Nonlinear memristive computational spectrometer

Xin Li; Jie Wang; Feilong Yu; Jin Chen; Xiaoshuang Chen; Wei Lu; Guanhai Li

doi:10.1038/s41377-024-01703-y

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Nonlinear memristive computational spectrometer

Article

- Nonlinear memristive computational spectrometer
- Nonlinear memristive computational spectrometer
- LSA 2025年14卷第1期
- Affiliations：
- Author bio：
  
  gghli0120@mail.sitp.ac.cn
- Funds：
  
  Strategic Priority Research Program (B) of Chinese Academy of Sciences (XDB0580000, XDB43010200, GJ0090406);This work was partially carried out at the Center for Micro and Nanoscale Research and Fabrication in University of Science and Technology of China and Soft Matter Nanofab (SMN180827) in ShanghaiTech University.;National Key Research and Development Program of China (2023YFA1406900); National Natural Science Foundation of China (62222514, 62350073, U2341226, 61991440); Shanghai Science and Technology Committee (23ZR1482000, 22JC1402900); Natural Science Foundation of Zhejiang Province (LR22F050004); Shanghai Municipal Science and Technology Major Project (2019SHZDZX01); Youth Innovation Promotion Association (Y2021070) and International Partnership Program (112GJHZ2022002FN) of Chinese Academy of Sciences; Shanghai Human Resources and Social Security Bureau (2022670), and China Postdoctoral Science Foundation (2023T160661, 2022TQ0353 and 2022M713261).
- DOI：10.1038/s41377-024-01703-y
  中图分类号：
- 收稿日期：2024-05-30，
  
  修回日期：2024-10-09，
  
  录用日期：2024-11-05，
  
  网络出版日期：2025-01-14，
- Accepted：
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Nonlinear memristive computational spectrometer[J]. LSA, 2025,14(1).

Xin Li, Jie Wang, Feilong Yu, et al. Nonlinear memristive computational spectrometer[J]. Light: science & applications, 2025, 14(1).
Nonlinear memristive computational spectrometer[J]. LSA, 2025,14(1). DOI： 10.1038/s41377-024-01703-y.

Xin Li, Jie Wang, Feilong Yu, et al. Nonlinear memristive computational spectrometer[J]. Light: science & applications, 2025, 14(1). DOI： 10.1038/s41377-024-01703-y.

摘要

Abstract

In the domain of spectroscopy

miniaturization efforts often face significant challenges

particularly in achieving high spectral resolution and precise construction. Here

we introduce a computational spectrometer powered by a nonlinear photonic memristor with a WSe

homojunction. This approach overcomes traditional limitations

such as constrained Fermi level tunability

persistent dark current

and limited photoresponse dimensionality through dynamic energy band modulation driven by palladium (Pd) ion migration. The critical role of Pd ion migration is thoroughly supported by first-principles calculations

numerical simulations

and experimental verification

demonstrating its effectiveness in enhancing device performance. Additionally

we integrate this dynamic modulation with a specialized nonlinear neural network tailored to address the memristor’s inherent nonlinear photoresponse. This combination enables our spectrometer to achieve an exceptional peak wavelength accuracy of 0.18 nm and a spectral resolution of 2 nm within the 630–640 nm range. This development marks a significant advancement in the creation of compact

high-efficiency spectroscopic instruments and offers a versatile platform for applications across diverse material systems.

关键词

Keywords

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