An Acad Bras Cienc (2021) 93(4): e20200774 DOI 10.1590/0001-3765202120200774
Anais da Academia Brasileira de Ciências | Annals of the Brazilian Academy of Sciences
Printed ISSN 0001-3765 I Online ISSN 1678-2690
www.scielo.br/aabc | www.fb.com/aabcjournal
PHYSICAL SCIENCES
Hierarchical Structure and Magnetic Behavior of
Zn-Doped Magnetite Aqueous Ferrofluids
Prepared from Natural Sand for Antibacterial
Agents
AHMAD TAUFIQ, DEFI YULIANTIKA, SUNARYONO SUNARYONO, ROSY E. SAPUTRO,
NURUL HIDAYAT, NANDANG MUFTI, HENDRA SUSANTO, SIRIWAT SOONTARANON
& HADI NUR
Abstract: This study performs natural sand-based synthesis using the sonochemical
route for preparing Zn-doped magnetite nanoparticles. The nanoparticles were dispersed
in water as a carrier liquid to form Zn-doped magnetite aqueous ferrofluids. Structural
data analysis indicated that the Zn-doped magnetite nanoparticles formed a nanosized
spinel structure. With an increase in the Zn content, the lattice parameters of the
Zn-doped magnetite nanoparticles tended to increase because Zn2+ has a larger ionic
radius than those of Fe3+ and Fe2+ . The existence of Zn–O and Fe–O functional groups
in tetrahedral and octahedral sites were observed in the wavenumber range of 400–700
cm–1 . The primary particles of the Zn-doped magnetite ferrofluids tended to construct
chain-like structures with fractal dimensions of 1.2–1.9. The gas-like compression (GMC)
plays as a better model than the Langevin theory to fit the saturation magnetization
of the ferrofluids. The ferrofluids exhibited a superparamagnetic character, with their
magnetization was contributed by aggregation. The Zn-doped magnetite ferrofluids
exhibited excellent antibacterial activity against gram-positive and negative bacteria. It
is suggested that the presence of the negatively charged surface and the nanoparticle
size may contribute to the high antibacterial activity of Zn-doped magnetite ferrofluids
and making them potentially suitable for advanced biomedical.
Key words: Iron sand, Zn-doped magnetite, aqueous ferrofluid, fractal structure,
antibacterial agent.
INTRODUCTION
Nanomaterials in the range 1–100 nm have become essential owing to their increased
surface-to-volume ratio. Magnetite, as a nanomaterial, has broad advanced applications in various
fields, particularly in medical and biological areas. During the last five years, it has been reported
that magnetite nanoparticles have potential applications in cancer therapy (Farzin et al. 2019),
as organic-inorganic Bronsted acid catalyst (Maleki et al. 2019), as contrast agents for computed
tomography scanning and magnetic resonance imaging (Sood et al. 2017), in bioseparation (Adams
et al. 2018), in thermal treatment and bioimaging (Yang et al. 2017), as carriers for removal Cr(VI) from
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HIERARCHICAL STRUCTURE AND MAGNETIC BEHAVIOR OF ZN-DOPED MAGNETITE AQUEOUS FERROFLUIDS
aqueous solution (Zhou et al. 2020), in targeted anticancer drug delivery system (Yew et al. 2020), and
as an antibacterial agent (Jency et al. 2020).
The integration of medicine and nanotechnology offers new prospects for treating human
diseases (Yan et al. 2019). Recently, the antibacterial performance of nanomaterials has received
global attention owing to its significant advantages in inhibiting bacterial growth rates, and these
have been propounded as nanomedicines. Nanoparticle activities in biological processes have been
scrutinized because of the extensive development of biotechnology combined with nanotechnology
in biomedical sciences. Their significant toxicity to bacteria suggests that nanoparticles could play
a fundamental role as future bactericides. The high biocompatibility of nanoparticles makes them
potentially promising as safety agents in living organisms. Although their medical application using
antibiotics is well established, there is limited information on how liquid nanoparticles, especially
in ferrofluids, can be postulated as secondary bactericides in medical treatment. Therefore, to allow
their more specific application as powerful antibacterial agents, it is essential to produce magnetite
nanoparticles in magnetite ferrofluids.
Practically, magnetite ferrofluids can be produced by coating magnetite nanoparticles and
dispersing them in an appropriate carrier liquid. A coating agent using a surfactant and carrier liquid
plays a vital role in providing highly stable ferrofluids for antibacterial agents (Petrenko et al. 2018).
