Issue
Natl Sci Open
Volume 1, Number 3, 2022
Special Topic: Novel Optoelectronic Devices
Article Number 20220020
Number of page(s) 13
Section Information Sciences
DOI https://doi.org/10.1360/nso/20220020
Published online 10 August 2022
  • Pedretti G, Milo V, Ambrogio S, et al. Memristive neural network for on-line learning and tracking with brain-inspired spike timing dependent plasticity. Sci Rep 2017; 7: 5288. [Article] [Google Scholar]
  • Ielmini D, Wong HSP. In-memory computing with resistive switching devices. Nat Electron 2020; 1: 333-343. [Article] [Google Scholar]
  • Zhang C, Zhou H, Chen S, et al. Recent progress on 2D materials-based artificial synapses. Crit Rev Solid State Mater Sci 2021; https://doi.org/10.1080/10408436.2021.1935212 [Google Scholar]
  • Porro S, Accornero E, Pirri CF, et al. Memristive devices based on graphene oxide. Carbon 2015; 85: 383-396. [Article] [CrossRef] [Google Scholar]
  • Jo SH, Chang T, Ebong I, et al. Nanoscale memristor device as synapse in neuromorphic systems. Nano Lett 2010; 10: 1297-1301. [Article] [Google Scholar]
  • Schranghamer TF, Oberoi A, Das S. Graphene memristive synapses for high precision neuromorphic computing. Nat Commun 2020; 11: 1. [Article] [Google Scholar]
  • Sharbati MT, Du Y, Torres J, et al. Low-power, electrochemically tunable graphene synapses for neuromorphic computing. Adv Mater 2018; 30: 1802353. [Article] [NASA ADS] [CrossRef] [Google Scholar]
  • Pickett MD, Medeiros-Ribeiro G, Williams RS. A scalable neuristor built with Mott memristors. Nat Mater 2013; 12: 114-117. [Article] [Google Scholar]
  • Goi E, Zhang Q, Chen X, et al. Perspective on photonic memristive neuromorphic computing. PhotoniX 2020; 1: 3. [Article] [Google Scholar]
  • Wang Z, Joshi S, Savel’ev S, et al. Fully memristive neural networks for pattern classification with unsupervised learning. Nat Electron 2018; 1: 137-145. [Article] [Google Scholar]
  • Strukov DB, Snider GS, Stewart DR, et al. The missing memristor found. Nature 2008; 453: 80-83. [Article] [Google Scholar]
  • Hui F, Grustan-Gutierrez E, Long S, et al. Graphene and related materials for resistive random access memories. Adv Electron Mater 2017; 3: 1600195. [Article] [CrossRef] [Google Scholar]
  • Ji Y, Cho B, Song S, et al. Stable switching characteristics of organic nonvolatile memory on a bent flexible substrate. Adv Mater 2010; 22: 3071-3075. [Article] [NASA ADS] [CrossRef] [PubMed] [Google Scholar]
  • Wang H, Zou C, Zhou L, et al. Resistive switching characteristics of thin NiO film based flexible nonvolatile memory devices. MicroElectron Eng 2012; 91: 144-146. [Article] [Google Scholar]
  • Liang J, Chen Y, Xu Y, et al. Toward all-carbon electronics: Fabrication of graphene-based flexible electronic circuits and memory cards using maskless laser direct writing. ACS Appl Mater Interfaces 2010; 2: 3310-3317. [Article] [CrossRef] [PubMed] [Google Scholar]
  • Yang YC, Pan F, Liu Q, et al. Fully room-temperature-fabricated nonvolatile resistive memory for ultrafast and high-density memory application. Nano Lett 2009; 9: 1636-1643. [Article] [Google Scholar]
  • Long S, Perniola L, Cagli C, et al. Voltage and power-controlled regimes in the progressive unipolar RESET transition of HfO2-based RRAM. Sci Rep 2013; 3: 2929. [Article] [Google Scholar]
  • Yu M, Cai Y, Wang Z, et al. Novel vertical 3D structure of TaOx-based RRAM with self-localized switching region by sidewall electrode oxidation. Sci Rep 2016; 6: 21020. [Article] [Google Scholar]
  • Sarkar B, Lee B, Misra V. Understanding the gradual reset in Pt/Al2O3/Ni RRAM for synaptic applications. Semicond Sci Technol 2015; 30: 105014. [Article] [Google Scholar]
  • Shim JH, Hu Q, Park MR, et al. Resistive switching characteristics of TiO2 thin films with different electrodes. J Korean Phys Soc 2015; 67: 936-940. [Article] [NASA ADS] [CrossRef] [Google Scholar]
