Chen Li, Chew Wee, Garland Marc
Department of Chemical and Environmental Engineering, 4 Engineering Drive 4, National University of Singapore, Singapore.
Appl Spectrosc. 2003 May;57(5):491-8. doi: 10.1366/000370203321666489.
An improved algorithm using minimization of entropy and spectral similarity (MESS) was tested to recover pure component spectra from in situ experimental Fourier transform infrared (FT-IR) reaction spectral data, which were collected from a homogeneous rhodium catalyzed hydroformylation of isoprene. The experimental spectra are complicated and highly overlapping because of the presence of multiple intermediate products in this reaction system. The traditional entropy minimization method fails to resolve real reaction mixture spectra, but MESS can successfully reconstruct pure component spectra of unknown intermediate products for real reaction systems by the addition of minimization of spectral similarity. The quantitative measure of spectral similarity between two spectra was given by their inner products. The results indicate that MESS is a stable and useful algorithm for spectral pattern recognition of highly overlapped experimental reaction spectra. Comparison is also made between MESS, entropy minimization, simple-to-use interactive self-modeling mixture analysis (SIMPLISMA), interactive principle component analysis (IPCA), and orthogonal projection approach-alternating least squares (OPA-ALS).
一种使用熵最小化和光谱相似性（MESS）的改进算法，用于从原位实验傅里叶变换红外（FT-IR）反应光谱数据中恢复纯组分光谱，该数据是从异戊二烯的均相铑催化氢甲酰化反应中收集的。由于该反应体系中存在多种中间产物，实验光谱复杂且高度重叠。传统的熵最小化方法无法解析实际反应混合物光谱，但MESS通过添加光谱相似性最小化，可以成功地为实际反应体系重建未知中间产物的纯组分光谱。两个光谱之间光谱相似性的定量度量由它们的内积给出。结果表明，MESS是一种用于高度重叠实验反应光谱的光谱模式识别的稳定且有用的算法。还对MESS、熵最小化、简单易用的交互式自建模混合物分析（SIMPLISMA）、交互式主成分分析（IPCA）和正交投影方法交替最小二乘法（OPA-ALS）进行了比较。
