Linearly potentiated synaptic weight modulation at nanoscale in a highly stable two-terminal memristor
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OpenAlex topics: Advanced Memory and Neural Computing · Neuroscience and Neural Engineering · Photoreceptor and optogenetics research
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References (72)
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1. L.A. Hart, Human Brain and Human Learning; Longman, New York, 1983.
2. E.R. Kandel, J.H. Schwartz, Principles of Neural Science, 2nd ed., Elsevier, New York, 1985.
3. Training and operation of an integrated neuromorphic network based on metal-oxide memristors10.1038/nature14441 ↗
4. In-memory computing with resistive switching devices10.1038/s41928-018-0092-2 ↗
5. Two-terminal floating-gate transistors with a low-power memristive operation mode for analogue neuromorphic computing10.1038/s41928-019-0331-1 ↗
6. Neuromorphic Engineering for Hardware Computational Acceleration and Biomimetic Perception Motion Integration10.1002/aisy.202000124 ↗
7. Neuro-inspired computing chips10.1038/s41928-020-0435-7 ↗
8. Shimeng Yu, Neuro-inspired Computing Using Resistive Synaptic Devices, Springer International Publishing, 2017. https://doi.org/10.1007/978-3-319-54313-0.10.1007/978-3-319-54313-0 ↗
9. Site-Specific Regulated Memristors via Electron-Beam-Induced Functionalization of HfO210.1002/smll.202105585 ↗
10. Highly transparent solid-state artificial synapse based on oxide memristor10.1016/j.apsusc.2020.147738 ↗
11. Control of Synaptic Plasticity Learning of Ferroelectric Tunnel Memristor by Nanoscale Interface Engineering10.1021/acsami.8b01469 ↗
12. A Transparent Photonic Artificial Visual Cortex10.1002/adma.201903095 ↗
13. Oxide-based RRAM materials for neuromorphic computing10.1007/s10853-018-2134-6 ↗
14. Memristive Synapses and Neurons for Bioinspired Computing10.1002/aelm.201900287 ↗
15. Mimicking Biological Synaptic Functionality with an Indium Phosphide Synaptic Device on Silicon for Scalable Neuromorphic Computing10.1021/acsnano.7b08272 ↗
16. Brain-like spatiotemporal information processing with nanosized second-order synaptic emulators; “solid-state memory visualizer”10.1016/j.nanoen.2020.105014 ↗
17. Recent Progress in Artificial Synapses Based on Two-Dimensional van der Waals Materials for Brain-Inspired Computing10.1021/acsaelm.9b00694 ↗
18. Artificial Synapses Emulated by an Electrolyte-Gated Tungsten-Oxide Transistor10.1002/adma.201801548 ↗
19. Evolution of Bio-Inspired Artificial Synapses: Materials, Structures, and Mechanisms
20. Analog-Type Resistive Switching Devices for Neuromorphic Computing
21. Neuro-Inspired Computing with Emerging Nonvolatile Memorys10.1109/JPROC.2018.2790840 ↗
22. Brain-like associative learning using a nanoscale non-volatile phase change synaptic device array10.3389/fnins.2014.00205 ↗
23. Y. Kaneko, Y. Nishitani, M. Ueda, Ferroelectric Artificial Synapses for Recognition of a Multishaded Image, IEEE Trans. Electron. Devices 61 (2014). http://doi.org/ 10.1109/TED.2014.2331707.10.1109/TED.2014.2331707 ↗
24. SiGe epitaxial memory for neuromorphic computing with reproducible high performance based on engineered dislocations10.1038/s41563-017-0001-5 ↗
25. Energy-Efficient Organic Ferroelectric Tunnel Junction Memristors for Neuromorphic Computing10.1002/aelm.201800795 ↗
26. Synaptic learning and memory functions achieved using oxygen ion migration/diffusion in an amorphous InGaZnO memristor10.1002/adfm.201103148 ↗
27. Controllable digital resistive switching for artificial synapses and pavlovian learning algorithm10.1039/C9NR02027F ↗
28. Improvement of Conductance Modulation Linearity in a Cu2+-Doped KNbO3 Memristor through the Increase of the Number of Oxygen Vacancies10.1021/acsami.9b18794 ↗
29. Highly Linear and Symmetric Weight Modification in HfO2-Based MWeight Entries
30. Electric-field-induced healing of inanimate topographies: Multistate resistive switching and nano-sized artificial synapse functionality10.1016/j.apsusc.2020.147190 ↗
31. Emulation of bio-synaptic behaviours in copper-doped zinc oxide memristors: A nanoscale scanning probe microscopic study10.1016/j.apsusc.2022.154860 ↗
32. Brain-like spatiotemporal information processing with nanosized second-order synaptic emulators; “ solid-state memory visualizer10.1016/j.nanoen.2020.105014 ↗
33. Neuro-inspired computing chips10.1038/s41928-020-0435-7 ↗
34. Highly Linear and Symmetric Weight Modification in HfO2-Based Memristive Devices for High-Precision Weight Entries10.1002/aelm.202000434 ↗
35. 2019_Analog-Type Resistive Switching Devices for Neuromorphic Computing.pdf10.1002/pssr.201900204 ↗
36. Improved Synaptic Behavior Under Identical Pulses Using AlOx/HfO2 Bilayer RRAM Array for Neuromorphic Systems10.1109/LED.2016.2582859 ↗
