Application of Metasurfaces in Microbolometers
-
摘要: 超表面突破了传统自然材料的电磁特性限制，同时也解决了三维超材料难以加工实现等瓶颈问题，使器件朝着集成化，小型化，低成本，可调谐的方向不断发展。目前超表面已在许多领域得到了较为广泛的应用，在探测器领域也越来越受到人们的重视，通过独特的材料、结构设计，超表面可有效完成电磁波各项特性的精确调控，通过超表面的集成，微测辐射热计在光吸收增强，器件波段选择改善等方面有了更多的可能性。本文针对超表面及其在微测辐射热计上的应用研究进行了阐述，展现了超表面在这一领域的发展趋势和广阔前景。Abstract: Metasurfaces have overcome the electromagnetic limitations of traditional natural materials and solved the bottlenecks of difficult processing and implementation of three-dimensional metamaterials, leading devices to continuously develop towards integration, miniaturization, low cost, and tunability. Metasurfaces are widely used in many fields and are increasingly valued in the field of detectors. Through unique material and structural designs, metasurfaces can effectively achieve precise control of various electromagnetic wave characteristics. Through the integration of metasurfaces, microbolometers are more likely to enhance light absorption and improve the device band selection. This article elaborates on the research on metasurfaces and their applications in microbolometers, demonstrating the development trend and broad prospects of metasurfaces in this field.
-
Keywords:
- metasurface /
- microbolometer /
- enhanced light absorption /
- waveband selection
-
0. 引言
在红外热成像设备的设计和应用中，经常针对不同厂家或者不同型号的红外探测器定制非标的红外图像处理算法，以及标定不同的算法参数。由于算法模型或者算法参数经常变化，导致设计算法、仿真、在硬件上调试算法的时间很多，开发周期很长，开发效率低下等问题。而常规的红外图像处理算法，包括数据采集、时域滤波、非均匀性校正、空域滤波、锐化增强、坏点校正以及调光映射等。设计的初期，需要从算法原理设计、算法模型的建立、数学过程的计算，转化成可实现的编程语言，然后实现和显示。
随着小型化、低功耗、低成本的红外热成像设备应用的普及和民用。FPGA处理器非常适合于该种应用需求，FPGA是高速并行的处理器，适合于图像阵列的算法处理和加速，并且功耗低，可反复编程设计，所以常应用于红外热成像设备中。
1. 传统的红外图像仿真方法
基于FPGA的红外图像处理算法，仿真流程示意图如图 1所示。
从图 1中可知，利用FPGA处理器进行图像处理，需要两步的仿真结果。
第一步：根据算法需求，设计算法原理，在Matlab软件上编程实现算法过程，先用浮点数进行设计和计算，代码设计和编写完成后，导入测试图像，进行仿真和显示，在显示窗口中显示出来[1-4]。对显示出来的图像效果进行评估，看看图像效果有没有达到算法原理期望的结果，如果没有，调整算法参数和实现过程，反复迭代调整直至图像效果达到期望的结果。达到期望结果后，进行定点化设计，将算法实现过程中的浮点数，全部转化成定点化数，比如INT8、INT16、INT32等，并且转化完成后，保证算法实现的结果仍然达到期望值，不损失精度，不丢失细节。然后再更换测试图像，测试数据设计成依次递增或者递减的特征数据，再进行仿真。
第二步：文献[5]、[6]提出定点化之后的算法原理和实现过程，编写FPGA的硬件描述语言，设计FPGA的逻辑，将第一步过程中的算法原理实现出来，再进行ModelSim仿真，仿真测试的输入激励是第一步中同样依次递增或者递减的特征数据，得到仿真结果，与第一步中每个关键节点（关键步骤）的结果进行比对，保证每一步的结果都与Matlab仿真的结果相同，才能确保算法效果的达到。
传统的红外图像仿真方法，分成上述两个步骤，先要进行Matlab仿真，显示评判效果达到之后，再启动定点化，将定点化之后的算法过程转化成FPGA中可以实现的过程，并用FPGA的硬件描述语言实现相关的逻辑，再进行ModelSim仿真，由于ModelSim不能像Matlab工具一样方便导入一张图像（图片数据）进行仿真，仿真结果不能直观地可视化显示。所以在第一步、第二步过程中，输入激励的时候制作一些递增、递减的相同特征数据进行仿真。对每一步关键步骤和最后结果的仿真比对，保证数据正确，才能保证算法原理的实现和算法效果的达到。
2. 基于ModelSim可视化的红外图像仿真方法
从上述传统的红外图像仿真过程看，既要实现Matlab代码编写、仿真、还要做定点化设计。等FPGA代码编写完成后，在ModelSim仿真的时候还要进行每一步过程的计算结果比对，并且不能直接可视化的方式看到算法运行的结果。存在实现过程复杂、开发效率低下，开发周期长等问题。针对这些问题，本文提出了一种新的基于ModelSim可视化仿真的红外图像仿真方法。如图 2所示为本文的实现框图。
