Astrozyten erfüllen unverzichtbare Aufgaben im ZNS. Sie sorgen im Normalfall unter anderem für eine ausgewogene K+/H2O-Clearence, regulieren den Gefäßdurchmesser, bilden die Blut-/Hirnschranke, betreiben “Transmitter-Recycling” und modulieren die interneuronale Signalweitergabe durch prä- und postsynaptische Mechanismen. Die Funktionen und Einflüsse dieser zentralnervösen Gliazellen unter pathologischen Bedingungen im ZNS sind bei weitem nicht so gut untersucht, aber ebenso vielfältig. Eine ganz entscheidende Frage stellt sowohl unter physiologischen wie auch pathologischen Bedingungen das Vorliegen eines Überlappungsfaktors des von benachbarten Astrozyten okkupierten Areals dar. Betrüge ein solcher Faktor ! 1, könnten mehrere Gliazellen das gleiche Areal auch unter pathologischen Bedingungen durch ihre vielfältigen Funktionen unterstützen. Dahingegen würde das Ausbleiben eines Überlappungsgrades ! 1 bedeuten, dass bestimmte Gebiete im Neuropil anfälliger gegen Noxen oder degenerative Veränderungen wären. Um diesen Überlappungsgrad zu untersuchen, wurden Hirnschnitte von Labormäusen mittels einer geeigneten Methodenkombination untersucht. Dabei wurde das durchschnittliche Volumen der Astrozyten im motorischen Kortex durch Golgi- Färbung, sowie deren Zellzahl pro Volumeneinheit durch immunhistochemische Färbungen untersucht und mittels konfokaler Laserscanning-Mikroskopie dokumentiert. Aus diesen Parametern ließ sich ferner der durchschnittliche Überlappungsfaktor im beschriebenen Areal berechnen. Im Interesse dieser Arbeit standen dabei neben dem Unterschied im Überlappungsfaktor der Astrozyten zwischen Wildtyp- und GFAP-/- VIM-/- Knockout- Mäusen, als Beispiel für ein genetisch bedingtes Fehlen dieser Intermediärfilamente, auch der Einfluss des fortschreitenden Lebensalters, so dass für beide Genotypen sowohl junge- als auch alte Tiere untersucht wurden. Folgende Ergebnisse lassen sich zusammenfassen: 1. Das Vorhandensein der Intermediärfilamente GFAP und Vimentin scheint keinen Einfluss auf das Volumen der Astrozyten im motorischen Kortex zu haben. 2. Das Lebensalter der V ersuchstiere steht mit dem V olumen der Astrozyten signifikant in Zusammenhang. Das von Astrozytenfortsätzen der knapp zwei Jahre alten Tiere okkupierte Volumen betrug mit durchschnittlich ca. 61.000 !m3 gut das Doppelte des Volumens in jungen Mäusen (ca. 28.000 !m3). 3. Die Zellzahl der Astrozyten im motorischen Kortex wird offenbar weder vom Lebensalter, noch vom Vorhandensein der Intermediärfilamente GFAP und Vimentin signifikant beeinflusst. 4. Der Überlappungsfaktor der Astrozyten im motorischen Kortex lag bei den jungen Kontroll-Tieren bei 0,87 und bei den jungen DKO-Tieren bei 0,96. 5. Der Überlappungsfaktor der Astrozyten im motorischen Kortex lag bei den alten Kontroll-Tieren bei 2,22 und bei den alten DKO-Tieren bei 2,10. Die Ergebnisse zeigen, dass das Fehlen der Intermediärfilamente GFAP und Vimentin keinen Einfluss auf den Überlappungsgrad der Astrozyten im motorischen Kortex hat. Die Ursache für phänotypisch manifeste Erkrankungen, wie z.B. der Alexander Krankheit, welche durch ein fehlerhaft exprimiertes GFAP in Astrozyten hervorgerufen wird, ist demnach in anderen Mechanismen zu suchen. Großen Einfluss auf den Überlappungsfaktor der Astrozyten hatte dagegen das Lebensalter der Versuchstiere, was sich mit neueren Erkenntnissen zur Funktion der Astrozyten im Hinblick auf Lernvorgänge, aber auch auf degenerative Prozesse, in Zusammenhang bringen lässt.

