Analysis of the Diffusion Process by Ph Indicator in Microfluidic Chips

micromachines

Article Analysis of the Diffusion Process by pH Indicator in Microﬂuidic Chips for Liposome Production

Elisabetta Bottaro 1,2 , Ali Mosayyebi 1, Dario Carugo 1,3,* and Claudio Nastruzzi 2,*

1 Bioengineering Science Group, Faculty of Engineering and the Environment, University of Southampton, Southampton SO17 1BJ, UK; [email protected] (E.B.); [email protected] (A.M.) 2 Department of Life Science and Biotechnology, University of Ferrara, Via Fossato di Mortara 17, 44121 Ferrara, Italy 3 Institute for Life Sciences (IfLS), University of Southampton, Southampton SO17 1BJ, UK * Correspondences: [email protected] (D.C.); [email protected] (C.N.); Tel.: +44-(0)23-8059-3242 (D.C.); +39-0532-455348 (C.N.)

Received: 28 April 2017; Accepted: 17 June 2017; Published: 1 July 2017

Abstract: In recent years, the development of nano- and micro-particles has attracted considerable interest from researchers and enterprises, because of the potential utility of such particles as drug delivery vehicles. Amongst the different techniques employed for the production of nanoparticles, microfluidic-based methods have proven to be the most effective for controlling particle size and dispersity, and for achieving high encapsulation efficiency of bioactive compounds. In this study, we specifically focus on the production of liposomes, spherical vesicles formed by a lipid bilayer encapsulating an aqueous core. The formation of liposomes in microfluidic devices is often governed by diffusive mass transfer of chemical species at the liquid interface between a solvent (i.e., alcohol) and a non-solvent (i.e., water). In this work, we developed a new approach for the analysis of mixing processes within microfluidic devices. The method relies on the use of a pH indicator, and we demonstrate its utility by characterizing the transfer of ethanol and water within two different microfluidic architectures. Our approach represents an effective route to experimentally characterize diffusion and advection processes governing the formation of vesicular/micellar systems in microfluidics, and can also be employed to validate the results of numerical modelling.

Keywords: liposomes; microfluidic; mixing; diffusion; pH indicator; microfluidic hydrodynamic focusing

1. Introduction Nanomedicine is an attractive field involving the production and clinical application of size-controlled nanoparticles, usually employed in therapy as drug delivery systems or in diagnostics as contrast agents [1]. Amongst the different types of nanoparticles, liposomes have attracted considerable interest for their application as drug delivery systems. Liposomes are artificial spherical vesicles generally composed of natural phospholipids, which performance depends on different physico-chemical variables including chemical composition, size and method of production [2]. Different techniques have been developed for producing size-controlled liposomes with reproducible physical properties; the preparation methods can be generally divided into two groups: (i) “bulk” methods, comprising common macroscale or batch techniques; and (ii) microfluidic methods. The first group includes lipid film hydration, solvent (ethanol or ether) injection, and reverse-phase evaporation [3,4]. In recent years, there has been a growing interest in the use of microfluidic-based production of liposome formulations. This approach has proven to be particularly effective, offering several advantages compared to macroscale techniques; these include small amount of reagents required,

Micromachines 2017, 8, 209; doi:10.3390/mi8070209 www.mdpi.com/journal/micromachines Micromachines 2017, 8, 209 2 of 16 potential for in-situ analysis at high temporal and spatial resolution, devices’ portability and cost effectiveness [5,6]. In microfluidics, the formation of liposomes is caused by the unfavorable interactions between lipids and water, causing the self-assembly of lipids (a process often defined as nanoprecipitation) to form spherical vesicles [7]. In a typical microfluidic method, phospholipids are dissolved in a polar solvent (e.g., ethanol or isopropanol) and injected in the central channel of a microfluidic hydrodynamic focusing (MHF) device. The solvent is subsequently focused by water streams coming from two lateral channels [8], leading to controlled mixing between chemical species. Therefore, the formation of liposomes in microfluidic devices is often governed by diffusive mass transfer of compounds at the liquid interface between solvent (i.e., alcohol) and non-solvent (i.e., water). The alcohol, in which the lipids are initially solubilized, diffuses into the water until it decreases down to a critical concentration [9]. The alcohol diffusion thus governs the formation of vesicles, by a mechanism described as “self-assembly”. Specifically, it has been postulated that the reduction of lipids’ solubility associated with water and alcohol diffusion across the fluid streams causes the formation of intermediate structures, in the form of oblate micelles, which finally enclose to form liposomes. It is well known that microfluidic systems are characterized by steady laminar flow, which typically occurs when the Reynolds number is lower than a critical value of ~2000, due to the stronger contribution of viscous forces compared to inertial forces at the micrometer scale [10]. The laminar flow regime has two main implications: (i) the flow in microchannels is typically characterized by parabolic fluid velocity profile; and (ii) the transfer of chemical species is dominated by diffusion, due to the low fluid velocity magnitude (resulting in low Péclet number) [11]. The diffusion of chemicals (i.e., solvents, solutes and suspended particles) depends on the contact area between the fluids flowing in the microchannels. The diffusion coefficient scales approximately with the inverse of the molecular size (i.e., the hydrodynamic radius) and also depends, to some extent, on the shape of the molecule [12]. Therefore, smaller molecules have higher diffusion coefficient and will move a longer average distance per unit time, compared to larger molecules that have a smaller diffusion coefficient. On one hand the mixing of chemical species in microfluidic channels is therefore highly controllable (i.e., being governed by diffusion) and reproducible (i.e., due to the laminar flow conditions), but on the other hand, it is associated with low throughput and in some cases full mixing may not be achieved within the limited length typical of microfluidic devices. Different methods for quantifying mixing in microfluidics have been presented; these are generally based on the acquisition of microscopic images of two or more colored or fluorescently labelled liquids, followed by quantification of mixing efficiency using simple mathematical functions. Examples of dyes employed are food dyes or stains for biological microscopy [13], or fluorescent dyes such as fluorescein [14,15]. Usually, mixing is quantified by processing a set of microscope images to yield a meaningful index, frequently defined as ‘mixing index’ that is representative of the extent of mixing. Different fluids are usually distinguished based on differences in the light intensity and spectral properties received by a charge-coupled device (CCD) camera. A dye is often used to absorb transmitted light, reflect incoming light, or emit light. The mixing index is computed using intensities of pixels over a cross-section of a grayscale image that delineates a mixing event or region. The simplest index is calculated by taking the standard deviation of the pixel intensities. This method, however, may not be suitable for comparing mixing efficiency across different studies, from the moment that it is sensitive to different lighting conditions that may be difficult to standardize [16]. One approach to measure the concentration of chemical species in microfluidic mixers is based on the use of fluorescent probes, where mixing is assessed from changes in the fluorescence intensity distribution along the device [17]. Three-dimensional characterization of the mixing performance Micromachines 2017, 8, 209 3 of 16 could be performed with these methods, by using confocal microscopes. Alternative techniques based on changes in the fluorescence lifetime of viscosity-sensitive molecular rotors have also been reported [18]. They, however, require expensive equipment, including sensitive detectors, suitable microscope optics, and specific software/hardware, which hinders their adoption from the broader microfluidic and lab-on-a-chip community. However, methods based on the use of a dye or fluorescent probe typically do not provide a direct quantification of the mixing between a solvent and a non-solvent, but rather a quantification of the transport of a selected dye or probe molecule. The physical and chemical properties of the probe may therefore have a significant impact on the measured mixing performance. In this study, we describe and critically analyze a new method for studying mixing processes in different microfluidic chip architectures for nanoparticle production (i.e., MHF or Y-junction), which is based on the use of the pH indicator bromoxylenol blue (BB). The method provides a direct quantification of the exchange between solvent and non-solvent, and it relies on the color shift of a pH sensitive molecule, rather than on color or fluorescence intensity changes.

