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 CoCl<sub>2</sub>(TMEDA) (TMEDA = N,N,N’,N’-tetramethylethylenediamine) precursor in combination with the intramolecularly stabilized Zn aminoalkyl compound Zn(DMP)<sub>2</sub> (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 CoCl<sub>2</sub>(TMEDA) - Zn(DMP)<sub>2</sub> 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 SiO<sub>2</sub> 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 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) | 0.000 | 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".