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Physical Sciences Reviews. 2016; 20150018
Volkan Degirmenci1 / Evgeny V. Rebrov2
Design of catalytic micro trickle bed reactors
1 School of Engineering, University of Warwick, Coventry, CV4 7AL, UK, E-mail: v.degirmenci@warwick.ac.uk
2 School of Engineering, University of Warwick, Coventry, CV4 7AL, UK and Department of Biotechnology and Chemistry, Tver
State Technical University, A. Nikitina str., 22 Tver, 170026, Russia, E-mail: E.Rebrov@warwick.ac.uk
DOI: 10.1515/psr-2015-0018
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Nomenclature
CP
CFD
dP
dR
DL
DM
h
g
MTBR
k
kL
L
n
ΔP
q
RF
T∞
T
TBR
u
x
Greek Letters
εB
εL
εLd
εLs
εL,t
μ
η
ρ
Ω
λeff
βL
σ
Subscripts
L
G
p
Dimensionless numbers
Bo
Eö
Fr
Mo
Nu
Pe
Heat capacity
Computational fluid dynamics
Particle diameter
Reactor diameter
Axial dispersion coefficient
Molecular diffusion coefficient
Heat transfer coefficient
Gravity
Micro trickle bed reactor
Rate constant
Mass transfer coefficient
Reactor length
Reaction order
Pressure drop
Volumetric heat generation rate
Radio frequency
Ambient temperature
Temperature
Trickle bed reactor
Superficial velocity
Fraction
Bed porosity
Liquid holdup
Dynamic liquid holdup
Static liquid holdup
Total liquid holdup
Micron
Effectiveness factor
Density
Energy dissipation factor
Effective conductivity of the reactor bed
Liquid saturation
Surface tension
Liquid
Gas
Particle
Bodenstein number (uL/DL )
Eötvös number ((ρ − ρf )L2 /σ)
Froude number (u2 /gL)
Morton number (gμ4 Δρ/ρ2 σ 3 )
Nusselt number (hL/λ)
Peclet number (uL/DL )
Evgeny V. Rebrov is the corresponding author.
© 2016 by Walter de Gruyter Berlin/Boston.
This content is free.
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Pr
Re
Sc
We
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Prandtl number (ν/α)
Reynolds number (uLρ/μ)
Schimdt number (ν/DM )
Weber number (ρu2 L/σ)
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1 Introduction
Gas-liquid-solid reactions can be performed in various types of multiphase reactors such as stirred slurry reactors, bubble columns, ejector loop reactors, fluidised bed reactors or trickle bed reactors. Slurry reactors could
be considered as an alternative to fixed bed reactors for highly exothermic reactions, because the high heat
capacity and possibly high thermal conductivity of liquids makes it easier to achieve uniform temperatures.
Besides, the small size of the catalyst particles often makes diffusional effects negligible. However, slurry reactors have various disadvantages. Retention and separation of catalyst particles in the reactor vessel poses great
operational challenges such as clogging in filters. Furthermore, solid loadings are limited in stirred slurry and
ejector loop reactors; therefore, their application is limited to fast reactions. Gas and liquid reactants can be fed
to a fixed bed reactor packed with solid catalyst particles either concurrently or counter currently. In concurrent feeding, the flow may be either downward or upward. Packed bed reactors with a concurrent gas-liquid
downward flow are called trickle bed reactors. Counter current operation is sometimes preferable for selective
removal of by-products, such as hydrogen sulphide removal in desulfurization processes. Upflow concurrent
packed bed reactors are called packed bubble column reactors. Bubble columns may handle solid loadings up
to 25–30 wt % and they offer excellent mass and heat transfer rates. However, there is a significant back mixing in these reactors, which results in lower selectivity in consecutive reactions. The advantage of down flow
trickle bed reactors with respect to an up flow bubble column is the fact that there is no limitation on the flow
rates imposed by flooding limits in TBRs. The flow rates are only limited by the available pressure head at the
inlet. Moreover, the liquid is much more evenly and thinly distributed as compared to bubble flow reactors.
Furthermore, for slow reactions that require high catalyst loadings, it is important to use trickle bed reactors.
These reactors can also be employed where direct contact between gas and a catalyst may benefit the overall
performance. Another important advantage of trickle bed reactors is their simplicity in operation at elevated
temperatures and/or pressures. Overall energy consumption is often lower as compared with other reactor
types, as the catalyst is not suspended in fluid as opposed to slurry, bubble column or stirred tank reactors.
Low axial dispersion can be achieved in trickle bed reactors as compared to other three-phase flow reactors,
therefore higher conversions and selectivities can be reached.
Trickle bed reactors are used in many chemical processes due to their advantages over slurry reactors such
as easy handling of catalysts and operation at elevated pressures. Traditionally, petrochemical industries use
TBRs for hydrocracking and hydrotreating; the fine chemical industries use them for hydrogenation, alkylation
and oxidation [1, 2]. In a typical TBR, gas and liquid flow concurrently downward over a packed solid bed of
catalyst. In some applications, such as desulfurization, a counter current operation is preferred where gas flows
upward and liquid downwards. In both operation modes, the reaction takes place between the dissolved gas
and the reactants in the liquid phase on the catalyst surface. Therefore, the mass and heat transfer limitations
dramatically affect the reactor’s performance. Several extensive reviews [1] and books on trickle bed reactors
have been published in the recent years [3].
The performance of trickle bed reactors depends on hydrodynamics, fluid phase mixing, interphase and
intraparticle heat and mass transfer rates, and reaction kinetics. In turn, the heat and mass transfer rates depend on particle shape and particle size distribution, wetting of catalyst particles and the mode of operation.
Conventional methods of design and optimization of trickle bed reactors often rely on empirical methods. The
conventional design methods usually provide only global descriptions. Averaged properties and empirically
evaluated model parameters are used in such models. These correlations may not be valid for larger scale reactors because hydrodynamics is different from that in laboratory reactors. These methods have limited applicability; engineering correlations often cannot be extended to different operational conditions. The uncertainties
of these models are related to lumped descriptions of processes taking place at different spatial and temporal
scales (from a molecular scale to macro scale). Therefore, CFD methods have often been employed in recent
studies for proper reactor design.
Transient reactor operation requires detailed knowledge of micro scale processes. Micro scale processes are
associated with a single particle and its surroundings. Key processes that occur at this scale are energy and mass
exchange between the phases. Analysis at this scale is performed using simulations in porous media. The micro
scale modelling could provide significant insight into reactor dynamics and may enhance the applicability of
macro-scale models.
Trickle bed reactor configurations can be classified into four types:
1. Conventional trickle bed reactors: these are comprised of randomly packed beds of catalyst particles;
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2. Micro trickle bed reactors comprising packed beds of microparticles: reactor functionality is similar to conventional trickle bed reactors; however, the particle size is several orders of magnitude smaller when compared to conventional reactors. These reactors have high surface-to-volume ratio; therefore, they provide
substantial enhancement in mass and heat transfer as compared to conventional reactors. They are useful
in controlling temperature in fast exothermic reactions, especially when the products are sensitive to high
temperatures [4]. The hydrodynamics in MTBR often make the scale-up or scale-down rather straightforward;
3. Semi-structured micro trickle bed reactors: these are comprised of non-randomly packed particles or catalysts coated on structured packing or metal foams. This structured packing requires a lower pressure drop
to operate. However, liquid flow distribution at the inlet is very crucial;
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4. Structured micro trickle bed reactors: in these reactors, the micro channels are patterned with arrays of
columns where the catalyst is coated. This uniform arrangement of pillars in the reactor channel mimics
the packed bed with the additional benefit of control in uniformly distributed packing.
Current and future emphasis on green routes for production of intermediates for fine chemicals and the pharmaceutical industry require an in-depth understanding of the underling physical phenomena to improve the
performance of novel concepts of trickle bed reactors, including micro trickle bed reactors (MTBR) and mesh
reactors, as those have many features characteristic to their size. It is therefore essential to clearly understand
the fundamentals of contacting fluid phases to realize the advantages of these types of reactors for existing and
emerging applications.
Flow regimes in TBR can vary from a bubble flow, pulsing flow, trickling and spray flow regime. In the
bubble flow regime, gas is dispersed in a continuous liquid. In a pulse flow regime, alternating gas-rich and
liquid-rich segments are prevalent in the reactor. In the trickle flow regime, a continuous gas phase and discontinuous liquid film exists. In a spray flow regime, liquid drops are dispersed in a continuous gas flow. In
a conventional TBR liquid, holdup is a major design parameter that defines the residence time of the reactant
in the liquid phase. The flow regime and the relative gas and liquid flow rates determine the liquid holdup.
We studied the hydrodynamics and the heat transfer of a MTBR [5]. The MTBR has a diameter of 26 mm with
a length of 86 mm packed with 110 micron catalyst particles. The liquid holdup was in the range of 0.88–0.90.
The residence time distribution showed that the gas flow rate does not affect the liquid holdup, dispersion and
mean residence time. This is a unique feature of micro trickle bed reactors.
Designing a reactor requires the precise knowledge of various parameters such as the reaction rate and
enthalpy, hydrodynamics and heat transfer properties of the reactor. The presence of hysteresis in pressure
drop, liquid holdup and wetting efficiency poses a challenge for the design of TBRs. Hysteresis is the difference
in pressure drop, liquid holdup and wetting efficiency between increasing and decreasing modes of operation.
Maiti et al. [6–8] reviewed the parameters controlling the hysteresis in TBRs which are start-up procedures,
cycling of flow, particle size, particle properties, flow ranges, column size and inlet liquid distribution. The
unique advantage of MTBRs is that the liquid holdup does not depend on gas flow rate and a zero dynamic
hold-up is observed. Therefore the mode of operation does not affect the hydrodynamics of the MTBR. In other
words, the hysteresis is not observed in MTBRs. High liquid holdup ensures the uniform wetting of the catalyst;
this simplifies the prediction of the mass transfer resistances to the catalyst particle.
For the gaseous reactants, the transport limitations occur due to the necessity that they must dissolve in a
liquid phase and reach the catalyst surface. The mass transfer limitations for the gaseous reactants affect the
reactor performance. In order to decrease this mass transport limitation, cyclic operation of a TBR could be
applied by alternating between different liquids at the reactor inlet. This will eventually induce a change in the
wetting properties of the catalyst and provide an ease of mass transfer for the gas phase reactants. Atta et al.
