TY - JOUR
T1 - Chemical imaging to reveal the resin distribution in impregnation-treated wood at different spatial scales
AU - Altgen, Michael
AU - Awais, Muhammad
AU - Altgen, Daniela
AU - Klüppel, André
AU - Koch, Gerald
AU - Mäkelä, Mikko
AU - Olbrich, Andrea
AU - Rautkari, Lauri
N1 - Funding Information:
We thank Tanja Potsch, Daniela Paul, and Gabriele Ehmke for their help with the UMSP measurements. This work made use of Aalto University Bioeconomy Infrastructure. English-language proofreading was provided by Heidi Henrickson.
Publisher Copyright:
© 2022 The Authors
PY - 2023/1
Y1 - 2023/1
N2 - 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.
AB - 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.
KW - Hyperspectral near-infrared (NIR) imaging
KW - Multivariate image analysis
KW - Phenol formaldehyde resin
KW - Ultraviolet (UV) microspectrophotometry
KW - Wood modification
UR - http://www.scopus.com/inward/record.url?scp=85143727142&partnerID=8YFLogxK
U2 - 10.1016/j.matdes.2022.111481
DO - 10.1016/j.matdes.2022.111481
M3 - Article
AN - SCOPUS:85143727142
SN - 0264-1275
VL - 225
JO - Materials and Design
JF - Materials and Design
M1 - 111481
ER -