Therefore, herein, we focused on using water as a carrier liquid to produce the aqueous magnetite
ferrofluids owing to their simplicity, stability, and biocompatibility. Nevertheless, despite producing
magnetite nanoparticles in aqueous ferrofluids, combining magnetite nanoparticles with metals and
metal oxides has also become an essential method for enhancing their antibacterial performance,
such as in magnetite/mordenite/CuO core-shell nanocomposites (Rajabi & Sohrabnezhad 2018),
magnetite/Ag nanocomposites (Amarjargal et al. 2013) (SiO2 /SnO2 )@ZnO@Fe3 O4 nanocomposites
(Sekhar et al. 2019), Fe3 O4 @PEG-SO3 H nanocomposite (Maleki et al. 2018), magnetite-TiO2 nanosheets
(Ma et al. 2015), magnetite/TiO2 core/shell nanoparticles (Chen et al. 2008), and hyperbranched
magnetite/polyurethane nanocomposites (Das et al. 2013). Introducing an appropriate transition metal
into magnetite is also one of the most potent methods for increasing the antibacterial activity. A
recent study shows that the Zn-doped magnetite exhibits a superior antibacterial performance than
a pure magnetite nanoparticle (Anjana et al. 2018). However, this work used only one Zn composition,
and was not yet fabricated as ferrofluids form. It is noteworthy that the Zn content may further
affect the particle size and structural, and magnetic properties of the Zn-doped magnetite ferrofluids,
resulting in changes in their antibacterial performance. Therefore, a comprehensive study involving
the variation of the Zn composition is required to obtain an appropriate composition for optimizing
the antibacterial performance of Zn-doped magnetite. Moreover, to reduce the mass production cost,
it is essential to produce high-quality Zn-doped magnetite ferrofluids using an inexpensive main
precursor and simple technique. Interestingly, natural sand, which is inexhaustible around the world
and especially in all areas of Indonesia, offers new possibilities for generating Zn-doped magnetite
ferrofluids.
In the application step, the critical process is the synthesis of the ferrofluids, which determines
the physicochemical properties and thermodynamic activities within the living materials (Taufiq
et al. 2018). Interestingly, the sonochemical technique allows the production of high-purity magnetic
nanoparticles with uniform size and high top surface area to bind with living material on cell
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membranes and walls. This characteristic showed a linear relation with solubility in an aqueous
environment as in fluids in living organisms. It plausibly causes the nanoparticles’ biological features
to generate different activities among those nanoparticles. Furthermore, this study employed a
sonochemical technique primarily owing to its advantages in generating negative pressure against
intermolecular binding in fluidic media, easily forming smaller particles and effectively preventing
agglomeration (Sancheti & Gogate 2017). Therefore, herein, we report the synthesis of Zn-doped
magnetite ferrofluids from natural sand by employing the sonochemical technique. Furthermore,
selected properties, such as hierarchical structure, particle size and morphology, functional group,
magnetization, and antibacterial activity, based on a dilution method, are also discussed.
MATERIALS AND METHODS
Natural sand was utilized as the primary precursor in synthesizing the Zn-doped magnetite
nanoparticles using the sonochemical route. The natural sand was obtained from Sine Beach located
in Tulungagung Regency, East Java, Indonesia (geographic coordinates of 8° 17’ 28.3” S 111° 56’ 06.7” E).
First, magnetite (Fe3 O4 ) powder extracted from natural sand was made to react with hydrochloric acid
(Sigma Aldrich, PA) at room temperature to obtain FeCl3 and FeCl2 solutions, as shown in Equation 1.
This reaction was maintained by employing a magnetic stirrer for 20 min at ambient temperature.
Fe3 O4 + 8 HCl −−→ FeCl2 + 2 FeCl3 + H2 O
(1–y )FeCl2 + 2 FeCl3 + y ZnCl2 + 8 NH4 OH −−→ Zny Fe3–y O4 + 4 (1+y )H2 O + 8 NH4 Cl
(1)
(2)
The resultant product shown in Equation 1 was then made to react with ZnCl2 (Sigma Aldrich, PA)
based on the targeted Zn/Fe ratio and titrated with ammonium hydroxide (Sigma Aldrich, PA) using
an ultrasonic bath with a frequency of 40 kHz to yield a black precipitate. This reaction was predicted
using Equation 2. The y/(y – 3) compositions (Zn/Fe ratios) of the samples were 0, 0.03, 0.07, 0.10,
and 0.13. These samples were coded as Y1, Y2, Y3, Y4, and Y5, respectively. Samples were washed with
distilled water several times until a normal pH was achieved to remove the remaining products shown
in Equation 2. Herein, the Zn-doped magnetite powders were prepared by drying the final products
at 100°C for one hour. Meanwhile, the Zn-doped magnetite ferrofluids were prepared by coating the
Zn-doped magnetite powders using tetramethylammonium hydroxide (Sigma Aldrich, PA) and then
dispersed in water.
The prepared samples were characterized by the X-ray diffraction (XRD) technique using an X-ray
diffractometer (X’Pert Pro, PanAnalytical, Netherlands) with Cu-Kα radiation (1.5406 Å) and 2-theta in
the range of 20➦–80➦, a transmission electron microscopy (TEM, JEOL JEM 1400, Japan) at a magnification
of 150,000×, a Fourier transform infrared (FTIR) spectroscopy (IRPrestige-21 spectrophotometer,
Shimadzu, Japan) in the wavenumber range of 400–4000 cm–1 , a vibrating sample magnetometer
(VSM) using OXFORD 1.2 H machine (Oxford Instrument, UK) with an applied magnetic field in
the range of -1 T and 1 T, and synchrotron-based small-angle X-ray scattering (SAXS) BL 1.3 SAXS
owned by Synchrotron Light Research Institute-Thailand to investigate the structure, particle size
and morphology, functional group, and magnetic properties. In this study, all characterizations were
maintained at ambient temperature. Meanwhile, the antibacterial performances of the Zn-doped
magnetite ferrofluids were investigated using a colony test employing E. coli and B. subtilis bacteria.
