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Enhanced electrical and magnetic properties of (Co, Yb) co-doped ZnO memristor for neuromorphic computing

Noureddine ElboughdiriChemical Engineering Department, College of Engineering, University of Ha'il, P.O. Box 2440, Ha'il 81441, Saudi ArabiaShahid IqbalDepartment of Physics, University of Wisconsin, La Crosse, WI, USASherzod AbdullaevEngineering School, Central Asian University, Tashkent, UzbekistanMohammed AljohaniDepartment of Chemistry, College of Science, Taif University, P.O. BOX. 110, 21944 Taif, Saudi ArabiaAkif SafeenDepartment of Physics, University of Poonch Rawalakot, Rawalakot 12350, PakistanKhaled AlthubeitiDepartment of Chemistry, College of Science, Taif University, P.O. BOX. 110, 21944 Taif, Saudi ArabiaSattam Al OtaibiDepartment of Physics, United Arab Emirates University, United Arab Emirates
RSC Advancesjournal2023en
ABI

Аннотация

We investigate the morphological, electrical, magnetic, and resistive switching properties of (Co, Yb) co-ZnO for neuromorphic computing. By using hydrothermal synthesized nanoparticles and their corresponding sputtering target, we introduce Co and Yb into the ZnO structure, leading to increased oxygen vacancies and grain volume, indicating grain growth. This growth reduces grain boundaries, enhancing electrical conductivity and room-temperature ferromagnetism in Co and Yb-doped ZnO nanoparticles. We present a sputter-grown memristor with a (Co, Yb) co-ZnO layer between Au electrodes. Characterization confirms the ZnO layer's presence and 100 nm-thick Au electrodes. The memristor exhibits repeatable analog resistance switching, allowing manipulation of conductance between low and high resistance states. Statistical endurance tests show stable resistive switching with minimal dispersion over 100 pulse cycles at room temperature. Retention properties of the current states are maintained for up to 1000 seconds, demonstrating excellent thermal stability. A physical model explains the switching mechanism, involving Au ion migration during "set" and filament disruption during "reset." Current-voltage curves suggest space-charge limited current, emphasizing conductive filament formation. All these results shows good electronic devices and systems towards neuromorphic computing.

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