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Preclude Powder Problems

March 25, 2015
Sophisticated analyses can provide insights to curb caking and improve processing.

Caking, crusting and agglomeration have always posed material-handling and processing challenges for the chemical industry. Recent studies indicate that sophisticated analytical techniques can help address these issues.

In the chemical industry more than 70% of materials — from feedstocks to additives and intermediates to manufactured products — come as relatively free-flowing powders, intended to be suitable for the manufacturing process or final application, notes Freeman Technology, Tewkesbury, U.K.

However, logistics often require storing materials for extended periods. This, in turn, can lead some powders to cake due to prolonged and undisturbed particle/particle interactions. Such caking (Figure 1) can significantly limit the ability of a powder to pass through the process train without interruption as well as negatively impact product quality.

Caked Material

Figure 1. Particles that clump together can make processing difficult and undermine product quality. Source: Freeman Technology.

While many studies have evaluated single influences on caking such as storage time or humidity, the advent of powder rheometry enables measuring a range of powder characteristics that can quantify the progression of caking, for example as a function of time, humidity or consolidation stress.

In a recent white paper, “Investigations into Homogeneous and Non-homogeneous Caking and Crusting in Powders using Powder Rheology,” Freeman Technology evaluated caking caused by four distinct factors: the chemicals involved, temperature, humidity and moisture migration (crusting). The materials assessed, all of which are in regular industrial use, included a three-component chemical blend, polymers, food powders and a sulfonated methyl ester employed in detergent manufacturing. An FT4 powder rheometer measured the flow energy of the samples before and after caking to quantify the resistance to flow.

Overall, the results show that the propensity to cake, via whatever mechanism, can be effectively quantified with respect to the powders’ flow properties; this, in turn, can assist with understanding and ultimately adapting the processing environment to limit caking and retain optimal processability.

Key Issues

The white paper raises two crucial issues, stresses operations director Jamie Clayton. First is the way in which powders are understood. In effect, they consist of solids, liquid and gases that move through a process as a bulk assembly. “Our approach has always been to characterize powder in this way. While physical properties such as size and shape, etc., are of course important, people are definitely becoming more understanding of the need to understand all factors that can influence powder behavior and these are encompassed in the properties of the bulk,” he notes.

Second is the question of how the process itself — from raw materials to final product— is considered. Potentially a wide range of stages and operations in any process may deserve individual attention, and the test methods employed must reflect these operations so as to provide relevant, useful information, he says. However, it’s also important to examine the overall process: “There’s little point in having a powder that is optimized for pressing into a tablet or pellet but which doesn’t discharge from a storage silo in the first place. The properties of the powder must be compatible with every stage in the process and this is an approach we see being adopted by our users.”

Nevertheless, Clayton still encounters the classic misinterpretation of powder flow as only being relevant to equipment such as hoppers, silos and chutes. In reality, he notes, it comes into play whenever particles must move with respect to each other, including in blending, filling, granulating or compacting operations.

Better Powder Analysis

Figure 2. Imaging systems that also incorporate Raman spectroscopy can differentiate particles of similar size and shape. Source: Malvern Instruments.

In addition, Clayton finds that many people continue to misuse traditional parameters, such as Carr’s indices and angle of repose, which often lack the sensitivity required and only measure a single factor. Likewise, well-established technology such as the shear cell, which can provide valuable information for evaluating the onset of flow, often gets misapplied beyond the understanding of hopper discharge, he cautions. “People are becoming more aware of the limitations of existing methods and are therefore more receptive to new techniques and quickly understand the benefits of our technology and our more comprehensive approach to powder characterization.”

Of course, as with any new approach, justifying the investment requires demonstrating it will help improve productivity and quality, and ultimately assist in achieving a final goal.

For example, better understanding of powder behavior enables optimizing formulations and process parameters so a tablet press can achieve maximum, high-quality output, which has immediate benefits. Conversely, a blockage that takes the press offline for a period or frequent output of substandard tablets have easily determined financial impact that may justify investing in tools to address such issues. “A similar analysis can be applied throughout the process chain of any operation; if a hopper or chute becomes blocked, what is the financial impact of the plant being down while this is resolved? What is the cost of disposing of a batch that didn’t meet the required specification? What are the implications of delivering poor quality products to the customer,” Clayton asks.

A perennial problem is batch-to-batch variability. End users may see differences in performance between batches of raw materials, all of which meet specifications, or even as a large batch is consumed. This problem also can arise when assessing new suppliers. It occurs because the specification isn’t comprehensive enough and isn’t relevant to the application in question. “A multi-faceted characterization tool allows all aspects of powder behavior to be evaluated and quantifies the influence of all variables within the powder — meaning that minor differences that otherwise might be overlooked can be identified,” he explains.

Similarly, maintaining the desired performance of a formulation as it goes from laboratory to production — often at plants in various parts of the world that use different equipment — requires well-defined quality criteria. “This not only reinforces the need for a holistic approach to powder characterization but the need for a holistic analysis of the entire design and manufacturing sequence,” he emphasizes.

