Fluid Bed Granulation Articles

A system for fluidized bed granulator automation with in-line multichannel near infrared (NIR) moisture measurement and a unique air flow rate measurement design was assembled, and the information gained was investigated. The multivariate process data collected was analyzed using principal component analysis (PCA). The test materials (theophylline and microcrystalline cellulose) were granulated and the calibration behavior of the multichannel NIR set-up was evaluated against full Fourier Transform (FT) NIR spectra. Accurate and reliable process air flow rate measurement proved critical in controlling the granulation process. The process data describing the state of the process was projected in two dimensions, and the information from various trend charts was outlined simultaneously. The absorbence of test material at correction wavelengths (NIR region) and the nature of material-water interactions affected the detected in-line NIR water signal.

A stochastic model for particle mixing and segregation in fluidized beds with baffles.



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In process engineering, fluidized beds have played an important role in the industry for quite a while already, and the rather complex motion of fluid and particles within such beds is of continued interest. Many measurement techniques have been used to study the distribution of particles and fluids ranging from simple to very complicated techniques, such as X-ray and radioactive tracing techniques. Some of the techniques used, for instance various types of probes are invasive and may disturb the movement of particles in the bed.


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Fluidized beds are among those basic reactors that have been used extensively for various applications in the process engineering industry. In spite of this, and as a result of the complex motion of fluids and particles inside the beds, still more information is needed to understand the transportation of particles inside the bed. During the last decade, a number ofdifferent methods, such as X-ray and radioactive tracing techniques, have been used to monitor the dynamics of particles inside fluidized beds.


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Gas-solid fluidized beds have been used for many decades to achieve good mixing between the solid material and the up-flowing gas. The latest sophisticated imaging techniques, such as tomographic systems, make it possible to analyze and visualize the solid dynamic movement and distribution inside in the bed. Taking fast images of the bed material during the fluidization process with high frequencies of 100 Hz usually does this. The main advantages of the imaging techniques are non-invasive nature, and suitability for industrial application where high temperature and pressure are required.


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One of the ingredients in Granular Dynamics (or DEM) is a description of interparticleforces. In this paper the effect of surface roughness o­n Hamaker and liquid bridgeinteractions is investigated. Three different models are used (excluded volume, stochasticroughness and explicit asperities). In general, the latter two give similar results. Roughnessdecreases interactions up to several orders of magnitude for rigid surfaces. To validate theanalytical results o­n liquid bridge interactions at low humidity, molecular dynamicssimulations were also performed o­n model systems.



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In a fluidized bed in which the particles vary in size or density segregation can occur.Including horizontal sieve-like baffles in the bed can greatly increase the tendency of powdersto segregate. This can make a fluidized bed particle classification process possible. In thisarticle a feasibility study of such a process is presented.Experiments were performed with a model system. It was found that the baffles increase thepurity of both the ‘flotsam’ and the ‘jetsam’ fractions. The capacity of a fluidized bed particleclassifier can be estimated using a mechanistic model, based o­n literature models. With sucha model we found that the baffles are most effective in systems that tend to segregate but doactually hardly segregate without baffles.