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Spectral Reconstruction Using Broadband Inkjet‐Printed Optical Filters

Baini, Leonardo ; Jin, Qihao ORCID iD icon 1; Zhang, Qiaoshuang ORCID iD icon 1; Gomard, Guillaume; Lemmer, Uli ORCID iD icon 1; Bartolini, Paolo; Taschin, Andrea; Wiersma, Diederik S.; Torre, Renato; Boschetti, Alice
1 Lichttechnisches Institut (LTI), Karlsruher Institut für Technologie (KIT)

Abstract:

Reconstructive spectroscopy offers a promising route toward miniaturization by replacing dispersive optics with computational recovery from encoded measurements, but existing implementations typically rely on complex nanofabrication and highly decorrelated encoding elements, limiting manufacturability and robustness. Here, we demonstrate a reconstructive spectrometer based on inkjet-printed interferometric optical filters featuring a minimalist tri-layer architecture and high optical throughput. Contrary to prevailing design principles, we show that smooth, strongly correlated filter responses can nonetheless enable accurate spectral reconstruction over a 400 nm visible bandwidth. By adaptively selecting optimized subsets of filters using a custom genetic algorithm, the system exploits the high signal-to-noise ratio of correlated encoders while maintaining reconstruction fidelity. In addition, we introduce a calibration and reconstruction framework that requires only minimal a priori knowledge of the measured spectra, increasing the viability of practical deployment of reconstructive spectrometers. The resulting procedure combines scalable fabrication, adaptive encoding, and robust reconstruction, with a strong basis of versatile and manufacturing-ready encoding elements.


Verlagsausgabe §
DOI: 10.5445/IR/1000198130
Veröffentlicht am 19.10.2026
Cover der Publikation
Zugehörige Institution(en) am KIT Lichttechnisches Institut (LTI)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2026
Sprache Englisch
Identifikator ISSN: 2195-1071
KITopen-ID: 1000198130
Erschienen in Advanced Optical Materials
Verlag John Wiley and Sons
Seiten e71918
Vorab online veröffentlicht am 13.10.2026
Nachgewiesen in OpenAlex
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