Affiliation:
1. School of Materials Science, Engineering Nanyang Technological University Singapore 639798 Singapore
2. Energy Research Institute @ NTU (ERI@N) Nanyang Technological University Singapore 637553 Singapore
Abstract
AbstractInspired by the brain, neuromorphic computing seeks to improve data‐centric applications in terms of power consumption and device footprint. The processing efficiency can be attributed to reconfigurable connections coupled with complex dynamics and efficient data sensing and signal processing. With field‐effect tunability, the three‐terminal thin‐film transistor is initially explored as a switch. Recently, transistors with added gates and modes have been fashioned as multi‐terminal devices capable of interconnecting complex networks and transducing multiple inputs. Here, the advances in both the semiconducting channel material and the configurational design of multi‐terminal devices are reviewed. The use of strong coupling and dynamical material properties in novel ion‐based capacitors, mixed‐ionic‐electronic semiconductors, low‐dimensional confined systems, stimuli‐responsive materials and redox‐active semiconductors has enabled new neuromorphic functionalities. These include improving reconfigurability using the regulatory ability of homeostasis, dendritic integration of sensory signals and the synaptic competition of resources. The transistor devices are also highly relevant in circuits that improve the efficiency of sensory transduction and signal processing; stimuli‐responsive semiconductors that adapt to the sensory inputs can be employed in the transistors and highly efficient sensorimotor connections between sensors and actuators can be emulated. These highly efficient, low‐complexity analog devices are crucial design elements for next‐generation neuromorphic systems.
Funder
National Research Foundation Singapore
Subject
Electronic, Optical and Magnetic Materials