Harnessing a WO x -based flexible transparent memristor synapse with a hafnium oxide layer for neuromorphic computing.
Debashis PandaYu-Fong HuiTseung-Yuen TsengPublished in: Nanoscale (2024)
Transparent memristor-based neuromorphic synapses are expected to be specialised devices for high-speed information transmission and processing. The synaptic linearity and potentiation/depression cycles are imperative issues for the application of memristors. This work explores a memristor for improving switching uniformity by introducing a thin HfO x interfacial layer as a diffusion-limiting layer sandwiched between WO x and ITO bottom electrodes. An optimized HfO x thickness not only provides the best switching properties but also shows superior synaptic properties. The optimized 15 nm thin WO x layer can retain the memristor's excellence in P / D linearity, a cycling stability of 494 epochs and image recognition up to 3 mm bending, making it suitable for flexible devices. The artificial synapse is capable of reversible short-term and long-term learning behaviors confirmed by spike-timing-dependent-plasticity (STDP) results. X-ray photoelectron spectroscopy confirms the device composition and provides the oxygen vacancy concentration at the WO x /HfO x interface to realize the switching mechanism. The thicknesses of the different layers are estimated from the high-resolution transmission electron microscopy observations. The fabricated device exhibits 92.2% transparency, as confirmed by the UV-Vis spectrum.
Keyphrases
- high resolution
- high speed
- electron microscopy
- atomic force microscopy
- solid state
- visible light
- mass spectrometry
- depressive symptoms
- photodynamic therapy
- high intensity
- molecular dynamics simulations
- magnetic resonance imaging
- gold nanoparticles
- social media
- optical coherence tomography
- machine learning
- magnetic resonance
- health information
- tandem mass spectrometry
- electron transfer