Interfacial Ion‐Trapping Electrolyte‐Gated Transistors for High‐Fidelity Neuromorphic Computing

Abstract Li + electrolyte‐gated transistors (EGTs) have received much attention as artificial synapses for neuromorphic computing. EGTs, however, have been still challenging to achieve long‐term synaptic plasticity, which should be linearly and symmetrically controlled with the magnitude of electrical potential at the gate electrode. Herein, a fluoroalkylsilane (FAS) self‐assembled monolayer (SAM) is introduced as a channel‐electrolyte interlayer with the function of sequential ion‐trapping in Li + EGTs. It is demonstrated that the retention of Li + ions can be enhanced, resulting in stable non‐volatile channel conductance update with high fidelity, linearity, and symmetry in EGTs treated with FAS with 5 fluoroalkyl chains. Through investigating electrical analysis and chemical analysis, it is verified that fluoroalkyl chains enable the sequential ion‐trapping at the channel‐electrolyte interface by coulombic attraction between Li + ions and fluorocarbons. Simulations of artificial neural networks using 20 × 20 digits show FAS‐treated EGTs are suitable as artificial synapses with an accuracy of 89.71% by identical gate pulses and 91.97% by non‐identical gate pulses. A methodological approach is newly introduced for developing synaptic devices based on EGTs for neuromorphic computing with high fidelity.