doi.org/10.26434/chemrxiv.11473080.v1

A computational study of APTES surface functionalization of diatom-likeamorphous SiO2 surfaces for heavy metal adsorptionJose Julio Gutierrez Moreno, Ke Pan, Yu Wang, Wenjin Li

Submitted date: 31/12/2019 • Posted date: 23/03/2020Licence: CC BY-NC-ND 4.0Citation information: Gutierrez Moreno, Jose Julio; Pan, Ke; Wang, Yu; Li, Wenjin (2020): A computationalstudy of APTES surface functionalization of diatom-like amorphous SiO2 surfaces for heavy metal adsorption.ChemRxiv. Preprint. https://doi.org/10.26434/chemrxiv.11473080.v1

The amorphous silica (SiO2) shell on diatom frustules is a highly attractive biomaterial for removing pollutantsfrom aquatic ecosystems. The surface activity of silica can be enhanced by modification with organosilanes. Inthis work, we present an atomic-level theoretical study based on Molecular Dynamics (MD) anddispersion-corrected Density Functional Theory (DFT-D3BJ) calculations on the surface stability andadsorption of heavy metal compounds on silane and APTES covered SiO2 surfaces. Our simulations showthat at low APTES coverage, molecular adsorption of Cd(OH)2 and HgCl2 is more favourable near themodifier, compared to As(OH)3 that binds at the hydroxylated region on silica. At higher coverages, themetallic compounds are preferentially adsorbed by the terminating amino group on the surface, whereas theadsorption in the region between APTES and the oxide surface is also spontaneous. The adsorption isstrongly driven by van der Waals interactions at the highly-covered surface, where the consideration ofdispersion corrections reduces the modifier-adsorbate interatomic distances and increases the adsorptionenergy by c.a. 0.4-0.7 eV. The adsorption of water is favourable, although it is generally weaker than for theheavy metal compounds. Based on our results, we conclude that the addition of APTES modifiers on silicaincreases the adsorption strength and provides extra binding sites for the adsorption of heavy metalpollutants. These outcomes can be used for the design more efficient biomaterials’ structures for heavy metalsdepollution.

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A computational study of APTES surface functionalization of diatom-

like amorphous SiO2 surfaces for heavy metal adsorption

José Julio Gutiérrez Moreno 1,2, Ke Pan 1, Yu Wang 1, Wenjin Li 1*

1 Institute for Advanced Study, Shenzhen University, Shenzhen 518060, China. 2 Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and

Guangdong Province, College of Physics and Optoelectronic Engineering, Shenzhen

University, Shenzhen 518060, China.

* liwenjin@szu.edu.cn

Abstract

The amorphous silica (SiO2) shell on diatom frustules is a highly attractive biomaterial

for removing pollutants from aquatic ecosystems. The surface activity of silica can be

enhanced by modification with organosilanes. In this work, we present an atomic-level

theoretical study based on Molecular Dynamics (MD) and dispersion-corrected Density

Functional Theory (DFT-D3BJ) calculations on the surface stability and adsorption of

heavy metal compounds on silane and APTES covered SiO2 surfaces. Our simulations

show that at low APTES coverage, molecular adsorption of Cd(OH)2 and HgCl2 is more

favourable near the modifier, compared to As(OH)3 that binds at the hydroxylated

region on silica. At higher coverages, the metallic compounds are preferentially

adsorbed by the terminating amino group on the surface, whereas the adsorption in the

region between APTES and the oxide surface is also spontaneous. The adsorption is

strongly driven by van der Waals interactions at the highly-covered surface, where the

consideration of dispersion corrections reduces the modifier-adsorbate interatomic

distances and increases the adsorption energy by c.a. 0.4-0.7 eV. The adsorption of

water is favourable, although it is generally weaker than for the heavy metal

compounds. Based on our results, we conclude that the addition of APTES modifiers on

silica increases the adsorption strength and provides extra binding sites for the

adsorption of heavy metal pollutants. These outcomes can be used for the design of

more efficient biomaterials’ structures for heavy metals depollution.

1. Introduction

The use of bio-adsorbents for removing toxic metals, such as diatom silica (SiO2)

frustules, is highly attractive due to their low-cost and abundant supply from natural

biomineralization in aquatic environemnts1-5. Diatoms are microscopic algae which

grow a nanostructured porous cell wall called frustule. Diatoms are composed by an

amorphous silica core, which possesses very limited material properties 6. Therefore,

new approaches are needed to functionalize diatom-based nanostructures to expand the

range of their useful properties while preserving or appropriately modifying its original

nanostructure.6-8

Organic molecules like organosilanes can be efficiently used for surface

functionalization. In the case of silica, the amorphous matrix can be chemically

patterned by adding the organosilanes reagents during the glass formation process.9

Surface functionalization with organosilanes build-up extremely complex chemical

architectures at the nano-scale on metal oxide surfaces such as silica 9 or graphene oxide

(GO) 10. Organosilanes modifiers have been widely used to expand the range of

applications of several oxide materials. Some examples are the development of glucose

biosensors 11 or protective anticorrosion barriers on graphene oxide 10; SiO2-based

catalysers used for hydrocarbons’ oxidation 12; or modified TiO2 nanoparticles with

enhanced pollutant adsorption rates that can be potentially used for environmental

purification purposes 13. In addition, the high flexibility of organic molecules compared

to other surface terminations can be also used for tuning the hydrophobic or hydrophilic

behaviour of surfaces 11.

In the last decade, numerous experimental studies proposed the use of functionalized

diatom for heavy metal (HM) removal in water4, 14-18, in addition to other technological

applications such as biological or micro/nanodevice applications.4, 5, 14, 19 HMs are one

of the most widespread contaminants and one of the most important threats to the

environment and health worldwide 20-23. The development of efficient platforms to

palliate the presence HMs from waters and soils is, therefore, a matter of primary

interest. HMs are very stable and cannot be biodegraded. Thus, the most efficient

methods for HM depollution involve physical removal or bioleaching techniques 24.

Recent studies have shown that the involvement of various functional groups (i.e.

hydroxyls, thiol or amino groups) enhances the diatom capacity to absorb HMs like

arsenide (As), cadmium (Cd) or mercury (Hg).4, 5, 19, 25

Aquatic ecosystems are a common end destination for a number of pollutants 26. Thus,

the management of wastewater-containing HMs has been one of the most prominent

challenges in the past few decades. As, Cd and Hg are some of the most serious

inorganic water and soil contaminants worldwide and present a significant threat to

public health 20, 22. As(III) is one of the most commonly found arsenide species in

aqueous solutions, while it presents more toxicity and higher mobility than to the also

abundant As(V) 27, 28. Available reports show that As(III) can form neutral molecules in

aqueous solutions, which suggest arsenous acid (As(OH)3) as one of the most common

As compounds in contaminated waters 29. Environmental exposure to cadmium Cd(II)

has been associated with severe health effects such as lung cancer or liver injury 30. In

aqueous solution, Cd(II) ions can form stable hydroxo-complexes such as cadmium

hydroxide (Cd(OH)2) 31. In the case of mercury, its elemental gaseous form (Hg(0)) can

oxidize to more water-soluble forms like Hg(II) species 32. Hg(II) complexes can be

photo-degraded or reduced by compounds produced via photochemical reactions 33. In

particular, the neutral HgCl2 molecule appears to be one of the most abundant Hg-

complexes in toxic environments 34.

