Jurnal Nanoteknologi

8/10/2019 Jurnal Nanoteknologi

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chemical engineering researchand design 9 1 ( 2 0 1 3 ) 23892400

Contents lists available at ScienceDirect

Chemical EngineeringResearch and Design

journal homepage: www.elsevier .com/ locate /cherd

Effectof hydrodynamics during solgel synthesis of TiO2nanoparticles: Frommorphology to photocatalytic properties

Mlisa Hatat-Fraile, Julie Mendret, Matthieu Rivallin, Stephan Brosillon

IEM (Institut Europen desMembranes), UMR 5635 (CNRS-ENSCM-UM2), Universit Montpellier 2, Place E. Bataillon,

F-34095 Montpellier, France

a b s t r a c t

In this study, the role of mixing hydrodynamics during the solgel synthesis of titania nanoparticles and the conse-

quences on their photocatalytic properties were investigated. For the first time three different T-mixer geometries

were tested. Alcoholic solutions of titanium tetra-isopropoxide and water were mixed in three different T-mixers

with turbulence promoters and thus differentmixing characteristics. The changes of nanoparticle sizes during the

induction time of the solgel process were followed by dynamic light scattering and velocity and turbulence fields

were simulatedbyComputational Fluid Dynamics (CFD) for the three T-mixergeometries. Theresults indicated that

macro-mixing is crucial during the first step as it determines the nucleation rate and then the primary particle size.

The micro-mixing has an influence on particle properties, especiallyon particle stability. Titanium dioxide nanopar-

ticles synthesized by the solgel process were deposited on alumina supports. A homogeneous filmof about 200nm

was deposited in all cases. Degradation of Acid Orange 7 (AO7) was used to evaluate the photocatalytic activity of

TiO2 coatings.No difference wasobserved between thephotoactivity of synthesized TiO2. Total mineralization of the

dye occurred after 24h irradiation.

2013 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

Keywords: Water treatment; Titaniumdioxide; Solgel synthesis; Photocatalysis; Mixing

1. Introduction

Advanced Oxidation Processes (AOPs) are those which allow

thedegradationof organicbio-recalcitrantpollutants inwater.

Broadly speaking, AOPs can be used as oxidation methods

in aqueous medium based on the use of highly reactive and

non-selective species, such as hydroxyl radicalsOH for the

destruction of organic compounds (Comninellis et al., 2008;Oturan et al., 2011). Due to the highly unselective reactions

involved in AOPs, the application of these techniques was

mainly directed to the removal of hazardous compounds in

polluted effluents. Photocatalysis is one of the most com-

monly used AOPs. In this method, the generation of the

oxidizing species is achieved by the irradiation in thenear UV

of a semiconductormaterial.

Among semiconductor materials, titaniumdioxide TiO2 is

considered as one of the best for photocatalysis application

(Fujishima et al., 1999; Chebli et al., 2011; Brosillon et al., 2008;

Molinari et al., 2009; Faisal et al., 2011; Lin et al., 1998, 2011;

Corresponding author. Tel.: +33 467144624; fax: +33 467149119.E-mail address:[email protected] (J. Mendret).Received17 July 2012;Received inrevisedform5 April 2013;Accepted25April2013

Abramovic et al., 2011). The use of aqueous nanometric TiO2particlesin theaqueousphase forpollutant treatment bypho-

todegradation has been widely studied (Faisal et al., 2011; Lin

et al., 1998, 2011; Abramovic et al., 2011; Molinari et al., 2002)

and provides very good elimination of organic species com-

pared with conventional treatment methods.However, one of

themaindrawbacksof thistechnologypertainsto therecovery

of the catalyst fromthereactiveenvironment. ImmobilizationofTiO2ona supportenablesthisdrawback tobemitigatedand

offers the possibility of preparing thin TiO2films of a desired

thickness andhomogeneitywiththepower todegradeorganic

compounds (Antoniouetal., 2009;Romanosaetal., 2012). Nev-

ertheless, according to several studies (Molinari et al., 2009;

