Thermally‐Strained Black Phosphorus Photovoltaics Toward Spatially‐Resolved Biomimetic Vision Enhancement

材料科学 光伏系统 光电流 神经形态工程学 光伏 光电子学 黑磷 光电探测器 纳米技术 极化(电化学) 光电效应 光电效应 各向异性 夜视 光热治疗 数字光处理 光学 光电传感器 热稳定性 图像传感器
作者
Jing–Yu Ji,Senjiang Yu,Mingliang Cheng,Yan Mo,Yijun Huang,Yibing Liu,Weitao Su,Chenxi Lu,Liang Hu
出处
期刊:Advanced Materials [Wiley]
卷期号:38 (6): e17056-e17056 被引量:6
标识
DOI:10.1002/adma.202517056
摘要

Abstract The bulk photovoltaic effect presents a promising opportunity for smart photovoltaic sensing devices without the need for complex junction configurations. Black phosphorus (BP), with thickness‐ and direction‐sensitive photoelectric characteristics and industrial scalability, is well‐suited for developing integrated and reconfigurable imaging sensors. Although BP‐based hetero‐/homo‐structures have demonstrated notable photovoltaic effects, the development of non‐junction BP devices remains challenging. Herein, thick BP is engineered with directional spontaneous polarization along the armchair direction by artificially applying anisotropic thermal strains. This modified BP exhibits an ultrabroad photovoltaic response spanning 365–1800 nm, achieving a peak photocurrent density of ≈52.2 mA cm −2 under µW‐level illumination, setting a new performance benchmark compared to existing non‐junction or homojunction BP‐based photovoltaic devices. Furthermore, robust operation stability and millisecond‐level response within the human eye visual range indicate the potential for biomimetic vision applications. Leveraging these superiorities, a spatially‐resolved imaging sensor that incorporates multi‐optical parameters modulated synaptic plasticity and photoelectric transport nonlinearity, is developed. Such an all‐in‐one sensor allows for synergistic perception and parallel processing of blended images, demonstrating an enhanced anisotropic recognition capability of up to 94.1%. The thermally‐strained symmetry‐breaking approach paves the way for nonlinear photovoltaic effects in low‐symmetry layered materials, advancing high‐integration low‐power neuromorphic sensors.
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