1. Neuromporphic devices and computing-in-memory 

2. Neural network and deep learning 

3. Hardware AI systems

2004-2007 Shanghai Institute of Ceramics, Chinese Academy of Sciences, PhD

2007-2009 Institute of Physics, Chinese Academy of Sciences,  Postdoctoral

2009-2011 Institute of Physics, Chinese Academy of Sciences,  Associated Prof. 

2011-2012 Seoul National University, Korea, Psotdoctoral

2012-2014 RWTH Aachen University, Germany, Humboldt Research Fellow

2013.11-2014.1 University of Cambridge, UK, Humboldt European Visitor

2014-1018 Institute of Physics, Chinese Academy of Sciences,  Associated Prof. 

2018-at present Institute of Microelectronics, Chinese Academy of Sciences, Prof.

   

ResearchGate: https://www.researchgate.net/profile/D-S-Shang

1) Y. Li, S. Wang, Y. Zhao, S. Wang, W. Zhang, Y. He, N. Lin, B. Cui, X. Chen, S. Zhang, H. Jiang, P. Lin, X. Zhang, X. Qi, Z. Wang*, X. Xu*, D. S. Shang*, Q. Liu, K. T. Cheng, M. Liu, Pruning random resistive memory for optimizing analogue AI, Nature Communications accepted (2025)

2) D. S. Shang*, Q. Luo, Hybrid memory to empower edge AI, Nature Electronics (2025)

3) Y. Li, J. Lai, S. Wang, N. Lin, X. Zheng, W. Sun, D. Dong, X. Xu, H. Ma, F. Zhang, X. Qi, Z. Wang*, X. Xu*, D. S. Shang*, H. Wang, M. Liu, Brain-inspired in-memory data pruning and computing with TaOx mem-selectors, Advanced Materials 37, e02168 (2025)

4) H. Ren, Y. He, K. Wong, R. Bao, N. Lin*, Z. Wang*, D. S. Shang*, When Pipelined In-Memory Accelerators Meet Spiking Direct Feedback Alignment: A Co-Design for Neuromorphic Edge Computing, ACM/IEEE International Conference on Computer-Aided Design (ICCAD), October 26-30, Munich, Germany, (2025)

5) M. Xu, S. Wang, Y. He, Y. Li, W. Zhang, M. Yang, X. Qi, Z. Wang*, M. Xu*, D. S. Shang*, Q. Liu, X. Miao, M. Liu, Efficient modelling of ionic and electronic interactions by resistive memory-based reservoir graph neural network, Nature Computational Science, doi: 10.1038/s43588-025-00844-3 (2025)

6) H. Chen, J. Yang, J. Chen, S. Wang, S. Wang, Y. He, D. Wang, B. Cui, X. Tian, Y. Yu, X. Chen, Y. Lin, X. Wu, Y. Li, X. Zhang, N. Lin, M. Xu, Y. Li, X. Zhang, Z. Wang*, H. Wang*, D. S. Shang*, Q. Liu, K. Cheng, M. Liu, Continuous-time digital twin with analogue memristive neural ordinary differential equation solver, Science Advances 11, eadr7571 (2025)

7) B. Wang, S. Wang, N. Lin, Y. Li, Y. Yu, Y. Zhang, J. Yang, X. Wu, Y. He, S. Wang, R. Chen, G. Li, X. Qi, Z. Wang*, D. S. Shang*, Topology Optimization of Random Memristors for Input-Aware Dynamic SNN, Science Advances 11, eads5340 (2025)

8) S. Wang, Y. Gao, Y. Li, W. Zhang, Y. Yu, B. Wang, N. Lin, H. Chen, Y. Zhang, Y. Jiang, D. Wang, J. Chen, P. Dai, H. Jiang, P. Lin, X. Zhang, X. Qi, X. Xu, H. So, Z. Wang*, D. S. Shang*, Q. Liu, K. T. Cheng, M. Liu, Random resistive memory-based deep extreme point learning machine for unified visual processing, Nature Communications 16: 960 (2025)

9) N. Lin, Z. Wang, D. S. Shang, Energy-efficient multimodal zero-shot learning using in-memory reservoir computing, Nature Computational Science 5, 11 (2025)