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All the characterization processes were conducted at ambient temperature. Approximately 0.1 mg of
E. coli and B. subtilis bacteria were suspended in 1 ml liquid nutrient. The sample was then incubated
at room temperature for 24 h. The bacterial suspension was diluted with liquid nutrients, resulting
in a similar density to that of the McFarland standard. The following step involved subculture on
Mueller–Hinton agar (MHA) medium and incubation for 24 h. The colony count method was used to
determine the bacterial growth rate in the medium and the number of bacterial colonies in this control
group. As a negative control group, other samples were treated with 0.1 g erythromycin antibiotic
dissolved in 1 ml of liquid nutrient. In the next step, a 0.5 ml antibiotic solution was mixed with 4.5 ml
bacterial suspension. The sample was incubated at room temperature for 24 h and subcultured on the
MHA medium. The last stage involved measuring the growing colonies on the media through colony
quantification. However, the treatment group was prepared by diluting 0.5 ml ferrofluids with 4.5 ml
bacterial suspension to obtain a total bacterial concentration of 5 × 105 CFU/ml. These samples were
then incubated for 24 h and subcultured on the MHA medium to observe the colony formation. As in
the previous steps, the total number of colonies formed was measured using a colony count method.
RESULTS AND DISCUSSION
The XRD patterns of the prepared Zn-doped magnetite powders, as shown in Figure 1a, are represented
by circles, whereas the quantitative data analysis results (fitting model) performed using the Rietveld
method by employing the Rietica program are represented by solid black lines. Visually, the solid
black lines coincide with the circles, indicating that the crystal structure model using ICSD 30860
for magnetite agrees well with the experimental data. The XRD results showed that all dominant
diffraction peaks were detected as the magnetite phase with hkl planes of (220), (311), (400), (422),
(511), (440), and (533) denoted by XRD peaks at 30.31°, 35.68°, 43.40°, 53.84°, 57.44°, 62.96°, and
74.22°respectively. Samples Y1, Y2, Y3, Y4, and Y5 have Zn/Fe ratios of 0, 0.03, 0.07, 0.10, and 0.13,
respectively. Based on the qualitative data analysis for Figure 1a, all samples exhibited similarly XRD
patterns, showing no impurity phases.
The quantitative data analysis for Figure 1b presented that each sample had a different peak
position for the highest peak. The increasing Zn content generally tended to change the 2-theta to
a lower value, indicating the decreasing particle size of the samples due to the formation of crystal
defect (Kucuk 2019).The crystal defect could be observed by the shiftiness of diffraction peak at 2-theta
(311), indicating that the Zn2+ ions had successfully replaced Fe2+ and Fe3+ in the spinel system.
According to the Bragg law, the displacement of the diffraction peak to a lower position of 2-theta
increases the lattice parameters. The data analysis results such as 2-theta position for the highest
peak, lattice parameters, crystal volume, molecular weight, crystallite size, and ionic distribution of the
samples are listed in Table I. All samples had a spinel cubic structure constructed by two sublattices,
i.e., tetrahedral (A) and octahedral (B) sites. All samples formed a crystal structure with a space group
Fd-3m Z. The ionic distribution of the Zn-doped magnetite was calculated based on the previous works
(Liu et al. 2016, Modaresi et al. 2019, Behdadfar et al. 2012, Lv et al. 2015, Simmons et al. 2015). Based
on Table I, it can be inferred that increasing the Zn content tends to increase the lattice parameters
(a = b = c) of the samples. Theoretically, this increase resulted from an increase in the content of
Zn2+ , which has a larger ionic radius than that of Fe2+ and Fe3+ (Mozaffari et al. 2015). Furthermore,
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Figure 1. (a) XRD patterns and (b) highest diffraction peaks of the Zn-doped magnetite nanoparticles.
since the spinel structure was cubic with V = a × b × c, the crystal volume also increased with lattice
parameters a, b, and c. The Zn2+ (74 pm) had a preference to replace place Fe2+ (61 pm) at the
A-site. Meanwhile, Fe2+ (49 pm) partially transited to Fe3+ at B-site to neutralize the electricity of
the crystal (Liu et al. 2012, 2016). The replacement of metallic ions with the larger ionic radius at A
and B-sites expanded the lattice parameters and crystal volume for samples Y1-Y4. However, it was
not observed for Y5 with the highest Zn content. The lattice parameters and crystal volume of Y5
decreased compared to that of Y4. This phenomenon was believed because Zn2+ partially moved to
the B-site. Furthermore, the crystallite size of the samples was in the range of 6.8(2)–8.6(3) nm.
FTIR experiment was conducted to study the sample functional groups further. The FTIR spectra in
the wavenumber range of 400–4000 cm–1 , as shown in Figure 2, provide information on the functional
groups of the Zn-doped magnetite nanoparticles. Based on the data analysis, the Zn-doped magnetite
nanoparticles indicated metal oxide (MO) groups originating from Zn–O and Fe–O functional groups
in the wavenumber range of 400–700 cm–1 (Mozaffari et al. 2015). Specifically, the wavenumber range
480–410 cm–1 showed atomic vibrations from the metals (Zn2+ , Fe2+ , and Fe3+ ) in tetrahedral and
octahedral sites (Tehrani et al. 2012). These indicated that the spinel structure of the samples was
successfully formed in agreement with the above XRD analysis. In the inverse spinel structure, the
Zn–O and Fe–O functional groups at tetrahedral and octahedral sites, respectively, overlap and reduce
the transmission intensity of the MOs. The present Zn ions with an atomic weight exceeding that of
Fe ions led to a decrease in the transmission intensity of the metal bindings. Furthermore, the peaks
at approximately 1630 and 3340 cm–1 originated from hydroxyl functional groups for the symmetrical
and asymmetrical types, respectively (Mandal & Natarajan 2015). Meanwhile, the weak peak at 2350
cm–1 can be attributed to CO2 molecules in the air (Gatelytė et al. 2011).
