A review of recent advancements in the crystallization fouling of heat exchangers

Abstract

A wide range of industrial processes (i.e., evaporation and condensation in desalination process, steam power plant, solar plant, etc.) involve heat transfer among the fluids. During the process of evaporative and cooling heat transfer, undesirable materials from the fluids accumulate on the surfaces, which critically reduces the performance of heat exchangers and creates one of the biggest challenges in energy transfer. Though the various studies on prediction and removal of fouling was conducted by numerous scientists, this problem is still unresolved in industrial process and is responsible for huge environmental damage and economic losses. This investigation provides a comprehensive overview of crystallization fouling in heat exchangers. Various factors affecting the deposition of crystallization foulaning such as fluid temperature, flow velocity, surface material and roughness, concentration and boiling are systematically reviewed. Accuracy and uncertainty of different equipment and experimental studies are discussed. In addition, fouling modelling is comprehensively discussed from earlier fundamental model to recent computational fluid dynamic and artificial neural networks model. Furthermore, mitigation of fouling with off-line and online approaches are chronologically discussed. Finally, an overview from environmental and economic prospective of fouling in heat exchangers are discussed. The future directions for crystallization fouling in heat exchangers are emphasized, which will support the researchers and industries to retard fouling and achieve economic benefits.

Full text

Vol.:(0123456789)
1 3
Journal of Thermal Analysis and Calorimetry
https://doi.org/10.1007/s10973-023-12544-z
A review ofrecent advancements inthecrystallization fouling ofheat
exchangers
KaleemullahShaikh1,2· KaziMdSalimNewaz1,5· MohdNashrulMohdZubir1,6· KokHoeWong3·
WajahatAhmedKhan4· ShekhAbdullah1· MdShadabAlam1· LuvindranSugumaran1
Received: 8 April 2023 / Accepted: 27 August 2023
© Akadémiai Kiadó, Budapest, Hungary 2023
Abstract
A wide range of industrial processes (i.e., evaporation and condensation in desalination process, steam power plant, solar
plant, etc.) involve heat transfer among the fluids. Duringthe process of evaporative and cooling heat transfer, undesirable
materials from the fluids accumulate on the surfaces, which critically reduces the performance of heat exchangers and cre-
ates one of the biggest challenges in energy transfer. Though the various studies on prediction and removal of fouling was
conducted by numerous scientists, this problem is still unresolved in industrial process and is responsible for huge environ-
mental damage and economic losses. This investigation provides a comprehensive overview of crystallization fouling in
heat exchangers. Various factors affecting the deposition of crystallizationfoulaning such as fluid temperature, flow velocity,
surface material and roughness, concentration and boiling are systematically reviewed. Accuracy and uncertainty of different
equipment and experimental studies are discussed. In addition, fouling modelling is comprehensively discussed from earlier
fundamental model to recent computational fluid dynamic and artificial neural networks model. Furthermore, mitigation
of fouling with off-line and online approaches are chronologically discussed. Finally, an overview from environmental and
economic prospective of fouling in heat exchangers are discussed. The future directions for crystallization fouling in heat
exchangers are emphasized, which will support the researchers and industries to retard fouling and achieve economic benefits.
Keywords Heat exchanger· Fouling· Fouling mitigation· Fouling modelling· Environmental impacts· Economic
evaluation
List of symbols
A Surface area (m2)
C Concentration (gL−1)
D Diffusion coefficient (m2s−1)
Δ
E
TOT
12
Total interaction energy (J)
h Convection heat transfer coefficient
(Wm−2 K−1)
Km Fluid deposit mass transfer coefficient (ms−1)
Kr Rate of reaction (m4kg−1 s−1)
K′
s
Deposit solubility product
m Mass (kg)
ṁ Mass flow rate (kg s−1)
n Order of reaction
Q Heat (J)
R Thermal resistance (m2KW−1)
Ra Arithmetic mean aberration
Re Reynold number
Rz Average surface roughness depth (µm)
Sh Sherwood number
t Time (s)
T Temperature (K, °C)
* Kazi Md Salim Newaz
salimnewaz@um.edu.my
* Mohd Nashrul Mohd Zubir
nashrul@um.edu.my
1 Department ofMechanical Engineering, Faculty
ofEngineering, Universiti Malaya, 50603KualaLumpur,
Malaysia
2 Faculty ofEngineering, Balochistan University
ofInformation Technology, Engineering, andManagement
Sciences (BUITEMS), 87100 Airport Road Quetta,
Balochistan, Pakistan
3 Carbon Neutrality Research Group (CNRG), University
ofSouthampton Malaysia, 79100IskandarPuteri, Malaysia
4 Nanotechnology andCatalysis Research Centre
(NANOCAT), Institute forAdvanced Studies, University
ofMalaya, 50603KualaLumpur, Malaysia
5 Centre ofAdvanced Manufacturing andMaterial Processing
(AMMP), University ofMalaya, 50603KualaLumpur,
Malaysia
6 Centre forEnergy Sciences (CES), University ofMalaya,
50603KualaLumpur, Malaysia

K.Shaikh et al.
1 3
U Overall heat transfers coefficient (Wm−2 K−1)
v Velocity (ms−1)
Wa* Work of adhesion
x Thickness (m)
Greek symbols
ƛ Thermal Conductivity, Wm K−1
β Inverse of time constant, s−1
τ Shear stress, Nm−2
ρ Density, kg m−3
Subscription and superscription
* Asymptotic
b Bulk solution
c Clean
d Deposit
f Fouling
r Removal
sat Saturation
Abbreviations
ANN Artificial neural network
AEMF Altering electromagnetic field
ANNM Artificial neural network model
CFD Computational fluid dynamic
DTPA Diethylene triamine pentaacetate
EAF Electronic antifouling
EDM Electric discharge machining
EDTA Ethylenediaminetetraacetic acid
FFNN Feed-forward neural network
GDP Gross domestic product
GNP Gross national product
MWCNT Multi-walled carbon nanotubes
PTFE Polytetrafluoroethylene
SCMC Sodium carboxymethyl cellulose
SEM Scanning electron microscopy
SWRO Sea water reverse osmosis
US Ultrasonic
USD United States dollar
VG Vortex generator
XRD X-ray diffraction
Introduction
Fouling or formation of mineral scale is a process where
undesired dissolved minerals (dissolved in the cooling fluid)
are deposited on the surfaces of the heat exchangers [1].
It is a common problem in desalination plants, water heat
exchangers [2], process plants, steam producing units and
household equipment [3]. Fouling in heat exchangers is
a problem as it enhances pressure drop andcreates extra
hurdles in heat transmission, and encourages tube material
corrosion. These influences can gradually decrease the effi-
ciency of heat transfer, and after a certain time, it loses its
acceptable efficiency limit and imposes forced shutdown,
and finally, it reduces operating service life of the heat
exchangers. Thus, fouling is considered as a critical con-
straint in operation and design of heat transfer equipment
[4].
The fouling effect on heat transfer equipment is com-
monly explained through the additional thermal resistance
owing to fouling layer. Thus, the overall heat transfer coef-
ficient (U) of the fouled equipment is calculated by using
Eq.1 [5].
where A and h are the heat transfer area and the heat transfer
coefficient, respectively, of the heat transfer fluids. Rwall is
the thermal resistance of the wall separating the two heat
transfer fluids. Rf is the fouling resistance developed by the
crystals deposits, depending on the situations of the heat
exchanger, where the crystals can deposit on one or both
the sides of the wall as shown in Fig.1. The term Rf can be
defined as the difference between the inverse values of the
overall heat transfer coefficient before the fouling (Uo) and
after the fouling (Uf) occurred as shown in Eq.(2):
(1)
1
U
=
(
1
h
1
+Rf,1
)
A2
A
1
+RWall +1
h
2
+R
f,2
(2)
R
f=
1
U
f
−
1
U
o
Fig. 1 Schematic of fouling on
heat exchanger [5]COLD SIDE
HOT SIDE
(T↑)
COLD SIDE
(T↑)
(T↓)
HOT SIDE
(T↓)
Heat exchanger wall
Fouling layer (Inversely soluble salts)
Fouling layer (Normally soluble salts)
t >> 0

