Mastering CT: Advanced Techniques in Practice

3. 4D Structure Study with X-ray Computed Tomography

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This is a written summary of a live webinar presented on January 15, 2024. The recording and resources are available on the recording page.

Presented by:

Presenter: Ted Huang
Rigaku
CT Applications Scientist
Rigaku
Director of X-ray Imaging
Katelynn Stuchlik
Rigaku
X-ray Imaging Account Manager

Webinar summary

This webinar, the third in the series Mastering CT: Advanced Techniques in Practice, begins by discussing how traditional ways of studying a material’s internal structure—cutting, polishing, and otherwise altering a sample before examining it—introduce expense, time, and possible artifacts. X-ray computed tomography avoids this by imaging intact samples nondestructively, making it possible to study materials dynamically and repeatedly under changing conditions. That capability forms the basis of so-called “4D CT,” which simply adds time as the fourth dimension to the familiar three-dimensional scan.

Ted showed that a 4D study means monitoring how a structure evolves—whether it’s a seed germinating, coffee beans roasting, or a lithium-ion battery electrode cracking during cycling—by acquiring a series of 3D CT volumes at successive times. He emphasized that while the term “4D” can sound like marketing jargon, in X-ray CT it has a concrete meaning: time-resolved 3D imaging that lets researchers observe real-time or periodic changes inside objects that cannot be seen by other means.

He contrasted ex situ and in situ methods. Ex situ experiments involve scanning a sample, removing it to apply stress, heat, or another treatment, and then scanning again. This allows use of standard mechanical or thermal equipment but risks disturbing the sample between scans. In situ studies are performed inside the CT instrument using miniature loading or heating stages that apply force or temperature during imaging. The advantage is that the sample never moves and the internal evolution can be captured live, though space, load capacity, and X-ray absorption by the fixtures become major limitations.

Examples illustrated both approaches. In ex situ mechanical work, Ted showed compression tests on meteorite rods and described how internal cracks propagated between scans. In situ testing, he inserted a compact mechanical stage directly into the CT chamber, showing force-displacement data and time-lapse images of cracking as it occurred. Temperature-controlled studies followed, from sintering 3D-printed ceramics to observing crystal growth in molten solder. He also shared less conventional 4D projects such as imaging bees building honeycombs—an ex situ case where samples were rescanned between bouts of hive activity—and live studies of batteries charging, where custom fixtures allowed simultaneous electrical cycling and scanning.

Polls during the session revealed that most participants were most interested in in-situ mechanical testing. Ted cautioned that no single approach is “better”; ex situ and in situ each solve different problems and can complement one another. For manufacturers, 4D CT can shorten design-to-production cycles and enable defect detection—porosity, cracks, or assembly flaws—without destroying parts. For researchers, it opens previously inaccessible views of how materials deform, react, or grow.

In a final demonstration, Ted described performing a spring-compression test inside Rigaku’s CT Lab HX using a Deben CT500 stage. He explained practical considerations such as sample alignment, travel limits, cabling clearance, and the need to record an initial scan before loading. After compression, the resulting images were compared and analyzed, showing how force curves relate to visible deformation. Complementary ex situ experiments by his colleague examined dough fermentation and salami heating, correlating structural changes to time and temperature.

In closing, Ted summarized that 4D CT merges three-dimensional imaging with temporal evolution to reveal how structures form, degrade, or respond to external stimuli. Success depends on thoughtful experiment design—controlling transportation and alignment for ex situ work, and stage constraints and setup for in-situ work. He and the moderators encouraged attendees to explore both avenues and suggested that future Rigaku webinars will build on this foundation to cover topics participants proposed. The tone throughout was practical, bridging academic curiosity and industrial application, showing that 4D CT is not just a research novelty but a versatile, nondestructive tool for understanding materials in motion.

Key questions answered in the webinar

A 4D study is fundamentally defined as 3D plus another dimension, which is time. Specifically, a 4D structure study is a 3D structure study with time-dependent development information. Since CT is an imaging tool that provides 3D information, it becomes a true 4D structure study tool when combined with time. The time factor in X-ray CT is typically time resolved, meaning it involves a periodic structure information update, rather than a fully instantaneous or live update. Examples of 4D studies include examining the sprouting of a seed, the structural changes in coffee beans during baking, or monitoring the development of porosity during bread dough fermentation.

