The advanced neuro-computing field requires new memristor devices with great potential as synaptic emulators between pre- and postsynaptic neurons. This paper presents memristor devices with TiO Nanoparticles (NPs)/Ag(Silver) and Titanium Dioxide (TiO) Nanoparticles (NPs)/Au(Gold) electrodes for synaptic emulators in an advanced neurocomputing application. A comparative study between Ag(Silver)- and Au(Gold)-based memristor devices is presented where the Ag electrode provides the improved performance, as compared to the Au electrode. Device characterization is observed by the Scanning Electron Microscope (SEM) image, which displays the grown electrode, while the morphology of nanoparticles (NPs) is verified by Atomic Force Microscopy (AFM). The resistive switching (RS) phenomena observed in Ag/TiO and Au/TiO shows the sweeping mechanism for low resistance and high resistance states. The resistive switching time of Au/TiO NPs and Ag/TiO NPs is calculated, while the theoretical validation of the memory window demonstrates memristor behavior as a synaptic emulator. Measurement of the capacitor-voltage curve shows that the memristor with Ag contact is a good candidate for charge storage as compared to Au. The classification of 3 × 3 pixel black/white image is demonstrated by the 3 × 3 cross bar memristor with pre- and post-neuron system. The proposed memristor devices with the Ag electrode demonstrate the adequate performance compared to the Au electrode, and may present noteworthy advantages in the field of neuromorphic computing.
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http://dx.doi.org/10.3390/mi11010089 | DOI Listing |
Sci Rep
December 2024
Department of Electronics and Telecommunications, Politecnico di Torino, 10123, Torino, Italy.
Chronic wounds are a syndrome that affects around 4% of the world population due to several pathologies. The COV-19 pandemic has enforced the need of developing new techniques and technologies that can help clinicians to monitor the affected patients easily and reliably. In this prospective observational study a new device, the Wound Viewer, that works through a memristor-based Discrete-Time Cellular Neural Network (DT-CNN) has been developed and tested through a clinical trial of 150 patients.
View Article and Find Full Text PDFAdv Mater
December 2024
Catalonia Institute for Energy Research (IREC), Jardins de les Dones de Negre 1, 2, Sant Adriá de Besós, Barcelona, 08930, Spain.
Neuromorphic hardware facilitates rapid and energy-efficient training and operation of neural network models for artificial intelligence. However, existing analog in-memory computing devices, like memristors, continue to face significant challenges that impede their commercialization. These challenges include high variability due to their stochastic nature.
View Article and Find Full Text PDFSmall Methods
December 2024
State Key Laboratory of Powder Metallurgy, Central South University, Changsha, 410083, China.
Memristors and magnetic tunnel junctions are showing great potential in data storage and computing applications. A magnetoelectrically coupled memristor utilizing electron spin and electric field-induced ion migration can facilitate their operation, uncover new phenomena, and expand applications. In this study, devices consisting of Pt/(LaCoO/SrTiO)/LaCoO/Nb:SrTiO (Pt/(LCO/STO)/LCO/NSTO) are engineered using pulsed laser deposition to form the LCO/STO superlattice layer, with Pt and NSTO serving as the top and bottom electrodes, respectively.
View Article and Find Full Text PDFNanotechnology
December 2024
Instituto de Nanociencia y Nanotecnología (CONICET-CNEA), Gral. Paz 1499 - San Martín - Argentina, BUENOS AIRES, 1650, ARGENTINA.
Our study demonstrates that strong cationic segregation can occur in amorphous complex oxide memristors during electrical operation. With the help of analytic techniques, we observed that switching the electrical stimulation from voltage to current significantly prevents structural changes and cation segregation at the nanoscale, improving also the device cycle-to-cycle variability. These findings could contribute to the design of more reliable oxide-based memristors and underscore the crucial effect that has the type of electrical stimulation applied to the devices on their integrity and reliability.
View Article and Find Full Text PDFACS Appl Mater Interfaces
December 2024
School of Materials Science and Engineering, UNSW Sydney, NSW 2052, Australia.
Domain walls are quasi-one-dimensional topological defects in ferroic materials, which can harbor emergent functionalities. In the case of ferroelectric domain wall (FEDW) devices, an exciting frontier has emerged: memristor-based information storage and processing approaches. Memristor solid-state FEDW devices presented thus far, however predominantly utilize a complex network of domain walls to achieve the desired regulation of density and charge state.
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