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Gotowe bibliografie tematyczne / Nanofluidic memristors

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Gotowa bibliografia na temat „Nanofluidic memristors”

Autor: Grafiati

Data publikacji: 2 czerwca 2025

Data aktualizacji: 31 lipca 2025

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Artykuły w czasopismach na temat "Nanofluidic memristors"

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Rivera-Sierra, Gonzalo, Patricio Ramirez, Juan Bisquert, and Agustín Bou. "Relaxation Time of Multipore Nanofluidic Memristors for Neuromorphic Applications." Journal of the American Chemical Society xxx, no. xxx (2025): A—J. https://doi.org/10.1021/jacs.5c04903.

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Memristors have been positioned at the forefront of the purposes for carrying out neuromorphic computation. Their tunable conductance properties enable the imitation of synaptic behavior. Nanofluidic memristors made of multipore membranes have shown their memristic properties and are candidate devices for liquid neuromorphic systems. Such properties are visible through an inductive hysteresis in the current–voltage sweeps, which is then confirmed by the inductive characteristics in impedance spectroscopy measurements. The dynamic behavior of memristors is largely determined by a voltage-

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Ismail, Abdulghani, and Boya Radha. "Mechano-ionic memristors for nanofluidic logic." Nature Electronics 7, no. 4 (2024): 258–59. http://dx.doi.org/10.1038/s41928-024-01150-y.

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Robin, P., T. Emmerich, A. Ismail, et al. "Long-term memory and synapse-like dynamics in two-dimensional nanofluidic channels." Science 379, no. 6628 (2023): 161–67. http://dx.doi.org/10.1126/science.adc9931.

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Fine-tuned ion transport across nanoscale pores is key to many biological processes, including neurotransmission. Recent advances have enabled the confinement of water and ions to two dimensions, unveiling transport properties inaccessible at larger scales and triggering hopes of reproducing the ionic machinery of biological systems. Here we report experiments demonstrating the emergence of memory in the transport of aqueous electrolytes across (sub)nanoscale channels. We unveil two types of nanofluidic memristors depending on channel material and confinement, with memory ranging from minutes

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Robin, Paul, Nikita Kavokine, and Lydéric Bocquet. "Modeling of emergent memory and voltage spiking in ionic transport through angstrom-scale slits." Science 373, no. 6555 (2021): 687–91. http://dx.doi.org/10.1126/science.abf7923.

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Recent advances in nanofluidics have enabled the confinement of water down to a single molecular layer. Such monolayer electrolytes show promise in achieving bioinspired functionalities through molecular control of ion transport. However, the understanding of ion dynamics in these systems is still scarce. Here, we develop an analytical theory, backed up by molecular dynamics simulations, that predicts strongly nonlinear effects in ion transport across quasi–two-dimensional slits. We show that under an electric field, ions assemble into elongated clusters, whose slow dynamics result in hysteret

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Bu, Yang, Zisun Ahmed, and Levent Yobas. "A nanofluidic memristor based on ion concentration polarization." Analyst 144, no. 24 (2019): 7168–72. http://dx.doi.org/10.1039/c9an01561b.

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Sheng, Qian, Yanbo Xie, Jun Li, Xinwei Wang, and Jianming Xue. "Transporting an ionic-liquid/water mixture in a conical nanochannel: a nanofluidic memristor." Chemical Communications 53, no. 45 (2017): 6125–27. http://dx.doi.org/10.1039/c7cc01047h.

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Vargas, J. V. C. "EDITORIAL." Revista de Engenharia Térmica 11, no. 1-2 (2012): 02. http://dx.doi.org/10.5380/reterm.v11i1-2.61972.

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Around the end of the twentieth century, nanotechnology appeared to be the new breakthrough, after the internet, for example. At that time, more efficient and affordable solar cells, green chemistry, quantum computing, lightweight composite aircraft, cell-size robots for medical applications were expected to be available soon. When the financial milestones did not become real, investors got disappointed and decided to rethink their plans. Yet today the perspectives are surprisingly upbeat. Currently, it is well known that restructuring matter at the nanoscale chemical and thermophysical proper

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Xu, Guoheng, Miliang Zhang, Tingting Mei, Wenchao Liu, Li Wang, and Kai Xiao. "Nanofluidic Ionic Memristors." ACS Nano, July 18, 2024. http://dx.doi.org/10.1021/acsnano.4c06467.

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Zhou, Xi, Yuanyuan Zong, Yongchang Wang, et al. "Nanofluidic memristor by elastic deformation of nanopores with nanoparticles adsorption." National Science Review, August 11, 2023. http://dx.doi.org/10.1093/nsr/nwad216.

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Abstract The memristor is the building blocks for neuromorphic computing. Hereby we reported a new type of nanofluidic memristor, by the principle of elastic strain on the polymer nanopores. With nanoparticles absorbed at the wall of a single conical polymer nanopore, we found pinched hysteresis of a current within scanning frequency between 0.01Hz and 0.1Hz, but switching to a diode below 0.01Hz and a resistor above 0.1Hz. We attributed the current hysteresis to the elastic strain at the tip side of the nanopore, caused by electrical force on the particles adsorbed at the inner wall surface.

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Portillo, Sergio, José A. Manzanares, Patricio Ramirez, Juan Bisquert, Salvador Mafe, and Javier Cervera. "pH-Dependent Effects in Nanofluidic Memristors." Journal of Physical Chemistry Letters, July 24, 2024, 7793–98. http://dx.doi.org/10.1021/acs.jpclett.4c01610.

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Streszczenia konferencji na temat "Nanofluidic memristors"

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Cervera, Javier, Patricio Ramirez, Sergio Portillo, Salvador Mafe, and Juan Bisquert. "Synaptical Tunability of Multipore Nanofluidic Memristors." In Neuronics Conference. FUNDACIO DE LA COMUNITAT VALENCIANA SCITO, 2023. http://dx.doi.org/10.29363/nanoge.neuronics.2024.016.

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Xie, Yanbo. "Resistance-restorable nanofluidic memristor and neuromorphic chip." In Neuronics Conference 2025. FUNDACIO DE LA COMUNITAT VALENCIANA SCITO, 2025. https://doi.org/10.29363/nanoge.neuronics.2025.014.

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Zhang, Pan, Long Xiao, Min Xia, Wei Li, and Wenping Guo. "Investigation of the mechanism for nanofluidic memristor by applying fluorescent characterization." In Optical Sensing and Imaging Technology, edited by HaiMei Gong, John E. Greivenkamp, Jun Tanida, Yadong Jiang, Jin Lu, and Dong Liu. SPIE, 2019. http://dx.doi.org/10.1117/12.2548151.

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