Kumar Jitendra, Lizotte Daniel, Marunchenko Alexandr, Tatarinov Dmitry, Singh Shivam, Vaynzof Yana, Scheblykin Ivan G
Chemical Physics and NanoLund, Lund University, 22100 Lund, Sweden.
School of Physics and Engineering, ITMO University, St. Petersburg 197101, Russian Federation.
ACS Energy Lett. 2025 Jul 11;10(8):3729-3734. doi: 10.1021/acsenergylett.5c01369. eCollection 2025 Aug 8.
A memlumor is an innovative neuromorphic luminescent device with a state-dependent photoluminescence quantum yield (PLQY) designed for optical neuromorphic computing applications. Metal halide perovskite memlumors leverage charge trapping and photodoping to modulate the PLQY, making it dependent on the excitation light history. Here, we demonstrate the ability of perovskite memlumors to classify time-dependent binary optical signals on sub-microsecond timescales. Sequences of laser pulses (representing ones) and gaps (absence of pulses representing zeros) were used to excite photoluminescence in MAPbBr and triple cation perovskite films. By reading only the time-integrated PL signal, we completely recognized the time-dependent input patterns containing 5 bits of information. The potential of perovskites for applications in optical reservoir computing based on their complex and diverse photophysics is discussed.
忆光器是一种创新的神经形态发光器件,具有与状态相关的光致发光量子产率(PLQY),专为光学神经形态计算应用而设计。金属卤化物钙钛矿忆光器利用电荷俘获和光掺杂来调制PLQY,使其依赖于激发光历史。在此,我们展示了钙钛矿忆光器在亚微秒时间尺度上对随时间变化的二进制光信号进行分类的能力。激光脉冲序列(代表“1”)和间隙(无脉冲代表“0”)用于激发MAPbBr和三阳离子钙钛矿薄膜中的光致发光。通过仅读取时间积分PL信号,我们完全识别了包含5位信息的随时间变化的输入模式。基于其复杂多样的光物理性质,讨论了钙钛矿在光学储能计算中的应用潜力。