To support the search for new device architectures with novel materials, imec develops analytical capabilities, whether for materials characterization or inline metrology.
Imec’s materials and components analysis and inline metrology expertise centers support imec’s ongoing R&D.
At the same time, they identify the innovative analytical capabilities that will be needed for tomorrow’s CMOS and post-CMOS semiconductor industry. If possible, they already implement them.
All according to our motto: “If you cannot see it, you cannot develop and control it.”
This expertise center supports the development of tomorrow’s process flows for IC fabrication. We provide offline analytical feedback and develop the new characterization techniques that will be required.
The tools and techniques that we have cover the complete state of the art. They include APT, TEM, STEM, SEM, FIB, SPM, Raman PL, XPS, UPS, HAXPES, SIMS, RBS and ERD. This capacity is further supported by synchrotron-based analysis carried out at sites such as DIAMOND, BESSY, Soliel, ...
The Inline Metrology center ensures that the process flows for semiconductor fabrication run as designed.
With the latest EUV lithography roadmap continuously pushing the boundaries of what is possible, we must also continuously develop new capabilities – often also a boost for lab-to-fab initiatives.
Another challenge we continue to work through is the ever-increasing data volume generated by a larger volume of smaller and more complex structures.
With the introduction of EUV patterning, it’s become necessary to better understand sub-picosecond exposure processes. Imec’s AttoLab will be the first industrial laboratory to do so. It will enable the study of EUV photon absorption and ionization processes at unprecedented timescales from attoseconds to picoseconds.
This new understanding will pave the way for the development of new lithographic materials. The AttoLab is jointly developed with KMLabs, a specialist in ultrafast laser and EUV technology.
Eventually, scaling will see the introduction of 2D materials. This will call for a new generation of tools for materials characterization and inline metrology.
Probably the biggest challenge will be to keep costs down while working with more complex structures and providing data faster.
Today, this is primarily supported via highly specialized techniques developed on mutually exclusive and costly platforms. Tomorrow’s solutions will include parallelization: synchronous measurements of potentially thousands of locations across a wafer. In this evolution, machine learning will be critical.
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