Pulp Uniformity Measurement of Single Fiber Properties

FIVE MILLION PULP FIBERS A HANDFULL OF PULP IS A LOT OF FIBERS

The distribution of single fiber properties has a significant affect on the properties and performance of pulp, paper, and absorbent products. This is difficult to prove or to take advantage of without single fiber measurements. AN HYPOTHESIS

Single Fiber Properties Kappa Length Kink Curl Surface Charge Cell Wall Thickness Fiber Performance / Pulp Behavior

Objectives Develop an optical method for measuring single fiber chemical properties such as kappa number and charge. Develop an optical method for measuring single fiber chemical properties such as kappa number and charge. Build an instrument capable of performing the analysis quickly on many fibers. Build an instrument capable of performing the analysis quickly on many fibers. Apply instrument to assess pulping uniformity and the relationship between pulp uniformity and pulp performance. Apply instrument to assess pulping uniformity and the relationship between pulp uniformity and pulp performance.

Fluorescent Probes Fluorescent probes may be used to investigate chemistry of fibers, mammalian cells, or other small particles Fluorescent probes may be used to investigate chemistry of fibers, mammalian cells, or other small particles High signal-to-noise High signal-to-noise Flow cytometry application Flow cytometry application Fluorescence response to substrate chemical environment Fluorescence response to substrate chemical environment Emission Spectral Shift – Kappa measurement Emission Spectral Shift – Kappa measurement Emission Intensity Shift – Charge measurement Emission Intensity Shift – Charge measurement

Single Fiber Kappa Measurement

Why pulp kappa uniformity is important ?  Brownstock pulp strength  Bleaching cost  Target kappa limitations Mean

Acridine Orange Stained Cellulose Fibers Green = 14 kappa Orange = 32 kappa Red = 83 kappa

AO Fluorescence Spectra for Fibers of Different Kappas

Change in Acridine Orange Fluorescence Ratio with Kappa for Three Wood Species kappa Red/Green Ratio D. Fir S. Pine Eucalyptus

Epi-Illumination Flow Cytometer

Fibers in Fibers out Light Source Flow Cell Condensing lens and Bandpass Filter Dichroic Mirrors Red CCD Bandpass Filters Green CCD Green Intensity = ### Red Intensity = ###

Epi-Illumination Flow Cytometer

Instrument Operation Sample preparation ~10 minutes Sample preparation ~10 minutes Instrument collects images, applies image processing algorithms ~ 10 min. Instrument collects images, applies image processing algorithms ~ 10 min. Statistics on fibers Statistics on fibers

Instrument Performance Evaluation of instrument noise Evaluation of instrument noise Reproduce fluorescence microscope results Reproduce fluorescence microscope results Comparison with independent method Comparison with independent method Kappa distribution measured at IPST with a density gradient column Kappa distribution measured at IPST with a density gradient column

Measurement Noise Standard fluorescent beads: 6.5% CV Propagates to +-1 kappa for kappa 30 fiber

Red/Green Fluorescence vs. Kappa for IPST Samples

Uniformity of Laboratory and Commercial Pulps

Statistical Representation of Pulp Uniformity Coefficient of variation Coefficient of variation (COV) (COV) gamma one gamma one Gamma one ~ 0 Gamma one= 1.89

Softwood and Hardwood Pulps Hardwood Hardwood COV ~ COV ~ gamma one ~ gamma one ~ Softwood Softwood COV ~ COV ~ gamma one ~ gamma one ~ COV=0.41 Gamma one =1.89 COV=0.39 Gamma one =0.19

Commercial vs. Laboratory Pulps COV=0.54 Gamma one= 1.6 COV=0.34 Gamma one =1.59

Effect of Chip Thickness on Hardwood Pulps

Effect of Enzyme pretreatment on Hardwood Pulps

Effect of pre-steaming and pressure COV= 0.27 Gamma one =1.42 COV= 0.31 Gamma one =1.29 COV= 0.41 Gamma one =1.89

Effect of Pulping Temperature SuperBatch softwood pulps SuperBatch softwood pulps Cooking temperature: 168ºC vs. 176 ºC Cooking temperature: 168ºC vs. 176 ºC Varied temperature and time at temperature to reach target Kappa (~20) Varied temperature and time at temperature to reach target Kappa (~20) ‘time to temperature’, and chip thickness distribution also varied, but not controlled. ‘time to temperature’, and chip thickness distribution also varied, but not controlled. 68 samples were analyzed 68 samples were analyzed

Results Linear regression analysis to investigate correlation between COV and cooking variables; temperature,time to temperature,thick chip percentage,thin chip percentage Linear regression analysis to investigate correlation between COV and cooking variables; temperature,time to temperature,thick chip percentage,thin chip percentage Regression model for all 68 trials

Linear regression analysis for all 68 trials  Temperature has a major effect on pulp uniformity  Temperature and time to temperature are correlated. Hence, analysis should split into low (~168ºC) and high temperature (~176ºC) groups Relative effect of individual variables

Linear regression model, low temperature (~168ºC) trials Effect of variables at low temperature Linear regression model, high temperature (~176ºC) trials Effect of variables at high temperature

Effect of temperature and ‘time to temperature’ COV=0.45 COV= 0.55 COV=0.48 COV= 0.54

Pulp uniformity from different digesters

Single Fiber Charge Measurement

Why is Fiber Charge Important? Charge facilitates retaining papermaking additives and fines Charge facilitates retaining papermaking additives and fines Better economics Better economics Lower environmental impact Lower environmental impact Charge has a profound effect on paper formation Charge has a profound effect on paper formation Poor formation leads to poor appearance Poor formation leads to poor appearance Uneven distribution of papermaking materials affects function (printing, absorbency, etc.) Uneven distribution of papermaking materials affects function (printing, absorbency, etc.) Drainage on papermachine Drainage on papermachine

Monitoring and Controlling Charge Bulk Solution Measurements Bulk Solution Measurements Titration techniques with cationic chemicals Titration techniques with cationic chemicals Assume uniform charge between particles Assume uniform charge between particles Electrokinetic Methods Electrokinetic Methods Differences in charge between single particles Differences in charge between single particles Many assumptions: Many assumptions: Electrophoresis: fines only; spherical particles; etc. Electrophoresis: fines only; spherical particles; etc. Electro Kinetic Analyzer (EKA): bulk solution Electro Kinetic Analyzer (EKA): bulk solution Poor correlation with bulk titration results Poor correlation with bulk titration results

Stain Selection Charge-Sensitive Cationic Stain Charge-Sensitive Cationic Stain

Charge-Sensitive Stains

Stain Selection Charge-Sensitive Cationic Stain Charge-Sensitive Cationic Stain MQAE (Blue 460nm Emission) MQAE (Blue 460nm Emission) Charge-Insensitive Reference Stain Charge-Insensitive Reference Stain Acridine Orange (Red 630nm Emission) Acridine Orange (Red 630nm Emission)

Charge IN-sensitive Stain

HIGH CHARGE FIBERS 0.29meq/g LOW CHARGE FIBERS 0.03meq/g Charge-Sensitive Blue Stain - MQAENOT Charge-Sensitive Red Stain - AO

Calibration Blue/Red Emission vs. Mean Fiber Charge

Epi-Illumination Flow Cytometer Fibers in Fibers out Light Source Flow Cell Condensing lens and Bandpass Filter Dichroic Mirrors Red CCD Bandpass Filters Green Intensity = ### Red Intensity = ### Blue CCD

Charge Distribution Charge, meq/g

Commercial Fiber Analyzer