Aminosilanes are attractive modifiers for their use on silica-based surfaces. 3-

Aminopropyltriethoxysilane (APTES) is probably the most commonly used aminosilane

35-38. The most common routes for silica functionalization show that APTES modifiers

are adsorbed in the form of self-assembled monolayer (SAM), with its amine group

extending away from the interface 37. APTES are covalently attached to the silica

surface through the formation of siloxane bonds. Aminosilanes (i.e. APTES or MPTES)

modified silica have been previously used for enzyme immobilization, being these

suitable for monitoring the quality of food or drinks 11. Recent adsorption studies have

demonstrated that APTES modified silica materials are good adsorbents for the removal

of HMs such as Cd and Hg from aqueous solutions 25, 39, 40.

Nonetheless, despite the significant experimental studies on the adsorption of HM at

biomaterials carried out in recent years, along with the popular use of APTES as a

modifier of silica, more fundamental works on the adsorption mechanisms on

functionalized silica are lacking. On this ground, we present a comprehensive

theoretical study on the atomic-level structure and molecular adsorption on surface-

modified amorphous SiO2. The amorphous silica bulk models were generated by

Molecular Dynamics (MD) simulations. We compare the structural properties of several

silica model surfaces, including hydroxylated and APTES-modified mixed models. The

adsorption of HM-pollutants: As(OH)3, Cd(OH)2 and HgCl2, and molecular water

(H2O) are discussed based on first-principles Density Functional Theory (DFT)

calculations including also long-range dispersions van der Waals (vdW) corrected

functional. We discuss the adsorption mechanisms of these HM compounds on a range

of diatom-like silica-based functionalised materials for benchmarking purposes,

determining the preferential adsorption sites, adsorbate orientation and adsorption

energy, which are the key parameters that dominate the fundamental interactions

between HMs and diatom-like biomaterials’ surfaces. The outcomes of this study

provide a comprehensive insight into the adsorption properties of APTES-modified

silica.

2. Methodology

The amorphous silica bulk model was generated by molecular dynamics (MD) melt-

quenching method within the framework of the LAMMPS 41 package. We used Tersoff

type 42 interatomic potentials for Si-O interactions. The integration time step was set to

0.1 fs and the Nosé-Hoover thermostat in its isothermal-isobaric form (NPT) was used

to set the constant pressure at 1atm and the temperatures along the simulation. Initially,

the atomic species in stoichiometric SiO2 composition with a total of 216 atoms (72 Si

and 144 O atoms) are randomly placed in a periodic cubic box with sides’ dimension of

15.50 Å. The system is carefully warmed up to 4000K at 5 K/ps rate. The temperature

was set well above the experimental melting point and equilibrated for 1 ns to assure the

initially random distribution of the atomic species in our model. The melted structure is

then quenched to 300K at 1 K/ps rate, by decreasing 10 K every 105 time-steps, and

finally equilibrated for 1 ns. Comparable quench rates were used to successfully obtain

the amorphous silica, silicon, and silicon carbide models in the melt-quenching

procedure 43-48.

The periodic Density Functional Theory (DFT) calculations are carried out within the

framework of the Vienna Ab Initio Simulation Package (VASP). The projector

augmented-wave (PAW) potentials 56, 57 are used to describe the core-valence

interaction, with the valence electrons described by periodic plane waves with cut-off

energy of 400 eV. We used the Perdew-Burke-Ernzerhof (PBE) exchange-correlation

functional 49. Additionally, the influence of long-range (VdW) dispersion forces was

accounted based on Grimme’s approach with Becke-Johnson damping correction (D3BJ

method), as implemented in VASP code 50, 51. The vdW interaction has been widely

considered in computational studies of molecules adsorbed on solid surfaces. Earlier

studies suggested that different implementations of the vdW interaction such as the

functionals DFT-D3, optPBE-vdW, optB86b-vdW, BEEF-vdW give comparable results

on the structures and adsorption energy of the similar adsorption systems, which are in

good agreement to experimental data 50, 52-54. To address the effect of vdW with the

limited computational resources at our disposal, we choose the so-called DFT-D3BJ

semi-empirical method for the following GGA calculations, which is expected to

improve the accuracy of the predicted geometric and electronic structures of the

adsorption systems. The influence of this additional correction in the calculated

adsorption energies and bond distances in the molecular adsorption simulations is also

discussed throughout the manuscript. We discuss the results from standard DFT for the

bulk and modified surface models while results presented from the HM adsorption

correspond to the D3 corrected systems. The convergence criteria used for energy and

forces on each atom are 10–4 eV and 0.02 eV/Å, respectively. Due to the large size of

the model, the calculations are done with Γ-point sampling grid, which is considered to

be sufficient. The use of a finer k-point grid is not expected to result in significant

differences in the geometrical relaxations and total energy values, while they

substantially increase the computational cost. The Methfessel-Paxton smearing function

with σ = 0.1 eV is used to integrate the Brillouin Zone.

The adsorption energy for the different molecules in this study is given by:

𝐸𝑎𝑑𝑠 = 𝐸𝑠𝑢𝑟𝑓+𝑎𝑑𝑠 − 𝐸𝑠𝑢𝑟𝑓 − 𝐸𝑚𝑜𝑙

Where Eads is the energy with which the adsorbate binds on the surface, Esurf+ads is the

total energy of the relaxed system after molecular adsorption, Esurf is the total energy of

the hydroxylated or APTES-modified surface, and Emol is the energy of the free-

standing adsorbed molecule. The energy of the isolated molecule was calculated in a

large box, to avoid molecule self-interaction, and using Γ-point sampling grid and the

same plane wave cut-off and convergence criteria as the surface models.

3. Results and discussion

3.1 Construction of amorphous SiO2 silica model surface

The amorphous silica model structure was generated by melt-quenching procedure

within MD simulations, as described in the methodology section. This procedure leads

to an equilibrated cubic box with side dimensions of 14.59 Å at ambient conditions (T =

300 K, P = 1 atm). The density of the resulting simulation box is 2.31 g/cm3, which is in

good agreement with experimental results and previous computational models of

amorphous silica.43-45, 55, 56

The radial pair distribution function (PDF) for Si-Si, Si-O and O-O pairs are shown in

Figure 1. In the short-range region, the Si-O first neighbours form a high and sharp peak

with its centre at 1.65 Å. The O-O and Si-Si peaks are broader than the first peak and

their maximum values are located at about 2.63 Å and 3.15 Å respectively. These

results are in good agreement with experimental measurements of amorphous SiO2 that

show the first peak position for Si-Si, Si-O and O-O pairs at 1.61 Å, 2.63 Å and 3.08 Å

respectively. 57 In a periodically crystalline structure, atomic positions are repeated in

space in a regular array following the so-called long-range order. In our model, the

absence of long-range order in our as-quenched silica model reflects the amorphous

distribution of this solid. In the bulk, most Si atoms are 4-fold coordinated (Si4f) while

among oxygen most are O2f species.

To assess the influence of size effects in our model, which may lead to errors associated

with the small size of the system, we also simulated a SiO2 tenfold model containing

2160 atoms (720 Si and 1440 O atoms). The structure obtained from the tenfold model

was found equivalent to the smaller structure. Comparison between both structures can

be accessed in the supporting information (Figure S1). While in MD simulations the

computational time is roughly linearly proportional to the number of atoms in the

system; in DFT calculations, the simulation of a the tenfold structure can be up to three

orders of magnitude more computationally expensive than the reduced system. This

makes quantum mechanical calculations of such a large structure unviable. Therefore,

considering the technical limitations in first-principles DFT calculations, we used the

216 atoms model for further simulations and analyses.

Figure 1: Pair distribution function (PDF) of amorphous SiO2 bulk model structure. The different pairs

are colour-coded in the figure, with Si-O pairs represented with a blue line, Si-Si in green and O-O in red.

The normalized number of pairs is represented along the y-axis while the x-axis presents the

corresponding distances in Å. For the structure of bulk amorphous SiO2 model structures and the

subsequent figures, Si atoms are represented by yellow spheres and O atoms are red.

