Neuromorphic Devices: Materials, Structures and Bionic Applications.
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| Title: | Neuromorphic Devices: Materials, Structures and Bionic Applications. |
|---|---|
| Authors: | Zhu, Liqiang1 (AUTHOR) zhuliqiang@nbu.edu.cn, Wan, Qing2 (AUTHOR) qing-wan@ylab.ac.cn |
| Source: | Nanomaterials (2079-4991). Sep2025, Vol. 15 Issue 17, p1299. 3p. |
| Subjects: | Neuromorphics, Artificial intelligence, Computer architecture, Organic field-effect transistors, Memristors |
| Abstract: | The article focuses on the advancements in neuromorphic devices and systems as a response to the challenges posed by traditional computing architectures in processing large data sets efficiently. It highlights the significance of brain-inspired neuromorphic engineering in enhancing artificial intelligence capabilities through innovative materials and device designs. The Special Issue includes twelve articles that cover various topics, such as neuromorphic computing hardware, flexible organic transistors, and memristive structures, all aimed at improving energy efficiency and cognitive functions in computing. This compilation serves as a valuable resource for ongoing research and development in neuromorphic electronics, appealing to a broad audience interested in the field. [Extracted from the article] |
| Copyright of Nanomaterials (2079-4991) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 187983403 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Neuromorphic Devices: Materials, Structures and Bionic Applications. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Zhu%2C+Liqiang%22">Zhu, Liqiang</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> zhuliqiang@nbu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Wan%2C+Qing%22">Wan, Qing</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> qing-wan@ylab.ac.cn</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Nanomaterials+%282079-4991%29%22">Nanomaterials (2079-4991)</searchLink>. Sep2025, Vol. 15 Issue 17, p1299. 3p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Neuromorphics%22">Neuromorphics</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+architecture%22">Computer architecture</searchLink><br /><searchLink fieldCode="DE" term="%22Organic+field-effect+transistors%22">Organic field-effect transistors</searchLink><br /><searchLink fieldCode="DE" term="%22Memristors%22">Memristors</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The article focuses on the advancements in neuromorphic devices and systems as a response to the challenges posed by traditional computing architectures in processing large data sets efficiently. It highlights the significance of brain-inspired neuromorphic engineering in enhancing artificial intelligence capabilities through innovative materials and device designs. The Special Issue includes twelve articles that cover various topics, such as neuromorphic computing hardware, flexible organic transistors, and memristive structures, all aimed at improving energy efficiency and cognitive functions in computing. This compilation serves as a valuable resource for ongoing research and development in neuromorphic electronics, appealing to a broad audience interested in the field. [Extracted from the article] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Nanomaterials (2079-4991) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=187983403 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/nano15171299 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 3 StartPage: 1299 Subjects: – SubjectFull: Neuromorphics Type: general – SubjectFull: Artificial intelligence Type: general – SubjectFull: Computer architecture Type: general – SubjectFull: Organic field-effect transistors Type: general – SubjectFull: Memristors Type: general Titles: – TitleFull: Neuromorphic Devices: Materials, Structures and Bionic Applications. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Zhu, Liqiang – PersonEntity: Name: NameFull: Wan, Qing IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 09 Text: Sep2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 20794991 Numbering: – Type: volume Value: 15 – Type: issue Value: 17 Titles: – TitleFull: Nanomaterials (2079-4991) Type: main |
| ResultId | 1 |