2. Experimental and Numerical Methods

2.1. Chemicals Highly pure phosphatidylcholine (PC) 90% from soybean (Phospolipon 90G) was purchased from Lipoid GmbH (Ludwigshafen, Germany). Dimethyldioactdecylammoniumbromide (DDAB), bromoxylenol blue (BB), trichloro(1H,1H,2H,2H)-perfluorooctylsilane, hydrofluoric acid, and ammonium fluoride were purchased from Sigma-Aldrich Co. Ltd (Irvine, UK). Polydimethylsiloxane (PDMS) monomer Sylgard®184 and curing agent were purchased from Dow Corning Corporation (Auburn, AL, USA), and SU-8 photoresist from Chestech Ltd (Rugby, UK). All other regents and solvents were supplied by Sigma-Aldrich Co. Ltd (Irvine, UK). The water employed was ultrapure water (Merck Millipore, Billerica, MA, USA).

2.2. Microfluidic Devices Design and Fabrication Two different microfluidic architectures were employed in the present study (see Figure1). #chip1-MHF is characterized by a cross flow geometry, in which the oblique side channels (length: 9.3 mm) intersect the central channel (length: 30 mm) with an angle of 40◦. The channels have a rectangular cross section with a width of 0.15 mm and a depth of 0.10 mm. They were produced via soft lithography. Briefly, a SU-8 mold with the designed microchannel architecture was fabricated following a standard procedure [19]. The mold was subsequently covered with a layer of a 10:1 (w/w) polydimethylsiloxane (PDMS) monomer and curing agent liquid mixture, and heated for 1 hour at 80◦. The solidified PDMS sheet, with the microchannel architecture on one surface, was then removed from the mold and permanently bonded to a glass slide after surface treatment with a plasma asher (PVA TePla AG, Wettenberg, Germany). #chip2-YJ is characterized by a “Y” shape geometry in which the 2 inlets intersect with a 120◦ angle; the mixing channel (length: 66 mm) has a serpentine geometry. Channels have a squared cross-section with width and depth of 0.32 mm. The device is made of cycloolefin copolymer (COC) and was obtained from Thinxxs Microtechnology (Zweibrücken, Germany). Micromachines 2017, 8, 209 4 of 16 Micromachines 2017, 8, 209 4 of 16

FigureFigure 1. Schematic 1. Schematic showing showing the the geometry geometry ofof thethe microf microﬂuidicluidic chips chips employed employed in the in present the present study. study. (A) #chip1-MHF(A) #chip1-MHF was was characterized characterized by by a cross a cross ﬂow flow geometry; geometry; while while ((BB)) #chip2-YJ#chip2-YJ was was characterized characterized by a “Y”by shape a “Y” geometry. shape geometry. The constitutive The constitutive materials material of thes of chips the chips and theand dimensions the dimensions of the of mainthe main channel (i.e., locatedchannel after(i.e., located the junction after the between junction the between inlet channels)the inlet channels) are also are reported. also reported.