10) N. Lin, S. Wang, Y. Li, B. Wang, S. Shi, Y. He, W. Zhang, Y. Yu, Y. Zhang, X. Qi, X. Chen, H. Jiang, X. Zhang, P. Lin, X. Xu, Q. Liu, Z. Wang*, D. S. Shang*, M. Liu, Resistive memory-based zero-shot liquid state machine for multimodal event data learning, Nature Computational Science 5, 37 (2025)

11) N. Lin, Y. Li, Y. He, S. Wang, H. Chen, K. Wong, C. Li, J. Yang, Y. Yu, M. Xu, Y. Han, R. Chen, X. Chen, X. Xu, J. Yang, D. S. Shang*, Z. Wang*, Re4PUF: A reliable, reconfigurable ReRAM-based PUF resilient to DNN and side channel attacks, 62st ACM/IEEE Design Automation Conference (DAC), June 22-25, San Francisco, CA (2025)

12) J. Yang, H. Chen, J. Chen, S. Wang, S. Wang, Y. Yu, B. Wang, N. Lin, X. Zhang, R. Chen, Z. Wang*, D. S. Shang*, H. Wang*, Q. Liu, M. Liu, Conditional diffusion model acceleration with first-demonstrated RRAM-based in-memory neural differential equation solver, IEEE International Electron Devices Meeting (IEDM), San Francisco, USA, Dec. 07-11, DOI: 10.1109/IEDM50854.2024.10873487 (2024)

13) H. Xu, D. S. Shang*, J. Tang*, Q. Luo, X. Xu, R. Liang, L. Pan, B. Gao, Q. Wang, D. He, Q. Liu*, M. Liu, H. Qian, H. Wu*, A biomimetic nociceptor based on a vertical multigate, multichannel neuromorphic transistor, ACS Nano 18, 30668 (2024)

14) S. Han, S. Liu, S. Du, M. Li, Z. Ye, X. Xu, Y. Li*, Z. Wang*, D. S. Shang*, CMN: A co-designed neural architecture search for efficient processing-in-memory-based mixture-of-experts, Science China: Information Sciences, 67, 200405 (2024).

15) F. Wang, W. Zhang, Z. Li, N. Lin, R. Bao, X. Xu, C. Dou, Z. Wang*, D. S. Shang*, In-memory search with learning to hash based on resistive memory for recommendation acceleration, npj Unconventional Computing 1: 10 (2024)

16) Y. Yu, S. Wang, M. Xu, W. Zhang, B. Wang, J. Yang, S. Wang, Y. Zhang, X. Wu, H. Cheng, D. Wang, X. Chen, N. Lin, X. Qi, D. S. Shang*, Z. Wang*, Random memristor-based dynamic graph CNN for efficient point cloud learning at the edge, npj Unconventional Computing, 1: 6 (2024)

17) Y. Zhang, W. Zhang, S. Wang, N. Lin, Y. Yu, Y. He, B. Wang, H. Jiang, P. Lin, X. Xu, X. Qi, Z. Wang*, X. Zhang*, D. S. Shang*, Q. Liu, K. T. Cheng, M. Liu, Semantic memory-based dynamic neural network using memristive ternary CIM and CAM for 2D and 3D vision, Science Advances, 10, eado1058 (2024).

18) N. Lin, S. Wang, X. Zhang, S. Wang, Y. He, W. Zhang, B. Wang, J. Li, M. Li, B. Cui, Y. Li, J. Chen, C. Xia, W. Xuan, X. Chen, D. S. Shang*, Z. Wang*, LSMR: Synerge randomness in liquid state machine and RRAM-based analog-digital accelerator, ACM/IEEE International Conference on Computer-Aided Design (ICCAD), October 27-31, New Jersey, (2024)

19) D. Dong, W. Zhang, Y. Xie, J. Yue, K. Ren, H. Huang, X. Zheng, W. Sun, J. Lai, S. Fan, H. Wang, Z. Yu, Z. Yao, X. Xu*, D. S. Shang*, M. Liu, Hardware Implementation of Next Generation Reservoir Computing with RRAM-Based Hybrid Digital-Analog System, Advanced Intelligent Systems, 6, 2400098 (2024).

