aalto1 untyped-item.component.html
In situ spectral reconstruction based on a memristor chip for energy-efficient computational spectrometry
Loading...
Access rights
embargoedAccess
URL
Journal Title
Journal ISSN
Volume Title
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
This publication is imported from Aalto University research portal.
View publication in the Research portal (opens in new window)
View publication in the Research portal (opens in new window)
Date
Major/Subject
Mcode
Degree programme
Language
en
Pages
Series
Nature Electronics
Abstract
Computational spectrometers, which rely on reconstruction algorithms to decode spectral information from raw sensor data, are of potential use in portable, in-field spectrometry. However, research on such systems primarily focuses on the front-end encoding devices, and back-end decoding hardware remains limited by severe overheads. Here we report an in situ computational spectrometer implemented on a fully integrated 576-Kb memristor chip. With systematic robustness analysis, we develop memristive regularization and filter embedding strategies to overcome the extreme sensitivity of ill-posed spectral reconstruction, achieving software-equivalent accuracy. System-level benchmarking shows that our hardware takes only 125.0 ns to reconstruct one spectrum consuming 6.7 nJ of energy, which is 26.5 times faster and 162.7 times more energy-efficient than state-of-the-art computational spectrometers. Our work illustrates the potential of memristor-chip-based computational spectrometry and provides approaches for efficiently implementing signal processing algorithms on memristor chips.
Description
Publisher Copyright: © The Author(s), under exclusive licence to Springer Nature Limited 2026.
Keywords
Other note
Citation
Zhao, H, Wang, L, Zhou, Y, Liu, S, Qin, Q, Li, X, Zhang, Y, Xi, Y, Jiao, Y, Liu, Z, Hu, R, Lin, Y, Feng, X, Lu, L, Hasan, T, Sun, Z, Liu, Y, Yao, P, Gao, B, Qian, H, Tang, J, Cai, W & Wu, H 2026, 'In situ spectral reconstruction based on a memristor chip for energy-efficient computational spectrometry', Nature Electronics. https://doi.org/10.1038/s41928-026-01571-x