2.3. Liposome Preparation and Characterization 2.3. Liposome Preparation and Characterization Liposomes were prepared using both #chip1-MHF and #chip2-YJ. The lipid mixture (containing LiposomesPC 90G at 90 were mM, preparedand DDAB using at 10 bothmM) #chip1-MHFwas dissolved andin ethanol #chip2-YJ. and injected The lipid into mixture the central (containing inlet PC 90Gchannel at 90 of mM, #chip1-MHF and DDAB or one at 10inlet mM) of #chip2-YJ; was dissolved water inwas ethanol instead andinjected injected into the into two the side central inlet inlet channelchannels of #chip1-MHF of #chip1-MHF or oneor the inlet second of #chip2-YJ; inlet of #chip2-YJ. water wasTeflon instead® tubes injectedwith an internal into the diameter two side of inlet channels750 µm of #chip1-MHF(Sigma Aldrich, or Irvine, the second UK) were inlet employed of #chip2-YJ. to connect Teflon the® inletstubes of with the devices an internal with diametersyringe of 750 µpumpsm (Sigma (Pump Aldrich, Systems Irvine, Inc., Farmingdale, UK) were employed PA, USA) tofor connect fluids’ delivery. the inlets of the devices with syringe Liposome formation at different flow regimes was investigated by changing the flow rate ratio pumps (Pump Systems Inc., Farmingdale, PA, USA) for fluids’ delivery. between water and ethanol (FRR) in the range 0.5–40, and the total flow rate (TFR) in the range 18.75– Liposome formation at different flow regimes was investigated by changing the flow rate ratio 75.00 µL/min. The liposome samples were collected from the outlet tube (a 30 mm long Teflon® tube betweenwith wateran internal and diameter ethanol of (FRR) 750 µm) in thein a 1.5 range mL microcentrifuge 0.5–40, and the tube. total Liposomes flow rate were (TFR) analyzed in the for range 18.75–75.00size andµ sizeL/min. distribution The liposome by DLS Zetasizer samples Nano were-ZScollected (Malvern Instruments from the outlet Ltd, Malvern, tube (a UK) 30 mmwith long Teflona® backscatteringtube with an detection internal angle diameter of 173°, of a 750He/Neµm) laser in athat 1.5 emits mL microcentrifugeat 633 nm, and a 4.0 tube. mW Liposomespower weresource. analyzed The for data size were and used size to distributionreport the intensit by DLSy mean Zetasizer diameter Nano-ZS (Z-average) (Malvern and the Instrumentsdispersity of Ltd, Malvern,the liposome UK) with formulations. a backscattering The mean detection particle anglesize was of obtained 173◦, a He/Nefrom the laser results that of three emits independent at 633 nm, and a 4.0 mWexperiments,power source.carried out The at data 21 °C were in water, used without to report sample the intensity dilution (sample mean diameter volume: 1 (Z-average) mL). Cryo- and the dispersityTransmission of theElectron liposome Microscopy formulations. (cryo-TEM) The meanimages particle of liposomes size was were obtained also acquired from the for results morphological characterization. For this purpose, a 3 mL aliquot of a liposome sample was applied of three independent experiments, carried out at 21 ◦C in water, without sample dilution (sample on plasma-treated (Gatan Solarus Model 950 Advanced Plasma System, pressure = 70 mTorr, H2 flow volume: 1 mL). Cryo-Transmission Electron Microscopy (cryo-TEM) images of liposomes were also = 6.4 sccm, O2 flow = 27.5 sccm, forward RF target = 50 W, exposure time = 30 s) carbon copper grids acquired(Quantifoil for morphological R 3.5/1), in the characterization. environmental chamber For this of purpose, a fully automated a 3 mL aliquot vitrification of aliposome device for sampleplunge was applied on plasma-treated (Gatan Solarus Model 950 Advanced Plasma System, pressure = 70 mTorr, H2 flow = 6.4 sccm,O2 flow = 27.5 sccm, forward RF target = 50 W, exposure time = 30 s) carbon copper grids (Quantifoil R 3.5/1), in the environmental chamber of a fully automated vitrification device for Micromachines 2017, 8, 209 5 of 16 plunge freezing (FEI Vibrot). The relative air humidity was equal to 100% and temperature to 22 ◦C. The excess solution was removed by blotting with filter paper for 2 s, followed by 1 s draining and plunging of the samples into a 1:1 mixture of liquid ethane and liquid propane, which was cooled to 170 ◦C. Vitrified samples were cryo-transferred into a Jeol JEM3200FSC cryo-TEM, operating at 194 ◦C. The temperature of the samples was 187 ◦C during image acquisition. The microscope was operated in bright field mode, using a 300 kV acceleration voltage; the in-column energy filter was set to 0–20 eV energy-loss range (zero-loss imaging). Micrographs were recorded with a Gatan Ultrascan 4000 CCD camera.

2.4. Analysis of Mixing in Microfluidic Chips The effect of FRR and TFR on the mixing of solvents and solutes in microfluidic channels were studied using the pH indicator BB and NaOH, which were added to the lipid solution and water respectively. BB was added to the ethanol lipid solution until saturation, after adjusting the pH by 0.1 M acetic acid; the concentration of NaOH in water was 0.1 N. BB is a weak acid, and appears in yellow (below pH 6) or light blue (above pH 7.6) color when it is in the protonated or deprotonated state, respectively. It has a green color in the interval of pH comprised between 6 and 7.6, as an intermediate of the deprotonating mechanism in neutral solution. Therefore, the mixing between ethanol containing BB and water containing NaOH within the microfluidic devices, causes an increase in pH resulting in a change in BB color. Different regions of the main channel within the two chips were imaged by an optical microscope (Hund® Wilovert 30, Helmut Hund GmbH, Wetzlar, Germany) equipped with a CCD camera (GXCAM-HICHROMESII, GT-Vision®, Haverhill, UK), at 4× magnification. Images were taken nearby the junction between inlet channels, and at a more distal location along the main channel (in close proximity to the device outlet). The latter position was selected in order to provide a quantification of the overall mixing performance of the devices, at fixed flow dynamic boundary conditions. Images were processed using ImageJ (NIH, Bethesda, MD, USA), to measure the width of the regions in which BB is either yellow, blue or green.

2.5. Numerical Simulation of Fluid and Species Transport The transport of fluids and chemical species within both microfluidic devices was characterized numerically, using computational fluid dynamic (CFD) simulations. Firstly, the geometry of the microfluidic channels was designed using Inventor Pro 2016 (Autodesk Inc., San Rafael, CA, USA), and then transferred to ICEM CFD 17.0 (Ansys Inc., Concord, MA, USA) for meshing. The fluidic domain was discretized into finite volumes of tetrahedral shape. A mesh dependence study was performed to identify a compromise between solution accuracy and computational cost, leading to an optimal number of mesh volumes of 704740063 (#chip1-MHF) and 407620651 (#chip2-YJ). These corresponded to a mesh volume edge size of 0.012 mm (#chip1-MHF) and 0.03 mm (#chip2-YJ). Ansys® Fluent 17.0 (Ansys Inc., Concord, MA, USA) was employed to solve for mass and momentum conservation equations (i.e., Navier-Stokes equations at laminar flow regime), and species transfer (i.e., advection-diffusion equations). Boundary conditions were defined so as to replicate the experimental ones; a mass flow boundary condition was imposed at the device inlets, atmospheric pressure was imposed at the outlets, and a no-slip boundary condition was imposed at the channel walls. The experimental values of TFR and FRR were simulated numerically. Fluids were assumed incompressible and Newtonian, and the ethanol-water diffusion coefficient was set to 1 × 10−9 m2/s [20]. The effect of solvents’ mixing on fluid density and viscosity was taken into consideration in the simulations. In order to compare the results of numerical simulations with the experimental images, the numerical contours of ethanol mass fraction were transferred to ImageJ for analysis. Stacks of RGB contour images at selected regions of interest (ROI) within the microfluidic devices were converted to 8-bit format, and subsequently thresholded to obtain a binary image. Reference Micromachines 2017, 8, 209 6 of 16 lines were defined in agreement with the experimental image processing protocol, in order to obtain the width of fluid layers of specific relevance for characterizing the mixing process. The physical width of Micromachines 2017, 8, 209 6 of 16 these layers was determined upon appropriate dimensional calibration of the images. the mixing process. The physical width of these layers was determined upon appropriate 3. Results and Discussion dimensional calibration of the images.

