Environmental Science and Pollution Research

https://doi.org/10.1007/s11356-024-35734-0

RESEARCH ARTICLE

Adsorptive performance of bismuth‑doped Ni‑Zn‑Co ferrite

nanoparticles for the removal of methylene blue dye
Dema Dasuki1 · Amani Aridi2 · Marwa Elkady3,4 · Khulud Habanjar1 · Gehan M. El‑Subruiti5 · Ramadan Awad6,7

Received: 25 September 2024 / Accepted: 3 December 2024

© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024

Abstract
Cancer, kidney and liver damage, and even death result from water contaminated with textile dyes. This study highlighted
a key approach for treating water contaminated with methylene blue (MB) dye. Bismuth-doped ferrite nanoparticles
­(Ni0.33Zn0.33Co0.33−xBixFe2O4) with 0 ≤  ×  ≤ 0.2 were synthesized using a chemical co-precipitation technique. For the struc-
tural analysis, X-ray diffraction (XRD) confirmed the successful formation of ferrite nanoparticles with a hematite phase of
21.02% for x = 0.2. The crystallite size decreased from 30.12 to 13.65 nm, as x increased from 0 to 0.2. Also, a decrease in
the grain size from 24.57 to 12.37 nm was verified via transmission electron microscope (TEM) analysis. Furthermore, the
X-ray photoelectron spectroscopy (XPS) confirmed the optimal stoichiometric proportions of the synthesized nanoparticles
through the elemental composition analyzed. Additionally, XPS analysis revealed that the un-doped sample has gained the
highest number of defects along with the photoluminescence spectra (PL) discussion. The optical analysis was investigated
by photoluminescence spectra (PL) through several excitation wavelengths. The detected PL peaks in the near-band energy
and the defect-level emission region confirmed the recombination rate and the presence of defects, respectively. Doping fer-
rite nanoparticles with bismuth increased the specific surface area from 43.82 to 71.83 ­m2·g−1 and altered pore volume and
diameter. For further investigation, the adsorption performance of ferrite nanoparticles was tested using MB as a pollutant.
Un-doped nanoparticles demonstrated significant adsorption activity, removing 97.1% of MB after a contact time of 120
min. Furthermore, un-doped nanoparticles exhibited improved adsorption activity in a basic medium, while Bi-doped nano-
particles showed enhanced performance in an acidic medium. This result was due to Bi-doping altering the surface charge,
as confirmed by zeta potential analysis. Among the applied non-linear isotherms, the Freundlich model best described the
adsorption of MB onto the ­Ni0.33Zn0.33Co0.33−xBixFe2O4 nanoparticles. Increasing the temperature boosted the adsorption
of MB onto the prepared nanoparticles.

Keywords Bismuth-doped · Ferrite nanoparticles · Methylene blue · Wastewater treatment

Responsible Editor: Tito Roberto Cadaval Jr

4
* Amani Aridi Chemical and Petrochemical Engineering Department,
aridiamani@gmail.com Egypt-Japan University of Science and Technology
(E-JUST), New Borg El‑Arab City, Alexandria, Egypt
1
Physics Department, Faculty of Science, Beirut Arab 5
Chemistry Department, Faculty of Science, Alexandria
University, Beirut, Lebanon
University, Alexandria, Egypt
2
Public Health Department, Faculty of Health Sciences, 6
Physics Department, Faculty of Science, Alexandria
Modern University of Business and Science, Beirut, Lebanon
University, Alexandria, Egypt
3
Fabrication Technology Research Department, Advanced 7
Department of Basic Sciences, Faculty of Computer Science
Technology and New Materials Research Institute
and Artificial Intelligence, Pharos University in Alexandria,
(ATNMRI), City of Scientific Research and Technological
Alexandria, Egypt
Applications (SRTA-City), New Borg El‑Arab City,
Alexandria 21934, Egypt

