(Invited) Spatial ALD, Deposition of Al<sub>2</sub>O<sub>3</sub> Films at Throughputs Exceeding 3000 Wafers per Hour
Bibliographic record
Abstract
During the last few years various types of ALD films have successfully been introduced in high-volume manufacturing in a number of industries. Particularly in the semiconductor industry the implementation is wide spread (high-k gate stacks, capacitor dielectrics, diffusion barriers, etc.). More recently a specific type of ALD film, Al2O3, was widely researched as a potential surface passivation layer for solar cell surfaces in the PV industry. Thin (< 10nm) Al2O3 films passivate p-type surfaces very effectively. On the one hand intrinsic negative charges in the dielectric film repel charge carriers, while on the other hand hydrogen that is present in the ALD films passivates dangling bonds at the Si/SiO2/ Al2O3 interface. The combination of both effects reduces the charge recombination losses considerably. The overall result is an increase in cell efficiency of 0.5-1% (absolute). Based on extensive testing of these films, it is to be expected that Implementation in PV manufacturing will take place in the near future. There is a large difference in film and process requirements of ALD films applied in the semiconductor and PV industries. Whereas uniformity and defects (particles) are very important in the IC industry this is much less so in PV. Much more important in the PV industry are cost and throughput. Typical numbers for both industries are a Cost of Ownership of 2-10 vs. 0.02-0.05$/wafer, respectively, and 10-50 vs 1500-2500 wfrs/hr.. As ALD processes are notoriously slow, ways must be found to increase the throughputs considerably. This is done by either using batch furnaces loaded with 500-1000 wafers per batch, or in-line systems in which wafers are loaded, processed and unloaded in a continuous flow of 0.5-0.8 wafers/s. The latter type of system is based on the so-called spatial ALD process. An example is shown in the figure. In this system (Levitrack) wafers are loaded in a track in which zones with precursors TMA and H2O are spatially separated by zones of inert gas. While floating on a gas cushion, the wafers pass ALD ‘cells’ with fixed sequences of TMA and water, adding a thin layer of Al2O3 with each passage through a cell. The advantages of this approach are several: high throughput, atmospheric processing, no deposition on the inside walls of the track, no moving parts such as valves, pumps, etc. Typical results obtained with this system are: film uniformity 3-4%, life time of solar cell charge carriers > 3ms, efficiency enhancement 0.4-0.8%, CoO ~ 0.04$/wfr. In the paper more details will be provided on the economy of this type of system, as well as on film characteristics and efficiency enhancements realized in a variety of solar cell structures.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.017 | 0.009 |
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".