1-s2.0-s0925400509002524-main

Sensors and Actuators B 139 (2009) 637647

Contents lists available at ScienceDirect

Sensors and Actuators B: Chemical

journa l homepage: www.e lsev ier .co

Numer amultila

John T. ANew Jersey Cen ence, SCastle Point on

a r t i c l

Article history:Received 2 FebReceived in reAccepted 16 MAvailable onlin

Keywords:MicromixerMicrofabricatiPassive mixingElongational owCFDResidence time distribution

icrochmentl sysis imw, anmuling pn speoluti

was obtained for the ow/mixing unit. This result was compared with numerical RTD predictions basedon computational uid dynamics (CFD) simulations. The simulation results are in good agreement withthe experimental data, especially in the low ow-rate range (Reynolds number

638 J.T. Adeosun, A. Lawal / Sensors and Actuators B 139 (2009) 637647

for mixing enhancement. For passive or static mixers, the inher-ently high surface-to-volume ratio (with the associated high masstransfer rate) in microscale mixer/reactor is generally made effec-tive for mixing enhancement by engineering or manipulating thegeometricaenvironmening the neemechanismmicromixer

The purpthe mixingmicromixerThis worksimulationstool; fabricand performof the mixposed silicocombines ation 2.1) forexperimenttribution (Rin the mixichoice andthe evaluatichallenges [

Variousowvisualiand imaginas Villermhave beenuexperimentof the charaable for theto generateing canbe lithe low locacharacterizprovide quaers but alsodifferent m

The RTDknownmetmacromixetion of mixthe so-callethat can besystems caniments can(dependingformance othe RTD daRTD modelmicromixerow, the apusefulwhenand validat

The CFDulation stuinvestigatinand multi-to obtain sport equatiA commercage, FLUENnumerical

the RTD data were achieved using Mathematica software. Thepresent work is aimed at expanding the knowledge base for thedesign, fabrication, and characterization of effective micromix-ers, the development of which will greatly benet the useful

tions of microchemical systems and other related novellogies.

ign and fabrication process

sign strategy for the proposed micromixer

ur earlier theoretical mixing study [20], three proposedminated/elongational ow micromixers (MEFMs) wereted for their mixing performance. One of the MEFMs thaterred to as MEFM-4 was selected for further study basedcriteria of high mixing performance with minimum pres-rop. This best MEFM shown in Fig. 1 is herein referredEFM-4 because the mixing elements strategically placedmixer channel oor are trapezoidal structures. Each of thees trapezoidal structures has a height of 857.8m, two par-ides of lengths 1000 and 1800m, and an angle of 65

en the slant edge and the longer parallel side. For effec-d rapid mixing enhancement, passive micromixers shouldigneventw traces.on the iffusl incrr. Asinlecha

tedsociaith thcal reationion areswam rrdere preill evM-4

Fig. 1l channels and ow structures within this microscalet. Therefore, it is the technical know-how of impos-ded geometric constraints with the associated mixings that distinguishes the mixing performance of onefrom another.ose of this research work is to design and characterizebehavior of a passive multilaminated/elongational owusing both numerical and experimental approaches.involves: using computational uid dynamics (CFD)as a vital design, optimization and characterization

ating the mixing unit using silicon-MEMS technology;ing experiments to validate the numerical predictionsing characterization. In the present work, the pro-n-based multilaminated/elongational ow micromixert least threemixingmechanisms (discussed later in Sec-mixing enhancement. The numerical simulations andal validationswere performedusing residence timedis-TD) as measure to characterize ow/mixing behaviorng-enhanced conguration. It is worth noting that theapplication of suitable characterization technique(s) foron of mixing behavior inmicrochannels still pose some8,16] that also need to be addressed.mixing characterization measures/methods such aszationof test solutions (containinga chemical indicator)g [15,17], RTD [1820], and test chemical reactions (suchauxDushman competing parallel reactions) [5,21]sed by investigators to characterize theoretically and/orally the degree of mixing in microuidic devices. Somecterizationmeasures have been found particularly suit-qualitative analysis ofmixing [17,21], but its applicationquantitative data for objective characterization of mix-mitedby insufcient sensitivity of the test solutions andl resolution of instrumentation [5]. The most desirable

ation measures/methods should be those that not onlylitative information for the comparisons of micromix-reliable quantitative data for direct characterization oficromixers.

measure chosen for this work, although a well-hod [22] for characterizing ow andmixing behavior inrs/reactors, is still anovel technique for thecharacteriza-ing in micromixers/reactors [1820,23]. By performingd tracer or stimulusresponse experiments, RTD dataused for ow andmixing evaluation in continuous owbe obtained. The RTD data obtained from tracer exper-be used directly or in combination with ow modelson theowsystemboundary conditions) topredict per-f non-ideal ow mixers/reactors. In the present study,ta were used in combination with a semi-empiricalto predict the ow/mixing behavior of the studied

. In the context of microchannels for low Re laminarplication of CFD tools in RTD studies becomes especiallyexperimental RTDdata canbeobtained for comparison

ion purposes.tools have been effectively applied in our prior sim-dies [20,24] and by other researchers [2529] forgowandmixingbehavior inmicrochannels for single-phase systems. These tools were used in our workolutions to three-dimensional ow and mass trans-ons, from which numerical RTD data were extracted.ially available nite volume-based CFD software pack-T, was used for our simulations, while all the otherprocessing steps including numerical integration of

applicatechno

2. Des

2.1. De

In omultilaevaluawe refon thesure dto as Mon theisoscelallel sbetwetive anbe desthem ethe ointerfabasedow. Tuid dnentiatransfeof feedmixingaminathe asally, wand loelongguratstructuupstre

