Journal of Hazardous Materials 407 (2021) 124874

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Journal of Hazardous Materials
journal homepage: www.elsevier.com/locate/jhazmat

Non-monotonic contribution of nonionic surfactant on the retention offunctionalized multi-walled carbon nanotubes in porous media
Miaoyue Zhang a, Scott A. Bradford b, Erwin Klumpp c, Jirka Šimůnek d, Chao Jin a, *,Rongliang Qiu a, e, **aSchool of Environmental Science and Engineering, Guangdong Provincial Key Lab for Environmental Pollution Control and Remediation Technology, Sun Yat-sen
University, Guangzhou 510006, PR China
United States Department of Agriculture, Agricultural Research Service, U. S. Salinity Laboratory, Riverside, CA 92507, USAc
Agrosphere Institute (IBG-3), Forschungszentrum Jülich GmbH, 52425 Jülich, GermanydDepartment of Environmental Sciences, University of California Riverside, Riverside, CA 92521, USAe
Guangdong Laboratory for Lingnan Modern Agriculture, College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, PR
Chinab

A R T I C L E I N F O

A B S T R A C T

Editor: Prof. G. Lyberatos

The concentration of nonionic surfactants like Triton X-100 (TX100) can influence the transport and fate of
emerging contaminants (e.g., carbon nanotubes) in porous media, but limited research has previously addressed
this issue. This study investigates the co-transport of functionalized multi-walled carbon nanotubes (MWCNTs)
and various concentrations of TX100 in saturated quartz sand (QS). Batch experiments and molecular dynamics
simulations were conducted to investigate the interactions between TX100 and MWCNTs. Results indicated thatthe concentration ratio of MWCNTs and TX100 strongly influences the dispersion of MWCNTs and interaction
forces between MWCNTs and QS during the transport. Breakthrough curves of MWCNTs and TX100 andretention profiles of MWCNTs were determined and simulated in column studies. MWCNTs strongly enhanced
the retention of TX100 in QS due to the high affinity of TX100 for MWCNTs. Conversely, the concentration of
TX100 had a non-monotonic impact on MWCNT retention. The maximum transport of MWCNTs in the QS
occurred at an input concentration of TX100 that was lower than the critical micelle concentration. This suggeststhat the relative importance of factors influencing MWCNTs changed with TX100 sorption. Results from inter­action energy calculations and modeling of competitive blocking indicate that the predictive ability of interactionenergy calculations and colloid filtration theory may be lost because TX100 mainly altered intermolecular forces
between the MWCNT and porous media. This study provides new insights into the co-transport of surfactants and
MWCNTs in porous media, which can be useful for environmental applications and risk management.

Keywords:
Multi-walled carbon nanotubes
TX100
Breakthrough curves
Retention profiles
Molecular dynamics simulation
And intermolecular force

1. Introduction
Nanomaterials such as carbon nanotubes (CNTs) (Iijima, 1991) havebeen widely used in hydrogen storage (Dillon et al., 1997), electronics(Avouris et al., 2007), sensors (Ertan et al., 2016; Golestanifar et al.,2015; Salmanpour et al., 2018; Yola and Atar, 2014; 2019), and may
potentially be employed in environmental remediation (Mauter andElimelech, 2008; Pan and Xing, 2012), surfactant removal (Gao et al.,2016), and water treatment (Camilli et al., 2014; Li et al., 2012) due totheir unique electric, chemical, and physical properties (Gannon et al.,2007; Gohardani et al., 2014). Aggregation of CNTs in the subsurface oraquatic suspension is one of the most practical challenges inhibiting
their use in industrial and environmental applications. Surfactants arecommonly used to promote the stabilization of nanoparticles that are
widely used in our daily life and environmental remediation (e.g.,contaminant leaching, hydraulic fracturing) (Desai and Banat, 1997; Palet al., 2019; Zhao et al., 2010). For example, Triton X-100 (TX100), a
nonionic surfactant, has been extensively used in the biochemical in­
dustry to stabilize nanoparticles because it is a relatively mild detergent,
non-denaturing, and biodegradable (Prediger et al., 2018). The wide use* Corresponding author.
** Correspondence to: School of Environmental Science and Engineering, Guangdong Provincial Keyfor Environmental Pollution Control and Remediation Tech­
nology, Sun Yat-sen University, Guangzhou 510006, PR China.
E-mail addresses: jinchao3@mail.sysu.edu.cn (C. Jin), eesqrl@mail.sysu.edu.cn (R. Qiu).
https://doi.org/10.1016/j.jhazmat.2020.124874
Received 29 September 2020; Received in revised form 10 December 2020; Accepted 11 December 2020
Available online 17 December 20200304-3894/© 2020 Elsevier B.V. All rights reserved.

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Journal of Hazardous Materials 407 (2021) 124874