[9] recently reviewed the cyclic operation of trickle bed reactors. In gas limited reactions, partial wetting of the
catalyst is desired; this could be achieved by alternating the liquid phase without sacrificing the reactor performance due to liquid maldistribution. In liquid limited reactions, the maximum mass transfer performance can
be achieved in complete catalyst wetting. The periodic operation provides a pulse flow regime at lower flow
rates, decreasing the cost of reactor operations. Another advantage of the periodic operation is the possibility to
supress the side reactions by limiting the contact time of reactants/products. In MTBRs, the periodic operation
could be useful – especially to prevent hot spot formation, specifically for highly exothermic reactions. The periodic variation of the catalyst wetting properties minimizes the risk of hot spot formation. Besides, the relatively
slow mode of operation provides the necessary time for heat removal through conduction and convection. The
MTBR designed by Chatterjee et al. [5] uses an external magnetic field and magnetic particles as the heating
medium; this provides almost instantaneous heating of the catalyst. Such a reactor design could be utilized to
induce periodic operations of heating and cooling cycles of the catalyst itself by controlling the external magnetic field rather than the liquid flow of species at controlled periods. This will enable the decoupling of the
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hydrodynamics from the adsorption/desorption kinetics of the reactants and products. The prospects of this
type of reactor design are discussed in detail in Section 4.
In this chapter, the hydrodynamics, mass and heat transfer, and periodic operation of micro trickle bed
reactors have been discussed. Several examples of emerging applications of multiphase micro trickle bed reactors have been highlighted. It is hoped that this chapter will provide insight in advancing our understanding
of micro trickle bed reactors.
2 Hydrodynamics
Different flow regimes may exist with different contacting and mixing characteristics. Each flow regime corresponds to a specific gas-liquid interaction, thus having a great influence on parameters such as liquid holdup,
pressure drop and mass and heat transfer rates. The volumetric gas and liquid flow rates as well as catalyst wettability determine the boundaries of flow regimes. Therefore hydrodynamics need to be carefully addressed
for proper reactor design.
2.1 Flow regimes
Downward flow packed bed reactors, namely trickle bed reactors (TBR), allow for a variety of flow regimes. In
general, four distinct flow regimes exist in TBRs:
1. Trickle flow regime: this regime exists when both gas and liquid flow rates are relatively low. In this regime,
gas phase is continuous, and the liquid phase is dispersed. It is also known as a low interaction regime, since
the flow in one phase does not significantly affect the flow in the other phase;
2. Pulsed flow: a higher gas flow rate results in pulsed flow, where the interaction between the phases is also
higher;
3. Spray flow: for a given liquid flow rate, if the gas flow rate is relatively increased too much, spray flow will
be obtained;
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4. Bubble flow: in contrast to the spray flow, if the liquid throughput is relatively high in comparison to the
gas flow, the liquid phase is continuous and the gas phase is dispersed; this is the bubble flow.
Schematic representation of bubble flow, pulsing flow, trickling regime and spray flow are given in Figure 1
[6]. The knowledge of transition between flow regimes is critical to design TBRs. A flow map for trickle bed
reactors for foaming and non-foaming liquids was developed by Charpentier and Favier [10] and reported in
various text books [11, 12].
Various hydrodynamic correlations are summarized in extensive reviews of two-phase flow systems in
packed beds [1, 13], and the role of hydrodynamics on conventional trickle bed reactors was covered in extensive reviews [14–18]. The transition from trickle to pulse flow is generally characterized by a sharp increase
in the root mean square pressure fluctuation for a small increase in gas or liquid flow rate. At low gas velocities
(ReG < 400), the flow regimes change consecutively from trickle flow to pulse flow and from pulse flow to bubble flow by increasing the liquid flow rate. For high gas flow rates, the transition is in the order of wavy, spray,
pulse and bubble flow by increasing the liquid flow rate. Many correlations and models have been proposed in
recent years to predict the regime boundaries. However, none of them has been entirely successful. Larachi et al.
[19] systematically analyzed the prediction performances of all the transition models and correlations against
all the transition data published in the literature since 1964. It was seen that the use of available phenomenological and semi-theoretical models for predicting flow transition leads to unacceptable errors. Based on all this
information, Larachi et al. [19] recommended the use of a neural network correlation that turned out to be the
most general correlation for predicting the trickle-to-pulse flow transition.
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Figure 1: Schematic representations of flow regimes in trickle-bed reactors. Reprinted with permission from “Ind Eng
Chem Res 2006;45(15):5185–5198” [6].
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2.1.1 Micro trickle bed reactors
The trickle flow regime prevails at relatively low gas and liquid flow rates. The liquid flows as a laminar film
and/or in rivulets over the catalyst particles, while gas passes through the remaining void space. Trickle flow
regime exists at low liquid and moderate gas flow rates where liquid flows as film over catalyst particles. In
this regime, inertial forces are weaker compared to the interfacial forces, and liquid hold-up is controlled by
capillary pressure. The trickle flow regime region widens with a decrease in liquid viscosity and/or surface
tension. Heat and mass transfer rates are slower when compared to other possible flow regimes.
Transition from a trickle to pulse flow regime occurs with an increase in either the gas or liquid flow rate.
In the pulse flow regime, local flow paths for gas are blocked by liquid pockets, which results in the formation
of alternate gas and liquid-enriched zones. A pulse flow regime has advantages in terms of the utilization
of a catalyst bed and higher heat and mass transfer rates. However, the operating window of this regime is
relatively small and decreases as the particle diameter increases. The concept of flow passage blockage at large
liquid holdups is reported by several authors [20, 21]. This blockage generates disturbances that propagate and
grow with the length of the reactor. In other studies, the appearance of a pulse flow regime is thought to be
related to the instability that occurs in the liquid film due to the shear exerted by the gas phase [22, 23].
Several experimental methods were used to detect the transition line from a trickle to pulse flow regime. A
change in slope of measured pressure drop versus gas or liquid flow rate indicates the transition to the pulse
flow regime [24]. Another group of methods is based on the application of different on-line transducers and
imaging techniques.
Gas and liquid properties have significant effects on the transition boundary. Cyclohexane has a three times
lower surface tension than water. As a result, a transition to a pulse flow regime occurs at lower liquid flow
rates (Figure 2) [25]. The influence of gas viscosity and density on the transition boundary is relatively small
when compared to that of liquid.
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Figure 2: Effect of gas and liquid throughputs on trickle to pulse flow regime transition boundary. Reprinted from
“Chem. Eng. Sci., volume 55, Attou A, Ferschneider G., a two-fluid hydrodynamic model for the transition between
trickle and pulse flow in a cocurrent gas-liquid packed-bed reactor, 491–511” [25].
Higher liquid viscosity leads to an increase in liquid holdup and therefore earlier transition to the pulse
flow regime.
Faridkhou et al. [26] employed digital image analysis to characterize the two flow regimes, hysteresis, and
transition thereof. The effect of gas density on the onset of flow regime transition was studied by comparing
the curves for air-water and argon-water systems. In MTBRs, the low-to-high interaction flow regime transition
at a given liquid superficial velocity shifts toward higher gas superficial velocities the higher the pressures (or
the gas densities) are. This makes the trickle flow operating region wider at elevated pressures or with gases
with higher molecular weights. As stated by Attou et al. [25], an increase in gas density leads to a decrease in
inertial forces and therefore transition occurs at higher gas velocities.
Faridkhou et al. [27] developed a method to study RTD in a MTBR. They used pellets of two different sizes:
53–63 μm and 106–125 μm and co-current operation. Due to relatively high pressure gradients of 500–3000
kPa/m, they carefully densified the bed prior to the experiments. The gas and liquid phases were brought into
contact by a T-junction located upstream of the packed bed consisting of a coaxial arrangement. The liquid
flows through the inner tube while the gas flows within the annular area between liquid line and the outer
tube. To avoid flow instabilities within the bed, it is of importance that the contact between the two phases
takes place at the start of the packed bed. They used two point electrodes inserted into the reactor wall via
two holes. The authors experimentally confirmed theoretically predicted maximum liquid velocity in the high
porosity zone close to the wall. The solid holdup was 0.592 and 0.576 for the 53–63 μm and 106–125 μm pellet
beds, respectively. The liquid holdup was in the range 0.22–0.25 for the 53–63 μm pellet bed and this value was
by 10–15% higher than that for the 106–125 μm pellet bed at the same gas and liquid velocity.
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2.1.2 Semi-structured micro trickle bed reactors
Since more than a decade, various micro and milli reactor concepts have been developed for gas-liquid-solid
reactions. Many of these reactors are becoming a key technology for the industry to face market pressures and
match increased environmental considerations. Due to their high mass and heat transfer performances and the
intrinsically safe design inherent to microstructures, they allow isothermal operation under otherwise explosive conditions. Furthermore, the small material inventory reduces the costs optimization of catalyst and/or
operating conditions that often decrease time to the market. These reactors have been applied in kinetic studies
of highly exothermic fast reactions, catalyst screening and process optimization.
Structured packings have the advantage that they are made to fit the dimensions of the reactor in which they
are placed and thus avoid the flow maldistribution due to a channelling or bypassing of the solids. Solid foam
packings represent a generation of materials combining relatively high specific surface area with low pressure
drop per unit height. This is largely due to the open-celled structure with very high voidages (up to 97 vol
%). The geometric surface areas of the solid foam packings increase as the voidage decreases (solids holdup
increasing) because the struts making up the unit cells increase in diameter. The ppi number (pore per linear
inch) of the solid foam packings is an independent parameter to describe the average cell size.
These packing materials commonly have a two-dimensional structure that redirects the liquid and gas flow
in planar directions. Several examples of structured packing materials are shown in Figure 3. In monoliths (including internally finned monoliths), the liquid and gas flows in separated channels, while in Mellapak, the
fluids flow down corrugated sheets of gauze stacked to form open channels between these sheets, and in Katapak some of the open channels are filled with spherical particles. In the development of these packings, the
aim was to increase their relatively low surface area, while maintaining a low pressure drop (high voidage) and
adequate contact between the flowing phases. Solid foams have been produced in different materials (metal,
ceramics, carbon, SiC, polymers, etc.). Banhart et al. [28] outlined the methods and procedures for producing
these and many other solid foams. In the particular field of chemical engineering, ceramic foams found application as heat exchangers, solar receivers, gas filters, packing columns or catalyst support. A review of this field
is proposed by Twigg et al. [29].
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Figure 3: Schematic representation of commonly available structured reactor packings. (a) Monolith, (b) internally finned
monolith, (c) Mellapak (Sulzer), (d) Katapak-S (Sulzer).
The surface area of random or structured packings can be enlarged by depositing catalytic coatings. However, due to most of the area being internal, it is not hydrodynamically accessible, and diffusion limitations
within the pores may still affect the transfer of components to the active catalyst. This mass transfer of components to the catalyst located on the solid support is essential for the operation of multiphase catalytic reactions.
A clear understanding of the corresponding mass transfer resistances is vital.
2.1.3 Structured micro trickle bed reactors
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A novel MTBR was developed where arrays of posts were built in each channel imitating the packing in conventional reactors [30] (Figure 4). These posts in the reactor channels provide a bed porosity of around 0.4 and
enhance the overall heat and mass transfer analogous to packing in conventional reactors.