In osonablthat wof MEFd such that the mixing mechanisms implemented inually lead to a reduction in diffusion path of uids innsverse direction and increase in uid-contact areas orWith these goals in mind, the MEFM-4 was designedhe concept of uid multilamination and elongationaluid multilamination leads to the desired reduction inion path while the elongational ow causes an expo-ease in contact areas or interfaces for effective massshown in Fig. 1, for intimate contact right at the onsetts, uid A and uid B are introduced alternately into thennel. With this uids introduction approach, multil-streams of thin multilamellae of uids are formed withted split-and-recombine ow downstream. Addition-e incorporation of themixing elements, uid stretchingorientation of uid interfaces results into the desiredal ow. In order to further enhancemixing in this con-t a design level, the last ve rows of trapezoidal mixingere ipped to form somewhat amirror image of the six

ows.to attain high ow rates (Q) while maintaining a rea-ssure drop, an appropriate ow distribution systemenly distribute the ow into and out of the channels(shown in Fig. 1) must be designed. Using computer-

. Multilaminated/elongational ow micromixer (MEFM-4).

J.T. Adeosun, A. Lawal / Sensors and Actuators B 139 (2009) 637647 639

Fig. 2. Model-backside.

aided desigmanifold anthe other atuniformowFig. 2 wheredescribed inA and B aredevice. Theto the frontsidemanifo(located alostart mixingthis mixer dinlet substreFig. 2a) andforming a station of conguratiochannel dim(V) of about

2.2. Microfabrication procedure

The fabrication of our proposed MEFM-4 was successfully com-pleted using the state-of-the-art equipment at Cornell NanoScale

e andadechnoingmingpho

n etcon00

yed tsequof t

ed, themoM-4.as ucha

n thenifolSciencwas mtion tepackagmachinnamelytive iocreatedtype 1emplominedetchingexpectwas thofMEF(ICP) wmixingholes ithe mabased MEFM-4 with manifold design: (a) the frontside and (b) the

n (CAD) and CFD software packages, one uid-outletd two uid-inlet manifolds one at the frontside andbackside, were designed and optimized to facilitate thedistributionofuids into the channels ofMEFM-4 (seeL=35.0mm and W=30.0mm). The CFD tool used wasour earlier theoretical study [20]. Both uids/speciesintroduced from the inlet ports at the backside of themanifolds are designed such that uid A ows directly-sidemanifold (see Fig. 2a). Fluid B ows from the back-ld (see Fig. 2b) and then through the four through-holesng the line of conuence shown in Fig. 2a) to meet andwith uid A. The geometric focusing [30] nature ofesign layout, i.e. two inlet streams splitting into eight-ams (immediately after the line of conuence shown inrecombining into four substreams downstream beforeingle stream at the exit, also creates global reorien-uid interfaces for effective mixing. This multichanneln has a channel depth of 300m and smallest ow-ension of 200m resulting in a ow-domain volume50L.

a depth ofa cross-secthrough froon the litho

For thefrontside amarks) wetor (GCA/M(HamatechThese threethe backsidfour ow-thfold, inlet ow-througnels and mthat are invures showbare locatedMEFM-4 (ssiliconwafewith 2-mneeded latethepatternsilicon/silicitive photoaligner (EVon the patte(Oxford 100two hot PRnext lithogron the backsurface as iwafer backsby inductivapproximatetching theM2) to a cewould comon both M2ering the pexposed siloxidehardmof the backsTechnology Facility (CNF). Themicrouidicmixing unitfrom silicon and PyrexTM using MEMS microfabrica-logy and the associated microchannel fabrication andethods [31,32]. Specicallyapplyingsiliconbulkmicro-

techniques, which involve two main fabrication stepsto-lithography (hereafter, lithography) and deep reac-hing (DRIE), the desired channels and structures wereboth sides of a double-side polished silicon wafer (p-4-in. diameter, 800-m thick). The fabrication processhree steps of lithography and DRIE each in a predeter-ence to ensure perfect back-to-frontside-alignment andhe ow-through structures in MEFM-4 (see Fig. 2). Asis alignment along with the associated etching process

st challenging requirement for the successful fabricationTheDRIE recipe enabled by inductively coupled plasmatilized for the deep etching (with vertical walls) of thennels, manifold structures, and critical four throughMEFM-4. The mixing channels (on the frontside) and

ds (on both the frontside and backside) were etched to300m while the four ow-through holes (each withtional dimension of 200m by 500m) were etched-m the backside of the 800-m thick wafer. More detailsgraphy and DRIE steps are described next.required lithography steps, the CAD layouts of thend backside of MEFM-4 (with suitable alignmentre rst transferred using an optical-pattern genera-ANN PG 3600F) and a mask-develop-etch equipmentHMP 900) to three 5-in.2 chrome-coated glass masks.glass masks are herein referred to as M1 (comprising

