Article
Chemistry, Multidisciplinary
Bolun Wang, Xuewen Wang, Enze Wang, Chenyu Li, Ruixuan Peng, Yonghuang Wu, Zeqin Xin, Yufei Sun, Jing Guo, Shoushan Fan, Chen Wang, Jianshi Tang, Kai Liu
Summary: This study presents a synaptic transistor that can operate at high temperatures, using MoS2 and Na+-diffused SiO2 as the main materials, achieving high on/off ratio and recognition accuracy.
Article
Nanoscience & Nanotechnology
Po-Cheng Tsai, Coung-Ru Yan, Shoou-Jinn Chang, Shih-Yen Lin
Summary: Bottom-gate transistors with mono-layer MoS2 channels and polycrystalline antimonene source/drain contact electrodes are successfully fabricated. The devices exhibit significant improvement in performance, including high field-effect mobility and large ON/OFF ratio. Moreover, increased photocurrents are observed in the MoS2 transistor under light irradiation.
Article
Chemistry, Multidisciplinary
Xinyu Wang, Xinyu Chen, Jingyi Ma, Saifei Gou, Xiaojiao Guo, Ling Tong, Junqiang Zhu, Yin Xia, Die Wang, Chuming Sheng, Honglei Chen, Zhengzong Sun, Shunli Ma, Antoine Riaud, Zihan Xu, Chunxiao Cong, Zhijun Qiu, Peng Zhou, Yufeng Xie, Lifeng Bian, Wenzhong Bao
Summary: This article introduces the fabrication of MoS2 field-effect transistors with consistent performance using a 4-inch high-quality monolayer MoS2 film, and explores the design and fabrication of basic circuits and more complex logic circuits.
ADVANCED MATERIALS
(2022)
Article
Materials Science, Multidisciplinary
Y. B. Liu, D. Cai, T. C. Zhao, M. Shen, X. Zhou, Z. H. Zhang, X. W. Meng, D. E. Gu
Summary: This study demonstrates a high-performance monolayer MoS2 Ion based synaptic device (ISD) using Na+ ions doped in the MoS2 lattice as ion sources. The device exhibits various synaptic plasticity and biological features, with low synaptic event response voltage and energy consumption. The resistance switching mechanism and the recognition accuracy of the MNIST handwritten digits are also investigated.
JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Mudasir A. Khanday, Farooq A. Khanday, Faisal Bashir
Summary: This study presents a new energy-efficient single transistor leaky integrate-and-fire neuron for future neuromorphic computing. The proposed SiGe-based single transistor neuron accurately mimics the spiking behavior of the biological neuron and has lower energy consumption compared to previous Si-based and Ge-based single transistor neurons. It also shows improvements in controllability, simplicity, integration density, and fabrication process. The proposed neuron has been employed to implement universal digital logic functions and has been verified for recognition ability of MNIST handwritten digits with an accuracy of 93.79%.
NEURAL PROCESSING LETTERS
(2023)
Review
Chemistry, Multidisciplinary
Yifei Wang, Qijun Sun, Jinran Yu, Nuo Xu, Yichen Wei, Jeong Ho Cho, Zhong Lin Wang
Summary: This article presents a systematic summary of Boolean logic computing based on emerging neuromorphic transistors, including logical operation modes, materials, device structures, and working mechanisms. The input mode of Boolean logic operation is classified into electrical input, optical input, and synergistic optical/electrical input. Additionally, modulation strategies using electrical, optical, and thermal signals to construct programmable logic functions are also summarized. These investigations hold great significance in advancing the development of high-efficiency and high integration density in future neuromorphic computing.