Figure 4: Micro-structured catalyst supports prior to porous silicon formation. (a) Channel view. (b) Micron scale striations produced by the etch process. Reprinted with permission from “J. Microelectromechanical Syst. 2002;11(6): 709–17”
[30].
In a follow up study, Wada et al. reported a multichannel microreactor in which the channels comprise
uniformly distributed pillars [31]. The multi-channel microreactor was built as an integrated system with a
pressure drop section at the inlet (Figure 5). Flow regimes were studied by a reaction between oxygen and ethyl
acetate (Figure 6). At low liquid to gas flow rates and all gas flow rates, an annular flow was observed. At high
liquid to gas flow ratios, slug flow existed. At high gas and liquid flow rates, churn flow was observed with
rapidly undulating gas-liquid interface shapes.
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Figure 5: Multichannel microreactor and design of the pressure drop zone. (a) Relationship between structure and normalized pressure drop. The depth was measured from the surface of the Si wafer. The depths of manifold and reaction
channels were 300 μm. The pressure drop across the shallow channels (25 μm deep) dominates the total pressure drop.
(b) Fabricated structure. (c) Picture of microfabricated multichannel microreactor. Reprinted with permission from “Ind.
Eng. Chem. Res. 2006;45(24):8036–42” [31].
Figure 6: Gas-liquid flow regimes observed in the multichannel microreactor with posts: (a) slug flow (gas as dark area);
(b) churn flow (the interface fluctuates rapidly and liquid periodically spans the entire channel); (c) annular flow (gas
flows at the center of reactor). The conditions used in the oxidation experiments fall within the rectangle in dashed lines.
Reprinted with permission from “Ind. Eng. Chem. Res. 2006;45(24):8036–42” [31].
In a follow up study, an integrated MTBR with cooling was developed [32]. In order to achieve an overall
device capacity of 1 ml min−1 , the reactor consisted of 32 parallel channels with a width of 650 μm, a depth of
300 μm that were packed with 5000 posts with a diameter of 70 μm. The 8 : 1 width-to-packing diameter ratio
provided uniform flow distribution. The authors observed significant differences in transition lines between
different flow regimes as compared with the flow regime maps for open channels, such as the Baker coordinate
map [33], Charpentier-Favier coordinate map [10] and Talmor coordinate map [34]. They also compared the
data obtained from similar studies by Losey et al. [30] and Wada et al. [31]. In all cases, substantial differences
in the position of regime boundaries were observed as compared to those observed in conventional TBRs. In
the case of the Baker coordinate map, the annular regime was observed in microchannel systems at conditions
corresponding to a dispersed regime in conventional systems. This is the direct result of substantial differences
in the relative strength of capillary and gravity forces which dictate the flow regime [35]. More accurate hydrodynamic models are required for predicting flow regimes in a structured MTBR. In consecutive hydrogenation
reactions, the order of selectivity to the intermediate product follows the pattern of an increased mass trans-
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fer rate [36]. Therefore, a MTBR packed with small catalyst particles could over perform monolith and other
structured reactors.
Krishnamurthy et al. [37] investigated a two-phase flow across a bank of staggered circular micropillars,
100 μm long with a diameter of 100 μm and a pitch-to-diameter ratio of 1.5. The device was sealed from the
top with a Pyrex cover which allows flow visualization. Pressure measurements were performed with pressure
transducers placed at the inlet, exit, and in three locations along the channel length. A two phase gas-liquid
flow was obtained by passing the two phases through a micromixer, which was located upstream of the main
pillar array and was fabricated as a part of the device. The mixer has two inlets, one for the water and one for
the nitrogen, and a series of closely spaced 50 μm diameter circular pillars with a pitch-to-diameter ratio of 1.3
(Figure 7).
Figure 7: Schematic view of pillared microreactor. Reprinted with permission from “Phys. Fluids. 2007;19(4):043302” [37].
Four different flow patterns were observed, namely bubbly slug, gas-slug, bridge and annular flows. In a
follow up study, the authors concluded that no significant deviations were observed between water and ethanol
with respect to flow patterns [38]. However, the reduction of surface tension affected the flow pattern transition
lines. The authors modified constant B in Eq. (7) to account for the effect of surface tension on pressure drop.
The resulting correlation was able to predict the combined experimental data for ethanol to within ± 10 %.
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2.2 Pressure drop
The calculation of pressure drop in trickle bed reactors is an important design parameter. It depends on the particle packing characteristics and the fluid properties. Many earlier correlations are based on the data obtained
with non-spherical particles such as Raschig rings and cylinders. These correlations under-predict the pressure
drop for spherical particles. Therefore, it is important to use a proper correlation based on flow regime, particle
size and operating pressure and temperature.
2.2.1 Micro trickle bed reactors
Most correlations for pressure drop in MTBRs are expressed in terms of Re numbers of gas and liquid phases.
Kan et al. [39] proposed a correlation which is valid for trickle and pulse flow regimes at standard temperature
and pressure.
( Δ𝑃
)
𝐿
3
𝐿𝐺
( Δ𝑃
)
𝐿
= 0.024𝑑𝑝 𝜇𝐿 (
𝐺
𝑅𝑒 𝑊𝑒
𝜀𝐵
) ( 𝐺 𝐺)
1 − 𝜀𝐵
𝑅𝑒𝐿
−1/3
.
(1)
εB is the bed porosity, Re is the Reynolds number based on particle diameter, We is the Weber number. The
subscripts L and G denote liquid and gas phases, respectively. Several correlations are available for a wider
range of temperatures and pressures.
Another class of correlations uses modified Lockhart-Martinelli number (Eq. (2)) instead of a single phase
pressure drop.
𝑋𝐿 =
1
𝑈
𝜌
= 𝐿 (√ 𝐿 ) .
𝑋𝐺
𝑈𝐺
𝜌𝐺
(2)
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Ellman et al. [40] proposed a correlation for a wider range of operating pressures of 0.1–10 MPa for low interaction regime:
−1.2
2
2𝜌𝐺 𝑈𝐺 [200(𝑋𝐺 𝜉1 )
Δ𝑃
=
𝐿
𝑑𝑝
+ 85(𝑋𝐺 𝜉1 )
−0.5
]
,
(3)
where ζ 1 is defined as follows;
𝜉1 =
𝑅𝑒𝐿2
(0.001 + 𝑅𝑒𝐿1.5 )
.
(4)
The pressure drop along the reactor was not influenced by the gas flow rate [40]. The steady state residence
time and liquid hold up were not changed whether starting from a fully liquid filled or fully gas filled reactor.
This shows an important characteristic of MTBRs: the hysteresis is not applicable.
2.2.2 Semi-structured micro trickle bed reactors
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Mohammed et al. [41] studied pressure drop using three different liquid distributors, namely a single point
distributor, spray nozzle and multipoint distributor in a cylindrical column (polyvinyl chloride) with an internal
diameter of 100 mm and a height of 163 cm. The highest pressure drop was observed for the single point liquid
distributor due to a high degree of liquid maldistribution. They observed an accumulation of the liquid phase
in the center region in the upper part of the packing. A more uniform initial distribution of the liquid phase
was observed with the multipoint and spray nozzle distributors.
The authors observed higher static liquid holdups at higher foam pore density. Moreover, especially for solid
foams with high pore density (e.g. 25 and 30 ppi), the static liquid holdup increased with increasing superficial
flooding velocity. The authors observed different values of the static holdup at high superficial flooding velocity
in experiments with foams of high pore density. They concluded that the rapid filling of the small pores may
cause forming of immobile gas pockets that cannot be replaced by the liquid phase. The number of gas pockets
and their location, in turn, is of a random nature and possibly affected by local geometry-flow interactions.
They also used two different pre-wetting modes, which are defined as follows:
1. “Kan-liquid” mode: adjusting the flow rates to the desired gas and liquid superficial velocity after operating
the packed bed for 10 min in the high-interaction regime. This mode represents the upper hydrodynamic
boundary [42];
2. “Levec” mode: adjusting the flow rates to the desired gas and liquid superficial velocity after initial liquid flooding of the packed bed followed by draining the bed under gravity for 15 min according to Levec
et al. [43] until only the residual liquid holdup remained. This mode represents the lower hydrodynamic
boundary.
A distinctive pressure drop multiplicity was found for the single point distributor. A higher pressure drop
branch was found for the “Kan-liquid” pre-wetting mode, which can be described as rapid flooding. This mode
of operation leads to an increased static liquid holdup especially in the wall region in the upper part of the
column. They concluded that uniform initial liquid distribution could dampen the occurrence of hydrodynamic
multiplicity.
The authors developed correlations to predict the pressure drop and liquid holdup model in tubular reactors with solid foam packings. To account for the influence of different velocities and physical properties of the
fluids, the liquid Reynolds number, the liquid Galileo number and gas Weber number were applied. Furthermore, the correlations include geometric properties of the foam, such as window diameter, specific surface area
and porosity.
𝑑𝑝
𝑑𝐿
𝜌𝐿 𝑔
𝑏
𝑐
= 𝑎1 𝑅𝑒𝐿1 𝑅𝑒𝐿1 (𝑎𝑠 𝑑𝑤
𝑏
𝑑𝑝
1 − 𝜀 𝑑1
)
𝜀
𝑐2
2
1 − 𝜀 𝑑2
𝑅𝑒 𝑊𝑒
⎛
⎜ 𝑑𝐿 ⎞
⎟
)
𝜀𝐿 = 𝑎2 ( 𝐺 𝐿 ) 𝐺𝑎𝐿 ⎜
⎟ (
𝑅𝑒𝐿
𝜌 𝑔
𝜀
⎝ 𝐿 ⎠
10
(5)
(6)
DE GRUYTER
Degirmenci and Rebrov
The window diameter (dw ) was used as a characteristic linear dimension of the foams for the dimensionless
numbers. The coefficients and exponents of the correlations are listed in Table 1 and Table 2.
Table 1 Coefficients and exponents for pressure drop correlation (Eq. (5)).
Pre-wetting
Pore density,
ppi
Flow regime
a1
b1
c1
d1
Levec
Levec
Kan-liquid
Kan-liquid
10, 20
25
10, 20
25
Trickle
Pulse
Trickle
Pulse
21.56
0.21
0.03
0.06
0.15
−0.15
0.20
0.04
3.45
0.53
3.02
0.46
9.80
0.37
6.86
0.26
Table 2 Coefficients and exponents for total liquid holdup correlation (Eq. (6)).
Pre-wetting
Pore density,
ppi
Flow regime
a2
b2
c2
d2
Levec
Kan-liquid
10, 20
10, 20
Trickle
Trickle
2426
170.3
0.78
0.60
−0.18
−0.16
0.82
0.35
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In the co-current upflow configuration, Stemmet et al. [44–46] observed bubble and pulsing regimes in a 1 cm
width reactor filled with 10 ppi solid foam packing with a solid holdup of 7 %. The liquid holdup increases with
increasing liquid velocity and decreasing gas velocity, up to the maximum voidage of the solid foam packing.
