Thermal Chemistry of Cu(I)-Iminopyrrolidinate and Cu(I)-Guanidinate Atomic Layer Deposition (ALD) Precursors on Ni(110) Single-Crystal Surfaces
Bibliographic record
Abstract
The thermal chemistry of tetrakis[Cu(I)- N - sec -butyl-iminopyrrolidinate] and bis[Cu(I)- N,N -dimethyl- N ′,N ″-di- iso -propyl-guanidinate], promising precursor for atomic layer deposition (ALD) applications, was investigated on a Ni(110) single-crystal under ultrahigh vacuum (UHV) conditions by using X-ray photoelectron spectroscopy (XPS) and temperature-programmed desorption (TPD). Both precursors, which exist as tetramers and dimers in the solid phase, respectively, undergo dissociative adsorption at temperatures below 200 K to produce adsorbed monomers on the surface. A β-hydride elimination step is then operative near 300 K that leads to the release of some of the ligands in dehydrogenated form. The remaining adsorbates obtained from either precursor undergo similar further decomposition between 350 K and 600 K as the Cu atoms are reduced from a Cu(I) oxidation state to metallic Cu(0). Hydrocarbons resulting from the elimination of the terminal moieties include ethene and acetonitrile from the Cu(I)-iminopyrrolidinate and propene from the Cu(I)-guanidinate, which are ejected at ∼420–490 K, and HCN in both cases at ∼570–580 K. These results shows several similarities with the surface chemistry previously reported for bis[Cu(I)- N,N ′-di- sec -butyl-acetamidinate], and they suggest a common behavior in the surface reactions of these families of Cu(I)-amidinate, Cu(I)-iminopyrrolidinate, and Cu(I)-guanidinate ALD precursors.
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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".