**7. Conclusion**

Memristive systems based on 2D-crystals, a new class of nonvolatile electronic components, are capable of solving the problem of scaling. Self-organized synapse-like memristive systems controlled by transitions between sp3 and sp2 -configurations of carbon in an electric field can be applied in artificial neural networks and intelligent machines. The high-efficient switching of nonvolatile resistance in atomic single-layer TMD (MoS2 , MoSe2 , WS2 , WSe2 ) memory is due to the inherent nature of layered crystallinity, which creates clear interfaces and clean tunnel barriers, which prevents excessive leakage and creates stable states. 2D memory can be used for existing applications in the memory/calculation area, as well as in new applications for radio frequency switching with extremely low power consumption. 2D photomemristors with a floating photogate show multiple states controlled in a wide range of electromagnetic radiation and can find application for a wide range of tasks related to neuromorphic computations, image processing and recognition of sounds, movements and speech necessary to create artificial intelligence. The future development of 2D memristive systems should use the possibility of self-organizing technology to form artificial neural networks and heterointerface interactions of biocompatible 2D crystals, such as graphene, with natural neurons.

[3] Lossev O. Oscillating crystals. The Wireless World and Radio Review. 1924;**15**:93-96

No. 2,524,033; Issued October 3, 1950

Science. 1957;**126**:105-112

Physics Review. 1948;**74**:231-232

1951

230-231

2008;**453**:80-83

10.1143/JJAP.50.070110

Sendai, Japan; 2010

Society. 2014;**64**:1399-1402

thesis]. Moscow: Moscow State University; 2015

oxidation. Nanotechnology. 2017;**28**:204005

Review. 1949;**75**:1208-1225. DOI: 10.1103/PhysRev.75.1208

[4] Bardeen J. Three-electrode circuit element utilizing semiconductive materials. US. Patent

Memristive Systems Based on Two-Dimensional Materials

http://dx.doi.org/10.5772/intechopen.78973

87

[5] Bardeen J, Brattain WH. Physical principles involved in transistor action. Physics

[6] Bardeen J. Semiconductor research leading to the point contact transistor. Nobel Lecture.

[7] Shockley W. Semiconductor amplifier. U.S. Patent No. 2,569,347; Issued September 25,

[8] Bardeen J, Brattain WH. The transistor, a semiconductor triode. Physics Review. 1948;**74**:

[9] Brattain WH, Bardeen J. Nature of the forward current in germanium point contacts.

[10] Strukov DB, Snider GS, Stewart DR, Williams RS. The missing memristor found. Nature.

[11] Novoselov KS, Geim AK, Morozov SV, Jiang D, Zhang Y, Dubonos SV, Grigorieva IV, Firsov AA. Electric field effect in atomically thin carbon films. Science. 2004;**306**:666-669

[12] Panin GN, Kapitanova OO, Lee SW, Baranov AN, Kang TW. Resistive switching in al/ graphene oxide/al structure. Japanese Journal of Applied Physics. 2011;**50**:070110. DOI:

[13] Panin GN, Kapitanova OO, Lee SW, Baranov AN, Kang TW. In Abstract of the 2nd International Symposium on Graphene Devices: Technology, Physics and Modeling.

[14] Kapitanova OO, Panin GN, Baranov AN, Kang TW. Synthesis and properties of graphene oxide/graphene nanostructures. Journal of the Korean Physical Society. 2012;**60**:1789-1793

[15] Kapitanova OO, Panin GN, Kononenko OV, Baranov AN, Kang TW. Resistive switching in graphene/graphene oxide/ZnO heterostructures. Journal of the Korean Physical

[16] Kapitanova OO. Nanostructures with resistive switching based on graphene oxide [PhD

[17] Kapitanova OO, Panin GN, Cho HD, Baranov AN, Kang TW. Formation of self-assembled nanoscale graphene/graphene oxide photomemristive heterojunctions using photocatalytic

[18] Goldsmith BR, Coroneus JG, Khalap VR, Kane AA, Weiss GA, Collins PG. Conductancecontrolled point functionalization of single-walled carbon nanotubes. Science. 2007;**315**:77

[19] Nagareddy VK, Barnes MD, Zipoli F, Lai KT, Alexeev AM, Craciun MF, Wright CD. Multilevel ultrafast flexible nanoscale nonvolatile hybrid graphene oxide–titanium

oxide memories. ACS Nano. 2017;**11**:3010-3021. DOI: 10.1021/acsnano.6b08668
