Applied Materials : Applied Materials' Next-Generation Defect Review and Classification Technology Improves Yield for Complex 3D

   Applied Materials : Applied Materials' Next-Generation Defect Review and
   Classification Technology Improves Yield for Complex 3D Transistors, 1X
                               Nanometer Nodes

  *SEMVision G6 system's unique multi-dimensional imaging delivers the
    industry's highest resolution and image quality
  *Advanced system design and full automation capabilities enable up to 100%
    faster throughput
  *Purity ADC dynamic machine learning algorithms deliver exceptional defect
    capture rate, classification accuracy and throughput

SANTA CLARA, Calif., July 8, 2013 - Applied Materials, Inc. today announced a
suite of new defect review and classification technologies for its
market-leading SEMVision^(TM) family of products to accelerate time to yield
for leading-edge chip manufacturing at 1X-nm and beyond. The Applied
SEMVision G6 defect analysis system combines unprecedented high-resolution,
multi-dimensional imaging capabilities with revolutionary machine learning
intelligence of the Purity^(TM) Automatic Defect Classification (ADC) system
that sets new performance benchmarks and brings first-of-a-kind DR SEM
technology to the semiconductor industry.

"The capabilities of current defect review and analysis tools are being
challenged by the requirements of emerging 1X nm design rules and 3D
architectures," said Itai Rosenfeld, corporate vice president and general
manager of Applied's Process Diagnostics and Control business unit. "Our
SEMVision G6 and Purity ADC solve the industry's toughest process control
problems for defect review with unmatched imaging technologies and a powerful
analysis tool for fast and accurate classification. Multiple market-leading
customers have already installed SEMVision G6 and Purity ADC systems and are
benefiting from up to 100% faster throughput, advanced imaging and
best-in-class classification quality for improved yields."

The SEMVision G6 system's resolution is a 30% improvement over the previous
generation, making it the highest available in the industry. This capability
and the system's unique e-beam tilt angle make the G6 the industry's superior,
field-proven DR SEM for finding, identifying and analyzing defects in 3D
FinFET and high aspect ratio structures at 1Xnm nodes. The system's advanced
detection assembly and sophisticated processing make possible high-quality
topographical images of tiny and shallow defects. High dynamic range
detection, collection of back-scattered electrons, and energy filtering enable
high aspect ratio imaging. High-energy imaging makes possible "see through"
penetration that reveals defects in underlying layers.

The Purity ADC's dynamic machine learning algorithms analyze and classify
defects, ensuring accuracy, quality and consistency to enable stable process
control and rapid and reliable excursion detection. Smart machine learning
algorithms also make possible the separation of real defects from the large
number of nuisance defects or false alarms, a challenge that is growing with
scaling and device complexity. By establishing a proven intelligent analysis
and classification process, Purity ADC gives customers the confidence for the
first time to rely on an automatic review system to correctly and quickly
identify classes of defects in a production environment and accelerate
time-to-yield. 

Applied Materials, Inc. (Nasdaq:AMAT) is the global leader in providing
innovative equipment, services and software to enable the manufacture of
advanced semiconductor, flat panel display and solar photovoltaic products.
Our technologies help make innovations like smartphones, flat screen TVs and
solar panels more affordable and accessible to consumers and businesses around
the world. Learn more at www.appliedmaterials.com.

                                    # # #

Contact:

Ricky Gradwohl (editorial/media) 408.235.4676

Michael Sullivan (financial community) 408.986.7977

PHOTO: The Applied Materials' SEMVision™ G6 defect analysis system

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Source: Applied Materials via Thomson Reuters ONE
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