UV Hyperspectral Imaging as Process Analytical Tool for the Characterization of Oxide Layers and Copper States on Direct Bonded Copper.

UV spectroscopy copper oxide layer thickness direct bonded copper hyperspectral imaging partial least squares regression principal component analysis pushbroom

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
04 Nov 2021
Historique:
received: 11 10 2021
revised: 01 11 2021
accepted: 03 11 2021
entrez: 13 11 2021
pubmed: 14 11 2021
medline: 17 11 2021
Statut: epublish

Résumé

Hyperspectral imaging and reflectance spectroscopy in the range from 200-380 nm were used to rapidly detect and characterize copper oxidation states and their layer thicknesses on direct bonded copper in a non-destructive way. Single-point UV reflectance spectroscopy, as a well-established method, was utilized to compare the quality of the hyperspectral imaging results. For the laterally resolved measurements of the copper surfaces an UV hyperspectral imaging setup based on a pushbroom imager was used. Six different types of direct bonded copper were studied. Each type had a different oxide layer thickness and was analyzed by depth profiling using X-ray photoelectron spectroscopy. In total, 28 samples were measured to develop multivariate models to characterize and predict the oxide layer thicknesses. The principal component analysis models (PCA) enabled a general differentiation between the sample types on the first two PCs with 100.0% and 96% explained variance for UV spectroscopy and hyperspectral imaging, respectively. Partial least squares regression (PLS-R) models showed reliable performance with

Identifiants

pubmed: 34770640
pii: s21217332
doi: 10.3390/s21217332
pmc: PMC8588143
pii:
doi:

Substances chimiques

Oxides 0
Copper 789U1901C5

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Références

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pubmed: 30307327

Auteurs

Mohammad Al Ktash (M)

Process Analysis and Technology PA & T, Reutlingen University, Alteburgstraße 150, 72762 Reutlingen, Germany.
Institute of Physical and Theoretical Chemistry, Eberhard Karls University Tübingen, Auf der Morgenstelle 18, 72076 Tübingen, Germany.

Mona Stefanakis (M)

Process Analysis and Technology PA & T, Reutlingen University, Alteburgstraße 150, 72762 Reutlingen, Germany.
Institute of Physical and Theoretical Chemistry, Eberhard Karls University Tübingen, Auf der Morgenstelle 18, 72076 Tübingen, Germany.

Tim Englert (T)

Robert Bosch GmbH, Automotive Electronics, Postfach 1342, 72703 Reutlingen, Germany.
Institute of Electrochemistry, Ulm University, Albert-Einstein-Allee 47, 89081 Ulm, Germany.

Maryam S L Drechsel (MSL)

Process Analysis and Technology PA & T, Reutlingen University, Alteburgstraße 150, 72762 Reutlingen, Germany.

Jan Stiedl (J)

Robert Bosch GmbH, Automotive Electronics, Postfach 1342, 72703 Reutlingen, Germany.

Simon Green (S)

Robert Bosch GmbH, Automotive Electronics, Postfach 1342, 72703 Reutlingen, Germany.

Timo Jacob (T)

Institute of Electrochemistry, Ulm University, Albert-Einstein-Allee 47, 89081 Ulm, Germany.

Barbara Boldrini (B)

Process Analysis and Technology PA & T, Reutlingen University, Alteburgstraße 150, 72762 Reutlingen, Germany.

Edwin Ostertag (E)

Process Analysis and Technology PA & T, Reutlingen University, Alteburgstraße 150, 72762 Reutlingen, Germany.

Karsten Rebner (K)

Process Analysis and Technology PA & T, Reutlingen University, Alteburgstraße 150, 72762 Reutlingen, Germany.

Marc Brecht (M)

Process Analysis and Technology PA & T, Reutlingen University, Alteburgstraße 150, 72762 Reutlingen, Germany.
Institute of Physical and Theoretical Chemistry, Eberhard Karls University Tübingen, Auf der Morgenstelle 18, 72076 Tübingen, Germany.

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Classifications MeSH