Zhang et al., 2003; Plantard et al., 2011) the deposited cata-

lyst tends to (i) diminish the efficiency of the photocatalysis

because the catalyst structure andmorphology induce a non-

optimal distributionof the irradiating light and (ii) be released

over time, thus decreasing theefficiency of thephotocatalytic

process. Furthermore, the level of photoactivity of the coated

0263-8762/$ see front matter 2013 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.http://dx.doi.org/10.1016/j.cherd.2013.04.022
http://www.sciencedirect.com/science/journal/02638762http://www.elsevier.com/locate/cherdmailto:[email protected]://localhost/var/www/apps/conversion/tmp/scratch_3/dx.doi.org/10.1016/j.cherd.2013.04.022http://localhost/var/www/apps/conversion/tmp/scratch_3/dx.doi.org/10.1016/j.cherd.2013.04.022mailto:[email protected]://www.elsevier.com/locate/cherdhttp://www.sciencedirect.com/science/journal/02638762


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chemical engineering researchand design 9 1 ( 2 0 1 3 ) 23892400 2391

Fig. 1 Sketch of the solgel reactor.

tetra-isopropoxide (TTIP) as alkoxide. 2-Propanol 98% (from

VWR) and TTIP 97% (from Aldrich) were usedwithout further

purification. Equal volumes of reactant solutions (i.e. 100ml)

were mixed at 293K in a static T-mixer. The TTIP/2-propanol

solution (A) at 0.153mol TTIP/L and H2O/2-propanol solution

(B) at 0.376molwater/Lwere injectedwithconstantequal flow

rates into a static T-mixer via two peristaltic pumps. The

hydrolysis ratio isH=CW/CTi=2.46. The air for the experiment

was dried using a silica gel desiccator. Solutions exiting the

reactor were collected in a small vessel at a thermostatically

controlled temperature of 273K (Fig. 1).

Static T-mixers with an inlet Reynolds number Rein ran-

ging from 6000 to 8000 offer all the characteristics necessary

inorderto obtainan optimal granulometryanda quasi-mono-

dispersed size distribution of particles (Azouani et al., 2010).

In this study, three different T-mixer configurations were cho-

sen to investigate the influence of the hydrodynamics on the

TiO2nanoparticles solgel elaboration: a simple T-mixer (Ts),

a T-mixerwith baffles (Tb),and a T-mixer composed of a large

pipe connected to a narrow pipe (Tn). Fig. 2 gives a detailed

schematic of theT-mixers. Baffles andnarrowpipeswerecho-

sen to create turbulence and therefore various mixing times

shorter than the typical reaction time based on Rivallin et al.,

givingaprimaryhydrolysistimeof severaltensofmilliseconds

forthe sameoperating conditions (Rivallinet al., 2004). For the

three T-mixers,thetworeactant streamswere fedtangentially

into opposite sides of the reactor through two 2mm inner

diameter eccentric pipes; the mixed solution left the reactor

from the bottom through an outlet pipe of 4mm inner diam-

eter for Ts and Tb and 2mm for Tn. Eccentric injection of the

reactive fluids created a vortex which promoted mixing. The

experimental inlet velocity chosen in this study is thehighest

one which enables the use of the three mixers (Tnis flow-rate

limited) with a turbulent inlet Reynolds number.

Fig. 2 T-mixers. Top view (a), front view ofTs (b), Tb (c)

and Tn (d).

2.2. Dip-coating reactor

During the induction period, the temporal stabilization of

extremely reactive TiO2 clusters and particles enabled the

efficient doping and deposition processes. Chemically active

sols reacted with the active sites of the support surface. In

this study, solgel TiO2 nanoparticles were immobilized dur-

ing the induction period on non-porous alumina supports

(100mm50mm 4mm 75g Technical Glass Company,UK) using a dip-coating apparatus (Dip Master 201, Chemat

Technology, Inc.). Supports were washed in an acid solution

and then submerged for 99s in the TiO2nanoparticle suspen-

sion. Thewithdrawal speed was 10cm/min. TiO2coating was

realized6 timesononefaceonly (theother faceswerehidden).Thesupportwas driedat 343K for24 h.Thethermaltreatment

was continued by calcinations at 673K for 3h to enable the

anatase formation with heating at 2K/min. Finally, the sup-

port was washed in order to remove excessive non-reacted

nano-particles.

