pubs.acs.org/est

ArticleSignificance of Non-DLVO Interactions on the Co-Transport ofFunctionalized Multiwalled Carbon Nanotubes and Soil
Nanoparticles in Porous Media
Miaoyue Zhang, Scott A. Bradford, Erwin Klumpp, Jiri Š imůnek, Shizhong Wang, Quan Wan, Chao Jin,*and Rongliang Qiu

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ABSTRACT: Derjaguin−Landau−Verwey−Overbeek (DLVO) theory is typicallyused to quantify surface interactions between engineered nanoparticles (ENPs), soil
nanoparticles (SNPs), and/or porous media, which are used to assess environmental
risk and fate of ENPs. This study investigates the co-transport behavior offunctionalized multiwalled carbon nanotubes (MWCNTs) with positively (goethite
nanoparticles, GNPs) and negatively (bentonite nanoparticles, BNPs) charged SNPsin quartz sand (QS). The presence of BNPs increased the transport of MWCNTs, but
GNPs inhibited the transport of MWCNTs. In addition, we, for the first time,observed that the transport of negatively (BNPs) and positively (GNPs) charged
SNPs was facilitated by the presence of MWCNTs. Traditional mechanisms
associated with competitive blocking, heteroaggregation, and classic DLVO
calculations cannot explain such phenomena. Direct examination using batch
experiments and Fourier transform infrared (FTIR) spectroscopy, asymmetric flow
field flow fractionation (AF4) coupled to UV and inductively coupled plasma mass spectrometry (AF4-UV-ICP-MS), and molecular
dynamics (MD) simulations demonstrated that MWCNTs-BNPs or MWCNT-GNPs complexes or aggregates can be formed duringco-transport. Non-DLVO interactions (e.g., H-bonding and Lewis acid−base interaction) helped to explain observed MWCNT
deposition, associations between MWCNTs and both SNPs (positively or negatively), and co-transport. This research sheds novel
insight into the transport of MWCNTs and SNPs in porous media and suggests that (i) mutual effects between colloids (e.g.,heteroaggregation, co-transport, and competitive blocking) need to be considered in natural soil; and (ii) non-DLVO interactions
should be comprehensively considered when evaluating the environmental risk and fate of ENPs.
KEYWORDS: multiwalled carbon nanotubes, soil nanoparticles, colloid-facilitated transport, molecular dynamics simulation,
asymmetric flow field flow fractionation■

INTRODUCTION
Carbon nanotubes (CNTs) are allotropes of carbon with acylindrical-shaped nanostructure1 that have unique electric,chemical, and physical properties. CNTs have been employedin numerous commercial applications and as adsorbents forenvironmental remediation and water treatment,2−6 which will
eventually result in their release into the subsurface.7 Current
studies have investigated the transport behavior of CNTs inporous media under various physical and chemical conditions,
including ionic strength (IS), water content, porous medium
grain size, input concentration of CNTs, surfactants, andorganic matter.8−13 However, information on the co-transportof CNTs and soil colloids or soil nanoparticles (SNPs), as wellas interactions of CNTs with soil colloids or SNPs is still
limited.
SNPs (e.g., clay minerals and iron oxides), which areabundant in the Earth’s critical zone14,15 and the smaller size
fractions (<100 nm in at least one dimension) in soil colloids,© 2022 American Chemical Society

can serve as carriers for contaminants and result in colloidfacilitated contaminant transport.16 Colloid-facilitated contaminant transport has been demonstrated to be one of the criticalpathways for the long-distance transport of contaminants insoil and groundwater. Such processes are mainly governed byinteractions between colloids and dissolved contaminants likeheavy metals, rare earth elements, and organic pollutants. A
few recent studies have demonstrated that soil colloids also
facilitate the co-transport of other colloids (e.g., engineered
nanoparticles (ENPs) and biocolloids), such as titanium
dioxide nanoparticles with clay particles,17 bacteria with
Received: January 28, 2022
Revised: June 8, 2022
Accepted: June 8, 2022
Published: June 22, 2022

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hematite,18 viruses with clay colloids,19−21 and plastic particles
with iron oxides.22,23 Clay minerals and iron oxides arecommon SNPs that ENPs can encounter in soil. However, theco-transport of ENPs and SNPs has received limited attention.
Mechanisms explaining the unique deposition behavior of
CNT in the presence of SNP in porous media are still notavailable in the literature.
The unique chemical and physical properties are commonly
introduced on the surface of ENPs when they are
manufactured (e.g., material doping, modification) byregulating surface moieties or functional groups to achieve
designed functionality (e.g., superhydrophobic/hydrophilic,antifouling, self-cleaning, etc).24,25 In contrast, SNPs aremuch more complex than ENPs because of the presence ofboth roughness and charge heterogeneity. In addition to vander Waals (VDW) and electrical double-layer (EDL)
interactions, the formation of SNP−ENP associations may
also be impacted by H-bonding and Lewis acid−baseinteractions.26−28 However, only a few studies have attempted
to differentiate the relative contribution of these interactions
on aggregation and retention processes in porous media.
Most previous studies17,29 attempted to interpret thedeposition of ENPs in porous media using coulombic
interactions (e.g., negative vs positive charge interactions),
whereas competitive blocking was regarded as the main
mechanism for enhanced transport of colloids.22,30,31 Additionally, investigations on the effect of soil colloids (e.g., microsized clay minerals or iron oxides) on the transport andretention of ENPs in porous media were frequently conducted
at high input concentrations of ENPs and low concentrationsof soil colloids.22,30 Such studies ignored the fact that the total
concentration of colloids/SNPs in soil is significantly higher
than the discharged concentration of ENPs.
DLVO theory assumes that colloid aggregation andretention are mainly controlled by interactions that arise
from VDW and EDL forces. The transport behavior of colloids
can sometimes be reasonably described by quantifying theseinteractions.22,32,33 For example, heteroaggregation between
carbon nanoparticles and mineral colloids resulted in
sedimentation of carbon nanoparticles due to reduced
electrostatic repulsion.26,34 However, some recent studies
indicated that ENPs (e.g., CNTs) could exhibit different
transport behavior from classic colloid filtration theory (CFT)and DLVO theory.27,35 For example, Katzourakis andChrysikopoulos indicated that aggregation could contributeto the attachment of ENPs in porous media.33 Liu et al.27 andYang et al.28 indicated that chemical bonds were formed
between carbon dots and minerals, as well as biochar andbentonite, in batch and aggregation experiments, respectively.
Soil colloids and ENPs were also found to be strongly
associated during transport experiments, even under variableflow conditions.36 It was hypothesized that attachment/
detachment and aggregation of ENPs might be influenced byother surface interactions such as H-bonding, Lewis acid−baseinteractions/reactions, ligand exchange, and other chemical
reactions. DLVO interactions are weakly or nondirectional,
whereas non-DLVO interactions are commonly orientationaldependent and preferentially associated with specific surfacefunctional groups.37 Co-transport has usually been attributed
to the strong affinity between soil colloids and ENPs, but has
neglected the role of non-DLVO interactions (e.g., H-bonding,Lewis acid−base, and ligand exchange). Interaction, association, and co-transport of ENPs and soil colloids/SNPs are