Vol.:(0123456789)
 Environmental Science and Pollution Research

Introduction inverse spinel ferrite, where N ­ i2+ ions occupy the A-site,
3+
and half of F ­ e ions migrate the B-site (Al-Senani et al.
Industrial disposal of unfiltered water has become a major 2022). Yet, C ­ o 2+ ions occupy the A-site, whereas F ­ e 3+
water pollution source, especially the textile dyes (Khalil ions incorporate in both the A-site and B-site (Hadouch
et al. 2020; Salama et al. 2022). A previous study has et al. 2022). Thus, the magnetic properties of inverse spi-
stated that 20% of used textile dyes are eliminated roughly nel ferrites enable their employment in magnetic applica-
in water (Rauf and Ashraf 2009). Accordingly, dyes can tions (Guragain et al. 2020). As reported, methylene blue
contaminate and stick in water and soil for an extended removal percentage reached around 99% for spinel ferrite
period (Elkady et al. 2019; Al-Tohamy et al. 2022). Most ­CdFe2O4 nanoparticles (Vodă et al. 2016). Moreover, Ru-
contaminations with water may cause a reduction in soil doped nanoferrites, (­ Cd0.4Ni0.4Mn0.2)Fe2−xRuxO4, showed
photosynthesis, a toxic aquatic environment, and serious a significant adsorption performance for the removal of
harm to human life (Yang et al. 2023a, b; Zhang et al. Congo red (Kassem et al. 2024).
2024; Li et al. 2024). This includes methylene blue, mala- The affordable and safe synthesis, high surface area,
chite green, Congo red, rhodamine B, methylene green, low dielectric and magnetic losses with high electrical
and methylene orange (Sudarshan et al. 2023). The cati- resistivity are recognized as bismuth element particular
onic dye that is mostly used for silk, cotton, and wood properties (Suresh and Vijaya 2016; Shahbazi et al. 2020).
dyeing, is known as methylene blue (MB) (Birniwa et al. Consequently, such characteristics promoted the structural,
2022). The ingesting of water contaminated with MB optical, and magnetic properties of nanoferrites when sub-
can cause serious side effects on humans such as nausea, stituted with bismuth ions (Sivasubramanian et al. 2022).
vomiting, jaundice, increased heart rate, profuse sweating, Thus, bismuth-doped spinel ferrite nanoparticles promote
and mental confusion. To tackle this, ongoing research is their applications in data storage and magnetic sensors, bio-
conducted to investigate the effectiveness of several water medical devices, and environmental applications (Gomez
treatment techniques. Currently, chemical, biological, and et al. 2021; Kharbanda et al. 2023). As stated previously,
physical techniques are recognized such as the oxidation the spinel structure of cobalt ferrite may not be alerted by
process, enzyme degradation, and adsorption (Saleh et al. a small concentration of bismuth ion substitution (Routray
2020). Rashid et al. (Rashid et al. 2021) reported the sig- and Behera 2017).
nificant efficiency of adsorption as being a simple, afford- In this work, spinel nanoferrites were synthesized having
able, eco-friendly, and sustainable method among several an equimolar percentage of nickel, zinc, and cobalt ions,
chemical and biological water treatment techniques. and doped with bismuth ions. Afterward, the synthesized
The ferrite nanoparticle properties, such as the high ­Ni0.33Zn0.33Co0.33-xBixFe2O4 nanoparticles were analyzed
chemical stability, magnetic, and magneto-optical prop- structurally, morphologically, and optically to gather the par-
erties, permit their usage as an adsorbent for water waste ticle’s purity and properties. Finally, a potential adsorption
treatment (Wang et al. 2012). Furthermore, ferrite nano- investigation was assessed through various operation factors
particles are stable and reusable, retaining performance (the initial concentration, pH, and contact time) over meth-
over four cycles, making them ideal for pollutant adsorp- ylene blue dye. For the wrap-up, three different isotherms
tion (Kassem et al. 2024; Farhat et al. 2024a). Aridi were applied to obtain the isotherm that perfectly describes
et al. (Aridi et al. 2023) reported a significant removal the adsorption activity (non-linear Langmuir, Freundlich,
percentage with 89% of malachite green dye after 120 and Temkin isotherms).
min of contact time and 20 mg of (1-x)Ni0.5Zn0.5Fe2O4/
(x)Zn 0.95Co 0.05O ferrite nanocomposites. Accordingly,
the spinel ferrites are known as a compound (­ AB2O4) of
divalent metal ions occupying tetrahedral sites (A) and Experimental techniques
trivalent metal ions located in octahedral sites (B) (Di
Quarto et al. 2024). The divalent and trivalent metal ions Materials
are known as magnesium, niobium, calcium, manganese,
zinc, cobalt, nickel, and bismuth (Suresh and Vijaya 2016; High purity (98–100%) starting materials were utilized
Banerjee et al. 2019). Normal spinel ferrite admitted an for ­N i 0.33 Zn 0.33 Co 0.33-x Bi x Fe 2 O 4 nanoparticle synthe-
enhancement in electrical properties when employed in sis. Nickel(II) chloride hexahydrate (­ NiCl2·6H2O), zinc
catalytic application (Anjaneyulu et al. 2024). In Z
­ nFe2O4, chloride ­(ZnCl2), iron(III) chloride hexahydrate ­(FeCl3.·),
which is established as normal spinel ferrites, zinc ions and bismuth(III) chloride ­( BiCl 3) were purchased from
­(Zn2+) occupy only A-site (Somvanshi et al. 2020). How- Sigma-Aldrich, while cobalt(II) chloride hexahydrate
ever, nickel ­NiFe2O4 and ­CoFe2O4 are mostly known as ­( CoCl 2·6H 2O) was purchased from acros organics. The
Environmental Science and Pollution Research

