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Chemical imaging to reveal the resin distribution in impregnation-treated wood at different spatial scales

Year of publication

2022

Authors

Altgen, Michael; Awais, Muhammad; Altgen, Daniela; Klüppel, André; Koch, Gerald; Mäkelä, Mikko; Olbrich, Andrea; Rautkari, Lauri

Abstract

<p>An inhomogeneous chemical distribution can be problematic in many biomaterial applications, including wood impregnation. Since wood is a hierarchically structured material, the chemical distribution must be considered on different length scales. Here, a combination of imaging methods revealed the distribution of phenol–formaldehyde resin in impregnation-treated European beech wood within the scale of several millimeters or larger (macroscopic) and the micron scale (cellular level). The macroscopic resin distribution was quantified by hyperspectral near-infrared (NIR) image regression. A partial least square regression model accurately predicted the resin content in the range of 0–30 % with average prediction errors of ≤0.93 % for calibration and the test set. The cellular resin distribution was investigated by mapping the UV absorbance in selected regions of interest at high lateral resolution using UV microspectrophotometry (UMSP). The application of both imaging techniques to board sections revealed a process-dependent resin distribution. NIR image regression quantified the drying-induced migration of resin toward the board surfaces. UMSP measurements in selected regions revealed that this resin migration also affected the resin distribution across cell walls. Overall, the results demonstrate the potential of combining chemical imaging techniques to quantify process-dependent heterogeneity and to develop efficient treatments for wood and other biomaterials.</p>
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Organizations and authors

Aalto University

Rautkari Lauri Orcid -palvelun logo

Awais Muhammad Orcid -palvelun logo

Altgen Daniela

Altgen Michael

Publication type

Publication format

Article

Parent publication type

Journal

Article type

Original article

Audience

Scientific

Peer-reviewed

Peer-Reviewed

MINEDU's publication type classification code

A1 Journal article (refereed), original research

Publication channel information

Publisher

Elsevier

Volume

225

Article number

111481

​Publication forum

62974

​Publication forum level

2

Open access

Open access in the publisher’s service

Yes

Open access of publication channel

Fully open publication channel

Self-archived

Yes

Article processing fee (EUR)

2300

Year of payment for the open publication fee

2022

Other information

Fields of science

Mechanical engineering; Materials engineering

Keywords

[object Object],[object Object],[object Object],[object Object],[object Object]

Internationality of the publisher

International

Language

English

International co-publication

Yes

Co-publication with a company

No

DOI

https://doi.org/10.1016/j.matdes.2022.111481

The publication is included in the Ministry of Education and Culture’s Publication data collection

Yes