Articlecomplex, and there are still many questions. For example, if
heteroaggregation occurs during the co-transport of ENPs andsoil colloids/SNPs, will the transport of ENPs be facilitated or
inhibited? Can attached ENPs contribute to the retention ofsoil colloids/SNPs in porous media?
The objective of this study is to investigate mechanisms thatgovern the co-transport and retention of functionalized
MWCNTs (1 mg L−1) and SNPs. Breakthrough curves(BTCs) and retention profiles (RPs) for both MWCNTs
and negatively charged bentonite nanoparticles (BNPs, at 0−10 mg L−1) or positively charged goethite nanoparticles(GNPs, at 0−4 mg L−1) were determined in column tests.
Mechanisms that contribute to the co-transport and competitive blocking behaviors were quantified numerically using
the HYDRUS-1D computer code. Direct experimental
evidence was obtained to identify the association between
MWCNTs and SNPs using batch experiments, transmission
electron microscopy (TEM), asymmetric flow field flow
fractionation (AF4) combined with UV and inductively
coupled plasma mass spectrometry (AF4-UV-ICP-MS), as
well as Fourier transform infrared (FTIR) spectroscopy.
Classic DLVO calculations and molecular dynamics (MD)simulations were conducted and compared to elucidate further
the role of non-DLVO interactions between SNPs and
MWCNTs on their deposition in porous media. Such analysis
provides essential knowledge and a research roadmap toevaluate the environmental risks of MWCNTs and otheremerging ENPs in natural environments.

■

MATERIALS AND METHODS

Carbon Nanotubes, Bentonite Nanoparticles, andGoethite Nanoparticles. Radioactively (14 C) labeled
MWCNTs (Bayer Technology Services GmbH, Leverkusen,
Germany) with a median diameter of 10−15 nm and a medianlength of 200−1000 nm38 were used in this study. Moreinformation on the synthesis, functionalization, and characterization of these MWCNTs is available in the literature.13 The
functionalization of MWCNTs resulted in the addition ofoxygen-containing groups (e.g., carboxylic groups) to theirsurface. Bentonite and goethite colloids were purchased from
Sigma-Aldrich Chemie GmbH (Munich, Germany). Moreinformation on the preparation of BNPs and GNPs issummarized in Section S1. Briefly, the prepared BNPs had adiameter of 5−200 nm (Figure S1a), and GNPs had a diameterof 5−120 nm and a length of 60−800 nm (Figure S1b). The
MWCNTs (0 and 1 mg L−1) and BNPs (0, 4, and 10 mg L−1)
or GNPs (0, 2, and 4 mg L−1) suspensions were prepared in IS= 1 mM KCl (pH = 5.4). The suspension of MWCNTs and/or
SNPs (BNPs or GNPs) was ultrasonicated for 15 min at 65 W
and again for 10 min before characterization and column
experiments discussed below. The concentration of 14C-labeled
MWCNTs was determined using a PerkinElmer (Rodgau)
liquid scintillation counter (LSC). Radioactively (14C)-labeled
MWCNTs are stable, and the attenuation of the radio signal
during the column experiments (<1 h) could be neglected. The
concentrations of BNPs and GNPs were determined from themeasurement of Al and Fe concentrations, respectively, by
inductively coupled plasma mass spectrometry (ICP- MS,
Agilent 7500) after digestion and dilution.
The hydrodynamic radius of the MWCNTs suspensions in
IS = 1 mM KCl at different concentrations of BNPs (0, 4, and10 mg L−1) or GNPs (0, 2, and 4 mg L−1) was measured using
a Zetasizer Nano (Malvern Instruments GmbH, 71083

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ArticleTable 1. Experimental Conditions and Mass Recoveries from Effluent for All Column Experiments; D50 = 240 μma
Co(M) [mg L−1]

Co(b) [mg L−1]

Co(g) [mg L−1]

q [cm min−1]

IS [mM]

Por.

Me_M [%]

Ms_M [%]

Mt_M [%]

Me_S [%]

Ms_S [%]

Mt_S [%]

1
0
0
1
1
1
1

0
4
0
4
10
0
0

0
0
4
0
0
2
4

0.72
0.71
0.71
0.71
0.71
0.71
0.72

1 K+
1 K+
1 K+
1 K+
1 K+
1 K+
1 K+

0.45
0.45
0.44
0.46
0.43
0.45
0.46

15.7
NA
NA
18.5
23.1
1.2
1.1

76.2
NA
NA
75.5
70.6
96.3
99.9

91.9
NA
NA
94.0
93.7
97.5
101.0

NA
24.9
8.8
31.7
40.5
20.2
21.4

NA
70.2
87.9
60.3
55.0
75.7
74.3

NA
95.1
96.7
92.0
95.5
95.9
95.7

a

NA denotes not applicable. Por. is the porosity of the column. Co(M), Co(b), and Co(g) are the input concentrations of MWCNTs, BNPs, and GNPs,
respectively. q is the Darcy velocity. Me_M, Ms_M, and Mt_M are the effluent percentage, retained percentage, and total percentage of MWCNTs
recovered from the column experiment, respectively. Me_S, Ms_S, and Mt_S are the effluent, solid, and total percentage of SNPs (BNPs or GNPs)
recovered in the column experiments, respectively.

