[47] L. J. Phillips, A. M. Rashed, R. E. Treharne, J. Kay, P. Yates, I. Z. Mitrovic, A. Weerakkody, S. Hall, and K. Durose. Dispersion relation data for methylammonium lead triiodide perovskite deposited on a (100) silicon wafer using a two-step vapour-phase reaction process. Data in Brief, 5:926–928, 2015.
[48] A. Polman and H. A. Atwater. Photonic design principles for ultrahigh-efficiency photovoltaics. Nature Materials, 11(3):174-177, 2012.
[49] M. J. D. Powell. An efficient method for finding the minimum of a function of several variables without calculating derivatives. The Computer Journal, 7(2):155-162, 1964.
[50] A. D. Rakić and M. L. Majewski. Modeling the optical dielectric function of GaAs and AlAs: Extension of Adachi's model. Journal of Applied Physics, 80(10):5909-5914, 1996.
[51] A. D. Rakic, A. B. Djurisic, J. M. Elazar, and M. L. Majewski. Optical properties of metallic films for vertical-cavity optoelectronic devices. Applied Optics, 37(22):5271-5283, 1998.
[52] R. Ramakrishnan, P. O. Dral, M. Rupp, and O. A. von Lilienfeld. Quantum chemistry structures and properties of 134 kilo molecules. Scientific Data, 1(1):1-7, 2014.
[53] L. M. Rios and N. V. Sahinidis. Derivative-free optimization: a review of algorithms and comparison of software implementations. Journal of Global Optimization, 56:1247-1293, 2013.
[54] B. Sanchez-Lengeling and A. Aspuru-Guzik. Inverse molecular design using machine learning: Generative models for matter engineering. Science, 361(6400):360-365, 2018.
[55] C. Schinke, P. C. Peest, J. Schmidt, R. Brendel, K. Bothe, M. R. Vogt, I. Kröger, S. Winter, A. Schirmacher, S. Lim, H. T. Nguyen, and D. MacDonald. Uncertainty analysis for the coefficient of band-to-band absorption of crystalline silicon. AIP Advances, 5(6):067168, 2015.
[56] M. F. Schubert, A. K. C. Cheung, I. A. D. Williamson, A. Spyra, and D. H. Alexander. Inverse design of photonic devices with strict foundry fabrication constraints. ACS Photonics, 9(7): 2327-2336, 2022.
[57] K. Šehić, A. Gramfort, J. Salmon, and L. Nardi. LassoBench: A high-dimensional hyperparameter optimization benchmark suite for Lasso. In Proceedings of the International Conference on Automated Machine Learning (AutoML-Conf), Baltimore, Maryland, USA, 2022.
[58] E. Shkondin, O. Takayama, M. E. A. Panah, P. Liu, P. V. Larsen, M. D. Mar, F. Jensen, and A. V. Lavrinenko. Large-scale high aspect ratio Al-doped ZnO nanopillars arrays as anisotropic metamaterials. Optical Materials Express, 7(5):1606-1627, 2017.
[59] W. Shockley and H. J. Queisser. Detailed balance limit of efficiency of p-n junction solar cells. Journal of Applied Physics, 32(3):510-519, 1961.
[60] R. H. Siddique, G. Gomard, and H. Holscher. The role of random nanostructures for the omnidirectional anti-reflection properties of the glasswing butterfly. Nature Communications, 6 (1):6909, 2015.
[61] T. Siefke, S. Kroker, K. Pfeiffer, O. Puffky, K. Dietrich, D. Franta, I. Ohlidal, A. Szeghalmi, E.-B. Kley, and A. Tünnermann. Materials pushing the application limits of wire grid polarizers further into the deep ultraviolet spectral range. Advanced Optical Materials, 4(11):1780-1786, 2016.
[62] S. So, T. Badloe, J. Noh, J. Bravo-Abad, and J. Rho. Deep learning enabled inverse design in nanophotonics. Nanophotonics, 9(5):1041–1057, 2020.
[63] D. G. Stavenga, S. Foletti, G. Palasantzas, and K. Arikawa. Light on the moth-eye corneal nipple array of butterflies. Proceedings of the Royal Society B: Biological Sciences, 273(1587): 661-667, 2006.
[64] R. Storn and K. Price. Differential evolution – a simple and efficient heuristic for global optimization over continuous spaces. Journal of Global Optimization, 11(4):341–359, 1997.