Memristive systems have been extensively explored for the realization of novel computing hardware architectures. In addition to conventional crossbar arrays based on two-terminal memristive cells, multiterminal memristive systems formed by self-organizing networks of nanoscale components have attracted growing interest. Here, we discuss the concept of transmemristance in multiterminal memristive networks, where emergent memristive behavior arises from the mutual interactions among a large number of nanowires (NWs). We show that transmemristance offers a new perspective for probing the internal dynamics of such systems, providing insights into their spatiotemporal evolution. Moreover, it can serve as a measurable physical quantity that reflects the internal state of the network and can be harnessed for the hardware implementation of unconventional computing paradigms.
Transmemristance in multiterminal memristive nanowire networks / Milano, Gianluca; Cultrera, Alessandro; Miranda, Enrique; Ricciardi, Carlo. - (2026), pp. 1-3. ( 2026 10th IEEE Electron Devices Technology & Manufacturing Conference (EDTM)) [10.1109/edtm65772.2026.11497048].
Transmemristance in multiterminal memristive nanowire networks
Milano, Gianluca;Miranda, Enrique;Ricciardi, Carlo
2026
Abstract
Memristive systems have been extensively explored for the realization of novel computing hardware architectures. In addition to conventional crossbar arrays based on two-terminal memristive cells, multiterminal memristive systems formed by self-organizing networks of nanoscale components have attracted growing interest. Here, we discuss the concept of transmemristance in multiterminal memristive networks, where emergent memristive behavior arises from the mutual interactions among a large number of nanowires (NWs). We show that transmemristance offers a new perspective for probing the internal dynamics of such systems, providing insights into their spatiotemporal evolution. Moreover, it can serve as a measurable physical quantity that reflects the internal state of the network and can be harnessed for the hardware implementation of unconventional computing paradigms.Pubblicazioni consigliate
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https://hdl.handle.net/11583/3010873
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