2.3. Characterization

The characterization of the particulate systems obtained in

thedifferent experimentswascarriedoutassumingan instan-

taneous formation of solid particles and a subsequent slow

aggregation/condensation process. Themean particle size of

the sol obtained after mixingwasmeasured by dynamic light

scattering (DLS)withaMalvernZetaSizerNanoseries (NanoS,

Malvern instruments) providing reliable information in the

size rangeof 16000nm.Thisdeviceenables themeasurement

of the mean particle size and the particle size distribution


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2392 chemical engineering researchand design 9 1 ( 2 0 1 3 ) 23892400

Fig. 3 Chemical structure of Acid Orange 7 (AO7).

(PSD). The mean particle size and particle size distribution

were followed with time by making regular measurements.

Scanning electronmicroscopy (SEM, S-4800, Hitachi) was car-

riedoutbeforeandafter thermaltreatments.Each experiment

was repeated three times in order to verify the synthesis and

characterization protocol reproducibility.

2.4. Photocatalytic reactor

Photocatalysis properties of the synthetized TiO2 coat-

ing were investigated by following the degradation of

Acid Orange 7 (AO7) as a model pollutant (Fig. 3). AO7

(purity>85%) was purchased from Aldrich and used with-

out further purification. The photocatalytic reactor consists

in a batch glass reactor composed of two tanks separated

by a UV transparent Plexiglas wall (Fig. 4). The first one

(height=200mm, width=50mm, depth=110mm) contains a

UV light (=365nm, Philips pL-L 24W/10/4P) and the second

one (height =200mm, width=85mm, depth=110mm) con-

tains contaminated water, an alumina support with TiO2coating andan air diffuser. The irradiance after theplexiglass

wall was about 22.76W/m2. The dissolved oxygen reached

a value of 8mg O2/L and only a slight decrease of the dis-

solved O2 (10%) was observed after 16h of irradiation. The

AO7 degradation under UV irradiation was monitored using

a UVvis spectrophotometer (UV-2401 PC Shimadzu). The

concentration of the model pollutant is calculated by the

calibration curve obtained from the absorbance of solutions

(max =485nm)atdifferent concentrations.Thephotocatalytic

activity of the TiO2 coatings elaborated in the three solgel

reactors was determined by studying the AO7 degradation

under UV irradiation. Firstly, alumina supports with or with-

out TiO2 coating were placed in a 10mg/L solution of AO7underdark conditions for 30min with bubbling air in order to

reach adsorption equilibrium. Then the UV-lamp was turned

on and at scheduled times, 1mL of sample was taken from

the reactor. The pH was the natural pH of the dye (7.2) and

Fig. 4 Scheme of the batch photocatalytic reactor.

no significant differencewasobservedbetween theinitial and

the final pH.

3. Governing equations and numericaldetails

Flow behavior in T-mixers was investigated by running CFD

simulations. Literature concerning nanoparticle precipitationreports that the fluid flow in a T-mixer is turbulent for

Reynoldsnumbers above 500 (Gradl et al., 2006). In this study,

the inlet velocity leads to a Reynolds number of around

2000 and therefore a turbulent fluid flow. The flow field

and the turbulence field were described using the standard

Reynolds-averageNavierStokes (RANS) approach and the k

turbulencemodel.Thismodel relies onseveralassumptionsin

particular that Reynoldsis high enough touse RANS approach

and that turbulence is in equilibrium in the boundary layer

meaning that production equals dissipation. These assump-

tions limit the accuracy of the model as in our case Reynolds

number is quite low. However, it was considered that the

limited accuracy is a fair trade-off for the amount of com-

putational resources saved compared with more complicated

turbulence models.

The problem is described in terms of a Reynolds-averaged

relativeconcentration cwhichisan inert scalarranging from0 to1 and isassumed tobe equal to1 inone feedstreamand to

0 in the other. The mixing at macro-scale was considered by

resolving the transport equation for steady-state conditions

that is:

UC [(D+ Dt)C] = 0 (3)

where D and Dt are the molecular and turbulent diffusion

coefficients respectively and the source term is null since the

mixture fraction is a non-reacting scalar. The turbulent dif-

fusioncoefficient canbe calculated usinga turbulent Schmidt

numberandtheBoussinesqhypothesis (Marchisio etal.,2006).