of both CNTs and surfactant will result in their release and co-transport
in the environment, but the potential impacts of surfactants and
MWCNTs (e.g., adsorption, aggregation, and co-transport) under various
aquatic conditions is still not well understood. Thorough knowledge of
mechanisms governing their contaminant interactions and environ­mental fate is therefore needed.
The stability of a nanoparticle suspension in surfactants’ presence
depends on π-π interactions, electrostatics, and hydrophobicity. Differ­ences in the chemical structure of a surfactant will alter the relative
importance of these dispersion mechanisms. For example, the anionicsurfactant sodium dodecylbenzenesulonate (SDBS) can induce a better
dispersion of nanoparticle suspensions than sodium dodecyl sulfate(SDS) by enhanced π-π interactions (Islam et al., 2002; Wusiman et al.,2013). Ionic surfactants can influence the aggregation behavior of col­loids by electrostatics, whereas nonionic surfactants do not (Gao et al.,2016; Oleszczuk and Xing, 2011). Previous studies have reported thatthe dynamic balance of repulsive and attractive forces between TX100
and CNTs determines the dispersion and aggregation of CNTs (Gao et al.,2016; Han et al., 2008; Hilding et al., 2003). The dispersion of CNT was
dependent not only on the availability of TX100 (e.g., the input con­centration of TX100) in suspension but also on the functional groups on
the surface of CNTs (Matarredona et al., 2003; Wang et al., 2004). Clark
et al. (2011) found that TX100 at low concentrations (0–0.6 wt%) pro­vided limited dispersibility of CNTs, whereas Rastogi et al. (2008) sug­gested an optimized ratio between TX100 to MWCNTs (350:1).
Surfactants can also impact the transport of nanoparticle suspensions. Lu
et al. (2013, 2014) demonstrated that CNTs that were stabilized byvarious surfactants exhibited different mobilities. An increase in theconcentration of the anionic surfactant SDBS enhanced the CNTs sus­
pension stability and transport in porous media (Zhang et al., 2019).
Studies examining the influence of nonionic surfactants (e.g., TX100)
on the CNTs transport and retention in porous media are still limited.
Most studies were performed at high input concentrations of CNTs withlow concentrations of a surfactant. However, the total surfactant con­centration of municipal sewer discharges is about 20–70 mg L− 1 (Mat­thijs et al., 1999), which is much higher than the discharged
concentration of CNTs (Gottschalk et al., 2009). Surfactants at theseconcentrations are high enough to stabilize a CNT suspension when both
surfactants and CNTs are released into the environment. Thus, it isimportant to evaluate the impacts of TX100 on the transport andretention of CNTs in response to the changes in dosage. It is also criticalto quantify the availability and distributions of surfactants downstream
from a field-remediation site in order to manage environmental risk.
Previous works have mostly focused on the effect of surfactants on
colloids, but ignored the transport of surfactants in porous media. A
better understanding is needed to assess the influence of CNTs on theretention of TX100 and the co-transport behavior of CNTs and TX100 in
porous media. For example, Becker et al. (2015) showed that the sta­bilizing agent could compete for the same retention sites as quantum dot
nanocrystals. Zhang et al. (2019) suggested that competitive blocking
was not the dominant mechanism governing the transport and fate of
CNTs when using SDBS.
In the present work, experiments exploring the co-transport offunctionalized multi-walled carbon nanotubes (MWCNTs, 5 mg L− 1) andnonionic surfactant TX100 (5–50 mg L− 1) in porous media were con­ducted. Both breakthrough curves (BTCs) of MWCNT and TX100 andretention profiles (RPs) for MWCNTs in saturated quartz sand (QS) were
determined. The adsorption behavior of TX100 on MWCNTs and quartz
sand was also quantified. The importance of competitive blocking on theco-transport behavior of TX100 and MWCNTs was investigated using
two models. The interactions between MWCNTs, sand, and TX100 were
quantified using both batch experiments and the molecular dynamics(MD) simulations, and compared with similar results for SDBS and
MWCNTs. The knowledge gained in this research sheds light on the rolesof the nonionic surfactant TX100 on the fate and transport of nano­materials (e.g., MWCNTs) in porous media.

2. Materials and methods
2.1. Carbon nanotubes, TX100, and quartz sandPurified quartz sand (QS, 240 µm, Quarzwerke GmbH, Frechen,
Germany) was used in batch and column experiments following a pro­
tocol in the literature (Kasel et al., 2013). Radioactively (14C) labeled
and unlabeled MWCNTs (Bayer Technology Services GmbH, 51368
Leverkusen, Germany) were applied in batch and column experiments.
These MWCNTs were boiled with 70% nitric acid (Sigma-Aldrich
Chemie GmbH, 89555 Steinheim, Germany) for 4 h to obtain additional
oxygen-containing functional groups (e.g., carboxylic and hydroxyl
groups) on the surface of MWCNTs. The characterization of function­
alized MWCNTs is given in Kasel et al. (2013). The MWCNTs have amedian diameter of 10–15 nm and a median length of 200–1000 nm(Pauluhn, 2010). The TX100 was purchased from Sigma-Aldrich. The
critical micelle concentration (CMC) of TX100 in 1 mM KCl was deter­
mined using a tensiometer (Dataphysics DCAT21, Germany). The CMC isapproximately 30 mg L− 1 (Fig. S1 of Supporting Information (SI)),
which is close to that reported by other studies (Cui et al., 2008; Shiet al., 2013). The electrophoretic mobility, zeta potential, and hydro­
dynamic radius of MWCNTs, and the electrophoretic mobility and zeta
potential of crushed QS in the presence of different TX100 concentra­
tions were determined using a Zetasizer Nano (Malvern Instruments
GmbH, Herrenberg, USA). The total interaction energy (Φs) between QS
and a spherical colloid with similar properties to MWCNTs in the pres­ence and absence of TX100 in 1 mM KCl solution was calculated basedon the approach of Bradford and Torkzaban (2013). Detailed informa­tion about experimental protocols, detection methods, and calculations
for interaction energy is given in Section S1 of the SI.
2.2. Batch experiments
The adsorption kinetics and adsorption isotherms of Triton X-100(TX100, 0–80 mg L− 1, Merck KGaA, Darmstadt, Germany) on MWCNTs(5 mg L− 1, 1 mM KCl) and QS (2 g) was determined using the dialysis
technique and in batch trials, respectively. Details about batch experi­ments and simulation equations are provided in Section S2 of the SI.
2.3. Column experiments
Column experiments (3 cm inner diameter and 12 cm length) fol­
lowed a procedure outlined in a recent study (Zhang et al., 2016b). The
grain size (d50 = 240 µm) of the porous medium, ionic strength (IS, 1 mM
KCl), and Darcy velocity (q = 0.71–0.73 cm min-1) were the same for allcolumn experiments. Briefly, the columns were wet-packed with puri­
fied QS and then purged with approximately 30 pore volumes (PVs) of
background electrolyte solution (1 mM KCl). Around 90 mL (close to 2.5
PVs) of a non-reactive tracer (1 mM KBr in 1 mM KCl) was then injected
into the column to assess the hydrodynamic conditions. Afterward, apulse of MWCNTs (approximately 90 mL, 5 mg L− 1, 1 mM KCl) mixed
with different TX100 concentrations (0–50 mg L− 1) was injected into thecolumn. All experiments were replicated and exhibited good reproduc­
ibility. A summary of the experimental conditions (Darcy velocity, massbalance information, etc.) is provided in Table 1.
The effluent concentrations of bromide were measured using a highperformance liquid chromatograph (STH 585, Dionex, Sunnyvale, CA,
USA) equipped with a UV detector (UV2075, Jasco, Essex, UK). The 14Clabeled effluent concentrations of MWCNT and TX100 were determinedusing a liquid scintillation counter (LSC) (PerkinElmer, Rodgau, Ger­many) and an UV-Vis spectrometer at a wavelength of 274 nm. Cali­
bration curves between absorbance and concentrations of MWCNTs,
TX100, and TX100-MWCNT were established at 274 nm and are shownin Section S3 and Fig. S2. The effectiveness of this approach for quan­tifying concentrations in the TX100-MWCNT system was assessed bycomparison with the additivity of individual absorbance from MWCNTs
2

