Emergence of Neuromorphic Devices using Conductive Materials of Various Ion Species

The development of hardware-oriented artificial intelligence (AI), such as information terminals and brain computers that operate with small size and low power consumption, is expected to develop into the next generation of information technology. In order to realize such hardware-oriented AI systems that do not rely on conventional supercomputers and complex programs, new concept devices with diverse functions, such as memristive and neuromorphic devices, should be required. To this end, it is necessary not only to further develop conventional semiconductor devices with characteristics suitable for digital arithmetic processing, but also to create novel devices that operate based on new principles.<br/>As you know, material properties can be significantly altered by slightly changing the composition and arrangement of its constituent atoms. Therefore, we have been actively searching for interesting nanophenomena arising from the control of composition and atomic configuration in nanostructures. Such nanostructure control can be achieved using ionic nanoarchitectonics techniques, which allow local control of ion transport and electrochemical reactions occurring at and near solid interfaces or surfaces. We have used the ionic nanoarchitectonics to create a variety of devices with unique electrical, magnetic, and optical functions and performance that cannot be obtained with conventional semiconductor devices^[1,2]. Some neuromorphic devices such as a decision-making device, artificial synaptic devices, multifunctional on-demand device, artificial vision device and physical reservoir devices^[3] have been fabricated using ion-conducting materials of various ion species. This talk will focus on the creation of various neuromorphic devices by ionic nanoarchitectonics using conductive materials of various ion species such as proton ions, lithium ions, silver ions, copper ions, and oxide ions.<br/><br/>Reference<br/>[1] K. Terabe et al. <i>Adv. Electron. Mater. </i><b>8</b>(8), 2100645, 2022<br/>[2] K. Terabe et al. <i>Nanoscale </i><b>148</b>(29), 13873-13879, 2016<br/>[3] T. Nishioka et al. <i>Sci. Adv</i>. <b>8</b>, eade1156 (2022)