  • Sangwan VK, Jariwala D, Kim IS, et al. Gate-tunable memristive phenomena mediated by grain boundaries in single-layer MoS2. Nat Nanotech 2015; 10: 403-406. [Article] [Google Scholar]
  • Wu W, Wu H, Gao B, et al. Suppress variations of analog resistive memory for neuromorphic computing by localizing Vo formation. J Appl Phys 2018; 124: 152108. [Article] [CrossRef] [Google Scholar]
  • Liu J, Yin Z, Cao X, et al. Bulk heterojunction polymer memory devices with reduced graphene oxide as electrodes. ACS Nano 2010; 4: 3987-3992. [Article] [CrossRef] [PubMed] [Google Scholar]
  • Geim AK, Novoselov KS. The rise of graphene. Nat Mater 2007; 6: 183-191. [Article] [Google Scholar]
  • Rehman MM, Rehman HMMU, Gul JZ, et al. Decade of 2D-materials-based RRAM devices: A review. Sci Tech Adv Mater 2020; 21: 147-186. [Article] [Google Scholar]
  • Wan Z, Streed EW, Lobino M, et al. Laser-reduced graphene: Synthesis, properties, and applications. Adv Mater Technol 2018; 3: 1700315. [Article] [CrossRef] [Google Scholar]
  • Chen Y, Zhang B, Liu G, et al. Graphene and its derivatives: Switching on and off. Chem Soc Rev 2012; 41: 4688-4707. [Article] [PubMed] [Google Scholar]
  • Tian H, Chen HY, Ren TL, et al. Cost-effective, transfer-free, flexible resistive random access memory using laser-scribed reduced graphene oxide patterning technology. Nano Lett 2014; 14: 3214-3219. [Article] [Google Scholar]
  • Wan Z, Umer M, Lobino M, et al. Laser induced self-N-doped porous graphene as an electrochemical biosensor for femtomolar miRNA detection. Carbon 2020; 163: 385-394. [Article] [CrossRef] [Google Scholar]
  • Yang C, Huang Y, Cheng H, et al. Rollable, stretchable, and reconfigurable graphene hygroelectric generators. Adv Mater 2019; 31: 1805705. [Article] [Google Scholar]
  • Zhao F, Cheng H, Hu Y, et al. Functionalized graphitic carbon nitride for metal-free, flexible and rewritable nonvolatile memory device via direct laser-writing. Sci Rep 2015; 4: 5882. [Article] [Google Scholar]
  • Bhaumik A, Narayan J. Wafer scale integration of reduced graphene oxide by novel laser processing at room temperature in air. J Appl Phys 2016; 120: 105304. [Article] [NASA ADS] [CrossRef] [Google Scholar]
  • Cui P, Seo S, Lee J, et al. Nonvolatile memory device using gold nanoparticles covalently bound to reduced graphene oxide. ACS Nano 2011; 5: 6826-6833. [Article] [CrossRef] [PubMed] [Google Scholar]
  • Wan Z, Wang S, Haylock B, et al. Tuning the sub-processes in laser reduction of graphene oxide by adjusting the power and scanning speed of laser. Carbon 2019; 141: 83-91. [Article] [CrossRef] [Google Scholar]
  • Zhang Y, Guo L, Wei S, et al. Direct imprinting of microcircuits on graphene oxides film by femtosecond laser reduction. Nano Today 2010; 5: 15-20. [Article] [Google Scholar]
  • Zhang YL, Guo L, Xia H, et al. Photoreduction of graphene oxides: Methods, properties, and applications. Adv Opt Mater 2014; 2: 10-28. [Article] [CrossRef] [Google Scholar]
  • Chen HY, Han D, Tian Y, et al. Mask-free and programmable patterning of graphene by ultrafast laser direct writing. Chem Phys 2014; 430: 13-17. [Article] [NASA ADS] [CrossRef] [Google Scholar]
  • Romero FJ, Toral-Lopez A, Ohata A, et al. Laser-fabricated reduced graphene oxide memristors. Nanomaterials 2019; 9: 897. [Article] [Google Scholar]
  • Strong V, Dubin S, El-Kady MF, et al. Patterning and electronic tuning of laser scribed graphene for flexible all-carbon devices. ACS Nano 2012; 6: 1395-1403. [Article] [CrossRef] [PubMed] [Google Scholar]
  • Belete M, Kataria S, Turfanda A, et al. Nonvolatile resistive switching in nanocrystalline molybdenum disulfide with ion-based plasticity. Adv Electron Mater 2020; 6: 1900892. [Article] [CrossRef] [Google Scholar]