37. Enhanced Switching Properties in TaOx Memristors Using Diffusion Limiting Layer for Synaptic Learning10.1109/JEDS.2020.2966799 ↗
38. Enhancing the synaptic properties of low-power and forming-free HfOx/TaOy/HfOx resistive switching devices10.1016/j.mee.2020.111358 ↗
39. A Methodology to Improve Linearity of Analog RRAM for Neuromorphic Computing, IEEE Symp
40. Gradual switching and self-rectifying characteristics of Cu/α-IGZO/p+-Si RRAM for synaptic device application10.1016/j.sse.2018.10.003 ↗
41. Toward a Reliable Synaptic Simulation Using Al-Doped HfO2 RRAM10.1021/acsami.9b21530 ↗
42. Adaptive Crystallite Kinetics in Homogenous Bilayer Oxide Memristor for Emulating Diverse Synaptic Plasticity10.1002/adfm.201706927 ↗
43. Long-term and short-term plasticity of Ta2O5/HfO2 memristor for hardware neuromorphic application10.1016/j.jallcom.2020.156675 ↗
44. M. Kumar, T. Som, Structural defect-dependent resistive switching in Cu-O/Si studied by Kelvin probe force microscopy and conductive atomic force microscopy, Nanotechnology. 26 (2015) 345702. https://doi.org/10.1088/0957-4484/26/34/345702.10.1088/0957-4484/26/34/345702 ↗
45. Dendritic Computation10.1146/annurev.neuro.28.061604.135703 ↗
46. Neuronal arithmetic10.1038/nrn2864 ↗
47. Studies on RF magnetron sputtered HfO2 thin films for microelectronic applications10.1007/s13391-015-4490-6 ↗
48. Oxygen partial pressure influenced stoichiometry, structural, electrical, and optical properties of DC reactive sputtered hafnium oxide films10.1002/sia.6902 ↗
49. Microstructures of HfOx Films Prepared via Atomic Layer Deposition Using La(NO3)3_6H2O Oxidants10.3390/ma14237478 ↗
50. Experimental and theoretical study of the synthesis of N-doped TiO2 by N ion implantation of TiO2 thin films10.1016/j.apsusc.2020.148493 ↗
51. Local Ion Irradiation-Induced Resistive Threshold and Memory Switching in Nb 2 O 5 /NbO x Films10.1021/am5021149 ↗
52. Surface studies of the chemical environment in gold nanorods supported by X-ray photoelectron spectroscopy (XPS) and ab initio calculations10.1016/j.jmrt.2021.08.059 ↗
53. In-Situ XPS Monitoring and Characterization of Electrochemically Prepared Au Nanoparticles in an Ionic Liquid10.1021/acsomega.6b00456 ↗
54. Self-organized titanium oxide nano-channels for resistive memory application10.1063/1.4936961 ↗
55. Ion Beam-Mediated Defect Engineering in TiO x Thin Films for Controlled Resistive Switching Property and Application10.1021/acsaelm.1c00417 ↗
56. Electronic properties of hafnium oxide: A contribution from defects and traps10.1016/j.physrep.2015.11.002 ↗
57. Tridyn-binary collision simulation of atomic collisions and dynamic composition changes in solids10.1016/0010-4655(88)90148-8 ↗
58. Pd/IGZO/p + -Si Synaptic Device with Self-Graded Oxygen Concentrations for Highly Linear Weight Adjustability and Improved Energy Efficiency10.1021/acsaelm.0c00341 ↗
59. Investigation and Manipulation of Different Analog Behaviors of Memristor as Electronic Synapse for Neuromorphic Applications
60. An Electronic Synapse Device Based on Metal Oxide Resistive Switching Memory for Neuromorphic Computation10.1109/TED.2011.2147791 ↗
61. Engineering the Synaptic Kinetic Process into Memristive Device10.1002/aelm.201800096 ↗
62. Bienenstock, Cooper, and Munro Learning Rules Realized in Second-Order Memristors with Tunable Forgetting Rate10.1002/adfm.201807316 ↗
63. Toward a generalized Bienenstock-Cooper-Munro rule for spatiotemporal learning via triplet-STDP in memristive devices
64. The Effect of Repetitive Stimulation on Facilitation of Transmitter Release at the Frog Neuromuscular Junction10.1113/jphysiol.1973.sp010348 ↗
65. J.E. Magleby, L. K.; Zengel, A Quantitative Description of Stimulation-induced Changes in Transmitter Release at the Frog Neuromuscular Junction, J. Gen. Physiol. 80 (1982) 613–638. https://doi.org/10.1085/jgp.80.4.613.10.1085/jgp.80.4.613 ↗
66. Determinants of the Time Course of Facilitation at the Granule Cell to Purkinje Cell Synapse10.1523/JNEUROSCI.16-18-05661.1996 ↗
67. Synaptic computation10.1038/nature03010 ↗
68. Short-Term Plasticity and Long-Term Potentiation in Artificial Biosynapses with Diffusive Dynamics10.1021/acsnano.7b08331 ↗
69. Arti fi cial Synapses with Short- and Long-Term Memory for Spiking Neural Networks Based on Renewable Materials10.1021/acsnano.7b03347 ↗
70. The role of synaptic ion channels in synaptic plasticity10.1038/sj.embor.7400830 ↗
71. Freestanding Artificial Synapses Based on Laterally Proton-Coupled Transistors on Chitosan Membranes10.1002/adma.201502719 ↗
72. R.S. Zucker, W.G. Regehr, S HORT -T ERM S YNAPTIC P LASTICITY, Annu. Rev. Physiol. (2002) 355–405. https://doi.org/10.1146/annurev.physiol.64.092501.114547.10.1146/annurev.physiol.64.092501.114547 ↗