CHARACTERIZATION OF BIMODAL PARTICLE SIZE DISTRIBUTIONS (PSD) BYSCANNING ELECTRON MICROSCOPY (SEM) AND LASER DIFRACTION (LD)

ANALÍA GALLARDO; CABRERA, FERNANDA; VILLAR, MARCELO; BUCALA, VERONICA; YAÑEZ, MARIA JULIA

Praga

Congreso; 18 th International Microscopy Congress; 2014

International Microscopy Society

ABSTRACT Among the more popular techniques for PSDs measurement, the SEM imagesanalysis (IA)and laser diffraction(LD) are used alone or combined. In this work,1gof lactose (mean dnv= 26.5mm, particle density=1.36 g/cm3) and 3 gPolyvinyl Chloride (PVC)resin (mean dnv=142.6mm , particle density=1.51 g/cm3) particleswere mixed to obtain a bimodal PSD.Figure 1 shows a SEM micrograph of thestudied particulate system. Based on the materials properties, a relationshipbetween the number of lactose (NL) and PVC (NPVC) particlesof 46:1 is expected.The NL:NPVCratioobtained from the LD number distributions was 43:1. However, the number passing cumulative distributions obtainedfrom IA revealed that NL:NPVC varied from 4 to 33,being this relationship strongly influenced by the SEMsample preparation. The basic calculation and the information provided by LD(which handles thousand of particles) allowed improving the methodof mounting particles on the SEM stub. Figure 2 shows the number passingcumulative functions obtained by LD and IA (using the best SEM samplepreparation method). LD estimates a higher NL than thatcalculated from IA, probably because LD can processmuch more particles and itis less sensitive to segregation problems than IA.Taking into account the mass ratio of lactoseand PVC and their densities, the theoretical cumulative volume of lactose (VL)and PVC (VPVC) should be around 23% and 77%, respectively. LDprovides directly the volume cumulative distribution of the powder that isbeing analyzed, instead for IA, this function has to be calculated from thenumber cumulative function assuming a given 3D particles shape. Figure 3 showsthe volume cumulative passind distributions for LD and IA, for the last methodspherical particles are assumed. These results indicatethat VLfor IAand LD was 28 and 18 %, respectively; values that are between the theoreticalvalue (23%). Eventhough IA estimates less NL, higher VLis found for this technique. For the IA data, the calculation of  the volume of each class of particlesassuming spherical shape requires to elevate the diameters to a power of 3.Eventhough lower NL is predicted by IA, the diameter measurementerrors or the deviation of the particles shape from a sphere may lead to theobserved higher VL. The simulated bimodal PSDand  itsevaluation by IA and LD allows stablishingthe prediction errors  and modifyingsample preparation procedures to optimize the PSD chacterization.