EM Flow Creator

In battery research, understanding the morphology of active materials and seperators is crucial for performance and safety.

Automated observation of positive-electrode material for lithium-ion battery.
(a) Outline of observation workflow.
(b) 500x secondary electron image.
(c) 5kx secondary/backscattered electron image.
(d) 35kx secondary/backscattered electron image.

(Instrument: SU8700. Accelerating voltage: 1kV. Detectors: Upper and Middle detectors.)

A common task in semiconductor material analysis is the sequential cross-sectional observation of device patterns.

Automated cross-sectional observation of semiconductor device patterns.
(a) Observation workflow.
(b) Secondary-electron image at 800x magnification.
(c) Secondary-electron image at 250,000x magnification.

(Instrument: SU9000II. Accelerating voltage: 5 kV. Detector: Upper detector.)

Automation is equally transformative in the life sciences, where finding minute biological structures across a large substrate is a common hurdle.

Automated observation of electrode-gap sensor for virus measurement.
(a) Optical microscope image and schematic diagram of electrode gap.
(b) Secondary-electron image at 10,000x magnification.
(c) Secondary-electron image at 300,000x magnification.

(Instrument: SU8600. Accelerating voltage: 3kV. Detector: Upper detector.)