[1] S. Pi, et al.. Memristor crossbar arrays with 6-nm half-pitch and 2-nm critical dimension. Nat. Nanotechnol., 14 (2019), pp. 35-39.
[2] Y. Kim, et al.. A bioinspired flexible organic artificial afferent nerve. Science, 360 (2018), pp. 998-1003.
[3] D. Das, et al.. Experimental and theoretical evidence of ion engineering in nanocrystalline molybdenum disulfide memristors for non-filamentary switching actions and ultra-low-voltage synaptic features. J. Mater. Chem. C, 11 (2023), pp. 7782-7792.
[4] J.H. Baek, et al.. Two-terminal lithium-mediated artificial synapses with enhanced weight modulation for feasible hardware neural networks. Nano-Micro Lett., 15 (2023), p. 69.
[5] T. Miao, et al.. Multisensory synapses based on Fe3O4/graphene transistors for neuromorphic computing. J. Mater. Chem. C, 11 (2023), pp. 7732-7739.
[6] J.B. Roldan, et al.. Spiking neural networks based on two-dimensional materials.. npj 2D Mater. Appl., 6 (2022), p. 63.
[7] M. Rao, et al.. Thousands of conductance levels in memristors integrated on CMOS. Nature, 615 (2023), pp. 823-829.
[8] D.-C. Hu, R. Yang, L. Jiang, X. Guo. Memristive synapses with photoelectric plasticity realized in ZnO1-x/AlOy heterojunction. ACS Appl. Mater. Interfaces, 10 (2018), pp. 6463-6470.
[9] H. Cho, et al.. Double-floating-gate van der Waals transistor for high-precision synaptic operations. ACS Nano, 17 (2023), pp. 7384-7393.
[10] R. Li, et al.. Multi-modulated optoelectronic memristor based on Ga2O3/MoS2 heterojunction for bionic synapses and artificial visual system. Nano Energy, 111 (2023), p. 108398.
[11] G. Han, J. Seo, H. Kim, D. Lee. Role of the electrolyte layer in CMOS-compatible and oxide-based vertical three-terminal ECRAM. J. Mater. Chem. C, 11 (2023), pp. 5167-5173.
[12] X. Han, et al.. Super-flexible, transparent synaptic transistors based on pullulan for neuromorphic electronics. IEEE Electron Device Lett., 44 (2023), pp. 606-609.
[13] P. Yao, et al.. Fully hardware-implemented memristor convolutional neural network. Nature, 577 (2020), pp. 641-646.
[14] Y. Zhang, et al.. A system hierarchy for brain-inspired computing. Nature, 586 (2020), pp. 378-384.
[15] P. Robin, N. Kavokine, L. Bocquet. Modeling of emergent memory and voltage spiking in ionic transport through angstrom-scale slits. Science, 373 (2021), pp. 687-691.
[16] Z. Guo, et al.. High-performance artificial synapse based on CVD-grown WSe2 flakes with intrinsic defects. ACS Appl. Mater. Interfaces, 15 (2023), pp. 19152-19162.
[17] M. Li, et al.. Boron nitride-mediated semiconductor nanonetwork for an ultralow-power fibrous synaptic transistor and C-reactive protein sensing. J. Mater. Chem. C, 11 (2023), pp. 5208-5216.
[18] J. Oh, S.M. Yoon. Resistive memory devices based on reticular materials for electrical information storage. ACS Appl. Mater. Interfaces, 13 (2021), pp. 56777-56792.
[19] Q. Lu, et al.. Low-dimensional-materials-based flexible artificial synapse: materials, devices, and systems. Nanomaterials, 13 (2023), p. 373.
[20] T.J. Raeber, et al.. Resistive switching and transport characteristics of an all-carbon memristor. Carbon, 136 (2018), pp. 280-285.
[21] K. Liao, et al.. Memristor based on inorganic and organic two-dimensional materials: mechanisms, performance, and synaptic applications. ACS Appl. Mater. Interfaces, 13 (2021), pp. 32606-32623.
[22] C. Gastaldi, et al.. Ferroelectric junctionless double-gate silicon-on-insulator FET as a tripartite synapse. IEEE Electron Device Lett., 44 (2023), pp. 678-681.
[23] M. Soliman, et al.. Photoferroelectric all-van-der-Waals heterostructure for multimode neuromorphic ferroelectric transistors. ACS Appl. Mater. Interfaces, 15 (2023), pp. 15732-15744.
[24] X. Yan, et al.. An artificial synapse based on La:BiFeO3 ferroelectric memristor for pain perceptual nociceptor emulation. Mater. Today Nano, 22 (2023), p. 100343.
[25] J. Shi, et al.. Evaluating charge-type of polyelectrolyte as dielectric layer in memristor and synapse emulation. Nanoscale Horiz., 8 (2023), pp. 509-515.
[26] J. Ren, et al.. Polyelectrolyte bilayer-based transparent and flexible memristor for emulating synapses. ACS Appl. Mater. Interfaces, 14 (2022), pp. 14541-14549.
[27] G.M. Matrone, et al.. Electrical and optical modulation of a PEDOT:PSS-based electrochemical transistor for multiple neurotransmitter-mediated artificial synapses. Adv. Mater. Technol., 8 (2023), p. 2201911.
[28] E. Ercan, et al.. Molecular template growth of organic heterojunctions to tailor visual neuroplasticity for high performance phototransistors with ultralow energy consumption. Nanoscale Horiz., 8 (2023), pp. 632-640.
[29] T. Zhang, R. Ai, W. Luo, X. Liu. Synaptic transistor based on PVK mixed with oxadiazole and its logic gate application. Org. Electron., 121 (2023), p. 106868.
[30] J. Lin, et al.. Design of all-phase-change-memory spiking neural network enabled by Ge-Ga-Sb compound. Sci. China Mater., 66 (2023), pp. 1551-1558.
[31] S.G. Sarwat, B. Kersting, T. Moraitis, V.P. Jonnalagadda, A. Sebastian. Phase-change memtransistive synapses for mixed-plasticity neural computations. Nat. Nanotechnol., 17 (2022), pp. 507-513.
[32] Y. Xu, et al.. Squeeze-printing ultrathin 2D gallium oxide out of liquid metal for forming-free neuromorphic memristors. ACS Appl. Mater. Interfaces, 15 (2023), pp. 25831-25837.
[33] P. Basnet, et al.. Asymmetric resistive switching of bilayer HfOx/AlOy and AlOy/HfOx memristors: the oxide layer characteristics and performance optimization for digital set and analog reset switching. ACS Appl. Electron. Mater., 5 (2023), pp. 1859-1865.
