Imaging

Award winning, high resolution imaging tools help you to understand ultrastructure of biological and inorganic specimens.

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Overview: 

There are a number of options and technologies available for digital imaging in transmission electron microscopy (TEM) applications today. Traditionally, high energy electrons could not be directly exposed to a sensor without excessively damaging the detector. As a consequence, conventional TEM cameras first expose the incoming electron beam to a scintillating film that converts the electrons into light (photons). These photons are then transferred to the sensor, either through a series of optical lenses or a coupled fiber optic plate. Finally, the light is collected by a sensor where the image is created pixel-by-pixel based on the amount of light detected at each position in the sensor.

Conventional TEM image detection architecture

There are four basic steps in TEM imaging to address incoming electrons:

  1. Convert electrons to signal
  2. Transfer signal
  3. Detect signal with sensor
  4. Electronically transfer signal and read-out to form image

What is different with direct detection?

There are only two steps in TEM imaging with direct detection:

  1. Convert electrons to signal – not applicable
  2. Transfer signal – not applicable
  3. Detect signal with sensor
  4. Electronically transfer signal and read-out to form image

One key difference between conventional and direct detection is a custom CMOS sensor that utilizes the only radiation hard architecture that can tolerate direct exposure to high energy particles. To add, extremely high speed electronics for data transfer and processing enable low-dose counting and super-resolution capabilities. Combined, this allows frame rates (4k x 4k) of 400 frames per second (fps) to be processed in real-time to achieve optimal results.

Convert electrons to signal          Transfer signal          Detect signal with sensor          Transfer signal and read-out image

Step 1) Convert electrons to signal

Gatan uses proprietary phosphor scintillators to optimize signal conversion that enhances detector sensitivity (SENS) and resolution. When you select a scintillator, it is appropriate to know the performance trade-offs between SENS and resolution.

  • Sensitivity (signal): Ideal for dose-sensitive use cases where you need to generate more photons per incoming electron (e.g., cryo-tomography, beam sensitive materials)
  • Resolution (spatial detail): Favorable for applications where you require more information to resolve details, but you can increase the dose (signal) without harming the sample (e.g., semiconductors and other less-sensitive materials)

Step 2) Transfer signal

Various coupling (lens- and fiber-coupled) mechanisms are available to optimize signal transfer and meet cost or performance targets for a given detector.

Lens-coupled: Lens optics transmit light to the sensor where it is converted into sensor electrons (signal)

  • Pros: (Gatan) Uses real transmission scintillator; can be less expensive than higher performance fibers
  • Cons: Light (information) loss with lensing, angular dependencies (<10% efficient); vignetting (light fall-off); image distortion for higher magnification

Fiber-coupled: Scintillator creates photons that subsequently create sensor electrons; fiber directly transmits light to sensor with high efficiency

  • Pros: Most efficient transmission of light information to the sensor (1:1 coupling of scintillator:sensor (>50% efficient) with no image distortion); can trade-off SENS verses resolution (fiber configuration detail)
  • Cons: Fiber optics are slightly higher cost; requires process optimization including cladding, sintering, bonding of fibers (Gatan proprietary)

Step 3) Detect signal with sensor

Sensor type (CCD vs. CMOS) offers significant trade-offs for TEM camera performance as there are fundamental differences in architecture.

  • Charge-coupled device (CCD): Charge transfers between neighboring cells, and read-out (e.g., noise) is seen at final stage; binning minimizes the impact of read-out noise
  • Complementary metal–oxide–semiconductor (CMOS): Charge immediately converts to voltage (read-out with digital output); supports high frame rates, low overall electronics noise

Both technologies possess inherent advantages, so the question arises about what unique performance characteristics arise from each choice. CCDs can have 100% fill factor that captures all incoming light, whereas part of the CMOS sensor is occupied by transistors and metal wiring associated with each pixel.  Historically, CCDs provided higher quality images with low noise, at affordable prices. Recent design advancements and processing techniques now advance CMOS sensor performance so it is a viable choice for some applications. Note that CCDs still maintain an advantage for binning in terms of signal-to-noise. However, CMOS chips can scale the number of read-out ports and achieve very high frame rates.

Step 4) Transfer signal and read-out image

When a charge converts to voltage, you typically generate noise

  • CCD: Transfer data out of serial register
  • CMOS: Converts to voltage per pixel

It is very important to optimize read-out noise (higher voltages) and speed (multi-port and fast read times) for CCDs.

  • Optimize controller for low read-noise; leverage multi-port read-outs for faster speed
  • Interline CCDs with binning have the fastest readouts (fps) – up to 30 fps due to 100% duty cycle

CMOS typically is seen as a fast sensor because you can run in rolling shutter mode verses the slow global shutter mode.

 

Research Spotlight

Nanomaterials, Mechanics and MEMS Laboratory

The team at the Nanomaterials, Mechanics, and MEMS Laboratory is focused on the synthesis and characterization of...

Diamond Light Source - eBIC for Industry

eBIC for Industry is a recently inaugurated center offering professional cryo-EM services to the global pharmaceutical and biotech industry.

Resources:

 

Nyquist frequency
Dose fractionation and motion correction
Improving DQE with counting and super-resolution

Application notes and Experiment briefs

Imaging 2D materials at low kV with Metro

Acquiring counted 4D STEM with the Metro camera

Extensible real-time data processing with Python in DigitalMicrograph

 In-situ lattice-resolution imaging of hydrogen absorption into nanoparticles

Imaging carbon nanoparticle agglomeration on MoS2 at a low dose rate

Imaging a lithium metal battery solid electrolyte interphase

 

Capturing nanoparticle transformation dynamics

Imaging of graphene at 200 kV using electron counting

Recording atomic-scale crystal nucleation and growth dynamics.

Imaging discrete ions at a liquid-solid interface using low-dose cryo-EM and electron counting

Electric field mapping in 2D heterostructures using differential phase contrast

Magnetite nanoparticle orientation mapping from a 4D STEM dataset

Dynamic in-situ lithiation of NiS-filled carbon nanotubes

Electron counting 4D STEM studies of human tooth enamel

Grain boundary structure of two-dimensional tellurium revealed by 4D STEM

Magnetite nanoparticle orientation mapping from a single low-dose transmission electron microscope image

Virtual (BF/DF) imaging reveals the position and concentration of precipitates in a Ni-W alloy

K3 IS: Low dose EM meets catalysis

High-speed 4D STEM diffraction analysis of directionally-grown ZnO nanowires: Benefits of a high-speed camera

Torsional deformation in subnanometer MoS interconnecting wires

 
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