REFERENCES

1. Hou, Y.; Hou, X. Bioinspired nanofluidic iontronics. Science 2021, 373, 628-9.

2. Noy, A.; Darling, S. B. Nanofluidic computing makes a splash. Science 2023, 379, 143-4.

3. Xu, G.; Zhang, M.; Mei, T.; Liu, W.; Wang, L.; Xiao, K. Nanofluidic ionic memristors. ACS. Nano. 2024, 18, 19423-42.

4. Song, R.; Wang, P.; Zeng, H.; et al. Nanofluidic memristive transition and synaptic emulation in atomically thin pores. Nano. Lett. 2025, 25, 5646-55.

5. Xiong, T.; Li, W.; Yu, P.; Mao, L. Fluidic memristor: bringing chemistry to neuromorphic devices. Innovation 2023, 4, 100435.

6. Shi, D.; Wang, W.; Liang, Y.; Duan, L.; Du, G.; Xie, Y. Ultralow energy consumption angstrom-fluidic memristor. Nano. Lett. 2023, 23, 11662-8.

7. Ramirez, P.; Portillo, S.; Cervera, J.; Bisquert, J.; Mafe, S. Memristive arrangements of nanofluidic pores. Phys. Rev. E. 2024, 109, 044803.

8. Kamsma, T. M.; Boon, W. Q.; Ter Rele, T.; Spitoni, C.; van Roij, R. Iontronic neuromorphic signaling with conical microfluidic memristors. Phys. Rev. Lett. 2023, 130, 268401.

9. Baram, D.; Kvetny, M.; Ake, S.; Yang, R.; Wang, G. Anodized aluminum oxide membrane ionic memristors. J. Am. Chem. Soc. 2025, 147, 11089-97.

10. Wang, D.; Kvetny, M.; Liu, J.; Brown, W.; Li, Y.; Wang, G. Transmembrane potential across single conical nanopores and resulting memristive and memcapacitive ion transport. J. Am. Chem. Soc. 2012, 134, 3651-4.

11. Hu, X.; Xu, H.; Lu, J.; et al. Selective ion transport of nonlinear resistive switching by hierarchical nanometer-to-angstrom channels for nanofluidic transistors. Sci. Adv. 2025, 11, eadw7882.

12. Emmerich, T.; Teng, Y.; Ronceray, N.; et al. Nanofluidic logic with mechano-ionic memristive switches. Nat. Electron. 2024, 7, 271-8.

13. Zhou, X.; Zong, Y.; Wang, Y.; et al. Nanofluidic memristor based on the elastic deformation of nanopores with nanoparticle adsorption. Natl. Sci. Rev. 2024, 11, nwad216.

14. Niu, Y.; Ma, Y.; Xie, Y. Soft memristor at a microbubble interface. Nano. Lett. 2024, 24, 10475-81.

15. Robin, P.; Kavokine, N.; Bocquet, L. Modeling of emergent memory and voltage spiking in ionic transport through angstrom-scale slits. Science 2021, 373, 687-91.

16. Robin, P.; Emmerich, T.; Ismail, A.; et al. Long-term memory and synapse-like dynamics in two-dimensional nanofluidic channels. Science 2023, 379, 161-7.

17. Ismail, A.; Nam, G. H.; Lokhandwala, A.; et al. Programmable memristors with two-dimensional nanofluidic channels. Nat. Commun. 2025, 16, 7008.

18. Xiong, T.; Li, C.; He, X.; et al. Neuromorphic functions with a polyelectrolyte-confined fluidic memristor. Science 2023, 379, 156-61.

19. Yang, R.; Balogun, Y.; Ake, S.; Baram, D.; Brown, W.; Wang, G. Negative differential resistance in conical nanopore iontronic memristors. J. Am. Chem. Soc. 2024, 146, 13183-90.

20. Zhang, Z.; Sabbagh, B.; Chen, Y.; Yossifon, G. Geometrically scalable iontronic memristors: employing bipolar polyelectrolyte gels for neuromorphic systems. ACS. Nano. 2024, 18, 15025-34.

21. Che, Q.; Li, C.; Chen, Z.; Yang, S.; Zhang, W.; Yu, G. High performance memristors based on imine-linked covalent organic frameworks obtained using a protonation modification strategy. Angew. Chem. Int. Ed. Engl. 2024, 63, e202409926.

22. Wang, W.; Liang, Y.; Ma, Y.; Shi, D.; Xie, Y. Memristive characteristics in an asymmetrically charged nanochannel. J. Phys. Chem. Lett. 2024, 15, 6852-8.

23. Xiao, Y.; Sun, W.; Gao, C.; et al. Neural functions enabled by a polarity-switchable nanofluidic memristor. Nano. Lett. 2024, 24, 12515-21.

24. Wang, Y. L.; Cao, J. T.; Liu, Y. M. Bipolar electrochemistry - a powerful tool for micro/nano-electrochemistry. ChemistryOpen 2022, 11, e202200163.

