June 27, 2023 – Thermo Fisher Scientific has introduced the Thermo Scientific™ Metrios™ 6 Scanning Transmission Electron Microscope ((S)TEM) — a new-generation, fully automated (S)TEM metrology solution designed to help enhance productivity and deliver data quality assurance for high-volume semiconductor manufacturing.
The Metrios 6 (S)TEM enables fully automated TEM metrology and characterization workflows with up to 20% in average productivity improvement compared to the previous generation of the Thermo Scientific Metrios (S)TEM.
The more complex the semiconductor device 3D architecture, the more exact the in-depth metrology and characterization processes must be. As a proven leader in high-impact innovation, Thermo Fisher sees firsthand that the atomic-scale 3D intricacies in today’s devices are driving a need for a highly automated (S)TEM platform to enable faster access to large-volume, high-quality data and help accelerate learning cycles.
Built to increase productivity and accelerate data acquisition—therefore facilitating yield improvements and reducing time-to-market—the Metrios 6 (S)TEM incorporates industry-leading hardware and machine-learning algorithms to obtain large-volume high-quality data from complex devices and novel materials rapidly.
New features and capabilities compared to previous Metrios generations include:
- Smart Stage fully automated sample insertion and retraction mechanism eliminates manual operation and potential for human errors, enabling customers to perform high-resolution imaging at a faster pace.
- New Thermo Scientific Ultra-X EDS detection system offers fast compositional characterization and elemental mapping to ease challenging analysis on the most beam-sensitive materials and enable at least two times faster data collection.
- Newly designed objective lens and source innovations enable voltage switching in minutes versus hours, higher-efficiency (S)TEM and EDS acquisition and uncompromised resolution.
- Machine-learning-enabled automation eliminates tedious recipe generation for routine (S)TEM analysis and provides automated workflows with flexibility to generate large volume data without using highly skilled operators.