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

Michael Altgen (Corresponding Author), Muhammad Awais, Daniela Altgen, André Klüppel, Gerald Koch, Mikko Mäkelä, Andrea Olbrich, Lauri Rautkari

Research output: Contribution to journalArticleScientificpeer-review

Abstract

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.

Original languageEnglish
Article number111481
JournalMaterials and Design
Volume225
DOIs
Publication statusPublished - Jan 2023
MoE publication typeA1 Journal article-refereed

Keywords

  • Hyperspectral near-infrared (NIR) imaging
  • Multivariate image analysis
  • Phenol formaldehyde resin
  • Ultraviolet (UV) microspectrophotometry
  • Wood modification

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