Oral Presentation Royal Australian Chemical Institute National Congress 2026

Spectroscopy-based process analytical technology in sustainable chemical and paper manufacturing (136775)

Sanathri Alwis 1 2 , Leo Lebanov 1 2 , Dilhara Dissanayaka 1 2 , Desmond E Richardson 2 , Noel Davies 3 , Meegan Grubb 4 , Paul Banham 4 , Michael Landman 4 , Thomas Rodemann 3 , Estrella Sanz Rodriguez 1 2 , Brett Paull 1 2
  1. Australian Centre for Research on Separation Science (ACROSS), School of Natural Sciences, University of Tasmania, Dobson Road PO Box 845, Sandy Bay, TAS 7006, Australia
  2. ARC Training Centre for Hyphenated Analytical Separation Technologies (HyTECH), School of Natural Sciences, University of Tasmania, Dobson Road PO Box 845, Sandy Bay, TAS 7006, Australia
  3. Central Science Laboratory, University of Tasmania, Dobson Road PO Box 845, Sandy Bay, TAS 7006, Australia
  4. Boyer Paper Mill Limited, Boyer , TAS 7140, Australia

Process Analytical Technology (PAT), both offline and online, enables real-time measurement and analysis of critical quality attributes throughout manufacturing, facilitating enhanced process understanding and immediate control decisions [1]. Herein, two spectroscopy-based PAT approaches were developed for application to sustainable production processes, namely a biosolvent production process and a paper manufacturing process, where the use of biomass as raw material and the complex nature of products generated in manufacturing from lignocellulosic biomass require sophisticated PAT strategies.

Firstly, a chemometric-assisted NIR spectroscopy-based method was developed to quantify furfural, furans, formaldehyde, formic acid, acetic acid and water in the Furacell™ process used to produce the biosolvent Cyrene™. Quantification of the targeted analytes was performed by GC-MS, GC-FID and Karl Fischer titration, and the obtained values were used as reference concentrations. Interval PLS (iPLS) outperformed full-spectrum PLS through optimised spectral preprocessing and interval selection. Excellent predictions were achieved, with water showing the highest performance (R²=0.971), followed by formic acid (R²=0.965), furans (R²=0.901), and furfural (R²=0.836). REP values ranged from 8.1 to 22.0% across all analytes.

During paper manufacturing using the thermo-mechanical pulping (TMP) process, significant amounts of wood extractives (resin acids, fatty acids, triglycerides) are released, causing pitch deposition and operational downtime. Therefore, a rapid, solvent-free UV–Vis spectroscopy approach combined with machine and deep learning techniques was developed for real-time extractives monitoring in papermaking process streams. Regression models (MLR, PLS, Random Forest, SVM, and XGBoost) were applied comparing with reference values obtained by solvent extraction followed by GC-FID analysis. Strong predictive performance was achieved, with MLR yielding an REP of 24.4% and R² of 0.781 for total resin acids, and XGBoost an REP of 33.1% and R² of 0.727 for total fatty acids.

Both spectroscopic frameworks provide a foundation for developing portable devices for on-site, real-time process monitoring in sustainable manufacturing.

References:

  1. Gerzon, G., Y. Sheng, and M. Kirkitadze, Process analytical technologies–advances in bioprocess integration and future perspectives. Journal of Pharmaceutical and Biomedical Analysis, 2022. 207: p. 114379.