[1] |
Zhu, X. L. et al. Plasmonic colour laser printing. Nature Nanotechnology 11, 325-329 (2016). doi: 10.1038/nnano.2015.285 |
[2] |
Kerse, C. et al. Ablation-cooled material removal with ultrafast bursts of pulses. Nature 537, 84-88 (2016). doi: 10.1038/nature18619 |
[3] |
Jeon, H. et al. Directing cell migration and organization via nanocrater-patterned cell-repellent interfaces. Nature Materials 14, 918-923 (2015). doi: 10.1038/nmat4342 |
[4] |
Sun, K. et al. Three-dimensional direct lithography of stable perovskite nanocrystals in glass. Science 375, 307-310 (2022). doi: 10.1126/science.abj2691 |
[5] |
Tan, D. Z., Zhang, B. & Qiu, J. R. Ultrafast laser direct writing in glass: Thermal accumulation engineering and applications. Laser & Photonics Reviews 15, 2000455 (2021). |
[6] |
Wang, J. S. et al. Laser machining fundamentals: micro, Nano, atomic and close-to-atomic scales. International Journal of Extreme Manufacturing 5, 012005 (2023). doi: 10.1088/2631-7990/acb134 |
[7] |
Malinauskas, M. et al. Ultrafast laser processing of materials: from science to industry. Light: Science & Applications 5, e16133 (2016). |
[8] |
Okamoto, Y. et al. High-quality micro-shape fabrication of monocrystalline diamond by nanosecond pulsed laser and acid cleaning. International Journal of Extreme Manufacturing 4, 025301 (2022). doi: 10.1088/2631-7990/ac5a6a |
[9] |
Wokosin, D. L. et al. All-solid-state ultrafast lasers facilitate multiphoton excitation fluorescence imaging. IEEE Journal of Selected Topics in Quantum Electronics 2, 1051-1065 (1996). doi: 10.1109/2944.577337 |
[10] |
Davis, K. M. et al. Writing waveguides in glass with a femtosecond laser. Optics Letters 21, 1729-1731 (1996). doi: 10.1364/OL.21.001729 |
[11] |
Zhang, Y. X. et al. Femtosecond laser direct writing of functional stimulus-responsive structures and applications. International Journal of Extreme Manufacturing 5, 042012 (2023). doi: 10.1088/2631-7990/acf798 |
[12] |
Zhang, D. S., Liu, R. J. & Li, Z. G. Irregular LIPSS produced on metals by single linearly polarized femtosecond laser. International Journal of Extreme Manufacturing 4, 015102 (2022). doi: 10.1088/2631-7990/ac376c |
[13] |
Geng, J. et al. Quasicylindrical waves for ordered nanostructuring. Nano Letters 22, 9658-9663 (2022). doi: 10.1021/acs.nanolett.2c03851 |
[14] |
Geng, J. et al. Surface plasmons interference nanogratings: wafer-scale laser direct structuring in seconds. Light: Science & Applications 11, 189 (2022). |
[15] |
Kawabata, S. et al. Two-dimensional laser-induced periodic surface structures formed on crystalline silicon by GHz burst mode femtosecond laser pulses. International Journal of Extreme Manufacturing 5, 015004 (2023). doi: 10.1088/2631-7990/acb133 |
[16] |
Saha, S. K. et al. Radiopaque resists for two-photon lithography to enable submicron 3D imaging of polymer parts via X-ray computed tomography. ACS Applied Materials & Interfaces 10, 1164-1172 (2018). |
[17] |
Mayer, F. et al. 3D fluorescence-based security features by 3D laser lithography. Advanced Materials Technologies 2, 1700212 (2017). doi: 10.1002/admt.201700212 |
[18] |
Hahn, V. et al. Two-step absorption instead of two-photon absorption in 3D nanoprinting. Nature Photonics 15, 932-938 (2021). doi: 10.1038/s41566-021-00906-8 |
[19] |
Lamont, A. C. et al. Direct laser writing of a titanium dioxide-laden retinal cone phantom for adaptive optics-optical coherence tomography. Optical Materials Express 10, 2757-2767 (2020). doi: 10.1364/OME.400450 |
[20] |
Lee, X. Y. et al. Automated detection of part quality during two-photon lithography via deep learning. Additive Manufacturing 36, 101444 (2020). doi: 10.1016/j.addma.2020.101444 |
[21] |
Hasegawa, S. et al. In-process monitoring in laser grooving with line-shaped femtosecond pulses using optical coherence tomography. Light: Advanced Manufacturing 3, 33 (2022). |
[22] |
Zvagelsky, R. et al. Towards in-situ diagnostics of multi-photon 3d laser printing using optical coherence tomography. Light: Advanced Manufacturing 3, 39 (2022). |
[23] |
Baldacchini, T. & Zadoyan, R. In situ and real time monitoring of two-photon polymerization using broadband coherent anti-stokes Raman scattering microscopy. Optics Express 18, 19219-19231 (2010). doi: 10.1364/OE.18.019219 |
[24] |
Zong, W. J. et al. Miniature two-photon microscopy for enlarged field-of-view, multi-plane and long-term brain imaging. Nature Methods 18, 46-49 (2021). doi: 10.1038/s41592-020-01024-z |
[25] |
