Effect of operating parameters on the microbubble size
It was observed that most of the microbubbles generated in the device were compressed between the top and the bottom surfaces of the microchannel, because the bubbles generated were larger than the depth of the microchannel. Bubbles smaller than the height of the channel (only a very small fraction of the total bubble population) adhered to the top surface of the channel and deformed due to the buoyant force. Therefore, all bubbles observed in the experiments were not spherical. It was assumed that the contact angles of the squashed bubbles on the channel walls (both on the PDMS and the glass surface) were very low (≈ 2 deg) (Abeywickrema et al. 2018). Therefore, the shape of the squashed microbubbles was considered to be a symmetrical ellipsoid (oblate spheroid). The diameters measured and reported in this study are equivalent to two equal semi-axis length of the spheroid, which is known as the equatorial diameter, \( d_{\text{e}} \). The depth of the microchannel (150 µm) was taken as the height (h) of the spheroid. The validity of this assumption was verified prior to bubble size analysis.
Considering a case where monodisperse microbubbles (polydispersity index \( \sigma \) < 4%, defined later) are produced within the device. The volume of an oblate spheroid (\( V_{\text{s}} \)) is given by
$$ V_{\text{s}} = \frac{1}{6}\pi d_{\text{e}}^{2} h, $$
(3)
Then, the total volume of gas (\( V_{b} \)) within \( n \) bubbles generated in time \( t^{\prime} \) can be calculated as
$$ V_{\text{b}} = \frac{1}{6}n\pi h\overline{{d_{e}^{2} }} , $$
(4)
where \( \overline{{d_{e}^{2} }} \) is the average of \( d_{\text{e}}^{2} \) for the bubbles generated during time \( t^{\prime} \).
If the shape of the bubbles within the microchannel can be represented by oblate spheroid, total volume of bubbles calculated using Eq. 4 should be equal to the gas discharged by the mass flow controller during the bubble generation process (\( V_{\text{inlet}} \)). Since the device is operated at low pressure (~ 1 bar), any volume change of the gas can be neglected. Volume change of gas due to humidity change was also neglected due to low-temperature (20 °C) operation. The total amount of gas discharged during bubble generation process is calculated as
$$ V_{\text{inlet}} = t^{\prime}Q_{\text{ig}} , $$
(5)
where \( Q_{\text{ig}} \) is the volumetric gas flow at the mass flow controller at standard conditions. The operating time \( \left( {t^{\prime}} \right) \) for this analysis was obtained by measuring the number of frames to produce 20 microbubbles and multiplying that by the time between two frames (0.1 ms when images recorded at 10,000 fps). This analysis was carried out at a liquid flow rate of 150 ml/h with the gas flow rate ranging from 0.2 sccm to 1 sccm, as these operating conditions produce a single bubble population with a low polydispersity index. Gas volumes calculated by Eqs. 4 and 5 are compared in Table 1.
Table 1 Comparison of gas volumes \( V_{\text{b}} \) and \( V_{\text{inlet}} \) calculated at \( Q_{\text{l }} \)= 150 ml/h
The difference between the volumes of gas discharged at the mass flow controller and the gas volumes is calculated using image analysis, and Eq. 4 agrees well within 5% for all operating conditions tested. This confirms our assumption that microbubbles recorded in the device are of oblate spheroid shape is valid; hence, average equatorial diameter (\( d_{\text{e,av}} \)) will be used in reporting bubble sizes produced in the device. Bubble size distributions acquired from image analysis were then used to determine the effects of volumetric gas flow rate, \( Q_{\text{ig }} \)(flow rate measured by the mass flow controller), and the liquid flow rate, \( Q_{\text{l }} \), on the microbubble size generated. Plasma was turned off for the first stage of the study.
Typical bubble generation process at the orifice is shown in Fig. 3. As both the gas and liquid flow into the flow-focusing area, gas–liquid interface forms a narrowing gas jet due to the liquid streams arriving from either side of the nozzle. As the gas–liquid interface passes the orifice (narrowing section) into the collection nozzle, gas expands and starts forming a bubble. Due to liquid drag from either side, the bubble starts to elongate in the flow direction until necking occurs. At this stage, the connection between the bubble and the gas flow is dynamically unstable and leads to bubble break-up. This newly generated bubble is entrained with the liquid flow but moves slower than the surrounding liquid due to viscous dissipation at the bubble–wall contact. The tip of the gas–liquid interface retracts back to the flow-focusing area following a break-up event. Bubbles moving in the collection chamber form highly ordered flowing bubble lattices. This sequence of events completes the cycle for bubble generation at low gas and liquid flow rates. A microscopic image of the bubbles produced in this regime and their respective bubble size distribution is shown in Fig. 4a.
