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A photoelectrical artificial synapse for novel neuromorphic network
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH).ORCID iD: 0000-0002-1768-1071
Fudan University, SIST, State Key Laboratory of ASIC and System.
Fudan University, SIST, State Key Laboratory of ASIC and System.
Fudan University, SIST, State Key Laboratory of ASIC and System.
Show others and affiliations
2018 (English)In: 2018 IEEE 18th International Conference on Nanotechnology (IEEE-NANO), Institute of Electrical and Electronics Engineers (IEEE), 2018, article id 8626411Conference paper, Published paper (Refereed)
Abstract [en]

The requirement of information acquisition and processing is growing rapidly. However, existing systems either suffering from inadequate processing ability or from architecture limitations being restricted by the data sensing and transmission process. In this work, a novel photoelectrical artificial synapse is developed to settle down these issues by proposing a new possibility of having a photoelectrical neuromorphic network. The photoelectrical artificial synapse has both light sensing and non-volatile multilevel states making it a suitable candidate as building block in a sensing-processing merged and photoelectrical- enabled neuromorphic system. The device also has physical flexibility to adapt to flexible and wearable systems. This work initiates a new area of novel artificial synapses and neuromorphic networks.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018. article id 8626411
Series
IEEE International Conference on Nanotechnology, ISSN 1944-9399
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-235726DOI: 10.1109/NANO.2018.8626411ISI: 000458785600189Scopus ID: 2-s2.0-85062273885ISBN: 9781538653364 (print)OAI: oai:DiVA.org:kth-235726DiVA, id: diva2:1253014
Conference
2018 IEEE 18th International Conference on Nanotechnology (IEEE-NANO), Cork, Ireland,July 23-36, 2018
Note

QC 20181008

Available from: 2018-10-03 Created: 2018-10-03 Last updated: 2019-03-13Bibliographically approved
In thesis
1. Flexible Electrical and Photoelectrical Artificial Synapses for Neuromorphic Systems
Open this publication in new window or tab >>Flexible Electrical and Photoelectrical Artificial Synapses for Neuromorphic Systems
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Over the past decade, the field of personal electronic systems has trended toward mobile and wearable devices. However, the capabilities of existing electronic systems are overwhelmed by the computing demands at the wearable sensing stage. Two main bottlenecks are encountered. The first bottleneck is located within the computing module, between the processing units and the memory, and is known as the von-Neumann bottleneck. The second bottleneck is located between the sensing module and the computing module of the system.

Inspired by neuromorphic computing, an architecture of the sensitive neuromorphic network (SNN) is developed as a candidate for overcoming both bottlenecks. Suitable building blocks, especially in flexible form, must be developed. In this work, starting from the demand analysis and followed by prototype development, performance optimization, and feasibility testing, two kinds of critical devices were developed for fabricating a photosensitive neuromorphic network (PSNN).

A high-performance flexible electrical artificial synapse that is based on the electron-trapping mechanism was developed. In addition to the basic memristive features, multiple kinds of synaptic plasticity were also demonstrated, which enriched the collection of possible applications. Furthermore, optimization on multiple performance metrics was easily performed using the intrinsic features and structure of the device.

A new photoelectrical artificial synapse was also realized by successfully combining light signal sensing and processing in a single synapse. A flexible dual-mode photoelectrical synapse, which fulfilled the requirements of the designed PSNN working protocol, was demonstrated. The device showed gate-tunable photomemristive features, thereby enabling its application as a photoelectrical artificial synapse.

Using the newly developed devices and the proposed network architecture, this work successfully initiated a new area of research, namely, the sensitive neuromorphic network, and provided a valid solution that addresses the current limitations of existing wearable electronic systems.

Place, publisher, year, edition, pages
KTH Royal Institute of Technology, 2018. p. 58
Series
TRITA-CBH-FOU ; 2018:46
Keywords
Flexible electronics, Neuromorphic network, Memristor, Electron trapping, Electrical artificial synapse, Photoelectrical artificial synapse
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Applied Medical Technology
Identifiers
urn:nbn:se:kth:diva-235742 (URN)978-91-7729-979-0 (ISBN)
Public defence
2018-10-31, T2, Hälsovägen 11C, Huddinge, 09:00 (English)
Opponent
Supervisors
Note

QC 20181008

Available from: 2018-10-08 Created: 2018-10-08 Last updated: 2018-10-08Bibliographically approved

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Publisher's full textScopushttp://ieeenano18.org/

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Yang, KunlongSeoane, Fernando

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