A review ofrecent advancements inthecrystallization fouling ofheat exchangers
1 3
If the value of U assumes constant throughout the area of
heat exchanger, the additional heat transfer surface area is
desired to attain the same performance as stated by Eq.(3).
Likewise, if the heat exchanger area assumed constant,
enhancement in temperature difference among the hot and
cold water stream is required to maintain the similar perfor-
mance of the heat exchanger (Eq.4).
If the parameters shown in Eqs.3 and 4 have not accom-
modated the adjustment of the fouling, then the decline in
performance of heat exchanger will appear and it could be
presented by Eq.5.
According to Bott [6], fouling can be categorized in six
types such as (i) crystallization fouling, (ii) corrosion foul-
ing, (iii) particulate fouling, (iv) chemical fouling, (v) solidi-
fication fouling and (vi) biofouling; among these six types
of fouling, crystallization fouling is responsible for more
than 25% of problems faced due to the fouling. Crystalliza-
tion fouling on heat transfer surfaces is commonly occurred
due to the accumulation of salts from insolubility, which
occurred from the degree of enhanced supersaturation, and
augmented temperature. It is reported that the process of
crystallization fouling phenomena can be separated into
three phases as shown in Fig.2, i.e., (i) induction phase, (ii)
roughness control phase and (iii) deposit growth phase. In
the induction period, stable nuclei formation and growth of
crystal appear on the heat transfer surface, while in rough-
ness control period the fouling resistance decreases because
(3)
Af
=A
o(
1+R
f
⋅U
o)
(4)
Δ
Tf=ΔTo
(
1+Rf⋅Uo
)
=ΔTo
U
o
U
f
(5)
Q
f=
Q
o
1+Rf
⋅
Uo
of the expansion in surface area comparative to smooth sur-
face [7, 8], whereas fouling growth period enhances the foul-
ing resistance against time owing to the formation of dense
fouling layer. Crystallization fouling process associates with
several fields, i.e., chemical kinetics, heat and mass transfer,
material science and so on [9].
Several scientists and industrialists from various field
have been challenged for this fouling issues. They observed
difficulties and complexities in fouling area [10–12]. The
purpose of this study is to provide the comprehensive over-
view of the recent advancement of the crystallization foul-
ing in heat exchangers and steps involving in this study
are mentioned in the flowchart shown in Fig.3. For this
purpose, the authors conducted this review with an overall
introduction of fouling and formation of crystals on the heat
exchanger surfaces. Different fouling phase and process were
comprehensively studied. Effects of numerous parameters on
fouling rate are elaborated from the crystallization point of
view; various effectual cleaning and mitigation strategies for
the reduction of fouling were systematically studied. Uncer-
tainty and accuracy of equipment used in different fouling
rigs were discussed. Fundamental model to recent CFD and
neural network model were explored, and finally, the impact
of fouling on environment and economic was reviewed.
Efforts were also made for some new interest in this field,
and some possible new research directions were elaborated.
This study will provide the benefits to the industrial stake
holders to enhance the efficiency of the heat exchangers uti-
lized in different industrial process applications and EPA to
control the emissions of the hazardous gasses.
Crystallization fouling
For experimental investigation, supersaturated inverse solu-
ble mineral salts solutions were prepared by the research-
ers to accelerate the deposition on heat exchanger surfaces
for the study of their deposition, formation, mechanism and
mitigation.
Through dissolving the mixture of calcium nitrate tet-
rahydrate (Ca (NO3)2·4H2O) and sodium sulphate (NaSO4)
powders in distilled water, artificial hard water of CaSO4 was
synthesized to perform the experiments. Equation(6) shows
the CaSO4 formation reaction [13, 14].
Likewise, CaCO3 solution was synthesized through the
reaction of dissolving calcium chloride (CaCl2) and sodium
bicarbonate (NaHCO3) in stochiometric ratios, and Eq.(7)
shows the reaction and formation of CaCO3 solution [13,
15].
(6)
Ca(NO3)2
⋅
4H2O+Na2SO4
→
CaSO4
⋅
2H2O+2NaNO3+2H2O
Fouling resistance/Rf
Time/t
Initiation phase
Deposit growth phase
Roughness
control phase
Saw-tooth rate
Asymptotic rate
Falling rate
Linear rate
Fig. 2 Different fouling phases and usual types of curves

K.Shaikh et al.
1 3
Similarly, for hard water solution of CaSO4 and CaCO3
composite, CaSO4 was prepared with the same reaction as
mentioned in Eq.6 while for perpetration of CaCO3, calcium
chloride (CaCl2·2H2O) and sodium bicarbonate (NaHCO3)
were dissolved to perform the reaction and produce the solu-
tion of CaCO3 as shown in Eq.8. After synthesizing CaSO4
and CaCO3, stoichiometric ratio of CaSO4 and CaCO3 solu-
tion was used for performing the experiments [16].
In the industries, high concentration of organic phosphate in
cooling tower is utilized to reduce the corrosion, and river
and lake water also accumulated organic phosphate from
agricultural runoff. This organic phosphate can easily be
oxidized with discrete oxidizers such as chlorine present in
the cooling water which reacts with the organic phosphate
and produces orthophosphate ion which gives rise to CaPO4
fouling on the surface of heat exchangers [17].
The impact of foulants removal and deposition on heat
exchanger surface was significantly noticed in the fouling
as shown in Fig.1. The fouling process in terms of foulant
deposition and removal can be presented through Eq.9 as
given by Kren and Seaton [18].
(7)
CaCl2+2NaHCO3
→
CaCO3+2NaCl +H2O+CO2
(8)
CaCl2
⋅
2H2O+2NaHCO3
→
CaCO3+2NaCl +4H2O+CO2
(9)
dm
f
dt
=

mf=

md−

m
r
where

mf,
md
and

mr
are the net deposition rate, deposition
rate, and removal rate, respectively. For the typical fouling
system, numerous removal (i.e., erosion, dissolution and
spalling) and multiple depositions (such as sedimentation
and crystallization) were predicted by researchers [19].
Both removal and deposition process occur simultaneously,
and it depends on various operating conditions such as sur-
face roughness, flow velocity and operating temperature. At
the interface of fouling, the reduction in the temperature is
noticed with the raise in deposits, that decline the temperature
further reduces the rate of deposition and produces a steady-
state slope [19].
Mathematical, foulant mass deposition rate per unit area
(

mf
) in terms of fouling factor (Rf), foulant density (ρf), thick-
ness of deposit layer (xf) and thermal conductivity of foulant
(ƛf) can be expressed using Eq.(10).
Crystallization fouling process
Fouling is a complicated phenomenon because of the
involvement of several numbers of variables. In terms of
the fundamentals, the fouling phenomena follow several pro-
cesses in growing deposition on the surface. Epstein [20]
divided fouling phenomena into five different categories
based on the most common fouling mechanisms: crystalliza-
tion fouling, particulate fouling, corrosion fouling, chemical
(10)
Crystalization fouling
in
heat exchangers
Process involves Factor affecting the
fouling Mittigation Modeling Cost impose
Intiation
Transpor t
Attachment
Removal
Ageing
Concerteration
pH
Pressure loss
Temperature
Flow velocity
Surface
condition
Design
Physical, Chemical, &
Mechanical treatent
AdditivesCFD Modeling
FundamentalEconomic loss
Environmentol loss
Nureal & hybrid
network odeling
surface treatment
Thermal and
electromagenetic
field
Offline
Boiling
Fig. 3 Flowchart of current study

A review ofrecent advancements inthecrystallization fouling ofheat exchangers
1 3
fouling and biofouling as shown in Fig.4. Here, the light
highlighted sections represent that the scientists have aver-
age understanding about the process in all the five fouling
mechanisms while the dark highlighted sections demonstrate
that the researchers have good or excellent understanding
about the processes in all the five fouling mechanisms,
whereas no highlighted sections represent that the research-
ers have poor understanding about the processes. The main
fouling process was subdivided into different stages such
as initiation, transport, deposition, removal and ageing [21,
22]. In this study, these five stages were discussed based on
crystallization fouling because the present study is focused
on review of crystallization fouling.
Initiation
The surfaces are conditioned during the initial period. At the
beginning of the fouling experiment, the induction period
was affected by the surface material, surface temperature,
coatings and surface roughness. Due to the increase in the
surface temperature and degree of supersaturation, induction
period decreases. With the deposit formation, the crystal-
lization nuclei appear in the induction period. This period
can last from few seconds to numerous weeks depending on
the chemical concentration, surface temperature, roughness,
fluid flow velocity, etc. The crystallization fouling could be
changed because of the decrease in induction period due
to the rise in the surface temperature [20]. The induction
period tends to reduce with the rise in roughness of surface.
Moreover, crystallization fouling is encouraged due to the
sites established by roughness on surface [21].
Transport
In transport, fouling substances in bulk fluid are transited
towards the heat exchanger surface through the boundary
layer as shown in Fig.5f. It depends on concentration dif-
ference among the bulk solution and surface fluid boundary
layer [22]. The foulants transport to the surface is usually
based on diffusion and convective mass transfer film theory,
and the mechanisms would be different for suspended par-
ticulates and crystallize foulants [25]. The surface deposition
flux can be expressed by Eq.(11).
where md is mass transfer convection coefficient, and Cb and
Cs are bulk solution concentration and concentration nearer
the surface of heat transfer, respectively. hd can be found
from Sherwood number (Sh = hd/d) which depends on geo-
metric and flow parameters.
Attachment
Once foulant transported, deposits stick with each other or
with the surface or they leave the surface to adhere at any
other place. Factors which can affect the adhesion are sur-
face shear force, surface energy, surface temperature and
composition of earlier deposited layer. Due to the electro-
magnetic forces, the salt ions arrive at the surface and adhere
to the surface for forming the nuclei. The formed nuclei
slowly raise with time and form fouling layer. So, for the
determination of attachment, forces acting on salt ion are
important as they approach to the surfaces. Properties of
deposits and surface (i.e., surface situation, size and density)
are the dominant phenomena of the attachment of deposits
[20, 21, 25].
Removal
Initially, in comparison with the deposition mechanism, the
removal mechanisms were poorly understood [18]; later
(11)
md
=h
d(
C
b
−C
s)
Fouling matrix
Fouling mechanism
Crystallization
Particulate
Chemical
Corrosion
Biological
Fouling process
Initiation
Transport
Deposition
Removal
Aging
Fig. 4 Epstein 5 × 5 matrix to characterize the fouling process, light
to dark shading present enhanced in level of understanding [20]
Fluid flow
Heat flow
Dissolution
Spalling Erosion
Fouling deposit
Heat transfer surface
(Sedimentation)
particles
(Crystallisation)
ions
Deposition Removal
+–
Fig. 5 Deposition and removal of crystallize foulant on heat
exchanger surface [26]

