DOI: https://doi.org/10.29363/nanoge.matnec.2022.016
Publication date: 23rd February 2022
Within the last few years, memristors have aroused much interest in the scientific community.[1] Their resistance tunability, as well as their hysteretic and non-volatile behaviour has made them attractive for memory applications. Recently, memristors are actively investigated as hardware implementations for future neuromorphic computers. This emerging field comprises novel electronic circuits inspired by the human brain, motivated by its strikingly low energy consumption, high efficiency of cognitive tasks, such as image or pattern recognition, and the ability of the brain to reconfigure nervous connections, also called neuronal plasticity.[2] Prominent candidates for enabling neuromorphic computing on a hardware-level are ferroic materials. An intrinsic feature of all ferroic materials is the occurrence of domain walls (DWs) separating domains, the latter being regions with homogeneous orientation of the order parameter (electric polarization in the case of ferroelectrics). Ferroelectrics have already been successfully employed for memristive devices such as ferroelectric tunnel junctions.[3] At the same time, ferroic materials paved the way for the large class of DW-based nanodevices, which can exhibit high reconfigurability as DWs can be easily written and erased.[4] Extensive works on the multiferroic oxide bismuth ferrite (BiFeO3) have shown that DWs in thin films can be more conducting than the domains.[5] During thin film growth, BiFeO3 self-assembles into a nanoscale network of conducting domain walls,[6] which can be tailored by varying the deposition parameters. While the memristive properties of the individual DWs have been demonstrated,[7] their functionality as building blocks for hardware-based neural networks is currently being investigated.[8] However, control of the nanoscale connectivity of the DW network, as well as characterizing the electrical conductivity through the network, has proven to be very challenging. Here we present our progress on the study of the transport properties of self-assembled DW networks in BiFeO3 thin films. Scanning probe techniques allow local DW probing to investigate the memristive properties and mapping of the conductive DW network.
This project is part of the EU-funded Innovative Training Network MANIC (“Materials for neuromorphic circuits”). We also like to acknowledge the financial support of the CogniGron research center and the Ubbo Emmius Funds (Univ. of Groningen).
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