Chemometric Modeling  for Pulp and Paper Industries

Chemometrics is the discipline that uses mathematical and statistical methods to improve the understanding of chemical information by extracting qualitative and quantitative information from analytical instrument data.  In Chemometrics, patterns in the data are modeled and these models are then routinely applied to future data in order to predict the same characteristics of a new sample. The reason for rapid emergence of Chemometrics is twofold: (i) introduction of instrumentation giving multivariate responses for each sample, and (ii) the availability and rapid advancement of computers.

Chemometric modeling has been used for developing new analytical methods prediction of properties of raw materials for Pulp and Paper Industries and finished production of such industries. Easy and nondestructive methods for sorting raw materials on the basis of spectral data from instruments can be developed with the classification techniques of Chemometric modeling.  Very recently, scientists are developing sensors based on Chemometric modeling for online determination of pulp and paper properties for such industries.

In Chemometric analysis, mathematical models are used to find the pattern in the data and also to find the association among the data. Quantification and qualification of the parameters are based on the developed models. Most of the cases mathematical equation takes place of standard chemicals we used for analyzing any sample. Therefore, reduction of chemical use in the testing procedure has been reduced, which eventually leads establishing the concept ‘Green chemistry’. Chemometric methods are mostly non-destructive and require minimum sample preparation hassle and time. Thus these methods are rapid and comparatively cheaper.  

Pulp and Paper Division of BCSIR Laboratories, Dhaka has already developed to non-destructive methods for quantification of lignocellulosic properties of Dhaincha and Jute, two potential non-wood raw materials for pulp and paper industries. Another method has also been developed here for prediction of dissolving pulp properties with spectroscopic data.

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