An Ultralow Power LixTiO2-Based Synaptic Transistor for Scalable Neuromorphic Computing

Artificial synapses based on electrochemical synaptic transistors (SynTs) have attracted tremendous attention toward massive parallel computing operations. However, most SynTs still suffer from downscaling limitations and high energy consumption. To overcome such drawbacks, a complementary metal-oxide-semiconductor (CMOS) back-end-of-line compatible solid-state SynT is presented, which includes an ultrathin (10 nm thick) quasiamorphous LixTiO2 channel. A nonvolatile conductance modulation (<75 nS) is achieved through reversible lithium intercalation into the channel, and synaptic functions, such as long-term potentiation/depression involve ultralow switching energy of 2 fJ mu m(-2). Moreover, this SynT shows excellent endurance (>10(5) weight updates) and recognition accuracy (>95% on the MNIST data test using crossbar simulations). Furthermore, a comprehensive electrochemical study allows deeper insight into the specific pseudocapacitive mechanism at the origin of conductance modulation. These results underline the high potential of LixTiO2-based SynTs for energy-efficient neuromorphic applications.

Automated summary

This study presents a new solid-state SynT based on LixTiO2 that overcomes the limitations of traditional SynTs, showing excellent endurance, recognition accuracy, and ultralow switching energy. Reversible lithium intercalation enables nonvolatile conductance modulation, while comprehensive electrochemical study provides insight into the specific mechanism of conductance modulation. These results highlight the high potential of LixTiO2-based SynTs for energy-efficient neuromorphic applications.