近年来在工业化和城镇化快速发展的地区, 由重金属污染导致的环境问题尤为突出, 特别是农业重金属污染更为社会所关注, 因此, 探索快速便捷的重金属污染甄别与监测方法极为重要。 高光谱遥感作为新兴的重金属污染监测技术已有了深入研究。 提出了固有波长尺度分解（IWD）概念和方法, 并结合Hankel矩阵和奇异值分解（SVD）等建立了植被重金属污染程度预测的IWD-Hankel-SVD模型, 该模型分为单变量模型和多变量模型。 单变量模型主要是通过重金属污染的植被光谱IWD处理来获取光谱信息固有旋转分量（PRC）以提取最佳PRC的有效特征波段; 在对各特征波段所构建的Hankel矩阵进行奇异值分解（SVD）基础上, 依据获得该模型的奇异熵实现重金属污染信息预测。 多变量模型是以植物叶绿素浓度相对值、 单变量模型奇异熵作为参数实现重金属污染的信息预测。 根据不同重金属Cu2+胁迫梯度下玉米植株污染的叶片光谱和叶绿素浓度以及叶片中Cu2+含量测定的数据, 首先对不同浓度Cu2+胁迫下玉米叶片光谱进行IWD分析, 获得能够较好保留原始输入光谱信息的最佳PRC, 并从中提取到有效特征波段553~680, 681~780, 1 266~1 429, 1 430~1 631, 1 836~1 913和1 914~2 111 nm; 然后对每一个特征波段构造其Hankel矩阵并进行SVD处理, 以求取单变量的IWD-Hankel-SVD模型奇异熵; 最后通过各特征波段所对应模型奇异熵与玉米叶片中Cu2+含量的相关分析, 得到依据1 266~1 429和1 836~1 913 nm特征波段计算出奇异熵与玉米叶片中Cu2+含量的决定系数R2均高达0.9左右, 说明这两个特征波段用于IWD-Hankel-SVD模型的Cu污染程度预测更具优越性和解释能力。 同时, 再把玉米叶片中叶绿素浓度相对值、 1 266~1 429和1 836~1 913 nm特征波段相应模型奇异熵作为参数, 采用偏最小二乘回归分析, 得出多变量IWD-Hankel-SVD模型的玉米叶片Cu污染程度预测能力更强, 决定系数R2达到0.9476, 证明了多变量模型更具有鲁棒性和稳健性。

Recently, the subject on “plasmonics’’ has received significant attention in designing surface plasmon resonance (SPR) sensors. In order to achieve extremely high-sensitivity sensing, multilayered configurations based on a variety of active materials and dielectrics have been exploited. In this work, a novel SPR sensor is proposed and investigated theoretically. The structure, analyzed in attenuated total reflection (ATR), consists of multilayer interfaces between gold and a metamaterial (LHM) separated by an analyte layer as a sensing medium. By interchanging between gold and LHM, under the effect of the refractive index (RI) of analyte set to be in the range of 1.00 to 1.99, the sharp peak reflectivity at the SPR angle takes two opposite behaviors predicted from the transfer matrix method. At the threshold value of 1.568 of the refractive index of analyte and when the LHM is the outer medium, the layered structure exhibits a giant sharp peak located at 43° of intensity up to 105 due to the Goos-Hànchen effect. With respect to the refractive index (RI) change and thickness of analyte, the characteristics (intensity, resonance condition, and quality factor) of the SPR mode, which make the proposed device have the potential for biosensing applications, have been analytically modelized.

Light trapping is of critical importance for constructing high efficiency solar cells. In this paper, we first reviewed the progress we made on the plasmonic light trapping on Si wafer solar cells, including Al nanoparticle (NP)/SiNx hybrid plasmonic antireflection and the Ag NP light trapping for the long-wavelength light in ultrathin Si wafer solar cells. Then we numerically explored the maximum light absorption enhancement by a square array of Ag NPs located at the rear side of ultrathin solar cells with wavelength-scale Si thickness. Huge absorption enhancement is achieved at particular long wavelengths due to the excitation of the plasmon-coupled guided resonances. The photocurrent generated in 100 nm thick Si layers is 6.8 mA/cm2, representing an enhancement up to 92% when compared with that (3.55 mA/cm2) of the solar cells without the Ag NPs. This study provides the insights of plasmonic light trapping for ultrathin solar cells with wavelength-scale Si thickness.