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AHMAD TAUFIQ et al.
Samples
2-theta(311) (°)
a = b = c (Å)
V(Å)3
Crystallite size (nm)
Rwp
Gof
Mw (g/mol)
Ionic distribution
Y1
35.70
8.370(4)
584.4(3)
8.6(3)
19.35
0.59
1852.4
2+ 3+
2–
[Fe3+
1 ]A [Fe1 Fe1 ]B O4
Y2
35.69
8.383(3)
589.1(3)
8.2(2)
19.56
0.61
1854.9
3+
2+ 3+
2–
[Zn2+
0.1 Fe0.9 ]A [Fe0.9 Fe1.1 ]B O4
Y3
35.60
8.389(4)
590.4(4)
7.9(2)
19.14
0.60
1857.5
3+
2+ 3+
2–
[Zn2+
0.2 Fe0.8 ]A [Fe0.8 Fe1.2 ]B O4
Y4
35.56
8.394(5)
591.4(7)
7.4(1)
19.79
0.62
1860.0
3+
2+ 3+
2–
[Zn2+
0.3 Fe0.7 ]A [Fe0.7 Fe1.3 ]B O4
Y5
35.58
8.391(5)
590.8(6)
6.8(2)
19.39
0.62
1928.6
3+
2+ 2+ 3+
2–
[Zn2+
0.3 Fe0.7 ]A [Zn0.1 Fe0.6 Fe1.3 ]B O4
HIERARCHICAL STRUCTURE AND MAGNETIC BEHAVIOR OF ZN-DOPED MAGNETITE AQUEOUS FERROFLUIDS
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Table I. XRD data analysis results of the Zn-doped magnetite nanoparticles.
AHMAD TAUFIQ et al.
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Figure 2. FTIR spectra of the
Zn-doped magnetite
nanoparticles.
The morphology and particle size distribution were further investigate based on the TEM results
for the Y1, Y3, and Y5 samples. Based on Figure 3a, it is found that the samples tend to form a spherical
shape. The particle size distribution of the samples was analyzed using a log-normal distribution,
and its results are presented in Figure 3b. Based on the analysis results, the average particle sizes
were 13.7(7), 11.5(5), and 14.3(7) nm for Y1, Y3, and Y4, respectively. The particle size correlated with the
nucleation mechanism and growth process during the synthesis process. In the early stage, the particle
formation was constructed by cationic-anionic interaction to form monomers. In the next step, several
monomers could grow fastly compare to other monomers depending on the balance-unbalance of
population nuclei in the system. Theoretically, the particle growth linearly depends on the nucleation
rate and density of nuclei (Kelton & Greer 2010).
The particle size distribution of the samples varied from approximately 3 to 30 nm showing the
polydispersity. The polydispersity index of Y1, Y3, and Y5 were 0.33(4) 0.39(5), and 0.40(6), respectively.
Based on the previous work, the polydispersity index value in the range of 0.08 to 0.70 indicated the
mid-range polydispersity character (Asmawati et al. 2014). Although the TEM results showed evidence
that the samples were successfully synthesized in nanometric size, the results could not be observed
in the real particle size and distribution as well as the form and structure of the Zn-doped magnetite
ferrofluids because the TEM experiment was conducted for the dried Zn-doped magnetite ferrofluids.
Therefore, a particular in-situ characterization was employed to investigate the real hierarchical
structure as well as from and structure factors of the ferrofluids using the synchrotron SAXS technique.
The SAXS profiles, as shown in Figure 4a are represented by intensity as a function of scattering
vector (q) as shown in Equation 3:
I(q) = C
Z ∞
0
P(q, R)S(q, R)R6 D(R)dR + Bkg
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(3)
AHMAD TAUFIQ et al.
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Figure 3. TEM images (a) and particle size distributions (b) of the dried Zn-doped magnetite ferrofluids.
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Figure 4. Synchrotron SAXS profiles of the Zn-doped magnetite ferrofluids (a); the black circles represent the
experimental data, and solid red lines represent the fitting model. (b) Schematic of the three-dimensional structure
of the Zn-doped magnetite ferrofluids.
where P(q, R) is the form factor, S(q, R) is the structure factor, D(R) is the particle size distribution, C
is the scale factor, R is the particle size, and Bkg is the background. Furthermore, the SAXS data were
analyzed employing a global fitting method using spherical form factor model, log-normal distribution,
and mass fractal structure factor as presented in respective Equations 4–6 (Yuliantika et al. 2020) as
follows:
P(q, R) = 9
sin(qR) – qR cos(qR) 2
(qR)3
ln 2 RR
N
0
√ exp
L(R) =
2σ 2
σR 2π
D
Z ∞
S(q, R) = 1 + D
R0 0
RD–3 h(R, ξ)
sin qR 2
R dR
qR
(4)
(5)
(6)
where L(R) represents the log-normal distribution function, ς represents the polydispersity index, Ro
represents the median radius of the particles, N represents the normalization factor, ξ represents
the correlation length, and D represents the fractal dimension (Taufiq et al. 2019). The fitting models
are represented by solid red lines, and the SAXS data are represented by black circles, as shown in
Figure 4a. Based on the figure, it is shown that the samples have two different slope characteristics in
two q regions. The low-q region 0.06–0.20 nm–1 represents the fractal aggregate scattering from the
structure factor, while the high-q region of 0.20–1.0 nm–1 represents monomer scattering from form
factor. The SAXS data analysis results are presented in Table II.
