mixing of particles notes

7/23/2019 Mixing of Particles Notes

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Mixing Process

In ancient time,they were used inthe production of

natural earthpigments such asochre, manganeseoxide and etc


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Mixing and its purpose

The act of combining various ingredientstogether until they reach an acceptable,consistent uniformity

To obtain a distribution in which eachparticle of a constituent is near a particle ofanother constituent

To obtain product of an acceptable quality

To control rates of heat transfer, masstransfer and chemical reaction


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Mixing

In mixing different kinds of particulatematter, three broad aspects have tobe considered :

Type of mixer selected or designedand the mode of its operation

Characterization of state of theresultant mixture

Rate and mechanism of the mixing

process


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TYPES OF MIXTURE

PERFECT MIXTURE

One in which a group of particles taken fromany position in the mixture will contain the sameproportions of each particles as the proportions

present in the whole mixture


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TYPES OF MIXTURE

RANDOM MIXTURE

Mixture in which the probability of finding aparticle of any component is the same at alllocations and equal to the proportion of that

component in the mixture as a whole

The best quality that can be achieved


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TYPES OF MIXTURE

SEGREGATING MIXTURE

Particles of one component have a greaterprobability of being found in one part of the

mixture


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SEGREGATION

caused by differences in size, shape and density

of constituent particles of a mixture

Effect the most differences in size

Effect the least differences in density except influidization


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MAIN SEGREGATION

MECHANISM Trajectory

Percolation of fines

Rising of coarseparticles by

vibration

ElutriationSegregation by elutriation

Segregation by percolation

Trajectory segregation


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MECHANISM OF

FOUR MECHANISM OF SEGREGATION

ACCORDING TO SIZE (WILLIAMS, 1990)

Trajectory segregation

Small particle of diameter, x and density p

drag is governed by Stokes law is projectedhorizontally with velocity, U into a fluid ofviscosity, and density, f, the limiting distanceis

-POWDERS FALL FROM THE END OF ACONVEYOR BELT


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MECHANISM OF MIXING

PERCOLATION OF FINE PARTICLES

Occur when mixture of particles is disturbed individual particles move, rearrangement in thepacking of the particles occurs. The gaps created

allow particles from above to fall and particles insome other place to move upwards

Occur during stirring,shaking,vibration or when

pouring particles into a heap-charging and discharging storage hopper


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MECHANISM OF MIXING

PERCOLATION OF FINE PARTICLES


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Occur whenmixture ofparticles ofdifferent size is

vibrated thelarger particlesmove upwards

Brazil-nut effect

RISE OF COARSE PARTICLES ON VIBRATION


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MECHANISM OF MIXING

ELUTRIATION SEGREGATION

Occur when mixture containing particles under50 m is charged into a storage vessel or hopper,

air is displaced upwards. The upward velocity ofthis air may exceed the terminal freefall velocityof some of the finer particles, which may thenremain in suspension after the larger particles

have settled t o the surface of the hoppercontents.


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PROBLEMS -

SEGREGATIONCoal industry

Performance of coal combustion

depends on particle sizedistribution and the mixed-nessof the particles

Detrimental to reliablecombustion performance andhandling difficulties


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PROBLEMS -

SEGREGATION

Packing for detergents / cements /polymer Industries

Variations in bulk density of the powdergoing to packaging

Not possible to fit 25kg into 25 kg bag

Mixing of constituents for detergents,drug, food industries

Chemical composition of the product

may be off specification


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REDUCING SEGREGATION

Making the size of the components as similar aspossible- not serious when all particle are lessthan 30 micron ( densities: 2000 3000 kg/m3)

Mobility of particles in free flowing powders canbe reduced -addition of small quantities of liquidto the mixtures

Components with a large difference ingranulometry, the coarser particles could becoated with the fine ones

Prevent action which facilitate segregation: Use

of inclined surfaces, hoppers with central flow


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EQUIPMENTS

Lacey(1954) identified three mechanism ofpowder mixing

SHEAR MIXING-shear stresses give rise to slipzones and mixing takes place by interchange ofparticles between layers within the zone

DIFFUSIVE MIXING occurs when particlesroll down a sloping surface

CONVECTIVE MIXING


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TUMBLING MIXERS DIFFUSIVEMIXING NOT SUITABLE FOR FREEFLOWING PARTICLES

A totally enclosed vessel rotatingabout axis, causes the particleswithin the mixer to tumble over

each other on the mixture surface Common vessel shape: cube,

double cone, drum, V and Y

Not suitable for material which

tend to agglomerate or granulate.Segregation on discharge

Axial mixing is slow compared toradial mixing


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V blender

Zarah

kasar

Zarah

halus

Paksi Simetri

76 mm76 mm

153 mm

900


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V blender

Mixture of sand at t = 0 min Mixture of tea at t = 0 min

Mixture of sand at t = 40 min Mixture of tea at t = 40 min


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CONVECTIVE MIXERS

An impeller operates within astatic shells and groups ofparticles are moved from one

location to another within thebulk of the mixture

Mixing dry granular powders or

paste, not suitable for verycohesive material oragglomerates. Easy to empty,difficult to clean


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Fluidized mixers

If particles within thebulk of the materialproceeds at high speeds,particles are thrown offor air is drawn into thebed.