Astrozyten erfüllen unverzichtbare Aufgaben im ZNS. Sie sorgen im Normalfall unter anderem für eine ausgewogene K+/H2O-Clearence, regulieren den Gefäßdurchmesser, bilden die Blut-/Hirnschranke, betreiben “Transmitter-Recycling” und modulieren die interneuronale Signalweitergabe durch prä- und postsynaptische Mechanismen. Die Funktionen und Einflüsse dieser zentralnervösen Gliazellen unter pathologischen Bedingungen im ZNS sind bei weitem nicht so gut untersucht, aber ebenso vielfältig. Eine ganz entscheidende Frage stellt sowohl unter physiologischen wie auch pathologischen Bedingungen das Vorliegen eines Überlappungsfaktors des von benachbarten Astrozyten okkupierten Areals dar. Betrüge ein solcher Faktor ! 1, könnten mehrere Gliazellen das gleiche Areal auch unter pathologischen Bedingungen durch ihre vielfältigen Funktionen unterstützen. Dahingegen würde das Ausbleiben eines Überlappungsgrades ! 1 bedeuten, dass bestimmte Gebiete im Neuropil anfälliger gegen Noxen oder degenerative Veränderungen wären. Um diesen Überlappungsgrad zu untersuchen, wurden Hirnschnitte von Labormäusen mittels einer geeigneten Methodenkombination untersucht. Dabei wurde das durchschnittliche Volumen der Astrozyten im motorischen Kortex durch Golgi- Färbung, sowie deren Zellzahl pro Volumeneinheit durch immunhistochemische Färbungen untersucht und mittels konfokaler Laserscanning-Mikroskopie dokumentiert. Aus diesen Parametern ließ sich ferner der durchschnittliche Überlappungsfaktor im beschriebenen Areal berechnen. Im Interesse dieser Arbeit standen dabei neben dem Unterschied im Überlappungsfaktor der Astrozyten zwischen Wildtyp- und GFAP-/- VIM-/- Knockout- Mäusen, als Beispiel für ein genetisch bedingtes Fehlen dieser Intermediärfilamente, auch der Einfluss des fortschreitenden Lebensalters, so dass für beide Genotypen sowohl junge- als auch alte Tiere untersucht wurden. Folgende Ergebnisse lassen sich zusammenfassen: 1. Das Vorhandensein der Intermediärfilamente GFAP und Vimentin scheint keinen Einfluss auf das Volumen der Astrozyten im motorischen Kortex zu haben. 2. Das Lebensalter der V ersuchstiere steht mit dem V olumen der Astrozyten signifikant in Zusammenhang. Das von Astrozytenfortsätzen der knapp zwei Jahre alten Tiere okkupierte Volumen betrug mit durchschnittlich ca. 61.000 !m3 gut das Doppelte des Volumens in jungen Mäusen (ca. 28.000 !m3). 3. Die Zellzahl der Astrozyten im motorischen Kortex wird offenbar weder vom Lebensalter, noch vom Vorhandensein der Intermediärfilamente GFAP und Vimentin signifikant beeinflusst. 4. Der Überlappungsfaktor der Astrozyten im motorischen Kortex lag bei den jungen Kontroll-Tieren bei 0,87 und bei den jungen DKO-Tieren bei 0,96. 5. Der Überlappungsfaktor der Astrozyten im motorischen Kortex lag bei den alten Kontroll-Tieren bei 2,22 und bei den alten DKO-Tieren bei 2,10. Die Ergebnisse zeigen, dass das Fehlen der Intermediärfilamente GFAP und Vimentin keinen Einfluss auf den Überlappungsgrad der Astrozyten im motorischen Kortex hat. Die Ursache für phänotypisch manifeste Erkrankungen, wie z.B. der Alexander Krankheit, welche durch ein fehlerhaft exprimiertes GFAP in Astrozyten hervorgerufen wird, ist demnach in anderen Mechanismen zu suchen. Großen Einfluss auf den Überlappungsfaktor der Astrozyten hatte dagegen das Lebensalter der Versuchstiere, was sich mit neueren Erkenntnissen zur Funktion der Astrozyten im Hinblick auf Lernvorgänge, aber auch auf degenerative Prozesse, in Zusammenhang bringen lässt.:BIBLIOGRAPHISCHE BESCHREIBUNG 1 INHALTSVERZEICHNIS 2 VERZEICHNIS DER ABKÜRZUNGEN 5 1. EINLEITUNG UND FRAGESTELLUNG 6 1.1 Das ZNS / Der Kortex 6 1.2 Gliazellen 9 1.2.1 Astrozyten 10 1.2.1.1 Morphologie / Morphometrie 10 1.2.1.2 Funktionen 12 1.2.1.3 reaktive Astrozyten 13 1.3 Intermediärfilamente 14 1.3.1 Funktionen 