The fitting results listed in Table II reveal that the primary particles (μ) of the Zn-doped magnetite
ferrofluids constructed the secondary particles (R) in a fractal structure with a chain-like structure
(1.2 < D < 1.4) for samples Y1–Y4. However, the Y5 sample has a more compact structure with D = 1.9
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Table II. Results of SAXS data analysis of the Zn-doped magnetic ferrofluids.
Samples
Monomer
Mass fractal aggregates
μ (nm)
σ
R (nm)
ξ (nm)
D
Nagg
Y1
3.0
0.30
13.4
35.1
1.2
6
Y2
4.1
0.41
12.2
45.2
1.4
5
Y3
4.1
0.41
11.3
132.1
1.4
5
Y4
4.3
0.43
9.1
36.1
1.4
3
Y5
4.4
0.37
13.5
27.0
1.9
8
with a shorter correlation length. The fractal structure with a chain-like structure was constructed
by form factors of various sizes. The formation of fractal structure constructed by primary particles
is visualized in Figure 4b. Based on the SAXS data analysis, it can be inferred that the Zn-doped
magnetite ferrofluids build a hierarchical structure with the chain-like aggregation with the specific
characteristics depending on the Zn composition.
A comprehensive structural characterization was conducted to reveal the structural properties of
the samples. The XRD, TEM, FTIR, and SAXS results confirmed that high-quality Zn-doped magnetite
nanoparticles were successfully synthesized by the sonochemical route using natural sand as a
primary precursor. Furthermore, the proposed study can be used as a model system to fabricate a
nanomaterial for biomedical applications. Therefore, to understand the effects of the Zn contents on
the physical properties of the samples, basic physical properties, such as magnetic behaviors, were
studied further, as shown in Figure 5.
The magnetic properties of the Zn-doped magnetite ferrofluids were investigated by VSM through
magnetization curves, scanning the external magnetic field from –1 to 1 T, as shown in Figure 5. In
this work, the ferrofluids as colloidal suspension contained the Zn-doped magnetite nanoparticles
dispersed in a polar liquid. The magnetic particle concentration was maintained by approximately
14%. The magnetic particles were stabilized using TMAH as a surfactant to create electrostatic
repulsion on the surface. Theoretically, in the [Fe3+ ]A [Fe2+ Fe3+ ]B O4 magnetite system, the magnetic
moment is solely produced by Fe2+ ions at the octahedral site (B) because the exchange interaction
between [Fe3+ ]A and [Fe3+ ]B is antiferromagnetic; therefore, they cancel each other, which is knows
as super-exchange interaction. The Zn2+ ions entering the tetrahedral position (A) reduce the
magnetization. The reduced magnetic moment at the tetrahedral site reduces the super-exchange
interaction between A and B but increases it between B and B. The stronger the interaction between
B and B, the lower the magnetic response (Cullity & Graham 2008). In this work, the magnetization
data were fitted using the Langevin equation, as written in Equation 7. Nevertheless, because the
Zn-doped magnetite ferrofluids constructed a more complex structure, the aggregation should be
taken into account to investigate the magnetization. Therefore, the magnetization data deviated from
the Langevin theory originating from the presence of the aggregate in the ferrofluids. Theoretically, the
Langevin theory can be applied to investigate the magnetization of the very dilute ferrofluids because
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Figure 5. Magnetization curves of the samples (a) Y1, (b) Y2, (c) Y3, (d) Y4, and (e) Y5. The solid red lines represent the
Langevin equation, the solid blue lines represent the MGC equation, and the black circles represent the
experimental data.
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of the magnetic particles exhibit as a monodisperse system without aggregation. However, in general
cases, the ferrofluids construct aggregate with various shapes, as also shown in this work.
M = Ms coth
μH
kT
kT
–
μH
(7)
The M and Ms are the magnetization and saturation magnetization, μ is the magnetic moment, H is
the magnetic field, k is the Boltzmann constant, and T is the temperature.
The aggregation is created when the interaction energy between magnetic particles is stronger
than that of thermal energy. As a consequence, the Zn-doped magnetite ferrofluids produce a fractal
structure with a polydispersity system. The chain-like aggregation of the ferrofluids as a dissipative
structure is constructed before applying an external magnetic field. It means that when the ferrofluids
are applied by an external magnetic field, the aggregation consumes some magnetic field energy
(Lin et al. 2010). Therefore, the magnetization of the Zn-doped magnetite ferrofluids deviate from the
Langevin theory. Furthermore, the average chain length of the ferrofluids does not significantly change
when the external magnetic field increase, just arranges the chains to produce a better alignment
along the direction of the external magnetic field (Wang et al. 2002).
