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<p>The steam explosion of softwood bark generates blow steam condensates rich in furans, such as furfural and 5-hydroxymethylfurfural (5-HMF). These are not only problematic inhibitors to enzymes and yeast but are also valuable platform chemicals, and their presence relates to the process intensity. This study explores the potential of Raman spectroscopy as a non-destructive tool for accurately quantifying furans in condensates from varying treatment conditions. During the experiments, the temperature was kept at 200&#xa0;°C; residence time was varied between 5, 10, and 20&#xa0;min; and 0, 2, and 4% w/w H<sub>2</sub>SO<sub>4</sub> was added. Collected condensates were analyzed by Raman and modeled using principal component analysis (PCA) and orthogonal projections to latent structures (OPLS). The PCA analysis revealed a distinct clustering of condensates based on the severity of the treatment. The OPLS calibration model for furfural showed excellent predictive capabilities (<i>R</i><sup>2</sup> = 0.986, <i>Q</i><sup>2</sup> = 0.969, RMSE<sub>cv</sub> = 253&#xa0;mg/L, and RMSEP = 155&#xa0;mg/L). Our results highlight the potential of Raman spectroscopy for real-time steam explosion process control and accurate quantification of furans in blow steam condensates.</p>

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Raman spectroscopy for the quantification of furans in blow steam condensates derived from steam explosion of softwood bark

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年2月11日

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  • Andreas Averheim,
  • Mikael Thyrel

摘要

The steam explosion of softwood bark generates blow steam condensates rich in furans, such as furfural and 5-hydroxymethylfurfural (5-HMF). These are not only problematic inhibitors to enzymes and yeast but are also valuable platform chemicals, and their presence relates to the process intensity. This study explores the potential of Raman spectroscopy as a non-destructive tool for accurately quantifying furans in condensates from varying treatment conditions. During the experiments, the temperature was kept at 200 °C; residence time was varied between 5, 10, and 20 min; and 0, 2, and 4% w/w H2SO4 was added. Collected condensates were analyzed by Raman and modeled using principal component analysis (PCA) and orthogonal projections to latent structures (OPLS). The PCA analysis revealed a distinct clustering of condensates based on the severity of the treatment. The OPLS calibration model for furfural showed excellent predictive capabilities (R2 = 0.986, Q2 = 0.969, RMSEcv = 253 mg/L, and RMSEP = 155 mg/L). Our results highlight the potential of Raman spectroscopy for real-time steam explosion process control and accurate quantification of furans in blow steam condensates.