Effect of the nature of the substrate on the surface chemistry of atomic layer deposition precursors
Bibliographic record
Abstract
The thermal chemistry of Cu(I)-sec-butyl-2-iminopyrrolidinate, a promising copper amidinate complex for atomic layer deposition (ALD) applications, was explored comparatively on several surfaces by using a combination of surface-sensitive techniques, specifically temperature-programmed desorption and x-ray photoelectron spectroscopy (XPS). The substrates explored include single crystals of transition metals (Ni(110) and Cu(110)), thin oxide films (NiO/Ni(110) and SiO2/Ta), and oxygen-treated metals (O/Cu(110)). Decomposition of the pyrrolidinate ligand leads to the desorption of several gas-phase products, including CH3CN, HCN and butene from the metals and CO and CO2 from the oxygen-containing surfaces. In all cases dehydrogenation of the organic moieties is accompanied by hydrogen removal from the surface, in the form of H2 on metals and mainly as water from the metal oxides, but the threshold for this chemistry varies wildly, from 270 K on Ni(110) to 430 K on O/Cu(110), 470 K on Cu(110), 500 K on NiO/Ni(110), and 570 K on SiO2/Ta. Copper reduction is also observed in both the Cu 2p3/2 XPS and the Cu L3 VV Auger (AES) spectra, reaching completion by 300 K on Ni(110) but occurring only between 500 and 600 K on Cu(110). On NiO/Ni(110), both Cu(I) and Cu(0) coexist between 200 and 500 K, and on SiO2/Ta a change happens between 500 and 600 K but the reduction is limited, with the copper atoms retaining a significant ionic character. Additional experiments to test adsorption at higher temperatures led to the identification of temperature windows for the self-limiting precursor uptake required for ALD between approximately 300 and 450 K on both Ni(110) and NiO/Ni(110); the range on SiO2 had been previously determined to be wider, reaching an upper limit at about 500 K. Finally, deposition of copper metal films via ALD cycles with O2 as the co-reactant was successfully accomplished on the Ni(110) substrate.
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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) | 0.000 | 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) | 0.000 | 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".