20) W. Zhang, Z. Li, X. Zhang, F. Wang, S. Wang, N. Lin, Y. Li, J. Wang, J. Yue, C. Dou, X. Xu, Z. Wang*, D. S. Shang*, Fully binarized graph convolutional network accelerator based on in-memory computing with resistive random-access memory, Adv. Intel. Syst. 6, 2300784 (2024)

21) R. Fang, X. Li, K. Ren, W. Zhang, H. Xu, L. Wang*, D. S. Shang*, Improved dynamic characteristics of oxide electrolyte-gated transistor for time-delayed reservoir computing, Applied Physics Letters 124, 053505 (2024)

22) Z. Li, R. Bao, W. Zhang, F. Wang, J. Wang, R. Fang, H. Ren, N. Lin, J. Yue, C. Dou, Z. Wang*, D. S. Shang*, 2T2R RRAM-based in-memory hyperdimensional computing encoder for spatio-temporal signal processing, IEEE Transactions on Circuits and Systems II: Express Briefs 71, 2614 (2024)

23) R. Fang, S. Wang, W. Zhang, K. Ren, W. Sun, F. Wang, J. Lai, P. Zhang, X. Xu, Q. Luo, L. Li, Z. Wang*, D. S. Shang*, Oxide-based electrolyte-gated transistors with stable and tunable relaxation responses for deep time-delayed reservoir computing, Advanced Electronic Materials, 10, 2300653, (2024)

24) H. Xu, D. S. Shang*, Q. Luo, J. An, Y. Li, S. Wu, Z. Yao, W. Zhang, X. Xu, C. Dou, H. Jiang, L. Pan, X. Zhang, M. Wang, Z. Wang, J. Tang, Q. Liu, M. Liu, A low-power vertical dual-gate neurotransistor with short-term memory for high energy-efficient neuromorphic computing, Nature Communications 14:6385 (2023)

25) N. Jiang, J. Tang, W. Zhang, Y. Li, X. Chen, R. Fang, Z. Guo, F. Wang, J. Wang, Z. Li, C. He*, G. Zhang*, Z. Wang*, D. S. Shang*, Bio-inspired in-sensor reservoir computing for self-adaptive visual recognition with two-dimensional dual-mode phototransistors. Advanced Optical Materials 11, 2300271 (2023)

26) Y. Jiang, D. Wang, N. Lin, S. Shi, Y. Zhang, S. Wang, X. Chen, H. Chen, Y. Lin, K. Loong, J. Chen, Y. Li, R. Fang, D. S. Shang*, Q. Wang*, H. Yu*, Z. Wang*, Spontaneous Threshold Lowering Neuron using Second-Order Diffusive Memristor for Self-Adaptive Spatial Attention, Adv. Sci. 10, 2301323 (2023)

27) R. Fang, W. Zhang, K. Ren, P. Zhang, X. Xu, Z. Wang, D. S. Shang*, In-materio reservoir computing based on nanowire networks: fundamental, progress, and perspective, Materials Futures, 2, 022701 (2023)

28) S. Wang, Y. Li, D. Wang, W. Zhang, X. Chen, D. Dong, S. Wang, X. Zhang, P. Lin, C. Gallicchio, X. Xu, Q. Liu, K. Chen, Z. Wang*, D. S. Shang*, M. Liu, Echo state graph neural networks with analogue random resistive memory arrays, Nat. Mach. Intell. 5, 104 (2023)

29) D. Wang, D. Liu, Y. Lin, A. Yuan, W. Zhang, Y. Zhao, S. Wang, X. Chen, H. Chen, Y. Zhang, Y. Jiang, S. Shi, K. Loong, J. Chen, S. Wei, Q. Zhang, H. Yu, R. Xu*, D. S. Shang*, H. Zhang*, S. Zhang*, Z. Wang*, Structural plasticity-based hydrogel optical Willshaw model for one-shot on-the-fly edge learning, InfoMat 5: e12399 (2023)

30) Y. Li, J. Chen, L. Wang, W. Zhang, Z. Guo, J. Wang, Y. Han, Z. Li, F. Wang, C. Dou, X. Xu, J. Yang, Z. Wang,* D. S. Shang*, An ADC-less RRAM-based Computing-in-Memory Macro with binary CNN for Efficient Edge AI, IEEE Trans. Circuits Syst. II: Express Briefs 70, 1871 (2023)

31) Z. Dai, F. Xiang, C. He, Z. Wang, W. Zhang, Y. Li, J. Yue*, D. S. Shang*, A Scalable Small-Footprint Time-Space-Pipelined Architecture for Reservoir Computing, IEEE Trans. Circuits Syst. II: Express Briefs 70, 3069 (2023)

