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      Miniaturization of optical spectrometers

      1 , 2 , 1 , 3 , 1 , 4
      Science
      American Association for the Advancement of Science (AAAS)

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          Abstract

          Spectroscopic analysis is one of the most widely used analytical tools in scientific research and industry. Although laboratory benchtop spectrometer systems offer superlative resolution and spectral range, their miniaturization is crucial for applications where portability is paramount or where in situ measurements must be made. Advancement in this field over the past three decades is now yielding microspectrometers with performance and footprint near those viable for lab-on-a-chip systems, smartphones, and other consumer technologies. We summarize the technologies that have emerged toward achieving these aims—including miniaturized dispersive optics, narrowband filter systems, Fourier transform interferometers, and reconstructive microspectrometers—and discuss the challenges associated with improving spectral resolution while device dimensions shrink ever further.

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          Most cited references94

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          Imaging-based molecular barcoding with pixelated dielectric metasurfaces

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            Is Open Access

            Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning

            Computational modeling of chemical and biological systems at atomic resolution is a crucial tool in the chemist’s toolset. The use of computer simulations requires a balance between cost and accuracy: quantum-mechanical methods provide high accuracy but are computationally expensive and scale poorly to large systems, while classical force fields are cheap and scalable, but lack transferability to new systems. Machine learning can be used to achieve the best of both approaches. Here we train a general-purpose neural network potential (ANI-1ccx) that approaches CCSD(T)/CBS accuracy on benchmarks for reaction thermochemistry, isomerization, and drug-like molecular torsions. This is achieved by training a network to DFT data then using transfer learning techniques to retrain on a dataset of gold standard QM calculations (CCSD(T)/CBS) that optimally spans chemical space. The resulting potential is broadly applicable to materials science, biology, and chemistry, and billions of times faster than CCSD(T)/CBS calculations.
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              A colloidal quantum dot spectrometer.

              Spectroscopy is carried out in almost every field of science, whenever light interacts with matter. Although sophisticated instruments with impressive performance characteristics are available, much effort continues to be invested in the development of miniaturized, cheap and easy-to-use systems. Current microspectrometer designs mostly use interference filters and interferometric optics that limit their photon efficiency, resolution and spectral range. Here we show that many of these limitations can be overcome by replacing interferometric optics with a two-dimensional absorptive filter array composed of colloidal quantum dots. Instead of measuring different bands of a spectrum individually after introducing temporal or spatial separations with gratings or interference-based narrowband filters, a colloidal quantum dot spectrometer measures a light spectrum based on the wavelength multiplexing principle: multiple spectral bands are encoded and detected simultaneously with one filter and one detector, respectively, with the array format allowing the process to be efficiently repeated many times using different filters with different encoding so that sufficient information is obtained to enable computational reconstruction of the target spectrum. We illustrate the performance of such a quantum dot microspectrometer, made from 195 different types of quantum dots with absorption features that cover a spectral range of 300 nanometres, by measuring shifts in spectral peak positions as small as one nanometre. Given this performance, demonstrable avenues for further improvement, the ease with which quantum dots can be processed and integrated, and their numerous finely tuneable bandgaps that cover a broad spectral range, we expect that quantum dot microspectrometers will be useful in applications where minimizing size, weight, cost and complexity of the spectrometer are critical.
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                Author and article information

                Contributors
                Journal
                Science
                Science
                American Association for the Advancement of Science (AAAS)
                0036-8075
                1095-9203
                January 28 2021
                January 29 2021
                January 28 2021
                January 29 2021
                : 371
                : 6528
                : eabe0722
                Affiliations
                [1 ]Department of Engineering, University of Cambridge, Cambridge CB3 0FA, UK.
                [2 ]College of Information Science and Electronic Engineering, State Key Laboratory of Modern Optical Instrumentation, Zhejiang University, Hangzhou 310027, China.
                [3 ]Key Laboratory of Education Ministry for Power Machinery and Engineering, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
                [4 ]Cambridge Graphene Centre, University of Cambridge, Cambridge CB3 0FA, UK.
                Article
                10.1126/science.abe0722
                33509998
                350ef9dd-6d28-4f80-994c-27a9e8d6c428
                © 2021

                https://www.sciencemag.org/about/science-licenses-journal-article-reuse

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