Advancing IR Laser Thermography in Composites via Thermal Analysis-Informed Machine Learning

K), from where the loss objective decreased by a factor of ca. 3 within only seven iterative rounds. A final experimental validation using these optimized parameters successfully reproduced three independent thermal images with only minor deviations, demonstrating the robustness and applicability of the proposed approach.

Authors

Rodrigo Q. Albuquerque (ORCID: https://orcid.org/0000-0001-9064-4982)
Julien Lecompagnon (ORCID: https://orcid.org/0000-0001-8614-3296)
Holger Ruckdäschel (ORCID: https://orcid.org/0000-0001-5985-2628)
Ali Sarhadi (ORCID: https://orcid.org/0000-0003-1078-493X)
Martin A. Eder

Institutions

Federal Institute For Materials Research and Testing (DE)
Institute for Innovative Process Engineering (DE)
Neue Materialien Bayreuth GmbH
University of Bayreuth (DE)
Technical University of Denmark (DK)

Publication Details

Journal: ACS Applied Materials & Interfaces
Published: 2026-04-17
DOI: https://doi.org/10.1021/acsami.6c00835
Primary Topic: Thermography and Photoacoustic Techniques
Type: article
Field-Weighted Citation Impact: 0.00

Funders

Innovationsfonden

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article

Advancing IR Laser Thermography in Composites via Thermal Analysis-Informed Machine Learning

Rodrigo Q. Albuquerque, Julien Lecompagnon, Holger Ruckdäschel, Ali Sarhadi et al.

Apr 17, 2026

ACS Applied Materials & Interfaces

Thermography and Photoacoustic Techniques

article

Advancing IR Laser Thermography in Composites via Thermal Analysis-Informed Machine Learning

Rodrigo Q. Albuquerque, Julien Lecompagnon, Holger Ruckdäschel, Ali Sarhadi, Martin A. Eder

April 17, 2026article en

Abstract

K), from where the loss objective decreased by a factor of ca. 3 within only seven iterative rounds. A final experimental validation using these optimized parameters successfully reproduced three independent thermal images with only minor deviations, demonstrating the robustness and applicability of the proposed approach.

ACS Applied Materials & InterfacesVol. 18(16)

Federal Institute For Materials Research and Testing (DE), Institute for Innovative Process Engineering (DE), Neue Materialien Bayreuth GmbH, University of Bayreuth (DE), Technical University of Denmark (DK)

Innovationsfonden

Openalex Percentile: Top 19%

Thermography and Photoacoustic Techniques

DOI Source OpenAlex

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