[34] G.K. Gupta, I.-J. Kim, Y. Park, M.-K. Kim, J.-S. Lee. Inorganic perovskite quantum dot-mediated photonic multimodal synapse. ACS Appl. Mater. Interfaces, 15 (2023), pp. 18055-18064.
[35] D.S. Assi, et al.. Low switching power neuromorphic perovskite devices with quick relearning functionality. Adv. Electron. Mater., 9 (2023), p. 2300285.
[36] Z. Xue, et al.. Halide perovskite photoelectric artificial synapses: materials, devices, and applications. Nanoscale, 15 (2023), pp. 4653-4668.
[37] J. Ren, H. Shen, Z. Liu, M. Xu, D. Li. Artificial synapses based on WSe2 homojunction via vacancy migration. ACS Appl. Mater. Interfaces, 14 (2022), pp. 21141-21149.
[38] Y. Wang, et al.. Optogenetics-inspired fluorescent synaptic devices with nonvolatility. ACS Nano, 17 (2023), pp. 3696-3704.
[39] Z. Shen, et al.. Ultralow-power consumption photonic synapse transistors based on organic array films fabricated using a particular prepatterned-guided crystallizing strategy. J. Mater. Chem. C, 11 (2023), pp. 3213-3226.
[40] D. Wu, Q. Zhang, X. Wang, B. Zhang. Interface-confined synthesis of a nonplanar redox-active covalent organic framework film for synaptic memristors. Nanoscale, 15 (2023), pp. 2726-2733.
[41] T.S. Rao, S. Kundu, B. Bannur, S.J. George, G.U. Kulkarni. Emulating Ebbinghaus forgetting behavior in a neuromorphic device based on 1D supramolecular nanofibres. Nanoscale, 15 (2023), pp. 7450-7459.
[42] E. Lee, et al.. Realizing electronic synapses by defect engineering in polycrystalline two-dimensional MoS2 for neuromorphic computing. ACS Appl. Mater. Interfaces, 15 (2023), pp. 15839-15847.
[43] Y. Zhao, et al.. A high linearity and energy-efficient artificial synaptic device based on scalable synthesized MoS2. J. Mater. Chem. C, 11 (2023), pp. 5616-5624.
[44] Y. Zhao, et al.. Side chain engineering enhances the high-temperature resilience and ambient stability of organic synaptic transistors for neuromorphic applications. Nano Energy, 104 (2022), p. 107985.
[45] Z. Feng, et al.. Organic memory devices and synaptic simulation based on indacenodithienothiophene (IDTT) copolymers with improved planarity. J. Mater. Chem. C, 10 (2022), pp. 16604-16613.
[46] L. Jiang, et al.. Deep ultraviolet light stimulated synaptic transistors based on poly(3-hexylthiophene) ultrathin films. ACS Appl. Mater. Interfaces, 14 (2022), pp. 11718-11726.
[47] M.-K. Song, et al.. Tyrosine-mediated analog resistive switching for artificial neural networks. Nano Res., 16 (2023), pp. 858-864.
[48] M.-K. Song, et al.. Humidity-induced synaptic plasticity of ZnO artificial synapses using peptide insulator for neuromorphic computing. J. Mater. Sci. Technol., 119 (2022), pp. 150-155.
[49] M. Hosseini, et al.. DNA aerogels and DNA-wrapped CNT aerogels for neuromorphic applications. Mater. Today Bio, 16 (2022), p. 100440.
[50] K. He, et al.. Artificial neural pathway based on a memristor synapse for optically mediated motion learning. ACS Nano, 16 (2022), pp. 9691-9700.
[51] H. Kim, et al.. Shape-deformable and locomotive MXene (Ti3C2Tx)-encapsulated magnetic liquid metal for 3D-motion-adaptive synapses. Adv. Funct. Mater., 33 (2023), p. 2210385.
[52] M. M.H. Tanim, Z. Templin, K. Hood, J. Jiao, F. Zhao. A natural organic artificial synaptic device made from a honey and carbon nanotube admixture for neuromorphic computing. Adv. Mater. Technol., 8 (2023), p. 2202194.
[53] L. Wang, T. Yang, Y. Ju, D. Wen. First-principles study of the electronic properties of egg albumen optoelectronic artificial synapses by carbon nanotube insertion.
[54] Z. Zhao, et al.. Redox-active azulene-based 2D conjugated covalent organic framework for organic memristors. Angew. Chem. - Int. Ed., 62 (2023), Article e202217249.
[55] N.B. Mullani, et al.. Surface modification of a titanium carbide MXene memristor to enhance memory window and low-power operation. Adv. Funct. Mater., 33 (2023), p. 2300343.
[56] Y. Cao, H. Hao, L. Chen, Y. Yang. Recent advances of carbon dot-based memristors: Mechanisms, devices, and applications. Appl. Mater. Today, 36 (2024), p. 102032.
[57] A. Krishnaprasad, et al.. Graphene/MoS2/SiOx memristive synapses for linear weight update.. npj 2D Mater. Appl., 7 (2023), p. 22.
[58] X. Yan, et al.. A new memristor with 2D Ti3C2Tx MXene flakes as an artificial bio-synapse. Small, 15 (2019), p. 1900107.
[59] Q. Tian, et al.. Temperature-modulated switching behaviors of diffusive memristor for biorealistic emulation of synaptic plasticity. Appl. Phys. Lett., 122 (2023), p. 153502.
[60] K. A.S. Fernando, et al.. Carbon quantum dots and applications in photocatalytic energy conversion. ACS Appl. Mater. Interfaces, 7 (2015), pp. 8363-8376.
[61] G.B. Novais, et al.. Isoflavones-functionalized single-walled and multi-walled carbon nanotubes: synthesis and characterization of new nanoarchitetonics for biomedical uses. J. Mol. Struct., 1294 (2023), p. 136351.
[62] H. Wang, et al.. Synthesis of NiCo2O4 nanoneedles on rGO for asymmetric supercapacitors. J. Electron. Mater., 50 (2021), pp. 4196-4206.
[63] X. Yan, et al.. Highly improved performance in Zr0.5Hf0.5O2 films inserted with graphene oxide quantum dots layer for resistive switching non-volatile memory. J. Mater. Chem. C, 5 (2017), pp. 11046-11052.
[64] J. Jang, et al.. Knitted strain sensor with carbon fiber and aluminum-coated yarn, for wearable electronics. J. Mater. Chem. C, 9 (2021), pp. 16440-16449.
[65] X. Zhang, et al.. Tunable resistive switching in 2D MXene Ti3C2 nanosheets for non-volatile memory and neuromorphic computing. ACS Appl. Mater. Interfaces, 14 (2022), pp. 44614-44621.
[66] C. Yang, et al.. Photoelectric memristor-based machine vision for artificial intelligence applications. ACS Mater. Lett., 5 (2023), pp. 504-526.
