Cobalt Metal ALD: Understanding the Mechanism and Role of Zink Alkyl Precursors as Reductants for Low Resistivity Co Thin Films
Bibliographic record
Abstract
In this work, we report a new and promising approach towards the atomic layer deposition (ALD) of metallic Co thin films. Utilizing the simple and known CoCl2(TMEDA) (TMEDA = N,N,N’,N’-tetramethylethylenediamine) precursor in combination with the intramolecularly stabilized Zn aminoalkyl compound Zn(DMP)2 (DMP = dimethylaminopropyl) as auxiliary reducing agent, a thermal ALD process is developed that enables the deposition of Zn free Co thin films. ALD studies demonstrate the saturation behavior of both precursors, linearity in dependency of the applied number of cycles as well as investigations of the temperature dependency of film growth in a regime of 140 - 215 °C. While the process optimization is carried out on Si with native oxide, additional growth studies are conducted on Au and Pt substrates. This study is complemented by initial reactivity and suitability tests of several potential Zn alkyl reducing agents. For the CoCl2(TMEDA) - Zn(DMP)2 combination, these findings allow to propose a series of elemental reaction steps hypothetically leading to pure Co film formation in the ALD process whose feasibility are probed by a set of DFT calculations. The DFT results show that for reactions of the precursors in the gas phase and on Co(111) substrate surfaces, a pathway involving C-C coupling and diamine formation through reductive elimination of an intermediate Co(II) alkyl species is preferred. Co thin films with an average thickness of 10 - 25 nm obtained from the process are subjected to thorough analysis comprising AFM, SEM, RBS/NRA as well as depth profiling XPS. Resistivity measurements for ~ 22 nm thick films grown on a defined SiO2 insulator layer yield highly promising values in a range of 15 - 20 μΩ cm without any after treatment.
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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 | 0.001 |
| 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".