从图 2中可知，基于ModelSim可视化的红外图像仿真方法相比传统的红外图像仿真方法，仿真过程简单很多，开发效率也会提高很多。在算法原理设计完成后，直接编写FPGA的硬件描述语言实现算法计算过程，再进行ModelSim仿真，仿真的时候，不再用特定的递增数据或者递减的特征数据做输入激励，而是用之前原始采集到的红外图像，如果算法原理是针对16 bit的原始红外图像处理，可以是Y16数据，针对8 bit的调光之后红外图像处理可以是Y8数据，之前采集到的红外图像Y16或者Y8数据，存放在RAW文件中。而RAW文件中的图像数据是可以用ImageJ查看的，ImageJ工具可以直接显示16位或者8位的RAW图像。
对于红外图像算法所用到的数据文件——RAW文件，是不能直接导入ModelSim进行仿真的，需要经过binary工具将raw文件转换成txt文件，在ModelSim中通过系统调用＄readmemb/ readmemh函数读入TXT文件的方式读入到内存中，然后进行图像算法处理，算法处理完成，调用＄writememb/ ＄writememh函数将算法处理之后的图像写入txt文件中，通过txt2bin工具，将txt格式的数据转换成bin文件，再通过直接改后缀名，将.bin改成.raw文件。这样输入输出都是raw格式的数据文件，导入ImageJ工具中显示，以可视化的方式显示出了图像。
所以，这样红外图像算法处理的输入是图像数据，输出是处理之后的图像数据，可以直观地在ImageJ工具中显示出来对比，分析红外图像算法的处理过程是否正确。并且每一步的计算过程和关键步骤的结果也可以通过如图 3内存查看的方式、图 4内存读写过程仿真的方式查看数据在内存中存储、写入和读出是否异常。并通过如图 5红外图像算法处理仿真过程来查看数据计算过程正确与否。
![]()
图 4 红外图像数据内存读写仿真波形数据Figure 4. Infrared image data memory reading and writing simulation waveform data![]()
图 5 红外图像算法处理仿真波形数据Figure 5. Infrared image algorithm processing simulation waveform data这样数据输入，写入内存，然后从内存中读出，再进行红外图像算法处理，每一步数据的处理都是可以查询和追溯的，所以既方便又快捷。如图 6所示为本文进行红外图像滤波降噪算法处理过程中的输入源图和处理完成之后输出结果对比图Image显示，图 7为本文中基于ModelSim仿真过程中输入输出文件结构示意图。
![]()
图 6 红外图像滤波降噪输入输出对比图Figure 6. Infrared image filtering noise reduction input and output contrast diagram![]()
图 7 基于ModelSim仿真过程文件结构示意图Figure 7. Schematic diagram of file structure based on ModelSim在反复调整算法过程，以及算法参数的情况下，能够很快得到想要的算法结果，比如图 6中右边是降噪之后的效果图，降噪之后，图像噪声能消除了，但是图像变得模糊了，说明降噪算法参数设置不合适，通过调整滤波器的系数和阈值之后，降噪效果有明显的改善，如图 8所示。
![]()
图 8 红外图像滤波降噪后优化参数效果图Figure 8. Optimization parameter effect after infrared image filtering and noise reduction上述图 6与图 8中的红外图像滤波降噪算法为非局部平均滤波降噪算法，算法流程如图 9所示。这种降噪算法是一种利用图像自相似性的空域滤波算法，相比传统高斯平滑、双边滤波等方法，保护更多的图像细节。图像各点之间可以同时进行运算，非常适合于在FPGA并行处理器上运算。根据相似性计算权重的时候，如果相似性阈值选择太大，算法滤波出来的效果如图 6所示，过度平滑了，图像变模糊了，而选择合适的相似性阈值，得到滤波出来的效果如图 8所示，既能滤除噪声，又能保留图像细节。在该种红外图像仿真方法中能很快得到一组适合的算法参数。
基于该种ModelSim可视化的红外图像仿真方法，能够快速地修改算法参数和调整算法计算过程，运行之后得到图像算法的仿真结果，并且输入、算法计算、输出等环节里的每一步数据都是可以通过内存或者波形查看的方式追溯数据处理过程，保证数据向着期望的方向计算和处理。
3. 分析讨论
本文提出两种红外图像的仿真方法，传统的红外图像仿真方法，需要进行Matlab仿真，仿真结束后，再进行定点化设计，才能指导FPGA进行编程和实现，最后启动ModelSim的仿真，并且传统的ModelSim仿真并不能直接对图像数据的输入进行仿真并且可视化，而是制作相关的递增或者递减的特征数据作为输入，并且Matlab仿真同样以该特征数据作为输入，进行仿真，最后对2组仿真数据结果进行比对，比对结果一致代表该算法在FPGA中运行正常，能达到期望的算法效果。该过程复杂、繁琐、开发效率低下、开发周期长等问题不可忽视。所以本文在传统的红外图像仿真方法上进行了改进和优化，提出了一种新的基于ModelSim可视化的红外图像仿真方法与系统。该种方法在传统方法上省去了Matlab仿真的过程和环节，同时也省去了定点化的设计过程。在算法原理设计完成后，启动FPGA硬件描述语言的编写和仿真，只是在仿真的时候，输入图像可以用之前采集好的红外图像或者用PS工具生成一张图片，保存为.raw文件，在仿真输入的时候用binary工具将raw格式文件转换成txt文件，就可以启动仿真过程了，仿真结束后，生成的结果TXT，再通过txt2bin工具，将txt格式的数据转换成bin文件，再通过直接改后缀名的方式，将.bin改成.raw文件。用ImageJ工具打开source.raw和result.raw文件就可以直观地对比显示在图像窗口上了。并且对于算法参数、计算过程的调整，也是很快得到相应的输出结果。该过程相对传统的Matlab仿真和ModelSim联合仿真要方便很多，尤其是在算法调整和参数的调整的情况下，又要重复一遍Matlab仿真，再去ModelSim仿真的过程。但是该种方法对于红外图像算法原理的理解和FPGA逻辑实现图像算法的能力要求比较高。并且本文针对红外图像的仿真方法与传统的红外图像仿真方法，在适用范围上是一样的，对象都是红外图像的算法仿真。针对具体的算法模型，需要将算法分解成各计算步骤，然后针对各计算步骤进行数据仿真，所以对于其他文献[7]中不同的算法，比如弱小目标的背景的抑制，突出目标的增强算法等都是一样的仿真过程。