precipitate agent sodium chloride (NaCl) was purchased Synthesis method

from Sigma-Aldrich as well.
Ni0.33Zn0.33Co0.33-xBixFe2O4 nanoparticles, for x = 0, 0.05, 0.1,
0.15, and 0.2, are synthesized by the chemical co-precipitation
technique, as seen in Fig. 1. Stoichiometric proportions of

Fig. 1  Scheme diagram for the

absorbent preparation technique
 Environmental Science and Pollution Research

starting materials, mainly ­NiCl2·6H2O, ­ZnCl2, ­FeCl3·6H2O,

­ oCl2·6H2O, and ­BiCl3, were dissolved individually in deion-
C
ized water. Upon mixing the starting solutions, one molar
aqueous solution was formed. After 30 min of continuous stir-
ring, three molar of sodium hydroxide was added dropwise
to the solution to reach a pH of 12. Afterwards, the solutions
were heated at 80 °C for 2 h under continuous stirring. Next,
the solution was filtered and washed with deionized water to
get a neutral pH. Then, the precipitate was dried at 100 °C
for 18 h followed by grinding to get fine powder. Finally, the
powder was calcined at 550 °C for 4 h. Eventually, gray color
nanoparticles were successfully formed.

Adsorption experiments

The synthesized nanoparticles were utilized as absorbents for

the methylene blue removal experiment. To do so, 0.05 g of
each absorbent was mixed in a 250-mL beaker using the batch
technique. Afterward, the absorbance reaction was initiated
through various operations, such as the initial concentration,
pH, and contact time. The initial concentration was assessed
from 5 to 100 mg/L, and the pH levels varied from 1 to 11
using 0.1 N HCl for acidic solution ranges or 0.1 N NaOH for
alkaline media, whereas the contact time increased from 30
to 120 min. Moreover, a UV mini 1240 V spectrophotometer
from Shimadzu was used to record the photometry measure-
ments for all examined samples. The findings were utilized Fig. 2  XRD pattern of ­
Ni0.33Zn0.33Co0.33-xBixFe2O4 nanoparticles
to determine the adsorption capacity and the adsorption effi- (0 ≤ x ≤ 0.2)
ciency of prepared samples using:
Ci − Cf
Removal % = × 100 (1) Results and discussion
Ci

