RESUMO
We have experimentally demonstrated a strong correlation between the electrical properties of Zn1-xTex Ovonic threshold switching (OTS) selector device and the material properties analysed by X-ray diffraction (XRD), spectroscopic ellipsometry, and X-ray photoelectron spectroscopy (XPS). The correlation and the key material parameters determining the device performances were investigated. By comparing the experimental data with the calculation results from various analytical models previously developed for OTS materials, the electrical properties of the device were shown to be dependent on the key material parameters; the concentration of sub-gap trap states and the bandgap energy of the OTS material. This study also experimentally demonstrated that those key parameters have determined the device performance as expected from the analytical model. The origin of the OTS phenomenon and conduction mechanism were explained both experimentally and theoretically. This leads to better understanding of the conduction mechanism of OTS devices, and an insight for process improvement to optimize device performance for selector application.
RESUMO
A 3D high-density switching device is realized utilizing titanium oxide, which is the most optimum material, but which is not practically demonstrated yet. The 1S1R (one ReRAM with the developed switching device) exhibits memory characteristics with a significantly suppressed sneak current, which can be used to realize high-density ReRAM applications.
RESUMO
We have investigated the analogue memory characteristics of an oxide-based resistive-switching device under an electrical pulse to mimic biological spike-timing-dependent plasticity synapse characteristics. As a synaptic device, a TiN/Pr0.7Ca0.3MnO3-based resistive-switching device exhibiting excellent analogue memory characteristics was used to control the synaptic weight by applying various pulse amplitudes and cycles. Furthermore, potentiation and depression characteristics with the same spikes can be achieved by applying negative and positive pulses, respectively. By adopting complementary metal-oxide-semiconductor devices as neurons and TiN/PCMO devices as synapses, we implemented neuromorphic hardware that mimics associative memory characteristics in real time for the first time. Owing to their excellent scalability, resistive-switching devices, shows promise for future high-density neuromorphic applications.
RESUMO
Dental implant surgery, which involves the surgical insertion of a dental implant into the jawbone as an artificial root, has become one of the most successful applications of computed tomography (CT) in dental implantology. For successful implant surgery, it is essential to identify vital anatomic structures such as the inferior alveolar nerve (IAN), which should be avoided during the surgical procedure. Due to the ambiguity of its structure, the IAN is very elusive to extract in dental CT images. As a result, the IAN canal is typically identified in most previous studies. This paper presents a novel method of automatically extracting the IAN canal. Mental and mandibular foramens, which are regarded as the ends of the IAN canal in the mandible, are detected automatically using 3-D panoramic volume rendering (VR) and texture analysis techniques. In the 3-D panoramic VR, novel color shading and compositing methods are proposed to emphasize the foramens and isolate them from other fine structures. Subsequently, the path of the IAN canal is computed using a line-tracking algorithm. Finally, the IAN canal is extracted by expanding the region of the path using a fast marching method with a new speed function exploiting the anatomical information about the canal radius. In experimental results using ten clinical datasets, the proposed method identified the IAN canal accurately, demonstrating that this approach assists dentists substantially during dental implant surgery.
