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The molecular weight of polyacrylonitrile (PAN) precursors plays an important role in specifying the properties of prepared carbon fibers. However, it is challenging to rapidly and conveniently determine the accurate molecular weight of PAN. Herein, a practical and facile molecular weight determination model of PAN based on near-infrared spectroscopy (NIR) combined with partial least squares (PLSs) is reported. Using the spectral modeling range from 4000 to 6000 cm −1  with standard normal variate (SNV) or multiplicative scatter correction (MSC) combined with smoothing and first-order differential, the optimized models with main factors number of nine are achieved. The models were systematically evaluated by root mean square error of calibration (RMSEC), root mean square error of prediction (RMSEP), and root mean squares error of cross-validation (RMSECV). In the determination of the molecular weight of the samples based on these optimized models, the value of the relative standard deviation is only 0.9%, and the value of deviation from the established gel permeation chromatography (GPC) method is between −0.037 × 10 5  and 0.051 × 10 5 . The results show that the reported NIR method has promising potential for the rapid and nondestructive determination of the molecular weight of PAN in production processes.

Rapid and Nondestructive Determination of Polyacrylonitrile Molecular Weight by Fourier Transform near-Infrared (NIR) Spectroscopy