Validation of a multi-component digital dissolution model for irregular particles

A new mesoscale simulation model for solids dissolution based on an computationally efficient and versatile digital modelling approach (DigiDiss) is considered and validated against analytical solutions and published experimental data for simple geometries. As the digital model is specifically designed to handle irregular shapes and complex multi-component structures, use of the model is explored for single crystals (sugars) and clusters. Single crystals and the cluster were first scanned using X-ray microtomography to obtain a digital version of their structures. The digitised particles and clusters were used as a structural input to digital simulation. The same particles were then dissolved in water and the dissolution process was recorded by a video camera and analysed yielding: the overall dissolution times and images of particle size and shape during the dissolution. The results demonstrate the coherence of simulation method to reproduce experimental behaviour, based on known chemical and diffusion properties of constituent phase. The paper discusses how further sophistications to the modelling approach will need to include other important effects such as complex disintegration effects (particle ejection, uncertainties in chemical properties). The nature of the digital modelling approach is well suited to for future implementation with high speed computation using hybrid conventional (CPU) and graphical processor (GPU) systems.

[1]  Xiaodong Jia,et al.  Validation of a digital packing algorithm in predicting powder packing densities , 2007 .

[2]  F Verhaeghe,et al.  Lattice Boltzmann model for diffusion-controlled dissolution of solid structures in multicomponent liquids. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[3]  Richard A Williams,et al.  A HYBRID MESOSCALE MODELLING APPROACH TO DISSOLUTION OF GRANULES AND TABLETS , 2007 .

[4]  Xiaodong Jia,et al.  Combining X-ray microtomography with computer simulation for analysis of granular and porous materials , 2010 .

[5]  Richard A Williams,et al.  From microstructures of tablets and granules to their dissolution behaviour , 2006 .

[6]  Frantisek Stepanek,et al.  The effect of granule microstructure on dissolution rate , 2008 .

[7]  P. Meakin,et al.  A three-dimensional level set simulation of coupled reactive transport and precipitation/dissolution , 2010 .

[8]  Bart Blanpain,et al.  In Situ Observation of the Dissolution of Spherical Alumina Particles in CaO–Al2O3–SiO2 Melts , 2007 .

[9]  K. Pruess,et al.  Numerical simulation of CO2 disposal by mineral trapping in deep aquifers , 2004 .

[10]  Sander Arnout,et al.  Dissolution and diffusion behavior of Al2O3 in a CaO–Al2O3–SiO2 liquid: An experimental-numerical approach , 2007 .

[11]  Richard A Williams,et al.  A packing algorithm for particles of arbitrary shapes , 2001 .

[12]  František Štěpánek,et al.  Computer-Aided Product Design: Granule Dissolution , 2004 .

[13]  Wei Ge,et al.  General approach for discrete simulation of complex systems , 2002 .

[14]  Chaoshui Xu,et al.  Property predictions for packed columns using Monte Carlo and discrete element digital packing algorithms , 2008 .

[15]  Joan E. Shields,et al.  Characterization of Porous Solids and Powders: Surface Area, Pore Size and Density , 2006 .

[16]  Peter C. Burns,et al.  Uranium Mineralogy and Neptunium Mobility , 2006 .

[17]  Qinjun Kang,et al.  Lattice Boltzmann simulation of chemical dissolution in porous media. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[18]  Xiaodong Jia,et al.  An Integrated Methodology to Evaluate Permeability from Measured Microstructures , 2006 .