**4. Conclusions**

322 Materials Science and Technology

Samples Pulp 1 Pulp 2 Pulp 3

log *Mp'* 5.133 5.071 5.157

*Mw* 16.07 ×104 12.83 ×104 15.59 ×104

*Mn* 3.989×104 3.878 ×104 4.355 ×104

Table 3. Logarithm of molecular weight log*Mp'*, mass-average molecular weight *Mw* , number-average molecular weight *Mn* , and polydispersity index *PDI'* of the three pulps

*PDI'* 4.030 3.309 3.581

Fig. 4. *MWD* curves of the three pulps by the *GPC* method.

measured by the *GPC* method.

Prediction of *MW* scale and *MWD* of cellulose by means of a rheology-based method was developed. With this method, insignificant effect of cellulose concentration on predicting *MW* and *MWD* of cellulose was found using a rheology-based method when the cellulose concentration in the NMMO·H2O solution is high enough. Furthermore, a method of calculating *PDI* of cellulose was established according to the Wesslan function which is the logarithm of the normal distribution function. For the cellulose/NMMO·H2O solution, the cellulose *MW* values calculated by the Rouse terminal relaxation time can be considered as the peak *MW* on the *MWD* curves of cellulose. Consequently, the reciprocal of the frequency is converted to the *MW* scale, obtaining *MWD* scale curves of cellulose.

Meanwhile, the results obtained by the rheology-based method were compared with those measured by the *GPC* method. All obtained results from the two methods are only relative values. The comparison shows that the calculated peak *MW* are approximately equal, the calculated *PDI* have the same trends, but the shapes of the *MWD* curves do not match. *GPC* method is advantageous to depict finer characteristics of the *MWD* of cellulose. In spite of that, the rheology-based method is simple and fast. Therefore it is a useful and easy way to analyze the *MW* scale and *MWD* of cellulose in the fiber industry.