17 1.3.2 Intermediärfilamente und Zellwachstum 18 1.4 Ziel der Arbeit 19 2. MATERIAL UND METHODEN 24 2.1 Die Versuchstiere 24 2.2 Golgi-Färbungen 25 2.3 Immunhistochemische Färbungen 26 2.3.1 Die indirekte Nachweismethode 27 2.4 Das konfokale Mikroskop 28 2.5 Mikroskopische Untersuchung 30 2.5.1 Untersuchung der Volumina 30 2.5.2 Untersuchung der Zellzahlen 32 2.6 Bildauswertung 34 2.6.1 Volumenmessung / Golgi-Präparate 34 2.6.2 Zellzahl / Immunhistochemie 37 2.7 Berechnungen / Überlappungsfaktor / Statistische Auswertung 38 3. ERGEBNISSE 40 3.1 Volumina der Astrozyten 40 3.2 Zellzahl der Astrozyten 45 3.3 Der Überlappungsfaktor 48 3.4 Zusammenfassung 51 4. DISKUSSION 52 4.1 Kritik an der Methodik 52 4.1.1 Golgi-Färbungen zur Volumenmessung 52 4.1.2 S100-ß als Marker zur Zellzahl-Bestimmung 53 4.1.3 Schrumpfung der Präparate 54 4.2 Einordnung der Ergebnisse in die Literatur / Schlussfolgerungen 56 5. ZUSAMMENFASSUNG 60 6. LITERATUR 64 SELBSTSTÄNDIGKEITSERKLÄRUNG 68 LEBENSLAUF 69 DANKSAGUNG 71

In addition to occasional opportunistic colonization of the oral mucosa, Candida albicans is frequently found in carious dentin. The yeast’s potential to induce dental caries as a consequence of its pronounced ability to produce and tolerate acids was investigated. Eighty caries-active Osborne-Mendel rats were raised on an ampicillin-supplemented diet and exposed to C. albicans and/or Streptococcus mutans, except for controls. Throughout the 28-day test period, the animals were offered the modified cariogenic diet 2000a, containing 40% various sugars. Subsequently, maxillary molars were scored for plaque extent. After dissection, the mandibular molars were evaluated for smooth surface and fissure caries. Test animals exposed to C. albicans displayed considerably more advanced fissure lesions (p < 0.001) than non-exposed controls. While S. mutans yielded similar results, a combined association of C. albicans and S. mutans had no effect on occlusal caries incidence. Substituting dietary sucrose by glucose did not modify caries induction by C. albicans. However, animals fed a diet containing 20% of both sugars showed no differences to non-infected controls. Smooth surface caries was not generated by the yeast. This study provides experimental evidence that C. albicans is capable of causing occlusal caries in rats at a high rate. / Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.

In addition to occasional opportunistic colonization of the oral mucosa, Candida albicans is frequently found in carious dentin. The yeast’s potential to induce dental caries as a consequence of its pronounced ability to produce and tolerate acids was investigated. Eighty caries-active Osborne-Mendel rats were raised on an ampicillin-supplemented diet and exposed to C. albicans and/or Streptococcus mutans, except for controls. Throughout the 28-day test period, the animals were offered the modified cariogenic diet 2000a, containing 40% various sugars. Subsequently, maxillary molars were scored for plaque extent. After dissection, the mandibular molars were evaluated for smooth surface and fissure caries. Test animals exposed to C. albicans displayed considerably more advanced fissure lesions (p < 0.001) than non-exposed controls. While S. mutans yielded similar results, a combined association of C. albicans and S. mutans had no effect on occlusal caries incidence. Substituting dietary sucrose by glucose did not modify caries induction by C. albicans. However, animals fed a diet containing 20% of both sugars showed no differences to non-infected controls. Smooth surface caries was not generated by the yeast. This study provides experimental evidence that C. albicans is capable of causing occlusal caries in rats at a high rate. / Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.