Ci and Cf represent the initial dye solution concentra- Structural, morphological, and optical properties
tion and solution concentration after the adsorption process,
respectively. The adsorbent quantity of MB was calculated at Figure 2 illustrates the XRD diffraction patterns of
equilibrium (qe) and at a certain period (qt) using the following ­Ni0.33Zn0.33Co0.33-xBixFe2O4 nanoparticles (x = 0, 0.05, 0.1,
equations (Rabaa et al. 2023): 0.15, and 0.2). The formation of the main ferrite phase is
confirmed in compliance with JCPDS No. 86–2267 (Thomas
Ci − Ce et al. 2023). Eleven main sharp peaks depict the (111), (220),
qe = ×V (2)
m (311), (222), (400), (422), (511), (440), (531), (620), and
(533) of the ferrite phase. Two minor peaks around 33.43°
Ci − Ct and 49.67° reflect the presence of α-Fe2O3 as an impurity
qt = × V. (3) phase, according to JCPDS No. 96–591-0083 (Siddhartha
m
Sairam et al. 2023).
Ce and Ct are the concentrations at equilibrium and at a Rietveld refinement was conducted by the Materials
time, while V and m are the volume of the solution and the Analysis Using Diffraction (MAUD) program for the phase
mass of the adsorbents, respectively. composition weight percentage and the crystallite size of the
prepared nanoparticles. The exactness of the fit is confirmed
by the refinement indices, such as goodness of fit (χ2), as
seen in Fig. 2 (Matar et al. 2023). All samples confirm the
dominancy of the ferrite phase over the α-Fe2O3 impurity
phase, as demonstrated in Fig. 3 (a). The phase composition
of the un-doped sample was determined with 96.96% for the
Environmental Science and Pollution Research

Fig. 3  a Changes in the percentage of ferrite and hematite phases as a function of x and b variation of the crystallite size (DS and DM), lattice
parameter (a), and X-ray density (ρx) with x for N
­ i0.33Zn0.33Co0.33-xBixFe2O4 nanoparticles (0 ≤ x ≤ 0.2)

ferrite phase and 3.03% for the α-Fe2O3 impurity phase. The crystallite size determined by using the Debye–Scherrer
hematite phase may be formed due to the loss of divalent equation (DS) (Badreddine et al. 2018):
cations during the sintering process (Verma et al. 2019). As
0.9𝜆
bismuth was doped up to 0.15, the α-Fe2O3 presence was DS = (4)
𝛽cos𝜃
narrowly detected (< 4%). However, the highest impurity
percentage reached 21.02% for x = 0.2. Accordingly, Suresh where, λ, β, and 2θ correspond to the wavelength of Cu-Kα
and Vijaya (2016) reported a similar increasing behavior radiation, the diffraction half-width at half maximum, and
of hematite with bismuth substitution in Z ­ nFe2-xBixO4 Bragg’s angle, respectively. DS illustrates a decrease from
nanoparticles. 13.72 to 6.11 nm with the increase of bismuth substitution
Furthermore, sample imperfections, such as dislocations, from 0 to 0.2, as depicted in Fig. 3 (b). This confirms the
vacancies, impurities, and interstitials, directly change the similar decreasing trend of crystallite size (DS and DM) with
XRD peak position, broadening, or intensity (Waje et al. the increase of bismuth substitution.
2010). The XRD peak intensities detected an increase as Particularly, the MAUD program computes the crystallite
x increased from 0.00 to 0.1, followed by a decrease as x size DM by collecting the average values of the full width
increased to 0.2. This increase in the intensity indicates a at half maximum (FWHM) of the XRD peaks. Hence, the
higher level of crystallinity, which may be attributed to the intensity variation of XRD peaks directly affects the values
enhancement of the structural ordering when bismuth ions of DM. Therefore, DM demonstrates higher values than the
were doped in ferrites (Nadeem et al. 2015). Inversely, the crystallite size obtained by the Debye Scherrer formula DS.
decrease in the intensity implies lower crystallinity, due to Moreover, the internal structure and characteristics of the
the variation in the chemical composition, thus the high for- prepared nanoparticles were obtained by calculating the
mation of hematite phase (α-Fe2O3) in this sample (Ramesh lattice parameter and X-ray density. Apparently, the varia-
et al. 2016). It is worth mentioning, that the crystallite size tion of lattice parameters in addition to the rise of molecular
was calculated in two distinct methods, by the MAUD pro- mass varies the values of X-ray density (Taneja et al. 2021).
gram (DM) and secondly by using the Debye–Scherrer equa- It is worth noting that the lattice parameter (a) and X-ray
tion (DS). Both methods confirm the decrease of crystallite density (ρx) were obtained using the following equations (Al
size along with the increase of bismuth doping x despite the Boukhari et al. 2020):
variation of the XRD pattern intensity.
The crystallite size (DM), determined by the MAUD pro-
√
a = dhkl h2 + k2 + l2 (5)
gram, decreased from 30.12 to 13.65 nm, as bismuth dop-
ing x increased from 0 to 0.2, respectively. This decrease is 8M
directly related to Bi substitution due to the large difference 𝜌x =
a3 × NA (6)
in ionic radii between the doping ion (1.17 Å) and the dopant
ion (0.65 Å) (Dos Santos et al. 2013). Moreover, the shift in where, dhkl, M, and NA are the interplanar distance, the
the main plane (311), detected around 2θ = 26° in the XRD molecular mass, and Avogadro’s number, respectively
diffraction pattern, may have resulted in the decrease of the (Channa et al. 2020; Verma et al. 2021). The values of the
 Environmental Science and Pollution Research