The MD-generated amorphous structure was used as input for the ab initio calculations

keeping constant the lattice parameters. Our simulation box exhibits an average density

that is in good agreement with experimental results, therefore we do not expect

significant differences with the DFT or DFT-D3 optimized lattices. The SiO2 surface

model is cleaved from the bulk by introducing a vacuum layer of about 15 Å in a plane

orthogonal to one of the axes. Whereas the in-plane parameters are kept constant along

the simulations, the slab is relaxed by ab initio and reflects the typical geometry patterns

of an amorphous hydroxylated silica surface. Although local lattice strains can alter the

structure of crystalline surfaces, this effect will be minimum in amorphous surfaces that

lack a short-range periodic structure. Therefore, we do not believe the adsorption

models will be affected by this assumption.

The presence of multiple under-coordinated atoms on the surface upon surface cleavage

(dangling bonds) is healed by saturating the two sides of the slab with H and OH

groups. Surface silane groups (SiOHx) are likely to form on silica in environments in

which water is present, either in liquid or gas phase.58 The hydroxyls present on the

amorphous silica surface (Figure 2) are originated from dissociated water molecules. In

our model, we added OH and H terminations to undercoordinated Si and O on the

surface, respectively. To fully saturate our model slab we added a total of 10 OH and 10

H terminations (or 10 O and 20 H atoms), which can be also interpreted as the

dissociative adsorption of 10 H2O molecules. The saturating terminations were initially

placed perpendicularly to the undercoordinated species and relaxed by DFT. The

resulting silanol-terminated slab model is represented in Figure 2.

Figure 2: Three-dimensional periodic box with DFT relaxed model of saturated amorphous SiO2 model

surface. The vacuum layer over the topmost layer has been cropped in the figure. Si atoms are represented

by yellow spheres, O atoms are red and H atoms are white.

3.2 Surface functionalization of silica surfaces

APTES functionalization has been previously used for biosensing applications and their

amino termination is key to promote the interaction between silica surfaces and

biomolecules1, 11. Prior to the adsorption of each APTES molecule, an OH termination

is removed from the initially hydroxylated surface. The aminopropyl part of APTES

(NH2-(CH2)3) is then attached to the undercoordinated surface Si3f and the rest (Si-

(OCH3)3) is removed. The adsorbed APTES will then have three attachment points

(shown in Figure S2), like the silane molecules that are exposed on the surface of silica.

The resulted model is aimed to mimic an APTES-modified silanol surface that results

from complete hydrolysis and condensation. A more detailed explanation of the

chemical processes for APTES functionalization of silica can be accessed in a previous

publication 11.

To assess for surface coverage effects, we tested models with 1, 3 and 8 (fully-covered)

APTES molecules on the amorphous (Figure 3). All models are stable and exhibit an

APTES distribution that is perpendicularly oriented with respect to the surface, with the

amino group terminating the modified structure. We calculate the relative formation

energy using the energy difference between 1xAPTES model and the hydroxylated

surface as a reference. To estimate the influence of surface relaxations to the calculated

adsorption energy, which contributions are sometimes hard to quantify, we define the

distortion energy (Edist) for the APTES modified surface as the energy difference

between the pristine model (before the adsorption of the HM molecule) and the relaxed

structure after HM desorption. We have previously used the adsorption/desorption

method for water on TiO2 interfacial systems and we found that surface relaxations can

contribute to up to 2.5 eV to the estimated adsorption energy values in highly disordered

slab models 59, 60. In the 1xAPTES model, successive adsorption/desorption procedures

result in structures with distorted APTES, which can be up to 7.2 eV lower in energy

compared to the undistorted initial reference structure. Here we use two different

models of the surface-modified with one APTES, which will be taken as reference states

for different adsorption cases. A table with the total energy values is included in Table

S1, in the supporting information section.

Figure 3: Surface models of APTES-functionalized amorphous silica. The top-to-down models represent

increasing surface coverage, from an isolated APTES (1xAPTES) to a fully covered surface (8xAPTES).

In the figures, Si atoms are represented by yellow spheres, O atoms are red, H atoms are white, C atoms

are grey and N atoms are blue.

At higher surface coverages, the model surfaces exhibit an overall decrease in the total

energy of 17% and 18% for the 3xAPTES in aligned and homogenous distribution

(Figure S4), respectively, and 18% for 8xAPTES, using the undistorted 1xAPTES as

reference. If we take the 1xAPTES distorted configuration as the reference model, the

respective stabilization upon surface coverage corresponds to 11% for 3xAPTES

(compare two models) and 12% for 8xAPTES. We tested two different models for the

3xAPTES surface, which are represented in the Supporting Information section. The

preferential adsorption distribution is when the modifiers are homogeneously distributed

on the surface (Figure S4b). This distribution allows some isolated APTES to incline

from their initially vertical position and interact with surface silane groups by H-

bonding. The distribution in which the APTES molecules are deposited in an aligned

neighbouring position (Figure S4a) was found to be less favourable, however, the small

difference in energy (0.09 eV/APTES) suggest the likely coexistence of both models on

the surface. Our results indicate the relative energy preference of models with high

coverage of APTES adsorbed in self-assembled monolayer form, compared to isolated

APTES when the modifiers are absorbed in perpendicular to the surface. However, the

flexibility of APTES allows the formation of H-bonds between the molecule and

terminating silane groups, which contributes to the stabilization of isolated molecules

on the surface.

On the DFT-relaxed hydroxylated silica surface, the Si-O bond lengths are in a range

between 1.61-1.68 Å, also in line with the above-described experimental values 57. The

small difference between bonds distances measured on the surface, which differ only by

up to 0.04 Å with respect to the median bond distance found in the amorphous bulk

structure, indicates the homogeneity between the bulk and slab models. In the APTES

modified models, we measured Si-C bond distances, formed between the Si and C from

APTES, in a range between 1.83-1.86 Å; C-C bonds between 1.52-1.55 Å, C-N bonds

between 1.46-1.48 Å, C-H bonds between 1.10-1.11 Å and N-H bonds have a length of

1.02 Å. These distances are not substantially affected either by the surface coverage rate

or by the inclusion of the long-range dispersion correction into the DFT calculations. A

table with the measured bond distances (Table S2) and angles (Table S3) as a function

of the surface coverage can be consulted in the supporting information.

3.3 Molecular adsorption at functionalized silica

3.3.1 Adsorption of pollutants at low APTES-covered surface

In this section, we describe the adsorption mechanisms of several HM compounds that

are stable in hydrated environments and that have been identified as dangerous

pollutants, namely Cd(OH)2, HgCl2 and As(OH)3 26, 28, 30-32. These molecules are used as

a benchmark to analyse the adsorption of HM compounds at APTES modified silica.

Figure 4 presents a schematic figure of the HM adsorption at APTES-modified silane-

covered silica surface. The different surface coverages, ranging between the

hydroxylated surface and highly covered by APTES, are represented in the figure. The

possible adsorption sites for HM are also indicated: e.g. adsorption at silanes, at the

APTES-silica interface and atop APTES modifiers on highly covered models.

The adsorption energy is discussed in terms of the interaction between each adsorbate

and the silica surface that is modified with one APTES molecule (Figure 3a). The

adsorption energy at hydroxylated silica was estimated by molecular deposition at the

silane-rich region on the surface, on which the interaction with the APTES modifier will

be minimal. These models will be compared with the highly covered surface model in

the next section (3.3.2). The Eads values for relaxed systems as a function of the surface

coverage and considering also the influence of long-range dispersions are given in table

1. As discussed before, surface relaxations can have an important weight in the

calculated adsorption energy. In our models, we used the undistorted 1xAPTES model

as a reference for the surfaces with the HM compound adsorbed far from the modifier

(Figure 5). The 1xAPTES distorted model (lower energy) was used as a reference for

the adsorption models in which the adsorbate is placed near the modifier (Figure 6).