[67] X. Feng, et al.. A novel nonvolatile memory device based on oxidized Ti3C2Tx MXene for neurocomputing application. Carbon, 205 (2023), pp. 365-372.
[68] Y. Cao, et al.. Neuromorphic visual artificial synapse in-memory computing systems based on GeOx-coated MXene nanosheets. Nano Energy, 112 (2023), p. 108441.
[69] H. Wan, et al.. Multimodal artificial neurological sensory-memory system based on flexible carbon nanotube synaptic transistor. ACS Nano, 15 (2021), pp. 14587-14597.
[70] M. Bacon, S.J. Bradley, T. Nann. Graphene quantum dots. Part. Part. Syst. Charact., 31 (2014), pp. 415-428.
[71] W. Chen, et al.. Construction of sugarcane bagasse-derived porous and flexible carbon nanofibers by electrospinning for supercapacitors. Ind. Crops Prod., 170 (2021), p. 113700.
[72] H. Yang, et al.. Nanocellulose-graphene composites: preparation and applications in flexible electronics. Int. J. Biol. Macromol., 253 (2023), p. 126903.
[73] M. Gupta, A. Verma, P. Chaudhary, B.C. Yadav. MXene and their integrated composite-based acetone sensors for monitoring of diabetes. Mater. Adv., 4 (2023), pp. 3989-4010.
[74] M. Serda, J. Korzuch, D. Dreszer, M. Krzykawska-Serda, R. Musio. Interactions between modified fullerenes and proteins in cancer nanotechnology. Drug Discov. Today, 28 (2023), p. 103704.
[75] A. Kaur, K. Pandey, R. Kaur, N. Vashishat, M. Kaur. Nanocomposites of carbon quantum dots and graphene quantum dots: environmental applications as sensors. Chemosensors, 10 (2022), p. 367.
[76] L. Tian, et al.. Carbon quantum dots for advanced electrocatalysis. J. Energy Chem., 55 (2021), pp. 279-294.
[77] A.B. Mishra, R. Thamankar. Artificial synapse based on carbon quantum dots dispersed in indigo molecular layer for neuromorphic applications. APL Mater., 11 (2023), p. 041122.
[78] W. Li, et al.. Carbon-quantum-dots-loaded ruthenium nanoparticles as an efficient electrocatalyst for hydrogen production in alkaline media. Adv. Mater., 30 (2018), p. 1800676.
[79] X. Xu, et al.. Electrophoretic analysis and purification of fluorescent single-walled carbon nanotube fragments. J. Am. Chem. Soc., 126 (2004), pp. 12736-12737.
[80] C. Donate-Buendia, et al.. Fabrication by laser irradiation in a continuous flow jet of carbon quantum dots for fluorescence imaging. ACS Omega, 3 (2018), pp. 2735-2742.
[81] F. Kazemizadeh, R. Malekfar, P. Parvin. Pulsed laser ablation synthesis of carbon nanoparticles in vacuum. J. Phys. Chem. Solids, 104 (2017), pp. 252-256.
[82] Q. Zhang, X. Sun, H. Ruan, K. Yin, H. Li. Production of yellow-emitting carbon quantum dots from fullerene carbon soot. Sci. China Mater., 60 (2017), pp. 141-150.
[83] J. Zhou, et al.. An electrochemical avenue to blue luminescent nanocrystals from multiwalled carbon nanotubes (MWCNTs). J. Am. Chem. Soc., 129 (2007), pp. 744-745.
[84] H. Zhu, et al.. Microwave synthesis of fluorescent carbon nanoparticles with electrochemiluminescence properties.
[85] J. Bian, et al.. Carbon dot loading and TiO2 nanorod length dependence of photoelectrochemical properties in carbon dot/TiO2 nanorod array nanocomposites. ACS Appl. Mater. Interfaces, 6 (2014), pp. 4883-4890.
[86] V. Sharma, P. Tiwari, S.M. Mobin. Sustainable carbon-dots: recent advances in green carbon dots for sensing and bioimaging. J. Mater. Chem. B, 5 (2017), pp. 8904-8924.
[87] Z.-G. Gu, et al.. MOF-templated synthesis of ultrasmall photoluminescent carbon-nanodot arrays for optical applications. Angew. Chem. - Int. Ed., 56 (2017), pp. 6853-6858.
[88] J. Shen, Y. Zhu, C. Chen, X. Yang, C. Li. Facile preparation and upconversion luminescence of graphene quantum dots. Chem. Commun., 47 (2011), pp. 2580-2582.
[89] J. Peng, et al.. Graphene quantum dots derived from carbon fibers. Nano Lett., 12 (2012), pp. 844-849.
[90] Z. Luo, et al.. Microwave-assisted preparation of white fluorescent graphene quantum dots as a novel phosphor for enhanced white-light-emitting diodes. Adv. Funct. Mater., 26 (2016), pp. 2739-2744.
[91] C.K. Chua, et al.. Synthesis of strongly fluorescent graphene quantum dots by cage-opening buckminsterfullerene. ACS Nano, 9 (2015), pp. 2548-2555.
[92] M. H.M. Facure, R. Schneider, L.A. Mercante, D.S. Correa. Rational hydrothermal synthesis of graphene quantum dots with optimized luminescent properties for sensing applications. Mater. Today Chem., 23 (2022), p. 100755.
[93] S.Y. Park, et al.. Photoluminescent green carbon nanodots from food-waste-derived sources: large-scale synthesis, properties, and biomedical applications. ACS Appl. Mater. Interfaces, 6 (2014), pp. 3365-3370.
[94] S. Zhuo, M. Shao, S.-T. Lee. Upconversion and downconversion fluorescent graphene quantum dots: ultrasonic preparation and photocatalysis. ACS Nano, 6 (2012), pp. 1059-1064.
[95] M. Buzaglo, M. Shtein, O. Regev. Graphene quantum dots produced by microfluidization. Chem. Mater., 28 (2016), pp. 21-24.
[96] Y. Dong, et al.. Blue luminescent graphene quantum dots and graphene oxide prepared by tuning the carbonization degree of citric acid. Carbon, 50 (2012), pp. 4738-4743.
[97] L. Wang, et al.. Gram-scale synthesis of single-crystalline graphene quantum dots with superior optical properties. Nat. Commun., 5 (2014), p. 5357.
[98] L. Tang, et al.. Deep ultraviolet photoluminescence of water-soluble self-passivated graphene quantum dots. ACS Nano, 6 (2012), pp. 5102-5110.
[99] S.-J. Jeon, et al.. Modulating the photocatalytic activity of graphene quantum dots via atomic tailoring for highly enhanced photocatalysis under visible light. Adv. Funct. Mater., 26 (2016), pp. 8211-8219.
