Charge Trapping and Defect Dynamics as Origin of Memory Effects in Metal Halide Perovskite Memlumors
Large language models for artificial intelligence applications require energy-efficient computing. Neuromorphic photonics has the potential to reach significantly lower energy consumption in comparison with classical electronics. A recently proposed memlumor device uses photoluminescence output that carries information about its excitation history via the excited state dynamics of the material. So
