Pulp Uniformity Measurement of Single Fiber Properties

Pulp UniformityPulp Uniformity

Measurement of SingleMeasurement of Single Fiber Properties 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 PropertiesSingle Fiber Properties

Kappa Length Kink CurlSurface Charge Cell Wall Thickness

Fiber Performance / Pulp Behavior

ObjectivesObjectives

Develop an optical method for Develop an optical method for measuring single fiber chemical measuring single fiber chemical properties such as kappa number and properties such as kappa number and charge. charge.

Build an instrument capable of Build an instrument capable of performing the analysis quickly on performing the analysis quickly on many fibers.many fibers.

Apply instrument to assess pulping Apply instrument to assess pulping uniformity and the relationship between uniformity and the relationship between pulp uniformity and pulp performance.pulp uniformity and pulp performance.

Fluorescent ProbesFluorescent Probes

Fluorescent probes may be used to Fluorescent probes may be used to investigate chemistry of fibers, mammalian investigate chemistry of fibers, mammalian cells, or other small particlescells, or other small particles High signal-to-noiseHigh signal-to-noise Flow cytometry applicationFlow cytometry application

Fluorescence response to substrate Fluorescence response to substrate chemical environmentchemical environment Emission Spectral Shift – Kappa measurementEmission Spectral Shift – Kappa measurement Emission Intensity Shift – Charge measurementEmission Intensity Shift – Charge measurement

Single Fiber Kappa Single Fiber Kappa MeasurementMeasurement

Why pulp kappa uniformity is important ?

Brownstock pulp strength

Bleaching cost

Target kappa limitations

Fiber kappa distribution of a kappa 34.4 softwood pulp

0

5

10

15

20

25

0 10 20 30 40 50 60 70 80 90 100

kappa

% fi

bers

Mean

Acridine Orange Stained Acridine Orange Stained Cellulose FibersCellulose Fibers

Green = 14 kappa Orange = 32 kappa Red = 83 kappa

AO Fluorescence Spectra AO Fluorescence Spectra for Fibers of Different for Fibers of Different

KappasKappas

Change in Acridine Orange Change in Acridine Orange Fluorescence Ratio with Kappa for Fluorescence Ratio with Kappa for

Three Wood SpeciesThree Wood Species

0.00

0.50

1.00

1.50

2.00

2.50

3.00

0 20 40 60 80 100

kappa

Red

/Gre

en R

atio

D. Fir

S. PineEucalyptus

Epi-Illumination Flow Cytometer

0

1

1

2

2

3

3

4

4

5

5

0 10 20 30 40 50 60 70

kappa

Re

d/G

ree

n

Finnish pine,continuous digester

Finnish pine,SuperBatch digester

Southern pine,laboratory cooked, UW

Southern pine,laboratory cooked,IPST

Epi-Illumination Flow Epi-Illumination Flow CytometerCytometer

Fibers in

Fibers out

Light Source

Flow Cell

Condensing lens and Bandpass Filter

Dichroic MirrorsRed CCD

Bandpass Filters

Green CCD

Green Intensity = ###

Red Intensity = ###

Epi-Illumination Flow Cytometer

Instrument OperationInstrument Operation

Sample preparation ~10 minutesSample preparation ~10 minutes Instrument collects images, applies Instrument collects images, applies

image processing algorithms ~ 10 image processing algorithms ~ 10 min.min.

Statistics on 1000 - 2000 fibersStatistics on 1000 - 2000 fibers

Instrument PerformanceInstrument Performance

Evaluation of instrument noiseEvaluation of instrument noise Reproduce fluorescence microscope Reproduce fluorescence microscope

resultsresults Comparison with independent Comparison with independent

methodmethod Kappa distribution measured at IPST Kappa distribution measured at IPST

with a density gradient columnwith a density gradient column

Measurement NoiseMeasurement Noise

Standard fluorescent beads: 6.5% CV

Propagates to +-1 kappa for kappa 30 fiber

R/G Distribution

0

50

100

150

200

250

300

350

0 2 4 6 8

R/G

frequency

Red/Green Fluorescence vs. Kappa

for IPST SamplesR2 = 0.9953

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

0 10 20 30 40 50 60 70

kappa

Red

/Gre

en

IPST Cook 1 (Kappa 64)

0

1

2

3

4

5

6

7

8

9

10

0 20 40 60 80 100

Kappa

% fi

bers

Density GradientPopulation

FKA Population

IPST Cook 7( kappa 33.4)

0

2

4

6

8

10

12

14

0 20 40 60 80 100Kappa

Pe

rce

nt

of

Fib

ers

FKA Population

density gradient

IPST cook 2 (Kappa 50.5)