4. 结论
对于红外图像处理算法在FPGA的实现过程中，本文阐述了传统的仿真方法，先进行Matlab仿真，仿真效果达到的前提下，再进行定点化设计，指导FPGA进行逻辑设计，完成算法原理的实现，最后启动ModelSim仿真，而且仿真结果的正确评判标准是与Matlab仿真结果比对一致，不一致的话，要优化定点化过程，再进行仿真，重复直至结果一致。而本文的仿真方法基于ModelSim的可视化仿真，省去了上述繁琐的开发过程，直接将图像源文件转化后导入ModelSim仿真，算法处理完成后，转成图像结果文件进行比对，用可视化的方式评判图像经过算法处理之后是否达到算法原理期望达到的算法效果。同时如果算法未到达期望效果，通过调整参数、算法实现过程，以及追溯输入图像、写入、读出内存过程，判断图像算法计算过程中数据的正确与否。所以该方法与传统的红外图像仿真方法相比，评估算法效果以可视化显示输入、输出对比图差异性来达到。评估算法计算过程的正确性，同样可以追溯数据处理过程的每一步的正确性来达到。所以该仿真方法的仿真效果是与传统的方法一致的。但是开发过程缩减了和效率上大大提升了，开发周期短。尤其是在反复调参和优化过程中，显得更为明显和方便便捷。
-
![]()
图 1 超表面相关理论示意图：(a)磁导率μ和介电常数ε正负分类及其对应材料示意图；(b)广义斯涅尔定律示意图（其中左图为其二维形式，右图为其三维形式）[6-7]；(c)辅助理解广义斯涅尔定律的溺水者困境示意图[8]；(d)亚波长V型金属天线超表面阵列实现反常折射和反射示意图[9]；(e)推导PB相位原理的庞加莱球示意图[10]
Figure 1. Schematic diagram of metasurface correlation theory: (a) positive and negative classification of magnetic permeability and permittivity and schematic diagram of their corresponding materials; (b) Schematic diagram of Snell's law in a generalized sense(The left image shows its two-dimensional form, and the right image shows its three-dimensional form)[6-7]; (c) Schematic diagram of the drowning person's plight that aids in understanding Snell's law in general[8]; (d) Schematic diagram of parastatic refraction and reflection of subwavelength V-shaped metal antenna metasurface array[9]; (e) Schematic diagram of a Poincaré sphere from which the PB phase principle is derived[10]
![]()
图 2 微测辐射热计超表面结构类型：(a)方块状孔洞型；(b)圆柱状孔洞型；(c)花瓣状天线型；(d)方块状天线型；(e)圆柱状天线型；(f)十字状天线型
Figure 2. Microbolometer metasurface structure type: (a) Square shaped pore type; (b) Cylindrical hole type; (c) Petal shaped antenna type; (d) Square antenna type; (e) Cylindrical antenna type; (f) Cross shaped antenna type
![]()
图 3 几种超表面吸收结构及其结果：(a)左图为长波红外吸收共振超表面结构示意图；右图为超表面吸收器的反射光谱图[42]；(b)上图和中图分别为周期性超表面结构的俯视图和结构示意图；下图为光学谐振腔和表面等离子体对器件吸收的影响示意图[43]；(c)左图为红外宽带超表面吸收器结构示意图；右图为超表面吸收器测量（实心曲线）和仿真（虚线曲线）的吸收光谱响应图[44]；(d)左图为结合超表面的微测辐射热计结构示意图；右图为在300℃下进行真空退火前后的电压噪声图[45]；(e)左图为红玫瑰状超表面吸收器结构示意图；右图为相对于表面法线入射时角度在0°~45°之间变化所对应的吸收光谱图[46]
Figure 3. Several metasurface absorption structures and their result diagrams: (a) The left figure is a schematic diagram of the long-wave infrared absorption resonance metasurface structure; The right image shows the reflectance spectrum of the metasurface absorber[42]; (b) The top view and schematic diagram of the periodic metasurface structure are shown in the upper and middle figures, respectively; The figure below shows the influence of optical resonator and surface