K.Shaikh et al.
1 3
scientists comprehended that the shear force among the
fluids and foulant deposition were responsible for removal
of foulants due to involvement of numerous factor such as
velocity gradient at surfaces, surface roughness and viscos-
ity of fluid. The fouling model commonly assumes that the
net deposition rate is the difference between the deposition
rate and the removal rate as shown in Eq.(9). Based on
Kern and Seaton model, the fouling curve can behave like
four different forms as per the removal rate such as linear,
falling, asymptotic and sawtooth as shown in Fig.2 [5, 13,
27, 28]. If the removal rate is constant or negligible, then the
linear fouling curve is obtained, and when the removal rate is
variable, sawtooth curve is formed. Similarly falling curve is
obtained from higher removal rate, whereas asymptotic foul-
ing is developed when the removal rate is equal to the depo-
sition rate. Shear forces at boundary between the fouling
deposit and fluid are accountable for removal. Shear forces
are determined through surface velocity gradient, surface
roughness and fluid viscosity. Surface removal is performed
by mechanism of erosion, spalling and dissolution as shown
in Fig.5 [21].
Ageing
Ageing of foulant deposits starts soon after the accumulation
on heat transfer surface [20]. Ageing quantitative data are
rarely reported because many fouling deposits required large
time scale to age [29, 30]. The process of ageing may include
the change in chemical structure or crystal, i.e., polymeri-
zation or dehydration [21, 25]. These changes particularly
at constant heat flux increase the temperature of deposits
and strengthen the foulant deposits with time. These altera-
tions during the ageing also change mechanical properties
of deposits. Mechanical strength of foulants can be altered
through the change in chemical composition of foulants by
chemical reaction [21].
Factors aecting thecrystallization fouling
rate
Fouling depends on numerous factors such as type of mineral
and itscomposition present in bulk solution, flow velocity,
pressure loss, temperature, pH, boiling and surface condi-
tion. These parameters are broadly explained below in detail:
Solution concentration
Fouling deposition expedites with the increase in the con-
centration of foulants in the solution. Figure6a depicts that
the deposition rate of CaSO4 at 3.6g L−1 concentration is
much higher than the deposition rate of CaSO4 at 3.0g L−1,
similarly, Fig.6b reveals that deposition rate of CaCO3 at
0.418g L−1 is greater than that at the 0.30g L−1 of CaCO3
concentration. Researchers also conducted the studies on
influence of fouling composition on heat exchanger surface
[31]. They examined the normal soluble salts (NaSO4 and
NaCl) characteristics as composite crystallization fouling in
double-pipe heat exchangers. Due to the common ion influ-
ence, NaSO4 is mainly deposited on heat transfer surface.
NaCl significantly influences the supersaturation of
NaSO4, while the increase in mass percentage of NaCl in
mixture solution gradually reduced the fouling thermal
resistance and prolonged theasymptotic thermal resistance.
Choi etal. [32] examined the CaSO4 crystallization foul-
ing in seawater reverse osmosis (SWRO) desalination and
observed similar influence of NaCl. The existence of NaCl
reduced the growth of CaSO4 crystals and permitted the for-
mation of larger crystals. Helalizadeh etal. [1] investigated
the effect of composite salts on crystallization fouling. Lin-
ear increase in fouling was noticed with the enhancement of
thermal resistance in the presence of mixture concentration
of CaSO4 and CaCO3 at 2g L−1 and 1g L−1, respectively,
while at 1g L−1 and 0.4g L−1 composition, a very little vari-
ation in fouling and thermal resistance was observed. Chong
and Sheikholelami [33] investigated the mixed crystalliza-
tion fouling of CaCO3 and CaSO4 and found that the addi-
tion of CaSO4 reduced the CaCO3 deposit strength. Due to
0
20
40
60
80
100
120
140
160
0100020003000400
05
000
Deposion/gm–2
Time/min
CaSO4 at 3.6 g/L
CaSO4 at 3.0 g/L
0
2
4
6
8
10
12
0500 1000 1500 2000 2500 3000 3500 4000 4500
Deposion/gm–2
Time/min
CaCO3 at 0.418 g/L CaCo3 at 0.3 g/L
(a)
(b)
Fig. 6 a Deposition of CaSO4 at two different supersaturated concen-
tration [29]. b Deposition of CaCO3 at two different supersaturated
concentration [28, 30]

A review ofrecent advancements inthecrystallization fouling ofheat exchangers
1 3
its stronger adherence, various research groups observed that
CaCO3 had a stronger effect on fouling than CaSO4. When
both the compounds were dissolved in water simultane-
ously, the deposit properties approximated to CaCO3. Song
etal. [16] conduct a study on CaSO4 and CaCO3 mix foul-
ing characteristics on plate heat exchanger surface. Results
of this study support the investigation [34] on composite
scale formation of CaSO4 and CaCO3 that reveals the pre-
cipitation of particles behaved as additional nucleation spots
that speed up the rate of deposition and increased fouling
[34]. However, CaCO3 becomes less adherent and CaCO3
solubility increased with the addition of CaSO4 [1]. This
study also observed that in comparison with CaCO3 fouling,
composite fouling of CaCO3 and CaSO4 produced a longer
asymptotic fouling period due to the increase in solubility
of composite fouling that cause greater average precipita-
tion on higher temperature than CaCO3 fouling alone. Fur-
thermore, the deposition rate produced by CaCO3 fouling
is higher than the composite fouling owing to the higher
adhesion of CaCO3 than the combined fouling. Moreover,
the relation between concentration of CaCO3 and asymp-
totic fouling period is inversed when the concentration of
CaCO3 increased, the asymptotic fouling period decreased
[16]. Similarly, Kromer etal., 2015, [35] investigated the
mixed salt formation and its mitigation of fouling in seawa-
ter falling tube evaporation desalination equipment. Study
indicated that Mg(OH)2 developed a layer on surface of cop-
per–nikel in the form of brucite. Even at a low evaporation
temperature, i.e., 50°C, magnesium-rich scale was formed
which supported the assumption of the study that the high
pH value at the solution–metal interface. Researchers also
found that once the surface was fully covered with mag-
nesium then the growth of magnesium layer stopped and
precipitation of CaCO3 in aragonite form started. They also
found an inverse relationship between the Mg2+ and CaCO3,
which means that with the increase of Mg2+, the CaCO3
concentration was decreased.
pH
In crystallization fouling, pH plays an important role and
effect of pH on fouling is not straightforward [4]. Research-
ers studied the effect of pH on the deposition of crystal-
lize foulant on heat exchangers surface. Höfling etal. [39]
studied the impact of pH on CaCO3 and CaSO4 composite
fouling deposition.
This depicts that at pH < 6 only CaSO4·2H2O was accu-
mulated on the surface of heat exchanger, while at pH 7.0
CaSO4·2H2O and CaCO3 (in aragonite and calcite form)
were deposited, whereas at pH 7.5 CaSO4·2H2O and CaCO3
(in aragonite form) and at 9.0 pH value CaSO4·2H2O and
CaCO3 (in vaterite form) were detected in X-ray diffraction.
Constant CaSO4 saturation at pH value between 4.0 and
10 was found as shown in Fig.7. Some researchers [1, 4]
reviewed the effect of pH on fouling deposition. Reduction in
fouling precipitation was found with the increase in the pH
value. For the consideration of polymorphism of CaCO3, pH
was most important factor. When 10 ≤ pH ≥ 12, it enhanced
the aragonite formation. At pH < 11 and low temperature
(about 7 ◦C), mostly pure calcite was formed, whereas pure
aragonite was formed at 58°C for pH < 10. However, CaSO4
is not significantly affected by pH and tends to precipitate
in various forms once the solution becomes supersaturated.
Augustin and Bohnet [40] studied the influence of pH on
CaCO3 fouling. To resist the corrosion, most of the heat
exchangers required pH > 6.0 and fouling resistance of
CaCO3 is also increased above the 6.0 pH value. The asymp-
totic fouling resistance increases with the pH values due to a
higher strength of the fouling layer caused by an increasing
crystal growth velocity for supersaturation. Similar study
for CaSO4 depicts fouling behaviour change below 4.0 pH
value.
Pressure loss
The quantification and detection of fouling mechanisms in
different industries depend on two crucial parameters: (1)
the pressure drop ∆p and (2) the fouling resistance Rf [41]
as shown in Fig.7. The first parameter illustrates the rise in
the pressure loss owing to the changing in surface rough-
ness and a decline in cross-sectional area. Therefore, the
pressure drop directly relates to the deposited mass which
blocks the flow passage. Figure8 shows that the time-related
fouling can be divided into various phases. During the early
initiation stage, the surface was preconditioned, and no
notable variation in pressure drop or thermal resistance was
evidenced. In the succeeding roughness-controlled stages,
the deposits began to form on the surface and raised the
pressure loss due to the higher roughness, and enhanced the
heat transfer [7]. Both stages together can be called as an
Fouling tendency
0
24 68 10 12 14
pH
Corrosive
Corrosive
Balanced
Balanced
Scaling
CaSO4
CaCO
3
Fig. 7 pH effects on CaSO4 and CaCO3 fouling [39, 40]

