标题： 微尺度光电突触，具有来自卤化物钙钛矿的可切换光电流 显示英文标题

标题： Microscale optoelectronic synapses with switchable photocurrent from halide perovskite

摘要： 高效视觉数据处理需要易失性人工突触，这些突触能够检测和处理光输入，理想情况下在同一个器件中完成。 在这里，我们展示了微尺度背接触式光电卤化物钙钛矿人工突触，它们利用偏置电压引起的离子迁移来调节其光电流。 光电流的变化是由于移动离子的积累，这在钙钛矿中诱导出瞬态电场。 光电流的变化是易失性的，衰减时间在秒级。 光电流的变化可以通过施加的电压和光照进行控制。 对称器件支持光电流极性的改变，可以在抑制性和兴奋性功能之间切换。 光电流可以通过受生物学启发的脉冲时间依赖可塑性（STDP）学习规则进行更新。 我们通过仿真展示了这如何可以被用作神经形态探测器中的注意力机制。 我们的制造工艺与CMOS以及忆阻器神经形态网络具有高密度集成兼容性，从而实现受大脑启发的节能视觉数据处理。 显示英文摘要

摘要： Efficient visual data processing by neuromorphic networks requires volatile artificial synapses that detect and process light inputs, ideally in the same device. Here, we demonstrate microscale back-contacted optoelectronic halide perovskite artificial synapses that leverage ion migration induced by a bias voltage to modulate their photocurrent. The photocurrent changes are due to the accumulation of mobile ions, which induces a transient electric field in the perovskite. The photocurrent changes are volatile, decaying on the order of seconds. The photocurrent changes can be controlled by both the applied voltage and illumination. The symmetric device supports changing of the photocurrent polarity, switching between inhibitory and exhibitory functioning. The photocurrent can be updated by spike-timing-dependent plasticity (STDP)-learning rules inspired by biology. We show with simulations how this could be exploited as an attention mechanism in a neuromorphic detector. Our fabrication procedure is compatible with high-density integration with CMOS and memristive neuromorphic networks for energy-efficient visual data processing inspired by the brain.