Issue

Vol. 17 (2025)

MXene-Ti3C2Tx-Based Neuromorphic Computing: Physical Mechanisms, Performance Enhancement, and Cutting-Edge Computing

https://doi.org/10.1007/s40820-025-01787-0
Kaiyang Wang
Medical Engineering & Engineering Medicine Innovation Center, Hangzhou International Innovation Institute, Beihang University, Hangzhou 311115, People’s Republic of China
http://orcid.org/0009-0002-6586-6182
Shuhui Ren
College of Electronic Information and Optical Engineering, Nankai University, Tianjin 300071, People’s Republic of China
Yunfang Jia
College of Electronic Information and Optical Engineering, Nankai University, Tianjin 300071, People’s Republic of China
http://orcid.org/0000-0002-2093-2118
Xiaobing Yan
Key Laboratory of Brain‑Like Neuromorphic Devices Systems of Hebei Province College of Electron and Information Engineering, Jiaruiyuan Biochip Research Center of Hebei University, Hebei University, Baoding 071002, People’s Republic of China
http://orcid.org/0000-0002-3266-515X
Lizhen Wang
Medical Engineering & Engineering Medicine Innovation Center, Hangzhou International Innovation Institute, Beihang University, Hangzhou 311115, People’s Republic of China
http://orcid.org/0000-0002-9658-659X
Yubo Fan
Medical Engineering & Engineering Medicine Innovation Center, Hangzhou International Innovation Institute, Beihang University, Hangzhou 311115, People’s Republic of China
http://orcid.org/0000-0002-3480-4395

Corresponding Author: Yubo Fan

yubofan@buaa.edu.cn

Nano-Micro Letters, Vol. 17 (2025), Article Number: 273

Abstract

Neuromorphic devices have shown great potential in simulating the function of biological neurons due to their efficient parallel information processing and low energy consumption. MXene-Ti3C2Tx, an emerging two-dimensional material, stands out as an ideal candidate for fabricating neuromorphic devices. Its exceptional electrical performance and robust mechanical properties make it an ideal choice for this purpose. This review aims to uncover the advantages and properties of MXene-Ti3C2Tx in neuromorphic devices and to promote its further development. Firstly, we categorize several core physical mechanisms present in MXene-Ti3C2Tx neuromorphic devices and summarize in detail the reasons for their formation. Then, this work systematically summarizes and classifies advanced techniques for the three main optimization pathways of MXene-Ti3C2Tx, such as doping engineering, interface engineering, and structural engineering. Significantly, this work highlights innovative applications of MXene-Ti3C2Tx neuromorphic devices in cutting-edge computing paradigms, particularly near-sensor computing and in-sensor computing. Finally, this review carefully compiles a table that integrates almost all research results involving MXene-Ti3C2Tx neuromorphic devices and discusses the challenges, development prospects, and feasibility of MXene-Ti3C2Tx-based neuromorphic devices in practical applications, aiming to lay a solid theoretical foundation and provide technical support for further exploration and application of MXene-Ti3C2Tx in the field of neuromorphic devices.


Highlights:
1 This review reveals the advantages of MXene-Ti3C2Tx for neuromorphic devices, classifies the core physical mechanisms, and outlines strategies to drive targeted optimization and future innovation.
2 The review outlines three key engineering strategies: doping engineering, interfacial engineering, and structural engineering, while also providing comprehensive guidance for material and device improvement.
3 MXene-Ti3C2Tx-based devices demonstrate groundbreaking potential in next-generation computing, such as near-sensor computing and in-sensor computing, enabling faster and more energy-efficient data processing directly at the sensor level.

Keywords

Neuromorphic device MXene-Ti3C2Tx Physical mechanisms Performance improvement Cutting-edge computing
Wang, Kaiyang, Shuhui Ren, Yunfang Jia, Xiaobing Yan, Lizhen Wang, and Yubo Fan. 2025. “MXene-Ti3C2Tx-Based Neuromorphic Computing: Physical Mechanisms, Performance Enhancement, and Cutting-Edge Computing”. Nano-Micro Letters 17 (May):273. https://doi.org/10.1007/s40820-025-01787-0.