plasma on device absorption[43]; (c) The left figure is a schematic diagram of the structure of the infrared broadband metasurface absorber; The right image shows the absorption spectral response diagram of metasurface absorber measurement (solid curve) and simulation (dashed curve)[44]; (d) Top view and schematic diagram of the microbolometer structure combined with metasurface and middle figures, respectively; The figure on the right shows the voltage noise diagram before and after vacuum annealing at 300℃[45]; (e) The left figure is a schematic diagram of the structure of the red rose-shaped metasurface absorber; The right figure is the absorption spectrum corresponding to the change of angle between 0° to 45° relative to the surface normal[46]
![]()
图 4 几种超表面波长选择结构及其结果（1）：(a)上图为中红外多光谱超表面基本单元结构示意图；下图为宽度不同的超表面吸收器集成到微测辐射热计上的吸收光谱图[49]；(b)左上、右上、中图分别为偶极型电阻板、槽型电阻板及偶极-槽镜堆叠超表面吸收器结构示意图；下图为偶极型电阻板层（红）、槽型电阻板层（蓝）及偶极-槽镜堆叠结构（黑）的吸收光谱图[50]；(c)左图为多光谱波长选择性超表面吸收器及超表面单个单元结构示意图；右图为三种不同尺寸的超表面吸收器的光谱响应图[51]
Figure 4. Several metasurface wavelength selection structures and their results (1) : (a) The above figure is a schematic diagram of the basic unit structure of the mid-infrared multispectral metasurface; The figure below shows the absorption spectrum integrated into the microbolometer with metasurface absorbers of different widths[49]; (b) The upper left, upper right, and middle figures are the schematic diagram of the structure of dipole type resistance plate, slot type resistance plate and dipole-slot mirror stacked metasurface absorber; The figure below shows the absorption spectra of the dipole resistor plate layer (red), the slot resistor plate layer (blue) and the dipolar-slot mirror stack structure (black)[50]; (c) The figure on the left is a schematic diagram of the structure of a multispectral wavelength-selective metasurface absorber and a single unit of metasurface; The figure on the right shows the spectral response of three metasurface absorbers of different sizes[51]
![]()
图 5 几种超表面波长选择结构及其结果（2）：(a)左上图为超表面结构示意图；右上图为超表面单个单元结构示意图；左下图为超表面的光谱响应图；右下图为吸收峰值波长与超表面顶部金盘半径的关系图[52]；(b)上图为六边形阵列窄带超表面结构示意图，下图为集成到微测辐射热计中的宽带超表面结构示意图[53]；(c)左图为超表面集成到SixGeyO1-x-y红外微测辐射计的装置结构侧视图（左为单腔，右为双腔）；右图为单腔微测辐射计的响应率和探测率示意图[54]
Figure 5. Several metasurface wavelength selection structures and their results (2) : (a) The upper left figure is a schematic diagram of the metasurface structure; The upper right figure is a schematic diagram of the metasurface single element structure; The lower left figure shows the spectral response of the metasurface; The figure below on the right shows the relationship between the absorption peak wavelength and the radius