Herrenberg, Germany) immediately after suspension preparation and after 1 h. This information was used to determine thestability of these suspensions.39,40 In particular, the hydrodynamic radii of all suspensions were within the same range at
0 and 1 h, which indicates that these suspensions were stable
during this time interval. The release of Al and Fe ions was also
determined to be negligible after the preparation of BNPs and
GNPs suspensions at 1 h.
Interaction Energy Calculations. The approach of
Bradford and Torkzaban41 was used to calculate the totalinteraction energy (Φ) between a planar quartz surface and aspherical colloid with similar properties to MWCNTs in thepresence of various concentrations of BNPs or GNPs in KCl
solution with an IS = 1 mM. The total interaction energies
between MWCNTs, MWCNTs and BNPs, and MWCNTs and
GNPs were also performed to help explain the aggregation
behavior between them. Other non-DLVO interactions (e.g.,steric forces, hydration effects, and Lewis acid−base forces)were not considered. Details pertaining to these calculations
are given in Section S2.
Batch Experiments. Batch experiments were conductedusing SNPs (BNPs or GNPs) and MWCNTs in accordancewith the Organization for Economic Cooperation andDevelopment (OECD)�guideline 106.42 Section S3 provides
details about the batch experiments. In brief, batch experiments were carried out under quasi-equilibrium conditions43,44
in 1 mM KCl solution. FTIR spectroscopy (Nicolet 6700,
Thermo Fisher) was conducted after batch experiments tocharacterize the associations between SNPs (BNPs or GNPs)
and MWCNTs.
Co-Transport Experiments. A stainless-steel column with
3 cm inner diameter and 12 cm length was uniformly wet
packed with purified quartz sand (QS, median grain size of 240μm).11,43 Approximately 30 pore volumes (PVs) of background electrolyte solution (1 mM KCl) were injected at aconstant Darcy velocity of 0.71−0.72 cm min−1 to equilibrate
the column before initiating an experiment.
A non-reactive (conservative) tracer experiment was
conducted to characterize the column’s hydraulic conditions.
Concentrations of bromide in the effluent were determinedusing a high-performance liquid chromatograph (STH 585,
Dionex, Sunnyvale, CA) equipped with a UV detector(UV2075, Jasco, Essex, U.K.). Transport experiments using
MWCNTs (0 and 1 mg L−1) and SNPs (0, 4, and 10 mg L−1
BNPs or 0, 2, and 4 mg L−1 GNPs) in 1 mM KCl solution
were conducted in a similar manner as the conservative tracer.
Single-particle ICP-MS has been demonstrated to quantify theenvironmental concentrations of metal nanoparticles,45−47 but

this methodology cannot determine concentrations of carbonbased nanoparticles. The input concentrations of MWCNTs
and SNPs were selected based on the results of preliminary
aggregation experiments with MWCNTs and SNPs (data notshown). An input concentration of 1 mg L−1 of MWCNTs was
employed to obtain high accuracy in transport studies. The
RPs of MWCNTs and SNPs (BNPs or GNPs) in column
studies were determined following the recovery of BTCs andexcavation of QS in 1 cm increments. The concentrations of
MWCNTs and BNPs or GNPs in the effluent and sand were
determined using the LSC and ICP-MS, respectively.
All BTCs are plotted herein as normalized effluent
concentrations (C/Co; where Co is the influent suspension
concentration) vs pore volumes. All RPs are given herein as
normalized solid-phase concentration (S/Co) as a function of
distance from the column inlet. Experiments were replicatedand exhibited good reproducibility. A summary of theexperimental conditions, including Darcy velocity and massbalance information, is provided in Table 1. The total massbalance for MWCNTs (Mt_M) and SNPs (Mt_S) in the column
experiments was very good (>91%, Table 1).
Numerical Modeling. A modified version of the
HYDRUS-1D computer code48 was employed to simulate
both the transport and retention of MWCNTs and SNPs
(BNPs or GNPs) in QS. The mass balance equations in the
aqueous and solid phases for MWCNTs are given as
CMjijD CM zyz
=
j
z
t
zk
z {
SM
=
t

MkMaC M

(vCM)
z

k C +
M Ma M

b

kMdSM
(1)

b

kMdSM

(2)

where D is the dispersion coefficient, CM is the aqueous phase
concentration, SM is the solid-phase concentration, v is thepore water velocity, kMa is the retention rate coefficient, kMd isthe detachment rate coefficient, z is the vertical distance, t is
the time, ρb is the bulk density, and θ is the porosity. The
parameter ψM is a dimensionless function to account for timeand depth-dependent retention and is given in this work as
ij
j
k

jj1
M = j

SM + MSS yzzijj d50 + z yzz
zz
zzjj
max
zj d
z
SM
{k 50 {

(3)max

where SM is the maximum solid-phase concentration, d50 is
the median grain size, ΓM is the area conversion factor between
SNPs (BNPs or GNPs) and MWCNTs, and β is an empiricalparameter that controls the shape of the retention profile. The
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ArticleTable 2. Fitted Model Parametersa
AICM
model

AICS

AICM+C

SMmax/Co [cm3 g−1]

M1

241.4

NF

1.689

M1

NF

−89.9

NF

M1

NF

291.2

NF

M1
M2

−329.1−326.9

1.639
1.639

M1
M2

−155.2−157.7

1.270
1.270

M1
M2

−279.1−285.0

1.734
1.734

M1
M2

−235.8−220.0

1.845
1.845

ΓM

kMa
[min−1]

SSmax/Co [cm3 g−1]

ΓS

Co (MWCNTs) = 1 mg L−1, Co (BNPs/GNPs) = 0 mg L−1, 1 mM KCl
NF
16.45
NF
NF
Co (MWCNTs) = 0 mg L−1, Co (BNPs) = 4 mg L−1, 1 mM KCl
NF
NF
2.264
NF
Co (MWCNTs) = 0 mg L−1, Co (GNPs) = 4 mg L−1, 1 mM KCl
NF
NF
2.881
NF
Co (MWCNTs) = 1 mg L−1, Co (BNPs) = 4 mg L−1, 1 mM KCl
NF
14.29
2.247
NF
2.35 × 10−3
14.29
2.247
7.57 × 10−4
Co (MWCNTs) = 1 mg L−1, Co (BNPs) = 10 mg L−1, 1 mM KCl
NF
14.12
1.724
NF
1.10 × 10−1
14.12
1.724
1.97 × 10−2
Co (MWCNTs) = 1 mg L−1, Co (GNPs) = 2 mg L−1, 1 mM KCl
NF
46.66
2.492
NF
3.25 × 10−3
46.66
2.492
1.61 × 10−1
Co (MWCNTs) = 1 mg L−1, Co (GNPs) = 4 mg L−1, 1 mM KCl
NF
47.11
2.402
NF
1.52 × 10−3
47.11
2.402
6.90 × 10−2

kSa
[min−1]

RMeff2

RMs2

RSeff2

RSs2

NF

0.987

0.908

NF

NF

10.72

NF

NF

0.989

0.981

22.91

NF

NF

0.620

0.993

9.88
9.88

0.993
0.993

0.971
0.971

0.986
0.986

0.980
0.980

9.65
9.65

0.984
0.984

0.995
0.995

0.940
0.941

0.971
0.974

14.32
14.32

0.94
0.942

0.980
0.977

0.654
0.680

0.996
0.996

14.08
14.08

0.974
0.973

0.941
0.941

0.899
0.899

0.990
0.990

a

SMmax/Co and kMa are the normalized maximum solid-phase concentration and the first-order retention rate coefficient of MWCNTs, respectively;
SSmax/Co and kSa are the normalized maximum solid-phase concentration and the first-order retention rate coefficient of SNPs (BNPs or GNPs),
respectively; NF denotes not fitted; RMeff2, RMs2, RSeff2, and RSs2 are the correlation of observed and fitted data for MWCNTs in the effluent,
MWCNTs in the solid phase, SNPs (BNPs or GNPs) in the effluent, and SNPs (BNPs or GNPs) in the solid phase, respectively. AICM and AICS
are the Akaike information criterion for MWCNTSs and SNPs (BNPs or GNPs) in the M1 model, respectively. AICM+S is the Akaike information
criterion for MWCNTSs and SNPs (BNPs or GNPs) in co-transport. ΓM is the area conversion factor between SNPs (BNPs or GNPs) and
MWCNTs. ΓS is the area conversion factor between MWCNT and SNPs (BNPs or GNPs). The fitted parameters of dispersion coefficient, kMd,
and kSd are in Table S2.