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Journal of Hazardous Materials 407 (2021) 124874

Table 1
Experimental conditions and mass recoveries from effluent for all column experiments. The ionic strength was 1 mM KCl, d50 = 240 µm, and the input concentration of
MWCNTs was 5 mg L− 1.
Co (M)[mg L-1]
5
0
0
5
5
5
5

Co (T)[mg L-1]

Disp.
[cm2 min− 1]q[cm min− 1]

Porosity

MT
[%]

Meff
[%]

Msolid[%]Mtotal
[%]

0
10
20
5
10
20
50

0.288
0.075
0.084
0.018
0.013
0.019
0.018

0.71
0.72
0.72
0.73
0.71
0.72
0.72

0.43
0.44
0.43
0.45
0.45
0.43
0.44

NA
92.3
94.9
41.4
50.8
64.8
80.9

17.5
NA
NA
44.3
75.9
10.0
4.1

87.1
NA
NA
52.7
33.7
87.9
88.3

104.6
NA
NA
97.0
109.6
97.9
92.4

Co(M) and Co(T) are the input concentrations of MWCNTs and TX100, respectively; Disp.is the estimated longitudinal dispersivity; q is the Darcy velocity; MT is theeffluent percentage of TX100 recovered from the column experiment; and Meff, Msolid, and Mtotal are the effluent percentage, the retained percentage, and the total
percentage of MWCNTs recovered from the column experiment, respectively.

and TX100. The excellent correlation between the measured absorbancefrom the TX100-MWCNT system with the sum of individual absorbanceof MWCNTs and TX100 is shown in Fig. S2b. Note that higher concen­
trations of MWCNTs were used in this study compared to a recent study
to avoid the influence of MWCNT absorbance at 274 nm (Zhang et al.,2016b). Afterwards, the sand in the packed column was excavated inapproximately 0.5–1 cm thick increments, dried, homogenized, com­busted using a biological oxidizer, and the retained MWCNTs for RPs
was determined using the LSC.

MWCNTs and TX100 was also modeled using this M1 model. More de­tails about simulation equations are provided in Section S4 of the SI.
3. Results and discussion
3.1. Characterization of MWCNTs and QS
Suspensions of MWCNTs (Co(M) = 5 mg L− 1) and TX100 (Co(T) = 0 to
50 mg L− 1) were prepared in 1 mM KCl. The pH of these suspensions wasstable, ranging between 5.23 and 5.28. Similarly, QS’s electrophoretic
mobility and zeta potential exhibited only slight changes when Co(T)increased from 0 to 50 mg L− 1 (Figs. S3a and S3c). Conversely, themeasured electrophoretic mobility and zeta potential of MWCNTs fluc­tuated in a non-monotonic manner with an increase in Co(T) (Figs. S3aand S3c). The electrophoretic mobility of MWCNTs became morenegative as Co(T) increased from 0 to 10 mg L− 1, and then increased (lessnegative) with further increases in Co(T).
Fig. S3b presents the corresponding hydrodynamic radii of MWCNTs(e.g., equivalent spheres that diffuse at the same speed as MWCNTs) inthese suspensions. The hydrodynamic radii were relatively stable when
Co(T) increased from 0 to 10 mg L− 1, but then started to increase withfurther increases in Co(T). These observations agreed with previous in­vestigations, which have attributed this behavior to electrosteric inter­action, hydration, and other effects (Dong et al., 2011; Yang et al.,2017). The adsorption of TX100 on MWCNTs surface could result in astronger dispersion of MWCNTs suspension due to steric repulsion
introduced by hydrophobic interaction, π-π interactions, and hydration
layers (Fatemi and Foroutan; Flynn et al., 2012; Yang et al., 2014). Suchenhanced dispersion could produce more negative electrophoretic
mobility of the MWCNTs (e.g., at 5 and 10 mg L− 1 TX100, Fig. S3a).