K.Shaikh et al.
1 3
induction stage. After induction stage, the layer growth stage
starts in which the deposits continuously develop on the sur-
face of heat exchanger, which raises the pressure loss, and
enhances the thermal resistance of heat exchanger. The sec-
ond parameter, the thermal resistance was earlier explained
in the introduction section.
Temperature
One of the most important parameters influencing the
fouling is temperature, i.e., bulk and surface temperature.
The salt's (such as CaCO3and CaSO4)solubility shows
an inverse solubility characteristicwith temperature,
i.e.,solubility decreases with the increase in the tempera-
ture. Hence, on heated surfaces, these salts tend to crystal-
ize and deposit, and additionally heterogeneous nucleation
mechanisms are also supporting salts deposition. In aque-
ous supersaturated solutions, CaCO3 is formed in poly-
morphs and strongly influenced by the temperature [31].
Thoughthe solubility of calcite is less, butthecalcite is
the most thermodynamically stable form of CaCO3 and
vaterite is the least stable form of CaCO3 [43]. Calcite
has hexagonal crystal form and commonly formed at room
temperature. Aragonite is belonging to orthorhombic sys-
tem and does not change to calcite when heated in dry air
and 400°C. Conversion rate of CaCO3 is increased with
the increase in the temperature; when CaCO3 contacted
with aragonite, conversion can take place at room tempera-
ture. Wang etal. [44] observed an opposite transformation
trend. In the existence of surface Zinc composite coat-
ing, CaCO3 fouling morphologies changed from calcite
to aragonite.
Due to least solubility, anhydrite is the most stable
crystal form of CaSO4 when higher temperature is con-
sidered. However, nucleation process of anhydrite is slow
[45]; therefore, crystals of gypsum are normally formed.
Gypsum in both the cases, before dehydration and after
rehydration, is commonly precipitated in the range of
40–98°C, where hemihydrate and anhydrite species are
possible. Inversely soluble salts are frequently noticed in
scaling investigation, where it demonstrates the enhanced
deposition rate with the higher inlet temperature of heat
exchangers as shown in Fig.9.
Figure8 demonstrates the results of studies conducted
by different researchers on effect of surface temperature
on fouling resistance, in which study conducted by Dong
etal. [46] shows that at 2.3 gL−1 CaSO4 concentration,
fouling resistance increased with the enhance of surface
temperature. At 3.4 gL−1, CaSO4 concentration initially
increased with the rise of surface temperature, but after
75°C fouling becomes asymptotic. Similarly, study con-
ducted by Atika etal. [47] shows at 0.4 gL−1 concentra-
tion of CaCO3 fouling resistance rise with the enhance in
surface temperature.
Flow velocity
The flow velocity has strong impact on fouling rate. Due to
the hydrodynamic effects such as surface shear and eddies
stress, flow velocity has direct impact on both removal
Thermal fouling resistance Rf [10–4 m2 KW–1
]
Pressure drop ∆p [bar]
0
Initiation
phase
Roughness
controlled phase
tini tind
Induction phase
Layer growth phase
Time
Rf
∆p0
∆p
Fig. 8 Schematic formation of thermal resistance and pressure drop
with respect to time [41, 42]
Fig. 9 Fouling resistance at
different surface temperatures
[46, 47]
– 0.0002
– 0.0001
0
0.0001
0.0002
0.0003
0.0004
0.0005
0.0006
55 60 65 70 75 80 85
90
Fouling resistance/m2 KW–1
Surface temperature/Ċ
CaSO4 at 2.3 g/L
CaCO3 at 0.4g/L
CaSO4 at 3.4 g/L

A review ofrecent advancements inthecrystallization fouling ofheat exchangers
1 3
and deposition rate. In contrast, it has indirect impacts on
the mass transfer coefficient, sticking ability and deposi-
tion strength. During the force convection heat transfer,
many studies on scale formation have been performed [4].
Results of these studies show that high velocity sometimes
accelerates the fouling [48] while in some cases it reduces
the deposition [49]. According to the study conducted by
Helalizadeh etal. [1], the fouling mechanism is clearly
diffusion-controlled at lower fluid velocity. However, foul-
ing process changed to reaction controlled at increasing
flow velocity. If the mass transfer in the fouling process is
not controlled, then the deposition rate remains independ-
ent of flow velocity if surface temperature stays constant.
Figure10a strengthens the statement of Hatch[48] that
higher flow velocity reduces the overall heat transfer coef-
ficient, while Fig.10b demonstratesthat with the increase
in the flow velocity the fouling resistance reduces [9, 36,
47], which supports the statement of Zhao and Chen [4]
thatfouling can directly affect the removal rate.
Surface condition
In recent years, surface material and its morphology has
enhanced the interest of researchers and is considered as
one of the important influencers in crystallization foul-
ing. Teng etal. [50] characterized the behaviour of vari-
ous surface materials for the study of CaCO3 crystalliza-
tion fouling using double-pipe heat exchanger. The results
illustrated the linear growth relationship among the rising
thermal conductivity of studied surface and foulant deposi-
tion. This investigation also supports the studies conducted
by other researchers, i.e., Wang etal.,[51] andCooper
etal., [52], where descending order of foulant deposits
wereobserved  i.e.,copper > aluminium > stainless steel.
Wang and Yang [53] observed that silicon carbide (SiC)
surface coating reduced the fouling deposition by 4 times
than that on stainless steel surface. If surface material
used is also prone to corrosion, then the enhanced foul-
ing can be observed [53]. This fouling effect can be criti-
cally reduced through the developing of oxide thin layers
on the metal surfaces that obstruct the additional corrosion.
Similar to corrosion, occurrence of organic layer also acts
Fig. 10 Effect of flow velocity
on a the overall heat transfer
coefficient [15], b fouling resist-
ance [9, 36, 47] as a function of
flow velocity
1000
1100
1200
1300
1400
1500
1600
1700
1800
1900
5000 6000 7000 8000 9000 10000 11000 12000 13000 14000 15000
Heat transfer co-efficient/Wm–2K–1
Reynold number/Re
T = 40 Ċ T = 50 Ċ T = 65 Ċ
0.0E + 00
2.0E – 04
4.0E – 04
6.0E – 04
8.0E – 04
1.0E – 03
1.2E – 03
00.2 0.40.6 0.
81
Fouling resistance/ Wm–2K–1
Flow velocity/ms
–1
Ataki et al., 2020
Grandos et al., 2020
Grandos et al.,2020
(a)
(b)

K.Shaikh et al.
1 3
as an accelerator of fouling layer [55]. Cooper etal.,[56]
revealed that fouling resistance in plate heat exchangers sig-
nificantly reduced due to turbulence produced through the
plate corrugation. Han etal. and Xu etal. [57, 58] observed
from numerical model that shorter distance between the vor-
tex generators (VGs) produces larger turbulence. When the
distance between VGs exceeds 55mm, the characteristics
found were similar to non-VGS. Hasan etal. [59] found that
asymptotic fouling resistance was brutally decreased due to
the use of multiple turbulence generators on the surface of
heat exchanger, which indicates great potential in getting the
trade-off benefit among the fouling mitigation, pressure drop
through VGs and improvement in heat transfer[60]. Hasan
etal. [61] also examined the fouling properties impact due
to the mechanical increment in surface for the attainment
of higher heat transfer rate. In double-pipe heat exchanger,
coil wire was used, which enhanced the turbulence near the
surface, and crucially obstructed the fouling and boosted
the heat transfer. Examination of CaSO4 fouling conditions
on shot-peened surfaces validated the observations of AL
Janabi and Malayeri[62]. In the presence of the shot peening
surface, the roughness enhanced, induction period reduced,
and initial fouling rate improved considerably. Furthermore,
short, peened surface deposits were resilient, thicker and
more equally structured. Under the fouling condition, porous
surfaces were also examined. Großerichterand Stichlmair,
and Zhao etal. [63, 64] investigation concluded that these
shot peening surfaces should not be utilized in applications
where intense fouling is expected owing to the accumulation
of severe deposits.
Roughness is a degree of the surface texture and can be
calculated through the vertical aberrations of real surface
to its ideal state. Surface roughness is generally defined by
numerous parameters, i.e., Rz (the average roughness depth)
and Ra (the arithmetic mean aberration) [65]. Heat transfer
effects due to surface roughness are well recognized and
are broadly used to enhance the various heating equipment
performance [3, 66, 67]. Two effects, which may contribute
in enhancement of heat transfer owing to roughness, are (i)
enhancement in turbulence near the wall and (ii) an addi-
tion of surface area comparative to smooth wall [7]. Lei
etal.,[70] recognized that surface texture has very strong
impact on size, distribution and growth rate of CaCO3 crys-
tal accompanied by enhancing the fouling rate. Yoon and
Lund [71] stated that surface roughness effect was not found
at Ra 0.08–0.60µm.
McGuire and Swartzel [72] demonstrate that surfaces
with Ra values of 0.41, 0.04, 1.93 and 2.31µm for rough,
polish stainless steel, aluminosilicate and polytetrafluoro-
ethylene (PTFE) coating, respectively, were not a factor
for fouling. Malayeri and Müller-steinhagen [73] also rec-
ognized that deposition of CaSO4 was severely affected
through the surface roughness level, and on rough surface,
higher fouling layer was found; hence, higher roughness
induced shorter induction periods.
Boiling/bubble formation
Crystallization fouling is more critical if boiling occur due to
bubbles formation process. The presence of bubbles reduces
the resistance of boundary layer, which makes easier for
salts to stick on heating surface [5, 74]. Moreover, bubbles
formed in boiling enhances shear stress due to the rise in
turbulence near the surface that leads to reduction in fouling
rate through suppression or removal [74]. Sometime fouling
process itself is a cause to transit in nucleate boiling due to
the surface temperature rises because of deposits formed as
indicated by Elhady and Malayeri [75]. They investigated
CaSO4 crystallization fouling impacts and perform numer-
ous experiments at constant heat flux circumstances and
illustrated enhance in surface temperature more than boiling
point due to the fouling leads bubbles nucleation. They also
found boiling occur after the induction period, where crys-
tallization fouling mechanism transfer from convective heat
transfer to subcooled boiling. Malayeri etal. and Rashidi
etal. [76, 77] reported that bottom pipe deposits in bundle
are usually dense and adherent. The enhancement in bubble
formation has tendency to increase the bundle shear force
and heat transfer rate on pipe surfaces and both reduced the
deposition rate. Haghshenasfard etal. [78] created a math-
ematical model for the prediction of CaSO4 fouling under
the subcooled boiling. They observed from the results that
surface temperature is enhanced with the increase in the
deposition rate. Due to the rise in the fluid velocity, deposi-
tion rate decreases and resistance in fouling is enhanced.
Peyghambarzadeh etal. [79] assessed the capabilities of
asymptotic model for the prediction of CaSO4 fouling dur-
ing the subcooled boiling. To predict the fouling occurrences
under the boiling circumstances, model has simplicity and
high accuracy; for the nucleate boiling fraction, model has
significant prediction capability. Nucleate boiling fraction
is a vital factor in fouling process under boiling situations
compared to other models. For example, Chen etal. [80]
developed model for the prediction of fouling during the
subcooled boiling but model cannot estimate nucleate boil-
ing fraction with high precision.
Figure11a demonstrates the transport mechanism and
development of microlayer on the surface of heat exchanger.
It is clearly predicted from the figure that during the bubble
growth, CaSO4 ions in microlayer remain trapped and water
evaporation causes it to become intensively supersaturated.
Figure11b shows the images of bubble departure as a func-
tion of heat flux at constant concentration of CaSO4 which
shows the direct relation between heat flux and thickness of
scale deposits.

