A sensor network for non-invasive identification of semiconductors

Andréa de Lima Ribeiro; Christian Röder; Margret C. Fuchs; Johannes Heitmann; Richard Gloaguen

doi:10.1117/12.3017512

20 June 2024 A sensor network for non-invasive identification of semiconductors

Andréa de Lima Ribeiro, Christian Röder, Margret C. Fuchs, Johannes Heitmann, Richard Gloaguen

Proceedings Volume 12999, Optical Sensing and Detection VIII; 1299917 (2024) https://doi.org/10.1117/12.3017512
Event: SPIE Photonics Europe, 2024, Strasbourg, France

Abstract

Efficient and sustainable production, recovery and recycling phases of semiconductors (SC) life cycles require noninvasive, inline methods able to identify their composition in material streams. Ideally, the sensor system should be fast and incorporated into conveyor-belt operations. Rapid identification as well as spatial distribution maps would allow for real-time monitoring and quality control of the material stream. Considering these requirements, we suggest the sequential use of fast hyperspectral reflectance imaging (HSI) and Raman spectroscopic sensors for the identification of SC types in a sensor network configuration. We propose spectral proxies based on electronic properties derived from HSI-reflectance (i.e. absorption edge linked to the band gap values) and Raman sensors (i.e. Raman-active phonon modes) for SC identification. We identify potential limitations of each proxy on identifying undoped/doped SC materials, and discuss which process workflows enable optimized SC classification. We demonstrate the multi-sensor approach with SC standards (GaAs, GaSb, InP, 4H-SiC, and Borosilicate) which are relevant for both opto- and power-electronic devices, and showcase the potential of sequential data acquisition by fast HSI-reflectance sensors in the visible to shortwave-infrared (integration times: (4.5–18) ms) and Raman scattering (excitation laser: 532 nm, acquisition times: (0.5–10) s).

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Andréa de Lima Ribeiro, Christian Röder, Margret C. Fuchs, Johannes Heitmann, and Richard Gloaguen "A sensor network for non-invasive identification of semiconductors", Proc. SPIE 12999, Optical Sensing and Detection VIII, 1299917 (20 June 2024); https://doi.org/10.1117/12.3017512

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available