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Inductively Coupled Plasma Atomic Emission Spectroscopy: Instrumentation01:26

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Inductively coupled plasma (ICP) is the common plasma source used in atomic emission spectroscopy (AES), a technique that detects and analyzes various elements in a sample. This method is often called inductively coupled plasma atomic emission spectroscopy (ICP-AES).
There are three main types of inductively coupled plasma atomic emission spectroscopy  (ICP-AES) instruments: sequential, simultaneous multichannel, and Fourier transform instruments, with the latter being less commonly used....
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Ultra-wide-field imaging Mueller matrix spectroscopic ellipsometry for semiconductor metrology.

Juntaek Oh1, Jaehyeon Son1, Changhyeong Yoon1

  • 1Advanced Process Development Lab 4, Semiconductor R&D Center, Samsung Electronics Co., Ltd., 1-1 Samsungjeonja-ro, hwaseong-si, Gyeonggi-do, 18848, Republic of Korea.

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We developed a novel ultra-wide-field imaging Mueller matrix spectroscopic ellipsometry system for semiconductor metrology. This advanced system significantly boosts data acquisition and throughput, enabling precise defect detection for enhanced manufacturing yield.

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Area of Science:

  • Optics
  • Materials Science
  • Semiconductor Manufacturing

Background:

  • Semiconductor metrology is crucial for quality control.
  • Existing methods like scanning electron microscopy are time-consuming and provide limited data.
  • There is a need for high-throughput, large-area metrology solutions.

Purpose of the Study:

  • To introduce an ultra-wide-field imaging Mueller matrix spectroscopic ellipsometry (IMMSE) system.
  • To demonstrate its capability for large-area, high-resolution semiconductor metrology.
  • To showcase its potential for yield enhancement in semiconductor manufacturing.

Main Methods:

  • Development of an IMMSE system with a 20mm x 20mm field of view and 6.5µm spatial resolution.
  • Acquisition of over 10 million Mueller matrix spectra.
  • Implementation of a signal correction algorithm for spectrum consistency.
  • Application of machine learning for spatially dense metrology across entire wafers.

Main Results:

  • The IMMSE system achieves the largest field of view reported to date.
  • It provides over 1987 times more metrology data and 662 times higher throughput than conventional methods.
  • Spatially dense metrology across the entire wafer area is achieved.
  • Demonstrated identification of spatial variations in dynamic random access memory (DRAM) structures.

Conclusions:

  • The IMMSE system offers a significant advancement in semiconductor metrology.
  • Its high throughput and data density enable efficient, large-area wafer inspection.
  • This technology has the potential to enhance semiconductor manufacturing yield by enabling early detection of critical structural variations.