emanifold pattern), M2 (comprising the pattern for therough holes, inlet hole/opening to the backside mani-ow-through hole to the frontside manifold, and outleth hole), and M3 (comprising the pattern for the chan-anifolds on the frontside). Fig. 3 shows the major stepsolved in the fabrication of MEFM-4. The schematic g-asically the cross-sectionwhere the four through-holeswith the cross-section for the inlet and outlet holes onee Fig. 2a). These steps are described herein fully. Ther was initially coated (using thermal oxidation furnace)thick silicon dioxide, which would act as hard maskr for the second DRIE step. In the rst lithographic step,on therstmask (M1)was transferred to thebackside ofon-dioxide wafer (earlier spin-coated with a thick pos-resist) by exposing the mask to UV light via a contact620). The oxide in the developed photoresist (PR) arearned wafer was then removed using a dielectric etcher). The PR on the wafer surface was stripped off using-stripper baths. The second mask (M2) was used in theaphic stepwith the above lithography process repeatedside of the wafer without removing the PR on the wafern the last step above. The exposed silicon area (on theide) was then etched to a depth of 200m using DRIEely coupled plasma (Unaxis SLR-770). The etch rate wasely 2m/min using this system. This DRIE step was foruidic structures (basedon thepattern transferred fromrtain depth such that the remaining depth to be etchedplete the etching requirement of the structural patternsand M1 for MEFM-4. The PR on the wafer surface (cov-attern transferred from M1) was stripped off and theicon area was etched 300mdeep with the 2-m thickask. Thisdeepsiliconetchingcompletes theprocessingide of the wafer.


Fig. 3. SchemSi wafer; andwith Pyrex wa

The remusing a bufthe oxide foPECVD), a 2unprocessewafer a 3-the last deethen emploof MEFM-4oxide in thein preparatthen etchedstructuresw

etch-through of some of the backside structures, such as the crit-ical four ow-through holes, one inlet ow-through hole, and oneoutlet ow-through hole. The PR and silicon dioxide remnants on

fer were nally removed using two hot PR-stripper bathsE sor cleaferandfourSon

ter hto thd wafacilixer(for

ally bthe waand BO

AfteturedwFig. 4aof thetionarydiameaccessmethowhichmicromaligneranodicatic gures showing the fabrication steps: (a) for the backside of the(b) for the frontside of the Si wafer and anodic bonding of the waferfers.

aining silicon dioxide on the wafer was then removedfered oxide etch (BOE; 6:1 HF solution) reaction withr about 30min. Using thermal deposition system (GSI-m thick oxide was deposited as hard mask on thed frontside of the wafer while on the backside of them thick oxide was deposited to act as etch stop for

p etching process (from the frontside). Lithography wasyed with the third mask (M3) to pattern the frontsideusing 8-m thick PR. Using the dielectric etcher, thedevelopedPR area on thepatternedwaferwas removedion for the last DRIE step. The exposed silicon area wasto a depth of 300m to obtain the frontside uidicith the required depth of 300mand consequently the

anodic bonof the silicing Ltd. (AMcomplete fo(Pyrex/silic35.0mm

3. Numeri

3.1. Mixing

In chooapplicablecongurationumerical dtest solutioaccurate fetion of mestream, (vi)interface, aexperiment

RTD is cindicator ofcharacterizof RTD wascussed in deby injectingstant rate (measuringof time. A nzones, axialshape of thDanckwertsdescribes qhave spentow systemfunction, Erelated to tgiven by:

E(t) = C(0

C(

where ti(Howeve

ferent sizesfunction, Elution, respectively.aning this wafer, the next step was to cover the struc-on both sides with 500-m thick PyrexTM glass wafers.b shows the structured frontside and backside of onemixing units obtainable on a wafer. Using the Sta-

ic-Mill Process (Stationary Model AP-1000), 800-moles were drilled through one PyrexTM wafer for uidice structured silicon wafer. Two-step anodic bondings used to cover the silicon wafer with PyrexTM wafers,itates optical and uidic access into the channels of thes. Using EV 501 wafer bonder with the EV 620 contactaligned bonding) at CNF, the structured PyrexTM wasonded to the bottom/backside of the silicon wafer. Theding of the second PyrexTM wafer to the top/frontsideon wafer was carried out at Applied Microengineer-L). The last processing step that made the MEFM-4

r our mixing study was dicing the bonded triple-stackon/Pyrex)wafer into four individualmicromixers of size30.0mm each.

cal analysis

characterization measure

sing the mixing characterization techniques that arenumerically and experimentally to microscale mixingns, the following issues need to be considered: (i)iffusion, (ii) computational time, (iii) sensitivity of thens or reaction(s), (iv) the appropriate methods for theeding/injection of the test uids, (v) the reliable detec-asurable signals in the outlet mixture or product(s)material of construction of the micromixer/detectionnd (vii) cost and relative ease of construction of theal setup.hosen for this work because it serves as a reasonablethe type and extent of mixing. In order to analyze and

e the mixing performance in real reactors, the conceptrst extensively used by Danckwerts [33] and later dis-tails by some authors [3436]. The RTD can be obtaineda tracer instantaneously (a pulse input) or at a con-

a step input) at the inlet of a ow system, and thenthe tracer concentration, C(t), at the exit as a functionumber of factors such as channeling, stagnation in deaddispersion, and imperfectmixingusually determine thee obtained response curves from the RTD experiments.[33] dened a function, known as RTD function, whichuantitatively how much time different uid elements(i.e., distribution of the times spent) in a continuous. Mathematically, the RTD (or exit age-distribution)

(t), can be dened such that for pulse input, E(t) ishe outlet tracer concentration, C(t), by the expression

t)

t)dt

= C(ti)i=0

C(ti)ti

(1)

= ti+1 ti) is the time step for the measurements.r, when the mixing performance of ow systems of dif-or ow conditions is to be compared, a normalized RTD(), is used instead of E(t). Both functions are related


the fr

by Eqs. (2aRTD.