However, when the gas flow rate exceeds a critical value at a given liquid flow rate, newly generated bubbles (B1) get squashed between the preceding bubble (B0) and the newly forming bubble (B2)—see Fig. 3c. This leads to elongation of the bubble (B1) in the transverse direction to the flow and could break-up into two or multiple bubbles. This observation agrees with the previous work where the bubble generation mechanism in a flow-focusing system changed into a different regime, when the gas flow rate exceeded a critical value (Garstecki et al. 2004). We believe that this transition occurs due to an increase in bubble density inside the observation chamber, when the gas volumetric flow rate exceeds the critical value for the device while the liquid flow rate is kept constant. There are several forces acting on a bubble that has just been formed (B1)—(i) drag force from the liquid flowing around the bubble, (ii) surface tension force at the top and bottom surfaces of the channel where bubble makes contact with channel walls, (iii) viscous dissipation where a thin film exists between the bubble and the channels, (iv) elastic shape restoring forces and (v) contact pressure force acting within the forming bubble (B2) that exerts a force on the formed bubble (B1). These forces elongate and destabilise bubble B1 and, if high enough (above the critical flow rate), will result in a break-up. The following bubble (B2) will only get elongated (no break-up); hence, this bubble splitting process is alternative. Break-up events that occur at the entrance to the collection chamber can be different depending on the flow parameters used. This could result in several bubble populations for a single experiment as shown in Fig. 4b–d. Let us denote the initial bubble populations produced at the orifice as \( P_{0} \). If a single bubble break-up event occurs repeatedly, two daughter bubble populations are produced—\( P_{1}^{i} \) (smaller daughter bubbles) and \( P_{1}^{j} \) (larger daughter bubbles). High gas and liquid flow rates could lead to two break-up events which lead to four daughter bubble populations—\( P_{1}^{i} \) and \( P_{1}^{j} \) from the first break-up event and \( P_{2}^{i} \) and \( P_{2}^{j} \) from the second break-up event.
At \( Q_{\text{l }} \) = 120 ml/h and \( Q_{\text{ig}} \) = 0.6 sccm, a single bubble population (\( P_{0} \)) is produced with no break-up events as shown in Fig. 4a. This is the typical outcome at low gas and liquid flow rates. When the gas flow rate is increased to 1.5 sccm (keeping \( Q_{\text{l }} \) at 120 ml/h, unchanged), a single repeated bubble break-up occurs. In this special case, daughter bubbles produced are approximately equal in size; therefore, only two bubble populations are produced (\( P_{0} \) and \( P_{1} \)) as shown in Fig. 4b. Images taken at this operating condition show that the daughter bubbles have moved away from the axis of the chamber and form a highly ordered lattice. Further increase in the gas flow rate to 2 sccm leads to unequal daughter bubbles from the single repeated break-up event (Fig. 4c). We believe that this is due to symmetry breaking nature of the bubble splitting process. At high gas and liquid flow rates tested, i.e. \( Q_{\text{l }} \) = 150 ml/h, \( Q_{\text{ig}} \) = 2 sccm, two repeated bubble break-up events occur with unequal bubble sizes leading to five bubble populations (\( P_{1} \), \( P_{1}^{i} \), \( P_{1}^{j} \), \( P_{2}^{i} \) and \( P_{2}^{j} \)) as shown in Fig. 4d.
