Uppsats

Research on funnel-shaped Memristors with Different Tilt Angles Based on Liquid/Liquid Interface

Master-uppsats

KTH/Skolan för elektroteknik och datavetenskap (EECS)

Publicerad: 2025

Språk: Engelska

Sammanfattning

The continuous advancement of artificial intelligence and big data in the current era has driven increasing demands for computing power. However, traditional von Neumann architectures are constrained by processing limitations, making further enhancements in computing power prohibitively expensive. Memristors, as devices that integrate storage and computing capabilities, have emerged as a promising research field. Nanofluidic memristors, in particular, have garnered significant attention due to their ease of fabrication and biocompatibility. This project developed a funnel- shaped nanofluidic memristor with an asymmetric structure. Using an ionic liquid (BMIMTFSI) and an electrolyte solution (KCl), the device achieved a memristive effect based on asymmetric ion transfer. Distinct hysteresis curves were obtained across seven sweep rates, ranging from 50 mV/s to 200 mV/s. Furthermore, to account for variations in the taper angle within the asymmetric structure, 18 devices with taper angles ranging from 0° to 90° were fabricated and tested at various angles. Distinct patterns in the hysteresis loop opening area were observed. The relationships among the hysteresis loop opening area, sweep rate, and taper angle were qualitatively analyzed. In addition, to explore the neuromorphic computing capabilities of memristors, pulse tests were conducted on the fabricated devices. By applying a specific number of read and write pulses, the short-term plasticity (STP) and short-term depression (STD) functions were measured. Finally, the basic functionalities of the devices, such as handwritten digit recognition, tic-tac- toe game and a simplified super mario game were evaluated through online simulations.

Information

Författare
Liu, Yu
Lärosäte / institution
KTH/Skolan för elektroteknik och datavetenskap (EECS)
Publiceringsdatum
2025
Uppsatstyp
Master-uppsats
Språk
Engelska