Computer simulation and modeling of glow discharge optical emission coded aperture elemental mapping

Elemental mapping (EM) yields necessary insights into mechanisms of interest in solid samples across multiple disciplines. There are several EM techniques available but long acquisition time is a common limitation. Glow discharge optical emission spectroscopy (GDOES) allows direct quantitative multi...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Analytica chimica acta 2024-09, Vol.1321, p.343001, Article 343001
Hauptverfasser: Agrawaal, Harsshit, Gamez, Gerardo
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Elemental mapping (EM) yields necessary insights into mechanisms of interest in solid samples across multiple disciplines. There are several EM techniques available but long acquisition time is a common limitation. Glow discharge optical emission spectroscopy (GDOES) allows direct quantitative multi-EM at very high throughput (∼10 s s) when coupled to traditional hyperspectral imaging (HSI) techniques. However, GDOES consumes the sample via sputtering, such that traditional HSI sequential scanning requirements lead to loss of information/resolution, which is compounded for multi-EM and limits nanomaterials analysis. Thus, there is a need for faster HSI to enable GDOES multi-EM of nanoscale materials. Here, a new technique is described, Glow discharge Optical emission Coded Aperture elemental Mapping (GOCAM), that takes advantage of compressive coded aperture spectral imaging to enable multi-EM in a single camera exposure. In this first phase of development, computer model simulations were implemented to study the effects of coded aperture parameters on data fidelity, which showed the best fidelity is achieved at smaller mask element sizes and transmittance of 60 %. In addition, SeSCIGPU demonstrated the best fidelity performance compared to several compressed sensing reconstruction algorithms, including TwIST, GAP-TV, SeSCICPU, and ADMM-TV, as evaluated by studying the effects of varying the corresponding hyperparameters. This study shows GOCAM's feasibility and provides a starting point for the second phase hardware development currently underway. GOCAM's potential to allow multi-EM from solid surfaces in a fraction of a second will be particularly enabling for nanostructured materials characterization. [Display omitted] •The new technique GOCAM combines GDOES EM and compressed sensing (CS) hyperspectral imaging.•Coded aperture mask transmittance and element size affect spectra and image fidelity.•SeSCIGPU outperforms other CS recovery algorithms for GOCAM.•GOCAM will enable multi-EM of nanostructured materials in a fraction of a second.
ISSN:0003-2670
1873-4324
1873-4324
DOI:10.1016/j.aca.2024.343001