科研论文
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2025
Charge redistribution to reduce contact resistivity in NiSi/Si system through interface modification: A first-principles study
W. Wang, P. Ren, S. Ye, H. Lu, R. Wang, Z. Ji, "Charge redistribution to reduce contact resistivity in NiSi/Si system through interface modification: A first-principles study," Appl. Phys. Lett. vol. 126, pp. 131601, Mar. 2025....
New
2025
DATIS: DRAM Architecture and Technology Integrated Simulation
ecture and Technology Integrated Simulation,” in 2025 3rd International Symposium of Electronics Design Automation (ISEDA), Hong Kong, China, 2025....
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2022
Characterization and Modelling of Hot Carrier Degradation in pFETs under Vd> Vg Condition for sub-20nm DRAM Technologies
ETs under Vd>Vg Condition for sub-20nm DRAM Technologies," 2022 IEEE International Reliability Physics Symposium (IRPS), Dallas, TX, USA, 2022, pp. 7B.1-1-7B.1-7, doi: 10.1109/IRPS48227.2022.9764561....
2024
Improved Positive Bias Temperature Instability of n-type Vertical C-Shaped-Channel Nanosheet FET by Forming Gas Annealing
Y. Shi, S. Jiang, H. Yang, Y. Zhang, L. Zhou, Z. Ji, Q. Liu, Q. Wang, H. Zhu, J. Luo, and W. Wang, “Improved Positive Bias Temperature Instability of n-type Vertical C-Shaped-Channel Nanosheet FET by Forming Gas Annealing,” in 2024 IEEE International Symposium on the Physical and Failure Analysis of Integrated Circuits (IPFA), Singapore, Singapore, 2024, pp. 1-5.
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2024
Memory-facilitated Joint-space Shift Adaptation in Traffic Forecasting
Y. Wei, H. Haitao, G. Schaefer, Z. Ji, Y. Wang and H. Fang, “Memory-facilitated Joint-space Shift Adaptation in Traffic Forecasting,” in 2024 International Joint Conference on Neural Networks (IJCNN), Yokohama, Japan, 2024, pp. 1-8.
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2024
Study on the Anomalous Characteristics of Random Telegraph Noise in FeFETs
P. Cai, Y. Wu, Z. Sun, H. Li, X. Wang, Z. Ji, R. Wang, R. Huang, "Study on the Anomalous Characteristics of Random Telegraph Noise in FeFETs,” in 2024 IEEE Silicon Nanoelectronics Workshop (SNW), Honolulu, HI, USA, 2024, pp. 35-36.
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2024
A New Framework to MOS Device for Cryogenic Application: Linking Materials with Modeling
C. Zhang, M. Wu, M. Yuan, Y. Xue, P. Ren, R. Wang, Z. Ji, “A New Framework to MOS Device for Cryogenic Application: Linking Materials with Modeling,” in 2024 2nd International Symposium of Electronics Design Automation (ISEDA), Xi'an, China, 2024, pp. 78-83.
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2024
A Memory-augmented Conditional Neural Process model for traffic prediction
Y. Wei, H. He, K. Yuan, G. Schaefer, Z. Ji, H. Fang*, “A Memory-augmented Conditional Neural Process model for traffic prediction,” Knowl.-Based Syst., vol. 304, p. 112578, Nov. 2024.
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2024
Unveiling the Role of Local Stress in Enhancing Ferroelectric Properties and Endurance of HfO2/ZrO2 Superlattice Structures
B. Cui, S. Ye, X. Wang, M. Wu, Y. Li, Y. Wu, Y. Wen, J. Liu, X. Li, P. Ren, Z. Ji, H. Lu, D.W. Zhang, R. Wang, R. Huang, “Unveiling the Role of Local Stress in Enhancing Ferroelectric Properties and Endurance of HfO2/ZrO2 Superlattice Structures,” IEEE Electron Device Lett., vol. 46, no. 1, pp. 107-110, Jan. 2025.
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2024
Insights into oxygen vacancy dynamics in HfO2–ZrO2 superlattice ferroelectric films: Implications for device reliability
M. Wu, B. Cui, X. Wang, M. Yuan, Y. Wu, Y. Wen, J. Liu, T. Zhang, P. Ren, S.Ye, R. Wang, Z. Ji, R. Huang, “Insights into oxygen vacancy dynamics in HfO2–ZrO2 superlattice ferroelectric films: Implications for device reliability,” J. Appl. Phys., vol. 136, no. 14, Oct. 2024.
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2024
DSTC: Dual-Side Sparsity Tensor Core for DNNs Acceleration on Modern GPU Architectures
C. Zhang, Y. Wang, Z. Xie, C. Guo, Y. Liu, J.Leng, G. Sun, Z. Ji, R. Wang, Y. Xie, R. Huang, ” DSTC: Dual-Side Sparse Tensor Core for DNNs Acceleration on Modern GPU Architectures,” IEEE Trans. Comput., vol. 74, no. 2, pp. 341-355, Feb. 2025.
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2024
Accurate prediction of dielectric properties and bandgaps in materials with a machine learning approach
Y. Hu, M. Wu, M. Yuan, Y. Wen, P. Ren, S. Ye, F. Liu, B. Zhou, H. Fang, R. Wang, Z. Ji, and R. Huang, “Accurate prediction of dielectric properties and band gaps in materials with a machine learning approach,” Appl. Phys. Lett., vol. 125, no. 15, pp.152905, Oct. 2024.
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2024
Insights into the ferroelectric orthorhombic phase formation in doped HfO2 thin films
Y. Wen, M. Wu, B. Cui, X. Wang, Y. Wu, Y.-C. Li, S. Ye, P. Ren, H.-L. Lu, R. Wang, Z. Ji, and R. Huang, “Insights into the ferroelectric orthorhombic phase formation in doped HfO2 thin films,” J. Appl. Phys., vol. 136, no. 12, pp.124105, Sept. 2024.
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