A review ofrecent advancements inthecrystallization fouling ofheat exchangers
1 3
Accuracy anduncertainty ofequipment
andexperiments
Brace etal. [82] calculated the thermal effectiveness (ε) of
overall fouling impact on the plate heat exchanger; they did
analysis of error propagation using Eq.12 throughout the
experimental conditions, in which they assumed constant
properties of the materials (i.e., fluid density and specific
heat).
They also provided a list of equipment with their uncertainty;
for example, the fluid temperatures were measured by using
K-type thermocouples with the uncertainty of ± 1.5°C, the
volume flow rate was measured by an electromagnetic flow-
meter with the uncertainty of ± 1%, the electrical conductiv-
ity was monitored by an EC probe with the accuracy of 0.5%,
the salt mass concentration was measured with the effective-
ness of ± 0.56 mgL−1, the surface temperature was measured
by the infrared sensor with the accuracy of ± 2°C and the
thermal effectiveness (ε) was calculated by the specific equa-
tion which showed ± 4.42 to 5.23% uncertainty. Similarly,
Shaikh etal., [83] provided the equipment preciseness in
their study, such as they used heater setting temperature data
with the accuracy of ± 0.05°C, chiller temperature data with
the accuracy of 0.1°C, thermocouples with the precision
of ± 1.5°C, flowmeter with the measuring accuracy of ± 4%
(12)
u
(𝜀)2=

𝜕𝜀
𝜕T
h, in 2
u

Th, in

2+

𝜕𝜀
𝜕T
c, in 2
u

Tc, in

2+

𝜕𝜀
𝜕T
c, out 2
u

Tc, out

2+

𝜕𝜀
𝜕
m
c2
u


mc
2
and data logger with the precision of 10ms. Shengxian etal.
[84] utilized the technical standard from literature to analyse
the uncertainty of the acquired test data.
Fouling mitigation
Crystallization fouling provides serious negative impact on
the heat transfer equipment, so the efficient cleaning or miti-
gation approaches are required to maintain appropriate capa-
bilities of equipment during its lifespan. Figure12 shows
the several methods to deal with fouling in heat exchang-
ers, from initial design to off-line cleaning. The selection
of these approaches usually depends on the heat exchanger
material, type, fouling mechanism, fouling severity, induced
cost, desired results and operating conditions [85]. This
study illustrates six fouling mitigation methods as mentioned
in the following subsections.
Mitigation offouling duringthedesign ofheat
exchanger
If possible, fouling mitigation is preferred to adopt in the
design process [86] while for efficacy of heat exchangers
the fouling mitigation and cleaning approaches are also
Salt solution Bubble departure
Evaporation
Diffusion
Crystallization
Tr iple
contact line
Heat flux/q′′
Heat flux/q′′
L
(a)
(b) Smooth hydrophilic surface
Fig. 11 a Schematic of bubble formation and transport mechanisms b bubble departure at variable heat flux for CaSO4 solution [81]

K.Shaikh et al.
1 3
added. Field engineers and the engineering science data
unit combinedly published design guidelines with these
fouling processes for the assistance of manufacturers, as
described by Pug etal. [27, 87]. The publications focus on
bulk water fouling and illustrate the most frequently foul-
ing mechanism, proposed range of operating values and
influencing parameters for fouling. Procedures for selec-
tion of material, cleaning and mitigation of fouling are
also given. Commonly recommended guidelines include
construction of heat exchanger from the suitable materials
and reduction of heat exchanger inside flow velocity. The
freshwater heat exchangers from cast iron and carbon steel
required significant maintenance during their lifespan.
So, to improve the performance of heat exchangers
and the reduction of maintenance the alloy materials are
recommended (i.e., stainless steels). For seawater system,
copper alloys are commonly used. However, due to numer-
ous benefits, use of titanium is increasing. Liquid–solid
fluidized bed heat exchanger has been recently used for
systems severely susceptible to fouling. where fluidized
particles are incessantly striking the walls and remov-
ing the foulants. Maddahi etal. [88] studied fouling of
CaSO4 on liquid solid fluidized bed heat exchanger they
also compared it with normally used forced convective
heat transfer. Due to the particle and wall collision fouling
was decreased remarkably and Heat transfer coefficient
considerably increased. They also developed a model and
validate with experimental data [89]. Such type of heat
exchangerswas also utilized in eutectic crystallization
fouling [90, 91]. Change in heat exchanger type or design
might cause huge expenses. So, off-line and online method
can be used tothe attain satisfactory operation such as
different inhibitor agent, surface coating, off-line cleaning
and miscellaneous method of inhabitation.
Mitigation offouling byphysical, chemical
andmechanical treatment
Irrespective of the change in filtration and operating condi-
tion, for the mitigation purpose numerous physical, chemi-
cal and mechanical methods have been developed during
the several years. Chemical inhibitors or agents are most
frequently used due to commercial availability at the range
of different conditions and suitability for all types of heat
exchangers. Numerous comparisons exist between the chem-
ical agents and the mitigators, based on the operating prin-
ciple the chemical agents and the mitigators are classified
into various groups (i.e., scale mitigators, pH controllers,
surfactant or dispersants, ion exchangers, adsorption agents,
antioxidants, oxidants, crystalline weaking agents and metal
deactivators) [85]. Sousa and Bertran [92] assessed the foul-
ing mitigator’s performance with unceasing measurement of
particle size distribution using laser diffraction and concomi-
tantly pH recording. Polymeric mitigators, which work as
both the nucleation and growth mitigators and show higher
efficiency in comparison to the phosphonates which behave
on growth principle. Shih etal. [93] evaluated five industrial
anti-scalants using calcium and turbidity measurement. In
induction time, considerable variations were observed due
to the anti-scalant and its dosages. There are several draw-
backs to use such types of chemicals, many of them may
contain substance which can damage the environment or can
react adversely with equipment material and produce cracks
or corrosion [94]. These demerits can shift the approach
to using of mechanical treatment such as wire brushes,
sponge balls or different types of additions. Specific mitiga-
tion methods were used for the reduction of crystallization
which occurs in the gas side of heat exchanger. Fouling spe-
cies (i.e., sulphur, sodium or vanadium) from gasses can be
removed before or after the gas combustion with several
Fig. 12 Various methods to pre-
vent fouling of heat exchangers
Fouling
mitigation
Online Online
Modification
in
Design
Chemical Fluid
cleaning
Feed
filters
Chemical
additives
Physical
Mechanical
Mechanical
Change
in
operation
condition

