The g-C3N4-TiO2 nanocomposite for non-volatile memory and artificial synaptic device applications

Recently, 2D layered materials like graphitic carbon nitride (g-C3N4) are gaining significant attention due to their excellent structural and electronic properties. Metal oxide g-C3N4 composite can enhance chemical properties which ultimately device performance. Given this, we report the synthesis of g-C3N4–TiO2 nanocomposite by ex-situ (solid state reaction) method for resistive switching (RS) applications. Initially, TiO2 nanoparticles (NPs) were optimized using annealing them at different temperatures composited with g-C3N4. The devices fabricated shows good RS very low SET RESET voltages (< 0.5 V), similar biological voltage scale. distribution all was studied cumulative probability Weibull techniques. Moreover, modeled predicted statistical time series analysis method. All demonstrated double-valued charge flux characteristics, suggesting presence a non-ideal memristor effect. g-C3N4-TiO2 (TiO2 NPs annealed 450 oC) endurance retention memory mimic various bio-synaptic such as potentiation-depression, excitatory postsynaptic current, paired-pulse facilitation. transport results reveal that Ohmic Child's square law dominated conduction device. Based on electrical results, plausible filamentary effect is presented. This study suggested beneficial both neuromorphic computing