Dt=C k2Sct

(4)

where Cis a numerical constant equal to 0.09, Sct is the tur-

bulent Schmidtnumberequal to0.7,k is theturbulencekinetic

energy and the turbulence energy dissipation rate which is

computed from theCFD turbulencemodel.

Mixing at the micro-scale was characterized by estimat-

ing the spacial distribution of the local Reynoldsnumber, Rel,which uses the local turbulence level and is given by:

Rel=k(v)

(5)

where is the kinematic viscosity. k and are obtained from

theRANS model.

Mixing in the reactor was investigated by computing CFD

simulations using the finite element software Comsol mul-

tiphysics 4.2. Simulations in the turbulent flow regime were

run using the RANS approach and employing the k turbu-

lence model and wall functions for the near wall treatment.

3-D geometries corresponding to the three different T-mixers

(Fig. 2) were meshedwith tetrahedral elements generated by

the software Comsol. Wall functions were used to describe

the flow at the walls. The wall functions in Comsol are such

that the computational domain is assumed to start a distance


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Fig. 7 SEM micrographies of the alumina support with and without TiO2 coating. Top viewwithout TiO2 coating (a), top

view with TiO2 coating (b) and front viewwith TiO2 coating (c).

coatings were observed using SEM (Fig. 7) in order to examine

their morphology anddefects.

With all thesamples obtained, similar TiO2coatingswith a

homogeneous thickness of about 200nm were observed. TiO2completely enveloped grains composing the alumina support

(Fig. 7c). However, cracks appeared on the film surface. This

phenomenonwas also noticed by Tian et al. and is attributedto the removal of residual hydroxyl and organic groups dur-

ing the heating process (Tian et al., 2009). No difference was

observed between coating morphology obtained from sols

synthesized in the three T-mixers.

4.3. Photocatalytic activity ofthe TiO2 coatings

Fig. 8 shows the normalized AO7 concentration versus time

for the different coatings. It emerges that the degradation

of AO7 by photolysis is weak since only 20% of the dye was

bleached after 16h of irradiation. The presence of the alu-

mina sheet alone (without TiO2) does not change the AO7

degradation rate, thus it can be concluded that the alumina

support does not participate in the photodegradation. In the

presenceofsynthesizedTiO2coatings,theyieldof degradation

of AO7 ranges from 73% to 79% after 16h of irradiation. Con-

sequently, the decrease of AO7 concentration is mainly due

to the heterogeneous photocatalytic degradation. It appears

that the three degradation rates are very similar. This result

is consistent with the measurement of the thickness of the

TiO2 film for the three cases which shown a similar thickness

(200nm) andthe evaluationof thequantitiesof TiO2coatedon

thealumina.Indeed theTiO2filmwas dissolvedby anacid fol-

lowing the protocol established by Coronado et al. (2003). The

Fig. 8 AO7 concentration under UV irradiation: without

any support (a), with uncoated alumina support (b), with

supports coated with TiO2 elaborated in Ts (c), Tn (d) and Tb(e).

amountof TiO2coated ranged from4.4 to6.6mg. Such a small

difference in the mass of TiO2 could explain the very similar

observed kinetics. So the preparation of TiO2 nanoparticles

with three different T-mixers gives particles which present

the same photocatalytic activity. The evolution of the AO7

UVvisible spectrum during irradiation is shown in Fig. 9.

It appears that the visible chromophor (=485nm) stronglydecreases and corresponds to the breakdown oftheN N bond

or C N bond as mentioned by Konstantinou and Albanis

(2004) and Zhang et al. (1998). During the first step of AO7

oxidation by photocatalysis, the main organic by-products

identified were benzene sulphonic acid, sulphoanilic acid,

1,4-naphthoquinone, phtalic acid(Vinodgopalet al., 1996) qui-

nineand4-hydroxybenzene sulphonicacid (Bauer et al., 2001;

Stylidi et al., 2003). The last organic by-products before com-

plete mineralization were aliphatic acids. Since the majority

of the by-products contain a naphthalene group or a benzene

ring, which both strongly adsorb light at =254nm, it is con-

sistent tomonitor thevariationof theabsorbanceat =254nm

(A254nm) versus time. Indeed, thedecreaseofA254nmindicatesthe opening of the rings. Then, as suggested by Shinde et al.