  • He CL, Zhuge F, Zhou XF, et al. Nonvolatile resistive switching in graphene oxide thin films. Appl Phys Lett 2009; 95: 232101. [Article] [NASA ADS] [CrossRef] [Google Scholar]
  • Zhuge F, Hu B, He C, et al. Mechanism of nonvolatile resistive switching in graphene oxide thin films. Carbon 2011; 49: 3796-3802. [Article] [CrossRef] [Google Scholar]
  • Hu B, Quhe R, Chen C, et al. Electrically controlled electron transfer and resistance switching in reduced graphene oxide noncovalently functionalized with thionine. J Mater Chem 2012; 22: 16422-16430. [Article] [Google Scholar]
  • Liang A, Zhang J, Wang F, et al. Transparent HfOx-based memristor with robust flexibility and synapse characteristics by interfacial control of oxygen vacancies movement. Nanotechnology 2021; 32: 145202. [Article] [Google Scholar]
  • Sangwan VK, Lee HS, Bergeron H, et al. Multi-terminal memtransistors from polycrystalline monolayer molybdenum disulfide. Nature 2018; 554: 500-504. [Article] [Google Scholar]
  • Yoshida M, Suzuki R, Zhang Y, et al. Memristive phase switching in two-dimensional 1T-TaS2 crystals. Sci Adv 2015; 1: 1-7. [Article] [Google Scholar]
  • Zhu X, Li D, Liang X, et al. Ionic modulation and ionic coupling effects in MoS2 devices for neuromorphic computing. Nat Mater 2019; 18: 141-148. [Article] [Google Scholar]
  • Li D, Wu B, Zhu X, et al. MoS2 memristors exhibiting variable switching characteristics toward biorealistic synaptic emulation. ACS Nano 2018; 12: 9240-9252. [Article] [CrossRef] [PubMed] [Google Scholar]
  • Wang L, Liao W, Wong SL, et al. Artificial synapses based on multiterminal memtransistors for neuromorphic application. Adv Funct Mater 2019; 29: 1901106. [Article] [CrossRef] [Google Scholar]
  • Shi K, Wang Z, Xu H, et al. Complementary resistive switching observed in graphene oxide-based memory device. IEEE Electron Device Lett 2018; 39: 488-491. [Article] [NASA ADS] [CrossRef] [Google Scholar]
  • Kim I, Siddik M, Shin J, et al. Low temperature solution-processed graphene oxide/Pr0.7Ca0.3MnO3 based resistive-memory device. Appl Phys Lett 2011; 99: 042101. [Article] [NASA ADS] [CrossRef] [Google Scholar]
  • Gao S, Yi X, Shang J, et al. Organic and hybrid resistive switching materials and devices. Chem Soc Rev 2019; 48: 1531-1565. [Article] [PubMed] [Google Scholar]
  • Jetty P, Sahu DP, Jammalamadaka S. Analog resistive switching in reduced graphene oxide and chitosan-based bio-resistive random access memory device for neuromorphic computing applications. Physica Rapid Res Ltrs 2022; 16: 2100465. [Article] [Google Scholar]
  • Wang LH, Yang W, Sun QQ, et al. The mechanism of the asymmetric SET and RESET speed of graphene oxide based flexible resistive switching memories. Appl Phys Lett 2012; 100: 063509. [Article] [NASA ADS] [CrossRef] [Google Scholar]
  • Mkhoyan KA, Contryman AW, Silcox J, et al. Atomic and electronic structure of graphene-oxide. Nano Lett 2009; 9: 1058-1063. [Article] [Google Scholar]
  • Saini P, Singh M, Thakur J, et al. Probing the mechanism for bipolar resistive switching in annealed graphene oxide thin films. ACS Appl Mater Interfaces 2018; 10: 6521-6530. [Article] [CrossRef] [PubMed] [Google Scholar]
  • Du C, Cai F, Zidan MA, et al. Reservoir computing using dynamic memristors for temporal information processing. Nat Commun 2017; 8: 2204. [Article] [Google Scholar]
  • Sun L, Wang Z, Jiang J, et al. In-sensor reservoir computing for language learning via two-dimensional memristors. Sci Adv 2021; 7: eabg1455. [Article] [Google Scholar]
  • Appeltant L, Soriano MC, Van der Sande G, et al. Information processing using a single dynamical node as complex system. Nat Commun 2011; 2: 1-6. [Article] [Google Scholar]
  • Tanaka G, Yamane T, Héroux JB, et al. Recent advances in physical reservoir computing: A review. Neural Networks 2019; 115: 100-123. [Article] [Google Scholar]

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