subscripts M and S on parameters indicate that they areassociated with MWCNTs and SNPs, respectively. Similar
equations are employed for SNPs when the subscript M isreplaced by S in eqs 1−3. Aggregation, particle size
distributions, and co-transport were assumed to play relatively
minor roles under the experimental conditions and were notaccounted for in the simulations, but the co-authors havedeveloped other models for this purpose.49,50
M1 and M2 models considering no and limited competitive
blocking, respectively, were used to simulate the co-transportof MWCNTs and SNPs in the column experiments.
Competitive blocking between MWCNTs and SNPs on the
QS was accounted for in the M2 model using a Langmuirian
blocking approach that was modified to include area
conversion factors between MWCNTs and SNPs, ΓM andΓS, respectively. The single-species transport of MWCNTs and
SNPs (BNPs or GNPs) were described by setting ΓM and ΓS tozero, respectively. The transport and retention parameters for
MWCNTs and SNPs (BNPs or GNPs) data sets wereindependently determined when using the M1 approach.
The M2 approach allows for competitive blocking by fixing theretention and release parameters to those determined from theM1 model, and then simultaneously optimizing values of ΓM
and ΓS to both MWCNTs and SNPs (BNPs or GNPs) data
sets. Parameters for model fitting are given in Tables 2 and S2,
along with the Pearson correlation coefficient (R2) and Akaike
information criterion (AIC),51 representing the goodness of fit.
More details about simulation equations are provided in
Section S4.
Online-Coupled AF4-UV-ICP-MS Analyses. The effluent
samples in co-transport experiments using MWCNTs (1 mg
L−1) and SNPs (4 mg L−1 BNPs or GNPs) in 1 mM KCl were

measured using transmission electron microscopy (TEM,
Hitachi SU8010, Japan), and AF4 (Postnova, Landsberg,
Germany) combined online with UV and inductively coupledplasma mass spectrometer (AF4-UV-ICP-MS). The solid
samples after batch experiments were diluted by 1 mM KCl
and sonicated, and then also measured by AF4-UV-ICP-MS.
The association between MWCNTs and SNPs, the hydrodynamic particle sizes, the intensities of UV, and theconcentrations of iron (Fe) and aluminum (Al) (proxies for
GNP and BNP, respectively) were determined using thisapproach. A 1 kDa polyethersulfone (PES) membrane and acarrier solution of 25 μM NaCl were used during themeasurement. To separate small particles, 1 mL from theeffluent sample was injected with a focus time of 20 min at a
cross-flow of 3 mL min−1. The particles were then separated bya linear cross-flow decrease for 40 min after focusing. The
largest particles were flushed last at a constant cross-flow of 0mL min−1 for 20 min. The particle size distribution of the AF4
separation was verified using latex standards with sizes of 20,
125, and 200 nm (from Postnova Analytics).52,53 Figure S2
shows blanks for single BNPs and GNPs suspensions in AF4UV-ICP-MS measurement (4 mg L−1, 1 mM KCl).
Molecular Dynamics Simulations. The all-atom MD
simulations were based on a Charmm36 force field54,55 andwere carried out using the Gromacs-4.6.7 software package.56
The time step was 2 fs, and the total run time was 10 ns NPT
for the equilibrium MD simulation. The relaxed system was
employed as a starting configuration. Energy minimization was
carried out prior to system relaxation with a composite
protocol of steepest descent using termination gradients of 100
kJ (mol·nm)−1. The Nose−Hoover thermostat57 was used tomaintain the equilibrium temperature at 298 K and 1 bar with10671

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ArticleFigure 1. Observed and fitted (M1 model) BTCs (a, c, e, g) and RPs (b, d, f, h) of MWCNTs and SNPs (BNPs or GNPs) with or without
additional SNPs in QS. The observed and fitted (M2 model) BTCs and RPs of MWCNTs and SNPs are shown in Figure S3. (a) BTCs of
MWCNTs with adding 0, 4, and 10 mg L−1 of BNPs; (b) RPs of MWCNTs with adding 0, 4, and 10 mg L−1 of BNPs; (c) BTCs of MWCNTs withadding 0, 2, and 4 mg L−1 of GNPs. (d) RPs of MWCNTs with adding 0, 2, and 4 mg L−1 of GNPs. (e) BTCs of BNPs with and without
MWCNTs at 4 and 10 mg L−1 of BNPs; (f) RPs of BNPs with and without MWCNTs at 4 and 10 mg L−1 of BNPs; (g) BTCs of GNPs with andwithout MWCNTs at 2 and 4 mg L−1 of BNPs. (h) RPs of GNPs with and without MWCNTs at 2 and 4 mg L−1 of BNPs; (i, j) mass ratio ofretained MWCNTs and retained BNPs and GNPs in co-transport experiments, respectively; (k) mass ratio of retained SNPs (BNPs or GNPs) andretained MWCNTs in co-transport experiments. The input concentration of MWCNTs was 1 mg L−1. The ionic strength was 1 mM KCl. The
Darcy velocity is 0.71−0.72 cm min−1.
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periodic boundary conditions imposed on all three dimensions.
The particle mesh-Ewald method58,59 was used to computelong-range electrostatics with a relative tolerance of 1 × 10−6.
A cutoff distance of 1.2 nm was applied to real-space Ewaldand van der Waals interactions. The LINCS algorithm60 was
applied to constrain bond lengths of hydrogen atoms. A leapfrog algorithm was used with a time step of 2 fs. The mean
distance between the centroids of MWCNTs, as well as thebinding energies and binding mechanism of MWCNTs, in thepresence of SNPs (BNPs or GNPs) were determined.