(Figure 8 (a)). The liquid holdup increases as the ppi number of the solid foam increases due to higher capillary
pressures and higher static liquid holdup.
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Figure 8: (a) Liquid holdup in a 10 ppi solid foam packing in the co-current upflow configuration; (b) Liquid holdup in 10
and 40 ppi solid foam packings in the co-current downflow configuration. Reprinted from “Chem. Eng. Sci., volume 62,
Stemmet CP, Meeuwse M, van der Schaaf J, Kuster BFM, Schouten JC., gas–liquid mass transfer and axial dispersion in
solid foam packings, 5444–5450” [46].
Similar behavior was observed in the co-current downflow configuration; however, the absolute value of
the liquid holdup at low gas velocities was much lower and it did not exceed 0.4 (Figure 8 (b)).
As the liquid viscosity increases from 0.8 to 2.0 mPa/s, the liquid holdup slightly increases by 10–15 %. This
increase in liquid holdup is more pronounced in the 10 ppi solid foam packing due to the higher wetting of the
packing material, resulting in more effective drainage of the solid foam packing.
2.2.3 Structured micro trickle bed reactors
Krishnamurthy et al. [37] studied the pressure drop in for a two-phase flow across a bank of staggered circular
micropillars. An improved pressure drop model has been developed based on both the relevant scaling effects
observed in their study and adoption from previous studies:
Δ𝑝𝐿𝐺
1
𝐵 ⋅ 𝑅𝑒𝑑
= 6 02𝐿 = 1 +
+ 2 ,
Δ𝑝𝐿
𝑋𝑊
𝑋𝑊
(7)
where XW is the Martinelli parameter
𝑋𝑊 =
( Δ𝑃
)
Δ𝐿
𝐿,
Δ𝑃
( Δ𝐿 )
𝐺
(8)
and ( Δ𝑃
) is the frictional pressure gradient across the channel that would result if the liquid flowed through
Δ𝐿
𝐿
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the channel alone at a mass flow rate equal to: G · (1 − x) · A, and ( Δ𝑃
) is the frictional pressure gradient
Δ𝐿 𝐺
across the channel that would result if the gas flowed through the channel alone at a mass flow rate of G · x ·
A. Here, x is the quality of the two-phase flow and A is the minimum cross-sectional flow area, which for the
staggered pillar device with a transverse pitch, ST , pillar diameter, D, width, w, and height, H, is given by
𝐴 =
𝑆𝑇 − 𝐷
𝑤 ⋅ 𝐻.
𝑆𝑇
(9)
Constant B is an empirically defined constant (Table 3). 90 % of the data fall within ± 20 % of the model when
using a flow-pattern-dependent model, while 90 % of the data fall within ± 25 % of the predicted values while
using all of the data. Thus the model is less sensitive to flow pattern and more sensitive to the liquid Reynolds
number, as opposed to some conventional scale studies.
Table 3 The values of the constant B for different flow patterns and their respective accuracy.
Flow patterns
B
Mean average error, %
Bubbly/gas slug flow
Bridge flow
Annular flow
All the flow patterns
0.0152
0.0256
0.0860
0.0358
12
14
1.7
17.8
The multiphase flow of gas and liquid through packing materials can occur in three configurations: cocurrent upflow, downflow and counter-current flow. A plug flow regime can be realized in the counter-current
flow configuration allowing for high conversion and selectivity. However, flooding may limit the reactor productivity at high gas and liquid flow rates. The co-current upflow configuration demonstrates a large pressure
drop as compared to other configurations. This may cause a large concentration gradient of gas phase reactants
over the length of the reactor. The co-current downflow configuration could result in catalyst densification if
rather soft catalyst pellets are used.
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Degirmenci and Rebrov
2.3 Liquid holdup
The liquid volume fraction in trickle bed reactors is characterized by dynamic liquid holdup and static liquid holdup. The latter is proportional to the number of stagnant liquid pockets. The difference between these
two parameters often determines the effective liquid residence time distribution in trickle bed reactors. For
kinetically controlled reactions, the reaction rate are directly proportional to the extent of internal wetting of
particles.
Liquid holdup can be expressed in two ways:
1. total liquid holdup (εL ) defined as volume of liquid per reactor volume;
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2. liquid saturation (βL ) defined as a volume of liquid per void volume.
The liquid hold-up consists of two parts: dynamic liquid holdup (εLd ) and static liquid holdup (εLs ). The latter
is the volume of liquid which remains in the bed after draining the bed.
The liquid hold-up controls the liquid residence time and therefore reactant conversion. Marquez et al. [47]
studied the dispersion and holdup in MTBRs. They used two reactors with lengths of 7 and 97 cm and with
a diameter of 2 mm packed with particles of 106–125 μm. They observed a rather high liquid holdup between
0.65 and 0.85. Under these conditions, the particles were fully wetted, which is a beneficial effect for the catalytic applications. Besides, the gas flow rate affected neither the holdup nor the dispersion. No liquid flow was
observed from the bed when both gas and liquid flow was stopped simultaneously, suggesting zero dynamic
holdup. Thus the flow in MTBR is comparable with the packed beds and liquid flow only, and the operation
mode does not affect the hydrodynamics in MTBRs. High liquid holdup values translate into good wetting characteristics of catalysts and are highly desired for catalytic reactor applications. These values are considerably
higher as compared to those in industrial TBR [48].
A similar effect was observed by Yang et al. [49]. The use of diluent particles with a diameter of 300 μm
increased liquid holdup from 0.05 to 0.20. In beds diluted with small particles, the liquid is more easily retained
between the particles due to the increased liquid-solid contact and high capillary forces that lead to higher total
liquid hold up. A similar observation was reported by Kulkarni et al. [50]: the dynamic hold up almost doubled
and the wetting efficiency reached 90 %. Bej et al. [51] studied the effect of the diluting the catalyst bed with
non-porous inert particles on the performance of MTBR. By testing various sizes of non-porous silicon carbide
particles, it was determined that the 160–190 μm diameter particles packed in a relatively small MTBR with
a volume of 5 ml considerably increased the liquid hold up and provided a comparable reactor performance
with a larger (100 ml) TBR.
MTBRs are employed in fine chemicals and pharmaceutical synthesis. Al-Herz et al. [52] studied the hydrogenation of 1-heptyne in a trickle bed reactor over a 1 wt % Pd/Al2 O3 catalyst. Various solvents were screened
and 95 % selectivity was achieved in isopropanol. They observed that the liquid flow rate significantly affects
the reactor performance. The gas flow rate was 10 ml min−1 and the liquid flow rate was increased gradually
from 5 ml min−1 to 20 ml min−1 . The liquid hold up is very low and thus a partial wetting of the catalyst is
expected. The wetting efficiencies were calculated by the correlation of Lebigue et al. [53] which is given below:
),
𝑓 = 1 − (− 1.986𝐹𝑟𝐿0.139 𝑀𝑜0.0195
𝜀−1.55
𝐵
𝐿
(10)
where FrL (liquid Froude number), MoL (liquid Morton number) and εB (bed porosity) are representative of the
flow behaviour at the pellet scale, the physical properties of the fluid and the bed topology. In all liquid flow
rates the catalyst wetting efficiency was above 91 % and increasing up to 97 % with the highest liquid flow rate.
The total liquid holdup was calculated by correlation from Lange et al. [54];
0.33
𝑑
𝜀𝐿,𝑡 = 0.16 − ( 𝑅 )
𝑑𝑃
𝑅𝑒𝐿0.14 ,
(11)
where dP and dR are the particle diameter and reactor diameter respectively. Total liquid holdup changes from
0.28 to 0.34 with the increasing liquid flow rate. Partial catalyst wetting is expected in such low liquid holdups.
Higher liquid flow rate increased the hydrogenation rate and it was leveled off after 15 ml min−1 . A similar trend
was observed for the 1-heptene selectivity. Improper catalyst wetting could be the culprit for lower observed
reaction rates at lower flow rates, and the reaction may fall within the kinetic regime above the liquid flow rate
of 15 ml min−1 .
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2.4 Flow maldistribution and start-up effects
Liquid phase maldistribution is an important factor in the design, scale-up and operation of trickle-bed reactors [55]. Large catalyst particles, uneven catalyst loading and a non-uniform liquid inlet distribution enhance
channeling. For a longer reactor, a small variation in vertical orientation during installation of reactor could also
lead to liquid maldistribution. Liquid maldistribution is often related to non-complete wetting of the reactor
zone near the inlet. However, no quantitative information is available in the literature.
For smaller particles, larger surface to volume ratio leads to better liquid spreading [56]. Therefore inert fine
particle are used to improve flow distribution. Wu et al. [57] suggested the use of an inert fine particle along with
catalyst particles to improve wetting in the reactor bed. Use of spherical particles with a uniform particle size
can provide better control on local packing characteristics and therefore on local mixing and transport rates.
Van Herk et al. [58] performed a flow image analysis; it revealed that segregation of inert and catalyst pellets
leads to preferential pathways in the bed, where the zones with the smallest particles were filled with stagnant
liquid that was refreshed much less often. The initial conversion level and the deactivation rate were only reproducible when the segregation was prevented by matching free-fall velocities of particles during the filling
procedure of the reactor.
Fishwick et al. [59] compared several different reactor types in selective hydrogenation of 2-butyne-1,4-diol
into the corresponding alkene over a 0.5 wt % Pd/Al2 O3 catalyst: a stirred tank reactor; wall coated monoliths
with a diameter of 5 and 10 cm; a wall coated capillary microreactor with a 2 mm diameter and a 50 mm trickle
bed reactor packed with 6 mm pellets diluted with 200 μm silicon carbide. The highest initial reaction rate
was observed in the TBR. However, the selectivity to alkene measured at a 90 % conversion was 100 % in the
monolith, capillary and stirred tank reactors; however, it was only 93 % in the TBR. The poor selectivity was
due to the presence of stagnant zones in TBR broadening the residence time distribution. All reactors operated
closed to a plug flow behavior under the used flow conditions [36].
Marquez et al. [60] studied different start up procedures and step changes in flow in MTBRs. As the Bond
number was in the order of 10−2 to 10−3 , the up flow and down flow patterns were identical and hysteresis was
not observed. However, a little hysteresis was observed in the pressure drop during step changes in liquid (and
gas) flow rates. The characteristic time to reach a new steady state after start up or after a step change in gas or
liquid flow rates was the same. This time depends on the pressure drop and can exceed the liquid residence
time by a factor of 3.2. The volume of the gas feed section, which is the volume of the tubing and the connections
after the mass flow controller to the top of the bed, should be minimized to reduce the characteristic time to
reach the new steady state after a step change.