Download Citation
Endnote/Zotero/Mendeley (RIS)
BibTeX
References
  1. J. He, S.L. Baxter, J. Xu, J. Xu, X. Zhou et al., The practical implementation of artificial intelligence technologies in medicine. Nat. Med. 25(1), 30–36 (2019). https://doi.org/10.1038/s41591-018-0307-0
  2. L. Gu, S. Poddar, Y. Lin, Z. Long, D. Zhang et al., A biomimetic eye with a hemispherical perovskite nanowire array retina. Nature 581(7808), 278–282 (2020). https://doi.org/10.1038/s41586-020-2285-x
  3. Y. Kim, A. Chortos, W. Xu, Y. Liu, J.Y. Oh et al., A bioinspired flexible organic artificial afferent nerve. Science 360(6392), 998–1003 (2018). https://doi.org/10.1126/science.aao0098
  4. F. Alibart, S. Pleutin, D. Guérin, C. Novembre, S. Lenfant et al., An organic nanop transistor behaving as a biological spiking synapse. Adv. Funct. Mater. 20(2), 330–337 (2010). https://doi.org/10.1002/adfm.200901335
  5. F. Cai, J.M. Correll, S.H. Lee, Y. Lim, V. Bothra et al., A fully integrated reprogrammable memristor–CMOS system for efficient multiply–accumulate operations. Nat. Electron. 2(7), 290–299 (2019). https://doi.org/10.1038/s41928-019-0270-x
  6. F. Zhang, H. Zhang, S. Krylyuk, C.A. Milligan, Y. Zhu et al., Electric-field induced structural transition in vertical MoTe2- and Mo1-xWxTe2-based resistive memories. Nat. Mater. 18(1), 55–61 (2019). https://doi.org/10.1038/s41563-018-0234-y
  7. X. Yan, Y. Pei, H. Chen, J. Zhao, Z. Zhou et al., Self-assembled networked PbS distribution quantum dots for resistive switching and artificial synapse performance boost of memristors. Adv. Mater. 31(7), 1805284 (2019). https://doi.org/10.1002/adma.201805284
  8. J.-M. Yang, E.-S. Choi, S.-Y. Kim, J.-H. Kim, J.-H. Park et al., Perovskite-related (CH3NH3)3Sb2Br 9 for forming-free memristor and low-energy-consuming neuromorphic computing. Nanoscale 11(13), 6453–6461 (2019). https://doi.org/10.1039/C8NR09918A
  9. S. Wang, J. Xu, W. Wang, G.N. Wang, R. Rastak et al., Skin electronics from scalable fabrication of an intrinsically stretchable transistor array. Nature 555(7694), 83–88 (2018). https://doi.org/10.1038/nature25494
  10. H. Zhang, Ultrathin two-dimensional nanomaterials. ACS Nano 9(10), 9451–9469 (2015). https://doi.org/10.1021/acsnano.5b05040
  11. C. Tan, X. Cao, X.-J. Wu, Q. He, J. Yang et al., Recent advances in ultrathin two-dimensional nanomaterials. Chem. Rev. 117(9), 6225–6331 (2017). https://doi.org/10.1021/acs.chemrev.6b00558
  12. X. Yan, K. Wang, J. Zhao, Z. Zhou, H. Wang et al., A new memristor with 2D Ti3C2Tx MXene flakes as an artificial bio-synapse. Small 15(25), 1900107 (2019). https://doi.org/10.1002/smll.201900107
  13. K. Wang, L. Li, R. Zhao, J. Zhao, Z. Zhou et al., A pure 2H-MoS2 nanosheet-based memristor with low power consumption and linear multilevel storage for artificial synapse emulator. Adv. Electron. Mater. 6(3), 1901342 (2020). https://doi.org/10.1002/aelm.201901342
  14. Y. Zhou, D. Liu, J. Wang, Z. Cheng, L. Liu et al., Black phosphorus based multicolor light-modulated transparent memristor with enhanced resistive switching performance. ACS Appl. Mater. Interfaces 12(22), 25108–25114 (2020). https://doi.org/10.1021/acsami.0c04493
  15. Y. Shen, W. Zheng, K. Zhu, Y. Xiao, C. Wen et al., Variability and yield in h-BN-based memristive circuits: the role of each type of defect. Adv. Mater. 33(41), 2103656 (2021). https://doi.org/10.1002/adma.202103656
  16. Y. Cheng, Y. Ma, L. Li, M. Zhu, Y. Yue et al., Bioinspired microspines for a high-performance spray Ti3C2Tx MXene-based piezoresistive sensor. ACS Nano 14(2), 2145–2155 (2020). https://doi.org/10.1021/acsnano.9b08952
  17. H. Wei, H. Yu, J. Gong, M. Ma, H. Han et al., Redox MXene artificial synapse with bidirectional plasticity and hypersensitive responsibility. Adv. Funct. Mater. 31(1), 2007232 (2021). https://doi.org/10.1002/adfm.202007232
  18. K. Rasool, M. Helal, A. Ali, C.E. Ren, Y. Gogotsi et al., Antibacterial activity of Ti3C2Tx MXene. ACS Nano 10(3), 3674–3684 (2016). https://doi.org/10.1021/acsnano.6b00181
  19. M. Okubo, A. Sugahara, S. Kajiyama, A. Yamada, MXene as a charge storage host. Acc. Chem. Res. 51(3), 591–599 (2018). https://doi.org/10.1021/acs.accounts.7b00481
  20. D. Xiong, X. Li, Z. Bai, S. Lu, Recent advances in layered Ti3C2Tx MXene for electrochemical energy storage. Small 14(17), 1703419 (2018). https://doi.org/10.1002/smll.201703419
  21. Y. Deng, T. Shang, Z. Wu, Y. Tao, C. Luo et al., Fast gelation of Ti3C2Tx MXene initiated by metal ions. Adv. Mater. 31(43), 1902432 (2019). https://doi.org/10.1002/adma.201902432