2.4. Molecular dynamics simulations
Molecular dynamics (MD) simulations were conducted to investigate
the mean distance between the centroids of MWCNTs, the binding en­ergies, and interaction mechanisms between MWCNTs and TX100, and
MWCNTs and SDBS (Baker et al., 2001; Kumari et al., 2014). In brief, theall-atom MD simulations were conducted using a GROMOS54a7 force
field (Schmid et al., 2011) created by the Automated force field Topol­
ogy Builder (ATB) (Malde et al., 2011) and were carried out using theGromacs-4.6.7 software package (Hess et al., 2008). The time step was 2
fs, and the total run time was 10 ns for the equilibrium MD simulation
under normal pressure and temperature. The relaxed system was used as
the starting configuration. Energy minimization was carried out with acomposite protocol of steepest descent using termination gradients of
100 kJ (mol nm)− 1. The Nose’-Hoover thermostat (Berendsen et al.,1984) was used to maintain the equilibrium temperature at 298 K andpressure at 1 bar. Periodic boundary conditions were imposed on all
three dimensions. The Particle Mesh-Ewald method (Astrakas et al.,2012; Essmann et al., 1995) was used to compute long-range electro­
statics within a relative tolerance of 1 × 10− 6. A cut-off distance of 1.2
nm was applied to determine the real-space Ewald and van der Waals
interactions. The LINCS algorithm (Hess et al., 1997) was applied toconstrain bond lengths of hydrogen atoms. A leap-frog algorithm (Van
Gunsteren and Berendsen, 1988) was used with a time step of 2 fs.

3.2. Adsorption of TX100 onto QS and MWCNTs
Fig. S4 shows the adsorption kinetics of TX100 on MWCNTs. The
adsorption of TX100 on MWCNT occurred fast and approached equi­
librium conditions after about 30 min (Fig. S4). The adsorption isotherm
experiments (Fig. 1a and b) were performed for 48 h to ensure equi­
librium conditions. The Langmuir model provided an excellent
description (R2 > 0.89) of the adsorption isotherms of TX100 on
MWCNTs (Fig. 1a) and TX100 on QS (Fig. 1b). A sharp increase of TX100
adsorption on MWCNTs was observed during the initial phase, followed
by a plateau at an equilibrium surfactant concentration of about 5 mg
L− 1 (qmax = 2.28 mM g− 1) (Fig. 1a). In contrast, the adsorption isothermof TX100 on QS had a low value of qmax = 4.9E-5 mM g− 1, reflecting a
relatively small affinity of TX100 for QS.
The adsorption mechanisms of nonionic surfactant TX100 on
MWCNTs were different from those of the anionic surfactant SDBS. The
adsorption of SDBS on MWCNTs (Zhang et al., 2019) (Fig. 1a) gradually
increased and then reached qmax of 0.96 mM g-1. The value of qmax for
SDBS on MWCNT (qmax of 0.96 mM g− 1) was much lower than for2.5. Numerical modeling
Models considering no and limited competitive blocking (denoted as
M1 and M2, respectively) that are available in the HYDRUS-1D com­puter code (Šimůnek et al., 2008) were used to simulate the co-transportof MWCNTs and TX100 in the column experiments. The subscripts M
and T on parameters indicate that they are associated with the MWCNTs
and TX100, respectively. Competitive blocking between TX100 and
MWCNTs on the QS was accounted for in the M2 model using a Lang­muirian blocking approach modified to include area conversion factors
between TX100 and MWCNTs, Г T and ГM [-]. In this case, Г M and Г T
were simultaneously optimized to both MWCNT and TX100 data sets.
Competitive blocking was neglected in the M1 model by setting Г M andГ T to zero and then independently optimizing the transport and reten­tion parameters for MWCNTs and TX100. Single species transport of3

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Journal of Hazardous Materials 407 (2021) 124874

Fig. 1. Adsorption isotherms of surfactant on different sorbents: (a) TX100 and SDBS on MWCNT and (b) TX100 and SDBS on quartz sand. The adsorption data of
SDBS was based on the former study (Zhang et al., 2019). The ionic strength was 1 mM KCl. Qe is the amount of TX100 or SDBS adsorbed at equilibrium on the solid
phase; Ce is the TX100 or SDBS concentration in the liquild phase at equilibrium.

TX100 on MWCNTs (qmax = 2.28 mM g− 1). In addition, the adsorption
behavior of TX100 on QS was different than SDBS. A higher adsorption
affinity for TX100 on QS was observed compared to SDBS on QS. The-SO3 group on SDBS can contribute to repulsive electrostatic interactions
with negatively charged MWCNT and QS (Islam et al., 2002; Ncibi et al.,2015). Conversely, the adsorption behavior of surfactants (TX100 and

Fig. 2. Observed and fitted (M1) BTCs of MWCNTs (a) and TX100 (b), and RPs of MWCNTs (c) with or without additional TX100 or MWCNTs in quartz sand. (a)BTCs of MWCNTs with adding TX100 (0–50 mg L− 1); (b) BTCs of TX100 with MWCNTs at 5–50 mg L− 1 TX100. (c) RPs of MWCNTs with adding TX100(0–50 mg L− 1); The input concentration of MWCNTs was 5 mg L− 1. The ionic strength was 1 mM KCl. The Darcy velocity is 0.71–0.73 cm min-1.
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Journal of Hazardous Materials 407 (2021) 124874

SDBS) with MWCNTs and QS can mainly be attributed to differences in
the hydrophobic interaction between the hydrophobic chains on thesurfactant and hydrophobic sites on the CNTs (Han et al., 2008; Mata­rredona et al., 2003), π-π interactions between benzene ring of surfac­
tant and CNTs (Tan et al., 2008), and hydrogen bonding (Islam et al.,
2002; Lin and Xing, 2008; Pan and Xing, 2008).

