Introduction Fine Particles

Transcription

1 1 Introduction Fine Particles Particle Characterisation Louk Peffer

2 Importance Particulate Materials Why / relevance? Product quality Process control. Physico-Chemical characterisation What? How? Particle size Particle shape Surface/porosity.. Techniques - Numbers - Area - Volume -.. 2

3 Particles are different..than liquid and gases We can measure a lot, but still a lot cannot be measured. This introduction will give awareness and an overview on what is possible. 3

4 Particles are involved in 70% of the industrial processes Dry powders, granules, suspensions, emulsions, slurries, aerosols, sprays, droplets Final products Semi-finished products Adjuvants Excipients / Active ingredients 4

5 Technological Applications in all areas of the Process Industries food processing, pharmaceutical, biotechnology, oil, chemical, mineral processing, metallurgical, detergent, power generation, paint, plastics, cosmetic industries Process behavior Viscosity, Reaction speed, Filtration, Polymerization, Spraying, Dissolution rate, Segregation, Agglomeration 5

6 Commercial products Well known Table salt and sugar Coffee creamer Baking soda Flour Cement Catalysts But also Paint Toothpaste Mascara Chewing gum Magnetic recording media.. 6

7 Quality products Coating thickness, color intensity, appearance of paint Setting time of cement Effectivity medicines Taste chocolate, coffee Effectivity and selectivity catalysts Cosmetics, color intensity, functionality.. 7

8 Quality aspects H.G. Merkus G.M.H. Meesters Product stability and structure in dispersions Dissolution rate, reactivity Drying rate, efficiency Rheological properties of powders, emulsions and suspensions: powder flowability, Dosability, fluidization, viscosity, (non-) Newtonian behavior Air dispersability, inhalation possibility Filtration rate, removal possibilities Pharmaceutical efficacy and side effects Safety, toxicity, dusting, explosion sensitivity/severity Catalytic activity and selectivity Concrete/ceramic strength Taste, mouthfeel, skin feel Gloss, hiding power, transparency Abrasive/polishing quality Packing density and product porosity 8

9 RELATION WITH PRODUCT PROPERTIES Size fractions are denoted as: mm mm mm mm mm Dissolution rate phenacetin (pain-relieving and fever-reducing drug 9

10 Better control of product quality.. Quality is... giving a customer what he wants today, at a price he is pleased to pay, at a cost we can contain, again, and again, and again; and when more desires develop for the future giving him something even better tomorrow. Seaver

11 Quality parameters Particle size Particle size distribution Particle shape Surface area Porosity Crystallite size Rates of.. - Dissolution - Reaction - Absorption / adsorption - Stability - Combustion - Hydration -. 11

12 Influenza virus 100nm Brownian motion - Tracking Viruses 2nm 900 nm Acanthamoeba polyphaga mimi 600 nm Thiomargarita namibiensis ( μm) 12

13 13 Sizes up to 12.5 cm

14 Particle characterization covers a vast array of interesting specs of matter all the way from large molecules (globular, proteins, polymers), to micelles, microemulsions, viruses, liposomes, latexes, pigments, clay, organic and inorganic oxides, sand, gravel etc. Bruce B. Weiner, 2010 Pore a negative particle? 14

15 Particle size vs. porosity Catalysts and carriers Porous particles have highly developed internal surface area and can be used for e.g. catalysis, absorption and carrier. 15

16 Similarity particle size and pore size characterisation Particles: 1-3 nanometers 12,500 millimeters Particle size Particle shape Charge properties Mechanical properties Pores: 0.4 nanometers 0.8 millimeters Specific area Pore size Pore volume Active site (crystalitte) 16

17 Size Determination Primary Secondarily Tertiary Physical Phenomena 17

18 Physical phenomena definition particle size distribution The presented particle size distribution, is a distribution of spheres which give the same signals on the detector as the analyzed sample; called equivalent sphere diameter referring to the technique e.g. Circular diameter, Stokes diameter, Sieve diameter, Hydrodynamic diameter. 18

19 Number Marbles Means of distributions Diameter Numbers [mm] diameters V= 4/3 π r 3 A= 4 π r Total Diameter 19

20 Marbles Means of distributions Mode: Highest frequency 16,0 x R (n min + n max )/2 = 27,5 x nl Number length mean arithmetic mean D[1,0] = d/n = 17,0 x ns Number surface mean D[2,0] = ( d 2 /n) ½ = 17,5 x nv Number volume / Number weight mean D[3,0] = ( d 3 /n) ⅓ = 18,2 Surface weighted (Sauter) D[3,2] = ( (n i D i ) 3 )/( (n i D i ) 2 ) 19,8 Volume / Mass weighted (De Broucker) D[4,3] = ( (n i D i ) 4 )/( (n i Di) 3 ) 22,9 20

21 21 Different means Svarovski (1990)

22 Consequences of shape Cilinder length diameter aspect ratio volume equivalent sphere diameter Majority of particles are irregular and with a rough surface : : : : : : : : : Span of the distribution? 22

