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

Conventional TEM image detection architectureThere 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:

What is different 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 signalLens-coupled: Lens optics transmit light to the sensor, where it is converted into sensor electrons (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 the sensor with high efficiencyFiber-coupled: Scintillator creates photons that subsequently create sensor electrons; fiber directly transmits light to the 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, and bonding of fibers (Gatan proprietary)

Renal sample at 3000x magnification. Fiber-coupled (left) vs. lens-coupled (right).

Step 3) Detect the signal with the 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 the 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 a 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.

CCD vs. CMOS

Step 4) Transfer signal and read-out image

When a charge converts to voltage, you typically generate noise

  • CCD: Transfer data out of the 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.

Resources:

 

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

Application notes and Experiment briefs

High-resolution image of water ice, showing atomic level detail

Atomic resolution imaging of hexagonal water ice

Ptychographic phase image of Stronium Titrate

K3 IS camera for electron ptychography: Mapping oxygen in SrTiO3

FIB-cut semiconductor sample imaged at 4k x 4k resolution, utilizing Frame Control feature of ClearView

Frame Control mode for optimized imaging and diffraction with ClearView camera

Low-dose diffraction patterns from a zeolite sample captured using the OneView

Capturing high-quality electron-counted diffraction at low dose with the Metro camera

SAED pattern of 2D-PI-BPDA and HRTEM image of the same specimen area

Imaging extremely beam-sensitive materials with Metro

MicroED projection on ZSM-5 with the K3

Acquiring counted electron diffraction data without a beam stop with Gatan electron counting direct detectors

Single frame from a continuous diffraction tomography dataset showcasing higher order reflections with resolutions exceeding 1 Å

Enhancing MicroED/3DED analysis with direct detection electron counting cameras

A frame from an in-situ video dataset with its corresponding FFT, showing clear visibility of lattice fringes

Monitoring and quantification of beam damage via low-dose continuous imaging

Image of Molybdenum disulfide captured with the Metro camera using live drift correction and a frame showing small region at the center of the FFT showing two full sets of spacings that are clearly resolved.

Imaging 2D materials at low kV with Metro

 Map of boron nitride from a counted 4D STEM dataset collected with the Metro camera.

Acquiring counted 4D STEM with the Metro camera

High-speed in-situ observation of the annealing of Platinum islands into branched Ruthenium nanostructures

 In-situ observation of the annealing of Pt islands into branched Ru nanostructures to make single-atom catalysts

CBED patterns of FEC-1 and FEC-2 NaCu5S3

Electron diffraction for chirality identification in spintronics

Sn (Tin) nanoparticle melting and crystallizing as the temperature oscillated

Extensible real-time data processing with Python in DigitalMicrograph

Fourier filtered overlays showing the α (purple) and β (red) phases as the hydrogenation takes place

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

Frames showing slow copper dendrite growth

Observing beam-induced dendritic growth over two different timescales

Low-dose in-situ video showing formation of carbon nanoparticles during heating

Imaging carbon nanoparticle agglomeration on MoS2 at a low dose rate

Cryo-TEM image of Li metal filament with SEI

Imaging a lithium metal battery solid electrolyte interphase

Low magnification, low-dose, TEM images of one Molybdenum disulfide grain boundary region before and after biasing to 1 V potential

Electric field-induced structural dynamics in MoS2 observed using in-situ transmission electron microscopy

Graphene imaged at 200 kV

Imaging of graphene at 200 kV using electron counting

Imaging ions at a liquid-solid interface

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

Schematic of MoS2/hBN sample analyzed

Electric field mapping in 2D heterostructures using differential phase contrast

Maximum diffraction pattern of Magnetite nanoparticles

Magnetite nanoparticle orientation mapping from a 4D STEM dataset

Lithiation progressed under -6 V of potential, where the Li-ions traveled down the inner wall of the CNT and alloyed with the NiS

Dynamic in-situ lithiation of NiS-filled carbon nanotubes

Cryo-STEM image displaying part of an enamel crystallite

Electron counting 4D STEM studies of human tooth enamel

 Crystallographic grain boundary classification of 2D tellurene

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

TEM image with a large field of view showing over 150 magnetite nanoparticles

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

Virtual imaging of Ni-W based alloys

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

Cu-Sn alloy dissociation acquired with a K3 IS direct detection camera

K3 IS: Low dose EM meets catalysis

   
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