The particles move apartand the bed assumes thecharacter of a liquid


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Fluidized mixers


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HIGH SHEAR MIXERS

HIGH SHEAR MIXERS- Emphasis on breakingdown agglomerates of cohesive powders


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ASSESING THE MIXTURE

Scale of scrutiny Danckwerts (1953)- maximumsize of regions of segregation in the mixturewhich will would cause it to be regarded as

imperfectly mixed

The end use of a particle mixture will determinethe quality of mixture required

TECHNIQUES FOR


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TECHNIQUES FOR

MEASURING HOMOGENEITY

OF A POWDER MIXTURE


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Invasive method-Sampling

thief probeThe size of samples

required to determine

the quality of the

mixture is governed bythe scale of scutiny

imposed by the

intended use of the

mixture.


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Evaluation of powder mixtures-

statistics relevant to mixing The true composition of

a mixture, , is often not

known but an estimate,

, may be found bysampling. If N samples

of composition yi to yN

in one component , the

estimate of the mixturecomposition, , si given

by

N

i

iyN

yncompositioMean1

1,


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statistics relevant to mixing Standard deviation and

variance. True std

deviation ,, and true

variance ,2,

of thecomposition of the

mixture are quantitative

measures of the quality

of the mixture Std deviation is square

root of variance

1

)(12

N

yy

S

N

i

i

N

y

S

N

i

i

1

2

2

)(


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statistics relevant to mixing Theoretical limit of

variance. For a two

component system the

theoretical upper andlower limits of mixture

variance are:

Upper limit (completely

segregated)

Lower limit ( randomly

mixed)

segregatedcompletelypp ),1(2

0

mixedrandomlyn

ppR ,

)1(2


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statistics relevant to mixing Mixing indices: A

measure of the degree

of mixing is lacey mixing

index

possiblemixingachievedMixingS

MR

/,22

0

22

0


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Evaluation of powder

mixtures

Lacey (1943) proposed statisticscould be used to monitor the

progress of powder mixing andcould be described by a mixingindex( MI).

0


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Evaluation of powder mixtures

Mixing Index - function of

1) standard deviation of composition aboutthe mean obtained from measurement, S

2) expected standard deviation of a

randomised mixture, Sr

3) standard deviation of a completelyunmixed system, So


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mixtures

22

0

22

0

lnln

lnln

R

sM

R

SM

0

0

2

0

2

SM

Ashton and Valentine (1966 )

Lacey (1943)

Westmacott and Lineham

(1960)


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mixtures

2

2

1

SM

22

0

22

0

R

SM

SM

R

1

1

0

0

R

SM

0

SM

Miles (1962)

Lacey (1954)

Lacey, Weidenbaum and Bonilla

(1955)

Beaudry (1948)

Yano,Kanise and Tanaka (1956 )


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Non invasive method

Magnetic Resonance Imaging (MRI),Discrete Element Model (DEM)

Simulation, Positron Emission Particle

Tracking (PEPT) and Digital ImageProcessing (DIP) are widely used to

study mixing operation.

Since invasive method required more

care during sampling process since

the sample must be taken at certain

time, many researchers have focused

on non-invasive methods that have


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Non invasive method

Since invasive method required moretime and care during sampling

process - the sample must be taken at

certain time, many researchers havefocused on non-invasive methods that

have more capability to investigate

mixing process.


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Magnetic Resonance Imaging

widely in medicine andpharmaceutical industry.

This method is based on

using magnetic field

gradients to encode thenuclear magnetic

resonance (NMR) signal

with spatial information.

The NMR signal will be

produced by certain nuclei

such as 1H, 13C and 31P

In medicalapplications, MRI is

required for

obtaining high-

resolution imagesof various organs

within the human

body by mapping

the distribution of1H, hydrogen

nuclei [Allen, T.,

1981]. ries


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MRI

Recently, there are several researches that

have been done by using MRI to investigate

mixing quality. Hardy et al., 2007 used MRI

to measure the mixing state of fine powders.The materials that been used in this

research are polymer microcapsules and

solid melamine. Both particles approximatelyare spherical in shape and have very similar

particle size with cut size, d50in the range of

6m and 9m.


