arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2606.26751physics.opticsquant-ph
收藏

3R-MoS2/多层膜混合超表面腔中的巨二次谐波产生

Giant Second-Harmonic Generation in 3R-MoS2/MLM Hybrid Metasurfaces Cavities

Institute of Materials Research and Engineering, Agency for Science, Technology, and Research (A*STAR)(材料研究工程研究所,科学、技术与研究局(A*STAR))

Omar A. M. Abdelraouf

AI总结:

提出基于物理信息AI的逆设计框架NanoPhotoNet-PINL,通过优化多层膜超表面实现3R-MoS2二次谐波强度提升超三个数量级。

摘要:

非线性二维材料如3R相二硫化钼(3R-MoS2)在原子薄平台上提供强二阶光学非线性,使其在片上频率转换、量子光产生和集成非线性纳米光子学中具有吸引力。然而,沉积在平面基底上的单层或少层3R-MoS2的二次谐波产生(SHG)效率仍然受到弱光-物质相互作用、不良相位匹配和小相互作用体积的根本限制。这里,我们介绍NanoPhotoNet-PINL,一种基于物理信息AI的逆设计框架,基于混合一维卷积神经网络和深度神经网络自编码器,专为非线性多层膜超表面定制。该模型直接将基频和二次谐波波长处的目标双共振反射光谱映射到所需的多层几何结构和材料组成,以最大化与嵌入的3R-MoS2片层的有效非线性重叠。通过将基于麦克斯韦的非线性电动力学整合到逆设计循环中,我们计算每个预测多层膜设计的二次谐波转换效率和模式重叠因子,实现物理引导的训练和评估。我们的方法在线性光谱流形上实现了超过约99.2%的逆设计预测效率,而优化的双共振多层膜相比平面基底上的裸3R-MoS2薄片,在SHG强度上实现了超过三个数量级的增强。NanoPhotoNet-PINL为高效二阶过程的非线性多层膜超表面和相位匹配双共振腔的智能逆设计建立了一个可推广的范式。

英文摘要:

Nonlinear 2D materials such as 3R-phase molybdenum disulfide (3R-MoS2) offer strong second-order optical nonlinearities in an atomically thin platform, making them attractive for on-chip frequency conversion, quantum light generation, and integrated nonlinear nanophotonics. However, the second harmonic generation (SHG) efficiency of monolayer or few-layer 3R-MoS2 deposited on planar substrates remains fundamentally limited by weak light-matter interaction, poor phase matching, and small interaction volumes. Here, we introduce NanoPhotoNet-PINL, a physics informed AI-driven inverse design framework based on a hybrid one-dimensional convolutional neural network and deep neural network autoencoder, tailored for nonlinear MLMs metasurfaces. The model directly maps target dual-resonant reflection spectra at the fundamental and second-harmonic wavelengths to the required multi-layer geometries and material compositions that maximize the effective nonlinear overlap with an embedded 3R-MoS2 sheet. By integrating Maxwell-based nonlinear electrodynamics into the inverse design loop, we compute the second-harmonic conversion efficiency and modal overlap factors for each predicted MLMs design, enabling physics-guided training and evaluation. Our approach achieves an inverse-design prediction efficiency exceeding ~99.2 % along the linear spectral manifold, while the optimized dual-resonant MLMs yield more than three orders of magnitude enhancement in SHG intensity compared to a bare 3R-MoS2 flake on a planar substrate. NanoPhotoNet-PINL establishes a generalizable paradigm for intelligent inverse design of nonlinear multi-layer metasurfaces and phase-matched dual-resonant cavities for high-efficiency second-order processes.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