Microscale-Concave-Interface-Induced Moiré Fringes for Smart Spectral Reconstruction

Microscale concave interfaces (MCIs) have opened new avenues for exploring innovative coloration mechanisms, leading to practical applications in fields such as anti-counterfeiting and traffic safety. A distinguishing feature of these MCIs is the formation of spectrally dependent concentric rings, governed by the refractive index distribution and dimensions of the hemispherical structures. In this work, we unveil a novel Moiré fringe pattern generated by superposing multiple concentric rings under polychromatic illumination of the MCIs. By capturing the spatial variations in these ring patterns with an inexpensive black-and-white CMOS camera, and analyzing the reflected spectrum, a machine learning algorithm is trained to recognize and reconstruct unknown incident spectra. The Moiré effect enhances the reconstruction of polychromatic spectra, as minute changes to the spatial composition of any superposing ring pattern are magnified in the resulting fringe. We demonstrate the development of an MCI-based smart spectrometer capable of achieving a spectral accuracy of 0.2 nm, high spectral resolution of 1.5 nm, and 450 nm bandwidth that spans the visible and near-infrared regime. This performance represents a significant improvement over similar devices and systems, and offers a cost-effective, compact solution for applications requiring precise spectral measurements, including portable sensing, elemental analysis, and advanced materials characterization.