A review ofrecent advancements inthecrystallization fouling ofheat exchangers
1 3
techniques. Soot blowers are used as a mechanical method
for removal of gas fouling. Like liquid fouling, gas-side foul-
ing influence is minimized through the control of important
process parameters. The amount of excess air, surface tem-
perature above the acidic dew point, elimination of flue gas
and air fuel ratio are essentially controlled parameters [95].
Mitigation offoulants withadditives
The inserts of non-crystallized particles into the bulk solu-
tion were also being investigated by different researchers and
presented some inspiring results [96, 97]. Kazi etal. [28]
added pulp of softwood fibre into the bulk solution which
were found toretardthe foulingdeposition in association
with the concentration of fibres added for all the tests as
shown in Fig.13. They also performed the experiments on
addition of Arabic gum as additive which produced simi-
lar results on fouling inhibition as shown in Fig.14 [98].
Teng etal. studied CaCO3 fouling mitigation with the addi-
tion of EDTA [99] and DTPA [50] treated MWCNT-based
nanofluid and obtained encouraging results as presented in
Fig.15, EDTA and DPTA treated MWCNT reduced the dep-
osition of CaCO3 on heat exchanger surface. Longer induc-
tion period was produced due to the increase in additive
concentration, the calcium ion adsorption by additive was
improved. Moreover, the EDTA-MWCNT additive enhanced
the water thermal conductivity, which improved heat transfer.
This improvement was achieved due to MWCNT, Brownain
motion and water molecules formed surface nanolayers.
Field emission scanning electron microscope (FESEM)
images of the heat exchanger surfaces taken at 500X are
shown in Fig.16 depicts the crystal deposit morphology of
surface with and without EDTA and MWCNT-EDTA addi-
tives. Figure16 presents the FESEM image which shows
that pointed, sharp and needlelike crystals were formed in
case of the addition of additives, and in case of no addition
of additives, larger crystals were formed. With the addition
of additives, the deposit was smoother and duller, and the
crystal size decreased. The metal surfaces were affected by
MWCNT-EDTA oxidation and it incurred loss of mass. In
comparison of EDTA additive, the higher concentrations of
DPTA revealed zero corrosion and delivered better antifoul-
ing properties. It is known that the groundwater, seawater
and river water contain metal ions such as Cu, iron and Pb.
also cause harmful impact on the heat exchanger surfaces.
Kazi etal. [21, 99] have suggested several additives to miti-
gatethese metal ions fouling, such as EDTA-functionalized
MWCNT and GNP, and DPTA-functionalized MWCNT
and GNP. Xu etal. [58] effectively reduced CaCO3 using
sodium carboxymethyl cellulose (SCMC) additive in the
bulk solution. The results showed the reduction in fouling
rate and increase in the initiation period. Qian etal. [100]
conducted a study on crystallization fouling of CaCO3 in the
appearance of soluble microbial products, produced from
sulphate-reducing bacteria. At the concentration lower than
200
150
100
50
0
0 1000 2000
Time/min
Deposition g/m2
3000 4000 5000
TIBRE EFFECT
NO FIBRE
0.005% FIBRE
0.01% FIBRE
0.1% FIBRE
Fig. 13 Cumulative foulant deposition under the effect of different
concentrations of fibre [28]
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
0 0.005 0.0075
Mass% of gum arabic
Cumulative scale deposition/g
0.01
Cumulative scale deposition under effect of
gum arabic/g
Scale deposition/g
Fig. 14 Cumulative foulant deposition under the effect of different
concentration of gum Arabic [98]
0.2
0.15
0.1
0.05
0
– 0.05
– 0.0743
– 0.132
– 0.1
– 0.15
Cases
Mass deposition
Mass deposition/g
0.1652
0.1018
0.0235
0.0064
0.0563
0.0051
0.0305
EDTA
MWCNT-EDTA
MWCNT-DTPA
0.0033
0.045%wt0.03%wt0.015%wtNo treatment
Fig. 15 Comparison of mass deposition under the effect of different
concentration of EDTA, MWCNT-EDTA, MWCNT-DPTA [102]

K.Shaikh et al.
1 3
the 8.79mg L−1, the soluble microbial products encouraged
calcite calcification through chelation and when the content
increased the growth of calcite formed in a peanut shape.
In general, the results suggested that the microbial products
are not favourable for CaCO3 surface crystallization. Beneck
etal. [101] analysed organic macromolecules antifouling
impact of CaSO4 on surface of reverse osmosis desalination
experimental step up. Results revealed that the existence of
macromolecules have transferred scaling mechanisms of
gypsum from bulk solution to surface crystallization.
Mitigation offouling using surface treatment
In the recent time, the focus of researchers has been trans-
ferred towards the surface treatments and development of
advanced coating, for the mitigation of crystallize fouling.
Al-Janabi and Malayari [62] assessed the impact of inter-
molecular interaction energies on CaSO4 fouling with the
modification of surface energy through four different types
of surface coating. They established fundamental standards
for surface energy on fouling and validate with their work.
Same group has conducted a study on NI–P–BN coating
which produced excellent results in reduction of adhesion
forces among foulants deposits and surface. However, the
coatings demonstrated considerable ageing, leading to poor
abrasion resistance [103]. Yang etal.[104] investigated
Ni–P–PTFE and Cu–DSA low energy surfaces and dis-
covered that the fouling was reduced in comparison with
uncoated copper surfaces. Later, they observed from the
experiments that the weakening of adhesion delay in foul-
ing can only be attained in induction period [105]. Cheng
etal. [106] examined Ni–P monocrystalline and amorphous
coatings, and discovered that both the coatings performed
as reductant of tap water fouling. It was deemed that the
properties of antifouling decreases with the increase in the
monocrystalline phase share. In later study [107] the same
research team investigated numerous PTFE content, such
as Ni–Cu–P–PTFE under boiling flow conditions. Antifoul-
ing properties in coatings were found and investigators also
observed that the fouling was promoted with the increase
in surface free energy value. He etal. [108] studied hierar-
chical micro and nanoscale structured surfaces antifouling
properties generated through electrical discharge machining
(EDM). Results reveal that such treatment enhanced sur-
face roughness, anti-corrosion properties and hydrophobic-
ity. Results also depicted that at lower heat flux ranges, the
induction period was considerably delayed in comparison
with polished surfaces. Oon etal. [15] investigated stainless
steel surface coating with titanium (chosen due to surface
adhesion and high corrosion resistance) and found reduc-
tion in CaCO3 deposition on the surface. Shaikh etal. [83]
applied MWCNT mixture with gum Arabic on stainless steel
surface (selected because of biodegradable nature of coat-
ing) and found decline in deposition of CaCO3 and enhance-
ment in overall heat transfer coefficient as shown in Figs.17
and 18. Mayeret al. [109] assessed CaCO3 adhesion forces
on modified and unprocessed stainless steel surfaces, which
can be utilized in detailed models of scaling.
Fig. 16 FESEM Image of
CaCO3 deposit on SS 316L sur-
face a without additive, b with
MWCNT-EDTA additive [99]
– 0.02
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
Low concentraon coang at 1:1 rao
of CNT/GA
High concerntraon coang at 1:2 rao
of CNT/GA
Mass of deposition /g
Without coatin
g
With coatin
g
Fig. 17 Effect of coating on CaCO3 mass deposition [83]

A review ofrecent advancements inthecrystallization fouling ofheat exchangers
1 3
Mitigation offouling throughthermal shocks,
electron antifouling, alternating electromagnetic
field andcombination ofultrasonic andalternating
electromagnetic field
Vosough etal. [110] examined the mitigation of fouling
through thermal shocks, when surface temperature suddenly
increased or decreased. The results illustrate those thermal
stresses due to shock, produced crack in fouling deposited
layer and supports removal of foulant. Effectiveness of ther-
mal shocks were observed at severe fouling condition. How-
ever, at lower bulk temperature, fouling concentration and
heat flux, the thermal shocks were not helpful for removal
of foulants. Electromagnetic water treatment experiments
were also performed, a strongly diverging topic among the
fouling investigators. Where numerous conflicting argu-
ments are drawn. Wang and Liang [111] studied reduction
of CaCO3 deposition with alternating electromagnetic field.
In U-shapedheat exchanger tube, the average diameter par-
ticles were significantly decreased with the application of
such treatment. Fan etal. [112] examined the impact of water
treatment with electronic antifouling (EAF) on crystalliza-
tionfouling. In this water treatment technique, the pipe was
wrapped with solenoid coil, through this treatment concen-
tration of dissolved minerals were decreased by converting
the minerals salts into insoluble crystals with the improve-
ment in collusion process. In comparison to untreated water,
fewer lager diameters crystals were produced in EAF treated
water. Han etal. [57] studied impact of Mg2+ ion on pre-
cipitation of CaCO3 with ultrasonic (US) and altering elec-
tromagnetic field (AEMF) treatment. They observed that
the existence of Mg2+ ion can delay the calcium carbon-
ate fouling and induction period. With the increase in the
Mg2+/Ca2+ ratio, the effect of ions increases. The team also
suggested that considerable anti-scaling efficiency can be
attained through the addition of suitable amount of Mg2+
ions with the combination of US + AEMF or AEMF + US
treatment.
Fouling mitigation withoff‑line cleaning
Though the heat exchangers are designed with the consid-
eration of fouling and the online mitigation is efficient, still
the off-line cleaning is essential for some time. This off-line
cleaning is normally attained through physical or chemical
fluid cleaning methods as illustrated in Müller etal. [95].
As the mechanical cleaning methods requires the process
shutdown, so, it is convenient to use it as occasionally as
feasible. While planning the cleaning cycles abest possi-
ble balance among cleaning cost, process performance and
reliability is needed. Several researchers reported about the
optimization of cleaning cycle, emphasis was mainly given
on one type of approach that fouling layer properties remain
same throughout the lifespan of heat exchangers. In contrast
to this strategy, gradual change in chemical and physical
properties of fouling deposits needs to be reported in the
suggested cleaning approaches. Epstein [113] considered
the length among the consecutive cleaning cycles first-time,
later some authors such as Pogiatzis etal. [114] adapted it
and added the deposit ageingin it. The impact of ageing was
included as enhancement in deposit layer which resist the
chemicals; and in that consequence it is recommended for
shifting the approach towards the mechanical cleaning. Like
a single heat exchanger, networks cleaning approach can be
optimized as revealed in the paper of Diaby etal. [115].
A strategy for network of 14 heat exchangers was invented
under the variable ageing rates (slow and fast) using specific
genetic algorithm. The approach produced considerable eco-
nomic benefits mainly when deposit ageing affect at larger
amount. The fouling cleaning depends on variation of input
Fig. 18 Overall heat transfer
coefficient for coated and non-
coated surfaces [83]
– 0.5
0
0.5
1
1.5
2
2.5
01020304050607
080
Overall heat transfer co-effiient kWm–2K–1
Time/h
SS316L Surface
Low concentraon coated surfcace
High concerntraon coated surface