Non-destructive structure study capability is crucial because it allows researchers to bypass the time-consuming and costly challenges associated with conventional, destructive methods. Destructive testing often requires sampling and preparation (such as cutting and polishing). This preparation introduces challenges, including concerns about whether the small, cut sample is truly representative of the product and if the preparation process caused additional damage to the structure. These concerns require spending extra time and resources to validate the process, leading to increased costs. By skipping this preparation step, non-destructive CT provides a non-interfering, direct analysis tool, saving time and simplifying the overall process, thus opening up the potential for easier 4D studies.

The capability to perform 4D studies can greatly benefit manufacturing by providing context on how a product operates and performs under real-life conditions. It is particularly valuable for integrating the product design and production cycle. Traditionally, using destructive methods means repeating the "build, destroy, get results" cycle for the build process, processing stage, and final product evaluation, which is time-consuming and requires ensuring consistency across multiple samples. With 4D capability, the examination can be integrated into one single straight line, allowing continuous examination throughout different processes (e.g., material development, assembly, packaging, and redesign phases) on the same sample, saving time and simplifying the cycle. For example, X-ray CT can be used in battery production to check particle distribution and quality, examine separator materials during assembly, and review the final packaging process for potential damage.

Ex situ testing involves scanning the sample, taking it out to perform the test (e.g., mechanical stress or heat treatment), and then scanning it again.

  • Advantages: You are free to use any conventional testing machine. This allows for utilizing conventional servo hydraulic jigs for mechanical tests (like bending or impact studies) or conventional heat treatment in a furnace with atmospheric control for extended periods.
  • Challenges: The most critical challenge is the transportation of the sample back into the CT chamber, especially since the structure may not be strong after the mechanical testing (e.g., if it cracked or shattered). Additionally, ex situ methods cannot capture continuous structure change or provide live structural information, limiting the study to before-and-after observations.

For in situ studies (where the experiment happens live inside the CT chamber), the most critical challenge is the sample setup and experiment design for the contraption/jig.

  • Limitations imposed by the setup: The setup itself dictates limitations such as the maximum sample size, the acceptable load or temperature range, and the specific geometry required to fit the jig.
  • X-ray absorption: The compression stages and jigs often rely on strong materials like tool steel or stainless steel, which are highly absorbent of X-rays. This absorption can significantly block the signal, potentially causing a loss of volume in the CT scan (e.g., up to 15% loss was noted in one study). This requires creative solutions, such as designing strong spacer blocks made of lighter-density material that are less X-ray absorbent, to ensure the full sample data is visible.

The sample design strategy depends on whether the experiment is ex situ or in situ:

  • Ex Situ: Since the testing mechanism is conventional (outside the CT chamber), the best practice is to follow established protocols or traditional standards as closely as possible.
  • In Situ: Because the testing is limited by the specific CT stage, you must imitate the standard but ultimately design the sample to fit the dimensions and limitations of the in situ stage. For example, if a standard rock core compression study requires a 3-inch rod, but the in situ jig cannot fit it, the sample must be downscaled while maintaining the required aspect ratio of the compression cylinder.

All models of CT systems can perform in situ analysis. The advantage of CT is that it scans whatever is placed on the rotational stage. In situ study simply requires doing something inside the CT chamber, which is possible as long as the necessary stage or mechanism fits. Researchers can use immediately available stages (though these might be restricted to certain CT models) or often design and create custom stages themselves to fit the specific chamber they are using.

4D data—which captures structural change over time—is represented by digitally aligning the acquired 3D data sets from different time points to observe the changes. Researchers digitally align the structures and layer them on top of one another to visualize the progression. While data from production models might be aligned relatively easily using CAD drawings, studies involving free-form samples (like a beehive) require more effort for accurate overlap. Since the data is preserved digitally, it provides freedom to manipulate the information in digital space to show the differences.

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