3.1. Liposome3. Results Preparation and Discussion In this study, two different microfluidic chips characterized by different constitutive materials 3.1. Liposome Preparation (i.e., PDMS and cycloolefin) and channel architecture were considered (see Figure1). Notably, one chipIn was this study, custom two built different using microfluidic a design chips previously characterized developed by different in cons ourtitutive group materials (#chip1-MHF), (i.e., whilePDMS the other and cycloolefin) was commercially and channel available architecture (#chip2-YJ). were considered They (see were Figure selected 1). Notably, as two one relevant chip was model devicescustom employed built using for a the design production previously of developed nanoparticles in our and group vesicular (#chip1-MHF), systems while by solventthe otherexchange was commercially available (#chip2-YJ). They were selected as two relevant model devices employed for the mechanism [21,22]. Devices’ constitutive materials were compatible with solvents employed in the production of nanoparticles and vesicular systems by solvent exchange mechanism [21,22]. Devices’ present study, and the microfluidic channels did not undergo any detectable deformation at the flow constitutive materials were compatible with solvents employed in the present study, and the ratesmicrofluidic investigated. channels Therefore, did not the undergo mixing performanceany detectable indeformation these chips at can the beflow considered rates investigated. independent fromTherefore, the material the properties.mixing performance in these chips can be considered independent from the material Particularly,properties. #chip1-MHF is characterized by a cross flow geometry, in which the oblique side channelsParticularly, intersect the #chip1-MHF central channel is characterized at an angle by ofa cross 40◦. #chip2-YJflow geometry, is instead in which characterized the oblique side by a “Y” shapechannels geometry intersect in which the central the two channe inletsl joinat an with angle a of 120 40°.◦ angle; #chip2-YJ and is the instead main characterized channel has aby 66 a mm“Y” long serpentineshape geometry geometry. in which the two inlets join with a 120° angle; and the main channel has a 66 mm Bothlong serpentine devices geometry. were employed for the production of liposomes, composed of PC/DDAB Both devices were employed for the production of liposomes, composed of PC/DDAB (at a (at a concentration of 9 mM and 1 mM, respectively). Different liposome samples were produced concentration of 9 mM and 1 mM, respectively). Different liposome samples were produced by by varying the FRR (from 10 to 50) and maintaining the TFR fixed at 37.5 µL/min. Liposomes were varying the FRR (from 10 to 50) and maintaining the TFR fixed at 37.5 µL/min. Liposomes were characterizedcharacterized for theirfor their size size and and dispersity dispersity by by DLS.DLS. DataData reported reported in Figurein Figure2 indicate 2 indicate that that liposomes liposomes produced with with #chip1-MHF #chip1-MHF were were generally generally smallersmaller (ranging (ranging between between 40 40 and and 110 110 nm nm in in diameter)diameter) than than those those produced produced by by#chip2-YJ #chip2-YJ (90–120 (90–120 nm nm in diameter).in diameter).

FigureFigure 2. Dimensional 2. Dimensional characteristics characteristicsof of liposomesliposomes produced produced by by microfluidics: microﬂuidics: Z-average Z-average (A) and (A) and dispersitydispersity (B). ( LiposomesB). Liposomes were were prepared prepared byby #chip1-MHF#chip1-MHF (filled (ﬁlled circles) circles) or or#chip2-YJ #chip2-YJ (open (open circles). circles). ExperimentalExperimental conditions conditions and and lipid lipid composition composition are described in in the the methods methods section. section. Data Data represent represent the averagethe average of 3 of batches, 3 batches, measured measured in in triplicate triplicate± ± SD;SD; Cryo-TEM Cryo-TEM images images of liposomes of liposomes produced produced using using #chip1-MHF (C) and #chip2-YJ (D) are reported, for a FRR of 10 and TFR of 37.5 µL/min. #chip1-MHF (C) and #chip2-YJ (D) are reported, for a FRR of 10 and TFR of 37.5 µL/min.