E() = tmE(

where dime

= ttm

RTD anaone-inlet smitigated fthe tracerinlet) whilewater owinlet, one-oThe concenexperimentcertain inleare met. Itthe CFD simbevalid, theimental meRTD functioresidence tition, and co(3), (4), anddeviate fromhydrodynammicrochannCoV of zerozero CoV imnon-uniformthis case, thRTD, the clothe better t

tm =

0

tE(t

0

E(t

(since

0

E(

(t

tm

mpu

is gmerintumrest itratin oformastemow

is) ouidom

giveny vecary, , auident ary cblemed.

= 0Fig. 4. Fabricated MEFM-4 (without PyrexTM covers): (a)

)(2b), where tm is the mean residence time of the

t); (2a)

nsionless time:

(2b)

lysis [22] is generally applicable to ow system withtream (where tracer is injected). This limitation isor our two-inlet, one-outlet ow system by injectinginto one of the two inlets (referred to as the main-feeding the second inlet with 1% of the main-inletrate. This makes this ow system effectively a one-utlet system as desired without any ow disturbance.trationtime data obtained from a stimulusresponsecan represent or be used to obtain the RTD provided

t and outlet boundary conditions earlier discussed [24]is worth mentioning that for the comparison betweenulations and the laboratory experimental RTD data toCFD simulations should approximate closely the exper-thods of injection and measurement [37,38]. Once then is obtained, statistical parameters such as the meanme (tm), variance (2) or square of the standard devia-efcient of variation (CoV) can be obtained using Eqs.(5), respectively. The RTD of a microchannel mixer willan ideal plug-ow mixer/reactor depending on the

icswithin themicrochannel. In the context of the staticel mixers designed to effect radial/transverse mixing, awould imply complete plug-ow mixing while a non-plies that there is axial dispersion or mixing caused byor laminar velocity prole andmolecular diffusion. In

e smaller the variance or the CoV, the narrower is the

2 =0

CoV =

3.2. Co

CFDthe numomeof inteconcensolutiothe infow symixinganalystonianmass, mtems)velocitand binwhile pof therepresboundthe proobtain

( v)

vser is the distribution to the mean residence time, andhe mixing quality.

)dt

)dt

=0

tE(t)dt =

t=0tE(t)t (3)

t)dt = 1)

t+ v v

cAt

+ (v.)

where

cA = AOur num

volume-basinterfaced w(Dual 3.0Gsize of abouservers andontside and (b) the backside.

tm)2E(t)dt =

t=0

(t tm)2E(t)t (4)

(5)

tational uid dynamics (CFD) simulation

enerally recognized as a powerful tool for obtainingcal solution to the equations of conservation of mass,, energy and chemical species describing the problemn a given ow geometry. Theoretically, the velocity andon elds of a tracer, which can be obtained from thethe transport phenomena equations [39], constitute alltion that is needed to determine RTD in a continuous. For the theoretical analysis of the isothermal, laminarproblem, the steady-state (or unsteady-state for RTDw and species mass transport of incompressible New-(s) can be described by equations of conservation ofentum, and chemical species transport (for binary sys-in Eqs. (68), respectively. In these equations, v is thetor, cA,A, andDAB are the concentration,mass fraction,diffusivity of the species A for system AB, respectively,nd are the pressure, density, and kinematic viscosity, respectively. In our simulation, uid/species A and Btracer and water, respectively. By applying appropriateonditions to the geometrical conguration of interest,is specied completely and a unique solution can be

(6)

1 2=

p + v (7)

cA = DAB2cA; (8a)

(8b)

erical simulations were performed using a niteed commercial CFD code of FLUENT (Fluent 6.3.26ith Gambit 2.4.6) installed on a 64-bit master server

Hz Intel Xenon with 8G of RAM and total hard-diskt 1400GB) within a Red Hat Enterprise Linux-cluster ofworkstations. Pro/Engineer, a powerful CAD software


package, was used for solid modeling of the micromixer cong-uration. GAMBIT preprocessor (CFD preprocessor from FLUENT)was used for extracting the uid ow domains of the geomet-rical congurations and for meshing. As part of the measures toobtain accuelements (qup the uidfectly as podomain intmesh depeval size of vneeded to oa mesh witcomputatiocessor to thsolver wasand speciesthe simulatcomparingthe existingequations atial manneralgorithms.

The convobtained r(since densthe inlet zocondition aof the conguid) wereobtain a stavergence crwere set ap

Using thequations, tsimulation,zero diffusifor the tracof one (forrst time stfor the seczone. The ptheoreticallsimulationsied for thdiscretizatitransport ean error gencal error cane mesh aschemes. Hdient optioin FLUENTwthe convectorder impliin solving tsolution fordata (acquinent of FLUdone to obtmeasuremement obtainin our tracethen expor2, and Comixing.

