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Variation in wood shrinkage evaluated by the eigenvalue distribution of the near infrared spectral matrix
Vibrational Spectroscopy ( IF 2.5 ) Pub Date : 2020-07-01 , DOI: 10.1016/j.vibspec.2020.103091
Harusa Tsutsumi , Hirokazu Haga , Takaaki Fujimoto

Abstract Wood interactions with water occur at the cell wall, therefore, shrinkage should be closely related to wood density. Nevertheless, woods with almost the same density often show substantially different shrinkage. This study suggests a method to evaluate variation in shrinkage based on an eigenvalue analysis of the near infrared spectral matrix. The set of eigenvalues calculated from the variance-covariance matrix was defined as the Hamiltonian, which represents the energy eigenstate of the wood, and the wood variation is discussed from the viewpoints of thermodynamics and statistical mechanics. To determine the validity of this idea, two sample groups with almost equal wood density values, one showing high shrinkage and the other low, were prepared. The eigenvalues of the high shrinkage samples were widely distributed compared with those of the low shrinkage samples. As a result, the Helmholtz free energy was higher in the high shrinkage samples and entropy was higher in the low shrinkage samples. Hence, the Hamiltonian calculated from the variance-covariance matrix of NIR spectra explained differences in shrinkage between the two groups and was consistent with actual physical images of woods. These results were also supported by optical micrographs and stiffness data. The dimensional changes of wood are complex phenomena involving many factors. The method proposed in this research would be useful for evaluating phenomena in which many factors contribute cooperatively to a system, rather than individually.

中文翻译:

通过近红外光谱矩阵的特征值分布评估木材收缩率的变化

摘要 木材与水的相互作用发生在细胞壁上,因此收缩应与木材密度密切相关。然而,几乎相同密度的木材通常表现出明显不同的收缩率。这项研究提出了一种基于近红外光谱矩阵的特征值分析来评估收缩变化的方法。由方差-协方差矩阵计算出的一组特征值被定义为哈密顿量,代表木材的能量特征状态,从热力学和统计力学的角度讨论了木材的变化。为了确定这个想法的有效性,准备了两个木材密度值几乎相等的样品组,一个显示出高收缩率,另一个显示出低收缩率。与低收缩样品相比,高收缩样品的特征值分布广泛。结果,高收缩样品的亥姆霍兹自由能较高,而低收缩样品的熵较高。因此,根据近红外光谱的方差-协方差矩阵计算的哈密顿量解释了两组之间收缩的差异,并与木材的实际物理图像一致。这些结果也得到了光学显微照片和刚度数据的支持。木材的尺寸变化是一个涉及多种因素的复杂现象。本研究中提出的方法将有助于评估许多因素协同作用于系统而不是单独作用的现象。高收缩样品的亥姆霍兹自由能较高,低收缩样品的熵较高。因此,根据近红外光谱的方差-协方差矩阵计算的哈密顿量解释了两组之间收缩的差异,并与木材的实际物理图像一致。这些结果也得到了光学显微照片和刚度数据的支持。木材的尺寸变化是一个涉及多种因素的复杂现象。本研究中提出的方法将有助于评估许多因素协同作用于系统而不是单独作用的现象。高收缩样品的亥姆霍兹自由能较高,低收缩样品的熵较高。因此,根据近红外光谱的方差-协方差矩阵计算的哈密顿量解释了两组之间收缩的差异,并与木材的实际物理图像一致。这些结果也得到了光学显微照片和刚度数据的支持。木材的尺寸变化是一个涉及多种因素的复杂现象。本研究中提出的方法将有助于评估许多因素协同作用于系统而不是单独作用的现象。从近红外光谱的方差-协方差矩阵计算的哈密顿量解释了两组之间收缩的差异,并与木材的实际物理图像一致。这些结果也得到了光学显微照片和刚度数据的支持。木材的尺寸变化是一个涉及多种因素的复杂现象。本研究中提出的方法将有助于评估许多因素协同作用于系统而不是单独作用的现象。从近红外光谱的方差-协方差矩阵计算的哈密顿量解释了两组之间收缩的差异,并与木材的实际物理图像一致。这些结果也得到了光学显微照片和刚度数据的支持。木材的尺寸变化是一个涉及多种因素的复杂现象。本研究中提出的方法将有助于评估许多因素协同作用于系统而不是单独作用的现象。
更新日期:2020-07-01
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