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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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 teacher head, 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".