  22. E. Li, C. Gao, R. Yu, X. Wang, L. He et al., MXene based saturation organic vertical photoelectric transistors with low subthreshold swing. Nat. Commun. 13(1), 2898 (2022). https://doi.org/10.1038/s41467-022-30527-w
  23. X. Zhang, S. Wu, R. Yu, E. Li, D. Liu et al., Programmable neuronal-synaptic transistors based on 2D MXene for a high-efficiency neuromorphic hardware network. Matter 5(9), 3023–3040 (2022). https://doi.org/10.1016/j.matt.2022.06.009
  24. J. Huang, S. Yang, X. Tang, L. Yang, W. Chen et al., Flexible, transparent, and wafer-scale artificial synapse array based on TiOx/Ti3C2Tx film for neuromorphic computing. Adv. Mater. 35(33), e2303737 (2023). https://doi.org/10.1002/adma.202303737
  25. D. Tan, N. Sun, J. Huang, Z. Zhang, L. Zeng et al., Monolayer vacancy-induced MXene memory for write-verify-free programming. Small 20(36), 2402273 (2024). https://doi.org/10.1002/smll.202402273
  26. K. Wang, Y. Jia, X. Yan, A biomimetic afferent nervous system based on the flexible artificial synapse. Nano Energy 100, 107486 (2022). https://doi.org/10.1016/j.nanoen.2022.107486
  27. S. Ren, K. Wang, X. Jia, J. Wang, J. Xu et al., Fibrous MXene synapse-based biomimetic tactile nervous system for multimodal perception and memory. Small 20(28), 2400165 (2024). https://doi.org/10.1002/smll.202400165
  28. U.J. Kim, D.H. Ho, Y.Y. Choi, Y. Choi, D.G. Roe et al., Deterministic multimodal perturbation enables neuromorphic-compatible signal multiplexing. ACS Mater. Lett. 4(1), 102–110 (2022). https://doi.org/10.1021/acsmaterialslett.1c00586
  29. K. Wang, S. Ren, Y. Jia, X. Yan, Dual biological-clock controllable low-power fibrous synapse array based on heterojunction switched conductive filaments. Nano Energy 127, 109765 (2024). https://doi.org/10.1016/j.nanoen.2024.109765
  30. K. Wang, Y. Jia, X. Yan, Neuro-receptor mediated synapse device based on crumpled MXene Ti3C2Tx nanosheets. Adv. Funct. Mater. 31(48), 2104304 (2021). https://doi.org/10.1002/adfm.202104304
  31. J. Huang, J. Feng, Z. Chen, Z. Dai, S. Yang et al., A bioinspired MXene-based flexible sensory neuron for tactile near-sensor computing. Nano Energy 126, 109684 (2024). https://doi.org/10.1016/j.nanoen.2024.109684
  32. K. Wang, J. Chen, X. Yan, MXene Ti3C2 memristor for neuromorphic behavior and decimal arithmetic operation applications. Nano Energy 79, 105453 (2021). https://doi.org/10.1016/j.nanoen.2020.105453
  33. H. Riazi, M. Anayee, K. Hantanasirisakul, A.A. Shamsabadi, B. Anasori et al., Surface modification of a MXene by an aminosilane coupling agent. Adv. Mater. Interfaces 7(6), 1902008 (2020). https://doi.org/10.1002/admi.201902008
  34. H. Huang, R. Jiang, Y. Feng, H. Ouyang, N. Zhou et al., Recent development and prospects of surface modification and biomedical applications of MXenes. Nanoscale 12(3), 1325–1338 (2020). https://doi.org/10.1039/C9NR07616F
  35. R. Wang, M. Li, K. Sun, Y. Zhang, J. Li et al., Element-doped mxenes: mechanism, synthesis, and applications. Small 18(25), e2201740 (2022). https://doi.org/10.1002/smll.202201740
  36. Y. Wen, T.E. Rufford, X. Chen, N. Li, M. Lyu et al., Nitrogen-doped Ti3C2Tx MXene electrodes for high-performance supercapacitors. Nano Energy 38, 368–376 (2017). https://doi.org/10.1016/j.nanoen.2017.06.009
  37. B. Lyu, Y. Choi, H. Jing, C. Qian, H. Kang et al., 2D MXene-TiO2 core-shell nanosheets as a data-storage medium in memory devices. Adv. Mater. 32(17), e1907633 (2020). https://doi.org/10.1002/adma.201907633
  38. N.B. Mullani, D.D. Kumbhar, D.-H. Lee, M.J. Kwon, S.-Y. Cho et al., Surface modification of a titanium carbide MXene memristor to enhance memory window and low-power operation. Adv. Funct. Mater. 33(26), 2300343 (2023). https://doi.org/10.1002/adfm.202300343
  39. X. Feng, J. Huang, J. Ning, D. Wang, J. Zhang et al., A novel nonvolatile memory device based on oxidized Ti3C2Tx MXene for neurocomputing application. Carbon 205, 365–372 (2023). https://doi.org/10.1016/j.carbon.2023.01.040
  40. Y. Cao, T. Zhao, C. Liu, C. Zhao, H. Gao et al., Neuromorphic visual artificial synapse in-memory computing systems based on GeOx-coated MXene nanosheets. Nano Energy 112, 108441 (2023). https://doi.org/10.1016/j.nanoen.2023.108441
  41. J.H. Ju, S. Seo, S. Baek, D. Lee, S. Lee et al., Two-dimensional MXene synapse for brain-inspired neuromorphic computing. Small 17(34), 2102595 (2021). https://doi.org/10.1002/smll.202102595
  42. Y. Wang, Y. Gong, L. Yang, Z. Xiong, Z. Lv et al., MXene-ZnO memristor for multimodal in-sensor computing. Adv. Funct. Mater. 31(21), 2100144 (2021). https://doi.org/10.1002/adfm.202100144
