Triple VTe2/graphene/VTe2 heterostructures as perspective magnetic tunnel junctions

Begunovich, Lyudmila V.; Kuklin, Artem V.; Visotin, Maxim A.; Кузубов, А. А.; Tomilin, Felix N.; Tarasov, A. S.; Mikhalev, Yuri G.; Аврамов, Павел В.

doi:10.1016/j.apsusc.2020.145315

Cited by 23 publications

(13 citation statements)

References 66 publications

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“…The MTJ consists of an insulator sandwiched between two magnetic electrodes. Previous investigations show that many exceptional spin-related phenomena such as spin filtering, tunnel magnetoresistance (TMR), and the Kondo effect, have been discovered in these junctions. − TMR is an important physical phenomenon that has a tremendous economic impact on magnetic information storage, including magnetoresistive random access memory (MRAM), microwave generators, radiofrequency sensors, and neuromorphic computing networks. Since the first detection of TMR in the FM/Al 2 O 3 /FM junction at room temperature, , a great deal of efforts has been made to this issue.…”

Section: Introductionmentioning

confidence: 99%

Perfect Spin Filtering Effect on Fe₃GeTe₂-Based Van der Waals Magnetic Tunnel Junctions

Zhang

et al. 2020

J. Phys. Chem. C

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Conventional magnetic tunnel junctions (MTJs) face many issues in experiments and cannot meet a human’s urgent demand. Thus, van der Waals (vdW) MTJs increase in response to the proper time and conditions. By employing the combination of density functional theory (DFT) with the nonequilibrium Green’s function (NEGF) methods, Fe3GeTe2|InSe|Fe3GeTe2 vdW MTJs is proposed for the first time. Fe3GeTe2 has proven to be an excellent electrode for vdW MTJ applications, which shows a nature metallic FM characteristic with a high Curie temperature. Furthermore, semiconductor InSe with high electron mobility, a quantum Hall effect, and high stability is selected to be used as a tunneling barrier without lattice mismatching. Our designed MTJs show equal ability as a spin up and spin down filter. One can obtain a different spin-directional current only by changing the bias polarity without very high purity addition. Furthermore, a high tunnel magnetoresistance (TMR) ratio can reach up to ∼700%. The physical mechanisms behind this interesting phenomenon are given by analyzing k ||-resolved transmission spectra and a complex band structure. Our results would provide theoretical foundation for designing two-dimensional spintronic logic, ultrafast magnetodynamics devices and information storage for new generation computer devices.

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Section: Introductionmentioning

confidence: 99%

Perfect Spin Filtering Effect on Fe₃GeTe₂-Based Van der Waals Magnetic Tunnel Junctions

Zhang

et al. 2020

J. Phys. Chem. C

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“…Reported TMR ratio from 1995 to 2022 for MTJs with Al 2 O 3 barriers, [ 69,83–87 ] MgO barriers, [ 75,88–95 ] and nonoxide barriers. [ 62,64,79,96–104 ] …”

Section: Memristor Switching Mechanismsmentioning

confidence: 99%

“…[69,[83][84][85][86][87] MgO barriers, [75,[88][89][90][91][92][93][94][95] and nonoxide barriers. [62,64,79,[96][97][98][99][100][101][102][103][104] junctions. An FTJ is a two-terminal device with an ultrathin ferroelectric layer in the middle and asymmetric conductive layers (usually metals or semiconductors) on both sides.…”

Section: Ferroelectric Tunnel Junctionmentioning

confidence: 99%

“…Annealing [70] Magnetron sputtering [66] STT MTJ [207] SOT MTJ [102] Quard MTJ [214] Ferroelectric tunnel junction PbTiO 3 , [109] BaTiO 3 , [126] SrTiO 3 , [120] Nb:SrTiO 3 [20] Limitations of tunnel height and tunnel length of ferroelectric barriers MFS [118] Extra dielectric layer [120] Doping [20] Phase change memory GST, [134] InGeTe, [138] GeSb, [142] Te-free SiSb [141] The uncontrollable crystallinity of phase change materials and large programming current Doping [138] Thin film deposition [193] Photolithography [20] Pore structure [165] µtrench structure [18] Thermal isolation [129] by shrinking the size of the memristor. The smallest memristor feature size is around two nanometers so far.…”

Section: Electrochemical Metallizationmentioning

confidence: 99%

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Essential Characteristics of Memristors for Neuromorphic Computing

