TY - GEN
T1 - Microwave-Assisted Fe3O4-Based Memristor for Brain-Inspired Computing
AU - Singh, Vivek Pratap
AU - Singh, Chandra Prakash
AU - Ranjan, Harsh
AU - Pandey, Saurabh Kumar
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2025
Y1 - 2025
N2 - Memristors have gained considerable attention as key components in neuromorphic computing systems due to their ability to emulate synaptic behavior (Potentiation/Depression). Fe3O4, an iron oxide material, exhibits intriguing electrical properties, making it a promising candidate for memristor applications. This study focuses on the microwave-assisted synthesis of Fe3O4-based memristors and explores their potential for integration into neuromorphic systems. The utilization of microwave irradiation during fabrication enhances the control over the material's crystal structure, morphology, and electrical properties, leading to improved memristor performance. The characterization of the synthesized memristors reveals their memristive behavior, including analog resistive switching (ARS), and ultra-low energy consumption. Furthermore, the implementation of memristors in a neuromorphic system demonstrates their capability to emulate synapses, enabling the development of energy-efficient artificial neural activity −0.6 V/+ 0.6 V at read voltage 0.1 V (Potentiation/Depression). This research contributes to the advancement of Fe3O4-based memristors and their integration into state-of-the-art brain-inspired neuromorphic computing architectures.
AB - Memristors have gained considerable attention as key components in neuromorphic computing systems due to their ability to emulate synaptic behavior (Potentiation/Depression). Fe3O4, an iron oxide material, exhibits intriguing electrical properties, making it a promising candidate for memristor applications. This study focuses on the microwave-assisted synthesis of Fe3O4-based memristors and explores their potential for integration into neuromorphic systems. The utilization of microwave irradiation during fabrication enhances the control over the material's crystal structure, morphology, and electrical properties, leading to improved memristor performance. The characterization of the synthesized memristors reveals their memristive behavior, including analog resistive switching (ARS), and ultra-low energy consumption. Furthermore, the implementation of memristors in a neuromorphic system demonstrates their capability to emulate synapses, enabling the development of energy-efficient artificial neural activity −0.6 V/+ 0.6 V at read voltage 0.1 V (Potentiation/Depression). This research contributes to the advancement of Fe3O4-based memristors and their integration into state-of-the-art brain-inspired neuromorphic computing architectures.
KW - Analog Resistive switching (ARS)
KW - Memristor
KW - Neuromorphic computing
UR - http://www.scopus.com/inward/record.url?scp=85207818891&partnerID=8YFLogxK
U2 - 10.1007/978-981-97-5269-0_15
DO - 10.1007/978-981-97-5269-0_15
M3 - Conference contribution
AN - SCOPUS:85207818891
SN - 9789819752683
T3 - Lecture Notes in Electrical Engineering
SP - 175
EP - 183
BT - Emerging VLSI Devices, Circuits and Architectures - Proceedings of the 27th International Symposium, VDAT 2023
A2 - Gupta, Anu
A2 - Chaturvedi, Nitin
A2 - Pandey, Jai Gopal
A2 - Dwivedi, Devesh
PB - Springer Science and Business Media Deutschland GmbH
T2 - 27th International Symposium on VLSI Design and Test, VDAT 2023
Y2 - 29 September 2023 through 1 October 2023
ER -