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MRI

As conclusion, the author has stated that

MRI is evenly well suited to study the mixing

state of fine powders. The advantage of this

technique is the maximum contrast betweenthe two components of mixture.


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Porion et al., 2004-MRI

investigate the segregation and mixingprocess in a pharmaceutical blender.

Turbula mixers

Two different particles which are poppyseed and sugar beads were used to study

the influence of the number of rotations,

rotation speed and filling level duringmixing process.


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analyse the movement of a single particle in

the research. They found that the limit filling

ratio of the container is 80% and thehomogeneity of mixture is proportional to

rotation speed.

Turbula mixers be efficient - (1) the rotation

is fast, (2) mix a little amount of small

particles in a sea of large ones, and (3) the

concentration of the smaller particles does

not exceeds 10 percent.


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Porion et al, 2004 also stated that MRI is

a good non-invasive method toinvestigate the kinematic of mixing and

segregation of dry binary particulate

mixture but, the particles or granules thatwill been used in the research must

contain oil. Hence, there are two options

which are to prepare the grain by oil

coating or to use oil containing particles

such as seed.


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MRI

Mller et al., 2008, - many new techniques

available for upgrading the imaging speed

and detailed information for MRI

applications. MRI can reveal usefulinformation such as voidage map and

motion of bubble formation and bubble rise.

P it E i i P ti l


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Positron Emission Particle

Tracking (PEPT) The use of the Birmingham positron camera

for tracking positron-emitting particles within

engineering structures has been

investigated, using particles containingtypically 4 MBq(becquerel) (100 Ci)18F(f luorodeoxyglucose)

P it E i i P ti l


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Positron Emission Particle

Tracking (PEPT) From the visualization, the flow phenomena

in three dimensions could be examined

[Rafiee et. al, 2011]. This method has been

used to analyze the motion and flow of fluidand particulate material in multiphase

system. It is commonly used in mineral

industry to study the flow of particulatesystem.


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PEPT

PEPT give much more detailed data and

valuable information that can be use for

further analysis. Other advantage for PEPT

is the tested material can differ from liquid,organic polymer to metallic and mineral

particles. The experimental equipment for

PEPT method also can be in much largescale. However, it is quite complicated

method and expensive.


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PEPT

Saito et al, 2011 -PEPT is widely used in industry

system such as fluidized bed and rotating drum

mixers. PEPT has been used as a new approach

to investigated granulation process in high-shearmixer.


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PEPT

The materials that be used in the researchare microcrystalline cellulose powder and

polyvinyl alcohol which are as a starting

material and binder respectively. different

characteristic of impact velocities take place

in different region depends on the position of

the region inside the mixer. The transfer size-

dependent rate of the granules also has beenobserved for each region.


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PEPT

In 1998, Stellema et. al.have developed an

improved PEPT to studied the motion of solid

in a gas-solids Interconnected Fluidized Bed

(IFB) reactor. Same size of 500 m particleswith also has same density have been used

in this research. The method has been

improved by using the graded absorberswhich capable to extracted important

information from the Compton spectrum.

DISCRETE ELEMENT MODEL


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DISCRETE ELEMENT MODEL

(DEM) SIMULATION

Discrete Element Model

(DEM) simulation has been

used to investigate the

quality of mixing.Researches - Rhodes et al.,

2001,Chaikittisilp et al.,

2006,Renzo et al., 2008,

Nakamura et al., 2007 andNorouzi et al., 2011have

studied the mixing process

in fluidized bed using DEM

simulation.

Research by Kaneko et

al., 2000 and Xu et al.,

2010 used DEM to

analyze the

characteristics of mixing

process in single helicalribbon agitator and

rotating drum

respectively. Xu et al.,

2010 [16] used 2D DEMsimulation to studied

mixing process have

recommended 3D DEM

simulation for their future

research.

Th lt f th


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DEM

Rhodes et al, 2001,

studied the mixing process

in gas fluidized bed using

a DEM model by usingparticles that have been

tagged with dark and light

colour. The density of the

particle is 2650 kg/m3 andthe particles size is 1mm.

The results of the

research shows that

the particles mixing

rate increases withincreasing of gas

velocity but that gas

velocity does not affect

the degree of mixture

homogeneity. Besides

that, when the size of

particles aredecreasing, the overall

mixing rate and the

degree of mixing will

increase.


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DEM

Renzo et al, 2008 -DEM

simulation process requires

integration of the Newton-

Euler equation of motionfor each particle and the

full solution of the

continuity and Navier-

Stokes equationsthroughout the bed.

They used a mixture

of glass ballotini and

steel shots that havesame particles size

(433m) but different

in particles density in

their experiment. TheDEM simulation has

been used to

investigate the mixture

behaviour at different

gas velocity and

component density

ratio.

