Lim, Hyungkwang Kim, Inho Kim, Jin-Sang Hwang, Cheol Seong Jeong, Doo Seok 2024-01-20T11:32:27Z 2024-01-20T11:32:27Z 2021-09-05 2013-09-27 0957-4484 https://pubs.kist.re.kr/handle/201004/127654 Chemical synapses are important components of the large-scaled neural network in the hippocampus of the mammalian brain, and a change in their weight is thought to be in charge of learning and memory. Thus, the realization of artificial chemical synapses is of crucial importance in achieving artificial neural networks emulating the brain's functionalities to some extent. This kind of research is often referred to as neuromorphic engineering. In this study, we report short-term memory behaviours of electrochemical capacitors (ECs) utilizing TiO2 mixed ionic-electronic conductor and various reactive electrode materials e. g. Ti, Ni, and Cr. By experiments, it turned out that the potentiation behaviours did not represent unlimited growth of synaptic weight. Instead, the behaviours exhibited limited synaptic weight growth that can be understood by means of an empirical equation similar to the Bienenstock-Cooper-Munro rule, employing a sliding threshold. The observed potentiation behaviours were analysed using the empirical equation and the differences between the different ECs were parameterized. English IOP PUBLISHING LTD NONSTOICHIOMETRIC TITANIUM-DIOXIDE NEURAL NETWORKS MEMRISTOR SYNAPSE POTENTIATION SATURATION TRANSISTOR MECHANISM TIO2-X DEVICE Short-term memory of TiO2-based electrochemical capacitors: empirical analysis with adoption of a sliding threshold Article 10.1088/0957-4484/24/38/384005 1 NANOTECHNOLOGY, v.24, no.38 NANOTECHNOLOGY 24 38 scie scopus 000324141800008 2-s2.0-84883632633 Nanoscience & Nanotechnology Materials Science, Multidisciplinary Physics, Applied Science & Technology - Other Topics Materials Science Physics Article NONSTOICHIOMETRIC TITANIUM-DIOXIDE NEURAL NETWORKS MEMRISTOR SYNAPSE POTENTIATION SATURATION TRANSISTOR MECHANISM TIO2-X DEVICE artificial synapse