  43. J.-Y. Mao, L. Zhou, X. Zhu, Y. Zhou, S.-T. Han, Photonic memristor for future computing: a perspective. Adv. Opt. Mater. 7(22), 1900766 (2019). https://doi.org/10.1002/adom.201900766
  44. S. Zhu, B. Sun, G. Zhou, T. Guo, C. Ke et al., In-depth physical mechanism analysis and wearable applications of HfO x-based flexible memristors. ACS Appl. Mater. Interf. 15(4), 5420–5431 (2023). https://doi.org/10.1021/acsami.2c16569
  45. S. Kim, S. Choi, W. Lu, Comprehensive physical model of dynamic resistive switching in an oxide memristor. ACS Nano 8(3), 2369–2376 (2014). https://doi.org/10.1021/nn405827t
  46. X. Yan, J. Zhao, S. Liu, Z. Zhou, Q. Liu et al., Memristor with Ag-cluster-doped TiO2 films as artificial synapse for neuroinspired computing. Adv. Funct. Mater. 28(1), 1705320 (2018). https://doi.org/10.1002/adfm.201705320
  47. Y. She, F. Wang, X. Zhao, Z. Zhang, C. Li et al., Oxygen vacancy-dependent synaptic dynamic behavior of TiOx-based transparent memristor. IEEE Trans. Electron Devices 68(4), 1950–1955 (2021). https://doi.org/10.1109/TED.2021.3056333
  48. Z. Wang, M. Rao, R. Midya, S. Joshi, H. Jiang et al., Threshold switching of Ag or Cu in dielectrics: materials, mechanism, and applications. Adv. Funct. Mater. 28(6), 1704862 (2018). https://doi.org/10.1002/adfm.201704862
  49. X. Yan, L. Zhang, H. Chen, X. Li, J. Wang et al., Graphene oxide quantum dots based memristors with progressive conduction tuning for artificial synaptic learning. Adv. Funct. Mater. 28(40), 1803728 (2018). https://doi.org/10.1002/adfm.201803728
  50. M. Downes, C.E. Shuck, B. McBride, J. Busa, Y. Gogotsi, Comprehensive synthesis of Ti3C2Tx from MAX phase to MXene. Nat. Protoc. 19(6), 1807–1834 (2024). https://doi.org/10.1038/s41596-024-00969-1
  51. T.D. Dongale, K.P. Patil, P.K. Gaikwad, R.K. Kamat, Investigating conduction mechanism and frequency dependency of nanostructured memristor device. Mater. Sci. Semicond. Process. 38, 228–233 (2015). https://doi.org/10.1016/j.mssp.2015.04.033
  52. V.A. Voronkovskii, V.S. Aliev, A.K. Gerasimova, D.R. Islamov, Conduction mechanisms of TaN/HfO x /Ni memristors. Mater. Res. Express 6(7), 076411 (2019). https://doi.org/10.1088/2053-1591/ab11aa
  53. B. Zeng, X. Zhang, C. Gao, Y. Zou, X. Yu et al., MXene-based memristor for artificial optoelectronic neuron. IEEE Trans. Electron Devices 70(3), 1359–1365 (2023). https://doi.org/10.1109/TED.2023.3234881
  54. A. Thomas, P. Saha, S.E. Muhammed, K.K. Navaneeth, B.C. Das, Versatile titanium carbide MXene thin-film memristors with adaptive learning behavior. ACS Appl. Mater. Interf. (2024). https://doi.org/10.1021/acsami.3c19177
  55. C. Du, Z. Qu, Y. Ren, Y. Zhai, J. Chen et al., Grain boundary confinement of silver imidazole for resistive switching. Adv. Funct. Mater. 32(8), 2108598 (2022). https://doi.org/10.1002/adfm.202108598
  56. J. Fang, Z. Tang, X.-C. Lai, F. Qiu, Y.-P. Jiang et al., New-style logic operation and neuromorphic computing enabled by optoelectronic artificial synapses in an MXene/Y: HfO2 ferroelectric memristor. ACS Appl. Mater. Interfaces 16(24), 31348–31362 (2024). https://doi.org/10.1021/acsami.4c05316
  57. T.R. Desai, S.S. Kundale, T.D. Dongale, C. Gurnani, Evaluation of cellulose-MXene composite hydrogel based bio-resistive random access memory material as mimics for biological synapses. ACS Appl. Bio Mater. 6(5), 1763–1773 (2023). https://doi.org/10.1021/acsabm.2c01073
  58. Z. Zhou, X. Yan, J. Zhao, C. Lu, D. Ren et al., Synapse behavior characterization and physical mechanism of a TiN/SiOx/p-Si tunneling memristor device. J. Mater. Chem. C 7(6), 1561–1567 (2019). https://doi.org/10.1039/C8TC04903C
  59. R. Guo, W. Lin, X. Yan, T. Venkatesan, J. Chen, Ferroic tunnel junctions and their application in neuromorphic networks. Appl. Phys. Rev. 7(1), 011304 (2020). https://doi.org/10.1063/1.5120565
  60. E. Lim, R. Ismail, Conduction mechanism of valence change resistive switching memory: a survey. Electronics 4(3), 586–613 (2015). https://doi.org/10.3390/electronics4030586
  61. X. Yan, Z. Zhou, B. Ding, J. Zhao, Y. Zhang, Superior resistive switching memory and biological synapse properties based on a simple TiN/SiO2/p-Si tunneling junction structure. J. Mater. Chem. C 5(9), 2259–2267 (2017). https://doi.org/10.1039/C6TC04261A
  62. M.P. Houng, Y.H. Wang, W.J. Chang, Current transport mechanism in trapped oxides: a generalized trap-assisted tunneling model. J. Appl. Phys. 86(3), 1488–1491 (1999). https://doi.org/10.1063/1.370918