DIGITAL IMAGE


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DIGITAL IMAGE

PROCESSING (DIP)Many researchers have done studies on

the application of image processing on

the mixing process, to cheap and

readily available computational andimage acquisition equipments,


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DIP

A study has been conducted

by Daumann et al., 2009 on

determination of mixing time

in discontinuous powdermixer by using image

analysis on a horizontal twin-

shaft paddle mixer with a

spiral mixing tool.

The method was

tested on cement

and ultramarine blue

powders. The mixingefficiency was

determined using

image processing

technique.


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DIP

The individual digital image,

taken during the mixing

process was analyzed via

Matlab Image ProcessingToolbox and the mixing

efficiency was determined

from the output.

Thresholding was

done by using Adobe

Photoshop CS2. The

experimental resultsare evaluated on the

basis of known

statistical

interrelationship bymeans of Fokker-

Planck equation for

powder mixing.


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DIP

Berthiaux et al., 2006

studied the application of

Principal Component

Analysis (PCA) forcharacterizing

homogeneity in powder

mixing using image

processing techniques.Test was performed on

semolina powders with

different colours.

Images were taken

using Charge-

Coupled Device

(CCD) camera. Theresults indicated that

the homogeneity

criterion was

dependant on thescale of scrutiny

chosen for the

images used.

DIP


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DIP Le Coent et al., 2005 used

image processing forobtaining the mixing time in

a glass stirred vessel. The

digital images were

analyzed using box-counting method which is

employed to perform the

fractal image analysis of

binary images. The images

obtained were processed

with the Scion Image

Software.

The results

indicated that theproposed method

allows the

determination of

the mixing time andquantification of the

degree of

homogeneity of the

blend.

An image analysis


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DIP Muerza et. al., 2002 has

used image analysis todefine and characterize

homogeneity of mixing

particles. Six continuous

Sulzer static mixers were

used in this research. The

technique was tested on

mixture of aspirin andsemolina powders.

An image analysis

technique was

developed as well as

systemic model ofthe powder flow. The

procedure starts by

introducing the

aspirin and semolinapowder in the static

mixer and the mixing

process will be taken

by a camera. Then,

the recorded film is

analyzed by using

Visilog software.


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DIP

Research methodology begins with preparation ofcoloured sago, determination of sago size,

image acquisition process, images pre-

processing using Adobe Photoshop CS2

software, image analysis using ImageProcessing Toolbox in Matlab software and

development of automated system for

indentifying the mixture homogeneity.


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image acquisition process

A web camera that is connected to a computer

will be placed on the top of the fluidized bed to

capture the image of mixing process. Sequences

of image will be captured in 30 second interval.The images are taken by executing Matlab

algorithm in the computer. The mixing process

image will be saved in the computer for further

analysis

images pre processing using


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images pre-processing using

Adobe Photoshop CS2 software,The mixing process images that have been

saved will be pre-processed in Adobe

Photoshop CS2 software to determine the

optimum threshold value. This process isbasically to separate region of interest from

its background or unwanted region to

facilitate further image analysis in Matlabsoftware.

image analysis using Image Processing


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image analysis using Image Processing

Toolbox in Matlab softwareThe sequences of image that has

been saved from image

acquisition process will be used

for Digital Image Processing

(DIP). RGB colour analysis by

using Image Processing Toolboxin Matlab software will be used to

determine the degree of mixture

homogeneity

DIP is a form of signal processingthat produces a digital image or a

set of characteristics or

parameters related to the image

as its output

Interest in digital image

processing methods stemsfrom two principal application

areas, namely: (1) improvement

of pictorial information for

human interpretation, and (2)

processing of image datastorage, transmission and

representation for autonomous

machine perception. The saved

images will be converted to

gray scale image according tored, green and blue colour.

Then, the gray scale images

will used to produce red, green

and blue colour distribution in

the form of histogram.


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Polymer Industry


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Polymer Industry

Crushed rubber, PVC andpigment mixtures

Polypropylene compound

Insulating material

Recycled plastics

Mixers

Ploughshare,Shaftless screw,

Vertical cone,

Batch Twin Shaft Paddle


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Cement Industries

Mixtures are Lime,

Cement, Gypsum

Ploughshare,

Batch Twin Shaft,

Continuous TwinShaft Paddle


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Food Industries

Flour + Lecithin

Flour + sugar

Flour + salt

Flour milling Flour + additives,Granular flour

Mixers

Ploughshare, Ribbon,Shaft-less screw,

Vertical cone,

Batch Twin Shaft Paddle


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Pharmaceutical industry


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Pharmaceutical industry

Production of products in solid dosage

Tablets and capsules can beadministered in exact and repeatabledoses, have high stability,bioavailability of the active ingredients

can be changed when necessary

Easily stored and transported

mixing of particles notes

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