Darweesh Rana, Yadav Rajesh Kumar, Adler Elior, Poplinger Michal, Levi Adi, Lee Jea-Jung, Leshem Amir, Ramasubramaniam Ashwin, Xia Fengnian, Naveh Doron
Faculty of Engineering, Bar-Ilan University, 52900 Ramat-Gan, Israel.
Institue of Nanotechnology and Advanced Materials, Bar-Ilan University, 52900 Ramat-Gan, Israel.
Sci Adv. 2024 May 17;10(20):eadn6028. doi: 10.1126/sciadv.adn6028.
Computational spectrometry is an emerging field that uses photodetection in conjunction with numerical algorithms for spectroscopic measurements. Compact single photodetectors made from layered materials are particularly attractive since they eliminate the need for bulky mechanical and optical components used in traditional spectrometers and can easily be engineered as heterostructures to optimize device performance. However, such photodetectors are typically nonlinear devices, which adds complexity to extracting optical spectra from their response. Here, we train an artificial neural network to recover the full nonlinear spectral photoresponse of a single GeSe-InSe p-n heterojunction device. The device has a spectral range of 400 to 1100 nm, a small footprint of ~25 × 25 square micrometers, and a mean reconstruction error of 2 × 10 for the power spectrum at 0.35 nanometers. Using our device, we demonstrate a solution to metamerism, an apparent matching of colors with different power spectral distributions, which is a fundamental problem in optical imaging.
计算光谱学是一个新兴领域，它将光电探测与数值算法结合用于光谱测量。由层状材料制成的紧凑型单光电探测器特别有吸引力，因为它们无需传统光谱仪中使用的笨重机械和光学组件，并且可以很容易地设计成异质结构以优化器件性能。然而，这种光电探测器通常是非线性器件，这增加了从其响应中提取光谱的复杂性。在这里，我们训练了一个人工神经网络来恢复单个GeSe-InSe p-n异质结器件的完整非线性光谱光响应。该器件的光谱范围为400至1100纳米，占地面积小，约为25×25平方微米，在0.35纳米处功率谱的平均重建误差为2×10。使用我们的器件，我们展示了一种解决同色异谱现象的方法，同色异谱现象是指具有不同功率光谱分布的颜色之间的明显匹配，这是光学成像中的一个基本问题。
