Non-photochemical laser-induced nucleation (NPLIN) has emerged as a promising primary nucleation control technique offering spatiotemporal control over crystallization with potential for polymorph control. So far, NPLIN was mostly investigated in milliliter vials, through laborious manual counting of the crystallized vials by visual inspection. Microfluidics represents an alternative to acquiring automated and statistically reliable data. Thus we designed a droplet-based microfluidic platform capable of identifying the droplets with crystals emerging upon Nd:YAG laser irradiation using the deep learning method. In our experiments, we used supersaturated solutions of KCl in water, and the effect of laser intensity, wavelength (1064, 532, and 355 nm), solution supersaturation (S), solution filtration, and intentional doping with nanoparticles on the nucleation probability is quantified and compared to control cooling crystallization experiments. Ability of dielectric polarization and the nanoparticle heating mechanisms proposed for NPLIN to explain the acquired results is tested. Solutions with lower supersaturation (S = 1.05) exhibit significantly higher NPLIN probabilities than those in the control experiments for all laser wavelengths above a threshold intensity (50 MW/cm²). At higher supersaturation studied (S = 1.10), irradiation was already effective at lower laser intensities (10 MW/cm²). No significant wavelength effect was observed besides irradiation with 355 nm light at higher laser intensities (≥50 MW/cm²). Solution filtration and intentional doping experiments showed that nanoimpurities might play a significant role in explaining NPLIN phenomena.

We present a droplet microfluidic platform mixing the contents of the droplet chaotically in microfluidic induction time measurements, a promising method for quantifying nucleation kinetics with minute amounts of solute. The nucleation kinetics of aqueous potassium chloride droplets dispersed in mineral oil without surfactants is quantified in the presence and absence of chaotic mixing. We demonstrate the ability of the proposed platform to dictate droplet size, to provide a homogeneous temperature distribution, and to chaotically mix the droplet contents. Chaotic mixing in induction time measurements is facilitated by the motion of droplets through serpentine micromixer bends, while the extent of mixing is controlled by how much droplets move. Different nucleation kinetics are observed in experiments where the droplets are static, mixed, and in motion. We hypothesize that the droplet motion induces formation of a thin-liquid Bretherton film surrounding the droplets. The thin film shields droplets from solid boundaries that are more efficient heteronucleant surfaces compared to liquid-liquid interfaces. We observed that repeated microfluidic induction time measurements, particularly with moving droplets, produce significantly distinct cumulative nucleation probability curves, indicating that the measured nucleation kinetics depend strongly on the details of the experimental procedure, which we discuss in detail. Finally, we compare the microfluidic experiments to well-mixed, milliliter volume, turbidity-based measurements in the context of classic nucleation theory.

A droplet-based microfluidic platform is presented to study the nucleation kinetics of calcium oxalate monohydrate (COM), the most common constituent of kidney stones, while carefully monitoring the pseudo-polymorphic transitions. The precipitation kinetics of COM is studied as a function of supersaturation and pH as well as in the presence of inhibitors of stone formation, magnesium ions (Mg2+), and osteopontin (OPN). We rationalize the trends observed in the measured nucleation rates leveraging a solution chemistry model validated using isothermal solubility measurements. In equimolar calcium and oxalate ion concentrations with different buffer solutions, dramatically slower kinetics is observed at pH 6.0 compared to pHs 3.6 and 8.6. The addition of both Mg2+ and OPN to the solution slows down kinetics appreciably. Interestingly, complete nucleation inhibition is observed at significantly lower OPN, namely, 3.2 × 10-8 M, than Mg2+ concentrations, 0.875 × 10-4 M. The observed inhibition effect of OPN emphasizes the often-overlooked role of macromolecules on COM nucleation due to their low concentration presence in urine. Moreover, analysis of growth rates calculated from observed lag times suggests that inhibition in the presence of Mg2+ cannot be explained solely on altered supersaturation. The presented study highlights the potential of microfluidics in overcoming a major challenge in nephrolithiasis research, the overwhelming physiochemical complexity of urine.

Nonphotochemical laser-induced nucleation (NPLIN) is a promising primary nucleation control method, yet its underlying mechanism remains elusive. To contribute to the discussion on whether the polarization of laser irradiation in NPLIN experiments influences the polymorphic outcome, we revisit NPLIN experiments with aqueous glycine solutions with supersaturations ranging between S = 1.5 and S = 1.7 irradiated by nanosecond pulses (∼7 ns) of near-infrared wavelength (1064 nm). Systematically altering laser light excitation properties, including the number of pulses and type of polarization, we quantified the nucleation kinetics and characterized the polymorphic form that crystallized upon laser irradiation. Due to the stochasticity of the nucleation process, a large number of samples (>100 per each experimental point) were studied under carefully controlled experimental conditions such as the ambient temperature, cooling rate, and aging period. We observed significant differences among laser-irradiated, spontaneously nucleated, and crash-cooled samples in terms of nucleation kinetics and polymorphic form. This result indicates that laser irradiation provides a different polymorph-forming pathway in comparison to crash-cooling and spontaneous nucleation. However, no clear dependence between the polymorphic form and the polarization of laser irradiation is observed. We discuss our results in the context of previous reports supported thorough quantification of sample heating in NPLIN experiments.