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2.5 Axial dispersion
Measurement of residence time distribution is the main method to determine axial dispersion. The axial dispersion model is used to describe all deviations from an ideal plug flow mode via a single parameter called
dispersion coefficient (DL ), which is often expressed in terms of the liquid phase Peclet number (Pe = uL/DL ).
The main factor contributing to the deviation from plug flow behavior is non-uniform porosity distribution
which could lead to channeling and short-circuiting. Non-uniform bed porosity can be induced by a wide particle size distribution or bed assembly methods resulting in non-uniform bed densification.
Mears [61] proposed a criterion to estimate the minimum reactor length required to avoid dispersion effects:
𝐶
𝐿
20𝑛
ln ( in ) ,
>
𝑃𝑒𝐿
𝐶out
𝑑𝑃
(12)
where n is the reaction order, and C is the concentration. It can be seen that dispersion effects can be more
pronounces at higher conversions or higher reaction orders, other parameters being the same.
At low liquid flow rates (ReL < 4), Fu et al. [62] showed that the dispersion depends on particle diameter
𝐵𝑜 = 0.00014(𝑑ℎ )
−0.75
(𝜀)−1 ,
(13)
where Bo is the Bodenstein number (Bo = uL/DL ).
MTBRs usually have short lengths that require accounting for axial dispersion. In conventional TBRs, the
particle size has the same order of magnitude with capillary length. Thus, the gravity is an important factor; it
should be taken into consideration during the reactor design. However, particle size in MTBRs is much smaller
than the capillary length that makes the effect of gravity negligible. The analysis of the multiphase flow becomes
the analysis of the perturbation from the single-phase flow. The single-phase dispersion in catalytic reactors
14
DE GRUYTER
Degirmenci and Rebrov
is well understood; the reactor models are developed based on the dispersion coefficient in which the Peclet
number appears in the dimensionless axial dispersion reactor model equation.
The Peclet number has two limits: at very low liquid velocities, the dispersion is dominated by molecular
diffusion where the Peclet number becomes uL/DM , where DM is the diffusion coefficient. The other limit is the
fully developed turbulent flow, where the particle Peclet number is around unity and independent of diffusion.
Marquez et al. [47, 60] studied the intermediate regime in a 2 mm inner diameter, 97 cm long MTBR packed
with 106–125 μm particles. The liquid was fed into the packed bed with a needle and the dispersion due to the
packing was analyzed by subtracting the spread observed in the empty reactor (Figure 9).
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Figure 9: Micropacked bed for stability and transient times studies. (A) 10 μl tracer injection loop. (B) Zoom showing
the way that gas and liquid are introduced in the bed. (C) Differential pressure transmitter. (D) Gas-liquid separator. (E)
Refractive-index cell. Reprinted with permission from “Ind. Eng. Chem. Res. 2010;49(3):1033–1040” [60].
Van Herk et al. [63] studied the scaling down of TBR for hydrodesulphurisation reactions. Their reactor
setup involved six parallel MTBRs with a diameter of 2 mm packed with particles of 100 μm. They studied the
residence time distributions with a pulse of 10 μl of colored dye. The inlet and outlet effects were eliminated by
performing the RTD experiments with and without the reactor. In the single–phase experiments, they found
an accurate agreement with the expected residence time within 5 % error. They claimed that the origin of the
error was due to small bubbles present in the space between the catalyst particles. The liquid residence time
was independent of the gas and the liquid flow rates. Thus it could be concluded that gravity plays little role
in the hydrodynamics of MTBRs.
In the MTBR at the Reynolds numbers around 1, the flow patterns were either bubble flow or segregated
flow. In the latter case, the gas flow could bypass the liquid resulting in low conversions. The Peclet numbers
were above 100 [63]. The high value of particle Peclet number implies the validity of a plug flow estimation
with short reactor lengths and an order of magnitudes of 10–20 particle diameters.
The dispersion ina MTBR and in a liquid-only flow fixed bed reactor turned out to be similar. Maiti et al. [8]
reported the effect of porosity on the hysteresis observed in TBRs. They found out that the hysteric behavior
of porous particles is much different from that of nonporous particles. While a hysteric behavior can expected
with porous microparticles, however the effect is too small to be observed for microparticles packed in MTBRs.
Kulkarni et al. found out that the use of 6 mm porous particles rather than the nonporous glass beads have
an impact on the residence time distribution in a laboratory-scale TBR with diameter of a 5 cm and 35 cm
length [50]. Higher dispersion was observed with the porous particles due to the diffusion of the tracer into
the catalyst pores. Moreover, the addition of 200 μm inert fine particles increased the Peclet number. The Peclet
number increased as the superficial liquid velocity increased.
Bodenstein numbers were reported in the range of 10–100 in a semistructured MTBR, which indicates the
importance of dispersion effects [32]. The Peclet number was studied in a MTBR with a diameter of 10 mm
and a 5 cm length packed with 150–250 μm catalyst particles at temperatures of 25–65 °C and 6.1 bar [64]. The
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DE GRUYTER
experiments were performed in step-response measurements with an inert tracer, which showed that the axial
dispersion should be taken into account.
Several authors reported that effect of gas flow rate on dispersion is almost negligible [50, 65, 66]. However
supercritical fluids behave like a gas rather than a fluid. Jin et al. [67] studied the hydrodynamics in a MTBR
with a diameter of 12.5 mm, a length of 110 cm under supercritical conditions. The reactor was filled with
particles in the range of 0.67–1.32 mm in diameter. N-hexane was utilized as the supercritical fluid at pressures
of 35–45 bar and temperatures between 140 and 280 °C. Nitrogen was used as the gas. It was observed that
the residence time distribution changes drastically with the gas flow rate. The mean residence time and the
dispersion decreased with the increasing gas flow rate under supercritical conditions.
3 Mass and heat transfer in micro trickle bed reactors
3.1 Mass transfer
Micro trickle bed reactors operate with a relatively small energy input as compared to other reactors as there is
no rigorous mixing mechanism present. Due to complete wetting, two types of mass transfer rate are relevant
for MTBR, i.e gas-liquid and liquid-solid.
3.1.1 Gas-liquid mass transfer
In a gas-liquid mass transfer process, the liquid side mass transfer rate is often a rate-limiting step. The gasliquid mass transfer rate depends on particle diameter, flow rates, fluid properties and flow regime. Reactor
geometry has virtually no effect on mass transfer rates.
The gas-liquid mass transfer rate increases with decreases in particle size. Several correlations have been
reported in literature. Some of them include pressure drop [68]
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𝑘𝐺𝐿 𝑎𝐺𝐿 = 0.0036(
𝑈𝐿 Δ𝑃
)
𝜀𝐿, 𝑑 𝐿
0.35
.
(14)
In this correlation, pressure drop should be known or estimated using other correlations. In another approach,
[69] expressed the gas-liquid mass transfer rate in terms of dimensionless numbers. They proposed an empirical
correlation for low interaction regime:
3.4
1/4
𝑘𝐺𝐿 𝑎𝐺𝐿 𝑑𝑘2
𝑎 𝑑
1/4
⎜ 𝑋𝐺
⎟ .
= 2 × 10−4 ⎛
𝑅𝑒𝐿1/5 𝑊𝑒𝐿1/5 𝑆𝑐𝐿1/2 ( 𝑣 𝑘 ) ⎞
𝐷𝐴𝐿
1−𝜀
⎝
⎠
(15)
The overall mass transfer coefficient for gases with limited solubility is typically controlled by liquid-side film
resistance. Therefore, the overall mass transfer coefficient value is close to that for the liquid-side mass transfer coefficient. The gas-liquid mass transfer coefficient (kL aGL ) depends on the interfacial area (aGL ), which for
structured packings is a function of the specific geometric surface area (aS ) and the liquid holdup. The physical
properties of the two phases, the lyophobicity of the solid and the solid holdup influence the value of kL aGL .
The gas-liquid surface area for gauze-type packings is correlated by Rocha et al. [70] as a function of the Froude
number:
𝑎𝐺𝐿
= 1 − 1.203 𝐹𝑟𝐿0.111 ,
𝑎𝑆
(16)
where aS is the specific surface area of the packing, and FrL is the liquid Froude number,
𝐹𝑟𝐿 =
𝜀2 𝑣𝐿2
.
𝑑𝑝 𝑔
(17)
Usually specific geometric surface area of the packing is in the order of 103 to 104 m2 m−3 .
In the co-current downflow configuration, the gas-liquid mass transfer coefficient increases as the liquid
velocity increases. The mass transfer is constant in the trickle flow regime with increasing gas velocity, while it
16
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Degirmenci and Rebrov
decreases with increasing ppi number. This can be explained by the increase in the strut size of the solid foam
packing decreasing ppi number. The larger the obstruction, the higher the degree of turbulence and hence an
increase in the refreshment of the liquid at the gas-liquid interface and enhanced gas-liquid mass transfer.
For multiphase systems, it is difficult to define the value of characteristic length as boundary layer analogies
with heat transfer are not applicable. Stemmet et al. [45] proposed the following correlation for a 10 ppi solid
foam packing
𝑘𝐿 𝑎𝐺𝐿 𝜀𝐿
𝑢 𝜌
= 3.68 − ( 𝐿 𝐿 )
𝐷𝐿
𝜇𝐿
1.16
𝑆𝑐𝐿0.5 .
(18)
The results for the gas-liquid mass transfer coefficient in the co-current upflow configuration were correlated
with a similar equation, where the influence of the gas velocity is included, similar to the correlations for packed
beds of spherical particles proposed in Fukushima and Kusaka [71]:
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𝑘𝐿 𝑎𝐺𝐿 𝜀𝐿
𝑢 𝐿 𝜌𝐿
= 311 ⋅ 𝑢0.44
)
𝐺 − ( 𝜇
𝐷𝐿
𝐿
0.92
𝑆𝑐𝐿0.5 .
(19)
Jensen et al. [72] studied the hydrogenation of cyclohexene as a model reaction with well-known kinetics in a
MTBR that contained 10 parallel channels with a width of 625 μm filled with catalyst pellets of 50–75 μm. Every
channel was equipped with individual gas and liquid inlets and filters at the outlet to prevent the catalyst from
leaking out. Splitting the inlet flow into multiple channels maintained the high surface-to-volume ratio and
allowed operation at a low pressure drop at 1.7 bar and at a liquid flow rate of 0.1 ml min−1 . A conventional
mass transfer analysis approach was applied including the resistances of gas absorption into the liquid and
diffusion of gas from the liquid to the catalyst and gas diffusion inside the catalyst pellet. The overall mass
transfer coefficient was in the range of 5–15 s−1 which is more than two orders of magnitude higher than the
trickle bed reactor systems packed with particles of 4–9 mm. In the presence of hydrogen excess at a pressure
of 6 bar, the reaction rate was limited by pore diffusion rather than by gas-liquid mass transfer [73].