32) H. Xu, R. Fang, S. Wu, J. An, W. Zhang, C. Li, J. Lu, Y. Li, X. Xu, Y. Wang, Q. Liu, D. S. Shang,* Li-ion-based electrolyte-gated transistors with short write-read delay for neuromorphic computing, Adv. Electro. Mater. 9, 2200915 (2023)

33) 方仁瑞，任宽，郭泽钰，徐晗，张握瑜，王菲，张培文，李悦，尚大山*，基于氧化物基电解质栅控晶体管突触的关联学习，无机材料学报 38, 399 (2023)

34) H. Xu, J. Lu, Y. Li, R. Fang, W. Zhang, X. Xu, Y. Wang, Q. Liu, D. S. Shang*, Improvement of weight stability in Li-ion-based electrolyte-gated transistor synapse by silica protective process, Appl. Phys. Lett. 121, 113505 (2022)

35) W. Zhang, S. Wang, Y. Li, X. Xu, D. Dong, N. Jiang, F. Wang, Z. Guo, R. Fang, C. Dou, K. Ni, Z. Wang*, D. S. Shang*, M. Liu, Few-shot graph learning with robust and energy-efficient memory-augmented graph neural network (MAGNN) based on homogeneous computing-in-memory, IEEE Symposium on VLSI Technology and Circuits, IEEE Honolulu, HI, USA, C25-3, p224-225, DOI: 10.1109/VLSITechnologyandCir46769.2022.9830418 (2022).

36) W. Sun, W. Zhang, J. Yu, Y. Li, Z. Guo, J. Lai, D. Dong, X. Zheng, F. Wang, S. Fan, X. Xu*, D. S. Shang*, M. Liu, 3D reservoir computing with high area efficiency (5.12 TOPS/mm2) implemented by 3D dynamic memristor array for temporal signal processing, IEEE Symposium on VLSI Technology and Circuits, IEEE Honolulu, HI, USA, C25-2, DOI: 10.1109/VLSITechnologyandCir46769.2022.9830310 (2022).

37) Y. Li, W. Zhang, X. Xu, Y. He, D. Dong, N. Jiang, F. Wang, Z. Guo, S. Wang, C. Dou, Y. Liu, Z. Wang*, D. S. Shang*, Mixed-precision continual learning based on computational resistance random access memory, Adv. Intel. Syst. 4, 202200026 (2022).

38) S. Wang, H. Chen, W. Zhang, Y. Li, D. Wang, S. Shi, Y. Zhao, K. Loong, X. Chen, Y. Dong, Y. Zhang, Y. Jiang, C. Furqan, J. Chen, Q. Wang, X. Xu, G. Wang, H. Yu, D. S. Shang*, Z. Wang*, Convolutional echo state network with random memristors for spatiotemporal signal classification, Adv. Intel. Syst. 4, 202200027 (2022).

39) J. Lu, Y. Li, Z. Xuan, H. Xu, S. Wu, Z. Wang, S. Long, Q. Liu, D. S. Shang*, One transistor one electrolyte-gated transistor for supervised learning in spiking neural networks, IEEE Electron Dev. Lett. 43, 296 (2022)

40) Y. Li, H. Xu, J. Lu, Z. Wu, S. Wu, X. Zhang, Q. Liu, D. S. Shang*, Electrolyte-gated transistors with good retention for neuromorphic computing, Appl. Phys. Lett. 120, 021901 (2022)

41) 任宽，张握瑜，王菲，郭泽钰，尚大山*，基于忆阻器阵列的下一代储池计算，物理学报，71, 140701 (2022)

42) Y. Li, Z. Xuan, J. Lu, Z. Wang, X. Zhang, Z. Wu, Y. Wang, H. Xu, C. Dou, Y. Kang, Q. Liu, H. Lv, D. S. Shang,* One transistor one electrolyte-gated transistor based spiking neural network for power-efficient neuromorphic computing system, Adv. Func. Mater. 31, 2100042 (2021)

43) J. Yu, Y. Li, W. Sun, W. Zhang, Z. Gao, D. Dong, Z. Yu, Y. Zhao, J. Lai, Q. Ding, Q. Luo, C. Dou, Q. Zuo, Y. Zhao, S. Chen, R. Zou, H. Chen, Q. Wang, H. Lv, X. Xu*, D. S. Shang*, M. Liu, Energy efficient and robust reservoir computing system using ultrathin (3.5 nm) ferroelectric tunneling junctions for temporal data learning, IEEE Symposium on VLSI Technology and Circuits, IEEE, Kyoto, Japan, T16-4, (2021)

