[1] Watts C M, Liu X L, Padilla W J. Metamaterial electromagnetic wave absorbers[J]. Advanced Materials, 24, OP98-OP120(2012).

[2] Dickey M D. Stretchable and soft electronics using liquid metals[J]. Advanced Materials, 29, 1606425(2017).

[3] Yu P, Besteiro L V, Huang Y J et al. Broadband metamaterial absorbers[J]. Advanced Optical Materials, 7, 1800995(2019).

[4] Li W, Valentine J. Metamaterial perfect absorber based hot electron photodetection[J]. Nano Letters, 14, 3510-3514(2014).

[5] Pfeiffer C, Grbic A. Metamaterial Huygens' surfaces: tailoring wave fronts with reflectionless sheets[J]. Physical Review Letters, 110, 197401(2013).

[6] Yang X, Zhao X, Yang K et al. Biomedical applications of terahertz spectroscopy and imaging[J]. Trends in Biotechnology, 34, 810-824(2016).

[7] Li A B, Singh S, Sievenpiper D. Metasurfaces and their applications[J]. Nanophotonics, 7, 989-1011(2018).

[8] Hedayati M K, Faupel F, Elbahri M. Review of plasmonic nanocomposite metamaterial absorber[J]. Materials, 7, 1221-1248(2014).

[9] Chen H T, O'Hara J F, Azad A K et al. Manipulation of terahertz radiation using metamaterials[J]. Laser & Photonics Reviews, 5, 513-533(2011).

[10] Ahmadivand A, Gerislioglu B, Ahuja R et al. Terahertz plasmonics: the rise of toroidal metadevices towards immunobiosensings[J]. Materials Today, 32, 108-130(2020).

[11] Naik G V, Shalaev V M, Boltasseva A. Alternative plasmonic materials: beyond gold and silver[J]. Advanced Materials, 25, 3264-3294(2013).

[12] Surjadi J U, Gao L B, Du H F et al. Mechanical metamaterials and their engineering applications[J]. Advanced Engineering Materials, 21, 1800864(2019).

[13] Shen D G, Wu G R, Suk H I. Deep learning in medical image analysis[J]. Annual Review of Biomedical Engineering, 19, 221-248(2017).

[14] Schmidhuber J. Deep learning in neural networks: an overview[J]. Neural Networks, 61, 85-117(2015).

[15] LeCun Y, Bengio Y, Hinton G. Deep learning[J]. Nature, 521, 436-444(2015).

[16] Wu Z H, Pan S R, Chen F W et al. A comprehensive survey on graph neural networks[J]. IEEE Transactions on Neural Networks and Learning Systems, 32, 4-24(2021).

[17] Naik G V, Liu J J, Kildishev A V et al. Demonstration of Al∶ZnO as a plasmonic component for near-infrared metamaterials[J]. Proceedings of the National Academy of Sciences of the United States of America, 109, 8834-8838(2012).

[18] Malkiel I, Mrejen M, Nagler A et al. Plasmonic nanostructure design and characterization via deep learning[J]. Light: Science & Applications, 7, 1-8(2018).

[19] Ma W, Cheng F, Xu Y H et al. Probabilistic representation and inverse design of metamaterials based on a deep generative model with semi-supervised learning strategy[J]. Advanced Materials, 31, e1901111(2019).

[20] Hou J J, Lin H, Xu W L et al. Customized inverse design of metamaterial absorber based on target-driven deep learning method[J]. IEEE Access, 8, 211849-211859(2020).

[21] Tian Y Z. Inverse design method of electromagnetic metamaterials based on machine learning[D], 30-31(2021).

[22] Tang Z M. Study on quantitative detection method of stabilizer based on terahertz spectroscopy technology[D](2022).

[23] Yang J P. Research on terahertz biosensor based on resonant structure[D](2022).

[24] Yang J P, Wang M C, Deng H et al. Dual-band terahertz sensor based on metamaterial absorber integrated microfluidic[J]. Acta Optica Sinica, 41, 2328001(2021).

[25] Li D M, Yuan S, Yang R C et al. Dynamical optical-controlled multi-state THz metamaterial absorber[J]. Acta Optica Sinica, 40, 0816001(2020).

[26] Ma L M, Xu H, Liu Y H et al. Broadband terahertz absorber based on graphene metamaterial[J]. Acta Optica Sinica, 42, 0923001(2022).

[27] Zhu H L, Zhang Y, Ye L F et al. Dual-control and tunable broadband terahertz absorber based on graphene-vanadium dioxide[J]. Acta Optica Sinica, 42, 1423002(2022).