non-monotonic RPs was not the focus of the current study.
To evaluate the relative contribution of TX100 sorption on theretention of MWCNTs in QS, the parameter RM/T was calculated as:
RM/T =

C0(M) *V*ΔMsolid
ΔRM
=
ΔRT
C0(T) *V*Δ(1 − MT )(1)

where ΔRM is the difference in retained mass of MWCNTs in the presence
and absence of TX100 (10 mg L− 1), ΔRT is the difference in retainedmass of TX100 in the presence and absence of MWCNTs, and V is theinjected volume of MWCNT suspension (90 mL). Note that ΔRM and ΔRT
have subtracted the corresponding single-species results to reflect theretained mass of MWCNTs and TX100, respectively, due to only cotransport. The value of RM/T, therefore, reflects the net mass of
MWCNT that was retained due to sorbed TX100.
Fig. 3 presents the calculated values of RM/T (mg mg− 1) as a functionof the TX100 concentration. The value of RM/T equalled − 0.8, − 0.64,
0.006, and 0.007 mg mg-1 when the TX100 concentration was 5, 10, 20,
and 50 mg L− 1, respectively. Negative values of RM/T when Co(T) = 5 and
10 mg L− 1 indicate that TX100 sorption on the MWCNTs decreased the
MWCNT retention, whereas positive values when Co(T) = 20 and
50 mg L− 1 show a minor enhancement in MWCNT retention due to
TX100 sorption. This trend clearly shows that increasing the TX100
concentration caused a transition from hindering to slightly enhancing
MWCNT retention. This non-linear impact of TX100 sorption suggeststhat mechanisms influencing MWCNT retention changed with the rela­tive ratio of TX100 and MWCNTs in suspension. However, the greatest
changes in MWCNT retention mechanisms are expected to occur at low
TX100 concentrations and be relatively insensitive at higher TX100
concentrations (e.g., 20–50 mg L− 1).
Experimental data were simulated using the M1 (independently,
Fig. 2a-c) and M2 (competitive blocking, Fig. S5) models. Table 2 in­dicates both M1 and M2 models equally described this data. Results from
the M1 model are therefore discussed below because it has fewer fitting
parameters. Simulation results when using the M1 model are shown in
Fig. 2a-c. The M1 model provided a reasonable description of the BTCs
for both MWCNTs (Fig. 2a) and TX100 (Fig. 2b) at different concen­
trations of TX100 (Table 2). Values of the depth-dependent retention
coefficient (k1M) and the normalized maximum solid phase concentra­tion (Smax
M /Co(M)) for MWCNTs initially decreased as the TX100

3.3. Transport and retention of MWCNTs and TX100
Bench-scale column tests were conducted to investigate the transportand retention behavior of MWCNTs (Co(M) = 5 mg L− 1) in the presenceof TX100 (Co(T) = 0–50 mg L− 1). The experimental conditions, including
mass balance information for all column experiments, are presented inTable 1. The total recovered mass (Mtotal) from the BTCs and RPs of
MWCNTs were all greater than 92%.
Fig. 2a presents observed BTCs for MWCNTs in QS in the presence ofvarious concentrations of TX100 (0–50 mg L− 1). BTCs are plotted hereinas the normalized effluent concentration (CM/Co(M)) versus PVs. The
value of Meff increased from 17.5% to 75.9% as the TX100 concentra­
tions increased from 0 to10 mg L− 1 (Fig. 2a, Table 1). When Co(T)increased from 20 m to 50 mg L− 1 (Fig. 2a, Table 1), the normalized
effluent concentrations of MWCNTs decreased from 17.5% to 4.1%. Thisobservation suggests that there was a critical Co(T) that corresponded tothe maximum transport of MWCNTs in QS. The transport of MWCNTs
increased when Co(T) was smaller than the critical concentration (e.g.,
10 mg L-1) and decreased when Co(T) was greater than the criticalconcentration.
Fig. 2b presents corresponding normalized BTCs (CT/Co(T)) for
TX100 (5–50 mg L− 1) in QS in the absence and presence of MWCNTs(Fig. 2a). TX100 exhibited significant amounts of breakthrough in theabsence of MWCNT (e.g., MT > 92.3% in Table 1). In contrast, BTCs of
TX100 and MT decreased with increasing Co(T) in the presence of
MWCNTs. This indicates that MWCNTs strongly inhibited the transportand enhanced the retention of TX100 in QS, especially at lower con­centrations of TX100. A significant fraction of TX100 was adsorbed onto
the MWCNT surfaces during co-transport (> 30.1% when Co(T)= 20 mg L− 1, Table 1), and a small fraction of TX100 was adsorbed onto
QS (< 7.7% when Co(T) = 10 mg L− 1, Table 1).
Fig. 2c presents observed RPs for MWCNTs in QS in the presence ofvarious concentrations of TX100 (0–50 mg L− 1). Here RPs are plotted as
normalized solid phase concentrations (S/Co(M)) versus column depth.
The corresponding BTCs for MWCNTs and TX100 were given in Fig. 2aand b, respectively. The MWCNT RPs exhibited a non-monotonic shape
regardless of the TX100 concentration. In contrast, most previoustransport studies with MWCNTs have reported that RPs exhibited a
hyper-exponential shape (Zhang et al., 2016a, 2017). The depth of
maximum retention of MWCNTs was close to the column’s inlet in theabsence of TX100. In contrast, there was significant remobilization ofretained MWCNTs as Co(T) increased (Fig. 2c). The depth of maximum
retention of MWCNTs first shifted down-stream (close to the outlet) andthen moved back up-stream (close to the inlet) as Co(T) increased. The
concentration of TX100 impacted not only the extent but also the shapeof the MWCNT RPs, suggesting that the governing retention mechanisms
shifted dynamically depending on the abundance of TX100 in suspen­sion. Non-monotonic RPs of colloids have previously been observed andattributed to surface charge heterogeneity of colloids (Li et al., 2004),
secondary energy minimum (Petosa et al., 2010; Tufenkji and Elimelech,2005), chemical and physical heterogeneities of porous media (Bradford
and Torkzaban, 2012; Wang et al., 2012), colloid distribution properties(Bradford et al., 2006; Chao et al., 2016), hydrodynamic conditions(Bradford et al., 2011), solid-phase colloid migration (Yuan and Shapiro,
2011), competitive blocking (Becker et al., 2015), and reversible
blocking (Leij et al., 2016). The above results clearly showed that in­teractions between MWCNT and TX100 contributed to the developmentof non-monotonic RPs. However, other factors may have also played arole, but the detailed determination of the underlying cause forFig. 3. The mass ratio of retained MWCNTs and retained surfactant (TX100 orSDBS) in co-transport experiments at different concentrations of TX100 or
SDBS. The retained TX100 equals the mass recoveries of TX100 from the solid
phase in co-transport experiments minus the mass recoveries of surfactant in QS
in SST (10 mg L− 1); The retained MWCNTs equals the mass recoveries of
MWCNTs from the solid phase in co-transport experiments minus the mass
recoveries of MWCNTs in QS in SST.
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Journal of Hazardous Materials 407 (2021) 124874