44) Y. Li, J. K. Lu, D. S. Shang,* Q. Liu, S. Y. Wu, Z. H. Wu, X. M. Zhang, J. G. Yang, Z. R. Wang, H. B. Lv, M. Liu, Oxide-based electrolyte-gated transistors for spatiotemporal information processing, Adv. Mater. 32, 2003018 (2020)

45) X. B. Bu, H. Xu, D. S. Shang,* Y. Li, H. B. Lv, Q. Liu, Ion-gated transistor: An enabler for sensing and computing integration, Adv. Intell. Syst. 2, 2000156 (2020)

46) C. S. Yang, D. S. Shang,* N. Liu, E. J. Fuller, S. Agrawal, A. A. Talin, Y. Q. Li, B. G. Shen, Y. Sun, All-solid-state synaptic transistor with ultralow conductance for neuromorphic computing, Adv. Func. Mater. 28, 1804170 (2018)

47) J. X. Shen, D. S. Shang,* Y. S. Chai, S. G. Wang, B. G. Shen, and Y. Sun, Mimic synaptic plasticity and neural network using memtranstors, Adv. Mater. 30, 1706717 (2018)

48) 尚大山*，孙阳，基于忆耦器实现神经突触可塑性和神经网络模拟，物理 47, 376 (2018)

49) 申见昕，尚大山*，孙阳，基于磁电耦合效应的基本电路元件和非易失性存储器，物理学报 67, 127501 (2018)

50) C. S. Yang, D. S. Shang,* N. Liu, G. Shi, X. Shen, R. C. Ru, Y. Q. Li, and Y. Sun, A synaptic transistor based on quasi-2D molybdenum oxide, Adv. Mater. 29, 1700906 (2017)

51) C. S. Yang, D. S. Shang,* Y. S. Chai, L. Q. Yan, B. G. Shen, and Y. Sun, Electrochemical-reaction-induced synaptic plasticity in MoOx-based solid state electrochemical cells, Phys. Chem. Chem. Phys. 19, 4190 (2017) (back cover)

52) J. X. Shen, D. S. Shang,* Y. S. Chai, Y. Wang, J. Z. Cong, S. P. Shen, L. Q. Yan, W. H. Wang, and Y. Sun, Nonvolatile Multi-level Memory and Boolean Logic Gates Based on a Single Ni/[Pb(Mg1/3Nb2/3)O3]0.7[PbTiO3]0.3/Ni Heterostructure, Phys. Rev. Applied 6, 064028 (2016)

53) P. P. Lu, D. S. Shang,* J. X. Shen, Y. S. Chai, C. S. Yang, K. Zhai, J. Z. Cong, S. P. Shen, and Y. Sun, Nonvolatile transtance change random access memory based on magnetoelectric P(VDF-TrFE)/Metglas heterostructures, Appl. Phys. Lett. 109, 252902 (2016)

54) C. S. Yang, D. S. Shang,* Y. S. Chai, L. Q. Yan, B. G. Shen, and Y. Sun, Moisture effects on the electrochemical reaction and resistance switching at Ag/molybdenum oxide interfaces, Phys. Chem. Chem. Phys. 18, 12466 (2016)

55) D. S. Shang,* S. Lee, and Y. Sun, Memristive switching in Cu/Si/Pt cells and its improvement in vacuum environment, Solid State Ionics 295, 1 (2016)

56) S. P. Shen, D. S. Shang,* Y. S. Chai, Y. Sun, Realization of a flux-driven memtranstor at room temperature, Chin. Phys. B 25, 027703 (2016)

57) D. S. Shang, Y. S. Chai, Z. X. Cao, J. Lu, and Y. Sun, Towards the Complete Relational Graph of Fundamental Circuit Elements, Chin. Phys. B 24, 068402 (2015) （本文荣获2018年度中国物理学会“最有影响力论文奖”一等奖）

58) D. S. Shang,* P. Li, T. Wang, E. Carria, J. Sun, B. Shen, T. Taubner, I. Valov, R. Waser, and M. Wuttig, Understanding the conductive channel evolution in Na:WO3-x-based planar devices, Nanoscale 7 6023 (2015)

59) D. S. Shang,* J. R. Sun, B. G. Shen, and M. Wuttig, Resistance switching in oxides with inhomogeneous conductivity, Chin. Phys. B 22, 067202 (2013) (Invited review)

60) L. L. Wei, D. S. Shang,* J. R. Sun, S. B. Lee, Z. G. Sun, and B. G. Shen, Gradual electroforming and memristive switching in Pt/CuOx/Si/Pt systems, Nanotechnology 24, 325202 (2013)

61) D. S. Shang,* L. Shi, J. R. Sun, and B. G. Shen, Visualization of the conductive channel in a planar resistance switching device based on electrochromic materials, J. Appl. Phys. 111, 053504 (2012).