These reference models where chose considering that APTES will be initially deposited

perpendicular to the surface. The initially metastable configuration (high energy local

minimum) can be altered by the presence of adsorbates that can interact with APTES

and distort the geometry towards a lower energy conformation. The energy decreasing

is driven by strong surface deformations in the silica and promoted by H interactions

between the tilted APTES and the hydroxyls on the surface. A comparison between the

two 1xAPTES models with the relevant interatomic distances is presented in figure S3.

Figure 4: Schematic representation of HM adsorption on APTES-modified hydroxylated SiO2. at high APTES

coverage. The different regions are denoted by different background colours in the figure. The oxide bulk region is

white, the hydroxylated surface (silane-covered) is reddish and the region where the HM are adsorbed is light blue.

APTES modifiers are represented by purple columns and HM adsorbates by grey balls.

At the lowest coverage of APTES, the DFT calculated adsorption energy for As(OH)3

deposited at the hydroxylated region on the surface (Figure 5a) is -0.53 eV (-0.59 eV

with D3BJ). The adsorption energy from the molecule initially adsorbed next to the

APTES modifier (Figure 6a) is -0.65 eV (-0.70 eV with D3BJ). The adsorption of

As(OH)3 at the silane-APTES interface is slightly more favoured compared to the

adsorption at the hydroxylated region. At the silane-APTES interface, the As(OH)3

molecule is adsorbed at distances of 2.27 Å, 2.11 Å and 1.74 Å between O in the

adsorbate and terminating H on the surface, and at 4.22 Å from APTES (Figure S5a).

When the adsorbate is deposited at the hydroxyl rich region, (Figure 5a) we found

distances of 1.74 Å, 1.93 Å and 2.89 Å for the H-bonds formed between O in the

adsorbate and the surface silane, being 4.82 Å away from APTES. The adsorption

seems to be mainly driven by the interaction between the adsorbed molecule and the

hydroxyl groups on the silica surface while the interaction with APTES is relatively

weak. The dispersion-corrected calculations present equivalent features than the DFT

results, with only a small strengthen for the molecular adsorption.

For Cd(OH)2, the computed adsorption energy is also stronger at the surface-APTES

interface (Figure 6b) with Eads = -0.85 eV, than at the hydroxylated region (Figure 5b) -

with Eads = -0.76 eV. The dispersion-corrected calculation further decreases the

adsorption energy to -0.96 in the most favourable configuration, while at the

hydroxylated region the numbers are similar to the standard DFT formulation. The

surface geometry of modified silica is not visibly affected by the adsorption of

Cd(OH)2, where the effect of the dispersion corrections is also minor. For example, we

measure bond distances (depicted in Figure S5b) of 1.52 Å between H from Cd(OH)2

and N in APTES (1.50 Å with D3BJ); and 1.85 Å between O from Cd(OH)2 and surface

H (1.82 Å with D3BJ).

low coverage high coverage

silane APTES/SiO2 APTES/SiO2 NH2

As(OH)3

DFT -0.53 -0.65 -0.31 -0.28

D3 -0.59 -0.70 -0.77 -0.78

Cd(OH)2

DFT -0.76 -0.85 -0.10 -0.28

D3 -0.77 -0.96 -0.69 -0.87

HgCl2

DFT -0.39 -0.64 +0.41 -0.07

D3 -0.38 -0.72 -0.30 -0.53

Table 1: Adsorption energy (eV) for As(OH)3, Cd(OH)2 and HgCl2 molecules at different adsorption sites

and surface coverages of APTES on partially silane-covered amorphous silica. For each adsorbate, the

adsorption energy calculated with standard DFT (PBE) is presented in the top panel, while the dispersion

corrected energies (D3BJ) are presented directly below.

Figure 5: Structure of molecular adsorption of (a) As(OH)3, (b) Cd(OH)2 and (c) HgCl2 at the

hydroxylated region on surface-modified amorphous SiO2 at low APTES coverage. Here and the

subsequent figures, the bonds formed by Si atoms are yellow, O are red, H are white, C are grey, N are

blue, As is purple, Cd is beige and Cl is green. The front perspective view is presented on the top panel

figures, while the top view, in which the silica and silane species are represented with thin lines, is shown

underneath.

Figure 6: Structure of molecular adsorption of (a) As(OH)3, (b) Cd(OH)2 and (c) HgCl2 at the interface

formed between the silica and APTES on surface-modified amorphous SiO2 at low APTES coverage. The

adsorption is stronger in these models, compared to the adsorption at the hydroxylated region (Figure 5).

The introduction of D3 correction contributes to the decreasing of the adsorption energy.

The adsorption of HgCl2 at the low APTES-covered silica follows a similar trend than

the previously described molecules. At the hydroxylated region (Figure 5c), the

calculated adsorption energy between HgCl2 and the surface is -0.39 eV (-0.38 eV with

D3BJ). For the adsorption of HgCl2 near the APTES molecule, depicted in Figure 6c,

the adsorption energy is more favourable, being this of -0.64 eV (-0.72 eV with D3BJ).

The calculated adsorption energies and geometries are again not strongly affected by the

D3 correction. The measured distance between N in APTES and the adsorbed Hg in its

most stable configuration is 2.56 Å, while in the corrected system (Figure S5c) the

equivalent distance is 2.54 Å.

We conclude that the presence of APTES on a hydroxylated silica surface, even at very

low coverages, and the subsequent formation of an APTES-silane interface, will

promote the adsorption of Cd(OH)2 and HgCl2 molecules, while As(OH)3 was found to

adsorb at the OH terminations on the silica surface. The adsorption of these molecules

was found as spontaneous in all the above-described models, whereas the adsorption

energy is always stronger when the adsorbate is placed near the APTES modifier. The

calculated adsorption energy and surface geometries are not strongly affected by the

addition of vdW interactions into the DFT formulation. However, the adsorption energy

can be strongly affected by surface relaxations, due to the lower stability of isolated

APTES molecules compared to models with higher surface coverage.

3.3.2 Adsorption of pollutants at highly APTES-covered surface

In this section, we discuss the adsorption of heavy-metal compounds on a silica surface

model that is highly-covered (fully-covered) with APTES molecules in the form of self-

assemble monolayer (SAM). We distinguish two different adsorption models. In the

first configuration, the adsorbate is initially placed in the “pocket” formed between the

APTES modifiers and the hydroxylated silica surface, as presented in Figures 7a-c. In

the second configuration, the adsorbate is placed at the terminating amino groups (NH2)

in APTES, and these do not interact directly with the oxide surface (e.g. Figures 7d-f).

The DFT-computed adsorption energy for As(OH)3 on the APTES-covered surface is -

0.31 eV for the molecule adsorbed at the silica-APTES interface (Figure 7a). In the

second configuration (Figure 7d) the adsorbate binds with H in the amino termination,

and the calculated adsorption energy is -0.28 eV. The adsorption energies are further

strengthened in the D3-corrected system, reaching values of -0.77 eV in Figure 7a and -

0.78 eV in Figure 7d. This over-binding is companied by a general decreasing of the

bond distances between the adsorbate and the modifiers. In Figure 7a, the As(OH)3

binds to a surface silanol forming an O···H bond with a length of 1.86 Å (1.79 Å with

D3BJ), and an H···O bond with a surface bridging oxygen at 1.87 Å (1.79 Å with

D3BJ). The distances between the H in As(OH)3 and their nearest H in APTES are 2.27

Å and 2.56 Å, or 2.22 Å and 2.35 Å with D3BJ, respectively. In Figure 7b, the distances

between the adsorbed As(OH)3 and APTES are 1.71 Å, 1.93 Å and 2.67 Å for H···N,

H···N and H···H, respectively. In the dispersion corrected system, the equivalent

interatomic distances are to 1.72 Å, 1.91 Å and 2.43 Å, respectively.