0

5

10

15

0 25 50 75 100 125 150

Kappa

% fi

bers


FKA Population

IPST Cook 3, Kappa 23.4

0

5

10

15

20

0 10 20 30 40 50 60

Kappa

Per

cent

of F

iber

s


FKA Population

Uniformity ofUniformity of Laboratory and Laboratory and

Commercial PulpsCommercial Pulps

typical kappa distribution for softwood pulp

0

5

10

15

20

25

0 10 20 30 40 50 60 70 80 90 100

kappa

% fi

bers

Statistical Representation of Pulp Statistical Representation of Pulp UniformityUniformity

Coefficient of variationCoefficient of variation

(COV)(COV)

gamma onegamma oneGamma one ~ 0

Gamma one= 1.89

( )

( )

standard deviation

Mean Kappa

3

3

( )iX

N

softwood and hardwood pulps

0

5

10

15

20

25

30

35

0 20 40 60 80

kappa

% f

iber

Birch 17.8

Pine 34.4

Softwood and Hardwood Softwood and Hardwood

PulpsPulps HardwoodHardwood

COV ~ 0.3-0.5COV ~ 0.3-0.5 gamma one ~ 0-gamma one ~ 0-

1.01.0

SoftwoodSoftwood COV ~ 0.3-0.7COV ~ 0.3-0.7 gamma one ~ 1.0-gamma one ~ 1.0-

3.03.0

COV=0.41Gamma one =1.89


Lab-cooked vs. commercial pulp

0

5

10

15

20

25

30

0 10 20 30 40 50 60 70 80 90kappa

% fi

bers

lab cooked 29.5

commercial 31.4

Commercial vs. Laboratory Commercial vs. Laboratory PulpsPulps

COV=0.54

Gamma one= 1.6


Effect of Chip Thickness on Effect of Chip Thickness on Hardwood PulpsHardwood Pulps

Effect of chip thickness

0

2

4

6

8

10

12

14

16

18

20

0 10 20 30 40 50 60 70 80

Kappa

%fib

ers

kappa 20.0, 2-4 mm

kappa 20.0, 8-10 mm

Effect of Enzyme Effect of Enzyme pretreatment on pretreatment on Hardwood PulpsHardwood Pulps

Effect of Enzyme Pretreatment

0

5

10

15

20

25

0 10 20 30 40 50 60 70

Kappa

% f

iber

s

Control Pulp kappa 20,8-10 mm chips

Enzyme pretreatedKappa 20, 8-10 mmchips

0

5

10

15

20

25

30

35

0 10 20 30 40 50 60 70 80 90 100

kappa

% fi

bers

control, kappa 34.4

pre-steamed , kappa 31.5

high pressure, kappa 31.3

Effect of pre-steaming and Effect of pre-steaming and pressurepressure

COV= 0.27Gamma one =1.42



Effect of Pulping Effect of Pulping Temperature Temperature

SuperBatch softwood pulpsSuperBatch softwood pulps Cooking temperature: 168Cooking temperature: 168ºC vs. 176 ºCºC vs. 176 ºC

Varied Varied temperature temperature and and time at time at temperaturetemperature to reach target Kappa to reach target Kappa (~20)(~20)

‘‘time to temperature’time to temperature’, and , and chip thickness chip thickness distributiondistribution also varied, but not controlled also varied, but not controlled..

68 samples68 samples were analyzed were analyzed

ResultsResults

Linear regression analysis to investigate Linear regression analysis to investigate correlation between correlation between COVCOV and cooking and cooking variables; variables; temperature,time to temperature,time to temperature,thick chip percentage,thin chip temperature,thick chip percentage,thin chip percentagepercentage

Regression model for all 68 trials

2

2.158 0.015* 0.005*

0.010* 0.012*

0.82

COV temp timeToTemp

thickChip thinChip

R

Linear regression analysis for Linear regression analysis for all 68 trialsall 68 trials

All trialsEffect of

individualVariables

All 0.82 0.82-

All minus temperature 0.12 0.70All minus ‘time to temp’ 0.58 0.24All minus thick chip % 0.67 0.15All minus thin chip % 0.75 0.07

Variables

2R

2iR

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

2

0.346 0.008*

0.013* 0.016*

0.78

COV timeToTemp

thickChip thinCihp

R

Linear regression model,

low temperature (~168ºC) trials Effect of variables at low temperature

2

0.450 0.005*

0.008* 0.013*

0.65

COV timeToTemp

thickChip thinChip

R

Linear regression model,

high temperature (~176ºC) trials Effect of variables at high temperature

Low temperature trialsEffect of individualvariables

All minus time to temp 0.09 0.69All minus thick chip % 0.31 0.47All minus thin chip % 0.56 0.22

0.78- VariablesAll 0.78

2R

2iR

High temperature trialsEffect of individualvariables

All minus time to temp 0.32 0.33All minus thick chip % 0.5 0.16All minus thin chip % 0.51 0.14

