Particles are everywhere - AIChE

© Copyright 2019, Sympatec GmbH, D-38678 Clausthal-Zellerfeld, Germany | AICHE| 20190204 APS1|EN

Particles are everywhere!

▪ Coffee

▪ Orange juice

▪ Agrospray

▪ Inhaled pharma

▪ Cement

▪ Minerals

▪ Fuel injection

▪ Additive manufacturing (3dp)

▪ Beer……


Reasons for particle size control

▪ Texture

▪ Taste

▪ Bioavailability

▪ Flow behavior

▪ Setting strength

▪ Packing behavior

▪ Flotation performance

▪ Minimal energy

▪ Maximum throughput

▪ Minimize dust

▪ Maximize safety

▪ Minimize waste


Particle Characterization“Best Practice“

▪ Best possible analysis results demand

» Representative sampling

» Dispersion to the primary particles

» Effective instruments for precise measurement and evaluation | Analysis

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Analysis Result


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Particle Size / µm

Sampling

Dispersion

Analytical instrument

In reference to Henk G. Merkus (1997), TU Delft

Technology-dependent

Particle CharacterizationError sources | Schematic


Extraction of a Sample for AnalysisSample Taking | Sample Splitting

Extraction of a partial sample

▪ Crucial for representative measurement results

▪ Representativity determined by

» Sample size

» Number of subsamples

» Particle size

» Width of distribution

» Segregation behaviour© markadan wikicc


▪ Representative amount?

▪ Spatula from the top?

▪ Does everyone do the same?

▪ Have we considered automation?

Representative SamplingLaboratory


Representative SamplingProcess

▪ Screw samplers, grab samplers, static probes…..

» Wide variety of available samplers

▪ TWISTER

» Sampling under process conditions

» Consideration of entire pipe cross section with controlled scan of closed spiral path

» All areas contribute equally weighted to the result

TWISTER| view into pipe


Representative SamplingProcess – Jet mill

Position of the particles changes with process conditions


Dispersion

▪ Always consider the state of the material in the process

▪ Consider changes caused by sample prep

» Dissolve fines

» Create artefacts

» Break agglomerates

» Release of fines

WET

DRY

• The sample consisted of fines adhered to larger particles

• The high viscosity of the liquid did not permit release of fines even with dispersants and sonication


Dry DispersionDispersion Principle | Injection

Dispersion with Compressed Air* Principle

» Velocity gradients

» Collisions between particles

» Collisions between particles and wall

*variable adaptation of the dispersion energy to the product requirements


RODOS | Unrivalled Dry DisperserReproducible Dispersion Effect

Powderintroduction

Mixing zone

Adaptable dispersionenergy via primary pressure and ring gap

Freeaerosol jet

Straightacceleration section

Length aids dispersion

Air flow rateup to 200 l/min

Particle streamvmax=100 m/s

Beam formation

Without | with baffle cascades

No re-agglomeration or deposits


RODOS Dry powder disperser

▪ Fast analysis (seconds)

▪ Variable sample amount

» <1mg <1kg

▪ Minimal cross contamination

▪ Variable energy input

» Understand cohesivity

» Correlation with process or product performance


untreated lactose very sensitive

to pressure increase !

Note the steep pressure response !

Dry Powder Cohesivity


Note the flat pressure response !

modified lactose shows no

change with increased pressure

Dry Powder Cohesivity


Sensor TechnologiesMeasuring Ranges

0.0001 0.001 0.01 0.1 1 10 100 1000 10000 1000000.1 nm 10 nm 100 nm 1 µm 10 µm 100 µm 1 mm 10 mm 100 mm

*Photon Cross Correlation Spectroscopy

PCCS* | Size and Stability 10,000 nm0.5 nm

Dynamic Image Analysis | Size and Shape 34,000 µm< 1 µm

Ultrasound Extinction | Size and Concentration 3,000 µm< 0.1 µm

Laser Diffraction | Size 8,750 µm0.1 µm

1 nm


Detection technology -Laser Diffraction

» Highly flexible

• Dry powder

• Suspension

• Emulsion

• Spray

» Excellent for fines

» Wide dynamic range

» Only spherical size given


Diffraction PatternsMono-disperse Small and Large Particles

Small particlesLarge diffraction angles

Large particlesSmall diffraction angles

r0 r0


HELOSOptical Setup

* ISO 13320, § 5, fig. 2 for particle size from 0.1 µm to approx. 3.0 mm

Laser lightsource

Beam expander

Dispersion

Particle flow

Opticalmodule

Detector

Measuring zone


HELOS | Sensor FamilyBR | KR | Dry and Wet

HELOS/BR 0.1 µm – 875 µm

HELOS/KR-Vario 0.1 µm – 8,750 µm

Variable measuring zone up to > 2 m

QUIXEL

HELOS/KR 0.1 µm – 8,750 µm

GRADIS

HELOS/KR 0.1 µm – 8,750 µm

OASIS/M


Cement ProductionProcess and Quality Control

▪ Fineness determines the final cement quality

▪ Energy-intensive grinding

▪ Optimum process operation and reduced energy consumption with direct control of the particle size