The adsorption of Cd(OH)2 is more favourable when the adsorbate is deposited above

the APTES modifiers (Figure 7e), with Eads = -0.28 eV; compared to the adsorption at

the APTES-silica interface, where Eads = -0.10 eV. The introduction of dispersion

corrections reinforces the adsorption energy by c.a. 0.6 eV in both examples, being

these -0.87 eV for the system in Figure 7e and -0.69 eV in 7b. The interatomic distances

between the adsorbed Cd(OH)2 and APTES are 2.41 Å (2.39 Å with D3BJ) for the bond

formed between Cd and N in Figure 7b; and 1.95 Å and 2.27 Å (1.89 Å and 2.29 Å with

D3BJ) for H···N and O···H, respectively, in Figure 7e.

Figure 7: Structure of molecular adsorption at surface-modified amorphous SiO2 at high APTES

coverage. a), b) and c) show, respectively, the adsorbed As(OH)3, Cd(OH)2 and HgCl2 molecules

deposited at the interface (pocked) formed between the surface and the APTES modifiers; d), e) and f)

display, respectively, the adsorbed As(OH)3, Cd(OH)2 and HgCl2 molecules deposited right above the

APTES modifiers, interacting with the terminating amino groups and far from the oxide surface. The role

of the dispersion correction is critical in this case, increasing the adsorption energies by c.a. 0.4-0.7 eV. In

the top-view figure, the species on the silica surface are represented with lines and the APTES that do not

interact with the adsorbate are represented with thinner sticks. For detailed interactions between the

absorbates and the surfaces, see Figure S6, in which only the main molecules involved in absorbate-

surface interactions are shown for clarity.

The DFT computed adsorption of an HgCl2 molecule was found to be endothermic in

the pocket between the APTES modifiers, with Eads = 0.41 eV (Figure 7c). The

adsorption by the amino terminations, with the adsorbate placed above the modified

surface (Figure 7f), is also quite weak and Eads = -0.07 eV. The introduction of D3

correction contributes to the stabilization of the molecule, and the corrected adsorption

energy is -0.30 eV and -0.53 eV, in Figures 7c and 7f, respectively. Here, standard DFT

calculations significantly underestimate the adsorption energy for the HgCl2 molecule

adsorbed on at the APTES-silica interface, giving a positive (non-spontaneous)

adsorption energy value. As demonstrated in recent works 52, 53, 61, the vdW corrections

play an important role in the interactions between adsorbates and solid surfaces

involving organic compounds. In consistency with these observations, we consider that

the introduction of D3 correction gives a more reliable result than the standard DFT

formulation. The distance between the adsorbed Hg (in HgCl2) and its nearest N is 2.45

Å and 2.39 Å in Figures 7c and 7f, both measured from the D3BJ corrected structure.

When the molecule is initially placed between APTES modifiers, the HgCl2 molecule

migrates towards the outer region of the surface upon DFT relaxation, leading to an

absorption model that is similar to the configuration presented in Figure 7f. This result

suggests the adsorption of HgCl2 by the amino (NH2) terminations as the most

favourable mode.

We conclude that the adsorption of As(OH)3, Cd(OH)2 and HgCl2 is stronger at the

fully-covered APTES-modified surface, compared to hydroxylated silica, especially

when the adsorbates interact directly with the amino terminations. Nevertheless, the

adsorption at the interface formed between APTES and the oxide surface is also

possible, even in the highly APTES-covered models. The consideration of dispersion

corrections (vdW) by the DFT-D3 method with BJ damping into the standard DFT

formulation is critical for the correct reproduction of the binding mechanism. The

dispersion correction increases the adsorption energy by c.a. 0.4-0.7 eV and reduces the

bond distances between the adsorbate and the surface in most of the cases. The As(OH)3

and Cd(OH)2 molecules are strongly adsorbed in both configurations, with binding

energies under -0.5 eV after vdW interactions are turned on. On the other hand, HgCl2

show either very weak or no adsorption with the standard DFT formulation, and the

adsorption mechanism is mainly mediated by vdW forces. In addition, the modification

with APTES molecules provides extra binding sites for the adsorption of these

pollutants, enhancing the efficiency of the initially hydroxylated silica surface as a HM

adsorbent material.

If we compare our simulations with previously available experimental works, we find

that Najafi and coworkers 39 reported a first-order adsorption rate of around 0.03 min-1

for the adsorption of Cd2+ on APTES modified silica nano hollow sphere and silica gel,

which corresponds to an estimated adsorption energy of c.a. -0.79 eV to -0.97 eV if a

pre-exponential factor of 109-1012 s-1 is used. The first-order adsorption rate for the

adsorption of Hg2+ on APTES-functionalized silica microparticles was reported to be

around 0.14 min-1 25, corresponding to adsorption energies between -0.69 eV and -0.87

eV. These adsorption energies are in agreement with our calculations of Cd(OH)2 (-

0.69 eV to -0.96 eV) and HgCl2 (-0.30 eV to -0.72 eV) molecules. Importantly, our

theoretical results predicted the correct order of adsorption performance for Cd(OH)2

and HgCl2 molecules.

3.3.3 Adsorption of water at APTES modified surface

Water is present in nearly any environment and can modify the structure and the

electronic properties of the material with which interacts 62, 63. The presence of

interfacial water can also mediate the interactions between adsorbates and the surface,

having a critical impact in the adsorption of molecules at the material’s surface. A

detailed analysis of water adsorption at all the surface models studied is out of the scope

of this study, more focused on the adsorption mechanisms of HM compounds. In Figure

8, we present the adsorption of a water molecule (H2O) at the low-covered and fully

APTES-covered surface. The D3-corrected system gives spontaneous adsorption of -

0.50 eV on the hydroxylated surface and -0.59 eV atop the APTES. These values are

weaker than the calculated adsorption for As(OH)3 and Cd(OH)2, and comparable to

HgCl2; on the same surface. Therefore, we do not expect that the interaction between

water and APTES will be an impediment that may prevent the adsorption of pollutants

on this material, as can happen at super-hydrophilic surfaces 64-66.

Figure 8: Structure of molecular H2O adsorption at surface-modified amorphous SiO2 at (a) low and (b)

high APTES coverage. The adsorbed H2O molecule is deposited (a) at the hydroxylated region and (b) at

the APTES modifiers, interacting with the terminating amino groups and far from the oxide surface. The

calculated adsorption energies of (a) -0.5 eV and b) -0.59 eV are weaker or comparable to the binding of

HM compounds, therefore a “water barrier” is not expected to mediate the interaction between the surface

and the adsorbed pollutants.

4. Conclusions

We carried out multi-scale simulations combining Molecular Dynamics (MD) and

dispersion corrected Density Functional Theory (DFT-D3BJ) on the atomic-level

structure of several amorphous silica modified surfaces. The amorphous bulk SiO2 was

generated by melt-quenching procedure within MD simulations. The surface model was

cleaved from the bulk and saturated with H and OH terminations to reproduce the

surface silane groups (SiOHx) formed on the oxide’s surface from dissociated water.

The silane-covered surfaces were modified with 3-Aminopropyltriethoxysilane

(APTES). The APTES molecules are stably adsorbed perpendicularly to the silica

surface, with the amino group terminating the modified models. The stability of the

APTES-covered surfaces is promoted upon surface coverage. The formation of APTES

continuous coverages is increased by the bonds formed between the APTES

neighbouring molecules, while isolated molecules can incline to strongly interact with

the OH terminations on the silica surface. Therefore, we expect macroscopic models in

which continuous coverages of APTES, also with the presence of voids and gaps in-

between molecules, may coexist along with stable isolated and tilted APTES molecules

on silane-covered regions.

