An optoelectronic synapse based on Cu-BHT MOF for multi-wavelength optical logic gates and neuromorphic vision system

The limitations of von Neumann architectures in computational speed and energy efficiency have driven the development of neuromorphic computing systems, where optoelectronic synaptic devices play a pivotal role in enabling brain-inspired information processing. This study presents an optoelectronic synaptic device based on a two-dimensional conductive metal-organic framework material Cu-BHT which exhibits broad visible-light absorption (300 - 600 nm), high photoconductivity, and solution processability. The fabricated device with a planar structure of Ag/Cu-BHT/Ag successfully simulates the key biological synaptic functionalities, including excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), and short-to-long-term memory transitions. The device achieves a high accuracy of 96.3% in MNIST handwritten digit recognition using a convolutional neural network (CNN). Furthermore, multi-wavelength response of the device enables optical logic operations (AND/OR) and associative learning paradigms, such as Pavlovian conditioning experiment. This work underscores Cu-BHT as a versatile material for neuromorphic computing and artificial visual systems, with future research exploring scalable fabrication and hybrid integration to realize adaptive vision platforms with enhanced energy efficiency.