Sizing (hydrophobization) is one of the most important process steps within the added-value chain of about 1/3rd of the worldwide produced paper & board products. Even though sizing with so-called reactive sizing agents, such as alkenyl succinic anhydride (ASA) was implemented in the paper industry decades ago, there is no total clarity yet about the detailed chemical and physical mechanisms that lead to their performance. Previous research was carried out on the role of different factors influencing the sizing performance, such as bonding between ASA and cellulose, ASA hydrolysis, size revision as well as the most important interactions with stock components, process parameters and additives during the paper making process. However, it was not yet possible to develop a holistic model for the explanation of the sizing performance given in real life application. This thesis describes a novel physico-chemical approach to this problem by including results from previous research and combining these with a wide field of own basic research and a newly developed method that allows tracing back the actual localization of ASA within the sheet structure. The carried out measurements and trial sets for the basic field of research served to evaluate the stock and process parameters that most dominantly influence the sizing performance of ASA. Interactions with additives other than retention aids were not taken into account. The results show that parameters, such as the content of secondary fibers, the degree of refining, the water hardness as well as the suspension conductivity, are of highest significance. The sample sets of the trials with the major impacting parameters were additionally analyzed by a newly developed localization method in order to better understand the main influencing factors. This method is based on optical localization of ASA within the sheet structure by confocal white light microscopy. In order to fulfill the requirements at magnification rates of factor 100 optical zoom, it was necessary to improve the contrast between ASA and cellulose. Therefore, ASA was pretreated with an inert red diazo dye, which does not have any impact on neither the sizing nor the handling properties of ASA. Laboratory hand sheets that were sized with dyed ASA, were analyzed by means of their sizing performance in correlation to measurable ASA agglomerations in the sheet structure. The sizing performance was measured by ultrasonic penetration analysis. The agglomeration behavior of ASA was analyzed automatically by multiple random imaging of a sample area of approx. 8650 µm² with a minimum resolution for particles of 500 nm in size. The gained results were interpreted by full factorial design of experiments (DOE). The trials were carried out with ASA dosages between 0% and 0.8% on laboratory hand sheets, made of 80% bleached eucalyptus short fiber kraft pulp and 20% northern bleached softwood kraft pulp, beaten to SR° 30, produced with a RDA sheet former at a base weight of 100 g/m² oven dry. The results show that there is a defined correlation between the ASA dosage, the sizing performance and the number and area of ASA agglomerates to be found in the sheet structure. It was also possible to show that the agglomeration behavior is highly influenced by external factors like furnish composition and process parameters. This enables a new approach to the explanation of sizing performance, by making it possible to not only examine the performance of the sizing agent, but to closely look at the predominant position where it is located in the sheet structure. These results lead to the explanation that the phenomenon of sizing is by far not a pure chemical process but rather a more physical one. Based on the gained findings it was possible so far to optimize the ASA sizing process in industrial-scale by means of ~ 50% less ASA consumption at a steady degree of sizing and improved physical sheet properties.