Micromachines 2017, 8, 209 7 of 16

In addition, an inverse correlation between liposome size and FRR in the microfluidic Micromachineshydrodynamic2017 ,focusing8, 209 device can be appreciated, with an increase in FRR resulting in a decrease7 of 16in liposome diameter. This is in agreement with previous studies reporting production of liposomes usingIn similar addition, microfluidic an inverse architectures correlation [8]. betweenConversely, liposome the size sizeof liposomes and FRR produced in the microfluidicwith #chip2- hydrodynamicYJ did not change focusing significantly device can with be appreciated,varying the withFRR. anPrevious increase studies in FRR using resulting serpentine in a decrease shaped in liposomemicrofluidic diameter. devices, This in iswhich in agreement mixing withis dominated previous studiesby advection, reporting have production shown that of liposomes liposome using size similarchanged microfluidic only marginally architectures with increasing [8]. Conversely, FRR [23,24], the size at values of liposomes of FRR produced> 1. with #chip2-YJ did not changeMoreover, significantly increasing with the varying FRR resulted the FRR. in Previous increased studies liposome using size serpentine dispersity shaped for #chip1-MHF, microfluidic devices,whilst size in whichdispersity mixing was isalmost dominated independent by advection, on FRR havefor liposomes shown that produced liposome using size #chip2-YJ. changedonly marginally with increasing FRR [23,24], at values of FRR > 1. 3.2. Analysis of Mixing in Microfluidic Chips by pH Indicator Moreover, increasing the FRR resulted in increased liposome size dispersity for #chip1-MHF, whilstTo size characterize dispersity the was mixing almost between independent ethanol on and FRR water for liposomes and its effect produced on liposome using #chip2-YJ.characteristics, a protocol based on the pH indicator bromoxylenol blue was established. BB was selected since it 3.2.presents Analysis a marked, of Mixing pH-dependent in Microfluidic chromatic Chips by pHchange Indicator that is easily detectable by optical microscopy. At pHTo < characterize 6 (i.e., the lipid the mixingsolution between in ethanol ethanol adjusted and with water acetic and itsacid) effect it appears on liposome yellow, characteristics, while at pH a> protocol7.6 (i.e., the based NaOH on the 0.1 pH N solution indicator in bromoxylenol water) it appears blue blue was established.(Figure 3). For BB pH was values selected comprised since it presentsbetween a6 marked,and 7.6 it pH-dependent has a green color. chromatic change that is easily detectable by optical microscopy. At pHTherefore, < 6 (i.e., theusing lipid BB, solutionthe process in ethanolof mixing adjusted in microfluidic with acetic devices acid) was it appearsanalyzed yellow, at different while flow at pHconditions > 7.6 (i.e., (i.e., the by NaOH varying 0.1 both N solution FRR and in TFR). water) Specifically, it appears blue FRR (Figure was set3 ).to For 0.5, pH 2.5, values 5.0, 10.0, comprised 20.0 and between40.0, whereas 6 and TFR 7.6 itwas has set a green to 18.75, color. 37.50 and 75.00 µL/min.

FigureFigure 3. ChangeChange in in chemical chemical structure structure and and color color of ofbrom bromoxylenoloxylenol blue blue (BB) (BB) as a as function a function of pH. of The pH. Thecolor color shifts shifts from from yellow yellow (at pH (at < pH 6) 7.6). pH >7.6).

3.2.1.Therefore, Microfluidic using Hydrodynamic BB, the process Focusing of mixing Device in microfluidic devices was analyzed at different flow conditionsThe microphotographs (i.e., by varying both taken FRR during and TFR). the Specifically, experiments FRR performed was set to with 0.5, 2.5, #chip1-MHF 5.0, 10.0, 20.0 at andthe 40.0,intermediate whereas TFR wasvalue set (37.5 to 18.75, µL/m 37.50in) are and reported 75.00 µL/min. in Figures 4 and 5, respectively showing the focusing region (i.e., at the inlet channels’ intersection; Figure 4) and the region towards the end of 3.2.1. Microfluidic Hydrodynamic Focusing Device the main channel (i.e., 10 mm from the outlet; Figure 5). TheAs illustrated microphotographs in Figure 4, taken in #chip1-MHF during the the experiments acidic BB ethanolic performed solution with is #chip1-MHF hydrodynamically at the intermediatefocused by the TFR aqueous value (37.5NaOHµ L/min)solution are into reported a narrow in stream, Figures 4which and5 ,width respectively depends showing on the theFRR. focusingNotably, regionthe width (i.e., of at focused the inlet stream channels’ is inversely intersection; correlated Figure to4) the and FRR the at region all TFRs towards tested; the for end instance, of the mainat TFR channel equal to (i.e., 37.5 10 µL/min mm from the the width outlet; progressivel Figure5). y decreased from 173 µm (at FRR = 0.5) to 33 µm (at FRRAs = illustrated 40). The numerical in Figure 4simulations, in #chip1-MHF are in theagreement acidic BB with ethanolic the experimental solution is data, hydrodynamically with the width focusedof the focused by the stream aqueous decreasing NaOH solution from 143 into µm a (at narrow FRR = stream, 0.5) to which17 µm width(at FRR depends = 40). These on the results FRR. Notably,suggest that the widththe pH of indicator focused approach stream is inverselyemployed correlated in this study to the is suitable FRR at allfor TFRscharacterizing tested; for the instance, shape at TFR equal to 37.5 µL/min the width progressively decreased from 173 µm (at FRR = 0.5) to 33 µm Micromachines 2017, 8, 209 8 of 16

(at FRR = 40). The numerical simulations are in agreement with the experimental data, with the width of the focused stream decreasing from 143 µm (at FRR = 0.5) to 17 µm (at FRR = 40). These results suggestMicromachines that the 2017 pH, 8, 209 indicator approach employed in this study is suitable for characterizing8 of 16 the shape of the focused stream, at the intersection between solvent and non-solvent streams within MHF of the focused stream, at the intersection between solvent and non-solvent streams within MHF architectures.architectures. Moreover, Moreover, data data suggest suggest that that at at lowerlower FRRs the the larger larger width width of the of the focused focused stream stream may may resultresult in higher in higher diffusion diffusion length, length, which which is is reﬂected reflected in liposomes liposomes having having a higher a higher diameter diameter (see Figure (see Figure 2). 2). SlowerSlower mixing mixing however however generated generated dimensionally dimensionally more uniform uniform liposomes, liposomes, which which is reflected is reﬂected in the in the lowerlower size dispersitysize dispersity at theat the lower lower FRRs FRRs (Figure (Figure2 2)).. ChangesChanges in in the the local local concentration concentration of lipids of lipids may may havehave also affectedalso affected liposome liposome size size and and size size dispersity. dispersity.