lattice parameter varies as x increases, due to the replace- Such analysis affirms the ideal stoichiometric proportions
ment of ­(Co2+) by large ionic radius (­ Bi3+) ions (Sathisha with the experimental proportions.
et al. 2020). In consequence, minor variation was detected Figure 5 demonstrates the high-resolution spectrum of the
for X-ray density between 4.79 and 5.31 g/cm3 with bismuth core energy level O 1s centered at 530.88 eV. The fitting of O
doping. Hence, the molecular weight (M) significantly rises 1s was deconvoluted into two Gaussian peaks at 529.8 ± 0.2
with the increase of B­ i3+ ions in the nanoparticles, due to its eV and 531.5 ± 0.1 eV. The main peak at 529.8 ± 0.2 eV
large atomic weight (208.98 g/mol) (Kumar 2020). refers to the oxygen lattice ­(OL) in metal-oxide (Bahnasawy
Furthermore, the X-ray photoelectron spectroscopy et al. 2022). The smaller and broader peak at 531.7 ± 0.2
(XPS) was analyzed to obtain the chemical oxidation state eV was attributed to the defects of oxygen vacancies (­ Ov)
and elemental composition for all the prepared samples. Fig- (Farhat et al. 2024b). It is worth mentioning that the un-
ure 4 exhibits the presence of the main photoemission peaks doped sample denotes the maximum area across all sam-
Zn-2p, Ni-2p, Co-2p, Fe-2p, Fe-2s, and O-1s of the primary ples, as seen in Table 2, resulting in the highest number of
orbitals for all prepared samples (Ortiz-Quiñonez et al. 2018; defects. Noteworthy, no major shift was detected in the bind-
Yousaf et al. 2020). Moreover, the Bi-4f photoemission peak ing energy (B. E.) of the XPS results as bismuth was doped
was labeled for doped samples, confirming the successful in ­Ni0.33Zn0.33Co0.33-xBixFe2O4 nanoparticles.
presence of Bi ions in all doped samples. Besides, the atomic Figure 6 presents the TEM micrographs in addi-
percentages listed in Table 1, authenticate the formation of tion to the grain size distribution histogram for
high-purity samples, without any detected impurities. As ­Ni0.33Zn0.33Co0.33-xBixFe2O4 nanoparticles. TEM micrograph
listed, cobalt atomic percentage (at.%) decreased from 4.12 of the un-doped sample, Fig. 6 a, shows well distribution
to 1.39% with the increase of x from 0 to 0.2. Inversely, bis- of spherical particles with a mean particle size of around
muth at.% increased from 0 to 2.76% as x rose from 0 to 0.2. 25 nm. More particles are agglomerated with bismuth sub-
stitution in the nano-ferrites. The most clustered nanopar-
ticles are detected in the highest doping sample (x = 0.2).
The agglomeration may be attributed to the large presence
of α-Fe2O3 phase (21.02%) in the highest doping concentra-
tion sample (x = 0.2), as depicted in XRD analysis (Kumar
et al. 2021). For the grain size analysis, a histogram was
developed with the support of ImageJ software. The mean
grain sizes established are 24.57 nm, 23.12 nm, 17.03 nm,
12.44 nm, and 12.37 nm for x = 0, 0.05, 0.1, 0.15, and 0.2,
respectively. Obviously, the grain size decreases with bis-
muth doping. Despite the similar decreasing trend of grain
size with the crystallite size determined in the XRD, higher
values of grain particles are detected compared to DS, as
depicted in Fig. 7. The bigger grain particle size may be
attributed to the observed agglomeration detected in the
TEM micrographs. As reported by Rhaman et al. (Rhaman
et al. 2019), the reduction of crystallite and grain size may
result from the ionic radius difference, which inhibits the
crystallite nucleation, or due to the larger surface-to-volume
area that aggregates some particles.
The optical properties of ­Ni0.33Zn0.33Co0.33-xBixFe2O4
nanoparticles are characterized by photoluminescence spec-
Fig. 4  XPS total survey spectra for ­Ni0.33Zn0.33Co0.33-xBixFe2O4 nano- tra (PL) through four excitation wavelengths λex 310, 330,
particles, for x = 0, 0.1, and 0.2 350, and 370 nm, as shown in Fig. 8 (a–d). The emission