Table 2Fitted model parameters.
Co (M)[mg L− 1]

Co (T)[mg L− 1]

Model

Smax
M /Co (M)[cm3 g-1]

ΓM
[-]

k1M
[min− 1]

Smax
T /Co (T)[cm3g− 1]

ΓT
[-]

k1T
[min− 1]kdT[min− 1]

R2BTC

R2RP

R2T BTC

5
0
0
5

0
10
20
5

5

10

5

20

5

50

SST
SST
SST
M1
M2
M1
M2
M1
M2
M1
M2

1.35
NA
NA
0.60
0.60
0.21
0.21
1.65
1.65
1.66
1.66

NA
NA
NA
0
0.08
0
0.09
0
0.10
0
0.11

13.00
NA
NA
10.55
10.55
5.99
5.99
20.71
20.71
27.77
27.77

NA
1.02
0.99
0.53
0.53
0.45
0.45
0.32
0.32
0.31
0.31

NA
NA
NA
0
0.02
0
0.03
0
0.25
0
0.19

NA
0.43
0.42
0.26
0.26
0.21
0.21
0.14
0.14
0.09
0.09

NA
4.3E-01
4.2E-01
3.1E-03
3.1E-03
4.4E-03
4.4E-03
4.7E-03
4.7E-03
6.8E-03
6.8E-03

0.97
NA
NA
0.99
0.99
0.99
0.99
0.92
0.92
0.99
0.99

0.88
NA
NA
0.95
0.95
0.35
0.35
0.59
0.58
0.15
0.15

NA
0.98
0.98
0.95
0.95
0.77
0.77
0.90
0.90
0.91
0.91

Co(M) and Co(T) are the input concentrations of MWCNTs and TX100, respectively; SST is the simulated model based on single-species transport of MWCNTs or TX100;
k1M is the first-order retention rate coefficient of MWCNTs; kdM (= 1.0E-04 min− 1) is the first-order release rate coefficient of MWCNTs; Smax
M /Co(M) is the normalized
maximum solid phase concentration of deposited MWCNTs; k1T is the first-order retention rate coefficient of TX100; kdT is the first-order release rate coefficient of
TX100; Smax
T /Co(T) is the normalized maximum solid phase concentration of deposited TX100; Γ M is the area conversion factor between MWCNTs and TX100; Γ T is thearea conversion factor between TX100 and MWCNTs; R2BTC, R2RP, and R2TBTC reflect the correlation of observed and fitted data for BTCs of MWCNTs, RPs of MWCNTs,
and BTCs of TX100; and NA denotes not applicable.