▪ Laser diffraction with dry dispersion is the superior method for the analysis of cement fineness

© Sympatec

Ball mill


Measuring ResultsCement | 5 Repetitions

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Particle Size / µm

Sample x(10%) x(50%) x(90%) copt

µm µm µm %◆ Cement_001 1.29 14.53 51.66 13.65

◼ Cement_002 1.30 14.58 51.39 11.18

⚫ Cement_003 1.31 14.69 51.73 10.08◆ Cement_004 1.29 14.51 51.42 13.93

◼ Cement_005 1.30 14.53 51.22 11.47


Cement – Automated Lab


MYTOS & MIXER on-lineCement Plant Germany

Screwsampler

MIXERsecondary sampler

off-lineoperationVIBRI

MYTOSIndustrial diffraction system


Return-on-InvestmentCement Plant

▪ Monitoring and control of the grinding process during continuous operation for constant quality

▪ Monitoring and control during frequent product changes

» Hit “on grade” product faster

▪ Saving on investment for an additional silo for out-of-spec material produced during product changes

▪ Reduction of blending effort of “out-of-spec in between” material into finished product


Trend DisplayCharacteristic Values | Product Change

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⚫ x10 / µm⚫ x50 / µm⚫ x90 / µm⚫ R3 -R30 / %⚫ Blaine-Value / cm²/g

Blaine=5.000 cm²/g

Blaine=3.500 cm²/gProduct Change


HELOS/KR-Vario | Laser DiffractionAgriculture Sprays

An Important Tool for the Agricultural Spray Industry

© Fotokostic dt


Spray DriftFactors

▪ Spray drift influenced by

» Nozzle design

» Pressure and flow of spray device

» Environmental influences wind and heat

» Addition of adjuvants into spray solution

▪ Droplet size is crucial for spray drift

© Oticki dt


Measuring Agriculture Spray DropletsChallenges

▪ Very wide droplet size distributions in agricultural sprays

» Fine and coarse droplets exist together

▪ Typically wide spray plumes

▪ Droplet sizes differ depending on spot of measurement in the plume

▪ Reliable detection of fine fraction < 105 µm and coarse fraction > 2 mm

▪ High spray concentrations may exist

▪ Rugged and versatile test components to operate in a variety of spray environments


HELOS/KR-VarioWind Tunnel Installation

© 2016 Winfield Solutions, LLC


Measurement ResultsTwo Different Nozzles

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Particle Size/ µm

Identifier x(10%) x(50%) x(90%) Q3(105µm)µm µm µm %

◆ Nozzle 1_001 15.53 132.59 356.72 45.05◆ Nozzle 1_002 15.51 131.99 349.25 45.15

◼ Nozzle 2_001 417.98 728.84 980.82 2.12

◼ Nozzle 2_002 422.96 734.23 986.47 1.71


Detection technology -Image Analysis

» Highly flexible

• Dry powder

• Suspension

• Emulsion

» Excellent for coarser

» Good dynamic range

» Size AND shape given

» Detection of small populations


Particle ShapesParticle Gallery | Examples

Tobacco

Fibre composite

Glass beads

Tablet

Salt crystal

Fruit piece

Starsand


QICPIC | Evaluation ModesProduct Specific Selection| Overview

Adapted to the Particle Characteristics

» Compact shape EQPC | Sphericity | Aspect ratio

» Elongated shape Feretmax | Feretmin | Convexity | Aspect ratio

» Fibrous LEFI | DIFI | VBFD | Straightness | Elongation

» Transparent Feretmean | PED | Aspect ratio

Comparison to Results of Other Measurement Technologies

» Sieving Feretmin | DIFI

» Laser diffraction EQPC


Particle Characterisation with Image AnalysisApplication and Benefits

▪ Better product understanding and quality assurance

▪ In addition to particle size the particle shape determines essential product characteristics