[100] Y. Deng, L. Liu, J. Li, L. Gao. Sensors based on the carbon nanotube field-effect transistors for chemical and biological analyses. Biosensors, 12 (2022), p. 776.
[101] B. Cho, et al.. Nonvolatile analog memory transistor based on carbon nanotubes and C60 molecules. Small, 9 (2013), pp. 2283-2287.
[102] Y. Bai, et al.. Stacked 3D RRAM array with graphene/CNT as edge electrodes. Sci. Rep., 5 (2015), p. 13785.
[103] K. Turcheniuk, R. Boukherroub, S. Szunerits. Gold-graphene nanocomposites for sensing and biomedical applications. J. Mater. Chem. B, 3 (2015), pp. 4301-4324.
[104] N. Arora, N.N. Sharma. Arc discharge synthesis of carbon nanotubes: comprehensive review. Diam. Relat. Mater., 50 (2014), pp. 135-150.
[105] S.-K. Chang-Jian, J.-R. Ho, J.-W.J. Cheng. Fabrication of transparent double-walled carbon nanotubes flexible matrix touch panel by laser ablation technique. Opt. Laser Technol., 43 (2011), pp. 1371-1376.
[106] X. Wu, H. Yin, Q. Li. Ablation and patterning of carbon nanotube film by femtosecond laser irradiation. Appl. Sci., 9 (2019), p. 3045.
[107] L. Ding, et al.. Selective growth of well-aligned semiconducting single-walled carbon nanotubes. Nano Lett., 9 (2009), pp. 800-805.
[108] F. Yang, et al.. Chirality-specific growth of single-walled carbon nanotubes on solid alloy catalysts. Nature, 510 (2014), pp. 522-524.
[109] X. Zhang, et al.. High-precision solid catalysts for investigation of carbon nanotube synthesis and structure. Sci. adv., 6 (2020), p. eabb6010.
[110] J. Zhao, et al.. Structural improvement of CVD multi-walled carbon nanotubes by a rapid annealing process. Diam. Relat. Mater., 25 (2012), pp. 24-28.
[111] J. Wu, K. Liang, C. Yang, J. Zhu, D. Liu. Synthesis of carbon nanotubes on metal mesh in inverse diffusion biofuel flames. Fuller. Nanotub. Carbon Nanostructures, 27 (2019), pp. 77-86.
[112] K. Li, et al.. Carbon-based fibers: fabrication, characterization and application. Adv. Fiber Mater., 4 (2022), pp. 631-682.
[113] Z. Liu, et al.. Multifunctional nanofiber mat for high temperature flexible sensors based on electrospinning. J. Alloys Compd., 941 (2023), p. 168959.
[114] C. Che, et al.. A dual-template strategy assisted synthesis of porous coal-based carbon nanofibers for supercapacitors. Diam. Relat. Mater., 137 (2023), p. 110140.
[115] A. Elhassan, I. Abdalla, J. Yu, Z. Li, B. Ding. Microwave-assisted fabrication of sea cucumber-like hollow structured composite for high-performance electromagnetic wave absorption. Chem. Eng. J., 392 (2020), p. 123646.
[116] Y. Jin, et al.. Low-temperature synthesis and characterization of helical carbon fibers by one-step chemical vapour deposition. Appl. Surf. Sci., 324 (2015), pp. 438-442.
[117] Q.A. Vu, et al.. A high-on/off-ratio floating-gate memristor array on a flexible substrate via CVD-grown large-area 2D layer stacking. Adv. Mater., 29 (2017), p. 1703363.
[118] B. Liu, et al.. Dimensionally anisotropic graphene with high mobility and a high on-off ratio in a three-terminal RRAM device. Mater. Chem. Front., 4 (2020), pp. 1756-1763.
[119] K.S. Novoselov, et al.. Electric field effect in atomically thin carbon films. Science, 306 (2004), pp. 666-669.
[120] Y. Zhu, et al.. Graphene and graphene oxide: synthesis, properties, and applications. Adv. Mater., 22 (2010), pp. 3906-3924.
[121] A.N. Obraztsov. Making graphene on a large scale. Nat. Nanotechnol., 4 (2009), pp. 212-213.
[122] C. Ding, Y. Dai, F. Yang, X. Chu. A molecular dynamics study of the mechanical properties of the graphene/hexagonal boron nitride planar heterojunction for RRAM. Mater. Today Commun., 26 (2021), p. 101653.
[123] K. Kumari, A.D. Thakur, S.J. Ray. The effect of graphene and reduced graphene oxide on the resistive switching behavior of La0.7Ba0.3/MnO3. Mater. Today Commun., 26 (2021), p. 102040.
[124] J. Chen, B. Yao, C. Li, G. Shi. An improved Hummers method for eco-friendly synthesis of graphene oxide. Carbon, 64 (2013), pp. 225-229.
[125] H. Yu, B. Zhang, C. Bulin, R. Li, R. Xing. High-efficient synthesis of graphene oxide based on improved Hummers method. Sci. Rep., 6 (2016), p. 36143.
[126] C. Guo, et al.. Efficient synthesis of graphene oxide by Hummers method assisted with an electric field. Mater. Res. Express, 6 (2019), Article 055602.
[127] H. Saleem, M. Haneef, H.Y. Abbasi. Synthesis route of reduced graphene oxide via thermal reduction of chemically exfoliated graphene oxide. Mater. Chem. Phys., 204 (2018), pp. 1-7.
[128] R. Trusovas, et al.. Reduction of graphite oxide to graphene with laser irradiation. Carbon, 52 (2013), pp. 574-582.
[129] K. Ai, Y. Liu, L. Lu, X. Cheng, L. Huo. A novel strategy for making soluble reduced graphene oxide sheets cheaply by adopting an endogenous reducing agent. J. Mater. Chem., 21 (2011), pp. 3365-3370.
[130] S. Rai, R. Bhujel, J. Biswas, B.P. Swain. Biocompatible synthesis of rGO from ginger extract as a green reducing agent and its supercapacitor application. Bull. Mater. Sci., 44 (2021), p. 40.
[131] W.-J. Sun, Y.-Y. Zhao, X.-F. Cheng, J.-H. He, J.-M. Lu. Surface functionalization of single-layered Ti3C2Tx MXene and its application in multilevel resistive memory. ACS Appl. Mater. Interfaces, 12 (2020), pp. 9865-9871.
[132] Y. Wang, et al.. Manipulation of the electrical behaviors of Cu/MXene/SiO2/W memristor. Appl. Phys. Express, 12 (2019), p. 106504.
[133] G. Ding, et al.. Configurable multi-state non-volatile memory behaviors in Ti3C2 nanosheets. Nanoscale, 11 (2019), pp. 7102-7110.
