Operando microscopy for neuromorphic hardware
Source abstract
Abstract
Microscopy techniques can uncover the physical properties and dynamic behaviours of materials, driving the discovery of emergent phenomena and guiding the design of next-generation computing hardware. As artificial intelligence becomes pervasive, the demand for high-performance materials to support sustainable information technologies is growing. This Review highlights state-of-the-art imaging from electron and X-ray to optical techniques to probe the dynamics of neuromorphic materials, including operando characterization of devices. We examine design principles for neuromorphic materials, along with obstacles that hinder their development. Emphasis is placed on spatially and temporally resolved approaches that capture state changes including phase transitions, ferroic switching and spin-wave propagation that emulate biological components such as neurons, synapses and their connectivity. We discuss challenges in operando characterization and the integration of artificial intelligence-driven analysis for feedback-guided material discovery. Finally, we outline opportunities for real-time imaging of neuromorphic systems, paving the way towards adaptive, brain-inspired hardware.
Source: europepmc · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Advanced Memory and Neural Computing · Advanced Electron Microscopy Techniques and Applications · Neural Networks and Reservoir Computing
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (100+)
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