K.Shaikh et al.
1 3
quantities, i.e., the process parameters uncertainty. Various
recommended cleaning approaches assume stable (steady-
state) operations of heat exchanger and its network. Actually,
the input quantities may fluctuate drastically and can sig-
nificantly effect the optimization result. Pretoro etal. [116]
established a normally used two-layer model (i.e., growing
deposit is characterized through the sum of 2 layers with
differentproperties andresistance to differentcleaning tech-
niques). For inlet hot temperature, Beta and Gaussian prob-
ability density functions were applied. The results illustrate
a significant impact of probability functions on optimum
cleaning cycle period and cost, emphasizing the significance
of input parameters control in heat exchangers to be cleaned.
Study conducted by Ismaili etal. [117] using various Gauss-
ian distributions demonstrated similar outcomes. Significant
inconsistency was found among the uncertainties or ignor-
ing it in the estimates of optimum cleaning schedule of heat
exchanger networks.
Fouling modelling
The present review demonstrates the transformation in foul-
ing modelling from the early stages’ observation phenomena
to the more scientific method that started with the study
of Kern and Seaton. Kern and Seaton developed a fouling
model was one, from the earliest model [18]. This model
assumed that the mass removal rate (ṁr) was proportional
to the accumulated mass (mf) while mass deposition rate
(ṁd) was assumed constant with time t, and hence the mass
deposition approach asymptotically with the increase in the
time. Therefore,
Accumulation rate = Deposition rate − Removal rate.
Integration of Eq.9 at initial condition mf = 0 and t = 0
gives
where
m∗
F
is asymptotic accumulated mass, β = 1/tc, tc is
time constant, which presents fouling element mean resi-
dence time on heat transfer surface. Using Eq.10, Eq.13
can be written as fouling resistance Rf at time t in the form
of asymptotic fouling resistance
R∗
f
.
It is noticeable that the real solution needs to find
R∗
f
and tc
term as variable function affecting the fouling process.
In 1962, Hasson, through the study of CaCO3 precipita-
tion [118], considered crystallization fouling as a mass transfer
process and suggested the growth rate (ṁg) model shown in
Eq.15:
(13)
mf
=m
∗
F(
1−e
−βt)
(14)
Rf
=R
∗
f(
1−e
−βt)
K′
s
is deposit solubility product, Km fluid–deposit mass trans-
fer coefficient, Kr surface crystal forming reaction rate. Km
(can acquire from system geometry reliant empirical values)
and product solubility (available in literature) allowed Has-
son to use the measured growth rate for determination of
reaction rate. He continued his research on the improvement
of model and hypothesized that the deposition of CaCO3
is predominantly controlled through Ca2+ and HCO3− ion
forward diffusion rate [119].
Crystallization fouling can usually be defined with the clas-
sical law of deposition rate where the rate of deposition (ṁd)
is characterized as temperature reliant constant rate
K∗
R
and
concentration driving force function; however, the influences
of growth spots and nucleation were not considered.
Bansal etal. [120] investigated the above classical model
with CaSO4 crystallization fouling in plate heat exchanger
and proposed a revised version:
where mcg is the total mass deposit at the initial stage of
crystal growth, mt represents the total mass deposit after t
time, n’ is the exponent reliant on fouling situation and N
represents the nucleation sites function (provided through
particles in solution).
Kern and Seaton suggested the general crystallization foul-
ing model thatalso tried the inclusion of surface energy in the
model [121].
where τfl symbolizes shear stress in fluid, xd thickness of
deposition,
W∗
a
deposit adhesion work on surface, ∆E12
TOT
total interaction energy among the surface and deposit.
Bohnet [122] developed a model for second order reaction
(i.e., precipitation of CaSO4) by converting Eq.11 in second
order and then he simplified it with Eq.16 for the devel-
opment of second order model with the minimum variable
requirements. The model predicts unlimited fouling layer
growth, when both reaction rates and diffusion are running
the process.
(15)

m
g=

Ca

HCO3

−K
�
s


1
Km
+

1
Kr
(16)

md
=K∗
R(
C
fl
−C
sat)n
(17)

m
d=K∗
R

Cfl−Csat

nNmt
m
cg

n�
(18)

m
d−
mr=K∗
R
(
Cfl−CSat
)
nC1
𝜏
fl
1
x
d(
W∗
a−ΔETOT
12
)

A review ofrecent advancements inthecrystallization fouling ofheat exchangers
1 3
where rate of reaction KR relies on the reaction order which
could be defined with the Arrhenius equation, Sherwood
number Sh and coefficient of diffusion D were used for the
derivation of mass transfer coefficient Km. Cfl and Csat are the
calcium sulphate concentration in the fluid and at the satura-
tion level, respectively. For calcium carbonate species, scal-
ing diffusion coefficient can be found in Segev etal. [123].
Meanwhile, other scientists particularly focused the induc-
tion period modelling [124].
Though the numerous models for crystallization fouling
have been reported, almost all of them made one or more of
the following generalization assumptions [51]:
• Assumed steady-state operation.
• Design and material of equipment are ignored.
• Roughness and induction delay period are not incorpo-
rated.
• Properties of fluid are assumed to be constant.
• Homogenous fouling layer is assumed.
• Deposits shape is not considered.
• Effect due to the change in flow cross section is not con-
sidered.
• Only single fouling mechanism is assumed.
• The effect of changing in surface area and surface rough-
ness is ignored.
These models did not take effort to describe the basic fouling
processes, but emphasis was given on quantification of vari-
ous selected parameters in a particular test rig, where most
of them are surface and bulk temperatures, flow velocity,
time and concentration. Yang etal. [125] created a simpli-
fied empirical model for industrial crystallization fouling
process characteristic. Jamialahmadi etal. [126] studied
dehydration process fouling for the generation of phosphoric
acid and suggested a systematic model for the improvement
of cleaning process. Later, model was based on the impact
of surface temperature, fluid velocity and concentration.
Easvy and Malayeri [127] suggested a finned tube CaSO4
scaling model during the nucleate pool boiling. Supersatu-
rated microlayer under the bubbles as geometry function
was calculated. The model results illustrated agreement with
heat flux experimental data in between 100 and 300 kWm−2.
Babuška etal. [128] designed a CaCO3 model that considers
both temperature distribution and ageing in deposit. They
involved ageing for removal of deposits and hence the model
capable of presenting the results in sawtooth behaviour.
(19)

m
d=Km

1
2

Km
KR

+Cfl−CSat
−

1
4

Km
KR

2
+

Km
KR

Cfl−CSat

Kapustenko etal. [129] create a model for prediction of
particulate and precipitation fouling at various fouling tem-
perature and flow velocity with and without increase ofthe
heat transfer in plate heat exchanger. But model was not
able to report the sizes and content of solid particulates or
salt concentration. Kapustenko etal. also [129] developed a
mathematical model for assessment of water fouling on plate
heat exchangers. However, it needs the determination of
numerous dimensionless constants. Souza and Costa [130]
designed a cooling water system model, comprising of water
pump, interconnected pipe section, cooling tower, and shell
and tube heat exchangers. Reduction in the performance
of entire system due to fouling were predicted. Bobič etal.
[131] presents dynamic response model for counter flow
plate heat exchanger under the condition of temperature fluc-
tuations and external flow. Even though the model does not
consider fouling, it offers attractive future control algorithm
view for energy efficient heating and cooling application.
This should be one which is capable of effectively predict-
ing the fouling. Such algorithms can offer rapid response to
an undesirable change in internal system (i.e., fouling above
the set threshold limit) and respond suitably. Though there
are plenty of sensible model and measurements exist, still
several essential principles not explored, most of them yet to
be verified in fundamental fouling study. These are perfectly
developed general models and are able to define the crys-
tallization fouling and its all-essential processes. But these
are not suitable for the complex nature problem. Neverthe-
less, study on fundamentals of fouling is significant for the
improvement of current model accuracy and enhancement of
their usage to wider variety of affecting parameters.
In the last few years, researchers shifted their focus from
single heat exchanger modelling to multiple or network heat
exchangers modelling, which permits the significant indus-
trial saving and supports the academia–industry collabora-
tion [131]. Guelpa and Verda [132] designed a methodology
for detection of fouling and examined it in six distribution
network of heating system at Turin district. The model was
capable of predicting the requirement of cleaning in any
heat exchanger network, based on temperature on both side
and mass flow on primary side, which are usually meas-
ured in district heating system. To adopt this methodology,
there is no need to provide the data related to the type of
heat exchanger, dimension, geometry and pressure drop.
The team claimed that through the regular cleaning of heat
exchangers the district network system can save up to 1.6%
of primary energy consumption. Artificial neural networks
are also demonstrating the encouraging results and consider-
ably enhance the accuracy of some fouling models designed
for industries. Davoudi and Vaferi [133] used ANNs for the
systematic prediction of fouling level on heat exchanger,
and here, the simplicity and small degree of error for large
data experiment are key features of this model. Aguel etal.