We discuss the adsorption of several heavy metal (HM) pollutants, namely As(OH)3,

Cd(OH)2 and HgCl2 at the modified surface. At low APTES coverage, the calculated

molecular adsorptions are stronger near the modifier, with energy values between -

0.70 for As(OH)3 and -0.96 eV for Cd(OH)2 in the D3-corrected systems; compared to

molecular deposition at the hydroxylated surface, where the adsorption is also

spontaneous. The deposition of APTES at high coverages increases the adsorption

strength of the tested HM-based molecules. The As(OH)3 and Cd(OH)2 molecules are

strongly adsorbed at the terminating amino groups, with binding energies in a range

between -0.7 eV and -0.9 eV. The absorption of HgCl2 is weaker and is mainly

mediated by vdW interactions. Unlike in low-covered surface, the D3 correction is

critical for the correct reproduction of the adsorption mechanism and increases the

adsorption energy by c.a. 0.4-0.7 eV, while it also reduces the modifier-adsorbate

interatomic distances at high APTES coverages. Our theoretical results predicted the

correct order of adsorption performance for Cd and Hg compounds, in line with

previous experimental works.

The adsorption of molecular water is weaker compared to the HM compounds in their

most favourable adsorption mode. Hence, we do not expect that the interactions

between water and APTES could form a barrier that could prevent the adsorption of

pollutants on this material.

Based on our results, we conclude that APTES modification of silica increases the

binding strength of several HM on the surface while it forms complex nanostructured

patterns on the surface that will provide more available binding sites for the adsorption

of these pollutants. Therefore, we propose APTES modified silica as a potential

candidate for removing HM-pollutants from aquatic media. The outcomes of this study

can be also used to design novel structures and biomaterials for HMs adsorption based

on the understanding of diatoms’ fundamental structural and electronic properties.

Conflicts of interest

There are no conflicts to declare.

Acknowledgements

This work was supported by the Startup Foundation for Peacock Talents, Shenzhen

University, the Postdoctoral Science Foundation of China under Grant No.

2018M643152 and the National Natural Science Foundation of China under Grant No.

31770777. We acknowledge the Paratera cloud server and the National Supercomputing

Center in Shenzhen for the provision of computational resources and technical support.

References

1. Dolatabadi, J. E. N.; de la Guardia, M., Applications of diatoms and silica

nanotechnology in biosensing, drug and gene delivery, and formation of complex metal

nanostructures. TrAC Trends in Analytical Chemistry 2011, 30 (9), 1538-1548.

2. Ragni, R.; Cicco, S.; Vona, D.; Leone, G.; Farinola, G. M., Biosilica from

diatoms microalgae: smart materials from bio-medicine to photonics. Journal of

Materials Research 2016, 32 (2), 279-291.

3. Lang, Y.; del Monte, F.; Dockery, P., The multiple roles of diatoms in

environmental applications: Prospects for sol-gel modified diatoms. In Sol-Gel

Materials for Energy, Environment and Electronic Applications, Pillai, S. C.; Hehir, S.,

Eds. Springer International Publishing: Cham, 2017; pp 101-120.

4. Ma, J.; Zhou, B.; Duan, D.; Wei, Y.; Pan, K., Silicon limitation reduced the

adsorption of cadmium in marine diatoms. Aquatic Toxicology 2018, (202), 136-144.

5. Zhang, J.; Ding, T.; Zhang, Z.; Xu, L.; Zhang, C., Enhanced adsorption of

trivalent arsenic from water by functionalized diatom silica shells. PloS one 2015, 10

(4), e0123395.

6. Sumper, M.; Brunner, E., Learning from diatoms: Nature's tools for the

production of nanostructured silica. Advanced Functional Materials 2006, 16 (1), 17-

26.

7. Losic, D.; Mitchell, J. G.; Voelcker, N. H., Diatomaceous lessons in

nanotechnology and advanced materials. Advanced Materials 2009, 21 (29), 2947-2958.

8. Gordon, R.; Losic, D.; Tiffany, M. A.; Nagy, S. S.; Sterrenburg, F. A., The

glass menagerie: diatoms for novel applications in nanotechnology. Trends in

biotechnology 2009, 27 (2), 116-127.

9. Mansur, H. S.; Lobato, Z. P.; Oréfice, R. L.; Vasconcelos, W. L.; Oliveira, C.;

Machado, L. J., Surface Functionalization of Porous Glass Networks:  Effects on

Bovine Serum Albumin and Porcine Insulin Immobilization. Biomacromolecules 2000,

1 (4), 789-797.

10. Li, J.; Cui, J.; Yang, J.; Ma, Y.; Qiu, H.; Yang, J., Silanized graphene oxide

reinforced organofunctional silane composite coatings for corrosion protection.

Progress in Organic Coatings 2016, 99, 443-451.

11. Marques, M. E.; Mansur, A. A.; Mansur, H., Chemical functionalization of

surfaces for building three-dimensional engineered biosensors. Applied Surface Science

2013, 275, 347-360.

12. Li, H.; Perkas, N.; Li, Q.; Gofer, Y.; Koltypin, Y.; Gedanken, A., Improved

silanization modification of a silica surface and its application to the preparation of a

silica-supported polyoxometalate catalyst. Langmuir 2003, 19 (24), 10409-10413.

13. Cheng, G.; Luo, J.; Qian, J.; Miao, J., Surface modification of nano-TiN by

using silane coupling agent. Materials Science-Poland 2014, 32 (2).

14. Hernández-Ávila, J.; Salinas-Rodríguez, E.; Cerecedo-Sáenz, E.; Reyes-

Valderrama, M. I.; Arenas-Flores, A.; Román-Gutiérrez, A. D.; Rodríguez-Lugo, V.,

Diatoms and Their Capability for Heavy Metal Removal by Cationic Exchange. Metals

2017, 7 (5), 169.

15. Bello, O. S.; Adegoke, K. A.; Oyewole, R. O., Insights into the adsorption of

heavy metals from wastewater using diatomaceous earth. Separation Science and

Technology 2014, 49 (12), 1787-1806.

16. Fernández, M. R.; Martín, G.; Corzo, J.; de la Linde, A.; García, E.; López,

M.; Sousa, M., Design and testing of a new diatom-based index for heavy metal

pollution. Archives of Environmental Contamination and Toxicology 2018, 74 (1), 170-

192.

17. Li, H.; Xie, Q. L.; Chen, N. C.; Xu, H.; Ma, L. L., Research Progress of

Adsorption on Heavy Metals from Aqueous Solutions by Modified Diatomite. Key

Engineering Materials 2016, 697, 766-770.

18. Ma, J.; Zhou, B.; Duan, D.; Pan, K., Salinity-dependent nanostructures and

composition of cell surface and its relation to Cd toxicity in an estuarine diatom.

Chemosphere 2019, 215, 807-814.

19. Kabiri, S.; Tran, D. N.; Azari, S.; Losic, D., Graphene-diatom silica aerogels

for efficient removal of mercury ions from water. ACS applied materials & interfaces

2015, 7 (22), 11815-11823.

20. Duffus, J. H., " Heavy metals" a meaningless term?(IUPAC Technical Report).

Pure and applied chemistry 2002, 74 (5), 793-807.

21. Hu, H.; Jin, Q.; Kavan, P., A study of heavy metal pollution in China: Current

status, pollution-control policies and countermeasures. Sustainability 2014, 6 (9), 5820.