Article“favorable sites” on the surface of QS were rapidly filled under
the selected conditions. Increasing the concentration of GNPs
produced more inhibition of the transport of MWCNTs inpacked QS.
Enhanced Transport of BNPs and GNPs. The presenceof MWCNTs enhanced the transport of both the BNPs and
GNPs in the packed column. The mass percentage recoveredin the effluent for BNPs (Me_S, Figure 1e and Table 1)
increased from 24.9 to 31.7% when the MWCNTs Co
increased from 0 to 1 mg L−1. This was associated with adecrease in the solid-phase mass percentage of BNPs (Ms_S,
Figure 1f and Table 1). Similarly, the breakthrough of GNPs
increased from 8.8 to 21.4% (Figure 1g and Table 1), whereas
the corresponding GNPs solid-phase mass recovery (Ms_S,
Figure 1h and Table 1) decreased when the concentration of
MWCNTs increased. All of the BTCs for BNPs (Figure 1e)and most of the BTCs for GNPs (Figure 1g) were welldescribed using the M1 model (R2 > 0.94 and 0.62 for BNPs
and GNPs, respectively, in Table 2). Fitted values of kSa andSSmax/Co for BNPs decreased with increasing BNPs concentration. Fitted values of kSa and SSmax/Co for GNPs were high,but only slightly decreased with increasing GNPs concentration. Interestingly, fitted values of kSa and SSmax/Co weresometimes larger for negatively charged BNPs than that for
positively charged GNPs (Table 2). This observation indicatedthat electrostatically favorable conditions were not the only
factors contributing to the limited goethite retention. Zhang etal.43 previously found that not all of the surface area ofgoethite-coated sand contributed to MWCNT retention due tonanoscale roughness that creates shallow primary minimum
interactions. The observation of rapid blocking of goethite
colloids on QS was consistent with this finding. The values of
kSa and SSmax/Co for BNPs and GNPs were lower in thepresence than in the absence of MWCNTs (Table 2). The
corresponding RPs for both MWCNTs and SNPs exhibited
hyper-exponential shapes (Figure 1). This was accounted for in
the M1 model by using a depth-dependent retention function
with β = 0.765. Note that previous studies with MWCNTs
have attributed this depth-dependent retention behavior to
straining.61−63
The net mass of MWCNTs that was retained due to SNPs
(RM/S) and the net mass of SNPs that was retained due to
MWCNTs (RS/M) were quantified to evaluate mutual
contributions. Values of RM/S and RS/M were calculated using
eqs 4 and 5, respectively, as■

RESULTS AND DISCUSSION
Contribution of BNPs and GNPs to MWCNT Transport. Observed and simulated (M1 and M2 models) BTCs
and RPs of MWCNTs with and without the negatively charged
BNPs in the QS packed column are presented in Figure 1a,b.
MWCNTs exhibited similar breakthrough behavior in thepresence and absence of BNPs (Figure 1a); e.g., a breakthrough occurred after ∼1 PV, and then normalized effluent
concentration gradually increased with continuous injection of
MWCNTs. Co-injected of BNPs with MWCNTs resulted inhigher effluent concentrations of MWCNTs. The recovered
mass percentage of MWCNTs in the effluent increased from
15.7 to 23.1% when the Co of BNPs increased from 0 to 10 mg
L−1 (Figure 1a and Table 1), respectively. The effluent
concentrations of MWCNTs rapidly decreased to low tailingvalues (C/Co < 0.02) after the eluting suspension was switched
to a colloid-free solution. The asymmetric shape of the BTCs
was reasonably described by the implemented M1 model with
Langmuirian blocking (R 2 > 0.94 in Table 2). The
corresponding RPs for MWCNTs (Figure 1b), which exhibited
hyper-exponential shapes along the direction of flow injection,
were effectively simulated (R2 > 0.97 in Table 2) using the M1
model associated with a depth-dependent retention function(β = 0.765). It should be noted that fitted values of kMa andSMmax/Co all decreased with increasing BNP concentration(Table 1). Such results suggested that increasing concentrations of BNPs could facilitate MWCNT transport.
The observed and simulated BTCs and RPs of MWCNTs
with and without positively charged GNPs (in the packed
column) are presented in Figure 1c,d. The transport of
MWCNTs was diminished in the presence of GNPs (2 and 4
mg L−1) compared to ones without GNPs. In particular, themass percentage of MWCNTs that was recovered in theeffluent (Me_M, Figure 1c and Table 1) decreased from 15.7 to
1.1% when the input concentration of GNPs increased from 0
to 4 mg L−1, respectively. A higher GNP concentration was
also associated with an increase in the solid-phase masspercentage (e.g., 76.2−99.9%) for MWCNTs (Table 1 andFigure 1d). The BTCs for MWCNTs in the presence of GNPs
(Figure 1c) (R2 > 0.94 in Table 2) and the RPs for MWCNTs(Figure 1d) and GNPs (R2 > 0.91 in Table 2) were also welldescribed using the M1 model. Note that fitted values of kMa
were very large in the presence of GNPs (Table 2), and this
delayed the breakthrough of MWCNT until blocking
decreased the number of available retention sites. The valuesof kMa and SMmax/Co for MWCNTs increased with the GNP
concentration (Table 2). These results collectively suggested
that although the retention of positively charged GNPs on thenegatively charged QS surface was commonly regarded as anelectrostatically favorable process, the observed blocking
behavior for GNPs indicated that there was only a limited
fraction of retention sites available for GNPs on the QS. These

RM/S =RM
RS(4)

R S/M =

RS
RM

(5)

where ΔRM is the difference in retained mass of MWCNTs in
the presence and absence of SNPs, ΔRS is the difference inretained mass of SNPs in the presence and absence of
MWCNTs, and RS and RM are the injected masses of SNPs
and MWCNTs, respectively. Note that ΔRM and ΔRS havesubtracted the corresponding single-species results to reflect
the retained mass of MWCNTs due to SNPs on co-transport.
The values of RM/S and RS/M, therefore, reflect the net mass of
MWCNTs and SNPs that were retained due to attached SNPs
and MWCNTs, respectively.
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ArticleFigure 2. AF4 fractograms (a−d) of MWCNTs associated with BNPs or GNPs in the effluent during the co-transport experiments (1 mg L−1
MWCNTs with 4 mg L−1 BNPs or GNPs, 1 mM KCl) and FTIR spectra of BNPs (e) and GNPs (f) before and after attachment with MWCNT at
1 mM KCl. (a, c) Intensities of UV (V) and (b, d) concentrations of Al (μg L−1) and Fe (μg L−1), respectively, for MWCNTs + BNPs and
MWCNTs + GNPs. The concentration of single MWCNT suspension for AF4-UV-ICP-MS measurement was 1 mg L−1 (1 mM KCl).

