The taking run on artificial intelligence in the last decades is based on the von Neumann architecture where memory and computation units are separately located from each other. This configuration causes a large amount of energy and time to be dissipated during data transfer between these two units, in contrast to synapses in biological neurons. A new paradigm has been proposed inspired by biological neurons in human brains, known as neuromorphic computing. Due to the unusual current-voltage characteristic of memristor devices such as pinched hysteresis loops, memristors are considered a key element of neuromorphic architecture. In this study, we report the basic current-voltage characteristic of the memristor devices in the form of Si/SiO/Pt(30 nm)/VO (3, 13, 25 nm)/Pt (30 nm) sandwich structure. Synaptic functions such as spike-time-dependent plasticity (STDP), paired-pulse facilitation (PPF), long-term potentiation (LTP), and long-term depression (LTD) of memristor devices were examined in detail. The oxide layer VO has been grown by using the VO target in a pulsed laser deposition (PLD) chamber. The composition and oxidation states of the oxide layer were examined using the X-ray photoelectron spectroscopy (XPS) technique. The status of oxygen vacancies, which play an active role in the operation of the devices, was examined with a photoluminescence (PL) technique. The experimental results showed that the thickness of the oxide layer can significantly influence the synaptic and resistive switching properties of the devices.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11190910 | PMC |
http://dx.doi.org/10.1021/acsomega.4c02001 | DOI Listing |
Adv Mater
January 2025
Institute of Modern Optics & Tianjin Key Laboratory of Micro-Scale Optical Information Science and Technology, Nankai University, Tianjin, 300350, P. R. China.
Memristors enable non-volatile memory and neuromorphic computing. Optical memristors are the fundamental element for programmable photonic integrated circuits due to their high-bandwidth computing, low crosstalk, and minimal power consumption. Here, an optical memristor enabled by a non-volatile electro-optic (EO) effect, where refractive index modulation under zero field is realized by deliberate control of domain alignment in the ferroelectric material Pb(MgNb)O-PbTiO(PMN-PT) is proposed.
View Article and Find Full Text PDFMicromachines (Basel)
December 2024
School of Integrated Circuit, Southeast University, Nanjing 210096, China.
Aluminum nitride (AlN) with a wide band gap (approximately 6.2 eV) has attractive characteristics, including high thermal conductivity, a high dielectric constant, and good insulating properties, which are suitable for the field of resistive random access memory. AlN thin films were deposited on ITO substrate using the radio-frequency magnetron sputtering technique.
View Article and Find Full Text PDFMicromachines (Basel)
November 2024
Department of Semiconductor Systems Engineering, Convergence Engineering for Intelligent Drone, Institute of Semiconductor and System IC, Sejong University, 209, Neungdong-ro, Gwangjin-gu, Seoul 05006, Republic of Korea.
We present a SnO gas sensor with an HfO layer that exhibits enhanced performance and reliability for gasistor applications, combining a gas sensor and a memristor. The transparent SnO gasistor with a 30 nm HfO layer demonstrated low forming voltages (7.1 V) and a high response rate of 81.
View Article and Find Full Text PDFACS Omega
December 2024
School of Physics and Astronomy, University of Nottingham, Nottingham NG7 2RD, U.K.
Small
January 2025
School of Advanced Materials Science and Engineering, Sungkyunkwan University, Suwon, 16419, Republic of Korea.
Homeostasis is essential in biological neural networks, optimizing information processing and experience-dependent learning by maintaining the balance of neuronal activity. However, conventional two-terminal memristors have limitations in implementing homeostatic functions due to the absence of global regulation ability. Here, three-terminal oxide memtransistor-based homeostatic synapses are demonstrated to perform highly linear synaptic weight update and enhanced accuracy in neuromorphic computing.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!