Reconstructive spectrometers: hardware miniaturization and computational reconstruction

Spectrometers serve as indispensable analytical tools across chemistry, materials science, environmental monitoring, medical diagnostics, and beyond. The emergence of reconstructive spectrometers represents a transformative leap in spectral analysis, combining miniaturized encoding hardware with adv...

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Vydané v:eLight Ročník 5; číslo 1; s. 23 - 24
Hlavní autori: Zhang, Yiru, Yang, Enbo, Yoon, Hoon Hahn, Cheng, Qixiang, Sun, Zhipei, Hasan, Tawfique, Cai, Weiwei
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Singapore Springer Nature Singapore 08.09.2025
Springer Nature B.V
SpringerOpen
Predmet:
Accuracy
Algorithms
Decoding algorithms
Deep learning
Design
Fourier transforms
Inverse design
Joint optimization
Lasers
Light
Machine learning
Manufacturing
Mathematical models
Miniaturization
Optical Devices
Optics
Photonics
Physics
Physics and Astronomy
Reconstructive spectrometers
Review
Sensors
Sparsity
Reconstructive spectrometers
Miniaturization
Joint optimization
Inverse design
Decoding algorithms
ISSN:2097-1710, 2662-8643
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Abstract Spectrometers serve as indispensable analytical tools across chemistry, materials science, environmental monitoring, medical diagnostics, and beyond. The emergence of reconstructive spectrometers represents a transformative leap in spectral analysis, combining miniaturized encoding hardware with advanced computational algorithms to revolutionize conventional approaches. These devices encode unknown spectral data into measurable signals, for which sophisticated algorithms then decode to reconstruct the original spectrum with high fidelity—all achieved within an ultra-compact footprint. In this review, we first establish the mathematical foundations governing spectral encoding and decoding. We then provide a detailed analysis of encoding strategy and state-of-the-art decoding techniques, followed by recent breakthroughs in hardware design for optimized spectral reconstruction systems. Finally, we address key challenges and future opportunities, offering insights into how reconstructive spectrometers may redefine spectroscopy beyond traditional laboratory settings.
AbstractList Spectrometers serve as indispensable analytical tools across chemistry, materials science, environmental monitoring, medical diagnostics, and beyond. The emergence of reconstructive spectrometers represents a transformative leap in spectral analysis, combining miniaturized encoding hardware with advanced computational algorithms to revolutionize conventional approaches. These devices encode unknown spectral data into measurable signals, for which sophisticated algorithms then decode to reconstruct the original spectrum with high fidelity—all achieved within an ultra-compact footprint. In this review, we first establish the mathematical foundations governing spectral encoding and decoding. We then provide a detailed analysis of encoding strategy and state-of-the-art decoding techniques, followed by recent breakthroughs in hardware design for optimized spectral reconstruction systems. Finally, we address key challenges and future opportunities, offering insights into how reconstructive spectrometers may redefine spectroscopy beyond traditional laboratory settings.
Abstract Spectrometers serve as indispensable analytical tools across chemistry, materials science, environmental monitoring, medical diagnostics, and beyond. The emergence of reconstructive spectrometers represents a transformative leap in spectral analysis, combining miniaturized encoding hardware with advanced computational algorithms to revolutionize conventional approaches. These devices encode unknown spectral data into measurable signals, for which sophisticated algorithms then decode to reconstruct the original spectrum with high fidelity—all achieved within an ultra-compact footprint. In this review, we first establish the mathematical foundations governing spectral encoding and decoding. We then provide a detailed analysis of encoding strategy and state-of-the-art decoding techniques, followed by recent breakthroughs in hardware design for optimized spectral reconstruction systems. Finally, we address key challenges and future opportunities, offering insights into how reconstructive spectrometers may redefine spectroscopy beyond traditional laboratory settings.
ArticleNumber 23
Author Sun, Zhipei
Zhang, Yiru
Yoon, Hoon Hahn
Hasan, Tawfique
Yang, Enbo
Cheng, Qixiang
Cai, Weiwei
Author_xml – sequence: 1
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  surname: Zhang
  fullname: Zhang, Yiru
  organization: Key Lab of Education Ministry for Power Machinery and Engineering, School of Mechanical Engineering, Shanghai Jiao Tong University
– sequence: 2
  givenname: Enbo
  surname: Yang
  fullname: Yang, Enbo
  organization: Key Lab of Education Ministry for Power Machinery and Engineering, School of Mechanical Engineering, Shanghai Jiao Tong University
– sequence: 3
  givenname: Hoon Hahn
  surname: Yoon
  fullname: Yoon, Hoon Hahn
  organization: Department of Semiconductor Engineering, Gwangju Institute of Science and Technology
– sequence: 4
  givenname: Qixiang
  surname: Cheng
  fullname: Cheng, Qixiang
  organization: Department of Engineering, University of Cambridge, GlitterinTech Limited
– sequence: 5
  givenname: Zhipei
  surname: Sun
  fullname: Sun, Zhipei
  email: zhipei.sun@aalto.fi
  organization: Department of Electronics and Nanoengineering, Aalto University, QTF Centre of Excellence, Department of Applied Physics, Aalto University
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  givenname: Tawfique
  surname: Hasan
  fullname: Hasan, Tawfique
  email: th270@cam.ac.uk
  organization: Cambridge Graphene Centre, University of Cambridge
– sequence: 7
  givenname: Weiwei
  orcidid: 0000-0003-3589-7500
  surname: Cai
  fullname: Cai, Weiwei
  email: cweiwei@sjtu.edu.cn
  organization: Key Lab of Education Ministry for Power Machinery and Engineering, School of Mechanical Engineering, Shanghai Jiao Tong University
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Keywords Reconstructive spectrometers
Miniaturization
Joint optimization
Inverse design
Decoding algorithms
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Snippet Spectrometers serve as indispensable analytical tools across chemistry, materials science, environmental monitoring, medical diagnostics, and beyond. The...
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SubjectTerms Accuracy
Algorithms
Decoding algorithms
Deep learning
Design
Fourier transforms
Inverse design
Joint optimization
Lasers
Light
Machine learning
Manufacturing
Mathematical models
Miniaturization
Optical Devices
Optics
Photonics
Physics
Physics and Astronomy
Reconstructive spectrometers
Review
Sensors
Sparsity
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Title Reconstructive spectrometers: hardware miniaturization and computational reconstruction
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