Calculated values of RM/S (mg mg−1) are shown in Figure
1i,j as a function of BNPs and GNPs, respectively, whereas
RS/M (mg mg−1) is given in Figure 1k as a function of
MWCNTs. It was found that values of RM/S were −1.8 × 10−3
and −5.7 × 10−3 mg mg−1 when the concentration of BNP was
4 and 10 mg L−1 (Figure 1i) but changed to 0.1 and 5.9E-02
mg mg−1 when the concentration of GNP was 2 and 4 mg L−1(Figure 1j), respectively. Negative values of RM/S indicate that
BNPs attached on the MWCNTs decrease the MWCNTs
retention, whereas positive values show an enhancement in
MWCNTs retention due to GNPs attachment. Additionally,
retention was hindered for both BNPs and GNPs due to theattachment of MWCNTs. Note that the RM/S values for
MWCNTs increased with increasing BNPs concentration(Figure 1i), while the RM/S values of MWCNTs decreased
with increasing GNPs concentration (Figure 1j). Such results
indicate that the enhancement in MWCNT retention due tothe presence of GNPs is still limited. A more negative value of
RM/S for GNPs in comparison to BNPs (Figure 1k) indicatesthat the inhibitory effect on MWCNT retention was more
pronounced for GNP than BNP.
Potential Mechanisms Contributing to the Retentionof MWCNTs. Previous studies indicated that the co-transportof ENPs and SNPs may occur via the following mechanisms:22,64 (i) competitive blocking due to limited retention
sites; (ii) heteroaggregation; and (iii) interaction between
these colloids and porous media. Each of these factors is
discussed below.
Competitive Blocking. Blocking (increasing effluent concentrations with continued particle injection) occurs for
MWCNTs, BNPs, and GNPs (Figure 1). Increasing the
SNPs Co will also decrease SSmax/Co and thereby enhanceblocking (sites fill faster at higher Co). When competitive
blocking is considered, the retention of SNPs will also
contribute to the filling of the MWCNT SMmax. Numericalsimulations exploring the significance of competitive blocking
were conducted by implementing the M1 and M2 modules,
respectively (Figure S3 and Table 2). Better simulation results(Figure S3 and Table 2) were achieved while using the M2

module and both ΓM and ΓS were greater than 0, suggestingthat competitive blocking should play a role in the co-transportof MWCNT and SNPs. However, one should note that thefitted values of ΓM and ΓS for the co-transport experiments
were low, indicating that competitive blocking is likely not thedominant contributor to co-transport enhancement(MWCNTs and BNPs) or inhibition (MWCNTs in thepresence of GNPs).
Heteroaggregation. Some recent studies suggested thatheteroaggregation could occur between ENPs and clay
minerals or iron oxides due to electrical interaction, cation
bridges, hydrogen bonding, and other interactions.65−69 Our
previous studies have shown that MWCNTs (1 mg L−1) in 1
mM KCl suspension are stable within 4 h in the absence of
BNPs and GNPs.36 MWCNT suspensions exhibited largerhydrodynamic radii after adding BNPs or GNPs that werestable for at least 1 h after preparation (Table S1). Such results
suggested that heteroaggregation (MWCNTs-BNPs and
MWCNTs-GNPs) occurred during the co-transport of
MWCNTs and SNPs (BNPs or GNPs) in porous media.
AF4-UV-ICP-MS has been used to study the interactions ofsoil elements (e.g., phosphorus) with soil colloids andnanoparticles.70−72 In this research, AF4-UV-ICP-MS wasused for the first time to characterize the association between
ENPs and SNPs in the effluent of co-transport experiments.
This method allows us to distinguish homo- and heteroaggregates of nanoparticles and colloids in suspension. Figure
2a,c shows the UV fractograms (volts) for MWCNTs-BNPs
and MWCNTs-GNPs, respectively, in the column effluent.
Figure 2b,d provides the corresponding plots of the ICP-MS
concentration (μg L−1) of particulate Al (for BNPs) and Fe(for GNPs), respectively, in effluent samples with thecorresponding hydrodynamic radius (nm). Extremely low
particulate Al and Fe concentrations were detected with pure
MWCNTs in the absence of SNPs (Figure 2b−d, black line, 1
mg L−1), indicating only minor traces of catalyst in
MWCNTs.61 The MWCNTs fractogram indicated two
different size ranges: 1−20 and 125−200 nm in both UV
and ICP-MS measurements (Figure 2a−d).73 Conversely,10674

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ArticleFigure 3. Plots of the dimensionless interaction energy as a function of separation distance (h) when a spherical colloid, with properties similar to
MWCNTs at an ionic strength of 1 mM KCl in the presence or absence of SNPs (BNPs or GNPs) (a), and in QS in the presence or absence of
SNPs (BNPs or GNPs) (b), respectively; (a) 1 mg L−1 MWCNT with adding 0 and 4 mg L−1 of SNPs (BNPs or GNPs); (b) 1 mg L−1 MWCNT
with adding 0 and 4 mg L−1 of SNPs (BNPs or GNPs) in QS.

their influence on ζ-potentials (Figure S6); e.g., the ζ-potentialof MWCNTs was more negative in the presence of BNPs(−40.9 and −41.4 mV for 4 and 10 mg L−1 BNPs,
respectively) and less negative in the presence of GNPs(−38.7 and −36.4 mV for 2 and 4 mg L−1 GNPs, respectively)in comparison to MWCNT suspensions without SNPs (−40.6
mV, Figure S6).
Although DLVO calculations in Figure 3 can explain theassociation of MWCNTs with GNPs, it cannot account for
associations between MWCNT and BNPs, the significant
amount of MWCNT retention, and competitive blocking.
Other forces and factors may therefore be required to explain
this behavior. For example, calculations in Figure 3 assume
smooth and chemically homogeneous surfaces, whereas surface
roughness and charge heterogeneity on natural surfaces or due
to attached SNPs will locally reduce or eliminate the energy
barrier.74,75 Furthermore, MWCNTs are not spherical inshape, and the particle shape, orientation with the surface, andthe interior properties are known to have a strong impact on
predicted energy barriers.76−78 If these factors eliminate theenergy barrier, then the MWCNTs can interact in a primary
minimum at a small separation distance and other non-DLVO
forces can contribute to the strength of the interaction.26,27
The FTIR spectra from batch experiments (Figures 2 andS7) showed O−H stretching (3437.4 cm−1), weak C−H
stretching (2918.4 cm−1) of −CH3 and CH2 groups, carboxylic
C�O (1726.9 cm−1) and COO− (1575.3 cm−1) stretching,
and C−O stretching (1152.4 cm−1) from functionalized
MWCNTs.79−81 A new band appeared at 1405.9 cm−1 (Figure2f) in comparison to the pristine GNPs, which was induced by
the complexation between GNPs and the COO− groups of
MWCNTs. Similar results have been observed for the
association of organic matter with iron oxide.27,82−84 In
addition, a small decrease in intensity of the band below
1000.0 cm−1 (607.7, 801.2, and 909.6 cm−1, Fe−O or Fe−OH
vibrations) and 3130.7 cm−1 (O−H stretching), as well as adisappearance in the intensity of the band around 1060.0 cm−1
(Fe−OH vibration), were attributed to the association
between water or Fe−OH or Fe−O vibrations of GNPs and
MWCNTs by non-DLVO interactions (e.g., H-bonding, Lewis
acid−base, or ligand exchange).26,82−84 Figure 2e shows theassociation between BNPs and MWCNTs, which exhibitedmuch weaker complexing ability in comparison to MWCNTs