ADVANCED FUNCTIONAL MATERIALS
(2023)
Article
Nanoscience & Nanotechnology
Joon-Kyu Han, Seong-Yun Yun, Ji-Man Yu, Seung-Bae Jeon, Yang-Kyu Choi
Summary: An artificial multisensory device for sensor computing is demonstrated using a single-transistor neuron (1T-neuron) for multimodal perception. The 1T-neuron simultaneously receives visual and thermal sensing signals and converts them into electrical signals in the form of spiking, which are then sent to a spiking neural network. This allows for realizing input neurons for multimodal sensing. By utilizing the optical and thermal behaviors of the 1T-neuron, visual and thermal sensing is achieved. A fingerprint recognition system is implemented to demonstrate the neuromorphic multimodal sensing system using the artificial multisensory 1T-neuron, which not only identifies genuine patterns but also detects forgeries.
ACS APPLIED MATERIALS & INTERFACES
(2023)
Article
Nanoscience & Nanotechnology
Hyeyeon Sunwoo, Woong Choi
Summary: In this study, highly stable and reversible n-type doping of monolayer MoS2 was achieved using thermal treatment in NMP. The thermal treatment in NMP improved the performance of MoS2 transistors and the doping effect remained effective for over 12 months.
Article
Chemistry, Multidisciplinary
Jingyun Zou, Zhengyang Cai, Yongjue Lai, Junyang Tan, Rongjie Zhang, Simin Feng, Gang Wang, Junhao Lin, Bilu Liu, Hui-Ming Cheng
Summary: The study presents an in-situ chemical vapor deposition method that allows for widely tunable doping concentrations in monolayer MoS2. By using appropriate vanadium precursors with different doping abilities, large-scale uniform doping to MoS2 can be achieved. Artificial synaptic transistors were fabricated using heavily doped MoS2, mimicking synaptic potentiation, depression, and repetitive learning processes.
Article
Physics, Applied
Sina Li, Jielian Zhang, Yan Li, Kai Zhang, Lingyu Zhu, Wei Gao, Jingbo Li, Nengjie Huo
Summary: Researchers have designed a vdW heterojunction device using low-symmetric CrOCl, which exhibits stable anti-ambipolar behavior and polarization-sensitive photodetection. The anti-ambipolar transport behavior in a MoTe2 channel is observed due to the gate-tunable band bending and charge transfer at the MoTe2/CrOCl interface. The device shows good photodetection performance with a responsivity of 1.05 A/W and a temporal response of 970 μs. With the anisotropic CrOCl as a photosensitizing layer, the device achieves polarization-sensitive photodetection with a photocurrent dichroic ratio of up to 6. This work provides a valid device model and design strategy for versatile optoelectronics, including anti-ambipolar transistors and polarimetric photodetectors.
APPLIED PHYSICS LETTERS
(2023)
Article
Chemistry, Multidisciplinary
Hyunmin Cho, Donghee Kang, Yangjin Lee, Heesun Bae, Sungjae Hong, Yongjae Cho, Kwanpyo Kim, Yeonjin Yi, Ji Hoon Park, Seongil Im
Summary: In addressing the high contact resistance in 2D devices, the use of thermal-evaporated ultrathin LiF between channel and source/drain metal has shown promising results in reducing RC values in MoS2 FETs. By utilizing the 4-bar FET method, lower RC values can be achieved, while transparent conducting oxide contact enables transparent MoS2 FETs to be realized.
Article
Nanoscience & Nanotechnology
Byeongjin Park, Yunjeong Hwang, Ojun Kwon, Seungkwon Hwang, Ju Ah Lee, Dong-Hyeong Choi, Seoung-Ki Lee, Ah Ra Kim, Byungjin Cho, Jung-Dae Kwon, Je In Lee, Yonghun Kim
Summary: This study proposes a robust artificial synaptic device combining a lithium silicate solid-state electrolyte thin film with a two-dimensional MoS2 material. The device exhibits excellent linearity and symmetry, allowing for reliable parallel analogue computation and achieving extremely low variations.
ACS APPLIED MATERIALS & INTERFACES
(2022)
Article
Chemistry, Multidisciplinary
Joon-Kyu Han, Jung-Woo Lee, Yeeun Kim, Young Bin Kim, Seong-Yun Yun, Sang-Won Lee, Ji-Man Yu, Keon Jae Lee, Hyun Myung, Yang-Kyu Choi
Summary: Neuromorphic hardware with a spiking neural network (SNN) can greatly improve the energy efficiency of artificial intelligence (AI) functions. This study demonstrates a neuromorphic module composed of synapses over neurons, achieved through monolithic vertical integration. By using techniques such as laser annealing and thermal annealing, the performance of the module is enhanced.
