Move critical sample decisions earlier in the workflow
High-end TEM access is limited, expensive, and often overbooked. In many labs, premium TEM time is still used for basic sample screening — only to discover later that the lamella is too thick, damaged, phase-altered, or not positioned on the right region of interest. The webinar presents a workflow shift: perform early screening and diffraction-based quality control directly in SEM or FIB-SEM before moving to the most expensive instruments.
By bringing 4D-STEM into the SEM environment, the session explores how users can collect information-rich diffraction data, validate sample readiness, and support downstream TEM work with greater confidence. The webinar also explains why this approach is not intended to replace high-end TEM, but to complement it by improving prescreening, sample validation, and workflow efficiency.
Explore 4D-STEM in SEM from workflow to real data
In this webinar, you will learn:
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How 4D-STEM works in SEM: a two-dimensional diffraction pattern is collected at each point in a two-dimensional scan, creating a 4D dataset.
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How diffraction patterns can provide information about crystal structure, crystal orientation, crystalline order, disorder, and lattice-related features.
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How an event-based TimePix3 detector supports high-dynamic-range diffraction data collection in the SEM.
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How low-dose operating conditions, including typical operation around 10 pA in the examples discussed, can benefit dose-sensitive samples.
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How virtual apertures can be used to reconstruct bright-field, annular bright-field, dark-field, and feature-specific contrast from the same pixelated dataset.
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How HDF5-based data and open-source 4D-STEM tools can support post-processing and deeper analysis.
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How SEM-based 4D-STEM can support sample preparation decisions, such as whether additional thinning or polishing is needed before more advanced analysis.
Reduce TEM prescreening and arrive prepared
The webinar presents 4D-STEM in SEM as a practical gatekeeping step between FIB-SEM preparation and high-end TEM analysis. Instead of transferring every sample to TEM for initial checks, users can deploy the 4D-STEM detector in the SEM/FIB-SEM, analyze diffraction data immediately, and select samples or regions of interest with more confidence.
In the webinar, Tescan explains that screening lamellae in FIB-SEM before transfer can reduce TEM time spent on prescreening by up to 70%, because the first-pass diffraction check no longer needs to be performed on the high-end instrument. The webinar also states that routine SEM-based analysis can operate at about 33% of the operational cost of equivalent high-end TEM work. These claims should be reviewed internally before publication as headline metrics.
Event-based detection, virtual apertures, and open analysis workflows
The webinar introduces a fully integrated retractable pixelated detector for SEM and FIB-SEM workflows. In Prof. Britton’s demonstration, the detector is described as a TimePix3-based system on an actuated arm, with a detector shield for protection when not in use. The detector supports high dynamic range and can count electron events, enabling diffraction data collection with both direct beam and scattered features visible in the dataset.
The session also shows how 4D-STEM datasets can be explored through virtual apertures. Users can reconstruct bright-field and dark-field images, inspect diffraction patterns, and then decide which datasets should be saved and post-processed in more detail. The webinar specifically discusses HDF5 data access and compatibility with classical 4D-STEM analysis workflows.
Technical themes covered:
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TimePix3 event-based detector operation
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High-dynamic-range diffraction data
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Low-dose 4D-STEM in SEM
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Virtual bright-field and dark-field imaging
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Spot patterns, Kikuchi bands, and wide-angle scattering
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HDF5 data handling
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LibreTEM, HyperSpy, and py4DSTEM workflows
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SEM/FIB-SEM sample screening before TEM
See 4D-STEM in SEM across real materials case studies
Prof. Ben Britton demonstrates how 4D-STEM in SEM can be applied to several materials challenges:
Aluminum alloys
The webinar shows how virtual bright-field STEM from the 4D detector reveals precipitates, nanoprecipitates, grain-boundary features, dispersoids, and dislocation-related contrast. The SEM-based data is compared with data from a dedicated instrument to show how much information can be obtained before engaging more advanced TEM/STEM analysis.
Semiconductor multilayers
The webinar discusses semiconductor multilayer analysis for screening, quality assurance, zone alignment checks, and layer thickness evaluation.
Polycrystalline copper
A fine-grained polycrystalline copper sample is used to show diffraction patterns containing spots and Kikuchi bands, virtual bright-field imaging, py4DSTEM indexing, and crystallographic orientation mapping. The webinar also shows how this data can connect to workflows familiar from EBSD analysis.
Air-sensitive perovskite systems
The webinar highlights perovskite materials where low-dose and in-vacuum analysis are especially valuable. The ability to perform FIB preparation followed immediately by 4D-STEM in SEM is presented as a way to study native structure and controlled air-sensitive degradation without unnecessary exposure to air.
Who should watch?
Built for microscopy teams that need faster, more confident sample decisions
This on-demand webinar is especially relevant for:
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Materials science researchers working with nanoscale structure and crystallography
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Electron microscopy specialists using SEM, FIB-SEM, STEM, or TEM
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TEM sample preparation teams validating lamella quality before transfer
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Core facility managers looking to improve instrument utilization and reduce rework
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Semiconductor, metals, nanomaterials, and advanced materials laboratories
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Method developers working with 4D-STEM datasets, virtual apertures, and open-source analysis tools
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University and research institute teams training students and researchers on correlative microscopy workflows
Ready to see 4D-STEM in SEM in action?
Watch the on-demand webinar to learn how event-based 4D-STEM in SEM can help your lab collect richer diffraction data, validate samples earlier, and make more confident decisions before moving to high-end TEM analysis.
