2D MoS2-based reconfigurable analog hardware

Biological neural circuits demonstrate exceptional adaptability to diverse tasks by dynamically adjusting neural connections to efficiently process information. However, current two-dimension materials-based neuromorphic hardware mainly focuses on specific devices to individually mimic artificial synapse or heterosynapse or soma and encoding the inner neural states to realize corresponding mock object function. Recent advancements suggest that integrating multiple two-dimension material devices to realize brain-like functions including the inter-mutual connecting assembly engineering has become a new research trend. In this work, we demonstrate a two-dimension MoS2-based reconfigurable analog hardware that emulate synaptic, heterosynaptic, and somatic functionalities. The inner-states and inter-connections of all modules co-encode versatile functions such as analog-to-digital/digital-to-analog conversion, and linear/nonlinear computations including integration, vector-matrix multiplication, convolution, to name a few. By assembling the functions to fit with different environment-interactive demanding tasks, this hardware experimentally achieves the reconstruction and image sharpening of medical images for diagnosis as well as circuit-level imitation of attention-switching and visual residual mechanisms for smart perception. This innovative hardware promotes the development of future general-purpose computing machines with high adaptability and flexibility to multiple tasks. This study introduces a reconfigurable MoS2-based neuromorphic hardware that integrates synaptic, heterosynaptic, and somatic functionalities. It adapts to diverse tasks like medical image enhancement and smart perception, advancing flexible, general-purpose computing solutions.