  63. X. Wang, G. Sun, N. Li, P. Chen, Quantum dots derived from two-dimensional materials and their applications for catalysis and energy. Chem. Soc. Rev. 45(8), 2239–2262 (2016). https://doi.org/10.1039/C5CS00811E
  64. K. Sattar, R. Tahir, H. Huang, D. Akinwande, S. Rizwan, Ferroelectric MXene-assisted BiFeO3 based free-standing memristors for multifunctional non-volatile memory storage. Carbon 221, 118931 (2024). https://doi.org/10.1016/j.carbon.2024.118931
  65. X. Qin, H. Liu, J. Hu, J. Huang, F. Yang et al., Light-tunable resistive switching properties of a BiFeO3/Ti3C2 heterostructure memristor. J. Electron. Mater. 52(6), 3868–3876 (2023). https://doi.org/10.1007/s11664-023-10374-1
  66. W.-Z. Song, H.-J. Qiu, J. Zhang, M. Yu, S. Ramakrishna et al., Sliding mode direct current triboelectric nanogenerators. Nano Energy 90, 106531 (2021). https://doi.org/10.1016/j.nanoen.2021.106531
  67. M.A. Lampert, Simplified theory of space-charge-limited currents in an insulator with traps. Phys. Rev. 103(6), 1648–1656 (1956). https://doi.org/10.1103/physrev.103.1648
  68. R. Zhang, Y. Lai, W. Chen, C. Teng, Y. Sun et al., Carrier trapping in wrinkled 2D monolayer MoS2 for ultrathin memory. ACS Nano 16(4), 6309–6316 (2022). https://doi.org/10.1021/acsnano.2c00350
  69. C. Gao, D. Liu, C. Xu, W. Xie, X. Zhang et al., Toward grouped-reservoir computing: organic neuromorphic vertical transistor with distributed reservoir states for efficient recognition and prediction. Nat. Commun. 15, 740 (2024). https://doi.org/10.1038/s41467-024-44942-8
  70. R. Li, Y. Sun, Q. Zhao, X. Hao, H. Liang et al., NIR-triggered logic gate in MXene-modified perovskite resistive random access memory. J. Mater. Chem. C 12(13), 4762–4770 (2024). https://doi.org/10.1039/d3tc03847e
  71. H. Wang, Y. Wu, J. Zhang, G. Li, H. Huang et al., Enhancement of the electrical properties of MXene Ti3C2 nanosheets by post-treatments of alkalization and calcination. Mater. Lett. 160, 537–540 (2015). https://doi.org/10.1016/j.matlet.2015.08.046
  72. R. Tang, S. Xiong, D. Gong, Y. Deng, Y. Wang et al., Ti3C2 2D MXene: recent progress and perspectives in photocatalysis. ACS Appl. Mater. Interfaces 12(51), 56663–56680 (2020). https://doi.org/10.1021/acsami.0c12905
  73. I.H. Im, S.J. Kim, H.W. Jang, Memristive devices for new computing paradigms. Adv. Intell. Syst. 2(11), 2000105 (2020). https://doi.org/10.1002/aisy.202000105
  74. M. Naguib, M. Kurtoglu, V. Presser, J. Lu, J. Niu et al., Two-dimensional nanocrystals produced by exfoliation of Ti3AlC2. MXenes. Jenny Stanford Publishing (2023). https://doi.org/10.1201/9781003306511-4
  75. L. Yu, Z. Fan, Y. Shao, Z. Tian, J. Sun et al., Versatile N-doped MXene ink for printed electrochemical energy storage application. Adv. Energy Mater. 9(34), 1901839 (2019). https://doi.org/10.1002/aenm.201901839
  76. F. Yang, Y. Huang, X. Han, S. Zhang, M. Yu et al., Covalent bonding of MXene/reduced graphene oxide composites for efficient electromagnetic wave absorption. ACS Appl. Nano Mater. 6(5), 3367–3377 (2023). https://doi.org/10.1021/acsanm.2c05150
  77. S. Wang, C. Song, Y. Cai, Y. Li, P. Jiang et al., Interfacial polarization triggered by covalent-bonded MXene and black phosphorus for enhanced electrochemical nitrate to ammonia conversion. Adv. Energy Mater. 13(31), 2301136 (2023). https://doi.org/10.1002/aenm.202301136
  78. S. Ling, S. Lin, Y. Wu, Y. Li, Toward highly-robust MXene hybrid memristor by synergetic ionotronic modification and two-dimensional heterojunction. Chem. Eng. J. 486, 150100 (2024). https://doi.org/10.1016/j.cej.2024.150100
  79. K. Wang, Q. Hu, B. Gao, Q. Lin, F.-W. Zhuge et al., Threshold switching memristor-based stochastic neurons for probabilistic computing. Mater. Horiz. 8(2), 619–629 (2021). https://doi.org/10.1039/d0mh01759k
  80. M. Abdullah, I. Elango, H. Patil, P.P. Patil, D. Aloysius et al., Metal-organic framework and MXene (ZIF-8: Ti3C2Tx) based organic and inorganic nanocomposite for bio-synaptic applications. Surf. Interfaces 51, 104708 (2024). https://doi.org/10.1016/j.surfin.2024.104708
  81. G. Zou, Z. Zhang, J. Guo, B. Liu, Q. Zhang et al., Synthesis of MXene/Ag composites for extraordinary long cycle lifetime lithium storage at high rates. ACS Appl. Mater. Interfaces 8(34), 22280–22286 (2016). https://doi.org/10.1021/acsami.6b08089
  82. M. Faustini, L. Nicole, E. Ruiz-Hitzky, C. Sanchez, History of organic–inorganic hybrid materials: prehistory, art, science, and advanced applications. Adv. Funct. Mater. 28(27), 1704158 (2018). https://doi.org/10.1002/adfm.201704158
