Department of Energy Science , Sungkyunkwan University , Suwon 16419 , Korea.
Singapore University of Technology & Design , 8 Somapah Road , 487372 , Singapore.
Nano Lett. 2018 May 9;18(5):3229-3234. doi: 10.1021/acs.nanolett.8b00994. Epub 2018 Apr 24.
Synaptic computation, which is vital for information processing and decision making in neural networks, has remained technically challenging to be demonstrated without using numerous transistors and capacitors, though significant efforts have been made to emulate the biological synaptic transmission such as short-term and long-term plasticity and memory. Here, we report synaptic computation based on Joule heating and versatile doping induced metal-insulator transition in a scalable monolayer-molybdenum disulfide (MoS) device with a biologically comparable energy consumption (∼10 fJ). A circuit with our tunable excitatory and inhibitory synaptic devices demonstrates a key function for realizing the most precise temporal computation in the human brain, sound localization: detecting an interaural time difference by suppressing sound intensity- or frequency-dependent synaptic connectivity. This Letter opens a way to implement synaptic computing in neuromorphic applications, overcoming the limitation of scalability and power consumption in conventional CMOS-based neuromorphic devices.
突触计算对于神经网络中的信息处理和决策至关重要,但在不使用大量晶体管和电容器的情况下,其技术实现仍然具有挑战性,尽管已经做出了巨大努力来模拟生物突触传递,如短期和长期可塑性和记忆。在这里,我们报告了基于焦耳加热和可扩展单层二硫化钼 (MoS) 器件中多功能掺杂诱导的金属-绝缘体转变的突触计算,其能量消耗与生物可比拟(约 10 fJ)。具有我们可调节兴奋性和抑制性突触器件的电路展示了实现人类大脑中最精确时间计算的关键功能,即通过抑制声音强度或频率相关的突触连接来检测耳间时间差。这封信为在神经形态应用中实现突触计算开辟了道路,克服了传统基于 CMOS 的神经形态器件在可扩展性和功耗方面的限制。