Scientific Research

High Speed Atmospheric Pressure Plasma Enhanced Spatial ALD of Silicon Nitride

Silicon nitride (Si3N4) is an essential material in semiconductor manufacturing. Atomic layer deposition (ALD) is a technique that allows precise control of film thickness and quality. Plasma-enhanced ALD (PE-ALD) further enhances the process by reducing the required temperature and improving layer properties. However, traditional PE-ALD processes for silicon nitride are relatively slow. To address this limitation, Jie Shen, Fred Roozeboom, and Alfredo Mameli have explored spatial ALD, which separates precursors and co-reactants in space rather than time [animated video]. This approach can significantly increase deposition rates.

In their research, Jie and his colleagues successfully demonstrated atmospheric-pressure plasma-enhanced spatial ALD (AP-PE-SALD) of silicon nitride at low temperatures (≤ 250 °C). They used a bis(diethylamino)silane (BDEAS)  as silicon precursor and a nitrogen plasma as reactant. 

This is a video of the atmospheric pressure plasma enhanced spatial ALD system, as used by the team (Shen, Roozeboom & Mameli) at the Holst Centre, Netherlands to achieve high throughput silicon nitride deposition.

Key Findings:

The researchers discovered that by decreasing the exposure time of the nitrogen plasma and the overall cycle time, they could reduce the oxygen content in the silicon nitride film. They achieved the lowest oxygen content of 4.7 atomic percent while maintaining a deposition temperature of 200 °C. They also achieved deposition rates of up to 1.5 nanometers per minute, approaching those of plasma-enhanced chemical vapor deposition, a widely used technique for high-throughput film deposition. By optimizing the process parameters, they achieved impressive results with respect to oxygen content reduction, deposition rates, and high-quality film formation. As measured by depth profile X-ray photoelectron spectroscopy,  13.7 at.% carbon was present at a deposition temperature of 200 °C. 

High Speed Atmospheric Pressure Plasma Enhanced Spatial ALD (PE-SALD) of Si3N4

Figure 1. Schematic views of (a) the 150-mm wafer lab-scale reactor and (b) the bottom-side of the spatial ALD injector head. The substrate is rotated below the precusor and plasma heads to deposit SiNx. The N2 bearing gas streams are controlled in such a way that the substrate is coated at close proximity. Recently published in the ALD Journal, by Shen, Roozeboom & Mameli. 

Implications:

This breakthrough in atmospheric-pressure plasma-enhanced spatial ALD opens up new possibilities for high-throughput and low-temperature deposition of SiNx. The improved deposition rates make it suitable for mass production. The ability to uniformly coat large areas and, in principle also, 3D structures with silicon nitride films has significant implications for various applications in microelectronics, optoelectronics, and device fabrication.

Whilst carbon contamination still remains a concern for the current process, the authors foresee that different precursor chemistries will lead to improved film composition and that especially N2 purifiers will allow for obtaining SiNx compositions that are less dependent on plasma exposure. Such independency will probably be a prerequisite prior to testing the atmospheric-pressure spatial ALD process on high-aspect ratio structures. 

Since carbon incorporation within the bulk of the SiNx films originates either from incomplete removal of the precursor’s ligands or from redeposition effects, one can expect that atmospheric-pressure spatial ALD using precursors with better exchangeable ligand groups such as BTBAS, or carbon-free precursors such as trisilylamine or neopentasilane will result in much lower carbon contaminations thus further improving the SiNx quality. Alternatively, a dual-plasma approach with an H2/N2 plasma exposure followed by an N2 plasma can be developed in order to drive out even more carbon.

This research expands the toolbox of advanced ALD, bringing us closer to achieving high speed atomic layer processing.

You can read the paper here:

 

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