62) D. S. Shang,* L. Shi, J. R. Sun, and B. G. Shen, Local resistance switching at grain and grain boundary surfaces of polycrystalline tungsten oxide films, Nanotechnology 22, 254008 (2011).

63) C. Y. Dong, D. S. Shang,* L. Shi, J. R. Sun, B. G. Shen, F. Zhu, R. W. Li, and W. Chen, Roles of silver oxide in the bipolar resistance switching devices with silver electrode, Appl. Phys. Lett. 98, 072107 (2011).

64) D. S. Shang,* L. Shi, J. R. Sun, B. G. Shen, F. Zhuge, R. W. Li, and Y. G. Zhao, Improvement of reproducible resistance switching in polycrystalline tungsten oxide films by in situ oxygen annealing, Appl. Phys. Lett. 96, 072103 (2010).

65) L. Shi, D. S. Shang,* J. R. Sun, and B. G. Shen, Flexible resistance memory devices based on Cu/ZnO:Mg/ITO structure, Phys. Status Solidi (Rapid Research Letters) 4, 344 (2010).

66) D. S. Shang, J. R. Sun, L. Shi, Z. H. Wang, J. Wang, and B. G. Shen, Electronic transport and colossal electroresistance in SrTiO3:Nb-based Schottky junctions, Appl. Phys. Lett. 94, 052105 (2009).

67) L. Shi, D. S. Shang,* J. R. Sun, and B. G. Shen, Bipolar Resistance Switching in Fully Transparent ZnO:Mg-Based Devices, Appl. Phys. Express 2, 101602 (2009).

68) D. S. Shang,* Q. Wang, L. D. Chen, W. D. Yu, X. M. Li, J. R. Sun, and B. G. Shen, Crystallinity dependence of resistance switching in La0.7Ca0.3MnO3 films grown by pulsed laser deposition, J. Appl. Phys. 105, 063511 (2009).

69) D. S. Shang, J. R. Sun, L. Shi, Z. H. Wang, and B. G. Shen, Resistance dependence of photovoltaic effect in Au/SrTiO3:Nb(0.5 wt %) Schottky junctions, Appl. Phys. Lett. 93, 172119 (2008).

70) D. S. Shang, J. R. Sun, L. Shi, and B. G. Shen, Photoresponse of the Schottky junction Au/SrTiO3:Nb in different resistive states, Appl. Phys. Lett. 93, 102106 (2008).

71) D. S. Shang, L. D. Chen, Q. Wang, Z. H. Wu, W. Q. Zhang, and X. M. Li, Reversible multilevel resistance switching of Ag-La0.7Ca0.3MnO3-Pt heterostructures, J. Mater. Res. 23, 302-307 (2008). (Outstanding Symposium Paper)

72) D. S. Shang, L. D. Chen, Q. Wang, Z. H. Wu, W. Q. Zhang, and X. M. Li, Asymmetric fatigue and its endurance improvement in resistance switching of Ag-La0.7Ca0.3MnO3-Pt heterostructures, J. Phys. D: Appl. Phys. 40, 5373-5376 (2007).

73) D. S. Shang, L. D. Chen, Q. Wang, W. Q. Zhang, Z. H. Wu, and X. M. Li, Temperature dependence of current-voltage characteristics of Ag-La0.7Ca0.3MnO3-Pt heterostructures, Appl. Phys. Lett. 89, 172102 (2006).

74) D. S. Shang, Q. Wang, L. D. Chen, R. Dong, X. M. Li, and W. Q. Zhang, Effect of carrier trapping on the hysteretic current-voltage characteristics in Ag/La0.7Ca0.3MnO3/Pt heterostructures, Phys. Rev. B 73, 245427 (2006).

1. Neuromporphic devices and computing-in-memory 

2. Neural network and deep learning 

3. Hardware AI systems