Sizing (hydrophobization) is one of the most important process steps within the added-value chain of about 1/3rd of the worldwide produced paper & board products. Even though sizing with so-called reactive sizing agents, such as alkenyl succinic anhydride (ASA) was implemented in the paper industry decades ago, there is no total clarity yet about the detailed chemical and physical mechanisms that lead to their performance. Previous research was carried out on the role of different factors influencing the sizing performance, such as bonding between ASA and cellulose, ASA hydrolysis, size revision as well as the most important interactions with stock components, process parameters and additives during the paper making process. However, it was not yet possible to develop a holistic model for the explanation of the sizing performance given in real life application. This thesis describes a novel physico-chemical approach to this problem by including results from previous research and combining these with a wide field of own basic research and a newly developed method that allows tracing back the actual localization of ASA within the sheet structure. The carried out measurements and trial sets for the basic field of research served to evaluate the stock and process parameters that most dominantly influence the sizing performance of ASA. Interactions with additives other than retention aids were not taken into account. The results show that parameters, such as the content of secondary fibers, the degree of refining, the water hardness as well as the suspension conductivity, are of highest significance. The sample sets of the trials with the major impacting parameters were additionally analyzed by a newly developed localization method in order to better understand the main influencing factors. This method is based on optical localization of ASA within the sheet structure by confocal white light microscopy. In order to fulfill the requirements at magnification rates of factor 100 optical zoom, it was necessary to improve the contrast between ASA and cellulose. Therefore, ASA was pretreated with an inert red diazo dye, which does not have any impact on neither the sizing nor the handling properties of ASA. Laboratory hand sheets that were sized with dyed ASA, were analyzed by means of their sizing performance in correlation to measurable ASA agglomerations in the sheet structure. The sizing performance was measured by ultrasonic penetration analysis. The agglomeration behavior of ASA was analyzed automatically by multiple random imaging of a sample area of approx. 8650 µm² with a minimum resolution for particles of 500 nm in size. The gained results were interpreted by full factorial design of experiments (DOE). The trials were carried out with ASA dosages between 0% and 0.8% on laboratory hand sheets, made of 80% bleached eucalyptus short fiber kraft pulp and 20% northern bleached softwood kraft pulp, beaten to SR° 30, produced with a RDA sheet former at a base weight of 100 g/m² oven dry. The results show that there is a defined correlation between the ASA dosage, the sizing performance and the number and area of ASA agglomerates to be found in the sheet structure. It was also possible to show that the agglomeration behavior is highly influenced by external factors like furnish composition and process parameters. This enables a new approach to the explanation of sizing performance, by making it possible to not only examine the performance of the sizing agent, but to closely look at the predominant position where it is located in the sheet structure. These results lead to the explanation that the phenomenon of sizing is by far not a pure chemical process but rather a more physical one. Based on the gained findings it was possible so far to optimize the ASA sizing process in industrial-scale by means