Feng Ce, Li Bo-Wen, Dong Yang, Chen Xiang-Dong, Zheng Yu, Wang Ze-Hao, Lin Hao-Bin, Jiang Wang, Zhang Shao-Chun, Zou Chong-Wen, Guo Guang-Can, Sun Fang-Wen
CAS Key Laboratory of Quantum Information, University of Science and Technology of China, Hefei 230026, China.
CAS Center for Excellence in Quantum Information and Quantum Physics, University of Science and Technology of China, Hefei 230026, China.
Sci Adv. 2023 Oct 6;9(40):eadg9376. doi: 10.1126/sciadv.adg9376. Epub 2023 Oct 4.
Neuromorphic computing has shown remarkable capabilities in silicon-based artificial intelligence, which can be optimized by using Mott materials for functional synaptic connections. However, the research efforts focus on two-terminal artificial synapses and envisioned the networks controlled by silicon-based circuits, which is difficult to develop and integrate. Here, we propose a dynamic network with laser-controlled conducting filaments based on electric field-induced local insulator-metal transition of vanadium dioxide. Quantum sensing is used to realize conductivity-sensitive imaging of conducting filament. We find that the location of filament formation is manipulated by focused laser, which is applicable to simulate the dynamical synaptic connections between the neurons. The ability to process signals with both long-term and short-term potentiation is further demonstrated with ~60 times on/off ratio while switching the pathways. This study opens the door to the development of dynamic network structures depending on easily controlled conduction pathways, mimicking the biological nervous systems.
神经形态计算在基于硅的人工智能中展现出了卓越的能力，通过使用莫特材料实现功能性突触连接可对其进行优化。然而，研究工作主要集中在两端人工突触，并设想由基于硅的电路控制网络，这很难开发和集成。在此，我们基于二氧化钒的电场诱导局部绝缘体 - 金属转变，提出一种具有激光控制导电细丝的动态网络。利用量子传感实现导电细丝的电导率敏感成像。我们发现细丝形成的位置可通过聚焦激光进行操控，这适用于模拟神经元之间的动态突触连接。在切换路径时，开/关比约为60倍，进一步证明了其具有处理长期和短期增强信号的能力。这项研究为基于易于控制的传导路径开发动态网络结构打开了大门，模拟了生物神经系统。