In this example, better mass transfer rate comes with the expense of the relatively high pressure drop per
unit volume of the reactor which was characterized by the energy dissipation factor (Ω = ΔP · uL /L) which is the
power input per unit volume of the reactor. The MTBR requires 2–5 kW m−3 , which is an order of magnitude
higher as compared to laboratory scale TBR (0.01–0.2 kW m−3 ).
The external mass transfer resistance was studied in hydrogenation of o-nitro-anisole to o-anisidine in a
MFBR over a Pd/zeolite catalyst [74]. Different bed lengths were used to change the residence time. The authors
concluded that mass transfer is much faster than intrinsic kinetics. However, in case of a fast reaction, mass
transfer limitations could have a considerable impact on reactor performance. Metaxas et al. [75] employed a
laboratory TBR with a diameter of 25 mm and a length of 475 mm for catalytic hydrogenation of benzene over a
Ni/Al2 O3 catalyst particles with a size of 350 μm. Mass transfer rates for hydrogen and benzene were observed
on the gas and liquid sides. Gas-side mass transfer limitations were higher in the case of a dilution of catalyst
with fine particles of 250 μm [76].
3.1.2 Liquid-solid mass transfer
It is difficult to measure the mass transfer resistance (kL and a) in conventional TBR therefore mass transfer
correlations for the low interaction regime involve the wetting efficiency term as a correction factor [77]. Van
Houwelingen et al. [78] reported a method for the determination of the wetting efficiency and liquid-solid mass
transfer resistance. The approach involves the use of hydrogenation of linear-octenes and iso-octenes, which are
first order in terms of olefin concentration, i.e. liquid-limited reactions. The deviations from first-order behavior
were interpreted as a combined effect of resistance to mass transfer and incomplete wetting. Authors derived an
equation for the catalyst activity to fit the conversion data with the assumption that liquid-solid mass transfer
and the reaction rate are linearly dependent on wetting efficiency.
Losey et al. [72] proposed a mass transfer film model to compare the performance of microreactors and
conventional multiphase reactors in hydrogenation reactions (Eq. (20)):
𝑅 =
𝐶𝐻2
,
1 + 1 + 1
𝑘𝐿 𝑎𝑖
𝑘𝑐 𝑎𝑠
𝜂𝑘
(20)
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Degirmenci and Rebrov
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where, R is the overall reaction rate, CH2 is the saturated solubility of hydrogen in the liquid, kL ai is the external
mass transfer resistance for transport of gas due to absorption to liquid, kc as is the external mass transfer resistance for transport due to the diffusion of dissolved gas that forms bulk liquid on the surface of the catalyst,
and ηk is the internal mass transfer resistance for diffusion of the reactant inside of the porous catalyst, which is
given by the effectiveness factor η. They obtained the value of overall mass transfer coefficient kL a = 5−15 s−1 for
multiphase microreactors which are much larger than laboratory batch reactors for multiphase systems where
kL a = 0.01−0.08 s−1 . Durante et al. [79] employed a MTBR for sugar hydrogenation, namely L-arabinose to arabitol. The gas-liquid and liquid-solid mass transfer resistances were evaluated. The numerical analysis showed
a good agreement with the experimental values and theoretical predictions. It turned out that the gas-liquid
mass transfer resistance is more significant than the liquid-solid mass transfer resistance in their MTBR.
In the semi-structured trickle bed reactor comprised of metal foam loadings, the liquid side mass transfer
coefficient (kL ) is mainly determined by the slip velocity between the gas and liquid phases in the co-current
upflow configuration. The value of kL remains rather constant over the entire range of gas velocities for most
of the solid foam packing. As the ppi number of the solid foam increases, the value of kL decreases due to an
increased number of small restrictions to the flow that decrease the local velocity of the liquid. This reveals a
lower turbulence and hence a lower kL value. It may also be argued that the lower liquid side mass transfer
coefficient at high ppi numbers is a result of thinner walls, incapable of inducing large eddies in the liquid
phases, leading to a reduced level of turbulence in the flowing liquid. Characteristic values for kL were reported
to be in the range between 450 and 500 s−1 for a 10 ppi solid foam and between 50 and 150 s−1 for a 40 ppi solid
foam for liquid flow rate between 0.02 and 0.04 m s−1 [44].
Mohammed et al. [80] proposed a correlation that considers the effect of the gas and liquid superficial velocities, the physical properties of the fluids and characteristic geometric features of the foam material on the
liquid-slid mass transfer coefficient in co-current flow configuration:
6 0𝑆ℎ
1 − 𝜀 𝑑3
𝑏
𝑐
= 𝑎3 𝑅𝑒𝐿3 𝑅𝑒𝐺3 (𝑎𝑠 𝑑𝑤
) .
0.33
𝜀
𝑆𝑐
(21)
The values of the parameters are given in Table 4.
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Table 4 Coefficients and exponents for the liquid–solid mass transfer correlation (Eq. (21)).
Pre-wetting
Pore density,
ppi
Flow regime
a3
b3
c3
d3
Levec
Levec
10, 20
25
Trickle
Pulse
0.13
1.58
0.805
0.54
−0.89
−0.09
−1.34
0.06
Eq. (21) shows that higher liquid superficial velocity favors the liquid–solid mass transfer, while increasing
foam pore density lowers the transfer rate. In the co-current down flow configuration, the liquid-side mass
transfer coefficient depends on both the liquid velocity and the ppi number of the solid foam packings, but it
does not depend on the gas velocity [45]. The value of kL is four times higher for the 10 ppi solid foam packing
than for 40 ppi. This higher rate of mass transfer is a result of a higher local mixing within the film flowing
over the 10 ppi solid foam packing due to the larger strut thickness. Characteristic values for kL were reported
to be in the range between 10 and 30 s−1 for a 10 ppi solid foam. The value of kL for the co-current downflow
configuration is an order of magnitude lower than that for the co-current upflow configuration. Volumetric mass
transfer coefficients, kL aGL , are not a function of the ppi number of the solid foam packing, but increase with
increasing gas and liquid velocities. Experimentally found values of the volumetric mass transfer coefficients
were in the range of 0.1 to 1.3 s−1 [44]. These results indicated a high potential for application of structured
packings in MTBR as the obtained values were one order of magnitude higher than in conventional packed
bed reactors.
Tourvielille et al. [81] compared the performance of different gas-liquid-solid microreactors (Table 5). Wall
coated monolith present lowest mass transfer coefficient and low pressure drop. Packed microreactor provides
good mass transfer rates; however, it is accompanied with high pressure drop as a trade-off.
Table 5 Performances of various microreactors in gas-liquid-solid reactions.
Mesh reactor
[82]
18
Micro trickle bed reactor
[27, 72]
Monolith reactor
[83, 84]
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)
𝑎𝐺𝐿 (m2 m−3
liquid
)
𝑎𝐿𝑆 (m2 m−3
liquid
−1
kL (s at 298 K)
Δ𝑃 (kPa m−1 )
𝐿
𝜀𝐿 (m−3 m−3
reactor )
Degirmenci and Rebrov
2500
6500
1–2
—
< 0.02
—
1.5–3 × 10
2–6
500-3000
0.15–0.27
—
4
1500–2500
0.03–0.12
< 10
0.25–0.75
3.2 Heat transfer
Many reactions performed in MTBRs are often highly exothermic, and heat released in these reactions is transported by conduction and convection. This may lead to non-uniform temperature distribution in the reactor
bed. Local hot spots may form in the micro packed bed due to poor fluid distribution. It could also deactivate
the catalyst and reduce conversion and selectivity [85]. Besides, solid-liquid heat transfer limitations affect the
kinetics of reactions. Heat management inside the catalyst bed without causing catalyst deactivation and/or
by-product formation is a critical task in the design of a MTBR. A near isothermal temperature distribution can
be achieved by structuring catalyst and inert material zones, and removing heat via cooling. In some cases, the
gas or liquid flows can be recycled to reduce conversion per pass and control temperature. Correct calculation
of heat transfer rates is crucial for design and scale-up of MTBR.
The particle size in MTBR is usually very small, therefore no intraparticle temperature gradient inside the
catalyst particle is observed. Few studies in literature deal with particle-liquid heat transfer rates in trickle-bed
reactors. The main reason is probably the difficulty to find accurate experimental methods.
Heat transfer rates increase with both increasing gas and liquid flow rate. In the trickle flow regime, the
effect of the gas flow rate is rather weak, while the transition to pulsing flow results in an increase in the local
average heat transfer rates [86].
Boelhouwer et al. [87] proposed a correlation for the Nu number
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𝑁𝑢 = 0.4 + 0.1 𝑅𝑒0.8 𝑃𝑟0.33 ,
(22)
where the Re number is based on the linear liquid velocity and the particle diameter. Ruether et al. [88] presented
a correlation for particle-liquid mass transfer in which a power of 0.77 for the Re number was found.
Heidari et al. [89] have developed CFD models to describe micro and meso scale heat transfer in TBRs at the
gas-liquid interphase. Their micro scale model was a modified version of a double-slit [90] model implemented
to determine the interfacial heat transfer. The meso-scale model was solved numerically to determine the effect
of particle shape on an interfacial heat transfer. They calculated the interfacial Nusselt number as a function
of pressure drop, liquid holdup and wetting efficiency. The Nusselt number increased with an increase in gas
phase Reynolds and Prandtl numbers and decreased as the liquid phase Prandtl, Reynolds and Eötvös numbers
increased.
Fedorov et al. [91] investigated heat transfer in a heat sink with rectangular micro channels by developing
a numerical model for fluid flow and the heat conduction in a silicon substrate. They observed rather complex
heat flux patterns because of a strong coupling between convection in the fluid and conduction in the substrate.
They concluded that axial heat conduction in micro packed beds should be taken into account. Lee et al. [92]
experimentally studied the heat transfer in rectangular micro channels with a width from 194 to 534 μm and
the depth of five times the width in each case. In case of a 1D heat transfer model with constant temperature or
constant heat flux boundary conditions, the deviations from the 3D full conjugate analysis were 12.4 % and 7.1
%, respectively, demonstrating the importance of the use of numerical simulations, instead of 1D correlation.
Norton et al. [93] reported that between 60 to 80 % of the heat generated in microstructured reactors is lost
to the surroundings regardless of the insulation. These losses could only be avoided by application of special
insulation techniques, such as vacuum insulation. Therefore microreactors, even with thick insulating packaging, cannot be operated adiabatically; heat losses to the environment should be taken into account. A pseudohomogeneous two parameter model with an effective thermal conductivity (λeff ) and heat transfer coefficient
at the wall (hw ) could satisfactory describe heat transfer in a MTBR [94].