22. Järup, L., Hazards of heavy metal contamination. British Medical Bulletin 2003,

68 (1), 167-182.

23. Wang, Y.; Björn, L. O., Heavy metal pollution in Guangdong Province, China,

and the strategies to manage the situation. Frontiers in Environmental Science 2014, 2

(9).

24. Lambert, M.; Leven, B.; Green, R., New methods of cleaning up heavy metal in

soils and water. Environmental science and technology briefs for citizens. Kansas State

University, Manhattan, KS 2000.

25. Yu, Y.; Addai-Mensah, J.; Losic, D., Functionalized diatom silica

microparticles for removal of mercury ions. Science and technology of advanced

materials 2012, 13 (1), 015008.

26. Pawar, R. R.; Kim, M.; Kim, J.-G.; Hong, S.-M.; Sawant, S. Y.; Lee, S. M.,

Efficient removal of hazardous lead, cadmium, and arsenic from aqueous environment

by iron oxide modified clay-activated carbon composite beads. Applied Clay Science

2018, 162, 339-350.

27. Gulens, J.; Champ, D. R.; Jackson, R. E., Influence of redox environments on

the mobility of arsenic in ground water. ACS Publications: 1979.

28. Ferguson, J. F.; Gavis, J. J. W. r., A review of the arsenic cycle in natural waters.

1972, 6 (11), 1259-1274.

29. Liu, Z.; Shen, J.; Carbrey, J. M.; Mukhopadhyay, R.; Agre, P.; Rosen, B. P.,

Arsenite transport by mammalian aquaglyceroporins AQP7 and AQP9. 2002, 99 (9),

6053-6058.

30. Ryan, J. A.; Pahren, H. R.; Lucas, J. B. J. E. R., Controlling cadmium in the

human food chain: a review and rationale based on health effects. 1982, 28 (2), 251-

302.

31. Bodek, I., Environmental inorganic chemistry: properties, processes, and

estimation methods. Pergamon: 1988.

32. Lindberg, S. E.; Brooks, S.; Lin, C. J.; Scott, K. J.; Landis, M. S.; Stevens, R.

K.; Goodsite, M.; Richter, A., Dynamic Oxidation of Gaseous Mercury in the Arctic

Troposphere at Polar Sunrise. Environmental Science & Technology 2002, 36 (6), 1245-

1256.

33. Atwood, D. A.; Atwood, D. A.; Bebout, D.; Berry, S.; Andrews, J.; Grant, G.;

Rabinovich, D.; Zaman, M.; Zhang, H., Recent developments in mercury science.

Springer: 2006; Vol. 120.

34. Morel, F. M.; Kraepiel, A. M.; Amyot, M., The chemical cycle and

bioaccumulation of mercury. Annual Review of Ecology and Systematics 1998, 29 (1),

543-566.

35. Prodromidis, M. I., Impedimetric immunosensors—A review. Electrochimica

Acta 2010, 55 (14), 4227-4233.

36. Kathi, J.; Rhee, K., Surface modification of multi-walled carbon nanotubes using

3-aminopropyltriethoxysilane. Journal of Materials Science 2008, 43 (1), 33-37.

37. Sarkar, A.; Daniels-Race, T., Electrophoretic deposition of carbon nanotubes on

3-amino-propyl-triethoxysilane (APTES) surface functionalized silicon substrates.

Nanomaterials 2013, 3 (2), 272-288.

38. Rahman, I.; Jafarzadeh, M.; Sipaut, C., Synthesis of organo-functionalized

nanosilica via a co-condensation modification using γ-aminopropyltriethoxysilane

(APTES). Ceramics International 2009, 35 (5), 1883-1888.

39. Najafi, M.; Yousefi, Y.; Rafati, A., Synthesis, characterization and adsorption

studies of several heavy metal ions on amino-functionalized silica nano hollow sphere

and silica gel. Separation and Purification Technology 2012, 85, 193-205.

40. Kong, X.-f.; Yang, B.; Xiong, H.; Zhou, Y.; Xue, S.-g.; Xu, B.-q.; Wang, S.-

x. J. J. o. C. S. U., Selective removal of heavy metal ions from aqueous solutions with

surface functionalized silica nanoparticles by different functional groups. 2014, 21 (9),

3575-3579.

41. Plimpton, S., Fast parallel algorithms for short-range molecular dynamics.

Journal of Computational Physics 1995, 117 (1), 1-19.

42. Munetoh, S.; Motooka, T.; Moriguchi, K.; Shintani, A., Interatomic potential

for Si–O systems using Tersoff parameterization. Computational Materials Science

2007, 39 (2), 334-339.

43. Hoang, V. V., Molecular dynamics simulation of amorphous SiO2 nanoparticles.

The Journal of Physical Chemistry B 2007, 111 (44), 12649-12656.

44. Vollmayr, K.; Kob, W.; Binder, K., Cooling-rate effects in amorphous silica: A

computer-simulation study. Physical Review B 1996, 54 (22), 15808.

45. Donadio, D.; Bernasconi, M.; Tassone, F., Photoelasticity of crystalline and

amorphous silica from first principles. Physical Review B 2003, 68 (13), 134202.

46. Deringer, V. L.; Bernstein, N.; Bartók, A. P.; Cliffe, M. J.; Kerber, R. N.;

Marbella, L. E.; Grey, C. P.; Elliott, S. R.; Csányi, G. J. T. j. o. p. c. l., Realistic

atomistic structure of amorphous silicon from machine-learning-driven molecular

dynamics. The Journal of Physical Chemistry Letters 2018, 9 (11), 2879-2885.

47. Nolan, M.; Legesse, M.; Fagas, G., Surface orientation effects in crystalline–

amorphous silicon interfaces. Physical Chemistry Chemical Physics 2012, 14 (43),

15173-15179.

48. Xue, K.; Niu, L.-S.; Shi, H.-J., Effects of quench rates on the short-and

medium-range orders of amorphous silicon carbide: A molecular-dynamics study.

Journal of Applied Physics 2008, 104 (5), 053518.

49. Perdew, J. P.; Burke, K.; Ernzerhof, M., Generalized gradient approximation

made simple. Physical Review Letters 1996, 77 (18), 3865.

50. Grimme, S.; Antony, J.; Ehrlich, S.; Krieg, H., A consistent and accurate ab

initio parametrization of density functional dispersion correction (DFT-D) for the 94

elements H-Pu. The Journal of Chemical Physics 2010, 132 (15), 154104.

51. Grimme, S.; Ehrlich, S.; Goerigk, L., Effect of the damping function in

dispersion corrected density functional theory. Journal of Computational Chemistry

2011, 32 (7), 1456-1465.

52. Ramalho, J. P. P.; Gomes, J. R.; Illas, F., Accounting for van der Waals

interactions between adsorbates and surfaces in density functional theory based

calculations: selected examples. RSC advances 2013, 3 (32), 13085-13100.

53. Liu, W.; Ruiz, V. G.; Zhang, G.-X.; Santra, B.; Ren, X.; Scheffler, M.;

Tkatchenko, A., Structure and energetics of benzene adsorbed on transition-metal

surfaces: density-functional theory with van der Waals interactions including collective

substrate response. New Journal of Physics 2013, 15 (5), 053046.

54. Klimeš, J.; Michaelides, A., Perspective: Advances and challenges in treating

van der Waals dispersion forces in density functional theory. The Journal of Chemical

Physics 2012, 137 (12), 120901.

55. Fogarty, J. C.; Aktulga, H. M.; Grama, A. Y.; Van Duin, A. C.; Pandit, S. A.,

A reactive molecular dynamics simulation of the silica-water interface. The Journal of

Chemical Physics 2010, 132 (17), 174704.

