[1] J Wang, F Ma, W Liang et al. Electrical properties and applications of graphene, hexagonal boron nitride (h-BN), and graphene/h-BN heterostructures. Mater Today Phys, 2, 6(2017).

[2] A Ranjan, N Raghavan, S J O'Shea et al. Conductive atomic force microscope study of bipolar and threshold resistive switching in 2D hexagonal boron nitride films. Sci Rep, 8, 2854(2018).

[3] K Qian, R Y Tay, V C Nguyen et al. Hexagonal boron nitride thin film for flexible resistive memory applications. Adv Funct Mater, 26, 2176(2016).

[4] S Roy, X Zhang, A B Puthirath et al. Structure, properties and applications of two-dimensional hexagonal boron nitride. Adv Mater, 33, 2101589(2021).

[5] F Ahmed, S Heo, Z Yang et al. Dielectric dispersion and high field response of multilayer hexagonal boron nitride. Adv Funct Mater, 28, 1804235(2018).

[6] Y S Gani, D S L Abergel, E Rossi. Electronic structure of graphene nanoribbons on hexagonal boron nitride. Phys Rev B, 98, 205415(2018).

[7] G H Lee, Y J Yu, C Lee et al. Electron tunneling through atomically flat and ultrathin hexagonal boron nitride. Appl Phys Lett, 99, 243114(2011).

[8] C Pan, Y Ji, N Xiao et al. Coexistence of grain-boundaries-assisted bipolar and threshold resistive switching in multilayer hexagonal boron nitride. Adv Funct Mater, 27, 1604811(2017).

[9] B Yuan, X Liang, L Zhong et al. 150 nm × 200 nm cross-point hexagonal boron nitride-based memristors. Adv Electron Mater, 6, 1900115(2020).

[10] H Zhao, Z Dong, H Tian et al. Atomically thin femtojoule memristive device. Adv Mater, 29, 1703232(2017).

[11] K Zhu, X Liang, B Yuan et al. Graphene-boron nitride-graphene cross-point memristors with three stable resistive states. ACS Appl Mater Interfaces, 11, 37999(2019).

[12] X Wu, R Ge, P A Chen et al. Thinnest nonvolatile memory based on monolayer h-BN. Adv Mater, 31, 1806790(2019).

[13] Q Zhao, Z Xie, Y P Peng et al. Current status and prospects of memristors based on novel 2D materials. Mater Horiz, 7, 1495(2020).

[14] C Y Wang, C Wang, F Meng et al. 2D layered materials for memristive and neuromorphic applications. Adv Electron Mater, 6, 1901107(2019).

[15] T Shi, R Wang, Z Wu et al. A review of resistive switching devices: Performance improvement, characterization, and applications. Small Struct, 2, 2000109(2021).

[16] W Huh, D Lee, C H Lee. Memristors based on 2D materials as an artificial synapse for neuromorphic electronics. Adv Mater, 32, 2002092(2020).

[17] Q Tao, R Wu, Q Li et al. Reconfigurable electronics by disassembling and reassembling van der waals heterostructures. Nat Commun, 12, 1825(2021).

[18] S Li, M E Pam, Y Li et al. Wafer-scale 2D hafnium diselenide based memristor crossbar array for energy-efficient neural network hardware. Adv Mater, 33, 2103376(2021).

[19] L Sun, Y Zhang, G Han et al. Self-selective van der waals heterostructures for large scale memory array. Nat Commun, 10, 3161(2019).

[20] S Wang, C Y Wang, P Wang et al. Networking retinomorphic sensor with memristive crossbar for brain-inspired visual perception. Nat Sci Rev, 8, 172(2021).

[21] N Jain, F Yang, R B Jacobs-Gedrim et al. Extenuated interlayer scattering in double-layered graphene/hexagonal boron nitride heterostructure. Carbon, 126, 17(2018).

[22] H Wang, T Yu, J Zhao et al. Low-power memristors based on layered 2D SnSe/graphene materials. Sci China Mater, 64, 198(2021).

[23] H K He, F F Yang, R Yang. Flexible full two-dimensional memristive synapses of graphene/WSe_{2 – x}O_y/graphene. Phys Chem Chem Phys, 22, 20658(2020).

[24] M Wang, S Cai, C Pan et al. Robust memristors based on layered two-dimensional materials. Nat Electron, 1, 130(2018).

[25] C Liu, H Chen, S Wang et al. Two-dimensional materials for next-generation computing technologies. Nat Nanotechnol, 15, 545(2020).

[26] Y Hao, H Wu, Y Yang et al. Preface to the special issue on beyond moore: Resistive switching devices for emerging memory and neuromorphic computing. J Semicond, 42, 010101(2021).

[27] Y Shen, W Zheng, K Zhu et al. Variability and yield in h-BN-based memristive circuits: The role of each type of defect. Adv Mater, 33, 2103656(2021).

[28] Z Zhou, J Zhao, A P Chen et al. Designing carbon conductive filament memristor devices for memory and electronic synapse applications. Mater Horiz, 7, 1106(2020).

[29] B Standley, W Z Bao, H Zhang et al. Graphene-based atomic-scale switches. Nano Lett, 8, 3345(2008).

[30] Y Hattori, T Taniguchi, K Watanabe et al. Layer-by-layer dielectric breakdown of hexagonal boron nitride. ACS Nano, 9, 916(2015).

[31] A Ranjan, N Raghavan, F M Puglisi et al. Boron vacancies causing breakdown in 2D layered hexagonal boron nitride dielectrics. IEEE Electron Device Lett, 40, 1321(2019).

[32] C Jin, F Lin, K Suenaga et al. Fabrication of a freestanding boron nitride single layer and its defect assignments. Phys Rev Lett, 102, 195505(2009).

[33] L Weston, D Wickramaratne, M Mackoit et al. Native point defects and impurities in hexagonal boron nitride. Phys Rev B, 97, 214104(2018).

[34] A Zobelli, C P Ewels, A Gloter et al. Vacancy migration in hexagonal boron nitride. Phys Rev B, 75, 094104(2007).