Reconfigurable Two-Dimensional Activation Neuron Device

Realizing energy-efficient and compact neuron devices, as well as integrating digital and analog signal processing capabilities within such a device, facilitates implementation of neural network edge computing but remains challenging. Herein, we develop a reconfigurable two-dimensional (2D) activation neuron featuring digital-analog mixed processing capabilities by 2D heterostructure. The band-to-band tunneling in the homojunction by gate-drain overlap design within the 2D channel enables the activation neuron to dynamically reconfigure subthreshold swings and threshold voltage, which is verified experimentally and by technology computer-aided design simulations and a rigorous analytical model. Consequently, the 2D activation neuron accurately replicates standard Softplus activation function while maintaining an ultralow leakage power of 10 pW. In neural network training, the activation neuron achieves accuracies exceeding 98%. These findings provide a potentially effective route for energy-efficient implementation of neural networks and edge computing systems.