56. Shan, T.-R.; Devine, B. D.; Hawkins, J. M.; Asthagiri, A.; Phillpot, S. R.;

Sinnott, S. B. J. P. R. B., Second-generation charge-optimized many-body potential for

Si/SiO 2 and amorphous silica. 2010, 82 (23), 235302.

57. Mozzi, R. L.; Warren, B. E., The structure of vitreous silica. 1969, 2 (4), 164-

172.

58. Yang, J.; Wang, E., Reaction of water on silica surfaces. Current Opinion in

Solid State Materials Science 2006, 10 (1), 33-39.

59. Gutiérrez Moreno, J. J.; Fronzi, M.; Lovera, P.; O’Riordan, A.; Nolan, M.,

Stability of adsorbed water on TiO2–TiN Interfaces. A first-principles and ab initio

thermodynamics investigation. The Journal of Physical Chemistry C 2018, 122 (27),

15395-15408.

60. Gutiérrez Moreno, J. J.; Fronzi, M.; Lovera, P.; O’Riordan, A.; Ford, M. J.;

Li, W.; Nolan, M., Structure, stability and water adsorption on ultra-thin TiO2 supported

on TiN. Physical Chemistry Chemical Physics 2019.

61. Carrasco, J.; Liu, W.; Michaelides, A.; Tkatchenko, A., Insight into the

description of van der Waals forces for benzene adsorption on transition metal (111)

surfaces. The Journal of Chemical Physics 2014, 140 (8), 084704.

62. Henderson, M. A., The interaction of water with solid surfaces: fundamental

aspects revisited. Surface Science Reports 2002, 46 (1), 1-308.

63. Diebold, U., The surface science of titanium dioxide. Surface Science Reports

2003, 48 (5), 53-229.

64. Guan, K., Relationship between photocatalytic activity, hydrophilicity and self-

cleaning effect of TiO2/SiO2 films. Surface and Coatings Technology 2005, 191 (2-3),

155-160.

65. Zhao, X.; Zhao, Q.; Yu, J.; Liu, B., Development of multifunctional

photoactive self-cleaning glasses. Journal of Non-Crystalline Solids 2008, 354 (12-13),

1424-1430.

66. Kobayashi, M.; Terayama, Y.; Yamaguchi, H.; Terada, M.; Murakami, D.;

Ishihara, K.; Takahara, A., Wettability and Antifouling Behavior on the Surfaces of

Superhydrophilic Polymer Brushes. Langmuir 2012, 28 (18), 7212-7222.

download fileview on ChemRxivA computational study of APTES surface functionalization ... (1.48 MiB)

Supporting information

A computational study of APTES surface functionalization of diatom-

like amorphous SiO2 surfaces for heavy metal adsorption

José Julio Gutiérrez Moreno 1,2 , Ke Pan 1, Yu Wang 1, Wenjin Li 1*

1 Institute for Advanced Study, Shenzhen University, Shenzhen 518060, China. 2 Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and

Guangdong Province, College of Physics and Optoelectronic Engineering, Shenzhen

University, Shenzhen 518060, China.

* liwenjin@szu.edu.cn

Figure S1: To assess the influence of size effect in our model, which in some cases may lead to

errors associated with the small size of the system simulated, we run a similar simulation for a

2160 atoms cubic box with dimensions of 33.6 Å. This figure shows the pair distribution

function (PDF) of amorphous SiO2 bulk model structure with 2160 atoms and comparison with

the 216 atoms (light colour lines). The different pairs are colour coded in the figure, with Si-O

pairs represented in blue, Si-Si in green and O-O in red. The normalized number of pairs is

represented along the y-axis while the corresponding distance in Å is on the x. For the structure

of bulk amorphous SiO2 model structures (2160 atoms), Si atoms are represented by yellow

spheres and O atoms are red.

After going through a melt-quenching process analogous to the described before, the simulation

box exhibits dimensions of 31.66 Å and a density of 2.26 g/cm3 at ambient conditions, which is

comparable to the smaller model. The PDF of the larger system presents a similar distribution

compared to the 216 atoms model. The only appreciable difference is the smother lines in the

2160 model compared with the smaller one, which is expected due to a large number of Si and

O species in the box.

E total (eV) ΔE undistorted (%) ΔE distorted (%)

silane covered -1825.01 - -

1xAPTES undistorted -1869.57 100 -

1xAPTES distorted -1876.79 - 100

3xAPTES aligned -1982.03 17% 11%

3xAPTES homogeneous -1982.23 18% 11%

8xAPTES -2245.17 18% 12%

Table S1: Total energy values and energy differences as a function of the APTES surface

coverage. The ΔE values are calculated using the energy difference between the hydroxylated

model (silane covered) and the 1xAPTES modified as a reference value. The positive ΔE

indicate the stabilization of the highly-covered models compared to isolated APTES.

1xAPTES

undistorted

1xAPTES

distorted

3xAPTES

aligned

3xAPTES

homogeneous 8xAPTES

Si-C 1.86 1.85 1.83-1.86 1.84-1.86 1.83-1.86

C-C 1.53-1.54 1.53-1.54 1.52-1.54 1.53-1.54 1.52-1.55

C-N 1.46 1.47 1.46-1.47 1.46-1.48 1.47-1.48

C-H 1.10-1.11 1.10-1.11 1.10-1.11 1.10-1.11 1.10-1.11

N-H 1.02 1.02 1.02 1.02 1.02

Table S2: Bond distances range (expressed in Å) between surface Si and C from APTES and

interatomic distances in the APTES molecule as a function of the surface coverage.

1xAPTES

undistorted

1xAPTES

distorted

3xAPTES

aligned

3xAPTES

homogeneous 8xAPTES

Si-C-C 114 119 109-121 110-115 112-122

C-C-C 114 111 111-112 112-114 112-114

C-C-N 110 111 110-112 110-111 110-113

Table S3: Angle ranges (expressed in º) formed between Si(surface)-C-C, C-C-C and C-C-N

from APTES as a function of the surface coverage.

Figure S2: Structure of APTES adsorption on amorphous silica. The adsorbed APTES

molecule and the three binding points to the silica surface are highlighted in the figure, while

the rest of the atoms on the surface are represented with thin lines.

Figure S3: Structure of 1xAPTES adsorption on amorphous silica. The shortened interatomic

distances between the adsorbed APTES and silane groups on the silica surface leads to an

overall decreasing of the total energy. Distances are denoted with black dashed lines and

expressed in Å.

Figure S4: Structure of 3xAPTES adsorption on amorphous silica. The (a) aligned distribution

presents the APTES molecules placed next to each other the surface. This distribution was

found to be less favourable by only 0.09 eV per APTES compared to (b). The preferential

adsorption if presented in (b), where the modifiers are more sparsely distributed on the surface.

This distribution allows some isolated APTES to incline from their initially vertical position and

interact with surface silane groups by H-bonding. The small energy difference between these

two models suggests the likely coexistence of both distributions on the material’s surface.

Figure S5: Distances between the HM compounds and their closest binding sites on the low

APTES-covered surface. The adsorbed HM are placed near the APTES modifier (energetically

favoured configuration), as shown in Figure 6 in main text. Distances are denoted with black

dashed lines and expressed in Å.

Figure S6: Distances between the HM compounds adsorbed on the highly-covered APTES-

modified and their closest binding sites. The structures in the top panel represent the adsorbed a)

As(OH)3, b) Cd(OH)2 and c) HgCl2 molecules deposited on the hydroxylated surface, at the

interface (pocked) formed between the surface and the APTES modifiers. The figures on the

bottom present the adsorbed d) As(OH)3, e) Cd(OH)2 and f) HgCl2 molecules above the APTES

modifiers, interacting with the terminating amino groups and far from the oxide surface.

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