Spectroscopy is a cornerstone in the field of optics. Conventional spectrometers generally require two elements. The first provides wavelength selectivity, for example, diffraction grating or Michelson interferometer. The second is a detector (or detector array). Many applications would benefit from very small and lightweight spectrometers. This motivates us to investigate what may be regarded as an ultimate level of miniaturization for a spectrometer, in which it consists solely of a detector array. We demonstrate a chip containing 24 pixels, each comprising a silicon nanowire (Si NW) array photodetector formed above a planar photodetector. The NWs are structurally colored, enabling us to engineer the responsivity spectra of all photodetectors in the chip. Each pixel thus combines wavelength selectivity and photodetection functions. We demonstrate the use of our chip to reconstruct the spectrum of an unknown light source impinging upon it. This is achieved by an algorithm that takes as its inputs the measured photocurrents from the pixels and a library of their responsivity spectra.

A hologram records the wavefront of light from an object, but it is usually not an image itself, and looks unintelligible under diffuse ambient light. Here a new paradigm to encode a color hologram onto a color printed image is experimentally demonstrated. The printed image can be directly viewed under the white light illumination, while a low-crosstalk color holographic image can be seen when the device is illuminated with red (R), green (G), and blue (B) laser beams. The device is a dielectric metasurface that consists of titanium dioxide (TiO 2) cones on a glass substrate. The dimensions of the TiO 2 cones are chosen to allow them to support visible-wavelength resonances, thereby producing the desired reflection spectra and thus the color printed image. The detour phase method is furthermore used to encode the hologram into the metasurface. The approach is conceptually different from previously demonstrated color printed images or holograms and presents opportunities for optical document security and data storage applications.

We computationally reconstruct short- to long-wave infrared spectra using an array of plasmonic metasurface filters. We illuminate the filter array with an unknown spectrum and measure the optical power transmitted through each filter with an infrared microscope to emulate a filter-detector array system. We then use the recursive least squares method to determine the unknown spectrum. We demonstrate our method with light from a blackbody. We also demonstrate it with spectra generated by passing the light from the blackbody through various materials. Our approach is a step towards miniaturized spectrometers spanning the short- to long-wave infrared based on filter-detector arrays.

Numerous applications exist for chemical detection, ranging from the industrial production of chemicals to pharmaceutical manufacturing, environmental monitoring and hazardous risk control. For many applications, infrared absorption spectroscopy is the favored technique, due to attributes that include short response time, high specificity, minimal drift, in-situ operation, negligible sample disruption, and reliability. The workhorse instrument for infrared absorption is the Fourier transform infrared (FTIR) spectrometer. While such systems are suitable for many purposes, new applications would be enabled by small, lightweight, low power and low cost infrared microspectrometers. Here we perform a detailed study on a microspectrometer chemical classifier comprising an array of plasmonic mid-infrared spectral filters used with a photodetector array, whose outputs are analyzed by a machine learning algorithm. We conduct simulations (including noise), demonstrating the identification of six gas-phase and six liquid-phase chemicals. We study the performance of our method at detecting the concentration of acetylene.

The realization of on-chip microspectrometers would allow spectroscopy and colorimetry measurement systems to be readily incorporated into platforms for which size and weight are critical, such as consumer grade electronics, smartphones, and unmanned aerial vehicles. This would allow them to find use in diverse fields such as interior design, agriculture, and in machine vision applications. All spectrometers require a detector or detector array and optical elements for spectral discrimination. A single device that combines both detection and spectral discrimination functions therefore represents an ultimate limit of miniaturization. Motivated by this, we here experimentally demonstrate a novel nanostructured silicon-based photodetector design whose responsivity can be tailored by an appropriate choice of geometric parameters. We utilize a unique doping profile with two vertically stacked, back-to-back photodiode regions, which allows us to double the number of detectors in a given on-chip footprint. By patterning the top photosensitive regions of each device with two sets of interleaved vertical slab waveguide arrays of varied width and period, we define the absorption spectra (and thus responsivity spectra) of both the upper and lower photodiode regions. We then use twenty such "fishnet pixels" to form a microspectrometer chip and demonstrate the reconstruction of four test spectra using a two-stage supervised machine-learning-based reconstruction algorithm.