4. Experimental analysis

4.1. Setup and procedure

sche5a. Tixer

dentthe iicontageuni

essiond orespc) wtes oit. Ainletstlete soluresceady spumcomm VOptimetaneo

the. Theng ct wig. 5acontionceroutUVancetratity) caon ths, thementa timn we ota acngthixinize thion zed uimatf ued frnderata oD anh osh habilitystemmentions.rate solution there is need to have as many structureduadrilateral/hexahedral elements) as possible makingdomain mesh and also aligning with the ow as per-ssible [40]. This was achieved by breaking the uido suitable sub-domains before meshing. In addition, andence study was carried out to determine the inter-olume elements suitable for adequate mesh resolutionbtain mesh-independent solution. Based on this study,h 3.8 million nodes was found adequate (consideringnal expenses) and then exported from GAMBIT prepro-e FLUENTsolver. TheFLUENTsegregatedpressure-basedused for the solution of three-dimensional uid owtransport problem. The validity of the CFD code forion of RTD in microchannels has been examined byCFD simulation result in tubular microchannel withtheoretical prediction [24]. In essence, the uid ow

nd species transport equation were solved in a sequen-using appropriate boundary conditions and numerical

erged solution to steady state uid ow problem wasst. A uniform velocity prole was specied indirectlyity is constant) by setting the desired mass ow rate atne(s). The no-slip condition was specied as boundaryt the walls and gauge pressure of zero at the outlet zoneurations. The properties specied forwater (as amodel =998.2 kg/m3 and =1.005106 m2/s. In order toble, converged solution, certain parameters and con-iteria such as under-relaxation factors and residualspropriately.e converged solution of the steady state uid owhe tracer species equation was solved as an unsteadywhose solution was then used for RTD analysis. The

ve ux was specied as boundary condition at the wallser species transport equation. Species mass fractionstime t=0 at pulse injection of tracer into water forep) and switched to zero (at t>0 after pulse injectionond and later time steps) were specied at the inletroperties of water were specied for the tracer sincey the tracer is taken as a water-like uid for our RTD. A mass diffusivity, DAB, of 1.5109 m2/s was spec-e tracer-water (AB) system. It should be noted thaton of the convective terms in momentum and speciesquations (Eqs. (7) and (8a-b) above) usually introduceserally referred to as numerical diffusion. This numeri-

n be considerably minimized [41] by using CFD-qualitynd choosing appropriate discretization (interpolation)ence, Green-Gauss node based was chosen as the gra-n while the QUICK and second-order upwind schemesere used as the higher order interpolationmethods forive terms in Eqs. (7) and (8a-b), respectively. The 2nd-cit unsteady formulation in FLUENT was also speciedhe species equation to give a more robust and accuratethe unsteady state simulation. The tracer concentrationred at the outlet zone using the postprocessing compo-ENT)were thenweighted by outlet surface area. This isain through-the-wall (or spatial average concentration)nt [35], which closely represents the type of measure-able at the outlet boundary of the ow/mixing systemr experiment. These weighted concentration data wereted into Mathematica for RTD analysis, in which tm,V were obtained and used to evaluate the degree of

Thein Fig.micromdepenatbothThe silblock/smixingcomprports athe corScientiow raing unat theone-ouvolumas uothe stesyringeusing ator (froOceanspectrosimultat bothdevicesampliinterac(see Fi

Thecalibrathe tracarriedfor theabsorbconcentionaliBasedtal runexperi

Atsolutiointo thing daThe leow/mminimdetectacquirthe esttime oobtainarea utime dfor RTfor eacestablirepeatow sexpericonditmatic of the setup for our tracer experiment is shownhe experimental setup for mixing characterization ins using RTD measure was designed such that the time-tracer absorbance or concentrationdata canbeobtainednlet andoutlet ofow/mixingcongurationsof interest.-fabricated MEFM-4 was mounted on a stainless-steelcustom-built for pressure-driven ow access into the

t (as shown in Fig. 5b). Suitable O-rings were used forn seal tting after aligning the three holes (two inletne outlet port) at the backside of the mixing unit withonding holes in the block. Two syringe pumps (from KDith 10-mL syringes were employed to deliver constantf deionized water via the two inlet ports into the mix-ow ratio of 100:1 was used (same as for simulation)in order to make the ow system effectively one-inlet,

system with practically zero ow disturbance. A micro-tion of uranine (a water-soluble tracer dye also knownin sodium), was then introduced as a pulse input intotate ow of water. Through a 10-mL syringe on anotherp, the tracer was introduced into themain inlet streamputer-controlled four-portmicro-volume sample injec-alco Instruments Co. Inc.). The detection system (fromcs Inc.) used comprises miniature PC2000 PC plug-iners with two congurations, a master and a slave, forus detection andmeasurement of the tracer absorbanceinlet and outlet sampling zones of the ow/mixinglight source (tungsten halogen lamp), ow-through

ells and the spectrophotometers were connected toth one another using 400-m diameter optical bers).sistency and the linearity of the calibration curves fromexperiments for the two sampling regions show thatconcentrations at which our RTD experiments wereare within the linear BeerLambert response rangevis spectrophotometers. Therefore, the obtained tracer, which is a quantity that is proportional to traceron (i.e. C(t) = kA(t), where k is the constant of propor-n be used directly after normalization for RTD analysis.e calibration experiment and initial tracer experimen-optimum amount and concentration of tracer for RTDs were determined.e, say t=0 s, a 1.0L of 0.5 g/L (500ppm) uranine

as injected for a very short time period of 0.145 swing deionized water while simultaneously initiat-quisition using the spectrometer operating software.of the tubing connecting the injection point to the

g system is reduced to the minimum possible so as toe axial dispersion of the pulse before reaching the inletone. The time-dependent absorbance data were thenntil the measurement time reached about ve timesed values of (=V/Q), the theoretical average residenceid in the microchannel. The absorbancetime curvesom tracer experiment should be normalized by theabsorbancetime curve. The normalized absorbance-btained were then used as concentrationtime data

alysis. Four replicates of experiments were performedw rate investigated with our experimental setup toigh repeatability of data. It should be noted that they of data obtained via tracer experiment in microscales depends largely on the ability to perform theunder carefully controlled and optimal experimental


device

4.2. Modeli

Needlessoretical perTherefore,is vital fortems whilefrom the mapproach baful for extrtheorem, fotion (a typiexists betw(i.e. Cpout(t)centration (given by the

