(424g) An Acoustic Streaming Microcrystallizer with Controllable Mixing and Fluid Shear to Study the Nucleation Kinetics of Acetaminophen

The pharmaceutical industry benefits tremendously from systems which improve control over the crystallization of an active pharmaceutical ingredient to speed up the design and development of new drug products. Particularly the nucleation step, which is the first step of crystallization and therefore affects all subsequent steps, is difficult to study, control, and predict. One route towards improved control over the nucleation process is through the use of microfluidic equipment, which offers high heat and mass transfer rates because of its large surface-to-volume ratio’s. Due to their low Reynolds number flows, microreactors suffer from two considerable drawbacks which impediments their use: weak convective mixing and particle clogging. The synergistic integration of ultrasound (sound waves with a frequency higher than 20 kHz) and microfluidic equipment has the potential to alleviate both problems ^1,2.

Acoustic streaming is the time-averaged fluid motion as a result of the viscous dissipation of an acoustic wave ^2,3. In microfluidic devices one specific type of acoustic streaming, Rayleigh streaming, can be induced by generating a standing ultrasonic wave in the reactor. A steady momentum flux from the pressure nodes to the antinodes then results in the appearance of counter-rotating vortices in the bulk of the solution ². Even though a lot of research has been done on the plethora of effects that are associated with the collapse and explosion of ultrasonic cavitation bubbles ^4,5, the effect of Rayleigh acoustic streaming on nucleation remains unexplored. This is surprising, as it has the potential to improve control over nucleation in small microcrystallizers. In this research acoustic streaming is studied as a controllable tool to intensify crystallization processes.

Methods

We present an acoustic streaming microcrystallizer with well-controlled mixing and fluid shear to control the nucleation kinetics of acetaminophen from aqueous solution. The microcrystallizer consists of a glass tube (with a volume of 392 L and a length of 15 cm) submersed in a temperature-controlled bath and is equipped with 16 periodically spaced axially polarized piezoelectric rings (as shown in the attached Figure). By applying an alternating voltage to these rings, a resonating standing wave in the axial direction is generated and streaming vortices appear. Changing the frequency alters the number of vortices between two piezoelectric rings (as shown in the attached Figure), whereas increasing the power intensity increases the strength of these vortices.

Firstly, the fluid mixing and shear in the microcrystallizer are measured for different ultrasonic frequencies and powers. The flows are characterized by recording the movement of inert polystyrene particles (2.5-3.0 m) in water (0.07 w%/v) in the sonicated microcrystallizer with a high-speed camera. These results are analyzed using PIVlab (in MATLAB) ⁶. The Villermaux-Dushman protocol ⁷ is used to characterize the micromixing. To determine the cavitational activity, or lack thereof, the concentration of OH-radicals present in the system is measured with terephthalic acid dosimetry ⁸.

Secondly, the nucleation kinetics of acetaminophen from aqueous solution are measured for various ultrasonic powers and frequencies. The induction time, defined here as the time from the start of sonication until the detection of the first crystal, in batch mode of operation is measured using microscopy images of the entire crystallizer for a supersaturation of approximately 6. The nucleation rates for different conditions are determined from their probability distributions of induction times ⁹.

Results

The number of vortices appearing between two piezo rings are observed: at 0.704, 1.344, and 2.304 MHz, respectively 6, 12, and 4 vortices are formed between two piezo rings. Streaming velocities from 0 to 2000 m/s and shear rates of up to 20 1/s can be generated using the streaming flows. Although cavitation is not completely suppressed, it does not affect the Rayleigh streaming in our setup. The production of radicals, which causes degradation of organic compounds, is orders of magnitude smaller than is common with conventional ultrasound equipment (which is operated at lower frequencies) ¹⁰.

Increasing the fluid mixing and shear by increasing the ultrasonic power from (0 W to 16 W) results in a large increase in the nucleation kinetics. At ultrasonic powers of 16 W the crystals follow the streamlines and form rotating torus-shaped patterns in the bulk of the solution. At lower powers, the number of crystals that nucleates is smaller such that they grow larger and eventually sediment. Changing the ultrasonic frequency did not affect the nucleation rates significantly.

Conclusions

In conclusion, acoustic streaming is shown to be an effective tool to control the nucleation kinetics in microcrystallizers, allowing for controllable fluid mixing and fluid shear by tuning the ultrasonic power intensity. A new acoustic streaming microcrystallizer actuated by piezoelectric rings, is presented. The crystallizer is designed and operated at resonance such that Rayleigh streaming is the dominant ultrasound mechanism. The microcrystallizer is completely characterized by linking the ultrasonic frequency and power to the fluid mixing and shear in the solution. These in turn are linked to the nucleation kinetics of acetaminophen from aqueous solution.

The microcrystallizer could be improved further by increasing the acoustic coupling between the capillary tube’s wall and the piezoelectric rings, such that the energy losses are reduced. In general, our experiments show the potential of acoustic streaming as an alternative energy source to control nucleation in small-scale tubular crystallizers. This work contributes to the development of ultrasonic microreactors for nucleation.

References

1 D. Fernandez Rivas and S. Kuhn, Top. Curr. Chem., , DOI:10.1007/s41061-016-0070-y.

2 M. Wiklund, R. Green and M. Ohlin, Lab Chip, 2012, 12, 2438–2451.

3 S. J. Lighthill, J. Sound Vib., 1978, 61, 391–418.

4 J. Jordens, B. Gielen, C. Xiouras, M. N. Hussain, G. D. Stefanidis, L. C. J. Thomassen, L. Braeken and T. Van Gerven, Chem. Eng. Process. - Process Intensif., 2019, 139, 130–154.

5 J. R. G. Sander, B. W. Zeiger and K. S. Suslick, Ultrason. Sonochem., 2014, 21, 1908–1915.

6 W. Thielicke and R. Sonntag, J. Open Res. Softw., 2021, 9, 1–14.

7 J. M. Commenge and L. Falk, Chem. Eng. Process. Process Intensif., 2011, 50, 979–990.

8 X. Fang, G. Mark and C. Von Sonntag, Ultrason. Sonochem., 1996, 3, 57–63.

9 S. Jiang and J. H. Ter Horst, Cryst. Growth Des., 2011, 11, 256–261.

10 J. Jordens, B. Gielen, L. Braeken and T. Van Gerven, Chem. Eng. Process. Process Intensif., 2014, 84, 38–44.