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1月10日外宾学术报告:Memlumors: Perovskite Luminescence Meets Neuromorphic Artificial Intelligence

来源: 发布时间:2025-01-07【字体:

报告人Alexandr Marunchenko, Lund University

会议时间20250110日(周五) 上午9:30

会议地点清河路390溢智厅

报告内容:

Metal-halide perovskites are emerging materials renowned for their high photoluminescence quantum yield and long charge carrier lifetimes. These properties make them ideal candidates for optoelectronic devices, including solar cells, photodetectors, and LEDs. In this talk an introduction of the concept of Memlumor, a luminophore with memory, and a demonstration of its functionality using metal-halide perovskite materials will be given. A novel technique, multi-pulse time-resolved photoluminescence, will be presented, which can detect changes in luminescence on ultrafast timescales. Operational mechanisms that enable modulation of perovskite quantum yield at rates up to 80 MHz, as well as detection of memory retention in luminescence lasting up to milliseconds will be discussed. A simple computing application of Memlumors: n-bit classification task will be demonstrated. This memory-enabled luminescence expands the application scope of perovskites far beyond conventional optoelectronic applications, paving the way for the creation of novel computing devices.

报告人简介:

Alexandr Marunchenko completed his Bachelor's and Master's degrees at the Moscow Institute of Physics and Technology. He is currently a PhD student at Lund University, conducting research related to optical computing using metal halide perovskites. His research primarily focuses on the analysis and characterization of metal halide perovskites through time-resolved photoluminescence spectroscopy, including as well the development of novel computational designs for perovskite-inspired optical components.

Recent publications: Marunchenko, A., Kumar, J., et al. ACS Energy Lett. 2024, 9 (5), 2075-2082; J. Phys. Chem. Lett. 2024, 15 (24), 6256-6265; ACS Energy Lett. 2024, 9, 5898-5906.


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