Several simulation methods have been developed to study the magnetization characteristics
of ferrofluids. A mean-field theory successfully describes the magnetization of the ferrofluids at a
weak applied magnetic field. Nevertheless, the theory starts to overestimate the magnetization of the
ferrofluids as the applied magnetic field increases. Therefore, a modified mean-field theory was also
developed to study the magnetization of ferrofluids at the medium to high applied field (Kuznetsov
2018). However, it was only appropriate to study the ferrofluids in a monodisperse system. Therefore,
in this work, we applied a model of gas-like compression (GMC) by considering the aggregation effect
on the magnetization of the ferrofluids. The modification of Langevin function by the GMC combined
with the susceptibility parameter is shown in Equations 8–10 (Li et al. 2007):
1 + ln φφH
+ χH
(8)
M = Mr + Ms coth α –
α
φH = (0.638 – φ) tanh γ (φα)2 + φ
α=
μ0 πMs d3m H
6kT
(9)
(10)
where Mr , Ms , χ, dm , k, and T represent the remanent magnetization, saturation magnetization,
susceptibility, magnetic particle size, Boltzmann constant, and temperature, respectively. Furthermore,
φH represents the aggregation volume fraction of the magnetic particles depends on the magnetic
field, φ represents the particle volume fraction, γ represents the degrees of interaction between
particles under the magnetic field, dm represents magnetic particle size, and μ0 represents the
permeability in a vacuum. Furthermore, the theoretical saturation magnetization of the Zn-doped
magnetite nanoparticles could be calculated using Equation 11 (Callister & Rethwisch 2010). The nB
is the magnetic moment per cell unit, a is the unit cell edge length or lattice parameter that can be
found in Table I, and μB is the magnitude of magneton Bohr.
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AHMAD TAUFIQ et al.
HIERARCHICAL STRUCTURE AND MAGNETIC BEHAVIOR OF ZN-DOPED MAGNETITE AQUEOUS FERROFLUIDS
n μ
Ms = B 3 B
(11)
a
Based on the data analysis results using Equations 8–10, the magnetic parameters are presented
in Table III. Theoretically, the increasing Zn composition, the magnetic moment, and saturation
magnetization of the Zn-doped magnetite tend to increase from Y1 to Y4 and decrease for Y5. Such
magnetic moment and saturation magnetization were calculated according to the ionic distribution
of the Zn-doped magnetite, as shown in Table I. However, the experimental data showed that the
saturation magnetization of the Zn-doped magnetite presented a different trend from the calculation.
It means that the saturation magnetization of the samples was contributed not only by the Zn
contribution but also by other parameters. Therefore, the form and structure factors, as well as the
aggregation, should be taken into account to more deeply investigate the saturation magnetization of
the samples.
Table III. Results of magnetization data analysis for the Zn-doped magnetite ferrofluids.
Samples
Magnetic moment calc. (μB )
Y1
Saturation magnetization (emu/g)
φH
H
χ
γ
0.99
0.45
2
1.59
0.98
0.22
6
1.03
1.23
0.30
0.30
15
13.89
2.60
2.89
0.97
0.49
1
12.87
0.36
0.54
0.99
0.23
7
Calc.
Langevin
MGC
32.0
9.80
5.44
5.71
Y2
36.8
11.06
1.45
Y3
41.6
12.45
Y4
46.4
Y5
43.2
When the magnetic moment per crystal unit of the Zn-doped magnetite increases, the magnetic
particle-particle interaction increases to form aggregation in the structure that is more compact. The
Brownian motion keeps the magnetic particles in the carrier liquid dispersed randomly in the absence
of an external magnetic field. This phenomenon is similar to gas molecules that spread in a container.
However, the magnetic particles aggregate in the presence of an external magnetic field because of
the magnetic particle-particle interaction. Therefore, the magnetic particles separate from the liquid
matrix, producing a phase transition that is concentrated with magnetic particles, separates from a
dilute phase, following the orientation of the particle magnetic moments along the direction of the
magnetic field. In this case, the particle aggregation can be regarded as the particles being placed
in an ”aggregate space”. Similar to compressed gas, the increasing magnetic field produces the more
compact aggregate, decreasing the ”aggregate space” (Li et al. 2007). The magnetic particles can be
viewed in the ”aggregate space”, where the magnetic moment motion in the space was constrained by
a matrix in the ferrofluids. Therefore, when the magnetization-demagnetization occurs, the magnetic
moment is not easily oriented following an applied external magnetic field because it was trapped in
the ”aggregate space”. In this case, the magnetic particles follow the behavior of gas-like compression
(Han et al. 2009). Based on the fitting results, it was shown that the saturation magnetization of
the Zn-doped magnetite ferrofluids deviates from the Langevin theory. This phenomenon occurred
because the Zn-doped magnetite ferrofluids have an aggregation structure. When the ferrofluids
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AHMAD TAUFIQ et al.
HIERARCHICAL STRUCTURE AND MAGNETIC BEHAVIOR OF ZN-DOPED MAGNETITE AQUEOUS FERROFLUIDS
aggregate with a shorter correlation length, the saturation magnetization would be optimum with
the smooth curve because the single domain magnetic behavior is more dominant. However, when
the ferrofluids have a longer correlation length, the saturation magnetization would deviate from the
Langevin theory and produce an unstable curve. Therefore, the GMC plays a better model than the
Langevin theory to fit the saturation magnetization of the Zn-doped magnetite ferrofluids.
Figure 6. Photographs of the
Zn-doped aqueous magnetite
ferrofluids (a) with and (b)
without an external magnetic
field.