The average equatorial diameter (\( d_{\text{e,av}} \)) and polydispersity index (\( \sigma \)) for bubble size distributions are shown in Fig. 5. Variations in bubble sizes in a bubble population were calculated using polydispersity index (\( \sigma \)) defined as
$$ \sigma = \frac{\delta }{{d_{\text{e,av}} }} \times 100\% , $$
(6)
where \( \delta \) is the standard deviation of measured equatorial diameters. In cases where daughter bubbles are produced and more than one peak was observed in the bubble size distributions shown in Fig. 4, \( \sigma \) was calculated separately for each bubble population and shown in the same figure using arrows leading from the initial bubble populations. For the lower liquid flow rates tested (i.e. 120 and 150 ml/h), \( d_{\text{e,av}} \) of the main population increases with \( Q_{\text{ig }} \) and a linear relationship is observed. For a given gas flow rate, a higher liquid flow rate always produced the smallest bubbles due to high liquid momentum and drag acting on the forming bubble. Therefore, the microbubble size is dependent on the flow ratio between \( Q_{\text{ig }} \) and \( Q_{l } \), whereby as \( Q_{\text{ig }} \) /\( Q_{\text{l }} \) increases, \( d_{e,av} \) increases (except for \( Q_{\text{l }} \) = 180 ml/h whereby the trend changes after \( Q_{\text{ig }} \) exceeds 0.8 sccm). This was expected due to the reduction in the shear stress and elongation when \( Q_{\text{l }} \) decreases (Dietrich et al. 2008). Daughter bubbles were produced at \( Q_{\text{ig }} \) > 1.5 sccm, \( Q_{\text{l }} \) = 120 ml/h and at \( Q_{\text{ig }} \) > 2 sccm, 150 ml/h. Transition of the bubble generating regime for daughter bubble production started at a lower \( Q_{\text{ig }} \) for \( Q_{\text{l }} \) = 120 ml/h compared to that of \( Q_{\text{l }} \) = 150 ml/h, and this could be due to the higher density of bubbles at the entrance to the collection chamber compressing the newly formed or forming bubbles as described earlier. In contrast, for the higher liquid flow rates tested (i.e. 180 ml/h), \( d_{\text{e,av}} \), increased with \( Q_{\text{l }} \) up to \( Q_{\text{ig }} \) = 0.8 sccm in a linear manner followed by a gradual drop \( d_{\text{e,av}} \) beyond \( Q_{\text{ig }} \) = 0.8 sccm. No daughter bubble population was observed at this liquid flow rate. This can be identified as another critical flow rate at which high liquid shear stress breaks up bubbles earlier in the growth phase and produces smaller bubbles that are stable and less susceptible to split in the collection chamber.
The polydispersity index (\( \sigma \)) for bubble size distributions shown in Fig. 5b varied between 2 and 7% and did not have a clear correlation with the gas flow rate. However, device operated at low liquid flow rates (120 ml/h and 150 ml/h) produced the least variability, where \( \sigma \) < 5% for all gas flow rates. \( \sigma \) for daughter bubble populations was reported separately on the same graph, and all values are below 5%. This result clearly demonstrates the capability of the device to generate monodisperse microbubbles. For the higher liquid flow rate of \( Q_{\text{l }} = \) 180 ml/h, operating condition at which no new bubble populations were observed, an increase in \( \sigma \) was observed for \( Q_{\text{ig }} \) > 0.8 sccm. Under these flow conditions, bubbles are significantly smaller than the bubbles observed at the lower liquid flow rates tested; hence, the bubble generation frequency increases dramatically. This limits the time for the gas–liquid interface to retract completely after bubble necking; therefore, variation in bubble growth time can be expected.
Effect of plasma on bubble generation
As the main purpose of the device is to transfer reactive species generated by the plasma to the liquid phase, it is essential to study the effect of plasma discharge on the microbubble generation. \( d_{\text{e,av}} \) measured with the plasma at various gas and liquid flow rates are shown in Fig. 6a. The trends observed in this graph are almost identical to that of with no plasma discharge, whereby an increase in the ratio \( Q_{\text{ig }} \)/ \( Q_{\text{l }} \) leads to an increase in \( d_{\text{e,av}} \). However, the magnitude of \( d_{\text{e,av}} \) values has changed for all inlet gas flow rates. Calculations confirmed that all \( d_{\text{e,av}} \) values increased by 5–8% as a result of the plasma. A comparison of this effect is shown in Fig. 6b, where \( d_{\text{e,av}} \) values are compared with and without the plasma effect at \( Q_{\text{l }} \) = 150 ml/h. It is interesting to note that daughter bubbles were produced at \( Q_{\text{ig }} \ge \) 1.5 sccm with plasma compared to that of operation at \( Q_{\text{ig }} \ge \) 2 sccm without plasma. A further study was conducted to investigate the change in microbubble formation time and the volumetric gas flow rate at the bubble forming orifice (\( Q_{\text{or}} \)) when operated with the plasma discharge.