So Freeman’s approach remains to simulate the process environment by subjecting the powder to the type of stress and flow regimes it will experience in-process and quantify the response. “The natural progression is therefore to extend our work to further understand the impact of processing variables. The caking white paper is a good example of this and further studies will investigate phenomena such as electrostatics and segregation,” notes Clayton.

Agglomerate Analysis

Agglomeration is the focus of the latest application note from Malvern Instruments, Malvern, U.K. “Identification of Agglomerates Using Automated Image Analysis,” describes the use of specific size and shape parameters, either independently or in combination, to identify agglomerates. It also exemplifies how automated image analysis helps reduce the workload associated with agglomerate detection by manual microscopy, and finishes by discussing the use of imaging in combination with Raman spectroscopy to detect multicomponent agglomerates.

The paper concludes that, taken together, these techniques enable quick analysis of a statistically relevant particle population for effective identification and classification of agglomerates. “These techniques can therefore be used to establish robust analytical methods for the analysis of agglomerates, aiding users in ensuring product quality remains consistent,” it states.

While estimating the total cost to the chemical industry of agglomeration-related issues is difficult, Paul Kippax, product group manager at Malvern, says it’s simple to see how they accumulate. In the case of inks, for example, agglomeration may reveal itself as instability during storage or in the printer reservoir, and poor performance at the print head. “In this instance the economic penalties for inadequate agglomeration control therefore ultimately present as loss of market share,” he notes.

With pharmaceuticals, agglomeration can detrimentally affect bioavailability and, consequently, the clinical efficacy and safety of a drug. On the other hand, agglomeration in the form of granulation often is deliberately used to enhance the flowability of tableting blends. “Here understanding and controlling agglomeration may therefore be a critical step in the development of a successful drug submission. Where this is the case, the financial benefit of resolving agglomeration issues rapidly is considerable.”

Overall, Malvern’s recent experience suggests that most formulators understand the potential problems associated with agglomeration. Furthermore there is well-established manufacturing practice within the industry with regard to dealing with agglomerated materials. For example, both milling and dispersion techniques are applied routinely, as necessary, to return a material to its intended particle size distribution. These options, although energy intensive, are generally effective for particle size control.

The real challenge from agglomeration comes with particle sizes below 20 microns. “Below 20 microns, and most especially as particle size falls below 10 microns, the strength of interparticulate forces increases substantially and there is a corresponding rise in the adhesion/cohesion mechanisms that underpin agglomeration,” says Kippax.

Automated image analysis is especially useful here and the chemical industry is receptive to it so long as the benefits are clearly and specifically demonstrated, he notes. “One of the attractive features of automated imaging is that you can literally see what extra information the method is going to provide. In some processes, agglomerates can be distinguished from primary particles simply on the basis of size, but in many instances this approach is not reliable, most especially when a product contains large primary particles.”

Automated imaging allows visual identification of agglomerates because images of each particle in a sample are recorded. This enables putting into place a secure classification procedure on the basis of size and shape. Agglomerates tend to be less regularly shaped than primary particles but each application calls for a unique set of classification criteria, which can be easily established via a series of scoping analyses.

The toughest agglomeration challenges are those where even size and shape in combination fail to adequately differentiate primary particles from agglomerates, Kippax says. Here, new imaging systems that also incorporate Raman spectroscopy can help because they enable the chemical identification of particles in a blend, thereby bringing an additional level of insight and a greater ability to reliably classify particles of similar morphology (Figure 2).

He cites the production of modern ceramics as a classic example where agglomeration control is critical. The properties of the finished product highly depend upon the physical properties of the powdered ceramic, most especially particle size and particle size distribution. These parameters affect both the packing behavior of the powdered ceramic and sintering times. Large particles tend to pack inefficiently, leading to the formation of pores that persist in the finished component, reducing its mechanic strength. In addition, large agglomerates can lead directly to defect formation during sintering, as agglomerated grains tend to grow more quickly than well-dispersed particles. Pore formation is controlled by eliminating agglomerates or using finer or polydisperse powders.

“In this application, laser diffraction is a valued technique because it has a broad dynamic range. This means that it can be used to accurately measure both the coarse and fine fraction of particles in a given sample. Laser diffraction is especially sensitive to the presence of coarse material and will therefore detect even small amounts of large particles that could compromise the quality of the finished product. Image analysis is highly complementary and can be used to differentiate large primary particles from agglomerates to provide the insight needed for secure process control,” he explains.

Today particle size is effectively used to control a broad range of factors, including reactivity, dissolution properties, packing density, bioavailability, flowability, stability, ease of inhalation, optical properties and consumer perception — many directly relating to the quality of the finished product and processability.

However, as manufacturing processes become more sophisticated, in many cases particle size data alone aren’t sufficient to control these factors. “It is often when manufacturers have exhausted the scope for process or product improvement afforded by particle size measurement alone that they become interested in other techniques such as automated image analysis, which can bring additional insight for product improvement or process troubleshooting,” Kippax concludes.

 Seán Ottewell is Chemical Processing's Editor at Large. You can email him at [email protected].

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