Measuring complex refractive index through deep-learning-enabled optical reflectometry

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dc.citation.articleNumber025025en_US
dc.citation.issueNumber2en_US
dc.citation.journalTitle2D Materialsen_US
dc.citation.volumeNumber10en_US
dc.contributor.authorWang, Ziyangen_US
dc.contributor.authorLin, Yuxuan Cosmien_US
dc.contributor.authorZhang, Kunyanen_US
dc.contributor.authorWu, Wenjingen_US
dc.contributor.authorHuang, Shengxien_US
dc.date.accessioned2023-05-02T18:37:01Zen_US
dc.date.available2023-05-02T18:37:01Zen_US
dc.date.issued2023en_US
dc.description.abstractOptical spectroscopy is indispensable for research and development in nanoscience and nanotechnology, microelectronics, energy, and advanced manufacturing. Advanced optical spectroscopy tools often require both specifically designed high-end instrumentation and intricate data analysis techniques. Beyond the common analytical tools, deep learning methods are well suited for interpreting high-dimensional and complicated spectroscopy data. They offer great opportunities to extract subtle and deep information about optical properties of materials with simpler optical setups, which would otherwise require sophisticated instrumentation. In this work, we propose a computational approach based on a conventional tabletop optical microscope and a deep learning model called ReflectoNet. Without any prior knowledge about the multilayer substrates, ReflectoNet can predict the complex refractive indices of thin films and 2D materials on top of these nontrivial substrates from experimentally measured optical reflectance spectra with high accuracies. This task was not feasible previously with traditional reflectometry or ellipsometry methods. Fundamental physical principles, such as the Kramers–Kronig relations, are spontaneously learned by the model without any further training. This approach enables in-operando optical characterization of functional materials and 2D materials within complex photonic structures or optoelectronic devices.en_US
dc.identifier.citationWang, Ziyang, Lin, Yuxuan Cosmi, Zhang, Kunyan, et al.. "Measuring complex refractive index through deep-learning-enabled optical reflectometry." <i>2D Materials,</i> 10, no. 2 (2023) IOP Publishing: https://doi.org/10.1088/2053-1583/acc59b.en_US
dc.identifier.doihttps://doi.org/10.1088/2053-1583/acc59ben_US
dc.identifier.urihttps://hdl.handle.net/1911/114871en_US
dc.language.isoengen_US
dc.publisherIOP Publishingen_US
dc.rightsThis is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by IOP Publishing.en_US
dc.titleMeasuring complex refractive index through deep-learning-enabled optical reflectometryen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
dc.type.publicationpost-printen_US
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