Troy Shinbrot

Powder technology in the pharmaceutical industry: the need to catch up fast

Pharmaceutical product development and manufacturing, which is largely an exercise in particle technology, is in serious need of technical upgrading. In this article, an overview of the current state of the art is provided, along with a discussion of expected research trends and their economic and societal impacts. In particular, the anticipated role of nanotechnology is discussed in some detail.

Experimentally validated computations of flow, mixing and segregation of non-cohesive grains in 3D tumbling blenders

Granular mixing is a vital operation in food, chemical, and pharmaceutical industries. Although the tumbling blender is by far the most common device used to mix grains, surprisingly little is known about mixing or segregation in these devices. In this paper, we report the first fully three-dimensional (3D) particle dynamics simulations of granular dynamics in two standard industrial tumbling blender geometries: the double-cone and the V-blender. Simulations for both monodisperse and bidisperse (segregating) grain sizes are performed and compared with experiment. Mixing and transport patterns are studied, and we find in both tumblers that the dominant mixing mechanism, azimuthal convection, contends against the dominant bottleneck, axial dispersion. The dynamics of blending, on the other hand, differs dramatically between the two tumblers: flow in the double-cone is nearly continuous and steady, while flow in the V-blender is intermittent and consists of two very distinct processes.

TRANSVERSE FLOW AND MIXING OF GRANULAR MATERIALS IN A ROTATING CYLINDER

The focus of this work is analysis of mixing in a rotating cylinder—a prototype system for mixing of granular materials—with the objective of understanding and highlighting the role of flow on the dynamics of the process. The analysis is restricted to low speeds of rotation, when the free surface of the granular solids is nearly flat, and when particles are identical so that segregation is unimportant. The flow is divided into two regions: a rapid flow region of the cascading layer at the free surface, and a fixed bed of particles rotating at the angular speed of the cylinder. A continuum model, in which averages are taken across the layer, is used to analyze the flow in the layer. Good agreement is obtained between the predictions of the flow model for the layer thickness profile and experimental results obtained by digital image analysis. The dynamics of the mixing process are studied by advecting tracer particles by the flow and allowing for particle diffusion in the cascading layer. The mixing model predictions for distribution of tracer particles and mixing rates are compared qualitatively and quantitatively to experimental data. Optimal operating conditions, at which mixing rates are maximum, are determined.

Spontaneous chaotic granular mixing

There are several types of instabilities in fluid mechanics that lead to spontaneous chaotic mixing and intricate patterns. Classical examples include the Kelvin–Helmholtz instability in shear layers, the instability of Taylor–Couette flow between rotating cylinders and the Rayleigh-Bénard instability in thermal convection. More recently, a variety of two- and three-dimensional chaotic mixing phenomena have been observed in other geometries. Mixing in granular flows, unlike that in stirred fluids, is thought to be diffusive—although periodic forcing has been used to enhance granular mixing, spontaneous chaotic granular mixing has not previously been reported. Here we report the observation of chaotic granular mixing patterns in simple cylindrical tumblers partially filled with fine grains. The patterns form spontaneously when sufficiently fine grains (≲300 µm diameter) are blended. We identify the mechanism by which the chaotic patterns are produced: a periodic stick–slip behaviour occurs in the shear layer separating static and flowing regions of grains. This causes weakly cohesive grains to mix at rates overwhelmingly exceeding those achievable for previously studied freely flowing grains.

Noise to order

Patterns in natural systems abound, from the stripes on a zebra to ripples in a riverbed. In many of these systems, the appearance of an ordered state is not unexpected as the outcome of an underlying ordered process. Thus crystal growth, honeycomb manufacture and floret evolution generate regular and predictable patterns. Intrinsically noisy and disordered processes such as thermal fluctuations or mechanically randomized scattering generate surprisingly similar patterns. Here we discuss some of the underlying mechanisms believed to be at the heart of these similarities.

Why do particle clouds generate electric charges

Granular flows, such as in silos or desert sandstorms, can form charged particle clouds in the presence of an electric field. Simulations and experiments on inert grains explain how significant electrical charges are able to accumulate.

Nonequilibrium Patterns in Granular Mixing and Segregation

For over 5000 years, granular mixing has been a topic of acutely practical concern. Paleolithic cave painters mixed their colors from blends of ochre and animal products; ancient Chinese and Egyptians blended inks and cosmetics from pork soot, crushed pearls, and compounds of lead; Aztec priests prepared drugs from concoctions of herbs and roots; and Michelangelo pigmented the Sistine chapel frescoes with blends including chalk, charcoal, and lead.

Progress in the control of chaos

Abstract In this review, we summarize several of the key contributions made over the past 5 years to the control of chaotic dynamical systems. The idea that chaotic systems can in fact be controlled may be counter-intuitive; after all they are unpredictable in the long term. Nevertheless, numerous theorists have independently developed methods which can be applied to chaotic systems, and many experimentalists have demonstrated that physical chaotic systems respond well to both simple and sophisticated control strategies. The great bulk of these researchers have restricted their study to low-dimensional systems, and correspondingly we critique this work at length. Most recently, a few researchers have proposed control techniques for application to high- or infinite-dimensional systems, and we describe this work in some detail as well.

Scaling surface velocities in rotating cylinders as a function of vessel radius, rotation rate, and particle size

Abstract In industrial practice, scale-up of granular flows in tumbling devices has been largely attempted using one of two parameters, either the vessel tangential speed (ω) or the Froude (Fr) number. In this communication, we measure surface velocities of 1.6-mm particles in half-filled rotating cylinders and find that neither ω nor Fr accurately scales changes in particle velocity with changes in vessel rotation rate, diameter, or particle size. New non-dimensional scaling criteria using a simplified model produce agreement in both the magnitude and shape of the velocity profiles. A strong dependence on both rotation rate and vessel radius is found and a small but measurable effect of particle size is also demonstrated. We find that there are two different scaling regimes that depend on whether or not the cascading layer reaches a symmetric equilibrium state. At lower rotation rates, Ω, cascading particles can reach equilibrium, and granular surface speeds scale as Ω2/3; at higher rotation rates, particle velocities scale as Ω1/2. New effects of relative particle size with respect to the cylinder diameter are also reported.

Chaos in a double pendulum

A novel demonstration of chaos in the double pendulum is discussed. Experiments to evaluate the sensitive dependence on initial conditions of the motion of the double pendulum are described. For typical initial conditions, the proposed experiment exhibits a growth of uncertainties which is exponential with exponent λ=7.5±1.5 s−1. Numerical simulations performed on an idealized model give good agreement, with the value λ=7.9±0.4 s−1. The exponents are positive, as expected for a chaotic system.