Oscillatory flow in confined spaces is central to understanding physiological flows and rational design of synthetic periodic-actuation based micromachines. Using theory and experiments on oscillating flows generated through a laser-induced cavitation bubble, we associate the dynamic bubble size (fluid velocity) and bubble lifetime to the laser energy supplied—a control parameter in experiments. Employing different channel cross-section shapes, sizes and lengths, we demonstrate the characteristic scales for velocity, time and energy to depend solely on the channel geometry. Contrary to the generally assumed absence of instability in low Reynolds number flows (<1000), we report a momentary flow distortion that originates due to the boundary layer separation near channel walls during flow deceleration. The emergence of distorted laminar states is characterized using two stages. First the conditions for the onset of instabilities is analyzed using the Reynolds number and Womersley number for oscillating flows. Second the growth and the ability of an instability to prevail is analyzed using the convective time scale of the flow. Our findings inform rational design of microsystems leveraging pulsatile flows via cavitation-powered microactuation.

Correction to: Scientific Reportshttps://doi.org/10.1038/s41598-024-68971-x, published online 13 August 2024 In the original version of this Article a previous rendition of Figure 2B, Figure 4 and Figure 5D was published. The original Figure 2, 4 and 5 and accompanying legends appear below. (Figure presented.) (Figure presented.) (Figure presented.) (A) Representative bubble dynamics for different channel geometries. (B) Universal motion of bubbles within channels with different size, shape and length. The dashed line represents the developed theory, Eq. (2). The marker colors represent the hydraulic diameters (d_h), the shapes represent the cross-section and the facecolor represent the lengths (L). The graphical marker symbols and colors established here are followed throughout this article. The black arrow represents the region of deviation(s) from the expected dynamics. The threshold laser energy absorbed for bubble formation estimated from experiments (E_th,exp) against theory (E_th,theory) presented in Eq. (5). (A,B) Representative dynamic bubble size curves illustrating the emergence of instabilities. The zones of the instabilities are highlighted using a shaded rectangular area. The arrows represent if the instabilities occur before or after X_max. (A) Illustrates the experimental data for different d_h with similar oscillation time. The instabilities emerge with increasing d_h. (B) Illustrates the data for d_h = 200 µm with increasing laser energies. The instabilities disappear with increasing E_abs. (C) Flow stability diagram with the transition line at W_o = 734. The markers represent the experiments and the lines represent the analytical estimate. The numbers correspond to the channel hydraulic diameters (in µm) with the dashed and solid lines representing the channel lengths L = 25 and 50 mm, respectively. (D) The dimensionless convective timescale against the L/d_h aspect ratio. The partition line is a linear relation between the x and y axes with 45 × 10⁻⁶ as the slope and the origin as the intercept. The original Article has been corrected.

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.

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.

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.