0.65- VariablesAll 0.65 2

iR2

iR

2R

Effect of temperature and ‘time to temperature’

Effect of temperature

0

5

10

15

20

25

30

35

40

0 10 20 30 40 50 60 70

kappa

% fi

bers

high temperature,19.3 kappa

low temperature,19.3 kappa

Effect of 'time to temperature'

0

5

10

15

20

25

30

35

40

0 10 20 30 40 50 60 70

kappa

%fib

ers

shorter time to temp.,kappa 20.2

longer time to temp.,kappa 20.5

COV=0.45

COV=0.55

COV=0.48

COV=0.54

Pulp uniformity from different digesters

0

10

20

30

40

50

0 10 20 30 40 50 60 70 80

Kappa Number

% F

iber

s

Continuousdigester, kappa19.0

SuperBatchdigester, kappa19.3

Single Fiber Charge Single Fiber Charge MeasurementMeasurement

Why is Fiber Charge Why is Fiber Charge Important?Important?

Charge facilitates retaining Charge facilitates retaining papermaking additives and finespapermaking additives and fines Better economicsBetter economics Lower environmental impactLower environmental impact

Charge has a profound effect on Charge has a profound effect on paper formationpaper formation Poor formation leads to poor appearancePoor formation leads to poor appearance Uneven distribution of papermaking Uneven distribution of papermaking

materials affects function (printing, materials affects function (printing, absorbency, etc.)absorbency, etc.)

Drainage on papermachineDrainage on papermachine

Monitoring and Controlling Monitoring and Controlling ChargeCharge

Bulk Solution MeasurementsBulk Solution Measurements Titration techniques with cationic chemicalsTitration techniques with cationic chemicals

Assume uniform charge between particlesAssume uniform charge between particles Electrokinetic MethodsElectrokinetic Methods

Differences in charge between single Differences in charge between single particlesparticles

Many assumptions:Many assumptions: Electrophoresis:Electrophoresis: fines only; spherical particles; fines only; spherical particles;

etc.etc. Electro Kinetic Analyzer (EKA):Electro Kinetic Analyzer (EKA): bulk solution bulk solution Poor correlation with bulk titration resultsPoor correlation with bulk titration results

Stain SelectionStain Selection

Charge-Sensitive Cationic StainCharge-Sensitive Cationic Stain

Charge-Sensitive StainsCharge-Sensitive Stains

Peak Intensites For EB, MEQ, and MQAE Stained Fibers

10.66.4

2830

960

5.6

1

10

100

1000

10000

0.03 0.29

Mean Fiber Charge, meq/g

Pea

k E

mis

sio

n In

ten

sity

, [L

og

] %

Ethidium Bromide

MEQ

MQAE

Stain SelectionStain Selection

Charge-Sensitive Cationic StainCharge-Sensitive Cationic Stain MQAE (Blue 460nm Emission)MQAE (Blue 460nm Emission)

Charge-Charge-InInsensitive Reference Stainsensitive Reference Stain Acridine Orange (Red 630nm Acridine Orange (Red 630nm

Emission)Emission)

Charge Charge ININ-sensitive Stain-sensitive Stain

MQAE and AO Emissions From Fibers at Two Charge Levels

0

20

40

60

80

100

120

140

160

180

MQAE (460nm) AO (635nm)

Inte

nsi

ty, %

0.03meq/g

0.03meq/g

0.29meq/g

0.29meq/g

MQAE Emission

Without AO 0.29meq/g

HIGH CHARGE FIBERS0.29meq/g

LOW CHARGE FIBERS0.03meq/g

Charge-Sensitive Blue Stain - MQAE NOT Charge-Sensitive Red Stain - AO

CalibrationCalibrationBlue/Red Emission vs. Mean Blue/Red Emission vs. Mean

Fiber ChargeFiber Charge

R2 = 0.99

0

5

10

15

20

25

30

35

40

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

Charge Titration Method, meq/g

Blu

e/R

ed E

mis

sio

n

Northwest Pulp

Northern Pulp

Epi-Illumination Flow Epi-Illumination Flow CytometerCytometer

Fibers in

Fibers out

Light Source

Flow Cell

Condensing lens and Bandpass Filter

Dichroic MirrorsRed CCD

Bandpass Filters

Green Intensity = ###

Red Intensity = ###

Blue CCD

Charge DistributionCharge Distribution

0

5

10

15

20

25

30

0.0 0.1 0.2 0.3 0.4 0.5

Bound MQAE, mol/g

Per

cen

tag

e o

f F

iber

s, %

0.04 meq/g

0.10 meq/g

0.17 meq/g

0.35 meq/g

Charge, meq/g

0.0 0.10 0.20 0.30 0.40 0.50 0.60

Commercial Fiber Commercial Fiber AnalyzerAnalyzer

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Pulp Uniformity Measurement of Single Fiber Properties