In this study, an in situ imaging system has been analysed to characterize the crystal size, the shape and the number of particles during a continuous crystallization process in a Continuous Oscillatory Baffled Crystallizer (COBC). Two image analysis approaches were examined for particle characterization in the suspension containing both small nuclei and larger grown crystals (nonspherical and irregular in shape). The pattern matching approach, in which the particles are approximated to be spherical, did result in an overestimation of the size. Alternatively, a segmentation-based algorithm resulted in reliable crystal size and shape characteristics. The laser diffraction analysis in comparison to the image analysis overestimated the particle sizes due to the agglomeration of particles upon filtration and drying. The trend in the particle counts during the start of crystallization process, including nucleation, determined by the image analysis probe was comparable with the one measured by FBRM, highlighting the potential of in situ imaging for process monitoring.

Various mechanisms have been proposed to explain the nonphotochemical laser-induced nucleation (NPLIN). Identifying the dominant mechanism requires addressing a large set of experimental parameters with a statistically significant number of samples, forced by the stochastic nature of nucleation. In this study, with aqueous KCl system, we focus on the nucleation probability as a function of laser wavelength, laser intensity, and sample supersaturation, whereas the influence of filtration and the laser-induced radiation pressure on NPLIN activity is also studied. To account for the nucleation stochasticity, we used 80-100 samples. The NPLIN probability showed an increase with increasing laser intensity. The results are different from the previous report, as a supersaturation independent intensity threshold is not observed. No dependence of the NPLIN probability on the laser wavelength (355, 532, and 1064 nm) was observed. Filtration of samples reduced the nucleation probability suggesting a pronounced role of impurities on NPLIN. The magnitude and the propagation velocity of the laser-induced radiation pressure were quantified using a pressure sensor under laser intensities ranging from 0.5 to 80 MW/cm². No correlation was found between the radiation pressure and NPLIN at our unfocused laser beam intensities ruling out the radiation pressure as a possible cause for nucleation.

The control of nucleation in crystallization processes is a challenging task due to the often lacking knowledge on the process kinetics. Inflexible (predetermined) control strategies fail to grow the nucleated crystals to the desired quality because of the variability in the process conditions, disturbances, and the stochastic nature of crystal nucleation. Previously, the concept of microwave assisted direct nucleation control (DNC) was demonstrated in a laboratory setup to control the crystal size distribution in a batch crystallization process by manipulating the number of particles in the system. Rapid temperature cycling was used to manipulate the super(under)saturation and hence the number of crystals. The rapid heating response achieved with the microwave heating improved the DNC control efficiency, resulting in halving of the batch time. As an extension, this work presents a novel design in which the microwave applicator is integrated in the crystallizer, hence avoiding the external loop though the microwaves oven. DNC implemented in the 4 L unseeded crystallizer, at various count set points, resulted in strong efficiency enhancement of DNC, when compared to the performance with a slow responding system. The demonstrated crystallizer design is a basis for extending the enhanced process control opportunity to other applications.

A comprehensive methodology to carry out a sequential parameter estimation approach has been developed and validated for the determination of the kinetic parameters of the crystallization of a generic organic compound. The strength of the approach lies in the thorough design of isothermal experiments which facilitate the isolation and/or decoupling of the different crystallization phenomena. This methodology has been applied for the parameter estimation of primary and secondary nucleation, growth and agglomeration kinetics. The resulting crystallization model has been able to reproduce the quantiles d₁₀, d₅₀ and d₉₀ of the volume-based particle size distribution of an independent seeded validation experiment with an error below 10 μm. The deviation in the prediction has been increased in the case of an independent unseeded experiment, although errors below the uncertainty of the measurement have been always obtained. The methodology here proposed is intended to be an efficient strategy for rapid modeling of batch crystallization processes. Â

A crystallizer was built and a procedure developed to accurately measure the eutectic solubility lines where ice and salt coexist in equilibrium with the solution, for potential application of Eutectic Freeze Crystallization. The eutectic solubility lines of the ternary system NaHCO₃-Na₂CO₃-H₂O were determined experimentally and calculated with the extended UNIQUAC model. The extended UNIQUAC model describes the experimental data quite well. Anhydrous NaHCO₃ and Na₂CO₃·10H₂O were the only two types of crystals present in equilibrium with ice crystals in the ternary system. At the quadruple point NaHCO₃ and Na₂CO₃·10H₂O are in equilibrium with a solution of about 4.34wt% of Na₂CO₃ and 4.77wt% of NaHCO₃ at -3.32°C. The anhydrous NaHCO₃ crystals were needle shaped with lengths between 5 and 10μm, that were agglomerated into particles of about 100-300μm, while the Na₂CO₃·10H₂O crystals were hexagonally shaped with sizes between 100 and 500μm.