of the gold disk at the top of the metasurface[52]; (b) The figure above is a schematic diagram of the narrowband metasurface structure of a hexagonal array, and the figure below is a schematic diagram of the broadband metasurface structure integrated into a microbolometer[53]; (c) The figure on the left shows a side view of the metasurface integrated into the SixGeyO1-x-y infrared microradiometer (single chamber on the left, double chamber on the right); The figure on the right is a schematic diagram of the response rate and detection rate of a single-cavity microradiometer[54]
![]()
图 6 几种超表面波长选择结构及其结果（3）：(a)左上，右上图分别为利用液晶调谐的吸收器截面图和在0 V（蓝色）和6 V（绿色）条件下液晶调谐吸收器的模拟（虚线）、测量（实线）反射光谱图；左下，右下图分别为为利用吸收腔压电调谐的吸收器截面图和不同腔体厚度值下的反射光谱图[55]；(b)上图为波长选择性测辐射热计示意图（底部为全视图，顶部为截面图）；下图为器件谐振波长与谐振器宽度(w)的关系图[57]；(c)左图为用于光谱和偏振检测的超表面集成微测辐射热计结构图；右下图为两种天线宽度不同的宽度超表面吸收器截面图及他们所对应的光谱吸收曲线图[58]
Figure 6. Several metasurface wavelength selection structures and their results (3) : (a) upper left and upper right figures are respectively the cross-section of the absorber tuned by liquid crystal and the simulation (dashed line) and measurement (solid line) reflection spectrum of the liquid crystal tuned absorber under 0 volt (blue) and 6 volts (green) conditions; The lower left and the lower right figures show the cross-section of the absorber tuned by piezoelectric tuning of the absorption cavity and the reflection spectrum under different cavity thickness values[55]; (b) Schematic diagram of wavelength-selective bolometer above (full view at the bottom and cross-sectional view at the top); The figure below shows the relationship between the resonant wavelength of the device and the width of the resonator (W)[57]; (c) The left image shows the structural diagram of a metasurface integrated microbolometer for spectral and polarization detection; The right image shows the cross-sectional view of the metasurface absorber with different widths of the two antennas and their corresponding spectral absorption curves[58]
-
[1] Veselago V G. The electrodynamics of substance with simultaneously negative values of ε and μ[J]. Physics-Uspekhi, 1968, 10: 509-514. DOI: 10.1070/PU1968v010n04ABEH003699
[2] Pendry J B. Negative refraction index makes perfect lens[J]. Phys. Rev. Lett. , 2000, 85: 3966-3969. DOI: 10.1103/PhysRevLett.85.3966
[3] Smith D R, Padilla W J, Vier D C, et al. Composite medium with simultaneously negative permeability and permittivity[J]. Phys. Rev. Lett, 2000, 84(18): 4184-4187. DOI: 10.1103/PhysRevLett.84.4184
[4] 罗先刚. 亚波长电磁学(上册)[M]. 北京: 科学出版社, 2017: 197-232. LUO Xiangang. Subwavelength Eectromagnetism (Volume 1)[M]. Beijing: Science Press, 2017: 197-232.