  83. Y. Li, Z. Wang, R. Midya, Q. Xia, J.J. Yang, Review of memristor devices in neuromorphic computing: materials sciences and device challenges. J. Phys. D Appl. Phys. 51(50), 503002 (2018). https://doi.org/10.1088/1361-6463/aade3f
  84. D.J. Kim, H. Lu, S. Ryu, C.-W. Bark, C.-B. Eom et al., Ferroelectric tunnel memristor. Nano Lett. 12(11), 5697–5702 (2012). https://doi.org/10.1021/nl302912t
  85. M.T. Sharbati, Y. Du, J. Torres, N.D. Ardolino, M. Yun et al., Low-power, electrochemically tunable graphene synapses for neuromorphic computing. Adv. Mater. (2018). https://doi.org/10.1002/adma.201802353
  86. F. Zhou, Y. Chai, Near-sensor and in-sensor computing. Nat. Electron. 3(11), 664–671 (2020). https://doi.org/10.1038/s41928-020-00501-9
  87. T. Wan, B. Shao, S. Ma, Y. Zhou, Q. Li et al., In-sensor computing: materials, devices, and integration technologies. Adv. Mater. 35(37), 2203830 (2023). https://doi.org/10.1002/adma.202203830
  88. C. Wang, N. Li, H. Zeng, L. Chen, D. Wu et al., MXene hybrid nanocomposites enable high performance memory devices and artificial synapse applications. J. Mater. Chem. C 12(10), 3662–3671 (2024). https://doi.org/10.1039/D3TC04561G
  89. Q. Zhang, Z. Zhang, C. Li, R. Xu, D. Yang et al., Van der Waals materials-based floating gate memory for neuromorphic computing. Chip 2(4), 100059 (2023). https://doi.org/10.1016/j.chip.2023.100059
  90. C. Li, X. Chen, Z. Zhang, X. Wu, T. Yu et al., Charge-selective 2D heterointerface-driven multifunctional floating gate memory for in situ sensing-memory-computing. Nano Lett. 24(47), 15025–15034 (2024). https://doi.org/10.1021/acs.nanolett.4c03828
  91. J. Zhu, Z. Wang, D. Liu, Q. Liu, W. Wang et al., Flexible low-voltage MXene floating-gate synaptic transistor for neuromorphic computing and cognitive learning. Adv. Funct. Mater. 34(40), 2403842 (2024). https://doi.org/10.1002/adfm.202403842
  92. K.A. Nirmal, W. Ren, A.C. Khot, D.Y. Kang, T.D. Dongale et al., Flexible memristive organic solar cell using multilayer 2D titanium carbide MXene electrodes. Adv. Sci. 10(19), 2300433 (2023). https://doi.org/10.1002/advs.202300433
  93. A.K. Thompson, F.R. Pomerantz, J.R. Wolpaw, Operant conditioning of a spinal reflex can improve locomotion after spinal cord injury in humans. J. Neurosci. 33(6), 2365–2375 (2013). https://doi.org/10.1523/JNEUROSCI.3968-12.2013
  94. S. Ren, K. Wang, Y. Jia, X. Yan, Ion migration-modulated flexible MXene synapse for biomimetic multimode afferent nervous system: material and motion cognition. Adv. Intell. Syst. 5(11), 2300402 (2023). https://doi.org/10.1002/aisy.202300402
  95. Y. Liu, D. Liu, C. Gao, X. Zhang, R. Yu et al., Self-powered high-sensitivity all-in-one vertical tribo-transistor device for multi-sensing-memory-computing. Nat. Commun. 13(1), 7917 (2022). https://doi.org/10.1038/s41467-022-35628-0
  96. M. Li, F.-S. Yang, H.-C. Hsu, W.-H. Chen, C.N. Kuo et al., Defect engineering in ambipolar layered materials for mode-regulable nociceptor. Adv. Funct. Mater. 31(5), 2007587 (2021). https://doi.org/10.1002/adfm.202007587
  97. W. Huh, S. Jang, J.Y. Lee, D. Lee, D. Lee et al., Synaptic barristor based on phase-engineered 2D heterostructures. Adv. Mater. 30(35), e1801447 (2018). https://doi.org/10.1002/adma.201801447
  98. V. Di Stefano, A. Lupica, M.G. Rispoli, A. Di Muzio, F. Brighina et al., Rituximab in AChR subtype of myasthenia gravis: systematic review. J. Neurol. Neurosurg. Psychiatry 91(4), 392–395 (2020). https://doi.org/10.1136/jnnp-2019-322606
  99. J. da Silva Prade, E.C. Bálsamo, F.R. Machado, M.R. Poetini, V.C. Bortolotto et al., Anti-inflammatory effect of Arnica montana in a UVB radiation-induced skin-burn model in mice. Cutan. Ocul. Toxicol. 39(2), 126–133 (2020). https://doi.org/10.1080/15569527.2020.1743998
  100. L. Nguyen, Z. Wang, A.Y. Chowdhury, E. Chu, J. Eerdeng et al., Functional compensation between hematopoietic stem cell clonesin vivo. EMBO Rep. 19(8), e45702 (2018). https://doi.org/10.15252/embr.201745702
  101. D. Tan, Z. Zhang, H. Shi, N. Sun, Q. Li et al., Bioinspired artificial visual-respiratory synapse as multimodal scene recognition system with oxidized-vacancies MXene. Adv. Mater. 36(36), 2407751 (2024). https://doi.org/10.1002/adma.202407751
  102. C.W. Lee, S.J. Kim, H.-K. Shin, Y.-J. Cho, C. Yoo et al., Optically-modulated and mechanically-flexible MXene artificial synapses with visible-to-near IR broadband-responsiveness. Nano Today 61, 102633 (2025). https://doi.org/10.1016/j.nantod.2025.102633
