As the demand for artificial intelligence continues to grow, the limitations of traditional von Neumann architecture in terms of energy efficiency and processing speed become more pronounced. Now, researchers from the School of Integrated Circuits at Shandong University, led by Professor Jialin Meng and Professor Tianyu Wang, have presented a comprehensive review on low-power memristors and their potential applications in neuromorphic computing. This work offers valuable insights into the development of next-generation computing technologies that can overcome these limitations.
Why Low-Power Memristors Matter
Innovative Design and Features
Applications and Future Outlook
This comprehensive review provides a roadmap for the development and application of low-power memristors in neuromorphic computing. It highlights the importance of interdisciplinary research in materials science, electronics, and computer science to drive innovation in this field. Stay tuned for more groundbreaking work from Professor Jialin Meng and Professor Tianyu Wang at Shandong University!
Nano-Micro Letters
Experimental study
Low‑Power Memristor for Neuromorphic Computing: From Materials to Applications
14-Apr-2025