much higher UV intensities and particulate Al and Fe
concentrations were observed in the effluent of co-transport
experiments when SNPs were present. Larger particles,
especially in the range of 125−200 nm, were found in theeffluent of co-transport experiments when SNPs were present,
and their composition was indicative of the presence ofheteroaggregates. TEM images were obtained for effluent
samples under different conditions (Figure S1c,d for BNPs,
and Figure S1e,f for GNPs) for further confirmation. It was
found that MWCNTs have interacted with BNPs and GNPs
(red circle) in the effluent. These findings indicate that BNPs
and GNPs were associated with MWCNTs under the tested
conditions.
Batch experiments with AF4-UV-ICP-MS measurements
were conducted to improve our understanding of theassociation between MWCNTs and BNPs or GNPs. Batch
results indicate that both BNPs and GNPs can adsorb
MWCNTs, but there were stronger affinities between
MWCNTs-GNPs than MWCNTs-BNPs (Figure S4). The
AF4-UV-ICP-MS results showed larger MWCNT-BNP and
MWCNT-GNP aggregates in batch than column experiments.
One potential explanation is that larger-sized aggregates wereretained in the QS during the co-transport of MWCNTs and
SNPs, and only smaller-sized aggregates were observed in theeffluent. Overall, AF4-UV-ICP-MS results from both column
and batch experiments indicated that MWCNTs-BNPs or
MWCNT-GNPs heteroaggregates were formed during cotransport.
Interactions. DLVO calculations are normally conducted to
explain observed aggregation and retention behavior. Figure 3apresents plots of Φ as a function of separation distance (h)when a spherical colloid with properties similar to MWCNTs
approaches a spherical colloid with properties similar to BNPs
or GNPs in KCl solutions at IS = 1 mM. A large energy barrier
is predicted between MWCNTs and MWCNTs-BNPs,
whereas there is no energy barrier between MWCNTsGNPs. Figure 3b presents similar information for a spherical
MWCNT colloid as it approaches the surface of QS in KCl
solutions at IS = 1 mM. A large energy barrier and a shallow
secondary minimum are predicted between the MWCNTs and
QS, although the height of the energy barrier and the depth ofthe primary minimum is a function of the various
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and GNPs. Only a slight decrease in intensity of the bandaround 467.9 (Si−O vibration), 525.0 (Si−O vibration),
3440.1 (O−H stretching), and 3621.6 (O−H stretching) cm−1
was found, suggesting the interaction between MWCNTs and
BNPs through water molecular and Si−O vibrations on BNPs.
The FTIR results provided qualitative information regarding
the interactions and indicated that the interactions between
MWCNTs (negatively charged) and SNPs (negatively charged
BNPs or positively charged GNPs, Figure 2e,f) are also
through non-DLVO interactions with functional groups of Si−
O on BNP surfaces or Fe−O and/or Fe−OH on the GNP
surfaces, and −COOH and/or −OH on MWCNT surfaces.
Only a few studies based on batch and aggregation experiments
have shown that carbon nanomaterials can interact withgoethite through H-bonding and/or Lewis acid−base interactions at both negatively and positively charged goethite, andfurther indicated that both H-bonding and Lewis acid−baseinteractions may overcome the electrostatic repulsion between
them.26,27 Consequently, results herein demonstrated that both
BNPs and GNPs could interact with MWCNTs through nonDLVO interactions (e.g., H-bonding, Lewis acid−baseinteractions, or ligand exchange).
Theoretical calculations evaluating the binding energies
between MWCNTs and SNPs were performed by conducting
MD simulations (Figure 4). The binding energies of BNPs

Article(Figure 4b) and GNPs (Figure 4c) with MWCNTs were−120.6 ± −7.6 and −175.3 ± −8.6 kJ mol−1, which isequivalent to −48.7 and −70.68 kT (1 kT = 2.476 kJ mol−1),85
respectively. These attractive interactions are much stronger
than expected for secondary minimum interactions and aremuch shallower than primary minimum interactions onsmooth surfaces. However, their magnitudes are comparable
to primary minimum interactions when surface roughness andcharge heterogeneities are considered for MWCNTs and SNPs
(Figure S5c,d).
In addition, MD simulations show that MWCNTs can becompletely wrapped by GNPs with a smaller mean distance(0.50 nm, Figure 4c) between the centroids of MWCNTs.
Although MWCNTs were also wrapped by BNPs, muchgreater dispersion around MWCNTs than GNPs wasobserved, resulting in a larger mean distance (0.54 nm, Figure4b) between the centroids of MWCNTs. The tiny difference of
0.50 and 0.54 nm still exhibited the effect of interactions
between MWCNTs and SNPs, which were in good agreementwith the observation of enhanced hydrodynamic radii of
MWCNTs found in the presence of GNPs and BNPs (Table
S1) and results of AF4-UV-ICP-MS.
Our MD simulations demonstrate that non-DLVO interactions between SNP and MWCNT are thermodynamicallyfeasible, so their contributions to the deposition andinteraction behavior of SNPs and MWCNTs should not beignored. FTIR results (Figure 2e,f) experimentally confirm
these findings. Non-DLVO interactions like chemical and Hbonding should make MWCNTs-SNPs aggregates that are
more stable than those predicted by conventional DLVO
theory, and consequently less susceptible to disaggregation.
Other than the commonly observed facilitated transport
behavior, we for the first time found that the transport of both
BNPs and GNPs was also facilitated by the presence of
MWCNTs. Such phenomena cannot be effectively explainedby the traditional mechanisms associated with competitive
blocking, heteroaggregation, and conventional DLVO calculations. Direct examination using novel tools of AF4-UV-ICPMS measurement combined with MD simulation, batch
experiments, and FTIR measurement collectively demonstrated that MWCNTs-BNPs or MWCNTs-GNPs complexes oraggregates could be formed and non-DLVO interactions (e.g.,
H-bonding, Lewis acid−base interactions, or ligand exchange)
played an important role in contributing to the co-transport
between SNPs (BNPs or GNPs) and MWCNTs. An input
concentration of 1 mg L−1 of MWCNTs was employed toobtain high accuracy and mass balance in studies designed toevaluate heteroaggregation and co-transport of ENPs and
SNPs in soil, although this value is high in comparison toenvironmentally relevant MWCNT concentrations that weremodeled or estimated by other studies.86,87 Consequently, themutual effects (enhancement or inhibition) of two colloids inco-transport should be considered in soil and groundwater.