[134] M. Tang, et al.. Surface terminations of MXene: synthesis, characterization, and properties. Symmetry, 14 (2022), p. 2232.
[135] T. Li, et al.. Fluorine-free synthesis of high-purity Ti3C2Tx (T=OH, O) via alkali treatment. Angew. Chem. - Int. Ed., 57 (2018), pp. 6115-6119.
[136] G. Li, L. Tan, Y. Zhang, B. Wu, L. Li. Highly efficiently delaminated single-layered MXene nanosheets with large lateral size. Langmuir, 33 (2017), pp. 9000-9006.
[137] J. Xuan, et al.. Organic-base-driven intercalation and delamination for the production of functionalized titanium carbide nanosheets with superior photothermal therapeutic performance. Angew. Chem. - Int. Ed., 55 (2016), pp. 14569-14574.
[138] A. Lipatov, et al.. Effect of synthesis on quality, electronic properties and environmental stability of individual monolayer Ti3C2 MXene flakes. Adv. Electron. Mater., 2 (2016), p. 1600255.
[139] M. Li, et al.. Element replacement approach by reaction with Lewis acidic molten salts to synthesize nanolaminated MAX phases and MXenes. J. Am. Chem. Soc., 141 (2019), pp. 4730-4737.
[140] P. Urbankowski, et al.. Synthesis of two-dimensional titanium nitride Ti4N3(MXene). Nanoscale, 8 (2016), pp. 11385-11391.
[141] S. Yang, et al.. Fluoride-free synthesis of two-dimensional titanium carbide (MXene) using A binary aqueous system. Angew. Chem. - Int. Ed., 57 (2018), pp. 15491-15495.
[142] M. Shen, et al.. One-pot green process to synthesize MXene with controllable surface terminations using molten salts. Angew. Chem. - Int. Ed., 60 (2021), pp. 27013-27018.
[143] G. Khurana, N. Kumar, M. Chhowalla, J.F. Scott, R.S. Katiyar. Non-polar and complementary resistive switching characteristics in graphene oxide devices with gold nanoparticles: diverse approach for device fabrication. Sci. Rep., 9 (2019), p. 15103.
[144] L.-J. Yu, et al.. Stateful logic operations implemented with graphite resistive switching memory. IEEE Electron Device Lett., 39 (2018), pp. 607-609.
[145] B. Walters, M.V. Jacob, A. Amirsoleimani, M.R. Azghadi. A review of graphene-based memristive neuromorphic devices and circuits. Adv. Intell. Syst., 5 (2023), p. 2300136.
[146] N. He, et al.. Inserted effects of MXene on switching mechanisms and characteristics of SiO2-based memristor: experimental and first-principles investigations. IEEE Trans. Electron Devices, 69 (2022), pp. 3688-3693.
[147] Y. Lin, et al.. Photoreduced nanocomposites of graphene oxide/N-doped carbon dots toward all-carbon memristive synapses. NPG Asia Mater., 12 (2020), p. 64.
[148] C. He, et al.. Tunable electroluminescence in planar graphene/SiO2 memristors. Adv. Mater., 25 (2013), pp. 5593-5598.
[149] C. Zang, et al.. Uniform self-rectifying resistive random-access memory based on an MXene-TiO2 Schottky junction. Nanoscale Adv., 4 (2022), pp. 5062-5069.
[150] Y.-J. Huang, S.-C. Lee. Graphene/h-BN heterostructures for vertical architecture of RRAM design. Sci. Rep., 7 (2017), p. 9679.
[151] M.A. Villena, et al.. SIM2RRAM:: a physical model for RRAM devices simulation. J. Comput. Electron., 16 (2017), pp. 1095-1120.
[152] T.F. Wu, et al.. Hyperdimensional computing exploiting carbon nanotube FETs, resistive RAM, and their monolithic 3D integration. IEEE J. Solid-State Circuits, 53 (2018), pp. 3183-3196.
[153] R. Zhang, et al.. High performance of graphene oxide-doped silicon oxide-based resistance random access memory. Nanoscale Res. Lett., 8 (2013), p. 497.
[154] J.-Y. Choi, et al.. Preparation of polyimide/graphene oxide nanocomposite and its application to nonvolatile resistive memory device. Polymers, 10 (2018), p. 901.
[155] Y. Chen, et al.. Realization of artificial neuron using MXene Bi-directional threshold switching memristors. IEEE Electron Device Lett., 40 (2019), pp. 1686-1689.
[156] N. He, et al.. V2C-Based memristor for applications of low power electronic synapse. IEEE Electron Device Lett., 42 (2021), pp. 319-322.
[157] C. Zhang, et al.. Carbon nanodots memristor: an emerging candidate toward artificial biosynapse and human sensory perception system. Adv. Sci., 10 (2023), p. 2207229.
[158] L. Li, et al.. Improved uniformity in resistive switching behaviors based on PMMA films with embedded carbon quantum dots. Appl. Phys. Lett., 118 (2021), p. 222108.
[159] M. Qi, et al.. Intensity-modulated LED achieved through integrating p-GaN/n-ZnO heterojunction with multilevel RRAM. Appl. Phys. Lett., 113 (2018), p. 223503.
[160] L. Wang, Y. Zhang, P. Zhang, D. Wen. Flexible transient resistive memory based on biodegradable composites. Nanomaterials, 12 (2022), p. 3531.
[161] N.-J. Kuo, et al.. One-pot synthesis of hydrophilic and hydrophobic N-doped graphene quantum dots via exfoliating and disintegrating graphite flakes. Sci. Rep., 6 (2016), p. 30426.
[162] S. Ali, J. Bae, C.H. Lee, K.H. Choi, Y.H. Doh. All-printed and highly stable organic resistive switching device based on graphene quantum dots and polyvinylpyrrolidone composite. Org. Electron., 25 (2015), pp. 225-231.
[163] L. Wang, W. Li, D. Wen. Soybean-based memristor for multilevel data storage and emulation of synaptic behavior. Microelectron. Eng., 267-268 (2023), p. 111911.
[164] J. Zhao, et al.. Charge trap-based carbon nanotube transistor for synaptic function mimicking. Nano Res., 14 (2021), pp. 4258-4263.
[165] I.S. Esqueda, et al.. Aligned carbon nanotube synaptic transistors for large-scale neuromorphic computing. ACS Nano, 12 (2018), pp. 7352-7361.
[166] L. Wang, J. Yang, Y. Zhang, D. Wen. Dual-Tunable memristor based on carbon nanotubes and graphene quantum dots. Nanomaterials, 11 (2021), p. 2043.
[167] C.-L. Tsai, F. Xiong, E. Pop, M. Shim. Resistive random access memory enabled by carbon nanotube crossbar electrodes. ACS Nano, 7 (2013), pp. 5360-5366.