of ~ 50% less ASA consumption at a steady degree of sizing and improved physical sheet properties.:Acknowledgment I Abstract III Table of Content V List of Illustrations XI List of Tables XVI List of Formulas XVII List of Abbreviations XVIII 1 Introduction and Problem Description 1 1.1 Initial Situation 1 1.2 Objective 2 2 Theoretical Approach 3 2.1 The Modern Paper & Board Industry on the Example of Germany 3 2.1.1 Raw Materials for the Production of Paper & Board 5 2.2 The Sizing of Paper & Board 8 2.2.1 Introduction to Paper & Board Sizing 8 2.2.2 The Definition of Paper & Board Sizing 10 2.2.3 The Global Markets for Sized Paper & Board Products and Sizing Agents 11 2.2.4 Physical and Chemical Background to the Mechanisms of Surface-Wetting and Penetration 13 2.2.4.1 Surface Wetting 14 2.2.4.2 Liquid Penetration 15 2.2.5 Surface and Internal Sizing 17 2.2.6 Sizing Agents 18 2.2.6.1 Alkenyl Succinic Anhydride (ASA) 19 2.2.6.2 Rosin Sizes 19 2.2.6.3 Alkylketen Dimer (AKD) 23 2.2.6.4 Polymeric Sizing Agents (PSA) 26 2.2.7 Determination of the Sizing Degree (Performance Analysis) 28 2.2.7.1 Cobb Water Absorption 29 2.2.7.2 Contact Angle Measurement 30 2.2.7.3 Penetration Dynamics Analysis 31 2.2.7.4 Further Qualitative Analysis Methods 33 2.2.7.4.1 Ink Stroke 33 2.2.7.4.2 Immersion Test 33 2.2.7.4.3 Floating Test 34 2.2.7.4.4 Hercules Sizing Tester (HST) 34 2.2.8 Sizing Agent Detection (Qualitative Analysis) and Determination of the Sizing Agent Content (Quantitative Analysis) 35 2.2.8.1 Destructive Methods 35 2.2.8.2 Non Destructive Methods 36 2.3 Alkenyl Succinic Anhydride (ASA) 36 2.3.1.1 Chemical Composition and Production of ASA 37 2.3.1.2 Mechanistic Reaction Models 39 2.3.1.3 ASA Application 42 2.3.1.3.1 Emulsification 42 2.3.1.3.2 Dosing 44 2.3.1.4 Mechanistic Steps of ASA Sizing 46 2.3.2 Physico-Chemical Aspects during ASA Sizing 48 2.3.2.1 Reaction Plausibility 48 2.3.2.1.1 Educt-Product Balance / Kinetics 48 2.3.2.1.2 Energetics 51 2.3.2.1.3 Sterics 52 2.3.2.2 Phenomena based on Sizing Agent Mobility 53 2.3.2.2.1 Sizing Agent Orientation 54 2.3.2.2.2 Intra-Molecular Orientation 55 2.3.2.2.3 Sizing Agent Agglomeration 55 2.3.2.2.4 Fugitive Sizing / Sizing Loss / Size Reversion 56 2.3.2.2.5 Sizing Agent Migration 58 2.3.2.2.6 Sizing Reactivation / Sizing Agent Reorientation 59 2.3.3 Causes for Interactions during ASA Sizing 60 2.3.3.1 Process Parameters 61 2.3.3.1.1 Temperature 61 2.3.3.1.2 pH-Value 62 2.3.3.1.3 Water Hardness 63 2.3.3.2 Fiber Types 64 2.3.3.3 Filler Types 65 2.3.3.4 Cationic Additives 66 2.3.3.5 Anionic Additives 67 2.3.3.6 Surface-Active Additives 68 2.4 Limitations of State-of-the-Art ASA-Sizing Analysis 69 2.5 Optical ASA Localization 71 2.5.1 General Background 71 2.5.2 Confocal Microscopy 72 2.5.2.1 Principle 72 2.5.2.2 Features, Advantage and Applicability for Paper-Component Analysis 74 2.5.3 Dying / Staining 75 3 Discussion of Results 77 3.1 Localization of ASA within the Sheet Structure 77 3.1.1 Choice of Dyes 77 3.1.1.1 Dye Type 78 3.1.1.2 Evaluation of Dye/ASA Mixtures 80 3.1.1.2.1 Maximum Soluble Dye Concentration 80 3.1.1.2.2 Thin Layer Chromatography 81 3.1.1.2.3 FTIR-Spectroscopy 82 3.1.1.3 Evaluation of the D-ASA Emulsion 84 3.1.1.4 Paper Chromatography with D-ASA & F-ASA Emulsions 85 3.1.1.5 Evaluation of the D-ASA Emulsion’s Sizing Efficiency 86 3.1.2 The Localization Method 87 3.1.2.1 The Correlation between ASA Distribution and Agglomeration 88 3.1.2.2 Measurement Settings 89 3.1.2.3 Manual Analysis 90 3.1.2.4 Automated Analysis 92 3.1.2.4.1 Automated Localization / Microscopy Measurement 92 3.1.2.4.2 Automated Analysis / Image-Processing 93 3.1.2.5 Result Interpretation and Example Results 96 3.1.2.6 Reproducibility 97 3.1.2.7 Sample Mapping 98 3.1.3 Approaches to Localization-Method Validation 102 3.1.3.1 Raman Spectroscopy 102 3.1.3.2 Confocal