Dudas et al. [95] studied a highly exothermic reaction of hydrogenation of thymol on a Ni/Al2 O3 catalyst (1.2
mm) in a 40 mm internal diameter MTBR. The temperature profile was controlled with a pre-heater. A hot zone
was observed in the reactor. The position of the hot zone moved along the bed during start up due to different
catalyst wetting at low liquid flow rates. However, at a high liquid flow rate of 2.85 kg h−1 , a considerable
temperature gradient was observed along the reactor lengths. Due to the hot zone in the beginning of the
reactor bed, thermal decomposition of reaction products occurred with formation of several by-products.
To reduce temperature gradients, we proposed to use radio frequency (RF) heating instead of a preheater
[5]. The reactor configuration was composed of alternating catalyst and heating zones. The heat was generated
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inside the reactor by magnetic particles placed in an external RF field. The heating zones contained nickel
ferrite microparticles with a diameter of 110 μm. The catalytic zones were packed with catalyst particles of the
same size. The temperature profile was studied along the reactor length after fast heating of a part containing
magnetic particles (Figure 10). The effective thermal conductivity of the bed (λeff ) and convective heat transfer
coefficient for the heat losses to the environment (hext ) were calculated from a 1D transient heat transfer model
(Eq. (23)).
𝜕
𝜕𝑇
𝜕𝑇
(𝜆𝑒ff
) + 𝑞 + ℎext 𝑎 (𝑇∞ − 𝑇) = 𝜌𝐶𝑃
,
𝜕𝑧
𝜕𝑧
𝜕𝑡
(23)
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where a is the external wall area per unit of the reactor volume, Cp is the heat capacity and q is the volumetric
heat production rate. The conduction and convective losses contributed 30 and 70 % of the total energy losses,
respectively. The number and relative positions of heating zones within the reactor were optimized to obtain
a near-isothermal temperature profile (Figure 11). The position of heating zones depends on the heat losses to
the environment and heat generation rate. Three heating zones, positioned at specific locations inside the bed,
provided a temperature nonuniformity of 2 °C over a length of 50 mm.
Figure 10: Temperature of reactor bed along the axial direction as a function of time (symbols). Lines are the guide for
an eye. The interface between the heated and non-heated zones is located at x = 40 mm. Reprinted from “Chem. Eng. J.,
volume 243, Chatterjee S, Degirmenci V, Aiouache F, Rebrov EV. Design of a radio frequency heated isothermal microtrickle bed reactor, 225–33” [5].
Figure 11: Steady state fluid temperature along the axial direction of the micro trickle bed reactor for (a) single zone,
(b) two zone, and (c) three zone configuration. Reprinted from “Chem. Eng. J., volume 243, Chatterjee S, Degirmenci V,
Aiouache F, Rebrov E V. Design of a radio frequency heated isothermal micro-trickle bed reactor, 225–233” [5].
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3.3 Scale up
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For large-scale processing, multiple MTBR may be connected in series or in parallel. For a number of fine chemical syntheses that require large liquid residence time, TBR are operated in a semi-batch mode when the liquid
flow has complete recycle with a recycle to feed ratio of above 50.
Hickman et al. [96] scaled up a 14 inch TBR packed with 200–400 μm particles from the laboratory scale.
They observed a substantial loss in the efficiency due to inefficient catalyst wetting. By adjusting the superficial
liquid velocities for efficient catalyst wetting and after a thorough investigation on the catalyst deactivation, the
reactor was scaled up by a factor of 3 × 106 .
The hydrodynamics of the TBRs are very sensitive to the scale of the reactor, which brings about the challenge of transposing laboratory data into a commercial-sized reactor. The scale up methods relying on 1D
models are not reliable because they use pressure drop and liquid holdup; this changes within the reactor in
a complex fashion with the change in a reactor’s scale. Large bed diameters lead to liquid maldistribution.
Ranade et al. [97] proposed a general scale up approach (Figure 12) based on CFD models that account for the
porosity and thus consider liquid maldistribution and local hot spot formation in hydrodesulfurization and
hydrodearomatization reactions.
Figure 12: Schematic of Steps in Scale-up and Scale-down. Reprinted from “Chem. Eng. Sci., volume 62, Gunjal PR,
Ranade V V. Modeling of laboratory and commercial scale hydro-processing reactors using CFD, 5512–5526” [97].
Simulations were then carried out at temperatures between 320 and 380 °C, pressures of 200–800 bar, and
initial H2 S concentration between 1.0 and 2.5 vol %. In MTBRs, superficial gas-liquid velocities were much
lower; this reduced the overall performance and mass transfer rates due to increased dispersion. The predicted
results were compared with the experimental data. While the results were not conclusive, it was shown that
slight alteration in hydrodynamic parameters led to very different predictions in the reactor performance. Simulation showed that the sensitivity of conversion at high temperature and pressure is rather low; however, it
becomes very sensitive to any alteration in hydrodynamic parameters at low temperatures and high liquid flow
rates. Therefore, it is crucial to develop correlations under realistic operating conditions and reactor sizes that
adequately represent hydrodynamic and multi-scale transport processes in order to achieve predictive models
for scale up.
4 Periodic operation
Trickle bed reactors are widely used in industrial applications [98]. A great economic potential still exists for
improving their performance either by process intensification in MTBRs or by novel operational methods [99].
The latter includes, among others, the cyclic operation of trickle bed reactors [100]. This approach has been
presented in several reviews [9]. In the cyclic operation, the inlet flow is forced to contact with another liquid
stream periodically switched between a low level (base) and high level flow rate. In the extreme case, the minimum flow rate could be set at zero; this is known as on-off cycling. As a result, a variation of catalyst wetting
is achieved and the gas transport to the catalyst surface is improved due to partial wetting of catalyst particles.
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This results in higher reaction rates in gas phase limited reactions. For the liquid phase limited reactions, the
pulse flow results in higher reactor performance due to a higher catalyst wetting at the maximum flow rate.
Despite these advantages, periodic operation is still not a viable alternative to conventional steady-state TBR
operation in industrial applications due to a considerably higher investment and operational costs.
Predicting the performance of a periodically operated TBR by theoretical models remains a challenging
task. Lange et al. [101] observed higher time-average conversions as compared to steady-state operation in catalytic hydrogenation of alpha-methylstyrene. They developed a reactor model for the unsteady state operation
of TBRs. In this model, they used conventional correlations for liquid holdup, wetting efficiency and axial dispersion to determine mass transfer coefficient. However, their model failed to describe all of the main transient
behavior observed. Improved correlations for the liquid hold up and mass transfer rate, determined under
actual conditions, are required to improve the model.
The complexity of modeling of TBR hydrodynamics arouses from the presence of multiple hydrodynamic
states showing different pressure gradients and liquid hold ups for identical gas and liquid flow rates. This
poses a particular challenge for a successful modeling of reactor performance. Borren et al. [102] studied the
influence of periodic operation on TBR hydrodynamics and the gas-liquid mass transfer. They used a laboratory scale TBR with a diameter of 40 mm packed with a γ-Al2 O3 catalyst with pellets of 2.57 or 3.14 mm.
Saturated aqueous solutions were used as the fluid medium and volumetric gas-liquid transfer coefficient (kL a)
was calculated from the oxygen mass balance in the liquid phase.
They found out that the operating mode influenced the two-phase pressure drop and gas-liquid mass transfer coefficient, but it has little effect on the dynamic liquid hold up. Simulations also showed that a significant
increase in conversion could be achieved by the increase of gas-liquid mass transfer resistance for the gaslimited reactions. However, fluid modulation alters the liquid-solid mass transfer too, which should be carefully weighed for the overall performance of a TBR.
An advantage of periodic operation of TBRs is fully utilized when the reaction is either highly exothermic or
endothermic. The fast removal of products with an inert stream of fluid facilitates the heat removal and prevents
the further reactions of the products. Liu et al. [103] studied the hydrogenation of 2-ethylanthraquinoes on a
Pd/Al2 O3 catalyst in a periodically operated TBR where the liquid feed was controlled in an on-off mode.
The performance of the reactor was analyzed with an operating period of 40–480 s at 300 kPa. The conversion
increased by 8 and 4 % at 333 and 343 K respectively as compared to steady-state operation. In a follow up study
[104], the effect of the cycle period, pressure, temperature and time-average flow rate on the performance was
investigated and compared with the steady-state operation. Their results showed that under optimal operating
conditions, the conversion and the selectivity were improved by 21 and 12 % respectively.
Periodic temperature oscillations could result in desired surface coverages, at least for a part of the cycle and
the performance could be improved in terms of selectivity and catalyst stability. Habtu et al. [105] investigated
the effect of constant and modulated feed temperature on the MTBR performance in phenol oxidation over an
activated carbon with a particle size of 500 μm. The study was conducted at ReL in the range from 0.15 to 1.0 and
ReG from 0.35 to 4.5 in a 25 cm long reactor with a diameter of 9.3 mm. An unsteady state pseudo-homogeneous
heat transfer model was used in the absence of chemical reaction. The overall heat transfer coefficient increased
from 1.25 to 2.5 W m−2 K−1 with an increase in pressure and/or liquid flow rate. The heat transfer is particularly
sensitive to the value of the dynamic liquid hold up. The gas flow rate only marginally affected the heat transfer.
Other recent parametric studies for the understanding of temperature on the hydrodynamics during periodic
operation by flow modulation were performed by Aydin et al. [106, 107].
Under MTBR operating conditions, at high liquid hold up and low Reynolds numbers, the periodic modulation of inlet liquid flow rates becomes negligible in terms of hydrodynamics. Massa et al. [108] studied phenol
oxidation over a CuO/Al2 O3 catalyst in a periodically operated TBR in an on-off liquid flow mode. During the
dry cycle, external mass transport coefficients were increased, resulting in higher oxygen concentrations at the
catalyst surface which in turn favors total oxidation. While the phenol conversion remained virtually the same
under cyclic operation, but the product distribution changed towards total oxidation products.
5 Applications
Hotz et al. [109] developed a disk-shaped packed bed microreactor containing a Rh/ceria/zirconia catalyst for
butane-to-syngas processing at a temperature of 550 °C (Figure 13). This microreactor was a part a butane fuel
processor that can be integrated into a micro solid oxide fuel cell (SOFC) system. A small reactor volume, a
highly compact design and a low pressure drop are crucial requirements for the integration of a fuel processor
into an entire micro SOFC system. The disk-shaped packed bed reactor demonstrated a 6.5 times lower pressure
drop compared to an equivalent tubular packed bed reactor at similar operating conditions.
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Figure 13: Schematic of the disk-shaped packed bed microreactor. Reprinted from “Chem. Eng. Sci., volume 63, Hotz N,
Osterwalder N, Stark WJ, Bieri NR, Poulikakos D. Disk-shaped packed bed micro-reactor for butane-to-syngas processing,
5193–5201” [109].
