It is no coincidence that the majority of powder processors share with tablet producers a heavy reliance on experience-based
manufacture. Powders are challenging materials to characterize because their behavior depends on so many variables, including
the properties of the particles themselves (e.g., hardness, porosity, size, shape, surface texture) and system variables such
as air content and humidity, for example.
The complexity of powders makes a first-principles analysis of behavior beyond our current capabilities and severely challenges
the relevance of single-number characterization. A more robust approach is to measure powders using reproducible methodologies
that quantify certain aspects of behavior in process-relevant ways. Relating the resulting data to product performance allows
the specification of powders that will perform in the required way in a given process environment.
A visual comparison of two different types of lactose—one spray dried, the other finely milled—provides a qualitative evaluation
of flow behavior. Spray-dried lactose, with relatively large spherical particles, moves easily around a jar. The finely milled
sample, with smaller angular particles, forms agglomerates, and its flow is more erratic. The finely milled sample is highly
cohesive, but the spray-dried sample is not.
Simply pouring these samples into a vessel or funnel confirms these observations. Nonetheless, if attempts are made to force
the powders through an orifice (with a diameter significantly larger than the particle size of the materials), then behavior
is markedly different. Under these conditions, the finely milled lactose will extrude through the orifice like a paste, and
the spray-dried lactose will tend to resist this forced flow. Selecting a lactose with good flow properties may not be the
straightforward task it initially appears.
Table I shows a selection of shear and dynamic parameters for both samples. Shear properties are determined by measuring the
stresses required to rotate one plane of a (usually) consolidated sample against another. Dynamic characterization, on the
other hand, involves measurement of the forces and torques required to maintain a specified flow pattern under various test
conditions. With dynamic instruments (e.g., powder rheometers), samples can be measured in an aerated state, giving information
for a broad range of applications. Comprehensive details of testing methodologies are provided in Reference 1.
Finely milled lactose is usually cohesive; that is, the particles stick to one another and to other surfaces such as container
walls, thus inhibiting consistent flow. Shear testing measures parameters such as cohesion and unconfined yield strength,
thereby quantifying the higher cohesive strength of the finely milled lactose. Here, though, the focus is flow, so which parameters
define flow behavior rather than the more general parameter of cohesivity?
Specific energy (SE) is a flow parameter measured under noncompacting conditions by rotating a rheometer blade upward through
an unconfined sample. Like most dynamic properties, it is measured using a conditioned sample—one that has been prepared by
being made to flow in a low-stress manner to establish a homogenized, slightly aerated, bed of powder. Conditioning before
the measurement ensures a consistent baseline state, essentially eliminating any effects associated with sample loading or
processing history such as previous levels of consolidation. The conditioning step is essential to ensure the best possible
reproducibility. The SE for the spray-dried lactose is much lower than that for the finely milled sample, which indicates
that it will flow more readily when unconfined and when the flow is initiated by gravity, such as when tumbling in a jar or
flowing into a die during tablet manufacture.
By contrast, basic flow energy (BFE) is measured by pushing a rheometer blade down through a sample, thereby inducing compaction
against the base of the vessel (confined flow). BFE values are highly differentiating and in this case clearly demonstrate
that finely milled lactose will be superior in a confined forced flow processing (see Table I). Other measurements clarify
the reasons for this apparent reversal in relative flow behavior.
Table I: Bulk, shear, and dynamic parameters for a spray-dried lactose and finely milled lactose.
The compressibility of the finely milled lactose is much higher than that of the spray-dried sample. In this case, compressibility
was defined as the change in bulk density induced through the application of a normal stress (<20 kPa). In general, finer
cohesive materials tend to have a higher porosity or air content, so compression has a marked effect, forcing out air and
increasing bulk density. Conversely, the spray-dried lactose has minimal cohesion and in its conditioned low-stress state,
packs efficiently. The gravitational forces acting on each particle exceed the cohesive forces between them and thus minimizes
the number of void spaces in the powder. The result is a stiff powder bed for which density changes little as a result of
These differences in compressibility provide a rationalization of the measured BFE values. With the finely milled lactose,
the compacting motion of the blade generates only localized compression and the flow zone is relatively small. The spray-dried
sample, on the other hand, does not easily compress, so the compacting force is transmitted through the sample. A large flow
zone is created with many particles in motion simultaneously, thereby resulting in a high BFE.
It is clear that flow behavior can vary and can be characterized in different ways, even when complicating factors such as
aeration, consolidation, and humidity are not considered in any detail. Powders are not intrinsically good or bad, but it
is the match between material and process that is crucial. The key to successful formulation and processing is identifying
and controlling the parameters that define performance for any given application. This information is uncovered by correlating
various powder properties with experience from the existing skill base or experimental work. The following examples highlight
correlations between measurable parameters and aspects of tableting.