Publications

Li, W., H. Barati Sedeh, D. Tsvetkov, W. J. Padilla, S. Ren, J. Malof, and N. M. Litchinitser. “Machine Learning for Engineering Meta-Atoms with Tailored Multipolar Resonances.” Laser and Photonics Reviews 18, no. 7 (July 1, 2024). https://doi.org/10.1002/lpor.202300855.

Schulz, S. A., R. F. Oulton, M. Kenney, A. Alù, I. Staude, A. Bashiri, Z. Fedorova, et al. “Roadmap on photonic metasurfaces.” Applied Physics Letters 124, no. 26 (June 24, 2024). https://doi.org/10.1063/5.0204694.

Rozman, N., K. Fan, and W. J. Padilla. “Symmetry-Broken High-Q Terahertz Quasi-Bound States in the Continuum.” ACS Photonics 11, no. 5 (May 15, 2024): 1893–1900. https://doi.org/10.1021/acsphotonics.3c01848.

Peng, R., S. Ren, J. Malof, and W. J. Padilla. “Transfer learning for metamaterial design and simulation.” Nanophotonics 13, no. 13 (May 3, 2024): 2323–34. https://doi.org/10.1515/nanoph-2023-0691.

Ma, H., A. B. Evlyukhin, A. E. Miroshnichenko, F. Zhu, S. Duan, J. Wu, C. Zhang, et al. “Extremely Thin Perfect Absorber by Generalized Multipole Bianisotropic Effect.” Advanced Optical Materials 12, no. 7 (March 5, 2024). https://doi.org/10.1002/adom.202301968.

Padilla, W. J., Y. Deng, O. Khatib, and V. Tarokh. “Fundamental absorption bandwidth to thickness limit for transparent homogeneous layers.” Nanophotonics, January 1, 2024. https://doi.org/10.1515/nanoph-2023-0920.

Leitenstorfer, A., A. S. Moskalenko, T. Kampfrath, J. Kono, E. Castro-Camus, K. Peng, N. Qureshi, et al. “The 2023 terahertz science and technology roadmap.” Journal of Physics D: Applied Physics 56, no. 22 (June 1, 2023). https://doi.org/10.1088/1361-6463/acbe4c.

Huang, L., L. Xu, D. A. Powell, W. J. Padilla, and A. E. Miroshnichenko. “Resonant leaky modes in all-dielectric metasystems: Fundamentals and applications.” Physics Reports 1008 (April 5, 2023): 1–66. https://doi.org/10.1016/j.physrep.2023.01.001.

Khatib, O., S. Ren, J. Malof, and W. J. Padilla. “Informed Deep Learning in Metamaterials.” In 2023 International Applied Computational Electromagnetics Society Symposium, ACES-Monterey 2023, 2023. https://doi.org/10.23919/ACES57841.2023.10114734.

Li, W., H. B. Sedeh, W. J. Padilla, J. Malof, and N. M. Litchinitser. “Mie Resonance-based Meta-atom Design with Machine Learning Method.” In 2023 Conference on Lasers and Electro-Optics, CLEO 2023, 2023.

Li, W., H. B. Sedeh, W. J. Padilla, J. Malof, and N. M. Litchinitser. “Multipolar Resonance Engineering Using Machine Learning.” In International Conference on Metamaterials, Photonic Crystals and Plasmonics, 1175, 2023.

Malof, J. M., S. Ren, and W. J. Padilla. “Forward and Inverse Design of Artificial Electromagnetic Materials.” In Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning, 345–70, 2023. https://doi.org/10.1002/9781119853923.ch11.

Fan, K., J. Q. Yang, Y. C. Xu, J. Wu, C. Zhang, D. C. Zhan, B. Jin, and W. J. Padilla. “Normalization flows for designing metasurfaces.” In International Conference on Metamaterials, Photonic Crystals and Plasmonics, 1170–71, 2023.

Li, W., H. B. Sedeh, W. J. Padilla, J. Malof, and N. M. Litchinitser. “Mie Resonance-based Meta-atom Design with Machine Learning Method.” In CLEO: Science and Innovations, CLEO:S and I 2023, 2023. https://doi.org/10.1364/CLEO_AT.2023.SW4P.5.

Padilla, W. J., and K. Fan. “Transparent phase dielectric metasurfaces.” In All-Dielectric Nanophotonics, 287–328, 2023. https://doi.org/10.1016/B978-0-32-395195-1.00015-6.

Deng, Y., S. Ren, J. Malof, and W. J. Padilla. “Deep inverse photonic design: A tutorial.” Photonics and Nanostructures - Fundamentals and Applications 52 (December 1, 2022). https://doi.org/10.1016/j.photonics.2022.101070.

Staude, I., H. Chen, A. Miroshnichenko, J. Takahara, and W. J. Padilla. “Metasurfaces for photonic devices.” Journal of Applied Physics 132, no. 19 (November 21, 2022). https://doi.org/10.1063/5.0131810.

Fan, K., R. D. Averitt, and W. J. Padilla. “Active and tunable nanophotonic metamaterials.” Nanophotonics 11, no. 17 (September 2, 2022): 3769–3803. https://doi.org/10.1515/nanoph-2022-0188.

Fan, K., V. Stenger, and W. J. Padilla. “Pyroelectric metamaterial millimeter-wave detector.” Applied Physics Letters 121, no. 2 (July 11, 2022). https://doi.org/10.1063/5.0094201.

Khatib, O., S. Ren, J. Malof, and W. J. Padilla. “Learning the Physics of All-Dielectric Metamaterials with Deep Lorentz Neural Networks.” Advanced Optical Materials 10, no. 13 (July 1, 2022). https://doi.org/10.1002/adom.202200097.

Ren, Simiao, Ashwin Mahendra, Omar Khatib, Yang Deng, Willie J. Padilla, and Jordan M. Malof. “Inverse deep learning methods and benchmarks for artificial electromagnetic material design.” Nanoscale 14, no. 10 (March 2022): 3958–69. https://doi.org/10.1039/d1nr08346e.

Padilla, W. J., and R. D. Averitt. “Imaging with metamaterials.” Nature Reviews Physics 4, no. 2 (February 1, 2022): 85–100. https://doi.org/10.1038/s42254-021-00394-3.

Dong, J., S. Ren, Y. Deng, O. Khatib, J. Malof, M. Soltani, W. Padilla, and V. Tarokh. “BLASCHKE PRODUCT NEURAL NETWORK (BPNN): A PHYSICS-INFUSED NEURAL NETWORK FOR PHASE RETRIEVAL OF MEROMORPHIC FUNCTIONS.” In ICLR 2022 - 10th International Conference on Learning Representations, 2022.

Padilla, W. J. “Deep Learning Metamaterials.” In International Conference on Metamaterials, Photonic Crystals and Plasmonics, 543, 2022.

Khatib, O., D. Gu, J. Smith, W. R. Deal, W. J. Padilla, and S. C. Reising. “Planar Metamaterial Absorbers for Calibration of Microwave Radiometers for Atmospheric Remote Sensing.” In International Geoscience and Remote Sensing Symposium (IGARSS), 2022-July:7212–17, 2022. https://doi.org/10.1109/IGARSS46834.2022.9884105.