Figure 4. Experimental and computational fluid dynamic (CFD) analysis of the effect of FRR on the Figure 4. Experimental and computational ﬂuid dynamic (CFD) analysis of the effect of FRR on shape of the focused stream, in #chip1-MHF. The images illustrate the experimental microscopic the shape of the focused stream, in #chip1-MHF. The images illustrate the experimental microscopic observations (left column) and the CFD simulations (mid and right columns) of the focusing region, observations (left column) and the CFD simulations (mid and right columns) of the focusing region, at the channels’ intersection; The images were employed to determine the focused stream width at at the0.175 channels’ mm from intersection; the inlet channel, The images as indicated were in employed the schematic to determineat the bottom; the The focused numerical stream contours width at 0.175of mm ethanol from themass inlet fraction channel, are asreported indicated at both in the the schematic mid-plane at ( themid bottom;column The) and numerical top-plane contours(right of ethanolcolumn mass) fractionof the device. are reported Experiments at both and the simulations mid-plane we (midre conducted column )at and TFR top-plane of 37.50 µL/min, (right columnand at ) of the device.varying Experiments FRRs. and simulations were conducted at TFR of 37.50 µL/min, and at varying FRRs.

Micromachines 2017, 8, 209 9 of 16 Micromachines 2017, 8, 209 9 of 16

Figure 5. Experimental and computational fluid dynamic (CFD) analysis of the effect of FRR on Figure 5. Experimental and computational ﬂuid dynamic (CFD) analysis of the effect of FRR on diffusion and focused stream width, in #chip1-MHF. The images illustrate the experimental diffusion and focused stream width, in #chip1-MHF. The images illustrate the experimental microscopic microscopic observations (left column) and the CFD simulations (mid and right columns) of the observations (left column) and the CFD simulations (mid and right columns) of the focusing region, focusing region, at the channels’ intersection; The images were employed to determine the focused at the channels’ intersection; The images were employed to determine the focused stream width at stream width at 10 mm from the outlet, as indicated in the schematic at the bottom; The numerical 10 mm from the outlet, as indicated in the schematic at the bottom; The numerical contours of ethanol contours of ethanol mass fraction are reported at both the mid-plane (mid column) and top-plane mass fraction are reported at both the mid-plane (mid column) and top-plane (right column) of the (right column) of the device. Experiments and simulations were conducted at TFR of 37.50 µL/min, device. Experiments and simulations were conducted at TFR of 37.50 µL/min, and at varying FRRs. and at varying FRRs.

Inversely,Inversely, higher higher FRRs FRRs produced produced a narrowera narrower focusing focusing of of the the lipidic lipidic ethanolic ethanolic solution, solution, resultingresulting in a lowerin a lower diffusion diffusion length length and and therefore therefore faster faster mixing. mixing. Liposomes Liposomes obtained at at these these conditions conditions were were smallersmaller in diameter,in diameter, but presentedbut presented a higher a higher size dispersity size dispersity (Figure 2(Figure). As mentioned 2). As mentioned earlier, differences earlier, in lipiddifferences concentration in lipid concentration (i.e., due to differences (i.e., due to in diff theerences ethanol/water in the ethanol/water ratio) may have ratio) also may inﬂuenced have also the

Micromachines 2017, 8, 209 10 of 16

final liposome size. A compromise between FRR and the concentration/dispersity of liposomes in the end-product should thus be considered when defining the operating conditions of MHF devices. Cryo-TEM images of liposomes produced with the MHF chip at FRR of 10 and TFR of 37.5 µL/min are reported in Figure2C. Notably, the analysis of the mixing in the main channel at 10 mm from the outlet (see Figure5), suggests that the mixing between the ethanolic solution and water is not complete at all FRRs investigated. This is evident from both experiments and numerical simulations, where excess ethanol in the central stream can be appreciated. This finding suggests that the production of supramolecular assemblies (i.e., liposomes or micelles) by MHF chips with limited channel dimensions, particularly in terms of total length of the main channel, may not be desirable. Data reported in Figure5 also indicate that complete mixing of ethanol and water would occur only in the glassware used to collect the samples, therefore diminishing the value of utilizing a highly controlled microfluidic environment. As a matter of fact, the size dispersity of liposomes produced with #chip1-MHF at the conditions reported in the present study was higher when compared with liposomes produced using #chip2-YJ, likely due to inefficient mixing within the microfluidic device. Notably, while the formation of liposomes by solvent exchange is a dynamic process, which kinetics is complex to model or experimentally capture, we can assume that this process reaches an equilibrium once the mixing between solvent and non-solvent is complete. Thus, for the production of liposomes at high throughput, it would be advisable to employ microfluidic chips containing static mixing elements to improve the mixing efficiency between solvent and non-solvent. Values of the width of the focused stream are reported in Figure6A,B, which comprise experiments carried out in the absence and in the presence of phospholipids in the acidic ethanolic solution, respectively. There is no notable effect of having lipids in the ethanolic stream on the shape and size of the focused stream (see Figure6A,B). It should be noted that the initial total lipid concentration in this study was equal to 100 mM, leading to a final concentration in the range 2–10 mM (depending on the FRR). These values are lower than typical concentrations of commercial formulations, which usually range between 5 mM and 25 mM. This limitation of microfluidic based production methods has been discussed elsewhere more comprehensively. It is envisaged that at these higher lipid concentrations the physical and interfacial properties of fluids may be affected, thus impacting on the size and shape of the focused stream. Panel C instead compares experimental and numerical data, showing good agreement between the two characterization methods.

3.2.2. Microfluidic ‘Y’-Shape Device In #chip2-YJ the acidic ethanolic solution of the indicator and the aqueous NaOH solution are pumped into the chip from the left and right inlets, respectively (see Figure7). In this microfluidic architecture, a single interface is formed between ethanol and water, which position depends on the FRR. As evident from Figure7, at lower FRRs (in the range 0.5 to 5.0) the interface is shifted towards the right inlet channel, whereas at higher FRRs (>5.0) the interface progressively shifts towards the left inlet channel. This trend is evident in both experimental and simulated conditions, suggesting that simulations are able to capture the interfacial interaction between solvent and non-solvent. A remarkable difference between #chip1-MHF and #chip2-YJ resides in the dimension of the diffusion layer formed between ethanol and water. In #chip1-MHF, the boundary between solvent and non-solvent appears rather sharp, while in #chip2-YJ a green colored region between ethanol and water is detectable, corresponding to a pH value comprised between 6 and 7.6 (Figure7). This is reflected in the numerical results, suggesting that mixing between ethanol and water has partially occurred already at the junction between inlets. The width of such diffusion layer appears to be directly related to TFR and inversely related to FRR. Notably, the higher residence time and slower mixing in this Micromachines 2017, 8, 209 11 of 16