(2009), a simplification could be made by correlating the rate

of decrease ofA254nmto the rate of mineralization:

d(A254nm)

dt d(TOC)

dt (7)

Fig. 10 presents the variation of absorbance of the visible

chromophor A486nmand A254nmduring photocatalysis of AO7.

Logically, AO7decolorationismorerapidat thebeginningthan

Fig. 9 Change of the AO7 absorption spectrum.

Experiment was carried out with an alumina support

coated with TiO2 elaborated in the solgel reactor with Ts.


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Fig. 10 Change of the absorbance of the solution for two

wavelengths: 254nm and 485nm during photocatalytic

reaction.

at the opening of thearomatic ring whichnecessitatesseveral

oxidation steps (Lhomme et al., 2005).However, after 24h of irradiation, the two absorbances,

A254nmandA486nm wereclose tozero indicating a concomitant

decoloration and mineralization. These results have already

been observed by other authors (Bauer et al., 2001; Lhomme

et al., 2006).

4.4. Hydrodynamics in T-mixers

Fig. 5 shows thatsol synthesizedwithTbhasa different behav-

ior than sol synthesized with Ts and Tn. The only difference

between the three experiments stands in themixer geometry

and could therefore be explained by differences in hydrody-

namics and characteristic times in themixer.

Thedetailedmechanisms ofmixingaredifficult to observe

experimentally dueboth to spatial limitations and to the very

short time scales involved. At this point, CFD can be used to

investigate thecharacteristics ofmixing in the chemical reac-

tors. Although a direct validation through comparison with

experimentaldata wouldbe preferred, it hasbeen proved that

CFD is a reliable tool that can be trusted in order to evaluate

trends and orders of magnitude for quantities such as flow

fieldandconcentrationgradient insuchgeometries(Marchisio

et al., 2006; Liu and Fox, 2005; Bothe et al., 2006).

Under perfect mixing conditions, the output local rela-

tive concentrationwould be c0/2=0.5. Concentration gradients

in a (x, y) plane at a z position can then be represented by

I=

(x,y)(c(x,y) (c0/2))2. Simulation results enable concentra-tion gradients to be plotted versus the z-axis (vertical pipe)

as shown in Fig. 11. I is an image of macro-scale segregation,

the smaller it is, the better mixing is. For all geometries, con-

centration gradients appear at the inlet and then disappear

progressively by convection and turbulent mixing along the

z-axis. It rapidly reachesa very low level andmacro-scale seg-

regation disappears in the first section from z=0to z=20mm

alongthe z-axisand thefluidleaving thereactorsis completely

mixed. This rapid mixing ismainly due to the vortex initiated

by eccentric arms (Fig. 12). The relative concentration in the

(x, y) plane sections along the z-axis is shown for the three

T-mixers in Fig. 13. As can be seen, from z=30mm, mixing

is completed and there is no longer any concentration gra-

dient and segregation. Before z=20mm, c ranges from 0.3to 0.7. Macro-mixing characteristics in the T-mixers seems

comparable.

Fig. 11 Concentration gradients along z-axis.

The present experimental results show that characteris-

tic induction time is equivalent when sols are synthesized

in Ts or Tn but shorter when synthesized in Tb (Fig. 5). In

addition, particles synthesized in Tb appear to be larger, lessstable and to agglomerate more rapidly. Mixing and particle

formation usually occur on a similar time-scale, as precipita-

tion is generally limited bymixing time-scale (Schwarzer and

Peukert, 2002). Thus, initial intensity of macro-mixing deter-

mines the initial level of supersaturation.This wasconfirmed

byWang et al. who performed direct numerical simulation of

the formation and growth of TiO2 nanoparticles in the two-

dimensional temporal mixing layer (Wang andGarrick, 2006).