Laser Scanning Fluorescent Microscopy 102 3.1.3.3 Decolorization 103 3.2 Factors Impacting the Sizing Behavior of ASA 104 3.2.1 ASA Type 105 3.2.2 Emulsion Parameters 107 3.2.2.1 Hydrolyzed ASA Content 107 3.2.2.2 ASA/Starch Ratio 109 3.2.2.3 Emulsion Age 110 3.2.3 Stock Parameters 111 3.2.3.1 Long Fiber/Short Fiber Ratio 111 3.2.3.2 Furnish Type 112 3.2.3.3 Degree of Refining 114 3.2.3.4 Filler Type/Content 116 3.2.4 Process Parameters 119 3.2.4.1 Temperature 119 3.2.4.2 pH-Value 120 3.2.4.3 Conductivity 122 3.2.4.4 Water Hardness 123 3.2.4.5 Shear Rate 125 3.2.4.6 Dwell Time 127 3.2.4.7 Dosing Position & Dosing Order 128 3.2.4.8 Drying 130 3.2.4.9 Aging 131 3.3 Factors Impacting the Localization Behavior of ASA 132 3.3.1 Degree of Refining 132 3.3.2 Sheet Forming Conductivity 135 3.3.3 Water Hardness 136 3.3.4 Retention Aid (PAM) 137 3.3.5 Contact Curing 138 3.3.6 Accelerated Aging 139 3.4 Main Optimization Approach 141 3.4.1 Optimization of ASA Sizing Performance Characteristics 142 3.4.2 Emulsion Modification 144 3.4.2.1 Lab Trials / RDA Sheet Forming 146 3.4.2.2 TPM Trials 147 3.4.2.3 Industrial-Scale Trials 149 3.4.2.4 Correlation between Sizing Performance Optimization and Agglomeration Behavior on the Example of PAAE 152 3.5 Holistic Approach to Sizing Performance Explanation 154 4 Experimental Approach 157 4.1 Characterization of Methods, Measurements and Chemicals used for the Optical Localization-Analysis of ASA 157 4.1.1 Characterization of used Chemicals 157 4.1.1.1 Preparation of Dyed-ASA Solutions 157 4.1.1.2 Thin Layer Chromatography 157 4.1.1.3 Fourier Transformed Infrared Spectroscopy 157 4.1.1.4 Emulsification of ASA 158 4.1.1.5 Paper Chromatography 159 4.1.1.6 Particle Size Measurement 159 4.1.2 Optical Analysis of ASA Agglomerates 160 4.1.2.1 Microscopy 160 4.1.2.2 Automated Analysis 163 4.1.2.2.1 Adobe Photoshop 163 4.1.2.2.2 Adobe Illustrator 164 4.1.2.3 Confocal Laser Scanning Fluorescent Microscopy 166 4.2 Characterization of Used Standard Methods and Measurements 166 4.2.1 Stock and Paper Properties 166 4.2.1.1 Stock pH, Conductivity and Temperature Measurement 166 4.2.1.2 Dry Content / Consistency Measurement 167 4.2.1.3 Drainability (Schopper-Riegler) Measurement 167 4.2.1.4 Base Weight Measurement 168 4.2.1.5 Ultrasonic Penetration Measurement 168 4.2.1.6 Contact Angle Measurement 169 4.2.1.1 Cobb Measurement 169 4.2.1.2 Air Permeability Measurements 170 4.2.1.3 Tensile Strength Measurements 170 4.2.2 Preparation of Sample Sheets 171 4.2.2.1 Stock Preparation 171 4.2.2.2 Laboratory Refining (Valley Beater) 171 4.2.2.3 RDA Sheet Forming 171 4.2.2.4 Additive Dosing 173 4.2.2.5 Contact Curing 174 4.2.2.6 Hot Air Curing 174 4.2.2.7 Sample Aging 174 4.2.2.8 Preparation of Hydrolyzed ASA 175 4.2.2.9 Trial Paper Machine 175 4.2.2.10 Industrial-Scale Board Machine 177 4.3 Characterization of used Materials 178 4.3.1 Fibers 178 4.3.1.1 Reference Stock System 178 4.3.1.2 OCC Fibers 179 4.3.1.3 DIP Fibers 179 4.3.2 Fillers 180 4.3.3 Chemical Additives 180 4.3.3.1 ASA 180 4.3.3.2 Starches 181 4.3.3.3 Retention Aids 181 4.3.3.4 Poly Aluminum Compounds 181 4.3.3.5 Wet Strength Resin 181 4.3.4 Characterization of used Additives 182 4.3.4.1 Solids Content 182 4.4 Description of Implemented Advanced Data Analysis- and Visualization Methods 183 4.4.1 Design of Experiments (DOE183 4.4.2 Contour Plots 184 4.4.3 Box-Whisker Graphs 185 5 Conclusion 186 6 Outlook for Further Work 191 7 Bibliography 192 Appendix 207 7.1 Localization Method Reproducibility 207 7.2 DOE - Coefficient Lists 208 7.2.1 Trial 3.3.4 – Impact of Retention Aid (PAM) on Agglomeration Behavior and Sizing Performance 208 7.2.2 Trial 3.3.5 – Impact of Contact Curing on Agglomeration Behavior and Sizing Performance 208 7.2.3 Trial 3.3.6 – Impact of Accelerated Aging on Agglomeration Behavior and Sizing Performance 209