  103. K. An, H. Zhao, Y. Miao, Q. Xu, Y.-F. Li et al., A circadian rhythm-gated subcortical pathway for nighttime-light-induced depressive-like behaviors in mice. Nat. Neurosci. 23(7), 869–880 (2020). https://doi.org/10.1038/s41593-020-0640-8
  104. W.C. Naber, R. Fronczek, J. Haan, P. Doesborg, C.S. Colwell et al., The biological clock in cluster headache: a review and hypothesis. Cephalalgia 39(14), 1855–1866 (2019). https://doi.org/10.1177/0333102419851815
  105. K. Wang, S. Ren, Y. Jia, X. Yan, An ultrasensitive biomimetic optic afferent nervous system with circadian learnability. Adv. Sci. 11(21), 2309489 (2024). https://doi.org/10.1002/advs.202309489
  106. J. Wu, L. Zhang, W. Chang, H. Zhang, W. Zhang et al., A biomimetic ionic hydrogel synapse for self-powered tactile-visual fusion perception. Adv. Funct. Mater. (2025). https://doi.org/10.1002/adfm.202500048
  107. R. Yu, X. Zhang, C. Gao, E. Li, Y. Yan et al., Low-voltage solution-processed artificial optoelectronic hybrid-integrated neuron based on 2D MXene for multi-task spiking neural network. Nano Energy 99, 107418 (2022). https://doi.org/10.1016/j.nanoen.2022.107418
  108. X. Duan, Z. Cao, K. Gao, W. Yan, S. Sun et al., Memristor-based neuromorphic chips. Adv. Mater. 36(14), 2310704 (2024). https://doi.org/10.1002/adma.202310704
  109. P. Yao, H. Wu, B. Gao, J. Tang, Q. Zhang et al., Fully hardware-implemented memristor convolutional neural network. Nature 577(7792), 641–646 (2020). https://doi.org/10.1038/s41586-020-1942-4
  110. A. Sokolov, M. Ali, H. Li, Y.-R. Jeon, M.J. Ko et al., Partially oxidized MXene Ti3C2Tx sheets for memristor having synapse and threshold resistive switching characteristics. Adv. Electron. Mater. 7(2), 2000866 (2021). https://doi.org/10.1002/aelm.202000866
  111. A.C. Khot, T.D. Dongale, K.A. Nirmal, J.K. Deepthi, S.S. Sutar et al., 2D Ti3C2Tx MXene-derived self-assembled 3D TiO2 nanoflowers for nonvolatile memory and synaptic learning applications. J. Mater. Sci. Technol. 150, 1–10 (2023). https://doi.org/10.1016/j.jmst.2023.01.003
  112. S. Saha, V. Adepu, K. Gohel, P. Sahatiya, S.S. Dan, Demonstration of a 2-D SnS/MXene nanohybrid asymmetric memristor. IEEE Trans. Electron Devices 69(10), 5921–5927 (2022). https://doi.org/10.1109/TED.2022.3199710
  113. T. Zhao, C. Zhao, W. Xu, Y. Liu, H. Gao et al., Bio-inspired photoelectric artificial synapse based on two-dimensional Ti3C2Tx MXenes floating gate. Adv. Funct. Mater. 31(45), 2106000 (2021). https://doi.org/10.1002/adfm.202106000
  114. A. Aglikov, O. Volkova, A. Bondar, I. Moskalenko, A. Novikov et al., Memristive effect in Ti3C2Tx (MXene) polyelectrolyte multilayers. ChemPhysChem 24(17), e202300187 (2023). https://doi.org/10.1002/cphc.202300187
  115. Y. Chen, Y. Wang, Y. Luo, X. Liu, Y. Wang et al., Realization of artificial neuron using MXene bi-directional threshold switching memristors. IEEE Electron Device Lett. 40(10), 1686–1689 (2019). https://doi.org/10.1109/LED.2019.2936261
  116. J. Gosai, M. Patel, L. Liu, A. Lokhandwala, P. Thakkar et al., Control-etched Ti3C2Tx MXene nanosheets for a low-voltage-operating flexible memristor for efficient neuromorphic computation. ACS Appl. Mater. Interfaces 16(14), 17821–17831 (2024). https://doi.org/10.1021/acsami.4c01364
  117. X. Lian, Y. Shi, X. Shen, X. Wan, Z. Cai et al., Design of high performance MXene/oxide structure memristors for image recognition applications. Chin. J. Electron. 33(2), 336–345 (2024). https://doi.org/10.23919/cje.2022.00.125
  118. S. Ling, C. Zhang, C. Zhang, M. Teng, C. Ma et al., Facile synthesis of MXene−Polyvinyl alcohol hybrid material for robust flexible memristor. J. Solid State Chem. 318, 123731 (2023). https://doi.org/10.1016/j.jssc.2022.123731
  119. Y. Wang, Y. Zhang, Y. Wang, H. Zhang, X. Wang et al., Realization of empathy capability for the evolution of artificial intelligence using an MXene(Ti3C2)-based memristor. Electronics 13(9), 1632 (2024). https://doi.org/10.3390/electronics13091632
  120. S. Fatima, R. Tahir, D. Akinwande, S. Rizwan, Enhanced memristive effect of laser-reduced graphene and ferroelectric MXene-based flexible trilayer memristors. Carbon 218, 118656 (2024). https://doi.org/10.1016/j.carbon.2023.118656
  121. A. Sharma, H.-S. Lee, C.-M. Yeom, H.K. Surendran, C. Narayana et al., Tailoring conductive MXene@MOF interfaces: new generation of synapse devices for neuromorphic computing. Chem. Mater. 36(17), 8466–8476 (2024). https://doi.org/10.1021/acs.chemmater.4c01596
