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
PIXIS
-
Deep cooling with lifetime vacuum
guarantee
-
UV-enhanced back-illuminated CCDs
- High resolution (2048 x 2048) and large field of
view (27.6 x 27.6mm)
-
Back-illuminated, deep depletion
detector for negligible etaloning and high sensitivity
in the NIR
-
True 16-bit dynamic range to
capture both dim and bright areas in the same
image
2D-OMA
V
-
InGaAs detector with sensitivity
from 0.8 µm to 1.7 µm
-
Cooled to -100ºC for low dark
current. Ideal for low-light level NIR fluorescence
applications
-
Excellent linearity and stability
for quantitative imaging
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