» Processability | Flowability, compressibility, attrition …

» Product quality | Fracture, aggregates, foreign particles …

▪ Image analysis supplies both size and shape information to differentiate between batches regarding attributes critical to quality


▪ for characterisation of real particles particle shape in addition to the particle size gains more and more importance

» image analysis (IA) can give valuable services

» Static Image Analysis (non-moving particles, e.g. on a microscope slide)

✓ depth e of the sharpness is defined

✓ high resolution for small particles

✘ small amount of data

✘ particles are orientated by the base

✘ problem with overlapping particles

• high effort for software correction

✘ tiny sample size

• sampling problems

• very poor statistics

camera

microscope slide

particles

e

Detection technology - Image Analysis


▪ a flow of moving particles is imaged✓enlarged sample size

✓arbitrary orientation

✓reduction of overlapping particles

▪ several companies offer systems

▪ reflection or transmission

▪ wet dispersion or free fall

▪ matrix or line scan cameras

Optimum:dynamic image analysis with product adapteddispersion and excellent statistics

Dynamic Image Analysis

camera

particle flowparticles

e enlargedvelo

city

v


Dynamic Image Analysis with dispersion

QICPIC


QICPIC | Evaluation | GraphiteParticle Size Distribution

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Particle Size/ µm

Sample x(10%) x(50%) x(90%)µm µm µm

◆ Batch 1 10.42 19.15 36.24⚫ Batch 2 11.21 18.72 33.83◼ Batch 3 11.02 19.12 35.18


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Aspect Ratio

QICPIC | Evaluation| GraphiteShape Parameter Aspect Ratio

related to S50

◆ Batch 1

⚫ Batch 2◼ Batch 3

AR 0.86AR 0.57 AR 0.64


QICPICParticle Gallery | Oversized Particle

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Particle Size/ µm

# of Particles x(10%) x(50%) x(90%) x(99%)µm µm µm µm

◆ 2,766,580 168.61 250.11 324.69 393.05

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▪ Oversized particle re-cognition in a chemical for natural gas distillation after spray granulation

▪ x99 = 393 µm

▪ Oversized particle EQPC = 1,239 µm

▪ 1 oversized particle in 2,766,580 particles totally


QICPICParticle Gallery | Oversized Particles

▪ Filter criteria with different size and shape parameters

▪ Up to 10,000 particles per gallery window

▪ Tracking to particle movie and export in CSV- and XML-files possible


Detection of Screen BreakageProduction and Quality Control

▪ Sieve breakage needs to be detected as early as possible to avoid out of spec batches

▪ Dynamic image analysis provides highest sensitivity especially for very narrow distribution and tiny quantitiesof coarse particles

▪ Smallest amount of coarse material is detected

▪ Earliest process interaction become possible

▪ Process confidence is significantly increased


Analysis Results | EQPCDetection of Sieve Breakage

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▪ Smallest amount of coarse particles needs to be detected reliably

▪ Customer specsR1400 < 0.5 %

Sample R3(1400µm)%

◆ EPS1 0.57

◼ EPS2 0.22


Installation | Measurement ContainerPICTOS | Control | 5 Production Lines

PICTOS adapted to 5 TWISTER samplers


Detection technology – Ultrasonic Extinction

» Must be liquid based

• Suspension

• Emulsion

» Contamination resistant

» High concentration

» Good dynamic range

» Size AND concentration

HF-ReceiverHF-Transmitter

Measuring zone


Attenuation spectrum

✓ 31 frequencies

✓ Fast scan < 60 sec.

✓ High dynamic range

(160 dB)

Background (Fluid)

Normal (Fluid & Particle)Cumulative (Q3) Distribution

Density (q3*)Distribution

Instrumentation - OPUS


Installation example – Cu/Ni Ore grinding

» Mill/Cyclone stage

» ~ 40% w/v solids

» 3 lines on one sensor

» Automated flushing

» 24/7 operation

» 3 mins/line inc cleaning


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time

Curve

x(50 %) /µm

Q3 200 mesh

Concentration

JNMC 14000 t/day , line 2

Sympatec OPUS

Installation example – Cu/Ni Ore grinding


Summary

▪ Sampling is critical

» Be aware of how much and where from

▪ Dispersion is important

» Does the measurement reflect the environment?

▪ Use an appropriate detection technique

» Does it detect a sensitive dimension?

» Is shape a factor?

» Small population detection?


Thank you for your attention

Andrew SmithInline & West Coast [email protected]+1 267 886 3455

mailto:[email protected]

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Particles are everywhere - AIChE