K.Shaikh et al.
1 3
[134] investigated the performance of heat exchangers in
phosphoric acid concentrating plant and developed a model,
which improved through backpropagation of ANN, where
the model can be utilized for estimation of heat exchangers
cleaning schedule. Sundar etal. [135] established a simpli-
fied and scalable mathematical model on the basis of deep
learning for fouling resistance predication using normal
measured parameters for heat exchangers in industries. The
value of R2, described how perfectly the model simulates
the actual data, which was indicating more than 99% accu-
racy. Benyekhlef etal. [136] established an ANN model for
estimation of MgO water and CuO water nanofluid effective-
ness for reduction of fouling resistance in heat exchanger.
With R2 value, the results of model were described which
represents more than 99% accuracy of model. Rohman
etal. [137] utilized feed-forward neural network (FFNN)
for estimation of fouling thickness in polyethylene tubular
reactor. Result of model illustrate more than 98% accuracy
for the prediction of fouling thickness. Though the ANNs
were revealing the excellent earlier results, the field is still
comparatively new, and publications related to fouling are
rare. In the current years, CFD modelling software have
also tremendously improved, which guided the utiliza-
tion of CFD in fouling process modelling. The numerical
method allows the computation of velocity gradient, local
temperature and concentration in space and time, which have
solid impact on fouling. Brahim etal. [138, 139] simulated
CaSO4 crystallization fouling on flat heater surface using
CFD software. Though the ageing and initiating period was
not incorporated, the CFD model still allowed appropriate
fouling layer growth prediction and estimation of tempera-
ture distribution. Walker and Sheikholeslami [140] run the
CFD model to describe the impact of flow velocity on bulk
crystallization. Using this model, the radial concentration
gradients was anticipated at laminar flow. Diffusive flux in
radial direction was predicted owing to distribution of flow
velocity in radial direction. As an alternative of the bulk
solution, the crystallization was predominantly anticipated
in viscous layers during the turbulent flow because of the
enhanced in-residence time of particles in this lower flow
velocity region. Xiao etal. [141] investigated induction
period microscale fouling. This study focused on crystals
growth with different density, shape, size, orientation, dis-
tribution and their impact on heat transfer and dynamic of
flow. Compared to wider and shorter crystals, the slim and
tall crystals were found for the enhancement of heat transfer
in the induction period in a better way. Yang [142] examined
the cured oil induction period fouling in tube heat exchanger.
The influence of flow velocity and temperature was simu-
lated with inclusion of formation, ageing and removal of
fouling in model. Zhang etal. [143] run a CFD software
to demonstrate the impact of main operating parameters on
CaSO4 fouling, i.e., foulant concentration, flow velocity,
deposit porosity and inlet temperature. Haghshenasfard
etal. [78] designed a subcooled flow boiling model, where
they estimated the deposition of CaSO4 on heated surface.
The impact of flow velocity, surface roughness, surface
temperature and fluid were anticipated. The model did not
incorporate the enhancement in thermal resistance due to
the rise in fouling layer. Ojaniemi etal. [144] developed a
CFD model for the simulation of calcium phosphate foul-
ing on plate heat exchanger. In this model precipitation of
minerals were based on saturation ratio. Results of model
agreed with experimental data. The accuracy of applied
CFD model depends on input conditions, and if more fun-
damental processes are incorporated, then this CFD model
become rapidly computationally demanding software. How-
ever, enhancing demand of computational software can be
achieved through sudden advancements in processing field,
demonstratingwide range of unexplored fouling simulation’s
future potential.
Cost imposed due tothefouling interms
ofeconomic loss andenvironmental damage
Economic loss due tothefouling
Fouling imposes extra cost on industrial heat transfer equip-
ment. In industries, cost related to the fouling have been
determined by some studies. Cost of fouling can usually
be divided into main five groups, i.e., (1) energy cost, (2)
maintenance cost, (3) cost of production loss, (4) [145] cost
of environmental management and (5) increased in capi-
tal expenditure [13]. Overall, cost of cleaning chemicals
and equipment are imposing addition to maintenance cost
of plants. The mechanical and chemical cleaning cost was
assumed as 250 €/cleaning and 500 €/cleaning, respectively
[146]. Cost of cleaning may vary from 700 to 1000 USD
for a single heat exchanger [147, 148]. In China, fouling
imposed annually 6065 USD/MW additional fuel cost due
to energy production loss in power plant [149]. Fouling adds
cost of 75,400 USD per km2 for management of the environ-
mental losses [148]. To compensate the fouling obstruction,
heat transfer area of heat exchangers is kept surplus. Simi-
larly, larger-size fans and pumps are selected to compensate
the increase in the pressure loss from the reduction in flow
area. One of the design approaches is to keep standby heat
exchangers in design process to make sure operation are not
interrupted when fouled heat exchangers are taken under
fouling deposition cleaning maintenance [150]. Only in USA
fouling in preheat train exchangers are responsible for 1.2
billion USD loss [30, 151]. Total cost due to fouling on heat
exchangers for industrial globe was predicted as 5 × 1010
USD/year. Study conducted by Pretoro etal. [116] reported
fouling cost in terms of 2018 gross national product (GNP)

A review ofrecent advancements inthecrystallization fouling ofheat exchangers
1 3
are shown in Table1 and Fig.19. Total yearly fouling cost
for Japan is 0.33% of 2018 GNP and is highest among the
other countries. For New Zealand and Australia, annually
fouling cost is 0.06% of 2018 GNP of both countries and
lowest among the other countries. In 2006, economic loss of
China due to fouling in thermal power plants were 4.68 bil-
lion USD which was around 0.169% of GDP of China [149].
Environmental damage due tothefouling
Fewer scientists studied the effect of heat exchangers foul-
ing on environment. Müller etal. [94] conduct a study on
impacts of heat exchangers on environments. In this study,
they said that fouling in exchangers’ pipe creates many
problems such as loss in heat transfer, under-deposit corro-
sion, flow maldistribution and pressure drop. All these have
not only negative impacts on economy of plants but also
have direct and indirect impact on environment. Disposal
of foulant and additive used for reduction of fouling can
create water and land pollution. ESDU reported that crude
oil refineries in USA are responsible for 7 million tonnes of
CO2 emissions due to fouling [151]. Elwerfalli [148] found
that the schedule shutdown for removal of fouling damaged
theenvironment within 5 kms radius. Casanueva-Robles and
Bott [152] found that with the increase in the fouling thick-
ness in condenser of power plant, emissions of carbon diox-
ide increased. They found that1000µm fouling thickness,
raised the emission rate by almost 2900 tonnes of CO2/h.
Due to increase in fouling, heat exchangers required more
electrical power and in most of industries electrical power
is produced using fossil fuels that emits different hazardous
gasses (i.e., CO2, CO, SOx and NOx.) which are hazardous
for both environment and human health.
Future direction
Future investigation of two or more composite fouling miti-
gation and modelling approach will enhance the research
background related to various factors that affect the foul-
ing mitigation process and sophisticated new eco-friendly
mitigation process for future applications. Therefore, devel-
oping of efficient, economical, eco-friendly carbon-based
additives from biodegradable waste and their composite
for the mitigation of deposits on heat exchanger surface is
always crucial. Additionally, new methods for mechanical
and fluid cleaning, coating of heat transfer surface with new
eco-friendly, corrosion resistive and composite nanomate-
rials such as GNP, CNT and hybrid of these through dif-
ferent techniques (i.e., powder physical vapour deposition,
electrophoresis, and dip and spray coating) and alteration of
design and operating conditions will help scientists in future
studies. Furthermore, modelling of composite fluid using
latest technology such as CFD, ANN, fuzzy logic, genteic
algorthim (GA) and particle swarm optimization (PSO) will
reduce the cost of experiments and challenges faced by pre-
vious fouling modelling attempts. Moreover, toxicity and
risk assessment of nanoadditive, assessment of reduction
in CO2, NOx and SOx emissions and economic benefits due
to mitigation of foulants should be carried out through life
cycle assessment (LCA) for provision of more environmen-
tal and economic benefits.
Conclusions
In recent years, people are gradually moving towards the car-
bon neutralization. In this regard, fouling is not adequately
considered, though the fouling in condenser of powerplants
alone increases tonnes of CO2 emissions. If this cause is
not adequate for consideration, fouling also imposed cost
as 0.33% of 2018 gross national products (GNP) of highly
industrialized countries. These two reasons together with
numerous others, warning to pay more attention towards
fouling and its mitigation measures should be noted. Most
design engineers ignored the fundamental information
Table 1 Fouling cost versus 2018 GNP [116]
S# Country Fouling cost/106
$/year
2018 GNP/106 $/year
1USA 14,175 20,891,000
2 Germany 4875 4,356,353
3 New Zealand 64.5 197,827
4 Australia 463 1,318,153
5 France 2400 2,962,799
6 Japan 10,000 5,594,452
0.00%
0.05%
0.10%
0.15%
0.20%
0.25%
0.30%
0.35%
USA Germany France Japan Australia New Zealand
Fouling cost in term of 2018 GNP (%)
Name of Countries
Fig. 19 Fouling impacts in terms of 2018 GNP % of different coun-
tries [116]

K.Shaikh et al.
1 3
about crystallize foulants and pay greater attention to foul-
ing mitigation approaches. But studies on fundamentals of
fouling can provide greater benefit in designing of future
heat exchangers. The models are mostly developed from
experimental investigation or based on partially empirical
assumptions. Computational fluid dynamics (CFD) simula-
tor and neural network will be vital when these fundamental
processes are adequately explained to forecast future pro-
cess in better way. Various mitigation methods were estab-
lished through different experiments, which demands fur-
ther awareness on operating principles; therefore, fouling
can only be reduced but never fully prevented. Hence, the
requirement of better and new approaches is always neces-
sary for the present and will be required in the future.
Acknowledgements This study is supported financially under the
Fundamental Research Grant Scheme awarded by the Ministry of
Higher Education Malaysia with Grant Number: FRGS/1/2019/TK03/
UM/02/12 (FP143-2019A). The authors also gratefully acknowledge
the support from Grants, RMF0400-13-2021, ST049-2022, RK001-
2022,Centre of Advanced Manufacturing and Material Processing
(AMMP), Centre for Energy Sciences(CES), Centre of Advanced
Materials (CAM), Department of Mechanical Engineering, Universiti
Malaya, and BUITEMS, Pakistanto conduct this research work.
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