@article {Dongale:2018:1533-4880:984,
title = "Mimicking the Synaptic Weights and Human Forgetting Curve Using Hydrothermally Grown Nanostructured CuO Memristor Device",
journal = "Journal of Nanoscience and Nanotechnology",
parent_itemid = "infobike://asp/jnn",
publishercode ="asp",
year = "2018",
volume = "18",
number = "2",
publication date ="2018-02-01T00:00:00",
pages = "984-991",
itemtype = "ARTICLE",
issn = "1533-4880",
eissn = "1533-4899",
url = "https://www.ingentaconnect.com/content/asp/jnn/2018/00000018/00000002/art00032",
doi = "doi:10.1166/jnn.2018.14264",
keyword = "Thin Film, Memristor, Hydrothermal Method, Synapse, Copper Oxide, Neuromorphic Computing",
author = "Dongale, T. D and Pawar, P. S and Tikke, R. S and Mullani, N. B and Patil, V. B and Teli, A. M and Khot, K. V and Mohite, S. V and Bagade, A. A and Kumbhar, V. S and Rajpure, K. Y and Bhosale, P. N and Kamat, R. K and Patil, P. S",
abstract = "In the present investigation, we have fabricated copper oxide (CuO) thin film memristor by employing a hydrothermal method for neuromorphic application. The X-ray diffraction pattern confirms the films are polycrystalline in nature with the monoclinic crystal structure. The developed
devices show analog memory and synaptic property similar to biological neuron. The size dependent synaptic behavior is investigated for as-prepared and annealed CuO memristor. The results suggested that the magnitude of synaptic weights and resistive switching voltages are dependent on the
thickness of the active layer. Synaptic weights are improved in the case of the as-prepared device whereas they are inferior for annealed CuO memristor. The rectifying property similar to a biological neuron is observed only for the as-prepared device, which suggested that as-prepared devices
have better computational and learning capabilities than annealed CuO memristor. Moreover, the retention loss of the CuO memristor is in good agreement with the forgetting curve of human memory. The results suggested that hydrothermally grown CuO thin film memristor is a potential candidate
for the neuromorphic device development.",
}