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Surface and Materials Analysis
When integrated circuits fail, failure analysis labs use a variety
of methods to determine the cause. Many types of failures will emit
small amounts of light (electro-luminescence) where the failure is occurring. The
location of the failure can be determined using a low-light, cooled CCD camera
and a microscope. This is known as emission microscopy.
Some failures which can be determined using emission microscopy include leakage
due to saturation, reverse bias junction avalanche and defects in gate oxide.
A typical experiment starts with a brightfield image of the surface of the
device to serve as a road map. A second image is taken with no illumination
to locate the failure site. The two images are then overlaid to indicate the
exact location of the failure site (see example image below). Because
failures often emit only small amounts of light, back-illuminated CCDs combined
with deep cooling provide the high-sensitivity required.
Fig 1: Brightfield and emission images are overlaid to
reveal the failure sites in a semiconductor sites
Solutions from Princeton Instruments
Princeton Instruments provides low-light level detectors with
sensitivity from deep UV (<10nm) to NIR (<1.7µm). Back-illuminated
PIXIS and VersArray cameras are offered with UV-enhanced CCDs for surface
imaging. To probe deeper under the surface using NIR imaging, the new PIXIS:
1024BR deep depletion CCD and 2D-OMA cameras provide extended NIR response
up to 1100nm and 1700nm respectively.
Recommended products include:
PIXIS
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Deep cooling with lifetime vacuum guarantee
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UV-enhanced back-illuminated CCDs
- High resolution (2048 x 2048) and large field of view (27.6 x 27.6mm)
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Back-illuminated, deep depletion detector for negligible
etaloning and high sensitivity in the NIR
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True 16-bit dynamic range to capture both dim and
bright areas in the same image
2D-OMA
V
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InGaAs detector with sensitivity from 0.8 µm to
1.7 µm
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Cooled to -100ºC for low dark current. Ideal for
low-light level NIR fluorescence applications
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Excellent linearity and stability for quantitative imaging
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