Etch pit density

The etch pit density (EPD) is a measure for the quality of semiconductor wafers.[1][2]

Etching

An etch solution is applied on the surface of the wafer where the etch rate is increased at dislocations of the crystal resulting in pits. For GaAs one uses typically molten KOH at 450 degrees Celsius for about 40 minutes in a zirconium crucible. The density of the pits can be determined by optical contrast microscopy. Silicon wafers have usually a very low density of < 100 cm⁻² while semi-insulating GaAs wafers have a density on the order of 10⁵ cm⁻².

Germanium detectors

High-purity Germanium detectors require the Ge crystals to be grown with a controlled range of dislocation density to reduce impurities. The etch pitch density requirement is typically within the range 10³ to 10⁴ cm⁻².

Standards

The etch pit density can be determined according to DIN 50454-1 and ASTM F 1404.[3]

References

Zhuang, D.; Edgar, J.H. (2005). "Wet etching of GaN, AlN, and SiC: a review". Materials Science and Engineering: R: Reports. 48 (1): 1–46. doi:10.1016/j.mser.2004.11.002. ISSN 0927-796X.
Klaus Graff (8 March 2013). Metal Impurities in Silicon-Device Fabrication. Springer Science & Business Media. pp. 152–. ISBN 978-3-642-97593-6.
J. Doneker; I. Rechenberg (1 January 1998). Defect Recognition and Image Processing in Semiconductors 1997: Proceedings of the seventh conference on Defect Recognition and Image Processing, Berlin, September 1997. CRC Press. pp. 248–. ISBN 978-0-7503-0500-6.

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[ZhuangEdgar2005-1] Zhuang, D.; Edgar, J.H. (2005). "Wet etching of GaN, AlN, and SiC: a review". Materials Science and Engineering: R: Reports. 48 (1): 1–46. doi:10.1016/j.mser.2004.11.002. ISSN 0927-796X.

[Graff2013-2] Klaus Graff (8 March 2013). Metal Impurities in Silicon-Device Fabrication. Springer Science & Business Media. pp. 152–. ISBN 978-3-642-97593-6.

[DonekerRechenberg1998-3] J. Doneker; I. Rechenberg (1 January 1998). Defect Recognition and Image Processing in Semiconductors 1997: Proceedings of the seventh conference on Defect Recognition and Image Processing, Berlin, September 1997. CRC Press. pp. 248–. ISBN 978-0-7503-0500-6.