concentration increased from 0 to 10 mg L− 1 and then increased with anincrease in the TX100 concentration from 20 m to 50 mg L− 1 (Table 2).
In addition, both values of k1T and Smax
T /Co(T) for TX100 decreased withan increase in the TX100 concentration from 5 to 50 mg L− 1, suggesting
the dependence between the attachment affinity of MWCNTs and theavailability of TX100 in quartz (Table 2).
The M1 and M2 models provided a less than satisfactory descriptionof the MWCNT RPs. Elimination of the depth-dependent retention by
setting the depth-dependent parameter β = 0 did not improve thedescription of the RPs (data not shown). The fitted values of detachment
coefficients (kdM and kdT) were also small, but the non-monotonic RPs
suggests that reversibly retained MWCNTs were being transported on
the solid phase in the presence of TX100. Fitted values of Γ M(0.081–0.109) and Γ T (0.015–0.253) for the co-transport experimentwith TX100 were larger than those for SDBS (4.16E-04 – 0.166) whenusing the M2 model (Zhang et al., 2019). This observation suggests thatcompetitive blocking played a more important role in enhancing
MWCNT transport in the presence of TX100 than in the presence of
SDBS.
It is commonly known that the presence of a surfactant can enhance
the transport of engineered nanoparticles (Lu et al., 2014; Zhang et al.,2019), and interaction energy calculations have been used to explainsuch phenomena (Jin et al., 2015; Zhang et al., 2016b). Fig. S6 presents
the total interaction energy (Φs) between MWCNTs and QS in thepresence of different TX100 concentrations when considering observedchanges in hydrodynamic radius and zeta potentials. The observed
non-linear and non-monotonic impact of TX100 on MWCNTs retention(Figs. 2 and 3) cannot be explained by these interaction energy calcu­
lations. For example, the interaction energy calculations predicted only
a minor difference in the energy barriers (~ 17.2%, Fig. S6) when Co(T)increased from 0 to 50 mg L-1. In contrast, observed MWCNT retention
behavior changed by ~ 298% (Fig. S7 and Table 1, calculated by themass recovery of MWCNTs at 10 and 50 mg L− 1 in the effluent). In
addition, the energy barrier first increased, achieved a maximum (for Co− 1(T) = 20 mg L ), and then decreased when Co(T) increased from− 1
0–50 mg L . The maximum and minimum retention of MWCNTs ispredicted to occur when the energy barrier is smallest (Co(T) = 0 mg L− 1)
and largest (Co(T) = 20 mg L− 1), respectively. In contrast, the minimum
and maximum retention of MWCNTs was experimentally observed tooccur when Co(T) = 10 and 50 mg L− 1, respectively. These discrepancies
suggest that conventional interaction energy calculations are inadequate
to explain the observed retention behavior. Inclusion of other factors(nanoscale chemical heterogeneity and roughness, and particle shape,
interior, and orientation with surface) and interactions (e.g., steric, hy­dration, and hydrophobic) may improve the descriptive ability ofinteraction energy calculations for MWCNT retention, but increases thenumber and variability of parameters that need to be fitted or measured(Jin et al., 2017; Ninham and Boström, 2006). The predictive ability ofinteraction energy calculations and the colloid filtration theory may belost because of increasing parameter uncertainty (Ninham and Yamin­sky, 1997).
3.4. Comparison of TX100 and SDBS behavior on MWCNTs
Zhang et al. (2019) studied the influence of various concentrations of
the anionic surfactant SDBS on the co-transport of MWCNTs. Below wecompare these results with those for the nonionic surfactant TX100 and
MWCNTs (Fig. 2) in the same QS and hydrodynamic conditions. The
main difference is therefore due to the surfactant type.
Fig. 4a presents a bar graph of Meff for MWCNT in QS as a function of
surfactant concentration. Both TX100 and SDBS influenced Meff for
MWCNT in a similar manner when the surfactant concentration was lessthan 10 mg L− 1. In particular, the value of Meff for MWCNT rapidly
increased from about 17% in the absence of surfactant to a value > 75%
when the surfactant concentration equaled 10 mg L− 1. In contrast,
TX100 and SDBS had an opposite influence on Meff for MWCNT at higher
surfactant concentrations. Specifically, the value of Meff for MWCNT
increased and plateaued near 90% when the SDBS concentration wasincreased from 10–50 mg L− 1, whereas Meff for MWCNT decreased to
4% when the TX100 concentration was increased to 50 mg L− 1. Theseobservations indicate that governing retention mechanisms for
MWCNTs remained fairly stable with increasing SDBS concentration but
changed with increasing TX100 concentration. Potential explanations
for these non-linear impacts of TX100 on the retention of MWCNTs in QS
will be discussed in detail below.
Fig. 4b also presents values of Meff for the surfactants (TX100 andSDBS) as a function of the surfactant concentration in the presence andabsence of MWCNTs. SDBS exhibited high mobility in both the presence
and absence of MWCNTs in QS. In contrast, TX100 was significantly
retained in the presence of MWCNTs. This difference was attributed tothe stronger interaction/binding between MWCNTs for TX100 than
MWCNTs and SDBS. The binding energies between MWCNTs and
TX100/SDBS were calculated using molecular dynamic (MD) simula­tions (Fig. 5) to investigate the interaction between TX100 and MWCNTs
further. The binding energies of TX100 and SDBS with MWCNTs were
− 99.12 ± − 3.82 kJ mol− 1 and − 58.47 ± − 1.96 kJ mol− 1, respec­tively, indicating that TX100 could interact with MWCNTs stronger than
SDBS, thus forming strong and stable binding with MWCNTs. These
calculations were supported by comparing TX100 and SDBS equilibrium
adsorption (Fig. 1) and column effluent (Fig. 4) results.
6

M. Zhang et al.

Journal of Hazardous Materials 407 (2021) 124874

Fig. 4. Summary of observed results of mass recoveries in the effluent (Meff, %) during SST and co-transport of MWCNTs (a, dark blue and black rectangles withdifferent concentrations of TX100 and SDBS (0–50 mg L− 1), respectively) and TX100/SDBS (b, light blue and light gray rectangles with different concentrations of
MWCNTs (0 or 5 mg L-1)) in QS. (a) The mass recoveries of MWCNTs in the effluent (Meff, %) at 0–50 mg L− 1 surfactant (TX100 or SDBS); (b) The mass recoveries of
surfactant (TX100 or SDBS) in the effluent (Meff, %) at 0 or 5 mg L− 1 MWCNTs. The concentration of MWCNTs and surfactant (TX100 or SDBS) in SST (Blank-0) is 5
and 10 mg L− 1, respectively. Some of the transport data of SDBS were based on the recent study (Zhang et al., 2019). (For interpretation of the references to color inthis figure legend, the reader is referred to the web version of this article.).
Fig. 5. (a) Interactions between
MWCNTs at various concentrations of
TX100 based on the MD simulation,d is the mean distance between thecentroids of two MWCNTs; (b) The
hydrogen bonding between MWCNTs
and TX100 according to the MD
simulation. Schematic diagrams (c-d)
of interactions between MWCNTs and
QS in the presence of TX100. (c) The
schematic mechanism for a positiveeffect of TX100 on MWCNTs in QS; (d)The schematic mechanism for a nega­tive effect of TX100 on MWCNTs in
QS. Red is oxygen, white is hydrogen,and light blue is carbon. The solvent of
KCl and water molecular has been
hidden for a better observation. (Forinterpretation of the references tocolor in this figure legend, the reader
is referred to the web version of thisarticle.).