Article
Chemistry, Multidisciplinary
Yingjie Chen, Baonan Jia, Guoying Qin, Huiyan Zhao, Lihong Han, Pengfei Lu
Summary: High-performance photocatalysts are crucial for harvesting solar energy and producing pollution-free hydrogen and oxygen through water splitting. In this study, we designed 144 van der Waals (vdW) heterostructures by combining different two-dimensional (2D) group III-V MX (M = Ga, In and X = P, As) monolayers to identify efficient photoelectrochemical materials. Using first-principles calculations, we investigated the stabilities, electronic properties, and optical properties of these heterostructures. GaP/InP in a BB-II stacking configuration was selected as the most promising candidate, with a type-II band alignment and suitable gap value for the catalytic reaction under pH = 0. Additionally, the construction of vdW heterostructure improved light absorption. These findings provide insights into the properties of III-V heterostructures and can guide experimental synthesis for photocatalysis applications.
Article
Engineering, Electrical & Electronic
Young-Woo Chung, Joon-Kyu Han, Jin-Woo Jung, Seong-Yun Yun, Ji-Man Yu, Mun-Woo Lee, Yang-Kyu Choi
Summary: This research demonstrates a thermally stable single-transistor neuron (1T-neuron) using a vertical nanowire Si MOSFET. By utilizing thermally insensitive band-to-band tunneling (BTBT) instead of temperature-sensitive impact ionization (I.I.), neuronal operation with thermal stability is achieved.
IEEE ELECTRON DEVICE LETTERS
(2022)
Article
Engineering, Biomedical
Yanchen Liu, Kun Qian, Shaogang Hu, Kun An, Sheng Xu, Xitong Zhan, J. J. Wang, Rui Guo, Yuancong Wu, Tu-Pei Chen, Qi Yu, Yang Liu
IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS
(2020)
Article
Engineering, Electrical & Electronic
Yuancong Wu, Y. H. Liu, Shuang Liu, Q. Yu, T. P. Chen, Y. Liu
ELECTRONICS LETTERS
(2020)
Article
Engineering, Electrical & Electronic
Jianxun Sun, Juan Boon Tan, Tupei Chen
IEEE TRANSACTIONS ON ELECTRON DEVICES
(2020)
Article
Engineering, Electrical & Electronic
Jianxun Sun, Juan Boon Tan, Tupei Chen
IEEE TRANSACTIONS ON ELECTRON DEVICES
(2020)
Article
Computer Science, Artificial Intelligence
G. C. Qiao, S. G. Hu, T. P. Chen, L. M. Rong, N. Ning, Q. Yu, Y. Liu
Article
Engineering, Electrical & Electronic
Rui Guo, YuanCong Wu, ShaoGang Hu, Qi Yu, Tupei Chen, Yang Liu
Summary: This work introduces an LC-VCO based PLL frequency synthesizer with a neural network based loop bandwidth tracking technique, which can maintain a constant loop bandwidth over different operating frequencies.
IEICE ELECTRONICS EXPRESS
(2021)
Article
Materials Science, Multidisciplinary
Yuanbo Li, Jianxun Sun, Teddy Salim, Rongyue Liu, Tupei Chen
Summary: A high-mobility transparent Indium-Gallium-Zinc-Oxide (IGZO) thin-film transistor (TFT) with sputtered AlOx passivation layer was reported, showing improved field-effect mobility, on/off current ratio, and driving current. The formation of an interfacial layer between the IGZO and AlOx layers was crucial in enhancing the electrical performance. Reliability tests, including long-term exposure and positive bias illumination stress, also exhibited improved results.