[168] S.-Y. Min, W.-J. Cho. Resistive switching characteristic improvement in a single-walled carbon nanotube random network embedded hydrogen silsesquioxane thin films for flexible memristors. Int. J. Mol. Sci., 22 (2021), p. 3390.
[169] Z. Wang, et al.. Vacancy-induced resistive switching and synaptic behavior in flexible BST@Cf memristor crossbars. Ceram. Int., 46 (2020), pp. 21569-21577.
[170] S. Hu, et al.. Resistive switching behavior and mechanism in flexible TiO2@Cf memristor crossbars. Ceram. Int., 45 (2019), pp. 10182-10186.
[171] H. Wang, T. Yu, J. Zhao, S. Wang, X. Yan. Low-power memristors based on layered 2D SnSe/graphene materials. Sci. China Mater., 64 (2021), pp. 1989-1996.
[172] H. Jeon, et al.. Detection of oxygen ion drift in Pt/Al2O3/TiO2/Pt RRAM using interface-free single-layer graphene electrodes. Carbon, 75 (2014), pp. 209-216.
[173] L.-W. Wang, C.-W. Huang, K.-J. Lee, S.-Y. Chu, Y.-H. Wang. Multi-level resistive Al/Ga2O3/ITO switching devices with interlayers of graphene oxide for neuromorphic computing. Nanomaterials, 13 (2023), p. 1851.
[174] B. Chakrabarti, T. Roy, E.M. Vogel. Nonlinear switching with ultralow reset power in graphene-insulator-graphene forming-free resistive memories. IEEE Electron Device Lett., 35 (2014), pp. 750-752.
[175] R. Tian, et al.. Resistance switching characteristics of Ag/ZnO/graphene resistive random access memory. Vacuum, 207 (2023), p. 111625.
[176] J. Zhou, et al.. Flexible random resistive access memory devices with ferrocene-rGO nanocomposites for artificial synapses. J. Mater. Chem. C, 9 (2021), pp. 5749-5757.
[177] H. Xie, et al.. Modeling and simulation of resistive random access memory with graphene electrode. IEEE Trans. Electron Devices, 67 (2020), pp. 915-921.
[178] M.V. Jacob, D. Taguchi, M. Iwamoto, K. Bazaka, R.S. Rawat. Resistive switching in graphene-organic device: charge transport properties of graphene-organic device through electric field induced optical second harmonic generation and charge modulation spectroscopy. Carbon, 112 (2017), pp. 111-116.
[179] Y. Wang, L. Wu, G. Liu, L. Liu. Non-destructive photovoltaic reading of interface type memristors using graphene as transparent electrode. J. Alloys Compd., 740 (2018), pp. 273-277.
[180] H. Tian, et al.. Monitoring oxygen movement by Raman spectroscopy of resistive random access memory with a graphene-inserted electrode. Nano Lett., 13 (2013), pp. 651-657.
[181] J. Lee, C. Du, K. Sun, E. Kioupakis, W.D. Lu. Tuning ionic transport in memristive devices by graphene with engineered nanopores. ACS Nano, 10 (2016), pp. 3571-3579.
[182] K.-C. Chang, et al.. Origin of hopping conduction in graphene-oxide-doped silicon oxide resistance random access memory devices. IEEE Electron Device Lett., 34 (2013), pp. 677-679.
[183] H. Liu, et al.. Graphene oxide for nonvolatile memory application by using electrophoretic technique. Mater. Today Commun., 25 (2020), p. 101537.
[184] P.J. Jesuraj, R. Parameshwari, K. Jeganathan. Improved performance of graphene oxide based resistive memory devices through hydrogen plasma. Mater. Lett., 232 (2018), pp. 62-65.
[185] A.H. Jaafar, N.T. Kemp. Wavelength dependent light tunable resistive switching graphene oxide nonvolatile memory devices. Carbon, 153 (2019), pp. 81-88.
[186] X. Liu, et al.. Flexible transparent high-efficiency photoelectric perovskite resistive switching memory. Adv. Funct. Mater., 32 (2022), p. 2202951.
[187] Q. Yuan, N. He, Y. Wang, Y. Sun, D. Wen. Gate controlled resistive switching behavior of heterostructure in the Ni-Co layered double hydroxide/graphene oxide transistor. Appl. Surf. Sci., 596 (2022), p. 153608.
[188] H.T. Ngo, et al.. Low operating voltage resistive random access memory based on graphene oxide-polyvinyl alcohol nanocomposite thin films. J. Sci.: Adv. Mater. Devices, 5 (2020), pp. 199-206.
[189] J.M. Kim, S.W. Hwang. Bipolar resistive switching behavior of PVP-GQD/HfOx/ITO/graphene hybrid flexible resistive random access memory. Molecules, 26 (2021), p. 6758.
[190] B. Zhao, et al.. Reproducible and low-power multistate bio-memristor from interpenetrating network electrolyte design. Infomat, 4 (2022), Article e12350.
[191] S. Ling, et al.. Facile synthesis of MXene-Polyvinyl alcohol hybrid material for robust flexible memristor. J. Solid State Chem., 318 (2023), p. 123731.
[192] H. Wei, et al.. Redox MXene artificial synapse with bidirectional plasticity and hypersensitive responsibility. Adv. Funct. Mater., 31 (2021), p. 2007232.
[193] N. He, et al.. Demonstration of 2D MXene memristor: stability, conduction mechanism, and synaptic plasticity. Mater. Lett., 266 (2020), p. 127413.
[194] X. Lian, et al.. Electrical properties and biological synaptic simulation of Ag/MXene/SiO2/Pt RRAM devices. Electronics, 9 (2020), p. 2098.
[195] X. Lian, et al.. Resistance switching characteristics and mechanisms of MXene/SiO2 structure-based memristor. Appl. Phys. Lett., 115 (2019), Article 063501.
[196] F. Sun, et al.. Conjugated polymer-functionalized 2D MXene nanosheets for nonvolatile memory devices with high environmental stability. ACS Appl. Nano Mater., 6 (2023), pp. 7186-7195.
[197] X. Liu, et al.. Study on energy and information storage properities of 2D-MXene/polyimide composites. Compos. B: Eng., 241 (2022), p. 110014.
[198] Z. Xu, et al.. Ultrathin electronic synapse having high temporal/spatial uniformity and an Al2O3/graphene quantum dots/Al2O3 sandwich structure for neuromorphic computing. NPG Asia Mater., 11 (2019), p. 18.
[199] Y. Pei, Z. Zhou, A.P. Chen, J. Chen, X. Yan. A carbon-based memristor design for associative learning activities and neuromorphic computing. Nanoscale, 12 (2020), pp. 13531-13539.