Yao, J. et al. Exploiting the potential of commercial objectives to extend the field of view of two-photon microscopy by adaptive optics. Optics Letters 47, 989-992 (2022). doi: 10.1364/OL.450973 |
[26] |
Zheng, G. A., Horstmeyer, R. & Yang, C. Wide-field, high-resolution Fourier ptychographic microscopy. Nature Photonics 7, 739-745 (2013). doi: 10.1038/nphoton.2013.187 |
[27] |
Zheng, G. A. et al. Concept, implementations and applications of Fourier ptychography. Nature Reviews Physics 3, 207-223 (2021). doi: 10.1038/s42254-021-00280-y |
[28] |
Yuan, X., Brady, D. J. & Katsaggelos, A. K. Snapshot compressive imaging: theory, algorithms, and applications. IEEE Signal Processing Magazine 38, 65-88 (2021). |
[29] |
Dou, Y. F. et al. Coded aperture temporal compressive digital holographic microscopy. Optics Letters 48, 5427-5430 (2023). doi: 10.1364/OL.503788 |
[30] |
Wang, P. et al. Full-resolution and full-dynamic-range coded aperture compressive temporal imaging. Optics Letters 48, 4813-4816 (2023). doi: 10.1364/OL.499735 |
[31] |
Chen, Z. Y. et al. Physics-driven deep learning enables temporal compressive coherent diffraction imaging. Optica 9, 677-680 (2022). doi: 10.1364/OPTICA.454582 |
[32] |
Wang, L. S. et al. Spatial-temporal transformer for video snapshot compressive imaging. IEEE Transactions on Pattern Analysis and Machine Intelligence 45, 9072-9089 (2023). |
[33] |
Meng, Z. Y., Yuan, X. & Jalali, S. Deep unfolding for snapshot compressive imaging. International Journal of Computer Vision 131, 2933-2958 (2023). doi: 10.1007/s11263-023-01844-4 |
[34] |
Wang, L. S., Cao, M. & Yuan, X. EfficientSCI: Densely connected network with space-time factorization for large-scale video snapshot compressive imaging. 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Vancouver, BC, Canada: IEEE, 2023, 18477-18486. |
[35] |
Yuan, X. et al. Plug-and-play algorithms for video snapshot compressive imaging. IEEE Transactions on Pattern Analysis and Machine Intelligence 44, 7093-7111 (2022). doi: 10.1109/TPAMI.2021.3099035 |
[36] |
Yuan, X. Generalized alternating projection based total variation minimization for compressive sensing. 2016 IEEE International Conference on Image Processing (ICIP). Phoenix, AZ, USA: IEEE, 2016, 2539-2543. |
[37] |
Qiao, M. et al. Deep learning for video compressive sensing. APL Photonics 5, 030801 (2020). doi: 10.1063/1.5140721 |
[38] |
Cheng, Z. H. et al. Recurrent neural networks for snapshot compressive imaging. IEEE Transactions on Pattern Analysis and Machine Intelligence 45, 2264-2281 (2023). doi: 10.1109/TPAMI.2022.3161934 |
[39] |
Gao, L. et al. Single-shot compressed ultrafast photography at one hundred billion frames per second. Nature 516, 74-77 (2014). doi: 10.1038/nature14005 |
[40] |
Liu, X. L. et al. Single-shot compressed optical-streaking ultra-high-speed photography. Optics Letters 44, 1387-1390 (2019). doi: 10.1364/OL.44.001387 |
[41] |
Wang, P., Liang, J. Y. & Wang, L. V. Single-shot ultrafast imaging attaining 70 trillion frames per second. Nature Communications 11, 2091 (2020). doi: 10.1038/s41467-020-15745-4 |
[42] |
Zhu, L. R. et al. Space-and intensity-constrained reconstruction for compressed ultrafast photography. Optica 3, 694-697 (2016). doi: 10.1364/OPTICA.3.000694 |
[43] |
Lai, Y. M. et al. Single-shot ultraviolet compressed ultrafast photography. Laser & Photonics Reviews 14, 2000122 (2020). |
[44] |
Ma, Y. Y., Feng, X. H. & Gao, L. Deep-learning-based image reconstruction for compressed ultrafast photography. Optics Letters 45, 4400-4403 (2020). doi: 10.1364/OL.397717 |
[45] |
Lu, Y. et al. Compressed ultrafast spectral-temporal photography. Physical Review Letters 122, 193904 (2019). doi: 10.1103/PhysRevLett.122.193904 |
[46] |
Kingma, D. P. & Ba, L. J. Adam: A method for stochastic optimization. International Conference on Learning Representations. San Diego: ICLR, 2015. |
[47] |
Qiao, M. et al. Snapshot coherence tomographic imaging. IEEE Transactions on Computational Imaging 7, 624-637 (2021). doi: 10.1109/TCI.2021.3089828 |
[48] |
Wang, L. S. et al. Snapshot spectral compressive imaging reconstruction using convolution and contextual transformer. Photonics Research 10, 1848-1858 (2022). doi: 10.1364/PRJ.458231 |
[49] |
Wang, X. D., Yuan, X. & Shi, L. P. Optical coherence tomography—in situ and high-speed 3d imaging for laser materials processing. Light: Science & Applications 11, 280 (2022). |
[50] |
Geng, J. et al. High-speed laser writing of structural colors for full-color inkless printing. Nature Communications 14, 565 (2023). doi: 10.1038/s41467-023-36275-9 |