Artificial Optoelectronic Synapse Featuring Bidirectional Post-Synaptic Current for Compact and Energy-Efficient Neural Hardware

被引:0
作者
Ahn, Hogeun [1 ,2 ]
Kim, Yena [3 ]
Seo, Seunghwan [2 ,4 ,5 ]
Lee, Junseo [1 ]
Lee, Sehee [1 ]
Oh, Saeyoung [4 ]
Kim, Byeongchan [1 ]
Park, Jeongwon [4 ]
Kang, Sumin [4 ]
Kim, Yuseok [4 ]
Ham, Ayoung [4 ]
Lee, Jaehyun [4 ]
Park, Donggeon [6 ]
Kwon, Seongdae [4 ]
Lee, Doyoon [2 ,5 ]
Ryu, Jung-El [2 ,5 ]
Shin, June-Chul [2 ,5 ]
Sahasrabudhe, Atharva [2 ,5 ]
Kim, Ki Seok [2 ,5 ]
Bae, Sang-Hoon [7 ,8 ]
Kang, Kibum [4 ,6 ]
Kim, Jeehwan [2 ,5 ]
Oh, Saeroonter [3 ]
Park, Jin-Hong [1 ,3 ,9 ]
机构
[1] Sungkyunkwan Univ, Dept Elect & Comp Engn, Suwon 16419, South Korea
[2] MIT, Dept Mech Engn, Cambridge, MA 02138 USA
[3] Sungkyunkwan Univ, Dept Semicond Convergence Engn, Suwon 16419, South Korea
[4] Korea Adv Inst Sci & Technol, Dept Mat Sci & Engn, Daejeon 34141, South Korea
[5] MIT, Res Lab Elect, Cambridge, MA 02138 USA
[6] Korea Adv Inst Sci & Technol, Grad Sch Semicond Technol, Daejeon 34141, South Korea
[7] Washington Univ, Dept Mech Engn & Mat Sci, St Louis, MO 63130 USA
[8] Washington Univ, Inst Mat Sci & Engn, St Louis, MO 63130 USA
[9] Sungkyunkwan Univ, SKKU Adv Inst Nanotechnol, Suwon 16419, South Korea
基金
新加坡国家研究基金会;
关键词
brain-inspired computing; hardware neural network; artificial synapse; artificial optoelectronic synapse; asymmetric metal contacts; van-der-Waals layered materials; PLASTICITY; NETWORKS;
D O I
10.1002/adma.202418582
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Conventional hardware neural networks (HW-NNs) have relied on unidirectional current flow of artificial synapses, necessitating a differential pair of the synapses for weight core implementation. Here, an artificial optoelectronic synapse capable of bidirectional post-synaptic current (IPSC) is presented, eliminating the need for differential synapse pairs. This is achieved through an asymmetric metal contact structure that induces a built-in electric field for directional flow of photogenerated carriers, and a charge trapping/de-trapping layer in the gate stack (h-BN/weight control layer) that can modulate the surface potential of the semiconductor channel (WSe2) using electrical signals. This structure enables precise control over the direction and magnitude of injected charge. The device demonstrates key synaptic behaviors, such as long-term potentiation/depression and spike-timing-dependent plasticity. A fabricated 3 x 2 artificial synapse array shows that the bidirectional IPSC characteristic is compatible with multiply-accumulate operations. Finally, the feasibility of these synapses in HW-NNs is demonstrated through training and inference simulations using the MNIST handwritten digits dataset, yielding competitive recognition rates and reduced total energy consumption for updating weights of the weight core compared to unidirectional IPSC-based systems. This approach paves the way toward more compact and energy-efficient brain-inspired computing systems.
引用
收藏
页数:10
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