Insights into synaptic functionality and resistive switching in lead iodide flexible memristor devices-Reference-Cited by-同舟云学术

Insights into synaptic functionality and resistive switching in lead iodide flexible memristor devices

Published:2024 Issue:3 Volume:9 Page:438-448
ISSN:2055-6756
Container-title:Nanoscale Horizons
language:en
Short-container-title:Nanoscale Horiz.

Author:

Jain Muskan¹²,Patel Mayur Jagdishbhai³,Liu Lingli⁴^ORCID,Gosai Jeny²⁵,Khemnani Manish¹²,Gogoi Himangshu Jyoti⁶,Chee Mun Yin⁴,Guerrero Antonio⁷^ORCID,Lew Wen Siang⁴,Solanki Ankur¹²^ORCID

Affiliation:

1. Department of Physics, School of Energy Technology, Pandit Deendayal Energy University, Raysan, Gandhinagar 382426, India

2. Flextronics Lab, Pandit Deendayal Energy University, Gandhinagar, Gujarat 382426, India

3. Department of Chemistry, Indian Institute of Technology Guwahati, Guwahati 781039, Assam, India

4. School of Physical and Mathematical Sciences, Nanyang Technological University, 637371, Singapore

5. Department of Chemistry, School of Energy Technology, Pandit Deendayal Energy University, Raysan, Gandhinagar 382426, India

6. Department of Electrical Engineering, Indian Institute of Technology Guwahati, 781039 Assam, India

7. Institute of Advanced Materials (INAM), Universitat Jaume I, 12006 Castello, Spain

Abstract

Neuromorphic platforms are gaining popularity due to their superior efficiency, low power consumption, and adaptable parallel signal processing capabilities, overcoming the limitations of traditional von Neumann architecture.

Funder

Gujarat Council on Science and Technology

Ministerio de Ciencia e Innovación

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/NH/D3NH00505D

Reference77 articles.

1. Deep learning-based noise robust flexible piezoelectric acoustic sensors for speech processing

2. Opportunities for neuromorphic computing algorithms and applications

3. A Survey of Neuromorphic Computing-in-Memory: Architectures, Simulators and Security

4. Highly transparent reconfigurable non-volatile multilevel optoelectronic memory for integrated self-powered brain-inspired perception

5. All-in-one metal-oxide heterojunction artificial synapses for visual sensory and neuromorphic computing systems

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