Cpout(t) =t0

Applyinggral in Eq. (9can be mathtion data, Cdata and a sow systemdiction of thow system

Modelsassumed intors. Two Ra semi-emp

sedas uFig. 5. (a) Schematic diagram of the experimental setup. (b) MEFM-4

ng of RTD were uSEM wto say, it is technically challenging to obtain the the-fect pulse or step injection of tracer experimentally.the acquisition of the inlet tracer concentration datathe determination of RTD of microchannel ow sys-excluding the effects of the auxiliary components

easured cumulative output response. A mathematicalsed on Convolution Integral theorem [35] is quite use-acting the model-based RTD (E(t)). According to thisr a linear ow process in which a one-shot tracer injec-cal imperfect pulse injection) was made, a relationshipeen the time-dependent output tracer concentrationobtained at time t), the E(t), and the input tracer con-i.e. Cin(t t) measured at time t earlier than t). This isconvolution integral:

Cin(t t)E(t)dt =t0

Cin(t t)E(t)t (9)

the above numerical version of the convolution inte-), the measured output concentration data (i.e. Cmout(t))ematically tted with the predicted output concentra-

pout(t), a convolution product of the input concentrationuitable RTD model. The model description of RTD in ais useful for estimating parameters and hence the pre-e ow/mixing behavior and/or the conversion for the.that closely represent ow in the real system areorder to predict the performance of non-ideal reac-

TD models: axial dispersion model (ADM) [19,35] andirical model (SEM) described by Ham and Platzer [42]

quite wellgurations[18] also usworkonmobased on thow systemis shown in

E()

= E(t)

= MNtN+

where

tk =tmintm

tmax In Eq. (1

real physicamodel obtaasymmetryobtained RTthe experimthe tracer, wcurves. In thcurvettingafter estimaassumed mobtain the vof deviationmounted on a stainless steel block/stage.

for RTD modeling in our prior work [24]. However, thesed in the present work since it was found to model

the hydrodynamic behavior of the microchannel con-studied better than the ADM. Boskovic and Loebbeckeed SEM and found it to be superior to ADM in theirdeling of RTD inmicrochannelmixers. TheRTD functione SEM [42], particularly suitable for themodeling of reals with certain asymmetric residence time distribution,Eq. (10a-b):

E(t)

tNk1

(1 t

tmax

)N1{1 t

Nk

tN

(1 t

tmax

)N}M1(10a)

ax

tmin(10b)

0a) above, M and N are the model parameters with nol signicance to ow or mixing behavior but the RTDinable is very useful in approximating RTDswith certain. In essence, the calculatedmean and the variance of theDs can be used to obtain the CoV. The tmin and tmax areental minimum and the maximum residence times ofhich can be estimated from the output concentratione convolutiondeconvolution technique, timedomainvianon-linearoptimizationwasused todetermineE(t)ting the parameters in the RTD model used. With theodel, the objective of the optimization problem was toalues of parameters that minimize the sum of squares() between the measured and the predicted outlet


Table 1The results of the RTD analysis for CFD simulation and experiment at different ow conditions.

CFD simulation Experiment

Flow rate (mL/min) (s) Re () Pef () P (Pa) tm (s) CoV (%) Data points tm (s) CoV (%) Data points0.20 35.72 5.1 3420 382 38.26 27.6 5857 41.51 32.3 9080.25 28.58 6.4 4270 478 30.80 29.2 4787 34.09 32.7 7440.40 17.86 10.2 6840 765 19.74 33.1 3192 22.35 40.6 6650.50 14.29 12.8 8550 957 16.07 34.9 2642 18.53 42.4 555

concentration curves. That is, from Eq. (9):

=[(

Cmout(t) t0

Cin(t t)E(t)t)]2

(11)

In order to solve this convolution and the resulting optimiza-tion problem for large number of data points obtained from ourexperiments, a codewaswritten and implemented using somepro-gramming functions available in Mathematica5.2 software. Afterperforming code validation exercises, the RTD model parametersM and N from SEM obtained based on the model tting was thenused to determine the RTD function (E(t) vs. t) and normalized RTDfunction (E vs. ) curves.

5. Results and discussion

5.1. Tracer experiment

Based on calibration experiment and initial experimental runs,a ow rate range of 0.200.50mL/min was chosen for our stud-

Fig. 6. The outfor MEFM-4: (

ies. Hence, data were obtained at four different volumetric owrates (Q) 0.20, 0.25, 0.40, and 0.50mL/min, for which the associ-ated low Reynolds number range is 5.112.8. The Reynolds number(Re=uLc/) and uid Peclet number (Pe=uLc/DAB) are calculated(shown in Table 1) based on the outlet cross-sectional area ofthe microchannel mixer (1000m by 300m), the characteris-tic length/diameter (Lc; based on the outlet ow cross-section),and the average velocity (u) through this cross-sectional area.Using the earlier-described experimental setup, time-dependentconcentration data were acquired (at the inlet and the outlet ofthe mixing unit) automatically (starting from time t=0) for thepulse injection of uranine into the main-inlet water ow stream.The implementation of the Mathematica5.2 code for the requiredconvolutiondeconvolutionof concentration andRTDmodel data ledto the determination of the predicted output concentration curve,model parameters, and the associated RTD model. At ow rates of0.20 and 0.40mL/min, for instance, the predicted and themeasuredoutput concentration curves based on SEM are shown in Fig. 6. Asexpected, there is a better t of the experimental data at a lowerow rate of 0.20mL/min since from the model tting it has a lowerput concentration curves (predicted and themeasured) based on SEMa) at 0.20mL/min and (b) at 0.40mL/min.