The hierarchical structure of the Zn-doped magnetite ferrofluids obtained by SAXS data analysis
is strongly related to the magnetic compression parameter (γ). For γ ∼
= 0, the ferrofluids are not
compressed to form aggregation. Therefore, Equation 8 becomes the Langevin equation that suitable
to fit magnetization data for a monodisperse system (Li et al. 2007). However, for the higher γ value,
it represents the strong interaction particles or compact aggregation when the particles under an
external magnetic field. Therefore, it affects the decreasing susceptibility, unstable magnetization
curve, and decreasing saturation magnetization. The γ parameter is appropriate to investigate the
intrinsic magnetization of the Zn-doped magnetite ferrofluids because this parameter is different
from the magneto-dipole interaction following the thermodynamics crystal theory. In this work, the
GMC with the γ parameter was used to fit very well the magnetization curves, presenting that the
model was in line with the experimental data. It means that the magnetization of the ferrofluids was
contributed by the aggregation of the magnetic particles embedded in the matrix. Furthermore, the
Zn-doped magnetite ferrofluids display superparamagnetic characteristics, with the remanence and
coercive field being almost negligible. The prepared Zn-doped ferrofluids are shown in Figure 6. In the
figure, the left side 6a shows the ferrofluids without an external magnetic field while the right side
6b shows the ferrofluids under an external magnetic field. Visually, the prepared Zn-doped magnetite
ferrofluids display a good response to an external magnetic field.
Finally, the antibacterial activities were studied using a colony test with E. coli and B. subtilis
bacteria. Based on Figure 7, generally, the Zn-doped magnetite ferrofluids show powerful antibacterial
properties compared to the classical antibiotic, erythromycin, with gram-negative and positive
bacteria. The bacterial killing activities of the Zn-doped magnetite ferrofluids herein might be
related to mechanical damage caused by their unique surface properties, wherein, according to the
previous results, the magnetic nanoparticles could destroy the E. coli membrane due to the rough
An Acad Bras Cienc (2021) 93(4) e20200774 14 | 20
AHMAD TAUFIQ et al.
HIERARCHICAL STRUCTURE AND MAGNETIC BEHAVIOR OF ZN-DOPED MAGNETITE AQUEOUS FERROFLUIDS
Figure 7. Antibacterial activity of the Zn-doped aqueous magnetite ferrofluids on E. coli (left-hand side) and B.
subtilis (right-hand side) bacteria.
magnetic edges (Wang et al. 2007). Moreover, the membrane surface charge of the bacteria and
nanoparticle surface charge suggest the influence of cell membrane disruption in the pathogen.
It was hypothesized that Zn-doped magnetite nanoparticles interact with the bacterial membrane
and change the zeta potential. Consequently, this interaction will affect van der Waals bonding and
hydrophobic interactions on amines, carboxyl groups, and phosphates within the cell membrane to
induce cell death (Xie et al. 2011). Interestingly, it was proposed that the essential role of Zn-doped
magnetite ferrofluids are their bactericidal effect, which reduces bacterial growth but cannot induce
complete cell death. It is only hypothesized that the treatment with magnetic nanoparticles produces
reactive oxygen species, such as H2 O2 , OH, and O2– to increase bacterial death through oxidative
stress, bacterial membrane peroxidation, and consequent DNA damage in both gram-negative and
positive bacteria (Applerot et al. 2012, Stankic et al. 2016).
Excellent antibacterial activities were observed herein on E. coli growth rates. Treating bacteria
with the magnetite ferrofluids doped with Zn significantly reduced their populations. Bacterial growth
activity was decreased to a greater extent in gram-negative than that in gram-positive bacteria. One
suggests that the colloidal stability achieved by combining Zn and magnetite can result in hydroxyl
radical formation and exacerbate lipid and protein damage in the membrane to accelerate cell death.
A previous finding showed that a mixture of Zn and ferrite enhanced antibacterial efficiency with
E. coli with no toxic effects in mammalian cells (Ravichandran et al. 2015). The better performance
of the magnetite ferrofluids doped with Zn also suggested an association with their ionic behavior.
Physically, bacterial growth inhibition was correlated with anion–cation interactions of Zn-doped
magnetite ferrofluids toward bacterial cells. Zn-doped magnetite ferrofluids were synthesized within
a water-carrier medium to optimize the killing process. The presence of cations and H2 O resulted
in membrane shrinkage due to the binding activity of cations with bacterial membrane to induce
plasmolysis and cell damage (Afkhami & Renardy 2017). The improved cationic interaction and H2 O
accelerated peptide bond hydrolysis, in particular 50% of the peptidoglycan component of E. coli
and approximately 35% of that of B. subtilis, occurred in gram-positive bacteria (Vollmer & Seligman
An Acad Bras Cienc (2021) 93(4) e20200774 15 | 20
AHMAD TAUFIQ et al.
HIERARCHICAL STRUCTURE AND MAGNETIC BEHAVIOR OF ZN-DOPED MAGNETITE AQUEOUS FERROFLUIDS
2010). We hypothesized that this caused differing viabilities of these bacteria. The primary role of
Zn within Zn-doped magnetite ferrofluids may enhance cell death through binding to the functional
groups of proteins and enzymes, decreasing the cell proliferation rate, disrupting the cell wall, inducing
cytoplasmic damage, and thus causing bacterial cell apoptosis (Vedernikova 2015).
Figure 8. Improvement of
antibacterial activity of the
Zn-doped aqueous magnetite
ferrofluids by the presence of
the negatively charged surface.
The only credible, though complex, the relationship between the properties of Zn-doped
aqueous magnetite ferrofluids and their antibacterial activity was found when we considered the
bacteria–surface interactions by the presence of negatively charged surface of Zn-doped magnetite.