[5] 李荣真. 基于超表面结构的等离子体偏振器件的研究[D]. 合肥: 合肥工业大学, 2016. LI Rongzhen. Study of Plasma Polarization Devices Based on Metasurface Structures[D]. Hefei: Hefei University of Technology, 2016.
[6] YU N, Genevet P, Kats M, et al. Light propagation with phase discontinuities: generalized laws of reflection and refraction[J]. American Association for the Advancement of Science, 2011, 6054: 333-337.
[7] CHEN Houtong, Antoinette J Taylor, YU Nanfang. A review of metasurfaces: physics and applications[J/OL]. Optics, 2017, https://arxiv.org/abs/1605.07672 .
[8] YU Nanfang, Federico Capasso. Flat optics with designer metasurfaces[J]. Nature Materials, 2014, 13: 139-150. DOI: 10.1038/nmat3839
[9] Aieta F, Genevet P, Yu N, et al. Out-of-plane reflection and refraction of light by anisotropic optical antenna metasurfaces with phase discontinuities[J]. Nano Letters, 2012, 12(3): 1702-1706. Doi: 10.1021/nl300204s.
[10] Bomzon Z, Biener G, Kleiner V, et al. Space-variant Pancharatnam-Berry phase optical elements with computer-generated subwavelength gratings[J]. Optics Letters, 2002, 27(13): 1141-1143. DOI: 10.1364/OL.27.001141
[11] Peifer C, Grhic A. Metamaterial huygens' surfaces: tailoring wave fronts with reflectionless sheets[J]. Phys. Rev. Lett. , 2013(110): 197401.
[12] LUO X G. Principles of electromagnetic waves in metasurfaces[J]. Science China Physics, Mechanics & Astronomy, 2015, 58(9): 594201-594201.
[13] PU Mingbo, HU Chenggang, WANG Min, et al. Design principles for infrared wide-angle perfect absorber based on plasmonic structure[J]. Optics Express, 2011, 19(18): 17413-17420. DOI: 10.1364/OE.19.017413
[14] 彭华新, 周济, 崔铁军, 等. 超材料[M]. 北京: 中国铁道出版社, 2020. PENG Huaxin, ZHOU Ji, CUI Tiejun, et al. Metamaterial[M]. Beijing: China Railway Press, 2020.
[15] Meinzer N, Barnes W L, Hooper I R. Plasmonic meta-atoms and metasurfaces[J]. Nature Publishing Group, 2014, 8(12): 889-898.
[16] Aieta F, Genevet P, Kats M A, et al. Aberration-free ultrathin flat lenses and axicons at telecom wavelengths based on plasmonic metasurfaces[J]. Nano Letters, 2012, 12(9): 4932-4936. DOI: 10.1021/nl302516v
[17] LIN D, FAN P, Hasman E, et al. Dielectric gradient metasurface optical elements[J]. Science, 2014, 345(6194): 298-302. DOI: 10.1126/science.1253213
[18] Khorasaninejad M, SHI Z, ZHU A Y, et al. Achromatic metalens over 60 nm bandwidth in the visible and metalens with reverse chromatic dispersion[J]. Nano Letters, 2017, 17(3): 1819-1824. DOI: 10.1021/acs.nanolett.6b05137
[19] CHEN K, FENG Y, Monticone F, et al. A reconfigurable active Huygens' metalens[J]. Advanced Materials, 2017, 29(17): 1606422. DOI: 10.1002/adma.201606422
[20] ZHENG G, Muehlenbernd H, Kenney M, et al. Metasurface holograms reaching 80% efficiency [J]. Nature Nanotechnology, 2015, 10(4): 308-312. DOI: 10.1038/nnano.2015.2
[21] LEE G Y, YOON G, LEE S Y, et al. Complete amplitude and phase control of light using broadband holographic metasurfaces[J]. Nanoscale, 2018, 10(9): 4237-4245. DOI: 10.1039/C7NR07154J
[22] NI Xingjie, Alexander V Kildishev, Vladimir M Shalaev. Metasurface holograms for visible light[J]. Nature Communications, 2013, 4: 2807. DOI: 10.1038/ncomms3807
[23] Kuznetsov S A, Astafev M A, Beruete M, et al. Planar holographic metasurfaces for Terahertz focusing[J]. Sci. Rep. , 2015, 5: 7738. DOI: 10.1038/srep07738
[24] Yuk T I, CHEUNG S W, ZHU H L. Mechanically pattern reconfigurable antenna using metasurface[J]. IET Microwaves, Antennas & Propagation, 2015, 9(12): 1331-1336.
