface chemistry. They can be used to prepare robust self-assembled monolayers (SAMs) for a variety of applications, including as small-molecule inhibitors (SMIs) for metal surfaces in the fabrication of next-generation integrated circuits with angstrom precision. However, little work has been performed to assess the effect of structural and electronic modifications to the basic NHC structure. Herein, we report the design and deposition of a series of 1,2,3-triazolylidene (Tz)-type carbenes on gold (Au) and Au/SiO 2 patterned substrates. Triazolylidenes are an important class of stable carbenes that can be prepared with ease by using click chemistry. In this work, we studied the selective deposition of 1,2,3-triazolium hydrogen carbonate salts. The thermal properties of these precursors were measured and shown to be appropriate for either solution or vapor phase deposition. Tz-SAM stability was studied by time-of-flight secondary-ion mass spectrometry (ToF-SIMS) of Tz SAMs before and after exposure to various conditions, leading to the conclusion that Tz SAMs have thermal stabilities greater than that of NHC SAMs reported to date. Tz SAMs were analyzed by using X-ray and ultraviolet photoelectron spectroscopy (XPS, UPS) and contact angle measurements. High selectivity for deposition on metal regions over dielectric regions on patterned Au/SiO 2 substrates enabled the use of Tzs as an entirely new class of SMIs on preventing ZnO deposition, providing considerable potential utility in microelectronics fabrication methods. Structure–property relationships were studied and provided key insight into the effectiveness of the SAM as a blocking agent.
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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".