Electrode Dependence of Tunneling Electroresistance and Switching Stability in Organic Ferroelectric P(VDF‐TrFE)‐Based Tunnel Junctions

Abstract

Ferroelectric tunnel junctions (FTJs) are promising candidates for nonvolatile memories and memristor-based computing circuits. Thus far, most research has focused on FTJs with a perovskite oxide ferroelectric tunnel barrier. As the need for high-temperature epitaxial film growth challenges the technological application of such inorganic junctions, more easily processable organic ferroelectrics can serve as alternative if large tunneling electroresistance (TER) and good switching durability would persist. This study reports on the performance of FTJs with a spin-coated ferroelectric P(VDF-TrFE) copolymer tunnel barrier. The use of three different bottom electrodes, indium tin oxide (ITO), La 0.67 Sr 0.33 MnO 3 , (LSMO), and Nb-doped SrTiO 3 (STO) are compared and it is shown that the polarity and magnitude of the TER effect depend on their conductivity. The largest TER of up to 10 7 % at room temperature is measured on FTJs with a semiconducting Nb-doped STO electrode. This large switching effect is attributed to the formation of an extra barrier over the space charge region in the substrate. The organic FTJs exhibit good resistance retention and switching endurance up to 380 K, which is just below the ferroelectric Curie temperature of the P(VDF-TrFE) barrier.

Reproducible Ultrathin Ferroelectric Domain Switching for High‐Performance Neuromorphic Computing

“…The pioneering work by Chanthbouala et al demonstrated that the gradual switching of the ferroelectric domain and the resulting change of resistance states can ensure a memristor response in FTJs . Subsequently, several works have explored the possibility of FTJs as artificial synapses . Recently, Boyn et al realized unsupervised learning using FTJ based simulations …”

“…[21] Subsequently, several works have explored the possibility of FTJs as artificial synapses. [18,24,25] Recently, Boyn et al realized unsupervised learning using FTJ based simulations. [26] In this work, we demonstrate an artificial synapse with ultralow femtojoule energy consumption based on Pt/BaTiO 3 / Nb-doped SrTiO 3 FTJ devices.…”

Impact of semiconducting electrodes on the electroresistance of ferroelectric tunnel junctions

“…1(g)], more notably in the high resistance state, with a larger conductance for positive bias which turns the junction into accumulation. 32 A similar effect is present in Pt/BTO/LSMO, even though it is less evident because of the smaller depleted region associated with the larger carrier density (N c $ 10 21 cm À3 ) [ Fig. 1(d)].…”

“…We note that this result is coherent with previous works on Pt/BTO/LSMO 20 and Pt/BTO/Nb:STO 17,31 FTJs, and this dependence has also been recently verified in devices where the same electrodes are used with an ultrathin organic ferroelectric. 32 Figures 1(f) and 1(i) show the capacitance of the two devices as a function of bias. For this measurement, an Agilent E4980 LCR meter has been used with a sinusoidal excitation of frequency f ¼ 100 kHz and amplitude V pp ¼ 200 mV.…”

Multifunctional Optoelectronic Device Based on Resistive Switching Effects

“…The resistance of the "memory" layer can be dynamically reconfigured by voltageor current-induced ion implantation, interfacial charge accumulation, and so on. Usually, the electrodes are metal or oxide, such as Ag, Au, Pt, Ta, Ir, Cu, ITO, and so on, which will affect the resistive switching behavior by their different work function, electron affinity, electrochemical energy, and so on [33,34]. For the "memory" layer, various kinds of materials have been used, including binary oxide, nitride, perovskite, low-dimensional materials, and organic materials [35][36][37][38][39][40][41][42][43][44][45].…”