Prior studies have shown that Zn2+ was incorporated in the structure of magnetite to form the
negatively charged surface of Zn-doped magnetite as demonstrated by an increased lattice constant
of the Zn-doped magnetite nanoparticles originated from an increased Zn content. All of the results
of the characterization obtained by FTIR, VSM, and synchrotron-based SAXS seems consistent with the
possibility of the incorporation of Zn2+ in magnetite. A schematic illustration of the improvement of
antibacterial activity of the Zn-doped aqueous magnetite ferrofluids by the presence of a negatively
charged surface is shown in Figure 8. In summary, two properties make Zn-doped magnetite an
excellent antibacterial agent. The first property is the presence of the negatively charged surface.
Secondly, the Zn-doped magnetite nanoparticles with the size are below 20 nm. Therefore, Zn-doped
magnetite ferrofluids prepared from natural sand are a new promising candidate material for use as
an antibacterial agent for medical treatment in daily life applications.
CONCLUSIONS
High-quality Zn-doped magnetite ferrofluids have been successfully synthesized through a
sonochemical route utilizing natural sand as the primary precursor. The Zn-doped magnetite
nanoparticles crystallized in a spinel cubic structure. Generally, an increased lattice constant of the
Zn-doped magnetite nanoparticles originated from an increased Zn content. The Zn-doped magnetite
ferrofluids constructed secondary particles in aggregation with a fractal dimension D < 2. The magnetic
An Acad Bras Cienc (2021) 93(4) e20200774 16 | 20
AHMAD TAUFIQ et al.
HIERARCHICAL STRUCTURE AND MAGNETIC BEHAVIOR OF ZN-DOPED MAGNETITE AQUEOUS FERROFLUIDS
particles formed a chain-like structure with different correlation lengths. Under an external magnetic
field, the magnetic particles in the ferrofluids placed aggregate space; therefore, the magnetization
data would deviate from the Langevin equation. The magnetization mechanism of the Zn-doped
magnetite ferrofluids was in line with the GMC with the susceptibility parameter. The aggregation
structure played an essential role in the magnetization of the ferrofluids. Since the antibacterial
activity of the Zn-doped magnetite ferrofluids exhibited excellent performance as an antibacterial
agent for E. coli and B. subtilis, one considers that the presence of the negatively charged surface
and the nanoparticle size may contribute to the high antibacterial activity of Zn-doped magnetite
ferrofluids. Therefore, the Zn-doped magnetite ferrofluids can be used as a new alternative material
for application in medical treatments.
Acknowledgments
This work was supported
074/SP2H/LT/DRPM/2019).
by
the
KEMENRISTEDIKTI
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How to cite
and H.N.; project administration, D.Y., N.H. and S.S.; funding
TAUFIQ A, YULIANTIKA D, SUNARYONO S, SAPUTRO RE, HIDAYAT N, MUFTI N,
acquisition, A.T. and D.Y. All authors have given their approval
to the final version of the manuscript.
SUSANTO H, SOONTARANON S & NUR H. 2021. Hierarchical Structure and
Magnetic Behavior of Zn-Doped Magnetite Aqueous Ferrofluids Prepared
from Natural Sand for Antibacterial Agents. An Acad Bras Cienc 93:
e20200774. DOI 10.1590/0001-3765202120200774.
Manuscript received on May 22, 2020;
accepted for publication on December 7, 2020
AHMAD TAUFIQ1
https://orcid.org/0000-0002-0155-6495
DEFI YULIANTIKA1
https://orcid.org/0000-0002-3436-1651
SUNARYONO SUNARYONO1
https://orcid.org/0000-0001-5033-3549
ROSY E. SAPUTRO1
https://orcid.org/0000-0001-6523-8181
NURUL HIDAYAT1
https://orcid.org/0000-0001-9232-7454
NANDANG MUFTI1
https://orcid.org/0000-0002-8260-8495
HENDRA SUSANTO2
https://orcid.org/0000-0002-3935-4848
SIRIWAT SOONTARANON3
https://orcid.org/0000-0001-9770-495X
HADI NUR4
https://orcid.org/0000-0002-4387-431X
1 Universitas
Negeri Malang, Faculty of Mathematics and Natural
Sciences,Department of Physics, Jl. Semarang, No. 5, Malang
65145, Indonesia
2 Universitas Negeri Malan, Faculty of Mathematics and Natural
Sciences, Department of Biology, Jl. Semarang, No. 5, Malang
65145, Indonesia
3 Synchrotron Light Research Institute, Nakhon Ratchasima, 111
University Avenue, Muang District, Nakhon Ratchasima 30000,
Thailand
4 Universiti Teknologi Malaysia, Ibnu Sina Institute for Scientific
and Industrial Research, Centre for Sustainable Nanomaterials,
81310 Johor Bahru, Johor, Malaysia
Correspondence to: Ahmad Taufiq
E-mail: ahmad.taufiq.fmipa@um.ac.id
Author contributions
The manuscript was written through the contribution of all
authors, specifically: conceptualization, A.T., H.N., N.M., and S.S.;
methodology, A.T., H.S., N.M., and H.N.; investigation, D.Y., R.E.S,
N.H., and H.S.; resources, D.Y., S.S. and N.H.; supervision, A.T.
An Acad Bras Cienc (2021) 93(4) e20200774 20 | 20