■

ENVIRONMENTAL IMPLICATIONS

Soil nanoparticles (SNPs) are one of the most active
components involved in many biogeochemical processes insoil and groundwater. In this work, a multiscale approach was
employed to comprehensively evaluate the contributions ofnegatively and positively charged SNPs (BNPs and GNPs) to
the transport and retention of MWCNTs in QS. The results
demonstrated that the mutual effects of MWCNTs and SNPs
(BNPs or GNPs) could not be well described by classic DLVO

Figure 4. (a−c) MD simulations of MWCNTs with BNPs or GNPs.
(a) Schematic molecular structure for BNPs, MWCNTs, and GNPs.
Red is oxygen (O), white is hydrogen (H), light blue is carbon (C),light pink is iron (Fe), yellow is silicon (Si), and purple is aluminum(Al). The solvent of KCl and water molecular has been hidden for abetter observation. (b, c) Interactions between MWCNTs and BNPs,
and MWCNTs and GNPs, respectively; d is the mean distance
between the centroids of two MWCNTs.
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theory, CFT, and competitive blocking due to the contributions of non-DLVO interactions to aggregation and cotransport of MWCNTs and SNPs. In natural soil andgroundwater environments, co-transport, heteroaggregation,or interactions of MWCNTs can occur with SNPs and colloids
regardless of the surface charge of particles and the collector(similarly or oppositely charged). Some colloidal contaminants
or other colloids with oxygen-containing functional groups likefunctionalized MWCNTs, biochar, or biocolloids can interact
with colloids and SNPs through non-DLVO interactions in soil
and groundwater. Future research should accurately quantify(e.g., MD simulation, atomic force microscopy (AFM), density
functional theory (DFT), etc.) the contribution of non-DLVO
interactions (e.g., H-bonding, Lewis acid−base interactions, or
ligand exchange) to colloids and SNPs (e.g., heteroaggregationand co-transport) in the environment. In fact, homo- andheteroaggregates in suspension can be distinguished by AF4UV-DLS-ICP-MS by determining changes in size fraction andelement composition. Single-particle ICP-MS also helps to
identify and quantify the low concentrations and size of ENPs
in the environment45−47 and possibly ENPs-SNPs aggregatesin the future.88 The interfacial forces between colloids andcollectors could be directly determined by AFM.89 Both MD
simulation and DFT could provide the interaction mechanism
between molecules or/and atoms.35,90 Consequently, the roleof non-DLVO interactions should be comprehensively
evaluated and further investigated when assessing the environmental risk and fate of ENPs or colloidal contaminants (e.g.,
coexistence of multisubstance) that are associated with soil
colloids/SNPs.

■

Guangdong Provincial Key Laboratory of Environmental
Pollution Control and Remediation Technology, Sun Yat-sen
University, Guangzhou 510006, P. R. China; orcid.org/
0000-0001-6590-333X; Phone: 86-20-39335060;
Email: jinchao3@mail.sysu.edu.cn
Authors

Miaoyue Zhang − School of Environmental Science andEngineering, Sun Yat-sen University, Guangzhou 510006, P.
R. China; Guangdong Provincial Key Laboratory ofEnvironmental Pollution Control and Remediation
Technology, Sun Yat-sen University, Guangzhou 510006, P.
R. China; orcid.org/0000-0002-2939-6665
Scott A. Bradford − Sustainable Agricultural Water Systems(SAWS) Unit, USDA, ARS, UC Davis, Davis, California
95616, United States; orcid.org/0000-0002-3260-2968
Erwin Klumpp − Agrosphere Institute (IBG-3),
Forschungszentrum Jülich GmbH, 52425 Jülich, Germany
Jiri Šimůnek − Department of Environmental Sciences,
University of California, Riverside, Riverside, California
92521, United States
Shizhong Wang − School of Environmental Science andEngineering, Sun Yat-sen University, Guangzhou 510006, P.
R. China; Guangdong Provincial Key Laboratory ofEnvironmental Pollution Control and Remediation
Technology, Sun Yat-sen University, Guangzhou 510006, P.
R. China
Quan Wan − Guangdong Provincial Key Laboratory ofAgricultural & Rural Pollution Abatement andEnvironmental Safety, College of Natural Resources andEnvironment, South China Agricultural University,
Guangzhou 510642, P. R. China
Rongliang Qiu − School of Environmental Science andEngineering, Sun Yat-sen University, Guangzhou 510006, P.
R. China; Guangdong Provincial Key Laboratory ofAgricultural & Rural Pollution Abatement andEnvironmental Safety, College of Natural Resources andEnvironment, South China Agricultural University,
Guangzhou 510642, P. R. China; Guangdong Laboratory for
Lingnan Modern Agriculture, Guangzhou 510642, P. R.
China; orcid.org/0000-0002-9469-5274

ASSOCIATED CONTENT

sı Supporting Information*

The Supporting Information is available free of charge athttps://pubs.acs.org/doi/10.1021/acs.est.2c00681.
Details pertaining to BNPs and GNPs preparation (S1),interaction energy calculations (S2), batch experiments(S3), and numerical modeling (S4); hydrodynamic radiiof MWCNTs, BNPs, GNPs, BNPs-MWCNTs, and
GNPs-MWCNTs at 1 mM KCl (Table S1); fitted
parameters based on M1 and M2 models (Table S2);
scanning electron microscope images of BNPs and
GNPs, and transmission electron microscopy images of
BNPs-MWCNTs and GNPs-MWCNTs in the effluentof column experiments (Figure S1); AF4 fractograms of
BNPs and GNPs suspensions (4 mg L−1 BNPs or GNPs,
1 mM KCl) (Figure S2); observed and fitted (M2model) BTCs and RPs in the column experiments(Figure S3); results of a batch experiment on theattachment of MWCNTs to BNPs or GNPs in 1 mM
KCl solution (Figure S4); interaction energies between
MWCNTs and QS in the presence or absence of SNPs
(BNPs or GNPs) under different roughness conditions(Figure S5); ζ-potentials of MWCNTs, BNPs, GNPs,
BNPs-MWCNT, and GNPs-MWCNTs at the ionicstrength of 1 mM KCl (pH ≈ 5.4) (Figure S6); andFTIR spectra of MWCNTs (Figure S7) (PDF)■

ArticleComplete contact information is available at:https://pubs.acs.org/10.1021/acs.est.2c00681
Notes

The authors declare no competing financial interest.

■

ACKNOWLEDGMENTS■

REFERENCES

Funding was provided by the National Natural Science
Foundation of China (project nos. 42077342 and 41877475)
and the 111 Project (project no. B18060). The authors
acknowledge Stephan Köppchen for bromide measurements.
Thanks go to Herbert Philipp and Claudia Walraf for theirtechnical assistance.

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AUTHOR INFORMATION

Corresponding Author

Chao Jin − School of Environmental Science and Engineering,
Sun Yat-sen University, Guangzhou 510006, P. R. China;
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