Dec 3, 2024
3:45pm - 4:00pm
Sheraton, Second Floor, Republic A
Chhotrai Soren1,Rajesh Jha1,Ankur Goswami1
Indian Institute of Technology Delhi1
Electronic computing is undergoing a paradigm shift with the advent of neuromorphic architecture from the archetype von Neuman architecture. In neuromorphic architecture [1], data processing occurs within the storage memory, eradicating the data latency period. The overall data processing speed reduces acutely, further decreasing energy costs. A memristor is a highly scalable fundamental circuit component that switches across multiple stable states [2] at a very low energy cost, deeming it suitable for neuromorphic application. Transition metal oxides (TMOs) are suitable materials for the fabrication of these memristive components [3] showcasing resistive switching due to physiochemical mechanisms based on ion migration, electrolyte gated, phase change, ferroelectric, spintronic, photonic migration, electronic migration, and metal-insulator transition. Owing to the abundance of materials showing MIT for vested interest of neuromorphic application VO
2 shows MIT at near room temperature [4]. VO
2 undergoes a transition from the low-temperature monoclinic (M1) phase to the tetragonal (R) phase at a temperature above 68
○C, along with the occurrence of several unstable phases during the transition. The transition temperature of VO
2 can also be tuned to a higher or lower value under the effect of tensile or compressive strain in the lattice under the influence of an electric field, magnetic field, and the illumination of a specific wavelength of light [5]. VO
2/TiO
2 memristor fabricated using pulsed laser deposition, when illuminated with a laser source of 405 nm, 532 nm, 633 nm, and 980 nm, shows changes in memristive properties like R
OFF/R
ON ratio and switching power. In order to concretize the functioning of the memristor as an artificial synapse, spiking time-dependent plasticity (STDP) analysis [6] is performed under different illumination conditions to boot.
References[1] C. Mead,
Proc. IEEE 78, 1629–1636 (1990).
[2] L. Chua,
IEEE Trans. Circuit Theory 18, 507–519 (1971).
[3] A. Rana, C. Li, G. Koster, and H. Hilgenkamp,
Sci. Rep. 10, 2–7 (2020).
[4] U. Chitnis, S. Kumar, S. A. Bukhari, C. Soren, R. K. Ghosh and A. Goswami,
Appl. Surf. Sci. 637, 157916 (2023).
[5] G. Li, D. Xie, H. Zhong,
Nat. Commun. 13, 1729 (2022).
[6] R. Naik B., D. Verma and V. Balakrishnan,
Appl. Phys. Lett. 120 (6) (2022).