Fig. 7. (a) the) for MEFM-4extracted RTD curves (E(t) vs. t) and; (b) the normalized RTDs (E vs.at ow rates of 0.20mL/min and 0.40mL/min.


Fig. 8. The com of: (a)

sumof squafor Q=0.40normalizedare shown i

5.2. CFD sim

Applyinganalysiswaother relevatreatment osteady stateApart fromof 382957using multichannel conthe spatialthrough-theoutlet insterepresent ma result of thmimic ourthousand titime, wererun. Themein Table 1 shcal averageof 7% at lowat higher is because osimulationow-weighaverage res

E vsed fu

mpaparison of the E vs. curves for the CFD simulation and experiment at a ow rate

res of deviation,=0.00070, comparedwith=0.00169mL/min. The extracted RTD curves (E(t) vs. t) and theRTDs (E vs. ) obtained from the respective RTD datan Fig. 7a and b.

RTDs (discuss

5.3. Coulations

the CFD approach described in Section 3.2, the RTDsperformedusingFLUENT integratedpostprocessor andnt mathematical packages for the required statisticalf the RTD data. The pressure drop result based on thesimulation of ow in MEFM-4 is shown in Table 1.

higher throughput, lower pressure drop (P in a rangePa for the ow rates studied) is another advantage ofchannel mixing congurations compared with single-gurations [20]. For the species transport simulation,average concentration data (that reasonably represent-wall measurements) were obtained at the mixing unitad of theow-weighted average concentrationdata thatixing-cup or closed-boundary measurements. This is ase fact that the through-the-wall measurements closelyexperimental concentration data acquisition. Tens ofme steps, depending on the ow rate ormean residencerequired to obtain convergence for each 3D simulationan residence times (tm) obtained at different ow ratesows that the CFD predicts reasonablywell the theoreti-residence times (). The degree of deviation: maximumer ow rates (i.e. 0.20 and 0.25mL/min) and about 12%ow rates (i.e. 0.40 and 0.50mL/min), is expected. Thisur mean residence time and RTD calculations via CFDwere purposefully (as earlier mentioned) not based onted average concentration data, upon which theoreticalidence time and RTD are derived [35]. The normalized

Based ontions and efunction (Erates of 0.20Fig. 8(a)(dexperimentthe curves o

Unlike abroad RTD [stirred-tankideal tubulabehavior (wner, the proits channelimprove onarrower thIt is not onto quantitaof the RTD.

The resuare shownin ow rateof MEFM-4and the sim(very low Rin MEFM-4such that mPeclet num0.20mL/min; (b) 0.25mL/min; (c) 0.40mL/min; and (d) 0.50mL/min.

. ) obtained for MEFM-4 at the ow rates studied arerther in the next sub-section.

rison of experimental data with numerical predictionsthrough-the-wall measurements for the CFD simula-xperiment, the plots obtained for the normalized RTD

) as a function of dimensionless time () at the ow, 0.25, 0.40 and 0.50mL/min for MEFM-4 are shown in), respectively. It can be seen from these gures that theal normalized RTD curves are in good agreement withbtained from simulations.single continuous-owstirred-tank reactor (CSTR)with34], a series of identically sized (say, n) continuous-owreactors (n-CSTRs) are sometimes used to model non-r reactors so as to closely approach plug ow reactorith narrower RTD) as n increases. In a similar man-posed MEFM-4 is designed with mixing elements onoor and other mixing enhancement mechanisms tow/mixing in a way that the RTD becomes narrower. Thee RTD, the closer it approaches ideal plug owbehavior.ly necessary to qualitatively match the RTD curves buttively compare the CoV values for the characterization

lt of the RTD analysis for our simulation and experimentin Table 1. The moderate increase in CoV with increaseimplies a reasonable decrease in mixing performance. The same trend is obtained for both the experimentulation. Considering the operating laminar ow regimee) in this study, the above results suggest that mixingis being controlled by transverse (or radial) diffusionixing improves with residence time (and decrease inber). Of course, there is optimum residence time for


good mixing. The real value of using CoV as a measure of mix-ing can be seen when different congurations are compared fortheir mixing performance. In fact, it has been shown in our earliernumerical work [20] that MEFM-4 exhibits remarkably better mix-ing performance than T-junction and other micromixers studied(at same msmaller CoVRTD data begood mixinmixing is cnel mixer oresults showwell the noand can thesystems.

6. Conclus

The mixinated/elonexperimentdesign, numtion of thisthat the debe based onow such tbe combine

Tracer edetection tedata for RTtion of RTDwas appliedical experimRTD data inwere used tmean residthen used tThe MEFM-narrow RTDating lowthe normaltion show gstudy). Thisdevelopingeffective msensing an(bio)chemicand other m

Acknowled

The authIndustrial TSociety Petrin support orication wa(CNF), a mNetwork, w(Grant ECS-individualsMeredith Msey CenterQian (form(Applied Mhofer ICT, G

References

[1] S.J. Haswell, R.J. Middleton, B. OSullivan, V. Skelton, P. Watts, P. Styring, Theapplication of micro reactors to synthetic chemistry, Chem. Commun. 5 (2001)391398.