Their numerical results show that macro-mixinghasa strong

influence on particle size as the largest particles are found in

the eddy core, while a high concentration of smaller particles

is found along the interface between reactant streams where

chemical reaction and nucleation takes place. In the presentstudy, mixing on a macro-scale seems the same in the three

mixers andis rapidlyeffective becauseof thevortexgenerated

in the upper region (Fig. 11). Then, one might suppose that

reaction and nucleation, which are known to be very rapid,

are initiated in the upper region ofT-mixers. According to

Marchisio et al., bettermixing favors nucleation with respect

to particle growth until a constant value is reached when the

characteristic mixing time becomes smaller than the typical

reaction time (Da


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Fig. 13 Relative concentration evolution in (x, y) planes at several z locations.

authors explain that further improvement inmixingdoes not

affect thefinalparticlesize distribution(Marchisio et al.,2009).

In this study, the situation is different as several geometries,

thus different hydrodynamic structures, were tested. The Da

number should be the same in the three T-mixers, as mixing

efficiencies are the same in the three mixers, and could not

explain results presented in Fig. 5.

With comparablemixing efficiency, the degree of supersa-

turation and thus the number of nuclei should be equivalentin the three T-mixers. The primary particles nucleated from

solutions are known to grow bymolecular addition or aggre-

gation with small subunits. This last phenomenon and the

next one, namely agglomeration, are encouraged by increas-

ing the number of collisions among suspended nanoscaled

particles. Indeed, particle growth and agglomeration can be

considered as transport-controlled for sufficient supersatura-

tion levels. In this way, shear forces in the turbulent flow-field

can have a significant effect. Indeed, high turbulence level,

after primary particles are formed, canhave a negative effect

on particle size as it enhances aggregation. Then, differences

observed in Fig. 5 could come from differences in hydrody-

namics after nucleation. Fig. 14 is a map of several relevantquantities regarding thehydrodynamiccharacterizationin the

central plane (Oyz): turbulence kinetic energy (k), turbulence

energydissipationrate() and localturbulenceReynolds num-

ber(Rel). Thisfigureconfirmsthathydrodynamics in theupper

region is the same for Tsand Tn. For these geometries, both

and k present high values in the vortex region and decrease

suddenly from z=6 mmwhere it reaches lower values. Rel is

around 9 in the middle part of the region and then stabilizes

around 7. Concerning hydrodynamics in Tb, the presence of

a baffle at z=11mm has a clear effect. It creates local turbu-

lence leading to bursts of and k and a rather homogeneous

Relaround 9. Thelocal Reynoldsnumber is an indicatorof the

turbulence level, it is theratio of the turbulencetime scale (k/)to the Kolmogorov time scale (/)1/2. Rel =1 thus corresponds

to a flow with only one time scale, that is to say laminar flow.

Here, there are differences in hydrodynamics in Tbcompared

with hydrodynamics in Ts and Tn which present less small-

scale turbulence. As some authors explained, the presence

of turbulence after themixing is completed, enhances shear-

induced diffusion (Scwarzer and Peukert, 2004). To obtain the

finest particles, solid formation should takes place in a per-

fectly mixed suspension and a slightly moving flow. Thus,

differences observed in Fig. 5 could be explained by a higher

level of turbulence after nucleation in Tb. On one hand it

increased the number of collisions between particles and on

theother hand, it could providemorewater around the nuclei(due tohighermixing rate)whichenhanced thedielectriccon-

stant around the nuclei and developed an environment for

the nuclei to aggregate making the median diameter larger

(Nagasawa et al., 2007).


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Fig. 14 , k and Rel in the three T-mixers in the reaction region from z=2mm (bottom) to z=18mm (top).

Thus, the present results suggest that small-scale convec-

tion after nucleation, meaning micro-mixing, could have an

effect on particle stability and mean size. Indeed, particles

synthesized in thehigher turbulencemixerare larger, lesssta-

bleand tend toagglomeratemore rapidly.Marchisioet al. have

investigated the effect of hydrodynamics on particle stability

with timewith a quitesimilar vortex reactor. Theyshowed for

a high Da number, the initial particle size is larger and par-

ticles tend to aggregate rapidly whereas when Da decreases,

initial size is smaller and particles are more stable over time

(Marchisio etal., 2009). In theircase, increasing theinletveloc-

ity leads to highermacro-mixing at themixer entrance. Then

the nucleation of very fine and numerous particles, which

are more stable, occurs. With their geometry, the influence of

turbulence after nucleation could not be tested. On the con-

trary, the present study enables the confirmation of theeffect

of shear-induceddiffusion.These experimental resultsunder-

line the importance of a well-tailored mixer which is not easy

to produce, as reaction time-scales are notwell-known.

