A selection of cellulose pulps was investigated for their chemical changes during the required process steps to viscose dope. The selection of the pulps was based on pulping process, original wood ...

Several grades of cellulose pulps were investigated for their influence on the product quality of a cellulose ether, ethyl-hydroxy-ethyl cellulose (EHEC). The selection of the pulps was based on pulping process, original wood type and intrinsic viscosity. In total, five sulfite pulps and four sulfate pulps were chosen, of which all but one sulfate pulp were of dissolving grade. The physical and chemical properties of the pulps were analyzed as well as important qualitative parameters of the final product EHEC. The influence of pulp properties on EHEC quality was investigated by multivariate data analyses.Principal component analysis showed that due to the influence of all variables, the pulps aligned in groups in accordance to the selection criteria pulping process and wood type. Partial least square regression revealed that high gel formation in EHEC is explained by the pulp properties high intrinsic viscosity and high Mw in combination with high caustic absorption rate and high total caustic absorption. The amount of hemicelluloses, in particular xylose, also contributed to gel formation. High cloud point for an EHEC solution was explained by a high MSEO and low DSEt of the EHEC molecules, where in turn a high MSEO could be predicted by a high pore area, high PD and a low caustic absorption rate. A low DSEt could on the other hand be predicted by a low hemicellulose content and hence a high R18. In a separate model, the same pulp properties explaining MSEO and DSEt also predicted cloud point directly. Fock reactivity and viscose dope filterability, both test methods originating from the viscose manufacturing, were shown to predict cloud point but have low predictability on other EHEC quality parameters.The models achieved can thus be utilized to predict final EHEC product qualities for new pulps within the design set of the chosen pulps.

The reactivity of dissolving pulp was experimentally determined in termsof residual cellulose in viscose. The correlations between 11 chemicalproperties of pulp and filter values and residual cellulose contents of viscosewere then investigated by multivariate data analysis. Both the viscose filtervalue and the residual cellulose were well modelled from the 11 propertiesby partial least squares regression. The results show that pulps with highacetone extractable fractions, high magnesium contents, low alkali resistanceand low viscosity, gave low viscose filter values and low residual cellulosecontents. Pulps with low residual cellulose contents also had low carboxylgroupcontents and low polydispersity. The results are interpreted as that in pulpwith high reactivity, the hemicellulose content is low and that the cellulosechains are shorter and more soluble in alkali. An explanation of the positiveeffect from the high extractive content is that the extractives facilitate thediffusion of carbon disulfide. A principal component analysis of CP/MAS 13 C-NMR spectral data of six pulp samples showed that differences inreactivity between the pulps could be explained by variations in the hydrogenbonds in the cellulose and/or changes in the glucosidic bonds. In a separatestudy electron beam processing enhanced the reactivity, i.e. lowered theresidual cellulose content, of the investigated pulps. The magnitude of theelectron dose, within the tested range (5.4–23.7 kGy), didnotseem to be important, but the reactivity within pulp sheets tended to be ratherinhomogeneous.

In this thesis technical nonionic surfactants are studied using multivariate techniques. The surfactants studied were alkyl ethoxylates (AEOs) and alkyl polyglucosides (APGs). The aquatic toxicity of the surfactants towards two organisms, a shrimp and a rotifer, was examined. The specified effect was lethality, LC50, as indicated by immobilisation. In a comparative study, the LC50 values obtained were used to develop two different types of model. In the log P model the toxicity was correlated to log P alone, while in the multivariate model several physicochemical variables, including log P, were correlated to the toxicity. The multivariate model gave smaller prediction errors than the log P model. Further, the change in reactivity when a surfactant mixture was added to dissolving pulp under alkaline conditions was studied, using the amount of residual cellulose as a measure of the reactivity. Ten AEO/APG mixtures were tested, and the mixture with greatest potential was studied in more detail. An optimum in the amount of added surfactant was found that seems to coincide, according to surface tension measurements, with the CMC.

The aquatic toxicity of 36 technical nonionic surfactants (ethoxylated fatty alcohols) was examined toward two freshwater animal species, the fairy shrimp Thamnocephalus playtyurus and the rotifer Brachionus calyciflorus. Responses of the two species to the surfactants were generally similar. A multivariate-quantitative structure-activity relationship (M-QSAR) model was developed from the data. The M-QSAR model consisted of a partial least squares model with three components and explained 92.4% of the response variance and had a predictive capability of 89.1%. The most important physicochemical variables for the M-QSAR model were the number of carbon atoms in the longest chain of the surfactant hydrophobe (redC), the molecular hydrophobicity (log P), the number of carbon atoms in the hydrophobe (C), the hydrophilic-lipophilic balance according to Davis (Davis), the critical packing parameter with respect to whether the hydrophobe was branched or not (redCPP), and the critical micelle concentration. Surfactant toxicity tended to increase with increasing alkyl chain lengths.