Volumetric gas flow rate at the orifice (\( Q_{\text{or}} \)) was determined as before by calculating the volume of 20 bubbles produced in the device and time for their formation in the presence of plasma. Table 2 and Fig. 7 show that plasma discharge increases the volumetric gas flow rate by 17–25% due to thermal expansion. Gas is supplied to the device at ~ 1 bar and 20 °C in all experiments, but as the gas flows through the plasma generation zone gas temperature increases. This leads to an increase in the volumetric gas flow rate at the orifice (\( Q_{\text{or}} \) at a temperature of \( T_{\text{or}} \)) compared to the inlet gas flow supplied by the mass flow controller (\( Q_{\text{ig }} \) at 20 °C). The temperature of the gas plasma (\( T_{\text{plasma }} \)) depends on various factors such as geometric features of the device, electric field applied, material properties and gas flow rate, but most DBD plasmas operate in the temperature range of 40–150 °C (Förster et al. 2005; Joussot et al. 2010; Wei et al. 2011; Daeschlein et al. 2012). Due to the heat losses through the microchannel walls, \( T_{{{\text{or}} \ne }} T_{\text{plasma}} \).
Table 2 Comparison between \( Q_{\text{ig}} \) and \( Q_{\text{or}} \) at \( Q_{\text{l }} \) = 150 ml/h with plasma
In addition to the thermal expansion of the gas, several other factors associated with the plasma could affect bubble generation. Gas flow through a plasma is unstable due to micro-discharges and shear instabilities (Lietz et al. 2017), and this could lead to high variability in the bubbles generation process. However, \( \sigma \) for microbubbles produced with plasma varied between 2 and 7% in this study. It is also reported that surface tension could be affected by the plasma species dissolved in the liquid (Yoon et al. 2018; Sommers et al. 2011) and as a consequence could alter bubble generation process. To ascertain whether these effects played a role in the bubble generation process in addition to thermal expansion, \( d_{\text{e,av}} \) was plotted against the flow rate at the orifice (\( Q_{\text{or}} \)) for both with and without plasma at 150 ml/h. In contrast to Fig. 8a, where \( d_{\text{e,av}} \) vs \( Q_{\text{ig }} \) graphs for operation with plasma and without plasma are separate, \( d_{\text{e,av}} \) vs \( Q_{\text{or}} \) graphs shown in Fig. 8b overlapped. This suggests that the change in volumetric gas flow rate by the plasma discharge was the main factor that affected bubble size. The gas temperature at the orifice (\( T_{\text{or}} \)) can be estimated by using combined ideal gas law as shown in Eq. (7).
$$ \frac{{P_{1 }^{'} V_{1} }}{{T_{1} }} = \frac{{P_{2}^{'} Q_{\text{or}} }}{{T_{\text{or}} }}, $$
(7)
where \( P_{1}^{'} \), \( V_{1} \) and \( T_{1} \) are pressure, volumetric flow rate and temperature of the gas at the inlet of the device and \( P_{2}^{'} \), \( Q_{\text{or}} \) and \( T_{\text{or}} \) are that of at the orifice, respectively. The pressure change due to plasma discharge was assumed to be negligible for these calculations. Figure 7 shows that the percentage increase in the gas flow rate from \( Q_{\text{ig}} \) to \( Q_{\text{or}} \) is proportional to \( T_{\text{or}} \) and combined with the results shown in Fig. 8b provides evidence to confirm that the bubble size increases under plasma operation was due to the thermal expansion of the gas.
Effect of surfactant concentration
Surfactant (PVA) was dissolved in all test solutions to obtain stable microbubbles and reduce bubble coalescence. Surfactants reduce the free energy required to produce bubble surfaces by reducing the interfacial surface tension (Langevin 2017). Since test solutions used in the experiments contained PVA at a concentration of 1 CMC or above, measured surface tension was 45 mN/m for all solutions. However, viscosity increased gradually with CMC and the results are shown in Fig. 9. It was observed that the average diameter of the bubbles decreases as the viscosity increases for both cases (i.e. with and without plasma), when the fluid flow rates were kept constant. These results agree with droplet formation in a T-shaped microchannel (Xu et al. 2006). It is possible that both the viscosity increase and the change in dynamic surface tension associated with increasing surfactant concentration contributed to this effect. Furthermore, the difference in average microbubble size produced for the two cases was reduced at high CMC values. This result suggests that liquid viscosity is a control parameter that can be manipulated to optimise the bubble size for mass transfer when operated with the plasma.