[2] J.R. Burnsm. Enolosh

ect co47.riniva. HarodationEhrfelicrom. Chemest, Mievemesseling p. NguyR16.Hesse: Proc.obbyers, J.Veen

erizatiinje

.. Bessoing, Aessel

ital m577.Schwegrate. Stroootic mang, Smicro.T. Ngmixe

.BoskoromixTrachse dist7.Adeosrienta111.anic, Sbette. J. 10. Paul,sta (Eons, Hohse,thod froreaAdeosistics i. Sci. 6ubin,m. EnlatzelStreure tool235.chonf04) 77. Heibce tim133.ian, Anctioardt,mericaMado2002.erpoo953. Dancm. Enean residence times) since its RTDs are narrower withvalues. Caution need be exercised when interpreting

cause obtaining narrowRTD does not necessarily implyg in every mixing/reaction system. However, if goodarefully designed into and optimized for a microchan-r reactor, narrow RTD should be expected. The abovethat the RTDs fromCFD simulation can predict reliably

n-ideal ow behavior in microchannel mixers/reactors,refore be used in estimating conversion inmicroreactor

ions

ing enhancement at low Re ow regime in a multilam-gational ow micromixer (MEFM-4) was investigatedally as well as numerically. The work involves theerical simulation, fabrication, andmixing characteriza-proposed multichannel micromixer. This study showssign of an ideal passive micromixer or reactor shouldthe concept of uid multilamination and elongational

hat high mixing performance and high throughput cand with minimized pressure drop.xperiment utilizing UVvis absorption spectroscopychnique was used to obtain the required concentrationD analysis. With the aim of obtaining model descrip-in the MEFM-4 studied, a semi-empirical model (SEM)to the experimental tracer data. By performing numer-ents using CFD tools, the laboratory acquisition ofMEFM-4 was suitably mimicked. The obtained data

o determine the characteristic moments of RTD such asence time and variance (or CoV). These measures wereo indirectly characterize mixing behavior in MEFM-4.4 shows a good mixing performance considering itswith the low values of CoV obtained at the oper-

Re ow regime. Results of the comparison betweenized experimental RTDs and those from CFD simula-ood agreement at various ow rates (5


[34] H.S. Fogler, Elements of Chemical Reaction Engineering, 3rd ed., Prentice HallPTR, Upper Saddle River, NJ, 1999, pp. 809918.

[35] O. Levenspiel, Chemical Reaction Engineering, 3rd ed., John Wiley & Sons, NewYork, 1999, pp. 257349.

[36] E.B. Nauman, Residence Time Distributions, Wiley, New York, 1983, pp. 352 (Chapter 1).

[37] E.B. Nauman, Residence time theory, Ind. Eng. Chem. Res. 47 (2008) 37523766.

[38] O. Levenspiel, J.C.R. Turner, The interpretation of residence-time experiments,Chem. Eng. Sci. 25 (1970) 16051609.

[39] R.B. Bird,W.E. Stewart, E.N. Lightfoot, TransportPhenomena, 2nded., JohnWiley& Sons, New York, 2001, pp. 846848.

[40] FLUENT 6.3 Documentation, Fluent Inc., Lebanon, New Hampshire, 2006.[41] E.M. Marshall, A. Bakker, in: E.L. Paul, V.A. Atiemo-Obeng, S.M. Kresta (Eds.),

Computational FluidMixing, JohnWiley & Sons, New Jersey, 2004, pp. 257338(Chapter 5).

[42] J.H. Ham, B. Platzer, Semi-empirical equations for residence time distributionsin disperse systemsPart 1: continuous phase, Chem. Eng. Technol. 27 (2004)11721178.

Biographies

John T. Adeosun obtained his B.Sc. in Chemical Engineering (1998) from ObafemiAwolowo University, Nigeria and his M.Eng. in Chemical Engineering (2004) fromStevens Institute of Technology, Hoboken, New Jersey, where he would be obtain-ing his Ph.D. in Chemical Engineering (2009). His research interest is in the design,fabrication, and characterization of microscale mixers/reactors using CFD, andexperimental study of the transport processes and reaction kinetics in these micro-chemical systems.

Adeniyi Lawal obtained his S.M. (1982) and Ph.D. (1985), both in Chemical Engi-neering, from Massachusetts Institute of Technology (MIT), Cambridge, and McGillUniversity, Canada, respectively. He is a Professor of Chemical Engineering at theDepartment of Chemical Engineering and Materials Science, Stevens Institute ofTechnology, Hoboken, New Jersey. His research interests are inmathematicalmodel-ing of transport processes in complexmacro- andmicro-geometries, and design anddemonstration of microreactor systems for on-demand, on-site chemical synthesisand biofuel production.

Numerical and experimental mixing studies in a MEMS-based multilaminated/elongational flow micromixerIntroductionDesign and fabrication processDesign strategy for the proposed micromixerMicrofabrication procedure

Numerical analysisMixing characterization measureComputational fluid dynamics (CFD) simulation

Experimental analysisSetup and procedureModeling of RTD

Results and discussionTracer experimentCFD simulationsComparison of experimental data with numerical predictions

ConclusionsAcknowledgementsReferences

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