ΑΝΑΚΟΙΝΩΣΗ

 Την Τρίτη 13 Δεκεμβρίου και ώρα 14:30 στην αίθουσα διδασκαλίας του ΠΜΣ Ηλεκτρονικής Φυσικής 213 (γυάλινο κτίριο) θα πραγματοποιηθεί διάλεξη με τίτλο

«Foundations of Memristor Theory»

από τον Dr.-Ing. habil. Alon Ascoli

Affiliation: Chair of Fundamentals of Electrical Engineering, Technische Universität Dresden

 

Abstract: With the CMOS aggressive downscaling trend approaching an inevitable end [1], intensive and extensive research is currently under way for engineering new materials, manufacturing novel devices, and developing innovative computing paradigms, to allow a sustainable progress in integrated circuit design beyond the Moore era. In this regard, the disruptive memristive nanotechnologies [2] promise to revolutionize the world of electronics in the years to come. With their extraordinary capability to combine multiple functionalities in one compact nanoscale physical volume, resistance switching memories may enable the implementation of ground-breaking data processing paradigms, including in-memory computing [3]-[4], in-memory sensing [5]-[6], and bio-inspired spike-based computing [7], as well as a bio-plausible reproduction of biological phenomena [8]-[9]. Despite the wide spectrum of opportunities, which memristors promise to open up in the electronics of the future, their inherent nonlinearity hinders their wide use in integrated circuit design. Recurring to the robust foundations of nonlinear circuit and system theory [10]-[12], overlooked for too long over the past few years, it is possible to acquire a deep understanding of the mechanisms, underlying the nonlinear dynamics of these nanodevices. This is a crucial preliminary step toward the development of a systematic approach to the design of novel circuits, which, exploiting the peculiar dynamics of memristors, shall improve the performance or extend the capabilities of state-of-the-art purely-CMOS electronic systems. This lecture discusses the fundamentals of memristor theory [13]-[14], explaining how the application of powerful nonlinear circuit- and system-theoretic methods may allow to gain precious insights into their operating principles.

 

References

[1]     R.S. Williams, “What’s next? [The end of Moore’s law]”, IEEE Comput. Sci. Eng., 19, 7-13, 2017, DOI: 10.1109/MCSE.2017.31

[2]     D. Ielmini and R. Waser, “Resistive Switching: From Fundamentals of Nanoionic Redox Processes to Memristive Device Applications,” 1st ed. Hoboken, NJ, USA: Wiley-VCH, 2016

[3]     D. Ielmini, and H.S.P. Wong, “In-memory computing with resistive switching devices” Nat. Electron. 1, 333- 343, 2018, DOI: 10.1038/s41928-018-0092-2

[4]     A. Ascoli, R. Tetzlaff, Sung-Mo “Steve” Kang, and L.O. Chua, “Theoretical Foundations of Memristor Cellular Nonlinear Networks: a DRM2-based Method to design Memcomputers with Dynamic Memristors”, IEEE Trans. Circuits and Systems-I (TCAS-I): Regular Papers, 2020, DOI: 10.1109/TCSI.2020.2978460

[5]     D. Heim, G.L. Barbruni, and S. Carrara, “A Novel Approach in Edge Computing: In-Memory Sensing of Cancer Markers,” ISCAS, 2022 , DOI: 10.1109/ISCAS48785.2022.9937907

[6]     I. Tzouvadaki, S. Stathopoulos, T. Abbey, L. Michalas, and T. Prodromakis, “Monitoring PSA levels as chemical state-variables in metal-oxide memristors” Sci. Rep., 10, 15281, 2020, DOI: 10.1038/s41598-020- 71962-3

[7]     M.D. Pickett, and R.S. Williams, “Phase transitions enable computational universality in neuristor-based cellular automata” Nanotechnology 24, 384002, 2013, DOI: 10.1088/0957-4484/24/38/384002

[8]     W. Yi, K.K. Tsang, S. K. Lam, X. Bai, J.A. Crowell, and E.A. Flores, “Biological plausibility and stochasticity in scalable VO2 active memristor neurons,” Nat. Commun. 9, 1-10, 2018, DOI: 10.1038/s41467-018-07052-w

[9]     A. Ascoli, A.S. Demirkol, L.O. Chua, and R. Tetzlaff, “Edge of Chaos Theory Resolves Smale Paradox,” IEEE Trans. Circuits and Systems-I (TCAS-I): Regular Papers, vol. 69, no. 3, pp. 1252- 1265, 2022, DOI: 10.1109/TCSI.2021.3133627

[10]   L. O. Chua, C. A. Desoer, and E. A. Kuh, “Linear and Nonlinear Circuits,” New York, NY, USA: McGrawHill, 1987

[11]   L. O. Chua, “Introduction to Nonlinear Network Theory,” New York, NY, USA: McGraw-Hill, 1969 [12] F. Corinto, M. Forti, and L. O. Chua, “Nonlinear Circuits and Systems With Memristors—Analogue Computing Via the Flux-Charge Analysis Method,” Cham, Switzerland: Springer, 2020.

[13]   L. Chua, “Resistance switching memories are memristors,” Appl. Phys. A, Solids Surf., vol. 102, no. 4, pp. 765-783, 2011

[14]   L. Chua, “Everything you wish to know about memristors but are afraid to ask,” Radioengineering, vol. 24, no. 2, pp. 319-368, Jun. 2015