[200] X. Yan, et al.. Graphene oxide quantum dots based memristors with progressive conduction tuning for artificial synaptic learning. Adv. Funct. Mater., 28 (2018), p. 1803728.
[201] C. Gao, et al.. A high-performance memristor device and its filter circuit application. Phys. Status Solidi - Rapid Res. Lett., 14 (2020), p. 2000389.
[202] H. Mao, et al.. MXene quantum dot/polymer hybrid structures with tunable electrical conductance and resistive switching for nonvolatile memory devices. Adv. Electron. Mater., 6 (2020), p. 1900493.
[203] A.S. Sokolov, et al.. Silver-adapted diffusive memristor based on organic nitrogen-doped graphene oxide quantum dots (N-GOQDs) for artificial biosynapse applications. Adv. Funct. Mater., 29 (2019), p. 1807504.
[204] M. Ali, A. Sokolov, M.J. Ko, C. Choi. Optically excited threshold switching synapse characteristics on nitrogen-doped graphene oxide quantum dots (N-GOQDs). J. Alloys Compd., 855 (2021), p. 157514.
[205] C. Wang, et al.. Memristive devices with highly repeatable analog states boosted by graphene quantum dots. Small, 13 (2017), p. 1603435.
[206] I.-J. Kim, M.-K. Kim, Y. Park, J.-S. Lee. Heterosynaptic plasticity emulated by liquid crystal-carbon nanotube composites with modulatory interneurons. ACS Appl. Mater. Interfaces, 12 (2020), pp. 27467-27475.
[207] Z. Wang, et al.. Vacancy-induced resistive switching and synaptic behavior in flexible BST@Cf memristor crossbars. Ceram. Int., 46 (2020), pp. 21569-21577.
[208] Q. Chen, et al.. Low power parylene-based memristors with a graphene barrier layer for flexible electronics applications. Adv. Electron. Mater., 5 (2019), p. 1800852.
[209] Y. Li, et al.. A robust graphene oxide memristor enabled by organic pyridinium intercalation for artificial biosynapse application. Nano Res., 16 (2023), pp. 11278-11287.
[210] P.-K. Yang, et al.. Fully transparent resistive memory employing graphene electrodes for eliminating undesired surface effects. Proc. IEEE, 101 (2013), pp. 1732-1739.
[211] J. Liu, et al.. Fabrication of flexible, all-reduced graphene oxide non-volatile memory devices. Adv. Mater., 25 (2013), pp. 233-238.
[212] Y. Kim, S.-B. Jeon, B.C. Jang. Graphene oxide-based memristive logic-in-memory circuit enabling normally-off computing. Nanomaterials, 13 (2023), p. 710.
[213] M. Zhang, et al.. Exploration of threshold and resistive-switching behaviors in MXene/BaFe12O19 ferroelectric memristors. Appl. Surf. Sci., 613 (2023), p. 155956.
[214] S. Fatima, M.W. Hakim, D. Akinwande, S. Rizwan. Self-generated double transition-metal carbide MXene/Graphene oxide trilayered memristors for flexible electronics. Mater. Today Phys., 26 (2022), p. 100730.
[215] X. Zhang, et al.. Tunable resistive switching in 2D MXene Ti3C2 nanosheets for non-volatile memory and neuromorphic computing. ACS Appl. Mater. Interfaces, 14 (2022), pp. 44614-44621.
[216] T. Yu, et al.. Hybridization state transition-driven carbon quantum dot (CQD)-based resistive switches for bionic synapses. Mater. Horiz., 10 (2023), pp. 2181-2190.
[217] M. Ali, A. Sokolov, M.J. Ko, C. Choi. Optically excited threshold switching synapse characteristics on nitrogen-doped graphene oxide quantum dots (N-GOQDs). J. Alloys Compd., 855 (2021), p. 157514.
[218] X. Li, et al.. Memristors based on carbon dots for learning activities in artificial biosynapse applications. Mater. Chem. Front., 6 (2022), pp. 1098-1106.
[219] C. Wang, et al.. Memristive devices with highly repeatable analog states boosted by graphene quantum dots. Small, 13 (2017), p. 1603435.
[220] M.V. Il’ina, O.I. Il’in, O.I. Osotova, V.A. Smirnov, O.A. Ageev. Memristors based on strained multi-walled carbon nanotubes. Diam. Relat. Mater., 123 (2022), p. 108858.
[221] P. Feng, et al.. Printed neuromorphic devices based on printed carbon nanotube thin-film transistors. Adv. Funct. Mater., 27 (2017), p. 1604447.
[222] Z. Liu, et al.. Photoresponsive transistors based on lead-free perovskite and carbon nanotubes. Adv. Funct. Mater., 30 (2020), p. 1906335.
[223] T. Wang, et al.. Reconfigurable neuromorphic memristor network for ultralow-power smart textile electronics. Nat. Commun., 13 (2022), p. 7432.
[224] W. Talsma, et al.. Synaptic plasticity in semiconducting single-walled carbon nanotubes transistors. Adv. Intell. Syst., 2 (2020), p. 2000154.
[225] K. Kim, C.-L. Chen, Q. Truong, A.M. Shen, Y. Chen. A carbon nanotube synapse with dynamic logic and learning. Adv. Mater., 25 (2013), pp. 1693-1698.
[226] R. Liu, et al.. Neuromorphic properties of flexible carbon nanotube/polydimethylsiloxane nanocomposites. Adv. Compos. Hybrid Mater., 6 (2023), p. 14.
[227] I. Varun, D. Bharti, A.K. Mahato, V. Raghuwanshi, S.P. Tiwari. High-performance flexible resistive RAM with PVP:GO composite and ultrathin HfOx hybrid bilayer. IEEE Trans. Electron Devices, 67 (2020), pp. 949-954.
[228] M.T. Sharbati, et al.. Low-power, electrochemically tunable graphene synapses for neuromorphic computing. Adv. Mater., 30 (2018), p. 1802353.
[229] B. Liu, et al.. Programmable synaptic metaplasticity and below femtojoule spiking energy realized in graphene-based neuromorphic memristor. ACS Appl. Mater. Interfaces, 10 (2018), pp. 20237-20243.
[230] S. Yuan, et al.. Robust and low-power-consumption black phosphorus-graphene artificial synaptic devices. ACS Appl. Mater. Interfaces, 14 (2022), pp. 21242-21252.
[231] K. Wang, Y. Jia, X. Yan. Neuro-receptor mediated synapse device based on the crumpled MXene Ti3C2Tx nanosheets. Adv. Funct. Mater., 31 (2021), p. 2104304.
[232] K. Wang, J. Chen, X. Yan. MXene Ti3C2 memristor for neuromorphic behavior and decimal arithmetic operation applications. Nano Energy, 79 (2021), p. 105453.
