Dataset of Controllable Photoelectric Dual-Output Artificial Light-Emitting Synapse Device

This dataset supports all figures and conclusions of the paper Controllable photoelectric dual-output artificial light-emitting synapse device, including raw test data and derived processed data from six categories: fabrication of artificial light-emitting synapse devices, photoelectric performance measurement, synaptic plasticity characterization, UV light suppression regulation, comparative test of devices without PVP layer, and handwritten digit recognition based on device neural network.Raw fabrication records: spin-coating parameters, annealing conditions, film solution ratios and electrode deposition parameters of each functional layer;Basic photoelectric characteristic data: I-V hysteresis curves under continuous voltage scanning, synchronous electroluminescence intensity, UV absorption spectra of TFB and PVP films, raw sampling data of device current decay under constant bias with 365 nm UV irradiation;Synaptic plasticity test data: EPSC current and synchronous luminescence under single/double electrical pulses, PPF index varying with pulse interval, dynamic device responses under different pulse frequencies and amplitudes, time-series electrical and optical outputs of device learning-forgetting cycles, repeated conductance modulation data under alternating electrical pulses and UV light;Comparative experimental data for mechanism analysis: pulse response and current variation under UV illumination of control QLED devices without PVP charge-trapping layer;Neural network simulation data: conductance evolution sequences with/without UV regulation, per-epoch classification accuracy of 3-layer artificial neural network for MNIST handwritten digit recognition, derived simulation data of synaptic weight mapping;