Micromachines 2017, 8, 209 11 of 16 specific device resulted in liposomes with larger diameter compared to those obtained with the MHF device,Furthermore, as illustrated the in numerical Figure2. results show a significant difference in the solvent concentration betweenFurthermore, the top and the mid numerical planes, resultslikely due show to a th significante ethanol differencemoving upwards in the solvent because concentration of its lower densitybetween compared the top and to midwater. planes, This likelyeffect dueis more to the evident ethanol in moving #chip2-YJ upwards compared because to #chip1-MHF, of its lower density due to thecompared larger cross-sectional to water. This area effect and is therefore more evident the lowe in #chip2-YJr mean fluid compared velocity. to Howe #chip1-MHF,ver, stratification due to the of fluidslarger cross-sectionaldue to differences area in and density therefore did thenot lowerappear mean to impact fluid velocity.on the mixing However, efficiency stratification in this ofspecific fluids device.due to differencesThis effect inhas density not been did previously not appear investig to impactated on in the depth, mixing and efficiency will form in thisthe specificbasis of device.future Thisstudies. effect has not been previously investigated in depth, and will form the basis of future studies.

Figure 6. Effect of FFR on the focused stream width at different TFRs, measured from experiments (A,B) and and simulations simulations (C (C) )using using #chip1-MHF. #chip1-MHF. TFR TFR was was set setto 18. to75 18.75 (circles), (circles), 37.50 37.50 (squares) (squares) and 75.00 and (triangles)75.00 (triangles) µL/min.µL/min. Experiments Experiments were carried were out carried in the out absence in the ( absenceA) or in (theA) orpresence in the of presence liposome of formingliposome lipids forming (B). lipidsData (representB). Data representthe average the of average 3 meas ofurements 3 measurements ± SD (the± maximumSD (the maximum standard deviationstandard deviationis equal to is 0.9). equal to 0.9).

Micromachines 2017, 8, 209 12 of 16 Micromachines 2017, 8, 209 12 of 16

FigureFigure 7.7. ExperimentalExperimental andand computationalcomputational ﬂuidfluid dynamicdynamic (CFD)(CFD) analysisanalysis ofof thethe effecteffect ofof microﬂuidicmicrofluidic parametersparameters on diffusion, diffusion diffusion layer layer width width and and wa water/ethanolter/ethanol interface interface position, position, in #chip2-YJ. in #chip2-YJ. The Theimages images illustrate illustrate thethe experimental experimental microscopic microscopic observations observations (left (left column column) )and and the the CFD simulationssimulations ((midmid andand rightright columnscolumns)) ofof the the “Y” “Y” junction junction region,region, atat thethe channels’channels’ intersection;intersection; TheThe imagesimages werewere employedemployed toto determinedetermine thethe widthwidth ofof thethe diffusiondiffusion layerlayer (i.e.,(i.e., thethe green green region) region) and and the the water/ethanol water/ethanol interfaceinterface position,position, asas indicatedindicated inin thethe schematicschematic atat thethe bottom;bottom; TheThe numericalnumerical contourscontours ofof ethanolethanol massmass fractionfraction areare reportedreported atat bothboth thethe mid-planemid-plane ((midmid columncolumn)) andand top-planetop-plane ((rightright column)) of the device. ExperimentsExperiments andand simulationssimulations werewere conductedconducted atat TFRTFR ofof37.50 37.50µ µL/min,L/min, and at varying FRRs.

As illustrated in Figure 8, the presence of serpentine mixing elements in #chip2-YJ is sufficient As illustrated in Figure8, the presence of serpentine mixing elements in #chip2-YJ is sufficient to achieve efficient mixing between ethanol and water at all FRRs investigated, without any evident to achieve efficient mixing between ethanol and water at all FRRs investigated, without any evident interfacial layer near the outlet of the device (Figure 8). As a result, liposome size dispersity was interfacial layer near the outlet of the device (Figure8). As a result, liposome size dispersity was nearly nearly invariant at the different FRRs. The proportion of ethanol and pH are clearly related to FRR; invariant at the different FRRs. The proportion of ethanol and pH are clearly related to FRR; i.e., at the i.e., at the lower FRRs (0.5 and 2.0) the pH is between 6 and 7.6 as reflected in the green color, and at lower FRRs (0.5 and 2.0) the pH is between 6 and 7.6 as reflected in the green color, and at FRR >10 FRR >10 the pH shifts towards basic values (blue colors). Notably, microfluidic architectures such as #chip2-YJ may provide the benefit of efficient mixing and lower size dispersity at the experimental conditions investigated in the present study.

Micromachines 2017, 8, 209 13 of 16 the pH shifts towards basic values (blue colors). Notably, microfluidic architectures such as #chip2-YJ may provide the benefit of efficient mixing and lower size dispersity at the experimental conditions investigatedMicromachines 2017 in the, 8, 209 present study. 13 of 16

Figure 8.8. Experimental and computational ﬂuidfluid dynamic (CFD)(CFD) analysis of the effect of microﬂuidicmicrofluidic parametersparameters on diffusion, diffusion, diffusion diffusion layer layer width width and and wa water/ethanolter/ethanol interface interface position, position, in #chip2-YJ. in #chip2-YJ. The Theimages images illustrate illustrate the theexperimental experimental microscopic microscopic observations observations (left (left column column) )and and the the CFD CFD simulations ((midmid andand rightright columnscolumns)) inin aa regionregion locatedlocated atat thethe endend ofof thethe serpentineserpentine geometry;geometry; TheThe imagesimages werewere employed toto determinedetermine thethe widthwidth ofof thethe diffusiondiffusion layerlayer (i.e.,(i.e., thethe greengreen region)region) andand thethe water/ethanol water/ethanol interfaceinterface position,position, asas indicatedindicated inin thethe schematicschematic atat the bottom; The numerical contours of ethanol mass fractionfraction areare reportedreported atat bothboth the mid-plane (mid column) and top-plane ( right column ) of the the device. device. Experiments andand simulationssimulations werewere conductedconducted atat TFRTFR ofof 37.5037.50 µµL/min,L/min, and at varying FRRs.

