We have found a memristive characteristic of an α-GTO thin-film device. The α-GTO thin-film layer is deposited using radio-frequency (RF) magnetron sputtering at room temperature and sandwiched between the Al top and bottom electrodes. It is found that the hysteresis loop of the flowing current (I) and applied voltage (V) characteristic becomes larger and stable after the one hundredth cycle. The electrical resistances for the high-resistance state (HRS) and low-resistance state (LRS) are clearly different and relatively stable. Based on various analysis, it is suggested that the memristive characteristic is due to the chemical reaction between the SnO
2
and SnO blocked by AlO
x
on the Al bottom electrode. It is marvelous that the memristive characteristic can be realized by such common materials, simple structures, and easy fabrication.
We have found a memristive characteristic of an amorphous Ga-Sn-O (α-GTO) thin-film device with double layers of different oxygen density. The double layers are deposited using radio frequency (RF) magnetron sputtering, whose gas for the lower layer contains less oxygen, whereas that for the upper layer contains more oxygen, and it is assumed that the former contains more oxygen vacancies, whereas the latter contains fewer vacancies. The characteristic is explained by drift of oxygen and is stable without forming operation because additional structures such as filament are unnecessary. The fabrication is easy because the double layers are successively deposited simply by changing the oxygen ratio in the chamber.
A memristor property of an amorphous Sn–Ga–O (α-TGO) thin-film device deposited using a mist chemical-vapor-deposition (mist-CVD) method has been found. The α-TGO device can be manufactured at a low cost because it does not include rare metals such as In. Moreover, it is expected that the α-TGO device can be manufactured at an even lower cost because the mist-CVD method is performed at atmospheric pressure. Here, the α-TGO layer was deposited using a hot-wall-type mist-CVD method. The hysteresis curve of the memristor characteristic was certainly obtained, and the electric resistances for the high- and low-resistance states were stably repeated at least 20 times. Although the switching ratio and repeatability are not sufficient in the case that it is applied to resistive random access memories, they are acceptable for some applications such as synapse elements in neuromorphic systems.
Artificial intelligences are indispensable in future societies, and neural networks are representative that mimic biological brains. However, the conventional ones are complicated software on high-spec hardware, the machine size is bulky, and power consumption is huge. Neuromorphic systems are practical solutions composed solely of optimized hardware. Therefore, we are investigating neuromorphic systems with amorphous met-al-oxide-semiconductor thin-film devices as synapse elements and proposing modified Hebbian learning done locally without extra control circuits. As a result, the conductance deterioration can be utilized as synaptic plasticity. It is expected that the neuromorphic systems are three-dimensional-integrated systems, the size can be compact, power can be low, and all functions of biological brains are realized. In this study, we have developed neuromorphic systems with crosspoint-type amorphous Ga-Sn-O thin-film devices as self-plastic synapse elements, and fundamental operations are confirmed. First, crosspoint-type devices are fabricated, and it is found that the electric current gradually decreases along the bias time. Next, a neuromorphic system is actually implemented using a field-programmable-gate-array chip and crosspoint-type devices, and it is confirmed that a function of letter recognition is obtained after learning process. Once the fundamental operations are confirmed, more advanced functions will be obtained by increasing the device and circuit scales.
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