An approach for in situ qualitative and quantitative analysis of moisture adsorption in nanogram-scaled lignin by using micro-FTIR spectroscopy and partial least squares regression

Teng Xiao; Hanmeng Yuan; Qiang Ma; Xin Guo; Yiqiang Wu

doi:10.1016/j.ijbiomac.2019.04.043

An approach for in situ qualitative and quantitative analysis of moisture adsorption in nanogram-scaled lignin by using micro-FTIR spectroscopy and partial least squares regression

Int J Biol Macromol. 2019 Jul 1:132:1106-1111. doi: 10.1016/j.ijbiomac.2019.04.043. Epub 2019 Apr 8.

Authors

Teng Xiao¹, Hanmeng Yuan², Qiang Ma², Xin Guo³, Yiqiang Wu⁴

Affiliations

¹ College of Science, Central South University of Forestry and Technology, Changsha 410004, China; College of Material Science and Engineering, Central South University of Forestry and Technology, Changsha 410004, China.
² College of Science, Central South University of Forestry and Technology, Changsha 410004, China.
³ College of Science, Central South University of Forestry and Technology, Changsha 410004, China. Electronic address: guocumt@163.com.
⁴ College of Material Science and Engineering, Central South University of Forestry and Technology, Changsha 410004, China.

PMID: 30974143
DOI: 10.1016/j.ijbiomac.2019.04.043

Abstract

Moisture sorption has a great impact on the mechanical properties of lignin. To better characterize the moisture sorption of lignin, an approach for in situ qualitative and quantitative analysis of moisture adsorption in nanogram-scaled lignin by using micro-FTIR spectroscopy and partial least squares regression is introduced in this study. Spectra of nanogram-scaled lignin were collected within the relative humidity (RH) of 0%-92%. A qualitative analysis of these measured spectra confirmed the effective water sorption sites and determined spectral ranges related to moisture adsorption. Using these identified spectral ranges, a quantitative forecasting model for the moisture content (MC) of lignin was built and developed according to partial least square regression (R², 0.9996; RMSECV, 0.408; RMSEP, 0.118). Furthermore, the water sorption isotherm of lignin was acquired using the established forecasting model in which a very positive correlation between the estimated and measured MCs was demonstrated using a dynamic vapor sorption (DVS) setup. The results confirmed the practicability and effectiveness of this in situ qualitative and quantitative analysis approach.

Keywords: Lignin; Micro-FTIR spectroscopy; Qualitative and quantitative analysis.

MeSH terms

Adsorption
Least-Squares Analysis
Lignin / chemistry*
Spectroscopy, Fourier Transform Infrared*

Substances

Lignin