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A Scanning Electron Microscopy-Compatible Optical Imaging Method for Mesoscopic All-Cell Brain Mapping
Published on: February 20, 2026
Operando microscopy for neuromorphic hardware
Yimei Zhu1, Alex Frano2, Shriram Ramanathan3
1Brookhaven National Laboratory, Upton, NY, USA. zhu@bnl.gov.
Nature Materials
|June 17, 2026
Summary
This review explores advanced microscopy techniques for understanding neuromorphic materials, crucial for developing brain-inspired computing hardware and sustainable information technologies.
Area of Science:
- Materials Science
- Condensed Matter Physics
- Nanotechnology
Background:
- Growing demand for high-performance materials in artificial intelligence and sustainable computing.
- Microscopy is key to understanding material properties and dynamic behaviors for next-generation hardware.
- Neuromorphic materials offer potential for emulating biological neural networks.
Purpose of the Study:
- To review state-of-the-art microscopy techniques for probing neuromorphic material dynamics.
- To examine design principles and challenges in neuromorphic material development.
- To highlight the role of operando characterization and AI in material discovery.
Main Methods:
- Electron microscopy
- X-ray imaging
- Optical microscopy techniques
- Operando characterization of devices
Main Results:
- Spatially and temporally resolved imaging captures critical state changes (phase transitions, ferroic switching, spin-wave propagation).
- These dynamics emulate biological neuronal functions like synapses and connectivity.
- Challenges in operando characterization and AI integration for material discovery are identified.
Conclusions:
- Advanced imaging techniques are vital for understanding and designing neuromorphic materials.
- Overcoming characterization challenges and integrating AI can accelerate feedback-guided material discovery.
- Real-time imaging of neuromorphic systems will enable adaptive, brain-inspired hardware.
