Publication date: 15th April 2025
Memristors, emerging as key enablers of next-generation computing, can be broadly categorized into diffusive and drift types based on their reset mechanisms. Diffusive memristors reset via the spontaneous movement of mobile species under zero bias, exhibiting stochastic dynamics that closely resemble biological ion transport, making them highly suitable for neuromorphic computing. In contrast, drift memristors rely on electric-field-driven ion migration, allowing precise control over non-volatile resistance states, which is ideal for analog neural network implementations.
This talk will present recent progress in memristor device design, array-level integration, and system-level demonstrations, highlighting their transformative potential in neuromorphic and analog computing architectures. Special emphasis will be placed on the role of material engineering, particularly in selecting materials with appropriate ion migration activation energies to optimize memristor performance. Additionally, emerging in-memory computing applications in scientific computing and edge AI hardware will be discussed to showcase the broad relevance of this technology.
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