Yilin Sun
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Yilin Sun has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Jian-Long Xu
Institute of Functional Nano and Soft Materials, Soochow University, Suzhou 215123, P. R. China
1 shared publication Yuandong Gao
School of Microelectronics Science and Technology, Sun Yat-sen University, Zhuhai, People’s Republic of China
1 shared publicationZerui Cai
School of Microelectronics Science and Technology, Sun Yat-sen University, Zhuhai, People’s Republic of China
1 shared publication- Zhifang Liu
Institute of Atomic Manufacturing Beihang University Beijing China
1 shared publication Zimu Wang
School of Microelectronics Science and Technology, Sun Yat-sen University, Zhuhai, People’s Republic of China
1 shared publication
Latest Publications
- Open Access
- 6 May 2026
- Published by Springer Nature in Nano-Micro Letters
- Vol. 18 (1) , 354
A Review on Multi-Level Asymmetric Design for 2D Neuromorphic Devices
Asymmetry has emerged as a critical design strategy for implementing essential neuromorphic functionalities, such as directional signal propagation, programmable plasticity, and bio-inspired dynamics. This principle involves deliberately breaking symmetry at various scales, which introduces unique physical phenomena including spontaneous built-in fields, anisotropic carrier transport, and memristive switching, which are foundational to synaptic and neuronal emulation. Despite growing research, a systematic synthesis of how asymmetry function across different design levels is lacking, hindering the development of guiding design principles. This review bridges this gap by systematically examining asymmetric engineering across three levels: materials, structures, and device. Benefiting from the inherent structural and electronic versatility of two-dimensional (2D) materials, their unique physical properties arising from such multi-level asymmetry for emulating and regulating synaptic plasticity are analyzed to demonstrate the resultant functional diversity and tunability of neuromorphic devices. Furthermore, existing challenges are discussed and a forward-looking perspective on integrating multiple asymmetries and extending the concept to circuit and system levels is provided. This work aims to establish a coherent design framework and provide a unique pathway for developing next-generation neuromorphic intelligent hardware based on 2D materials."Image missing"
- 6 May 2026
- Published by Springer Nature in Nano-Micro Letters
- Vol. 18 (1) , 354
Open AccessA Review on Multi-Level Asymmetric Design for 2D Neuromorphic Devices
Asymmetry has emerged as a critical design strategy for implementing essential neuromorphic functionalities, such as directional signal propagation, programmable plasticity, and bio-inspired dynamics. This principle involves deliberately breaking symmetry at various scales, which introduces unique physical phenomena including spontaneous built-in fields, anisotropic carrier transport, and memristive switching, which are foundational to synaptic and neuronal emulation. Despite growing research, a systematic synthesis of how asymmetry function across different design levels is lacking, hindering the development of guiding design principles. This review bridges this gap by systematically examining asymmetric engineering across three levels: materials, structures, and device. Benefiting from the inherent structural and electronic versatility of two-dimensional (2D) materials, their unique physical properties arising from such multi-level asymmetry for emulating and regulating synaptic plasticity are analyzed to demonstrate the resultant functional diversity and tunability of neuromorphic devices. Furthermore, existing challenges are discussed and a forward-looking perspective on integrating multiple asymmetries and extending the concept to circuit and system levels is provided. This work aims to establish a coherent design framework and provide a unique pathway for developing next-generation neuromorphic intelligent hardware based on 2D materials."Image missing"