The CMC of TX100 in 1 mM KCl was determined to be 30 mg L− 1
(Fig. S1). However, numerous studies have indicated that premicellar
aggregation was observed for surfactants at a much lower CMC con­centration (Cui et al., 2008; Menger and Littau, 1993). That is to say, themonomers, premicelles, and micelles coexisted in the solution, and thesize of premicelles could grow as the concentration of surfactant
increased (Cui et al., 2008). As a result, TX100-TX100 interactions act as“glue” and provide additional attachment sites between the
TX100-MWCNT and TX100-QS surface. The MD simulation in Fig. 5aalso showed that the mean distance between the centroids of MWCNTs
first increased (from 6.398 to 6.904 nm) at a lower concentration of

TX100 and then decreased (from 6.904 to 6.018 nm) when overcrowded
TX100 existed. These findings are consistent with the enhanced hydro­
dynamic radii of MWCNTs when the concentration of TX100 was equal
to 20 and 50 mg L− 1 (Fig. S3b). The presence of TX100 also induced apositive effect on the MWCNTs retention in QS (Fig. 3) when Co(T)equaled 20 or 50 mg L− 1. Under these conditions, most of the MWCNT
surfaces should be surrounded by TX100 (Fig. 5d). Redundant TX100
could form a bilayer or surfactant aggregates (“hemimicelles”) on the
MWCNTs surface (Li et al., 2009), resulting in stronger intermolecularadhesive force due to these hydrophobic surfaces (Boo et al., 2018;
Tiraferri et al., 2012).
7

M. Zhang et al.

Journal of Hazardous Materials 407 (2021) 124874

All these results suggested that redundant or overcrowded TX100
could deteriorate the dispersion and resulted in the aggregation of
MWCNTs (Han et al., 2008; Wang et al., 2004). Note that when an
excessive number of hydrophilic groups of TX100 was available in thesystem, the hydrogen bonding could be generated between MWCNTs
and TX100 (Fig. 5b), suggesting that the hydrophilic groups of MWCNTs
interacted with TX100 and therefore resulted in more aggregation. Last
but not least, the excess amount of TX100 might overturn the surface of
QS and MWCNTs from hydrophilic towards hydrophobic, thus effec­
tively enhancing the aggregation of MWCNTs but also the retention on
the QS surface. Some recent studies conducted by Elimelech andco-workers demonstrated using the colloidal-AFM technology that in­teractions between the hydrophobic-hydrophobic surface might besignificantly stronger than those between hydrophilic-hydrophobicgroups (Boo et al., 2018; Tiraferri et al., 2012).
In summary, a critical input concentration of TX100 (Co(T) lower thanCMC) corresponds to the maximum transport of MWCNTs in QS. The
enhancement and inhibition of the retention of MWCNTs on QS is a
result of the balance of attractive and repulsive forces between MWCNTs
and QS due to adsorbed TX100 (Fig. 5c and d).

the work reported in this paper.
Acknowledgments
Fundings were provided by the National Key R&D Program of China(Project No. 2018YFD0800700), the 111 Project (Project No. B18060),
and the National Natural Science Foundation of China (Project Nos.
41701547, 42077342, 42007334). The authors would like to acknowl­edge Stephan Köppchen for bromide measurement. Thanks to Herbert
Philipp and Claudia Walraf for their technical assistance.
Appendix A. Supporting information
Supplementary data associated with this article can be found in the
online version at doi:10.1016/j.jhazmat.2020.124874.
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4. Conclusions
Surfactants are commonly used to disperse colloids and thus facili­tate colloid transport in porous media. Such enhanced transport depends
not only on the type of surfactants but also on their relative ratio to thetargeted colloid. The nonionic surfactant TX100 (from lower to higher
than the CMC of TX100) contributed to the retention of MWCNTs in a
non-linear, non-monotonic manner. In contrast, the anionic surfactant
SDBS (lower than the CMC of SDBS) produced a monotonic response to
MWCNT retention in porous media. There is a critical TX100 concen­
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philic interactions. MWCNTs also strongly inhibited TX100 transport in
QS due to the strong affinity of TX100 for MWCNTs. Other factors suchas adsorption of the surfactant on the colloid and the collector, aggre­
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dynamically with the ratio between surfactant and MWCNTs, must becomprehensively considered to better predict particle retention in thepresence of surfactants. Potential implications are i) surface modifica­tion of other colloids and nanoparticles by nonionic surfactants may
potentially be exploited to deliver them to desired locations (e.g., bio­
char, hydroxyapatite), ii) leaching colloidal contaminants (e.g., micro­
plastic) by nonionic surfactant for remediation purposes may be
conducted, and iii) the inadvertent release of nonionic surfactant may
increase the risk of colloid contamination (e.g., pathogenic microor­ganisms). Therefore, these findings provide new insights into the effects
of nonionic surfactants on the fate of colloids or nanoparticles in thesubsurface and further suggest their roles in remediation scenarios andcontamination risks.
CRediT authorship contribution statement
Miaoyue Zhang: Project administration, Investigation, Software, andWriting - original draft. Scott A. Bradford: Investigation, Formal anal­ysis, Software, Writing - Review & Editing. Erwin Klumpp: Conceptu­
alization, Supervision, Data Curation, and Review & Editing. Jirka
Šimůnek: Software, Review & Editing. Chao Jin: Conceptualization,
Data Curation, and Writing - Review & Editing. Rongliang Qiu:
Conceptualization, Supervision, and Review & Editing.
Declaration of Competing Interest
The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to influence8M. Zhang et al.

Journal of Hazardous Materials 407 (2021) 124874

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