Learning in colloidal polyaniline nanorods

Liquid-based computing media are massively parallel computing devices with high fault-tolerance and self-healing capabilities. They can compute by propagating and interacting phase waves or by changing their internal coordination.Colloidal suspensions of conductive polymer nanorods are expected to be interesting candidates for developing the computing subsystem in such applications, because of their anisometry which makes them particularly susceptible to electrical fields.In this work, we investigateda suspension of polyaniline nanorods (NRs) to explorethe potential of generatinglearning mechanisms in the colloid and applyingthem in the computing system of future cybernetic systems. We demonstrated that learning, as expressed in the formation of programmable conductive pathways leading to distinct states, can be implemented using Alternated Current (AC) electrical stimulation. We achievedrepeatable programming of colloid resistance anisotropy that can be easily mapped into binary logic, demonstrating that this is due to the AC field effects on the hydrogen bonds that stabilise the dispersoids in the solvent as well as the charges' orientation inside the polymeric chains. We also influencedthe conductivity of polyaniline (PANI) NRs by changing their molecular conformation. The findings establish robustprotocols for programming future liquid robots.