ECS JOURNAL OF SOLID STATE SCIENCE AND TECHNOLOGY
(2021)
Article
Physics, Applied
Shuang Liu, Yuancong Wu, Canlong Xiong, Yihe Liu, Jing Yang, Q. Yu, S. G. Hu, T. P. Chen, Y. Liu
Summary: PIM technology enhances the performance of RC systems, demonstrated in this work using a PIM chip platform. Nonlinear dynamic system predictions and recognition tasks were carried out, saving 50% energy and requiring fewer operations compared to traditional RC systems.
APPLIED PHYSICS LETTERS
(2021)
Article
Computer Science, Artificial Intelligence
S. G. Hu, G. C. Qiao, T. P. Chen, Q. Yu, Y. Liu, L. M. Rong
Summary: In this study, a SNN based on STDP for online learning with weight quantization/binarization was developed. The quantized SNN achieved high recognition accuracy on the MNIST dataset with reduced storage requirements and improved computing efficiency. This approach can significantly save hardware costs and provide a trade-off between computational cost and performance.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Materials Science, Multidisciplinary
Y. B. Li, J. Zhang, J. X. Sun, T. P. Chen
Summary: This study aims to find a suitable HfO2-based resistive random-access memory (RRAM) structure for large-area applications and successfully inserts an ultrathin Al2O3 layer to achieve stable operations at low current levels.
ECS JOURNAL OF SOLID STATE SCIENCE AND TECHNOLOGY
(2021)
Article
Nanoscience & Nanotechnology
Y. H. Liu, L. Chen, X. W. Li, Y. C. Wu, S. Liu, J. J. Wang, S. G. Hu, Q. Yu, T. P. Chen, Y. Liu
Summary: This study proposes a lightweight automatic epilepsy detection system based on a neuromorphic chip, utilizing a neural network model for high-accuracy detection without the need for prior knowledge. The system shows high classification accuracy in tests and offers the possibility of epilepsy detection in wearable or portable devices.
Article
Multidisciplinary Sciences
Y. A. Liu, L. Chen, X. W. Li, Y. L. Liu, S. G. Hu, Q. Yu, T. P. Chen, Y. Liu
Summary: This paper proposes an advanced encryption standard (AES) cryptosystem based on memristive neural network. The proposed algorithm shows higher security and robustness compared to conventional AES.
SCIENTIFIC REPORTS
(2022)
Article
Engineering, Biomedical
Shuang Liu, J. J. Wang, J. T. Zhou, S. G. Hu, Q. Yu, T. P. Chen, Y. Liu
Summary: In this article, a spiking neural network (SNN) based on both SRAM processing-in-memory (PIM) macro and on-chip unsupervised learning with Spike-Time-Dependent Plasticity (STDP) is presented. The co-design of algorithm and hardware improves area and energy efficiency. The proposed macro utilizes charge sharing of capacitors for fully parallel operations and a programmable high-precision PIM threshold generator is designed to achieve low DNL and high linearity. With the combination of the hardware-friendly STDP algorithm, parallel WLs and PBLs, unsupervised learning and MNIST dataset recognition are realized.
IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS
(2023)
Article
Chemistry, Analytical
Hongzhe Wang, Junjie Wang, Hao Hu, Guo Li, Shaogang Hu, Qi Yu, Zhen Liu, Tupei Chen, Shijie Zhou, Yang Liu
Summary: This paper proposes an RRAM PIM accelerator architecture that does not use ADCs and DACs. Additionally, no additional memory usage is required to avoid the need for a large amount of data transportation in convolution computation. Partial quantization is introduced to reduce the accuracy loss. The proposed architecture can substantially reduce the overall power consumption and accelerate computation. The simulation results show that the image recognition rate for the CNN algorithm can reach 284 frames per second at 50 MHz using this architecture. The accuracy of the partial quantization remains almost unchanged compared to the algorithm without quantization.
Article
Chemistry, Multidisciplinary
Yuanbo Li, Tupei Chen, Xin Ju, Teddy Salim
Summary: This study presents the fabrication of a transparent thin film transistor (TFT) using InGaZnO and TaOx, which exhibits various synaptic behaviors and high responsivity to light, indicating potential applications in neuromorphic systems.