1 Micro trickle bed reactors
Conversion of biomass to fuels and chemicals has attracted great attention as one of the future technologies for
a sustainable the low carbon society [110]. Hydrogenation of biomass-derived molecules into sugar alcohols
is an important step for the production of value added chemicals and intermediates for the chemical industry
[111]. In the future, trickle bed reactors might be a choice for various reactions. Jeon et al. [112] described the
hydrogenation of C9 -aldehyde into C9 -alcohol over a supported Ni-MgO catalyst. Their reactor has a diameter
of 0.5 inch and a length of 80 cm. A selectivity of 90 % to C9 -alcohol was observed at full conversion at 130 °C
and 400 psi.
Kilpio et al. [113] investigated the hydrogenation of glucose into sorbitol in a MTBR (Figure 14).
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Figure 14: Hydrogenation of glucose to sorbitol.
Sorbitol is an alternative sweetener and a platform chemical for a wide variety of compounds. Their reactor
has a diameter of 10 mm and a length of 70 mm packed with a commercial Ru/C catalyst pellets of 100–250
μm or 330–500 μm in diameter. 90 % selectivity to sorbitol was obtained in the 90–130 °C range. The catalyst
deactivation was clearly pronounced, especially at the entrance region where the highest reactant concentration
was observed. They combined reaction kinetics and deactivation kinetics in a single model that agreed well with
the observed reaction behavior. The model is based on an axial dispersion model using temperature-dependent
kinetics and deactivation. Their simulations predicted no temperature gradient rise inside the particles. The
effectiveness factor was around 70 % due to internal diffusion limitations.
Xi et al. [114] used MTBRs with a diameter of 13 mm a length of 45 cm for a ruthenium-catalyzed hydrogenolysis of lactic acid (2-hydroxypropanoic acid) to propylene glycol (1,2-propanediol), which is an important reaction step for the biomass utilization (Figure 15). Lactic acid can be produced from renewable sources such
as carbohydrates derived from agricultural crops and waste biomass. Lactic acid is very reactive due to its hydroxyl and carboxyl functional groups and it can be converted into various chemicals through polymerization,
esterification, dehydration and oxidation [115].
Figure 15: Hydrogenolysis of lactic acid into propylene glycol.
This reaction is usually performed in a batch reactor, because mass transfer limitations could be eliminated
via vigorous agitation. The MTBR was packed with catalyst particles and inert glass beads of the size 200 μm
and operated at a liquid flow rate of 100 ml h−1 . The translation of a batch protocol to a MTBR demonstrated
similar values for the reaction rate of 4.9 × 10−4 kmol m−3 cat s−1 when the both reactors operated in the intrinsic kinetic regime. The MTBR approaches fully wetted behavior and essentially acts as a differential reactor.
A detailed model was developed for MTBR that accounts for interphase mass transfer, temperature gradients
and partial wetting of catalyst particles. However, the model predictions must be handled cautiously, since
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predicting fractional wetting and mass transport coefficients did not always match with the experimental observations.
Son et al. [116] employed a MTBR with a diameter of 16 mm and 200 mm length for the transesterification
of sunflower oil with methanol to produce biodiesel over a CaO catalyst with the size of 1–2 mm. The reactor allowed for a separation of the products and reactant (methanol) when it was operated in a semi batch
mode where the condensed products were collected in a reservoir attached to the bottom of the reactor and the
methanol was collected in a condenser at the exit. A 98 % yield of fatty acid methyl esters was achieved at 373
K with oil and methanol flow rates of 3.8 and 4.1 ml h−1 .
Glycerol is the side product of biodiesel production. The growing production of biodiesel as a renewable
source-based fuel leads to an increased amount of glycerol. The utilization of glycerol strongly affects the process economy. Brander et al. [117] employed a commercial MTBR (Vinci Technologies) to investigate various
possible glycerol reaction pathways such as oxidation over a Pt-Bi catalyst, aqueous phase reforming and hydrogenolysis over Ru/C and Ru/TiO2 catalysts. Glycerol is a highly functionalized molecule and thus a large
number of value added chemicals can be obtained from glycerol by a variety of chemical reactions (Figure 16).
Xi et al. [118] reported the hydrogenolysis of glycerol where a MTBR was used with a diameter of 12.5 mm
and 61 cm length in a similar study. A one dimensional, non-isothermal reactor model was developed based
on the kinetic model, intra particle mass transport; liquid-solid and gas-liquid mass transfer coefficients were
calculated using correlations for conventional reactors. They applied the reactor model to a large set of steady
state trickle bed reactor experiments at a variety of operating conditions to predict glycerol conversion. The
three kinetic constants were adjusted and all other constants and coefficients governing hydrodynamics and
mass/heat transfer in the model are taken straight from literature or textbook correlations. As a result, good
agreement was observed between the predicted and experimental results.
Figure 16: Transformations of glycerol into high value chemicals.
The conventional batch synthesis of 6-hydroxybuspirone, an important pharmaceutical product, suffers
from low process safety, difficulties in upscaling of cryogenic equipment and long reaction times. Therefore
a continuous process is highly desired. LaPorte et al. [119] successfully scaled up the process of formation of
6-hydroxybuspirone from buspirone, which includes enolization, oxidation and quench steps in a TBR (Figure
17). At first, the authors used a two stage CPC CYTOS microreactor that provided a 85–92 % conversion with a
residence time of 5 min corresponding to a 300 g of product per day. Then a pilot-plant TBR with four columns
was constructed. A yield of 83 % (41.4 kg) was obtained in steady state operation for 72 h. This time was limited
by the amount of the available feed solution and potentially can be extended.
Figure 17: Preparation of 6-hydroxybuspirone. Adapted from “Org. Process. Res. Dev. 2008;12(5): 956–966” [119].
Adipic acid is a commercially important intermediate for the production of nylon-6,6. The commercial processes include a two-step oxidation of cyclohexane that results in large amounts of N2 O, a major air pollutant
and greenhouse gas. The synthesis based on oxidation with hydrogen peroxide is considered a greener alternative. An adipic acid yield of 50 % in the direct oxidation of cyclohexene by hydrogen peroxide was reported
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Degirmenci and Rebrov
by Shang et al. [120] at 100 °C and a residence time of 20 min in a MTBR with a diameter of 10 mm and a length
of 20 cm packed with 212–300 μm inert glass beads.
Figure 18: One-step oxidative cleavage of cyclohexene to synthesize adipic acid.
Selective hydrogenation of α,β-unsaturated aldehydes, such as citral, leads to a wide range of fine chemical
intermediates. A simplified reaction scheme of successive citral hydrogenation is shown in Figure 19. Wörz
et al. [121] replaced a batch operation into a continuous process. They employed 1 wt % Pd/SiO2 and 5 wt
% Pd/Al2 O3 catalysts covered with ionic liquid layer ([BMIM][N(CN)2 ]), 1-butyl-3-methylimidazolium dicyanamide in a MTBR with a diameter of 16 mm packed with catalyst pellets of 300–350 μm [121]. The use
of ionic liquids enhanced the reaction selectivity towards citronellal to 100 % at 70 °C at 52 % conversion with
a liquid flow rate of 1 ml min−1 .
Figure 19: Consecutive reactions in citral hydrogenation.
Maki-Arvela et al. [73] employed MTBRs for the parallel screening of catalysts. They used six parallel reactors, each of which had the internal diameter of 10 mm packed with two different catalyst particle sizes of
63–90 μm and 150–200 μm. The model reaction used to observe the performance of the reactors was citral hydrogenation. They obtained excellent reproducibility.
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2 Semi-structured and structured trickle bed reactors
A semi-structured MTBR based on monolithic structures [122, 123], filled with catalyst particles of 0.8 mm in
diameter, was used in hydrogenation of alpha-methylstyrene over a Pd catalyst [124]. The monolith segments
had a square cross section of 10 × 10 mm2 , a length of 5.0 cm and contained 64 parallel flow channels with a
hydraulic diameter of 1 mm. The authors compared the semi-structured MTBR, a wall coated monolith and a
larger scale TBR. The monolithic reactor and semi-structured MTBR demonstrated reaction rates that were at
least two times higher than those achieved in the conventional TBR. Slug flow was the dominant flow regime
observed at the liquid and gas superficial velocities in the range of 0.02 to 0.2 m s−1 and 0.04 to 0.2 m s−1
respectively.
Van Herk et al. [58] studied the hydrogenation of biphenyl over a Pt-Pd/Al2 O3 catalyst in a MTBR with a
diameter of 2.2 mm and a length of 475 mm. They have used microfabricated beds where pillars in 100–150
μm diameter were uniformly distributed. Phosphite, amine, and olefin oxidation with ozone were studied in a
structured MTB and up to 100 % increase in selectivity was observed. [30, 31]
A structured MTBR was used for the production of singlet oxygen from chlorine gas and hydrogen peroxide
at different pressures, flow rates and chlorine mole fraction [32]. A singlet-delta oxygen yield of 78 % was
obtained at the optimal reactor performance, occurring at a gas flow rate of 75 ml min−1 and an outlet pressure
of 0.13 bar. A complete bottom-to-top modeling, design, construction and flow testing of a fully MTBR system
were developed.
6 Outlook
Two phase micro and meso scale packed bed reactors provide significant advantages of performing industrial
relevant reactions [125] due to high catalyst wetting, absence of hysteresis effects and avoiding hot spot formation by the fast removal of heat. High liquid hold ups are observed and gas flow rates hardly effect either
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the dispersion or the mean flow rate in MTBRs. This feature simplifies the reactor models as the hydrodynamics approach the plug flow behavior of single phase packed bed reactors. The catalyst particle sizes are
typically below 250 μm and the reactor diameters are below 30 mm. In recent years, much attention has been
placed on the use of MTBRs as platforms for testing the commercial catalysts in the laboratory scale and developing methods for obtaining reliable data for conventional size industrial reactors especially in the field of
hydrodesulphurization. MTBRs possess great potential in the pharmaceutical and fine chemicals industry as
they are offering greener processes. In future sustainable chemical industries, TBRs will play an increasingly
important role for the conversion of renewable feedstocks. The literature is limited, and more understanding is
necessary for scale up and process intensification of MTBRs combined with a holistic approach to the process
industry [126]. Reliable correlations for the parameter estimation are essential to develop predictive models
for scale up. The bottleneck for commercial application is the energy requirement per reactor volume for high
gas-liquid superficial velocities to keep high throughputs. Scaling up strategies need to be developed either in
axial dimensions or by multiplying the reactors in parallel; this could provide high throughputs required by
industrial-scale production.
Acknowledgment
This article is also available in: Saha, Catalytic Reactors. De Gruyter (2015), isbn 978-3-11-033296-4.
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