Mass transfer of reactive species
Mass transfer performance of the microfluidic device was evaluated by measuring the degradation of indigo solutions for single pass treatments. The results are shown in Fig. 10. For all three liquid flow rates tested, the highest indigo degradation occurred at \( Q_{\text{ig}} \approx \) 0.8 sccm, while the lowest dye degradation occurred at \( Q_{\text{ig }} \) = 0.2 sccm. As the gas flow rate through the plasma generation zone increases, concentration of reactive species in the plasma effluent is expected to increase proportionately. However, since the power input to the plasma is constant (120 mW ± 12%), concentration of reactive species in the gas effluent is expected to plateau at high gas flow rates. Furthermore, we found that microbubble size increases with \( Q_{\text{ig }} \) (as shown in Fig. 6a); hence, the mass transfer rates could be affected. Due to these competing effects, decolourisation percentage at \( Q_{\text{ig }} \ge 0.4 \) observed in Fig. 10 is nearly constant for all liquid flow rates. The difference in decolourisation percentage observed at various liquid flow rates in Fig. 10 could be due to several reasons. Consider the case where gas flow rate is kept constant and the liquid flow rate is increased gradually. Firstly, the residence time of the liquid in contact with the bubbles will decrease providing less time for mass transfer. Secondly, high liquid throughput treats a higher liquid volume within a given time; therefore, concentration reduction of indigo will be less compared to that of at low \( Q_{\text{ig }} \). Finally, bubble size decreases with the liquid flow rate as shown in Fig. 6a and will affect mass transfer rates.
In Fig. 10, decolourisation percentages reported at each liquid flow rate treated different volumes of liquid in a given time. In order to compare the transfer rate of reactive species under different operating conditions, the amount of dye degraded per a unit time should be considered. Figure 11 is plotted by multiplying the percentage decolourisation with the respective liquid flow rate under which the experiment was carried out. Overlap of graphs for different liquid flow rates suggests that the influence of the liquid flow rate on the mass transfer rate is negligible. Slight drop in degradation rate at the higher liquid flow rate may be attributed to insufficient residence time of the liquid in the device for mass transfer. Figures 10 and 11 do not provide a clear correlation between the bubble size produced and mass transfer as mixing patterns at the orifice and bubble lattices formed at the collection chamber may also play a part in mass transfer.
In designing a microfluidic device for generation and transfer of reactive species, it is useful to know the volumetric mass transfer coefficient (\( K_{\text{L}} a \)). Concentration measurements of species are generally used with Eq. 8 to estimate the \( K_{\text{L}} a \), where \( C_{i}^{*} \) is the physical solubility of species \( {\text{i}} \) in the solution, \( C_{\text{i, inlet}} \) and \( C_{{i , {\text{outlet}}}} \) are liquid phase concentration of species \( i \) at the inlet and outlet and \( t \) is the residence time (Yue et al. 2007).
$$ K_{\text{L}} a = \ln \left( {\frac{{C_{\text{i}}^{*} - C_{\text{i, inlet}} }}{{C_{\text{i}}^{*} - C_{\text{i, outlet}} }}} \right) \cdot \frac{1}{t}. $$
(8)
In this study, several plasma species were produced and transferred to the solution, and most of them are known to decolourise the dye. In order to estimate the \( K_{\text{L}} a \) values for each species, separate concentration measurements are required. These measurements are difficult as most reactive species require specific probes that selectively measure their concentration. Furthermore, short lifespan of highly reactive species makes it difficult to detect them in the bulk liquid as their effective diffusion lengths vary from ~ 10−8 to 10−4 m (Liu et al. 2015). Even though the indigo decolourisation percentages reported in Fig. 10 are useful in comparing mass transfer efficiency at different operating parameters, these results cannot be used to determine \( K_{\text{L}} a \).
Decolourisation of indigo dye presented in this study is comparable to previous studies reported in the literature. For instance, Ruo-bing et al. (2005) and Gao et al. (2013) achieved a discoloration rate of 40% with a 20-min treatment and 99% with a 15-min treatment in a batch reactor, respectively. At the optimal conditions, this study achieved up to 60% decolouration within 5–10 s of treatment using the combined plasma microbubble chip developed. This result clearly demonstrates the potential of this microfluidic reactor for transferring reactive species continuously into a target liquid.