23 Equivalent sphere concept Flow laminar turbulent Equivalent projected area circle diameter, D A Equivalent surface area diameter, D S Equivalent sieve diameter, D Si Equivalent volume diameter,d V Stokes diameter, D St REM Standard ISO (Laser Diffraction) uses X 23

24 Characteristics of distributions Mode (most frequent) Median, midpoint (not mean!) Mean diameter (depending!) D 10 10% smaller than D 50 Median D 90 90% smaller than Q 3 cumulative volume undersize 1-Q 3 cumulative volume oversize Q 0 q 0 q 3 cumulative number undersize fractional density distribution fractional volume density distribution 24

25 Density and cumulative undersize Q 3 (D), % Cumulative volume undersize distribution (for constant density equal to mass distribution REM left, right or mid of the bar? 25

26 Cumulative distribution ( cum < or >) D 50 = 50 % of distribution smaller than that size D 10 D 50 D 90 Modus most frequent 26

27 Distribution modes (q, Q) Laser Diffraction, Sieving, Sedimetation: volume distribution Image Analysis, Electrical Sensing Zone: number distribution V= 4/3 π r 3 What you see? 27

28 Number Number Number Number Bimodale number distribution Number Distribution Cumulative Uppersize Volume Distribution Particle size, µm % 80.00% 60.00% 40.00% 20.00% 0.00% Particle size, µm Particle size, µm % Cumulative Undersize Light Intensity Distribution Number Distribution & Cumulative Undersize 50.00% 0.00% Particle size, µm Particle size, µm Particle size, µm 28

29 29 Electrical Sensing Zone

30 Particle size and particle area mathematical idealisation Area: 6 * (edge length) 2 Volume: (edge length) 3 Area: 4 π r 2 Volume: 4/3 π r 3 S. A. [ m2 g ] = 6 μm ρ Cube with edge length 1 cm (area 6 cm 2 ) Divide in cubes of 1 μm in total cubes Exhibit a total area of cm 2 30

31 Correct and relevant presentation Experimental conditions, dispersing, measuring, results, explanation Principle of the technique Designation of the instrument Dispersing system and conditions Figures q, differential distribution (volume, number, area) Q, cumulative undersize 1-Q, cumulative uppersize Table of values, D 10, D 50, D 60, D 90, mean, modes, span (X ) Definitions & explanation of used terms, variables and formula 31

32 Technical Development Sieving 4000 BC, 1867 Andreasen sedimentation 1928, Microscopy 1639 Imaging 1950 Fraunhofer 1800 Static light scattering 1960 Dynamic light scattering 1970 Laser obscuration

33 Light Scattering Techniques Brownian Motion Laser Diffraction Static light scattering Photon Correlation Spectroscopy (PCS) Dynamic light scattering Laser Obscuration Time Technology Pattern Laser Sample 33

34 Equivalent Sphere Concept The principal result of the Laser Diffraction technique is a volume-based Particle Size Distribution for a collective of spheres having defined optical properties, for which the calculated scattering behavior gives an optimum match with the measured scattering pattern of a sample. 34

35 Gravitational Sedimentation Classical, Reliable Technique - Simple Algorithm Particle falling due to gravity in viscous liquid (or air) Gravitational force Sedimentation Vessel Buoyant force Drag force Gravitational Centrifugal SFFF Andreasen pipette (1928) Instrumental 35

36 Equivalent Sphere Concept The principal result of the Sedimentation technique is a volume or light extinction based Particle Size Distribution for a collective of spheres having defined hydrodynamic properties, for which the settling behavior matches with the measured steady-state settling velocity of the sample. 36

37 Electrical Sensing Zone Technique Wallace Coulter 1940 Coulter Principle Constant current + - Particles change the conductivity in the orifice Voltage pulse is a measure of particle volume 37

38 Equivalent Sphere Concept The principal result of the Electrical Sensing Zone technique is a number-based Particle Size Distribution, where the size of particles is related to their equivalent volume. 38

39 Sieving Egypt B.C. Portland Cement Principal sieve series 45 µm 125 mm 5 µm 32 µm Execution - Manual - Shaking - Sonic - Air sifting 39

40 Equivalent Sphere Concept The principal result of the Sieving technique is a Particle Size Classes Distribution for a collective of spheres that just pass through the apertures of a sieving medium entitled as equivalent sieve diameter, near mesh diameter, calibrated diameter or nominal size of the sieve. 40

41 Particle Image Analysis Static or Dynamic Seeing is believing Optical Microscopy Digital Image Analysis Static Dynamic SEM TEM Morphological Imaging Dispersibility Shape Classification and distribution Sizing Particle Thumbnails, Captured images that met user defined shape parameters 41

42 Summary Particle Size Distribution Techniques Technique Range (µm) Calibration Time Repeatabilty (%) Resolution (%) Bias (%) Sieving N 5 min 1 hrs Sedimentation N hrs Electrical Senzing Zone Y 1-5 min < 1 Laser Diffraction N 1-30 sec < 2 Dynamic Light Scattering N 1 min < 2 Imaging N 15 min - hrs μm - Ultrasound Extinction Y 5 min < 3 Sample preparation 5 min - 1 week, typical few hours 42

43 43 Thank you for your attention!