Quantitative results are provided in Figure 9, showing the influence of FRR on the water/ethanol interface position and diffusion layer width, respectively. In both simulations and experiments, the water/ethanol interface position reduced with increasing FRR. Good agreement between the experimental (Figure 9A) and the computational (Figure 9B) measurements can also be appreciated. Moreover, the presence of lipids in the ethanolic stream does not have a significant effect on the shape and size of this interface (see Figure 9A,B). Cryo-TEM images of liposomes produced with the Y- junction chip at FRR of 10 and TFR of 37.5 µL/min are reported in Figure 2D.

Micromachines 2017, 8, 209 14 of 16

Quantitative results are provided in Figure9, showing the inﬂuence of FRR on the water/ethanol interface position and diffusion layer width, respectively. In both simulations and experiments, the water/ethanol interface position reduced with increasing FRR. Good agreement between the experimental (Figure9A) and the computational (Figure9B) measurements can also be appreciated. Moreover, the presence of lipids in the ethanolic stream does not have a signiﬁcant effect on the shape and size of this interface (see Figure9A,B). Cryo-TEM images of liposomes produced with the

Y-junctionMicromachines chip 2017 at, 8, FRR 209 of 10 and TFR of 37.5 µL/min are reported in Figure2D. 14 of 16

FigureFigure 9.9. EffectEffect ofof FFRFFR onon thethe water/ethanol water/ethanol interfaceinterface positionposition atat differentdifferent TFRs,TFRs, measuredmeasured fromfrom experimentsexperiments ( A(A,B,B)) and and simulations simulations ( C(C)) using using #chip2-YJ. #chip2-YJ. TFRTFR waswas setset toto 18.7518.75 (circles),(circles), 37.5037.50 (squares)(squares) andand 75.0075.00 (triangles)(triangles) µµL/min.L/min. Experiment Experimentss were were carried carried out out in in the the absence absence (A (A) )and and in in the the presence presence of ofliposome liposome forming forming lipids lipids (B (B).). Data Data represent represent the the average ofof 33 measurementsmeasurements ±± SDSD (the(the maximummaximum standardstandard deviation deviation is is equal equal to to 0.5). 0.5).

In conclusion, the experimental approach based on the pH indicator BB proved to be effective In conclusion, the experimental approach based on the pH indicator BB proved to be effective for for studying the influence of FRR and TFR on the mixing performance of microfluidic devices. studying the inﬂuence of FRR and TFR on the mixing performance of microﬂuidic devices. Notably, the Notably, the method was validated using numerical simulations, demonstrating its ability to provide method was validated using numerical simulations, demonstrating its ability to provide a qualitative a qualitative and quantitative characterization of the mixing between a solvent (ethanol) and a non- and quantitative characterization of the mixing between a solvent (ethanol) and a non-solvent (water). solvent (water). The proposed method may provide a useful tool to design and validate appropriate experimental conditions for the use of microfluidic devices in the preparation of supramolecular assemblies, such as liposomes.

4. Conclusions Microfluidic-based production of vesicular systems has proven to be an effective technique, offering several advantages compared to macroscale methods, particularly in terms of control over the physical properties of the end-product. These properties are usually highly dependent on the mixing between a solvent (i.e., ethanol) and a non-solvent (i.e., water). Thus, the design of a microfluidic architecture for vesicular systems’ production requires an in-depth characterization of

Micromachines 2017, 8, 209 15 of 16

The proposed method may provide a useful tool to design and validate appropriate experimental conditions for the use of microﬂuidic devices in the preparation of supramolecular assemblies, such as liposomes.

4. Conclusions Microfluidic-based production of vesicular systems has proven to be an effective technique, offering several advantages compared to macroscale methods, particularly in terms of control over the physical properties of the end-product. These properties are usually highly dependent on the mixing between a solvent (i.e., ethanol) and a non-solvent (i.e., water). Thus, the design of a microfluidic architecture for vesicular systems’ production requires an in-depth characterization of the mixing within the microfluidic environment. In this study, we report on the development of a novel method based on the use of a pH indicator, and we demonstrated its utility by charactering the transport of solvent and non-solvent within two different microfluidic mixers typically used for the production of vesicular or micellar systems. Numerical simulations were performed to validate the experimental findings. With these methods, we evaluated the effect of the hydrodynamic boundary conditions (specifically the ratio between inlet flow rates, FRR) on the mixing performance of the selected microfluidic architectures, which had distinct geometrical and fluid dynamic characteristics. Our findings suggest that, in MHF devices, particular attention must be paid to the length of the main channel in order to achieve efficient mixing within the microfluidic device. The presence of a serpentine in the main channel was observed to significantly improve the mixing performance, and complete mixing was achieved for the large majority of FRRs and TFRs investigated. The latter device architecture may provide the benefit of efficient mixing at a larger spectrum of FRRs. Compared to other mixing characterization methods based on changes in color or fluorescence intensity of a dye or probe, our proposed technique relies on the color-shift of a pH sensitive molecule, and may therefore be less sensitive to the lighting conditions employed in the experiment. Furthermore, it provides a route for qualifying and quantifying the solvent exchange process, which is postulated to govern the formation of vesicular systems in microfluidic devices. The proposed mixing characterization method also presents advantages of cost-effectiveness and easiness of implementation in non-specialised laboratory settings, including those lacking in adequate computational facilities or expertise for performing numerical studies.

Acknowledgments: Authors would like to thank the µ-VIS X-Ray Imaging Centre at the University of Southampton, for having provided access to their computing facilities to run the numerical simulations reported in this study. Author Contributions: The concept and idea were developed by Claudio Nastruzzi; the processing of the samples was performed by Elisabetta Bottaro, Ali Mosayyebi and Dario Carugo; Experiments, simulations and data analysis were performed by Elisabetta Bottaro, Ali Mosayyebi and Dario Carugo; Elisabetta Bottaro, Ali Mosayyebi, Dario Carugo and Claudio Nastruzzi wrote the paper. Conﬂicts of Interest: The authors declare no conﬂict of interest.

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