Csóka Levente, Csoka Worakan, Tirronen Ella, Nikolskaya Ekaterina, Hiltunen Yrjö, Ohtani Bunsho
Faculty of Informatics, ELTE Eötvös Loránd University, 1053 Budapest, Hungary.
Fiber Laboratory, South-Eastern Finland University of Applied Sciences, 57200 Savonlinna, Finland.
Polymers (Basel). 2024 Dec 5;16(23):3419. doi: 10.3390/polym16233419.
In this study, we explored the structural and chemical modifications of cellulose fibres subjected to chemical and mechanical treatments through an innovative analytical approach. We employed photoacoustic spectroscopy (PAS) and reversed double-beam photoacoustic spectroscopy (RDB-PAS) to examine the morphological changes and the chemical integrity of the treated fibres. The methodology provided enhanced sensitivity and specificity in detecting subtle alterations in the treated cellulose structure. Additionally, we applied Coifman wavelet transformation to the PAS signals, which facilitated a refined analysis of the spectral features indicative of chemical and mechanical modifications at a molecular level. This advanced signal processing technique allowed for a detailed decomposition of the PAS signals, revealing hidden characteristics that are typically overshadowed in raw data analyses. Further, we utilised the concept of energy trap distribution to interpret the wavelet-transformed data, providing insights into the distribution and density of energy states within the fibres. Our results indicated significant differences in the energy trap spectra between untreated and treated fibres, reflecting the impact of chemical and mechanical treatments on the fibre's physical properties. The combination of these sophisticated analytical techniques elucidated the complex interplay between mechanical and chemical treatments and their effects on the structural integrity and chemical composition of cellulose fibres.
在本研究中，我们通过一种创新的分析方法，探究了经过化学和机械处理的纤维素纤维的结构和化学改性。我们采用光声光谱法（PAS）和反向双光束光声光谱法（RDB - PAS）来检测处理后纤维的形态变化和化学完整性。该方法在检测处理后纤维素结构的细微变化方面具有更高的灵敏度和特异性。此外，我们对PAS信号应用了科伊夫曼小波变换，这有助于在分子水平上对指示化学和机械改性的光谱特征进行精细分析。这种先进的信号处理技术能够对PAS信号进行详细分解，揭示出在原始数据分析中通常被掩盖的隐藏特征。此外，我们利用能量陷阱分布的概念来解释小波变换后的数据，从而深入了解纤维内能量状态的分布和密度。我们的结果表明，未处理纤维和处理后纤维的能量陷阱光谱存在显著差异，这反映了化学和机械处理对纤维物理性能的影响。这些复杂分析技术的结合阐明了机械处理和化学处理之间的复杂相互作用及其对纤维素纤维结构完整性和化学成分的影响。
