Electrolyte Gated Synaptic Transistor based on an Ultra‐Thin Film of La_0.7Sr_0.3MnO₃

Abstract

Developing electronic devices capable of reproducing synaptic functionality is essential in the context of implementing fast, low‐energy consumption neuromorphic computing systems. Hybrid ionic/electronic three‐terminal synaptic transistors are promising as efficient artificial synapses since they can process information and learn simultaneously. In this work, an electrolyte‐gated synaptic transistor is reported based on an ultra‐thin epitaxial La0.7Sr0.3MnO3 (LSMO) film, a half‐metallic system close to a metal‐insulator transition. The dynamic control of oxygen composition of the manganite ultra‐thin film with voltage pulses applied through the gate terminal allows reversible modulation of its electronic properties in a non‐volatile manner. The conductance modulation can be finely tuned with the amplitude, duration, and number of gating pulses, providing different alternatives to gradually update the synaptic weights. The transistor implements essential synaptic features such as excitatory postsynaptic potential, paired‐pulse facilitation, long‐term potentiation/depression of synaptic weights, and spike‐time‐dependent plasticity. These results constitute an important step toward the development of neuromorphic computing devices leveraging the tunable electronic properties of correlated oxides, and pave the way toward enhancing future device functionalities by exploiting the magnetic (spin) degree of freedom of the half metallic transistor channel.

Oxide Ionic Neuro-Transistors for Bio-inspired Computing

“…The implementation of synaptic plasticity plays an essential role in realizing ionic dynamic neuromorphic computing. A wide variety of synaptic ionic computing behaviors such as post-synaptic currents [41,100,[116][117][118][119][120][121][122][123][124], short-term plasticity [29,64,69,[125][126][127][128][129][130][131][132][133][134][135][136][137], long-term plasticity [138][139][140][141], and synaptic learning rules [142][143][144] have been implemented by oxide ionic transistors.…”

In2O3/ZnO heterojunction thin film transistor for high recognition accuracy neuromorphic computing and optoelectronic artificial synapses

“…A monolayer of In 2 O 3 was used as the semiconductor layer, and we manufactured and tested three TFTs with varying lithiumzirconium ratios across gate voltages spanning from −0.5 V to 2 V. Figure S5(a) presents the transfer curves of the three devices, while figure S5(b) displays the corresponding leakage currents. From the figure, it is evident that the leakage current increases gradually with lithium ion doping, which can have a detrimental impact on the transistor [24]. Both the 5:1 and 3:1 devices exhibit larger hysteresis windows and lower subthreshold swing(SS).…”

Compliance-Free and Forming-Free Digital and Analog Resistive Switching in a Perovskite-Based Artificial Synaptic Device: Mimicking Classical Pavlovian Learning

“…Currently, perovskite oxides, especially materials like La 0.7 Sr 0.3 MnO 3 (LSMO), − Pr 0.7 Ca 0.3 MnO 3 (PCMO), Nb/SrTiO 3 (NSTO), BiFeO 3 (BFO), and Sr 2 Nb 3 O 10 , are garnering significant attention for their potential applications in memristive devices. This heightened interest arises from their ability to offer multifunctionality within a single device through interactions among charge, spin, orbit, and lattice orders. − Only the bio-synaptic behavior of these materials is rarely studied.…”