[25] ZHU H L, CHEUNG S W, LIU X H, et al. Design of polarization reconfigurable antenna using metasurface[J]. IEEE Transactions on Antennas and Propagation, 2014, 62(6): 2891-2898. DOI: 10.1109/TAP.2014.2310209
[26] NI C, CHEN M, ZHANG Z, et al. Design of frequency and polarization reconfigurable antenna based on the polarization conversion metasurface[J]. IEEE Antennas and Wireless Propagation Letters, 2017, 17(1): 78-81.
[27] WAN X, ZHANG L, JIA S L, et al. Horn antenna with reconfigurable beam-refraction and polarization based on anisotropic huygens metasurface[J]. IEEE Transactions on Antennas and Propagation, 2017, 65(9): 4427-4434. DOI: 10.1109/TAP.2017.2722829
[28] CAI H, CHEN S, ZOU C, et al. Multifunctional hybrid metasurfaces for dynamic tuning of terahertz waves[J]. Adv. Opt. Mater. , 2018, 6(14): 1800257. DOI: 10.1002/adom.201800257
[29] Tasolamprou A C, Koulouklidis A D, Daskalaki C, et al. Experimental demonstration of ultrafast thz modulation in a graphene-based thin film absorber through negative photoinduced conductivity[J]. ACS Author Choice, 2019, 6(3): 720-727.
[30] ZHAO X, WANG Y, Schalch J, et al. Optically modulated ultra-broadband all-silicon metamaterial terahertz absorbers[J]. Acs Photonics, 2019, 6(4): 830-837. DOI: 10.1021/acsphotonics.8b01644
[31] CONG L, Singh R. Spatiotemporal dielectric metasurfaces for unidirectional propagation and reconfigurable steering of terahertz beams[J]. Advanced Materials, 2020, 32(28): 2001418. DOI: 10.1002/adma.202001418
[32] Mousavi S H, Khanikaev A B, Neuner B, et al. Suppression of long-range collective effects in meta-surfaces formed by plasmonic antenna pairs[J]. Optics Express, 2011, 19(22): 22142-22155. DOI: 10.1364/OE.19.022142
[33] ZHANG J, MEI Z, ZHANG W, et al. An ultrathin directional carpet cloak based on generalized snell's law[J]. Applied Physics Letters, 2013, 103(15): 1780.
[34] LIU S, XU H X, ZHANG H C, et al. Tunable ultrathin mantle cloak via varactor-diode-loaded metasurface[J]. Optics Express, 2014, 22(11): 13403-13417. DOI: 10.1364/OE.22.013403
[35] NI Xingjie, WONG Zijing, Michael M, et al. An ultrathin invisibility skin cloak for visible light[J]. Science, 2015, 349(6254): 1310-1314. DOI: 10.1126/science.aac9411
[36] TAN X, ZHANG H, LI J, et al. Non-dispersive infrared multi-gas sensing via nanoantenna integrated narrowband detectors[J]. Nature Communications, 2020, 11(1): 5245. DOI: 10.1038/s41467-020-19085-1
[37] 苏君红. 红外材料与探测技术[M]. 杭州: 浙江科学技术出版社, 2015. SU Junhong. Infrared Materials and Detection Technology[M]. Hangzhou: Zhejiang Science and Technology Press, 2015.
[38] Dereniak L Eustace. Infrared Detectors and Systems[M]. Hoboken: Wiley, 1996.
[39] 邓洪朗, 周绍林, 岑冠廷. 红外和太赫兹电磁吸收超表面研究进展[J]. 光电工程, 2019, 46(8): 13. DENG Honglang, ZHOU Shaolin, CEN Guanting. Progress in infrared and THz electromagnetic absorption metasurface[J]. Photoelectric Engineering, 2019, 46(8): 13.
