Szczegóły publikacji
Opis bibliograficzny
Leaky integrate-and-fire model and short-term synaptic plasticity emulated in a novel bismuth-based diffusive memristor / Piotr Zawal, Gisya ABDI, Marlena Gryl, Dip Das, Andrzej SŁAWEK, Emilie A. Gerouville, Marianna MARCISZKO-WIĄCKOWSKA, Mateusz MARZEC, Grzegorz Hess, Dimitra G. Georgiadou, Konrad SZACIŁOWSKI // Advanced Electronic Materials [Dokument elektroniczny]. — Czasopismo elektroniczne ; ISSN 2199-160X. — 2024 — vol. 10 iss. 7 art. no. 2300865, s. 1–14. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 13–14, Abstr. — Publikacja dostępna online od: 2024-05-01
Autorzy (11)
- AGHZawal Piotr
- AGHAbdi Gisya
- Gryl Marlena
- Das Dip
- AGHSławek Andrzej
- Gerouville Emilie A.
- AGHMarciszko-Wiąckowska Marianna
- AGHMarzec Mateusz M.
- Hess Grzegorz
- Georgiadou Dimitra G.
- AGHSzaciłowski Konrad
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 154576 |
|---|---|
| Data dodania do BaDAP | 2024-07-23 |
| Tekst źródłowy | URL |
| DOI | 10.1002/aelm.202300865 |
| Rok publikacji | 2024 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Advanced Electronic Materials |
Abstract
Memristors, being prospective work-horses of future electronics offer various types of memory (volatile and nonvolatile) along with specific computational functionalities. Further development of memristive technologies depends on the availability of suitable materials. These materials should be easily available, stable, and preferably of low toxicity. Commonly used materials are lead halide perovskites, however, they are highly toxic and unstable under ambient conditions. Therefore a novel material is developed on the basis of bismuth iodide. In reaction with butylammonium iodide, it yields a novel compound, butylammonium iodobismuthate (BABI). Here, a diffusive memristor is introduced based on this compound and evaluates its memristive and neuromorphic properties. In contrast to nonvolatile memristors, the BABI memristors exhibit diffusive dynamics, which enable them to store the information only for short periods of time. This property is utilized to mimic the short-term synaptic plasticity described by the leaky integrate-and-fire model of a biological neuron. Combined with high switching uniformity and self-rectifying behavior, these devices show high classification accuracy for MNIST handwritten datasets, paving the way for their application in neuromorphic computing systems.