  122. R. Tahir, S. Fatima, S.A. Zahra, D. Akinwande, H. Li et al., Multiferroic and ferroelectric phases revealed in 2D Ti3C2Tx MXene film for high performance resistive data storage devices. NPJ 2D Mater. Appl. 7, 7 (2023). https://doi.org/10.1038/s41699-023-00368-2
  123. Y. Zou, E. Li, R. Yu, C. Gao, X. Yu et al., Electret-based vertical organic synaptic transistor with MXene for neural network-based computation. IEEE Trans. Electron Devices 69(12), 6681–6685 (2022). https://doi.org/10.1109/TED.2022.3211478
  124. C. Gu, H.-W. Mao, W.-Q. Tao, Z. Zhou, X.-J. Wang et al., Facile synthesis of Ti3C2Tx-poly(vinylpyrrolidone) nanocomposites for nonvolatile memory devices with low switching voltage. ACS Appl. Mater. Interfaces 11(41), 38061–38067 (2019). https://doi.org/10.1021/acsami.9b13711
  125. A. Melianas, M.-A. Kang, A. VahidMohammadi, T.J. Quill, W. Tian et al., High-speed ionic synaptic memory based on 2D titanium carbide MXene. Adv. Funct. Mater. 32(12), 2109970 (2022). https://doi.org/10.1002/adfm.202109970
  126. S. Kim, S.B. Jo, J. Kim, D. Rhee, Y.Y. Choi et al., Gate-deterministic remote doping enables highly retentive graphene-MXene hybrid memory devices on plastic. Adv. Funct. Mater. 32(20), 2111956 (2022). https://doi.org/10.1002/adfm.202111956
  127. M. Zhang, Q. Qin, X. Chen, R. Tang, A. Han et al., Towards an universal artificial synapse using MXene-PZT based ferroelectric memristor. Ceram. Int. 48(11), 16263–16272 (2022). https://doi.org/10.1016/j.ceramint.2022.02.175
  128. L. Yue, H. Sun, Y. Zhu, Y. Li, F. Yang et al., Electrical-light coordinately modulated synaptic memristor based on Ti3C2 MXene for near-infrared artificial vision applications. J. Phys. Chem. Lett. 15(34), 8667–8675 (2024). https://doi.org/10.1021/acs.jpclett.4c02281
  129. H. Qiu, S. Lan, Q. Lin, H. Zhu, W. Liao et al., Simulation of neural functions based on organic semiconductor/MXene synaptic transistors. Org. Electron. 131, 107090 (2024). https://doi.org/10.1016/j.orgel.2024.107090
  130. Y. Cao, C. Zhao, T. Zhao, Y. Sun, Z. Liu et al., Brain-like optoelectronic artificial synapses with ultralow energy consumption based on MXene floating-gates for emotion recognition. J. Mater. Chem. C 11(10), 3468–3479 (2023). https://doi.org/10.1039/D2TC04745D
  131. X. Zhang, H. Chen, S. Cheng, F. Guo, W. Jie et al., Tunable resistive switching in 2D MXene Ti3C2 nanosheets for non-volatile memory and neuromorphic computing. ACS Appl. Mater. Interfaces 14(39), 44614–44621 (2022). https://doi.org/10.1021/acsami.2c14006
  132. C. Zhu, Y. Hao, H. Wu, M. Chen, B. Quan et al., Self-assembly of binderless MXene aerogel for multiple-scenario and responsive phase change composites with ultrahigh thermal energy storage density and exceptional electromagnetic interference shielding. Nano-Micro Lett. 16(1), 57 (2023). https://doi.org/10.1007/s40820-023-01288-y
  133. X.-J. Lian, J.-K. Fu, Z.-X. Gao, S.-P. Gu, L. Wang, High-performance artificial neurons based on Ag/MXene/GST/Pt threshold switching memristors. Chin. Phys. B 32(1), 017304 (2023). https://doi.org/10.1088/1674-1056/ac673f
  134. N. Qin, Z. Ren, Y. Fan, C. Qin, C. Liu et al., MXene-based optoelectronic synaptic transistors utilize attentional mechanisms to achieve hierarchical responses. J. Mater. Chem. C 12(20), 7197–7205 (2024). https://doi.org/10.1039/D4TC00473F
  135. X. Wan, W. Xu, M. Zhang, N. He, X. Lian et al., Unsupervised learning implemented by Ti3C2-MXene-based memristive neuromorphic system. ACS Appl. Electron. Mater. 2(11), 3497–3501 (2020). https://doi.org/10.1021/acsaelm.0c00705
  136. M. Zhang, Y. Wang, F. Gao, Y. Wang, X. Shen et al., Formation of new MXene film using spinning coating method with DMSO solution and its application in advanced memristive device. Ceram. Int. 45(15), 19467–19472 (2019). https://doi.org/10.1016/j.ceramint.2019.06.202
  137. M. Zhang, X. Chen, Z. Chen, R. Dan, Y. Wei et al., Exploration of threshold and resistive-switching behaviors in MXene/BaFe12O19 ferroelectric memristors. Appl. Surf. Sci. 613, 155956 (2023). https://doi.org/10.1016/j.apsusc.2022.155956
  138. N. He, J. Liu, J. Xu, X. Lian, X. Wan 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(7), 3688–3693 (2022). https://doi.org/10.1109/TED.2022.3175448
  139. Q. Zhang, E. Li, Y. Wang, C. Gao, C. Wang et al., Ultralow-power vertical transistors for multilevel decoding modes. Adv. Mater. 35(3), 2208600 (2023). https://doi.org/10.1002/adma.202208600
Read More
Author biographies are not available.
Download this PDF file
PDF
Statistic
Read Counter : 1690 Download : 1277

Most read articles by the same author(s)