[233] L. Guo, et al.. Stacked two-dimensional MXene composites for an energy-efficient memory and digital comparator. ACS Appl. Mater. Interfaces, 13 (2021), pp. 39595-39605.
[234] V.K. Perla, S.K. Ghosh, K. Mallick. Role of carbon nitride on the resistive switching behavior of a silver stannate based device: an approach to design a logic gate using the CMOS-memristor hybrid system. ACS Appl. Electron. Mater., 5 (2023), pp. 1620-1627.
[235] X. Wan, et al.. Unsupervised learning implemented by Ti3C2-MXene-based memristive neuromorphic system. ACS Appl. Electron. Mater., 2 (2020), pp. 3497-3501.
[236] F. Zahoor, F.A. Hussin, F.A. Khanday, M.R. Ahmad, I.M. Nawi. Ternary arithmetic logic unit design utilizing carbon nanotube field effect transistor (CNTFET) and resistive random access memory (RRAM). Micromachines, 12 (2021), p. 1288.
[237] B. Alimkhanuly, J. Sohn, I.-J. Chang, S. Lee. Graphene-based 3D XNOR-VRRAM with ternary precision for neuromorphic computing. npj 2D Mater. Appl., 5 (2021), p. 55.
[238] S. Choi, et al.. Energy-efficient three-terminal SiOx memristor crossbar array enabled by vertical Si/graphene heterojunction barristor. Nano Energy, 84 (2021), p. 105947.
[239] M. Li, et al.. Multimodal optoelectronic neuromorphic electronics based on lead-free perovskite-mixed carbon nanotubes. Carbon, 176 (2021), pp. 592-601.
[240] Y. Sun, et al.. Resistive switching of two-dimensional NiAl-layered double hydroxides and memory logical functions. J. Alloys Compd., 933 (2023), p. 167745.
[241] S. Kim, et al.. Pattern recognition using carbon nanotube synaptic transistors with an adjustable weight update protocol. ACS Nano, 11 (2017), pp. 2814-2822.
[242] A. Melianas, et al.. High-speed ionic synaptic memory based on 2D titanium carbide MXene. Adv. Funct. Mater., 32 (2022), p. 2109970.
[243] J. Liu, et al.. Research progress in optical neural networks: theory, applications and developments. Photonix, 2 (2021), p. 5.
[244] N. Wang, et al.. Intelligent designs in nanophotonics: from optimization towards inverse creation. Photonix, 2 (2021), p. 22.
[245] T. Yu, et al.. A carbon conductive filament-induced robust resistance switching behavior for brain-inspired computing. Mater. Horiz., 11 (2024), pp. 1334-1343.
[246] J. Liang, et al.. All-Optically Controlled Artificial Synapses Based on Light-Induced Adsorption and Desorption for Neuromorphic Vision. ACS Appl. Mater. Interfaces, 15 (2023), pp. 9584-9592.
[247] F. Xia, et al.. Carbon nanotube-based flexible ferroelectric synaptic transistors for neuromorphic computing. ACS Appl. Mater. Interfaces, 14 (2022), pp. 30124-30132.
[248] Y. Choi, et al.. Gate-Tunable synaptic dynamics of ferroelectric-coupled carbon-nanotube transistors. ACS Appl. Mater. Interfaces, 12 (2020), pp. 4707-4714.
[249] S. Kim, et al.. Synaptic device network architecture with feature extraction for unsupervised image classification. Small, 14 (2018), p. 1800521.
[250] S. Liu, Y. Cheng, F. Han, S. Fan, Y. Zhang. Multilevel resistive switching memristor based on silk fibroin/graphene oxide with image reconstruction functionality. Chem. Eng. J., 471 (2023), p. 144678.
[251] Y. Wang, et al.. MXene-ZnO memristor for multimodal in-sensor computing. Adv. Funct. Mater., 31 (2021), p. 2100144.
[252] J.H. Ju, et al.. Two-dimensional MXene synapse for brain-inspired neuromorphic computing. Small, 17 (2021), p. 2102595.
[253] M. Zhang, et al.. Towards an universal artificial synapse using MXene-PZT based ferroelectric memristor. Ceram. Int., 48 (2022), pp. 16263-16272.
[254] J. Xu, et al.. Optimized near-zero quantization method for flexible memristor based neural network. IEEE Access, 6 (2018), pp. 29320-29331.
[255] J. Kim, J.H. Choi, S. Kim, C. Choi, S. Kim. Transition of short-term to long-term memory of Cu/TaOx/CNT conductive bridge random access memory for neuromorphic engineering. Carbon, 215 (2023), p. 118438.
[256] C. Hu, Z. Wei, L. Li, G. Shen. Strategy toward semiconducting Ti3C2Tx-MXene: phenylsulfonic acid groups modified Ti3C2Tx as photosensitive material for flexible visual sensory-neuromorphic system. Adv. Funct. Mater., 33 (2023), p. 2302188.
[257] L. Shan, et al.. Bioinspired kinesthetic system for human-machine interaction. Nano Energy, 88 (2021), p. 106283.
[258] Y.-B. Guo, L.-Q. Zhu. Recent progress in optoelectronic neuromorphic devices. Chin. Phys. B, 29 (2020), Article 078502.
[259] B. Zeng, et al.. MXene-based memristor for artificial optoelectronic neuron. IEEE Trans. Electron Devices, 70 (2023), pp. 1359-1365.
[260] X. Han, et al.. Recent progress in optoelectronic synapses for artificial visual-perception system. Small Struct., 1 (2020), p. 2000029.
[261] G. Ding, et al.. MXenes for memristive and tactile sensory systems.
[262] L. Ai, et al.. Ligand-triggered self-assembly of flexible carbon dot nanoribbons for optoelectronic memristor devices and neuromorphic computing. Adv. Sci., 10 (2023), p. 2207688.
[263] Z. Chen, et al.. Resistive switching memory based on polyvinyl alcohol-graphene oxide hybrid material for the visual perception nervous system. Mater. Des., 223 (2022), p. 111218.
[264] K. Wang, Y. Jia, X. Yan. A biomimetic afferent nervous system based on the flexible artificial synapse. Nano Energy, 100 (2022), p. 107486.
[265] H. Wan, et al.. Flexible carbon nanotube synaptic transistor for neurological electronic skin applications. ACS Nano, 14 (2020), pp. 10402-10412.
[266] Z. Zhao, et al.. Large-scale integrated flexible tactile sensor array for sensitive smart robotic touch. ACS Nano, 16 (2022), pp. 16784-16795.
[267] S. Kim, Y. Lee, H.-D. Kim, S.-J. Choi. A tactile sensor system with sensory neurons and a perceptual synaptic network based on semivolatile carbon nanotube transistors. NPG Asia Mater., 12 (2020), p. 76.
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