Przyczyna Dawid, Mech Krzysztof, Kowalewska Ewelina, Marzec Mateusz, Mazur Tomasz, Zawal Piotr, Szaciłowski Konrad
Academic Centre for Materials and Nanotechnology, AGH University of Science and Technology, Mickiewicza 30, 30-059 Krakow, Poland.
Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, Mickiewicza 30, 30-059 Krakow, Poland.
Materials (Basel). 2023 Oct 13;16(20):6675. doi: 10.3390/ma16206675.
Memristors possess non-volatile memory, adjusting their electrical resistance to the current that flows through them and allowing switching between high and low conducting states. This technology could find applications in fields such as IT, consumer electronics, computing, sensors, and medicine. In this paper, we report successful electrodeposition of thin-film materials consisting of copper tungstate and copper molybdate (CuWO and CuMoO), which showed notable memristive properties. Material characterisation was performed with techniques such as XRD, XPS, and SEM. The electrodeposited materials exhibited the ability to switch between low and high resistive states during varied cyclic scans and short-term impulses. The retention time of these switched states was also explored. Using these materials, the effects seen in biological systems, specifically spike timing-dependent plasticity, were simulated, being based on analogue operation of the memristors to achieve multiple conductivity states. Bio-inspired simulations performed directly on the material could possibly offer energy and time savings for classical computations. Memristors could be crucial for the advancement of high-efficiency, low-energy neuromorphic electronic devices and technologies in the future.
忆阻器具有非易失性存储器，可根据流经它们的电流调整其电阻，并允许在高导电状态和低导电状态之间切换。这项技术可应用于信息技术、消费电子、计算、传感器和医学等领域。在本文中，我们报告了由钨酸铜和钼酸铜（CuWO 和 CuMoO）组成的薄膜材料的成功电沉积，这些材料表现出显著的忆阻特性。使用 XRD、XPS 和 SEM 等技术进行了材料表征。电沉积材料在不同的循环扫描和短期脉冲期间表现出在低电阻状态和高电阻状态之间切换的能力。还探索了这些切换状态的保持时间。利用这些材料，基于忆阻器的模拟操作以实现多种导电状态，模拟了在生物系统中观察到的效应，特别是峰电位时间依赖可塑性。直接在材料上进行的仿生模拟可能为经典计算节省能量和时间。忆阻器对于未来高效、低能耗的神经形态电子设备和技术的发展可能至关重要。