[40] 徐天宇. 微纳结构超表面增强吸收研究[D]. 长春: 长春理工大学, 2019. XU Tianyu. Ultrasurface-Enhanced Absorption Study of Micro-Nano Structures[D]. Changchun: Changchun University of Science and Technology, 2019.
[41] Maier T, Brückl H. Wavelength-tunable microbolometers with metamaterial absorbers[J]. Optics Letters, 2009, 34(19): 3012-3014. DOI: 10.1364/OL.34.003012
[42] Smith E M, Nath J, Ginn J, et al. Responsivity improvements for a vanadium oxide microbolometer using subwavelength resonant absorbers[C]// SPIE Defense + Security, 2016, Doi: 10.1117/12.2223954.
[43] LI Q, YU B Q, LI Z F. Surface plasmon-enhanced dual-band infrared absorber for VOx-based microbolometer application[J]. Chinese Physics B, 2017(8): 269-274.
[44] JUNG J Y, SONG K, Choi J H, et al. Infrared broadband metasurface absorber for reducing the thermal mass of a microbolometer[J]. Scientific Reports, 2017, 7(1): 430. DOI: 10.1038/s41598-017-00586-x
[45] Alkorjia O, Abdullah A, Koppula A. Metasurface based uncooled microbolometer with high fill factor[C]// International Conference on Solid-State Sensors, Actuators and Microsystems & Eurosensors, XXXIII, 2019: 2126-2129.
[46] Swett D W. Near zero index perfect metasurface absorber using inverted conformal mapping[J]. Scientific Reports, 2020, 10(1): 9731. DOI: 10.1038/s41598-020-66476-x
[47] Joseph J Talghader, Anand S Gawarikar, Ryan P Shea. Spectral selectivity in infrared thermal detection[J]. Light: Science & Applications, 2012, 1(8): e24-e24.
[48] Thomas Maier, Hubert Brückl. Wavelength-tunable microbolometers with metamaterial absorbers[J]. Optics Letters, 2009, 34(19): 3012-3014. DOI: 10.1364/OL.34.003012
[49] Maier T, Brueckl H. Multispectral microbolometers for the midinfrared[J]. Optics Letters, 2010, 35(22): 3766-3768. DOI: 10.1364/OL.35.003766
[50] Kim H, Neikirk D P, Andresen B F, et al. Three-dimensional dual-band stacked microbolometer design using resistive dipoles and slots[C]//Proceedings of SPIE - The International Society for Optical Engineering, 2013, 8704: 19.
[51] JUNG J Y, LEE J, CHOI D G, et al. Wavelength-selective infrared metasurface absorber for multispectral thermal detection[J]. IEEE Photonics Journal, 2015, 7(6): 1-11.
[52] DU K, LI Q, ZHANG W, et al. Wavelength and thermal distribution selectable microbolometers based on metamaterial absorbers[J]. IEEE Photonics Journal, 2015, 7(3): 1-8.
[53] LIU Tao, QU Chuang, Mahmoud Almasri, et al. Design and analysis of frequency-selective surface enabled microbolometers[C]//Infrared Technology and Applications XLII. SPIE, 2016, 9819: 487-494.
[54] LIU T, Abdullah A A, Alkorjia O, et al. Device architecture for metasurface integrated Uncooled SixGeyO1-x-y Infrared Microbolometers (Conference Presentation)[C]// Infrared Technology and Applications XLV, 2019, 11002: 372-378.
[55] Creazzo T A, Zablocki M J, Zaman L, et al. Frequency selective infrared optical filters for micro-bolometers [C]// SPIE Defense + Security, 2017, 10194: 611-618.
[56] Gallacher K, Millar R W, Giliberti V, et al. Mid-infrared n-Ge on Si plasmonic based microbolometer sensors[C]//IEEE International Conference on Group IV Photonics, 2017: 3-4.
[57] DAO T D, Doan A T, Ishii S, et al. MEMS-based wavelength-selective bolometers[J]. Micromachines, 2019, 10(6): 416. DOI: 10.3390/mi10060416
[58] JIANG S, LI J, LI J, et al. Metamaterial microbolometers for multi-spectral infrared polarization imaging[J]. Optics Express, 2022, 30(6): 9065-9087. DOI: 10.1364/OE.452981
下载:
计量
- 文章访问数: 297
- HTML全文浏览量: 66
- PDF下载量: 146