Differences observed in Tb compared with Tn and Tssuggest that nucleation occurred around the first baffle (at

z=11mm) andthen growthproceeded after this baffle (for the

current inlet velocity). Then, knowledge of residence time in

this region would enable the typical particle formation time

to be estimated.

The particle tracing function of Comsol software was used

in order to evaluate the residence time in the reaction region.

Here, particle tracing is used as a tool to simply estimate an


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Fig. 15 Example of particle trajectory in Tb.

order of magnitude of residence times in the T-mixer and

not as a residence time distribution prediction tool which

requires several thousand particles and long computation

times. Hence, about 200massless particleswere injected fromdifferent locationsat thetwo inlet (y, z) planes(x=20, x=20).Fig. 15 represents an example of the trajectory foroneparticle

in Tb and Table 1 presents the synthesis of mean residence

time at the vortex outlet, z=2mm, tz=2, at z=11mm (firstbaffle location), tz=11, at z=20mm, tz=20, and atthemixer out-let z=200mm, tz=200, and the standard deviation for thesevalues. Depending on the T-mixer geometry, residence time

in the mixer is between 37.0 and 113.3ms. When particles

leave the reaction zone, residence time is between 13.6 and

15.7ms. Mean residence time at z=11mm inTbcould be used

to estimate an order of magnitude of the characteristic parti-

cle formation time.After entering theT-mixer, themean time

before molecules reach the vortex is 4.8ms and thus charac-teristic particle formation time is estimatedat around 6ms.

Although such a value is very important for the process of

scale-up, only a few quantitative values are available in the

Table 1 Mean residence time and standard deviationfor z=2, z=11mm, z=20mm and z=200mm for 200particles.

Ts Tb Tn

tz= 2 (ms) 5.9 5.9 5.9 (ms) 1.3 1.0 1.1

tz= 11 (ms) 11.0 11.0 10.1 (ms) 1.9 2.5 1.9

tz= 20 (ms) 15.7 13.6 15.4 (ms) 2.2 2.8 1.8

tz= 200 (ms) 113.3 99.8 37.1 (ms) 0.7 11.0 4.4

literature. Table 2 summarizes the characteristic particle for-

mation time-scale found in the literature for solgel synthesis.

The value of this typical time is very dependent on operating

conditions. The order ofmagnitude found in this studyseems

consistentwithvalues available in the literature.Nonetheless,

it canbenoted that thecharacteristic time found in this studyisnotin accordancewith thefirsthydrolysistimeofaboutsev-

eraltens ofmillisecondsgivenbyRivallinet al. (2005) in similar

operating conditions. Based on this latter value, the reaction

zone,andthus theparticle formationarea,was expectedafter

z=40mm, which justified the initial baffle and narrow pipe

location.

These results confirmthe rapidnessof the solgel reaction

which is limited by the mixing rate. Adequate mixers which

canachieveanefficientmixingwithina fewmillisecondsmust

be found. T-mixers like theonepresented could be optimized

for thevelocity range tested. Other static mixersmust be con-

sidered with well-located turbulence promoters. CFD can be

a reliable tool in order to calibrate appropriate mixers for aspecific nanoparticle precipitation application.

Precipitation is a complex phenomenon; the particle field

and its evolution reflect spatial variations of convection, dif-

fusion and chemical reaction. It is well-known that solgel

synthesis is based on thehydrolysis and polycondensation of

metal compoundprecursors and that these two types of reac-

tions occur simultaneously in a conventional solgel method,

i.e.polycondensationbegins before completehydrolyzation of

themetal compound. This leadstoa complicatedstatearound

the metal ion which depends on the synthesis parameters.

The way those parameters affect the process is still not clear.