25. Fosdick, S. E.; Knust, K. N.; Scida, K.; Crooks, R. M. Bipolar electrochemistry. Angew. Chem. Int. Ed. Engl. 2013, 52, 10438-56.

26. Seeber, R.; Zanardi, C.; Inzelt, G. The inherent coupling of charge transfer and mass transport processes: the curious electrochemical reversibility. ChemTexts 2016, 2, 8.

27. Kwan, K. W.; Ngan, A. H. W. A tuneable ionic memristor based on bipolar electrochemistry. J. Mater. Chem. C. 2025, 13, 17537-43.

28. Yu, L.; Hou, Y.; Wang, Y.; et al. Quartz nonadherent and clean exfoliation of the heteroatom-doped bulk carbon nanotubes array. Nano. Lett. 2023, 23, 9383-91.

29. Yang, D.; Tian, D.; Xue, C.; et al. Tuned fabrication of the aligned and opened CNT membrane with exceptionally high permeability and selectivity for bioalcohol recovery. Nano. Lett. 2018, 18, 6150-6.

30. Hosseini, H.; Ghaffarzadeh, M. Surface functionalization of carbon nanotubes via plasma discharge: a review. Inorg. Chem. Commun. 2022, 138, 109276.

31. Mechelhoff, M.; Kelsall, G. H.; Graham, N. J. Electrochemical behaviour of aluminium in electrocoagulation processes. Chem. Eng. Sci. 2013, 95, 301-12.

32. Seidenberg, J. R.; Mitsos, A.; Bongartz, D. Interpreting concentration and activation overpotentials in electrochemical systems: a critical discussion. J. Electrochem. Soc. 2025, 172, 043506.

33. Natishan, P. M.; O’grady, W. E. Chloride ion interactions with oxide-covered aluminum leading to pitting corrosion: a review. J. Electrochem. Soc. 2014, 161, C421-32.

34. Liu, Y.; Chandresh, A.; Heinke, L. Impact of the channel length in nanoporous electric double-layer capacitors on the charge transport explored by metal-organic framework films. ACS. Phys. Chem. Au. 2025, 5, 266-73.

35. Falvo, M. R.; Clary, G. J. Taylor RM, 2. N. D.; et al. Bending and buckling of carbon nanotubes under large strain. Nature 1997, 389, 582-4.

36. Wang, C.; Liu, Y.; Al-ghalith, J.; Dumitrică, T.; Wadee, M.; Tan, H. Buckling behavior of carbon nanotubes under bending: from ripple to kink. Carbon 2016, 102, 224-35.

37. Chen, K.; Tsutsui, M.; Zhuge, F.; et al. Nanochannel - based interfacial memristor: electrokinetic analysis of the frequency characteristics. Adv. Electron. Mater. 2021, 7, 2000848.

38. Zucker, R. S.; Regehr, W. G. Short-term synaptic plasticity. Annu. Rev. Physiol. 2002, 64, 355-405.

39. Blitz, D. M.; Foster, K. A.; Regehr, W. G. Short-term synaptic plasticity: a comparison of two synapses. Nat. Rev. Neurosci. 2004, 5, 630-40.

40. Kamsma, T. M.; Kim, J.; Kim, K.; et al. Brain-inspired computing with fluidic iontronic nanochannels. Proc. Natl. Acad. Sci. U. S. A. 2024, 121, e2320242121.

41. Xu, Y. T.; Yu, S. Y.; Li, Z.; et al. A nanofluidic spiking synapse. Proc. Natl. Acad. Sci. U. S. A. 2024, 121, e2403143121.

42. Ramirez-morales, R. R.; Ponce-ponce, V. H.; Molina-lozano, H.; Sossa-azuela, H.; Islas-garcía, O.; Rubio-espino, E. Analog implementation of a spiking neuron with memristive synapses for deep learning processing. Mathematics 2024, 12, 2025.

43. Li, P.; Liu, J.; Yuan, J. H.; et al. Artificial funnel nanochannel device emulates synaptic behavior. Nano. Lett. 2024, 24, 6192-200.

44. Ramirez, P.; Portillo, S.; Cervera, J.; et al. Neuromorphic responses of nanofluidic memristors in symmetric and asymmetric ionic solutions. J. Chem. Phys. 2024, 160.

45. Li, J.; Xu, H.; Sun, S.; et al. In situ learning in hardware compatible multilayer memristive spiking neural network. IEEE. Trans. Cogn. Dev. Syst. 2022, 14, 448-61.

46. Noh, Y.; Smolyanitsky, A. Synaptic-like plasticity in 2D nanofluidic memristor from competitive bicationic transport. Sci. Adv. 2024, 10, eadr1531.

47. Zhang, P.; Xia, M.; Zhuge, F.; et al. Nanochannel-based transport in an interfacial memristor can emulate the analog weight modulation of synapses. Nano. Lett. 2019, 19, 4279-86.