Mediating Short-Term Plasticity in an Artificial Memristive Synapse by the Orientation of Silica Mesopores
© 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
| Veröffentlicht in: | Advanced materials (Deerfield Beach, Fla.). - 1998. - 30(2018), 16 vom: 18. Apr., Seite e1706395 |
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| 1. Verfasser: | |
| Weitere Verfasser: | , , , , , , , , , |
| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2018
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| Zugriff auf das übergeordnete Werk: | Advanced materials (Deerfield Beach, Fla.) |
| Schlagworte: | Journal Article artificial memristive synapses mesopores orientation short-term plasticity silica |
| Zusammenfassung: | © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. Memristive synapses based on resistive switching are promising electronic devices that emulate the synaptic plasticity in neural systems. Short-term plasticity (STP), reflecting a temporal strengthening of the synaptic connection, allows artificial synapses to perform critical computational functions, such as fast response and information filtering. To mediate this fundamental property in memristive electronic devices, the regulation of the dynamic resistive change is necessary for an artificial synapse. Here, it is demonstrated that the orientation of mesopores in the dielectric silica layer can be used to modulate the STP of an artificial memristive synapse. The dielectric silica layer with vertical mesopores can facilitate the formation of a conductive pathway, which underlies a lower set voltage (≈1.0 V) compared to these with parallel mesopores (≈1.2 V) and dense amorphous silica (≈2.0 V). Also, the artificial memristive synapses with vertical mesopores exhibit the fastest current increase by successive voltage pulses. Finally, oriented silica mesopores are designed for varying the relaxation time of memory, and thus the successful mediation of STP is achieved. The implementation of mesoporous orientation provides a new perspective for engineering artificial synapses with multilevel learning and forgetting capability, which is essential for neuromorphic computing |
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| Beschreibung: | Date Completed 01.08.2018 Date Revised 01.10.2020 published: Print-Electronic Citation Status PubMed-not-MEDLINE |
| ISSN: | 1521-4095 |
| DOI: | 10.1002/adma.201706395 |