ZEISS at Microscopy & Microanalysis (M&M) 2026

Three-dimensional imaging of micro- and nano-structures by X-ray microscopy (XRM / microCT) has become a critical technique in materials research, biological science, geoscience, and failure analysis labs. This talk will present the latest XRM technology and product developments from ZEISS, spanning innovations in hardware (X-ray sources, detectors, rapid scanning strategies…) as well as software (intuitive instrument control, deep learning-based reconstruction, compositional analysis,..). Taken together, these technology developments will be shown to push the boundaries of the technique in terms of imaging resolution, acquisition speed, data clarity, and broad user accessibility.

Continued miniaturization of semiconductor devices and need for characterizing smaller features in various materials research disciplines place unprecedented demands on preparing TEM lamella, ET and APT samples, and precise cross-sectioning. The workflow to achieve damage-free samples the first time with precise endpoint control has become increasingly challenging as we dive deeper into more complex and beam-sensitive artifacts. Join us for this presentation to learn how ZEISS is addressing these workflow challenges through recent advances in focused ion beam–scanning electron microscope (FIB‑SEM) instrumentation.

Compared to traditional operation, microscopy automation offers the potential for both improved productivity and result repeatability. This talk will demonstrate two new tools for automation of the materials microscopy lab:

1. ZEISS Blockwise is an innovative and intuitive new software platform designed to automate electron microscope (EM) control, image analysis, and metrology. Tailored for R&D, failure analysis, and QA/QC labs, this no-code platform integrates a drag-and-drop workflow builder, seamless integration with hardware, and advanced image analysis tools. We’ll show how the low-code environment simplifies complex tasks while still offering flexibility for advanced users through Python scripting.
2. ZEISS X-ray microscopes offer a robust Python API for building advanced and customized user operation. In this talk, a demonstration of such a case will be presented in which a framework of Large Language Model (LLM) agents have been deployed to control the XRM by interpreting natural language user instructions, dictating Python API commands to the microscope, and performing automated processing and analysis of resulting 2D/3D image data. This architecture lays a foundation for myriad automated 3D imaging workflows, without the requirement for manual and time-consuming user coding.