ReviewNanophotonics (Berlin, Germany)2022
Computational spectrometers enabled by nanophotonics and deep learning.
Review in Nanophotonics (Berlin, Germany), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
26 citing papers in PubMed.
- Wavelength-scale noise-resistant on-chip spectrometer.Nature communications · 2026Article
- Dynamically tunable membrane metasurfaces for infrared spectroscopy and strong light-matter interactions.Light, science & applications · 2026Article
- Silicon Photonic On-Chip Spectrometer Based on Cascaded Mach-Zehnder Interferometer.Sensors (Basel, Switzerland) · 2026Article
- Broadband and high-resolution snapshot spectroscopy with high-index transition metal dichalcogenides.Nature communications · 2026Article
- Broadband on-chip spectral sensing via directly integrated narrowband plasmonic filters for computational multispectral imaging.Nanophotonics (Berlin, Germany) · 2025Article
- Single-Pixel Infrared Miniaturized Spectrometer Enabled by Ultra-Broadband Reconfigurable Photodetection.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Miniaturized disordered photonic molecule spectrometer.Light, science & applications · 2025Article
- A Low-Cost Computational Spectrometer Based on a Trained Sparse Base Matrix.Sensors (Basel, Switzerland) · 2025Article
- Empowering nanophotonic applications via artificial intelligence: pathways, progress, and prospects.Nanophotonics (Berlin, Germany) · 2025Review
- Highly accurate, efficient, and fabrication tolerance-aware nanostructure prediction for high-performance optoelectronic devices.Scientific reports · 2024Article
- Advances in Miniaturized Computational Spectrometers.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Review
- Denoising-autoencoder-facilitated MEMS computational spectrometer with enhanced resolution on a silicon photonic chip.Nature communications · 2024Article
- Miniaturized on-chip spectrometer enabled by electrochromic modulation.Light, science & applications · 2024Article
- Very-large-scale-integrated high quality factor nanoantenna pixels.Nature nanotechnology · 2024Article
- Snapshot computational spectroscopy enabled by deep learning.Nanophotonics (Berlin, Germany) · 2024Article
- Unique Hyperspectral Response Design Enabled by Periodic Surface Textures in Photodiodes.ACS photonics · 2024Article
- AI-Based Metamaterial Design.ACS applied materials & interfaces · 2024Review
- Nonlinear self-calibrated spectrometer with single GeSe-InSe heterojunction device.Science advances · 2024Article
- A Neural Network Computational Spectrometer Trained by a Small Dataset with High-Correlation Optical Filters.Sensors (Basel, Switzerland) · 2024Article
- Compact angle-resolved metasurface spectrometer.Nature materials · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A new type of spectrometer that heavily relies on computational technique to recover spectral information is introduced. They are different from conventional optical spectrometers in many important aspects. Traditional spectrometers offer high spectral resolution and wide spectral range, but they are so bulky and expensive as to be difficult to deploy broadly in the field. Emerging applications in machine sensing and imaging require low-cost miniaturized spectrometers that are specifically designed for certain applications. Computational spectrometers are well suited for these applications. They are generally low in cost and offer single-shot operation, with adequate spectral and spatial resolution. The new type of spectrometer combines recent progress in nanophotonics, advanced signal processing and machine learning. Here we review the recent progress in computational spectrometers, identify key challenges, and note new directions likely to develop in the near future.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.