Microwave-Assisted Fe3O4-Based Memristor for Brain-Inspired Computing

Vivek Pratap Singh; Chandra Prakash Singh; Harsh Ranjan; Saurabh Kumar Pandey

doi:10.1007/978-981-97-5269-0_15

Microwave-Assisted Fe₃O₄-Based Memristor for Brain-Inspired Computing

Vivek Pratap Singh
, Chandra Prakash Singh
, Harsh Ranjan
, Saurabh Kumar Pandey

Department of Advanced Battery Convergence Engineering

Indian Institute of Technology Patna

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

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.

Original language	English
Title of host publication	Emerging VLSI Devices, Circuits and Architectures - Proceedings of the 27th International Symposium, VDAT 2023
Editors	Anu Gupta, Nitin Chaturvedi, Jai Gopal Pandey, Devesh Dwivedi
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	175-183
Number of pages	9
ISBN (Print)	9789819752683
DOIs	https://doi.org/10.1007/978-981-97-5269-0_15
State	Published - 2025
Event	27th International Symposium on VLSI Design and Test, VDAT 2023 - Pilani, India Duration: 29 Sep 2023 → 1 Oct 2023

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	1234 LNEE
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	27th International Symposium on VLSI Design and Test, VDAT 2023
Country/Territory	India
City	Pilani
Period	29/09/23 → 1/10/23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Analog Resistive switching (ARS)
Memristor
Neuromorphic computing

Access to Document

10.1007/978-981-97-5269-0_15

Cite this

Singh, V. P., Singh, C. P., Ranjan, H., & Pandey, S. K. (2025). Microwave-Assisted Fe₃O₄-Based Memristor for Brain-Inspired Computing. In A. Gupta, N. Chaturvedi, J. G. Pandey, & D. Dwivedi (Eds.), Emerging VLSI Devices, Circuits and Architectures - Proceedings of the 27th International Symposium, VDAT 2023 (pp. 175-183). (Lecture Notes in Electrical Engineering; Vol. 1234 LNEE). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-97-5269-0_15

Singh, Vivek Pratap ; Singh, Chandra Prakash ; Ranjan, Harsh et al. / Microwave-Assisted Fe₃O₄-Based Memristor for Brain-Inspired Computing. Emerging VLSI Devices, Circuits and Architectures - Proceedings of the 27th International Symposium, VDAT 2023. editor / Anu Gupta ; Nitin Chaturvedi ; Jai Gopal Pandey ; Devesh Dwivedi. Springer Science and Business Media Deutschland GmbH, 2025. pp. 175-183 (Lecture Notes in Electrical Engineering).

@inproceedings{b2883d5a67654bfd899af2b754f264d1,

title = "Microwave-Assisted Fe3O4-Based Memristor for Brain-Inspired Computing",

abstract = "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.",

keywords = "Analog Resistive switching (ARS), Memristor, Neuromorphic computing",

author = "Singh, \{Vivek Pratap\} and Singh, \{Chandra Prakash\} and Harsh Ranjan and Pandey, \{Saurabh Kumar\}",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.; 27th International Symposium on VLSI Design and Test, VDAT 2023 ; Conference date: 29-09-2023 Through 01-10-2023",

year = "2025",

doi = "10.1007/978-981-97-5269-0\_15",

language = "English",

isbn = "9789819752683",

series = "Lecture Notes in Electrical Engineering",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "175--183",

editor = "Anu Gupta and Nitin Chaturvedi and Pandey, \{Jai Gopal\} and Devesh Dwivedi",

booktitle = "Emerging VLSI Devices, Circuits and Architectures - Proceedings of the 27th International Symposium, VDAT 2023",

address = "Germany",

}

Singh, VP, Singh, CP, Ranjan, H & Pandey, SK 2025, Microwave-Assisted Fe₃O₄-Based Memristor for Brain-Inspired Computing. in A Gupta, N Chaturvedi, JG Pandey & D Dwivedi (eds), Emerging VLSI Devices, Circuits and Architectures - Proceedings of the 27th International Symposium, VDAT 2023. Lecture Notes in Electrical Engineering, vol. 1234 LNEE, Springer Science and Business Media Deutschland GmbH, pp. 175-183, 27th International Symposium on VLSI Design and Test, VDAT 2023, Pilani, India, 29/09/23. https://doi.org/10.1007/978-981-97-5269-0_15

Microwave-Assisted Fe₃O₄-Based Memristor for Brain-Inspired Computing. / Singh, Vivek Pratap; Singh, Chandra Prakash; Ranjan, Harsh et al.
Emerging VLSI Devices, Circuits and Architectures - Proceedings of the 27th International Symposium, VDAT 2023. ed. / Anu Gupta; Nitin Chaturvedi; Jai Gopal Pandey; Devesh Dwivedi. Springer Science and Business Media Deutschland GmbH, 2025. p. 175-183 (Lecture Notes in Electrical Engineering; Vol. 1234 LNEE).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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 - https://www.scopus.com/pages/publications/85207818891

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 -

Singh VP, Singh CP, Ranjan H, Pandey SK. Microwave-Assisted Fe₃O₄-Based Memristor for Brain-Inspired Computing. In Gupta A, Chaturvedi N, Pandey JG, Dwivedi D, editors, Emerging VLSI Devices, Circuits and Architectures - Proceedings of the 27th International Symposium, VDAT 2023. Springer Science and Business Media Deutschland GmbH. 2025. p. 175-183. (Lecture Notes in Electrical Engineering). doi: 10.1007/978-981-97-5269-0_15