A series of 38 nonionic technical surfactants (ethoxylated fatty alcohols) has earlier been characterized by 19 different physicochemical descriptor variables (critical micelle concentration, critical packaging parameter, cloud point, etc.). The information content of the partly correlated variables was summarized by principal component analysis (PCA). This analysis showed that the surfactants were divided into subgroups according to their structure.The detergency performance toward nonpolar soil on textile was examined for a subset of the nonionic surfactants with the use of statistical experimental design. In the washing experiments, the surfactant concentration, the washing time, and the temperature were altered in a systematic way according to statistical experimental design. It was shown that the detergency effect reached a plateau at high values of the examined variable settings. The toxicity (LC50) of the nonionic surfactants were also tested with a cyst-based toxicity test with a fairy shrimp (Thamnocephalus platyurus).A joint multivariate quantitative structure-property and structure-activity relationship (QSP(A)R) with good predictive capability was determined with partial least squares (PLS) modeling. The model showed that variables that can be considered to measure equilibrium properties (e.g., critical micelle concentration, log P, and hydrophobic-hydrophilic balance) were the most influential ones to explain the LC50 values. The variables that can be considered to measure or influence dynamic properties (e.g., highest derivative of the transmittance-temperature curve dCP at the cloud point) were the most influential to describe the washing performance. The joint multivariate analysis showed that it was possible to find surfactants with high efficiency and low toxicity.

The toxicity of a number of non-ionic surfactants towards Thamnocephalus platyurus (sweet water fairy shrimp) has been examined. The measurements have been performed with the use of so-called Toxkits, and the results have been expressed both as a mean LC(50) value for each of the surfactants, and with a relative scale estimated using of multi dimensional scaling (MDS). An algorithm is shown in matlab code, with which it is possible to per form MDS on a difference matrix with a lot of systematically missing values. The thus obtained results have been combined with the physico-chemical data for the surfactants, and QSAR models have been estimated for the toxicity (log(LC(50))) of the surfactants. The physico-chemical properties with the main influence on the models were the hydrophilic-lipophilic-balance (HLB), the hydrophobicity (log P), the critical micellar concentration (CMC) and the number of carbon atoms in the hydrophobic part (C) of the surfactant.

The detergency effect of a series of technical nonionic surfactants has been examined. The detergency experiments have been performed according to different central composite circumscribed statistical designs. The data from the differently designed investigations were combined, and a response surface model was estimated for each surfactant with the use of partial least squares of latent structures. The combination of the designed series gave a new insight into the importance of a variable not considered before. The effects of different transformations and model complexities were investigated and a new approach to compare the efficiency of the different surfactants was found. In the evaluation of the individual designs all replicates were used in the calculations, while the evaluation of the combined designs was made with the use of the mean values of each experimental point. The reason for this is presented.

The detergency effect has been examined for a series of technical nonionic surfactants with the use of statistical experimental designs and revealed a plateau in each of the response surfaces obtained. The surfactant concentrations and washing temperatures, needed to reach the edge of each detergency effect plateau, were also determined. These conditions, which define the edge of the plateau, could be well modeled from the physicochemical properties of the surfactants with the use of partial least squares of latent structures. It was also possible to point out the importance of the different physicochemical properties. If an experimental design has been utilized, the detergency effect of a nonionic surfactant can be modeled from multiple linear regression as a function of surfactant concentration, washing time, and washing temperature. We have shown how these regression coefficients can be modeled from the physicochemical properties of the surfactants. Partial least squares of latent structures were used to estimate these models as well. We also demonstrated how these models can be used to predict the regression coefficients of a surfactant not included in the model estimations. The resultant regression coefficients can then be used to predict the detergency effects of this surfactant at different variable settings. The detergency effects thus obtained are in good agreement with measured data acquired under corresponding conditions.

A number of technical non-ionic surfactants have been characterized with the use of 18 different variables, both theoretical and experimental ones. A principal component analysis (PCA) was made on the collected data. Plotting the obtained score values against each other showed a clustering of the surfactants into five groups. The way the surfactants clustered was due to their structures, mainly the length of the ethylene oxide chain and the degree of branching in the hydrophobic part. With the use of partial least squares modelling of latent variables (PLS), it was also possible to model the critical micellar concentration (CMC) from the other physicochemical variables. The calculated and the observed CMC values were in good agreement provided that the calculations were done per surfactant group. Poor predictions were obtained when the CMC was modelled over all surfactants simultaneously. This indicates that the groups given by PCA are different classes of non-ionic surfactants.