Chen

Song

Wang

et al. 2022

Adv Elect Materials

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increasingly problematic. Unlike the Von Neumann computing platform, the human brain relies on neurons and synapses for storage and computation, which do not have clear boundaries between them. Therefore, nanodevices that mimic synapses, for high-efficiency computing, have been investigated; among these nanodevices, memristors have attracted most attention because of their low power consumption, high integration density, and the ability to simulate synaptic plasticity, which meet the standards of neuromorphic computing. [4] The first report on the resistive switching phenomenon dates back to the 1960s; [5] since early theories were insufficient to explain this phenomenon, research had been done on it. It was not until the memristor was theoretically proposed in 1971, that the mechanisms underpinning the resistive switching became abundant. [6] The first memristor was manufactured by Hewlett-Packard in 2008. [7] Since then, memristors made of diverse materials have been successfully studied, including conductive filament memristors, magnetic tunnel junctions, ferroelectric tunnel junctions, phase-change memristors, and so on (Figure 1). These devices have been used for storage and computing purposes. [8,9] In recent years, there have been many reviews investigating neuromorphic computing from the perspectives of device electrical properties, [9,10] resistive switching materials, [11,12] memristive synapses and neurons, [13] algorithm optimization, [14] and circuit design. [15] Different from the existing literature, we discuss the possibility of achieving brain-like computing from the perspective of memristor technology and review the establishment of spiking neural network neuromorphic computing systems. In this article, we first review the resistive switching mechanisms of different types of memristors and focus on factors, which affect device stability and the corresponding optimization measures that have been applied. Furthermore, we study the stochasticity, power consumption, switching speed, retention, endurance, and other properties of memristors, which are the basis for neuromorphic computing implementations. We then review various memristor-based neural networks and the building of spike neural network neuromorphic computing systems. Finally, we shed light upon the major challenges and offer our perspectives and opinions for memristor-based brainlike computing systems.The memristor is a resistive switch where its resistive state is programable based on the applied voltage or current. Memristive devices are thus capable of storing and computing information simultaneously, breaking the Von Neumann bottleneck. Since the first nanomemristor made by Hewlett-Packard in 2008, advances so far have enabled nanostructured, low-power, high-durability devices that exhibit superior performance over conventional CMOS devices. Herein, the development of memristors based on different physical mechanisms is reviewed. In particular, device stability, integration density, power consumption, switching speed, retention, and e...

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Section: Introductionmentioning

confidence: 99%

Above-room Curie temperature and barrier-layer-dependent tunneling magnetoresistance in 1T-CrO₂ monolayer based magnetic tunnel junctions

Liu

Tang

Gan

et al. 2022

Phys. Chem. Chem. Phys.

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Triple VTe2/graphene/VTe2 heterostructures as perspective magnetic tunnel junctions

Cited by 23 publications

References 66 publications

Perfect Spin Filtering Effect on Fe₃GeTe₂-Based Van der Waals Magnetic Tunnel Junctions

Perfect Spin Filtering Effect on Fe₃GeTe₂-Based Van der Waals Magnetic Tunnel Junctions

Essential Characteristics of Memristors for Neuromorphic Computing

Above-room Curie temperature and barrier-layer-dependent tunneling magnetoresistance in 1T-CrO₂ monolayer based magnetic tunnel junctions

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Triple VTe2/graphene/VTe2 heterostructures as perspective magnetic tunnel junctions

Cited by 23 publications

References 66 publications

Perfect Spin Filtering Effect on Fe3GeTe2-Based Van der Waals Magnetic Tunnel Junctions

Perfect Spin Filtering Effect on Fe3GeTe2-Based Van der Waals Magnetic Tunnel Junctions

Essential Characteristics of Memristors for Neuromorphic Computing

Above-room Curie temperature and barrier-layer-dependent tunneling magnetoresistance in 1T-CrO2 monolayer based magnetic tunnel junctions

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Perfect Spin Filtering Effect on Fe₃GeTe₂-Based Van der Waals Magnetic Tunnel Junctions

Perfect Spin Filtering Effect on Fe₃GeTe₂-Based Van der Waals Magnetic Tunnel Junctions

Above-room Curie temperature and barrier-layer-dependent tunneling magnetoresistance in 1T-CrO₂ monolayer based magnetic tunnel junctions