Rare studies about the mixing effect during particle synthesis

have all underlined the importance of controlling mixing inorder to get the desired particle size distribution. Thepresent

study proves that the mixing quality might have an effect not

only on particle size but also on their stability.

Table 2 Estimation of typical particle formation time under various operating conditions.

Reference Typical particleformation time

(ms)

Operating conditions

Azouani et al. (2010) 1.05 TiO2, CTTIP= 0.146M, H=1.9, T=298K

Marchisio

etal.

(2006)

Precipitation of barium sulfate:

A+B solid7.7 ca= 100mol/m3, cb= 100mol/m3

1.7 ca= 500mol/m3, cb= 500mol/m3

3.2 ca= 100mol/m3, cb= 500mol/m3

Marchisio et al. (2009) 30 TiO2, CTTIP=1mol/l, H=2, hypochloric acid concentration: 0.25mol/l

Marchisio et al. (2008) 59 TiO2, CTTIP= 0.5mol/l,H=4, hypochloric acid concentration: 0.25mol/l

Present study 6 TiO2, CTTIP= 0.153mol/l, H=2.46


11/12


Thus, whensynthesizingnanoparticles, mixing, which is a

key parameterwhichmust be optimizedas a small difference

in the first particle formationstep, results in significant differ-

ences in particle size, particlenumberdensity andhydrolyzed

state. Particle distribution size and stability could be deter-

mined by both kinetics of solid formation and residence time

distribution of individual particles.

5. Conclusion

In this work, the role of hydrodynamics during production

of titanium dioxide nanoparticles via solgel reaction in T-

mixers was investigated. For the first time three different

T-mixer geometries were tested. This study was carried out

quantitatively by using three T-mixers with turbulence pro-

moters and thus different mixing characteristics. The main

novelty of this works is in the investigation of the effect of

hydrodynamics on both nanoparticle morphology and pho-

tocatalytic activity. In addition, this analysis is supported by

CFD simulations of the velocity and turbulent fields in three

T-mixers.Results show that mixing plays a different role according

to mixing-scale. All studies about nanoparticles precipitation

agree about formation steps: first a burst of particles is pro-

duced in a very short time then the sol changes through

aggregation. Themacro-mixing was comparable in the three

studied T-mixers. A high nucleation rate leads to small parti-

cles: on a large scale, the better the mixing is performed, the

smaller the created particles will be. Besides, micro-mixing

could affect the evolution of particles which will be less sta-

ble if shear induced diffusion is promoted during particle

growth. Our study showed, for the first time, that increasing

turbulences after the nucleation had an effect on the particle

stability since the induction time for Tb was shorter (1500 s)

than for Tsand Tn(2800 s).

The particle distribution was the same for the three T-

mixerswhichpresenteddifferent hydrodynamics in theoutlet

pipe but the same inlet Re number. Hence it was concluded

that theparticle size distributionwas probably more depend-

ent on the inlet Renumber than the T-mixer geometry.

The solgel TiO2 nanoparticles from the T-mixers were

used to coat alumina support. In all cases, a homogeneous

thin film of about 200nmwas obtained. The deposited mass

of TiO2was very similar.

The photocatalytic efficiency of TiO2coatingwas testedby

following thedegradation of AO7 in an aqueous solution. The

degradation andmineralizationkinetic rate were very close in

thethree cases. So thedifference in the hydrodynamics of the

T-mixers didnot directly influence the photocatalytic activity

of the TiO2coating.

In this study, a typical particle precipitation time was

estimated at around 6ms (CTTIP =0.153mol/L, H=2.46). This

contribution to the particle precipitation time characteriza-

tioncould helpduring future processscale-up. Indeed,mixing

must be considered as anoperating parameterduring synthe-

sis and so be actively used to produce the desired product:

a non-optimized mixing can greatly affect one of the main

advantages of TiO2, the relatively high surface area to vol-

ume ratio. CFDcalculationis anefficient tool, theuse ofwhich

could be of great benefitduring process scale-up so as to opti-

mize the design of mixing geometries. The results presented

here also provideevidence for theneed to performpopulation

balance calculations in parallel with particle size distribution

measurements in order to better understand and distinguish

the relative effect of macro and micro-mixing on the final

product.

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