Table 1  Elemental composition x Atomic percentage (%)

of ­Ni0.33Zn0.33Co0.33-xBixFe2O4
nanoparticles, for x = 0, 0.1, O Fe Co Ni Zn Bi
and 0.2
0.00 62.48 26.50 4.12 3.51 3.39 0.00
0.10 68.92 21.45 2.01 3.31 3.03 1.27
0.20 66.73 22.66 1.39 3.37 3.09 2.76
Environmental Science and Pollution Research

­ i0.33Zn0.33Co0.33-xBixFe2O4 nanoparticles for all samples a x = 0, b x = 0.1, and c x = 0.2

Fig. 5  HR-XPS of core energy level O 1s of N

Table 2  The peak position and binding energy for ­OL and Ov peaks Then the intensity increased till it reached the maximum
for each of ­Ni0.33Zn0.33Co0.33-xBixFe2O4 nanoparticles, for x = 0, 0.1, value of 1406 a.u. for x = 0.15. Finally, the emission peak
and 0.2
intensity decreases to 983 a.u. for the highest doping value
x OL Ov x = 0.2. A similar variation of NBE emission peak intensity
B. E. (eV) Area B. E. (eV) Area was detected for all the samples examined at λex = 310, 330,
and 350 nm. It is important to mention that the peaks in
0 529.79 18,459.15 531.7 3157.59 the NBE region, located in the UV region, arise from the
0.1 529.81 10,529.88 531.42 1428.76 electron–hole pairs recombination (Ambala et al. 2023).
0.2 529.72 20,654.55 531.68 1766.61 Hence, the highest recombination rate was detected for the
sample with the highest intensity peak, x = 0.15, through
all samples. As previously reported, the inconstancy of
peaks were detected in the near-band energy (NBE) region charge carrier recombination may be caused by the inclu-
and defect-level-emission (DLE) region. For λex = 310 nm, sion of bismuth in the ferrite structure (Sharmin and Basith
the main emission peaks were detected in the NBE region 2022). Moreover, the emission peaks detected in the defect-
around 340 nm. The emission peak intensity fluctuates with level-emission (DLE) region fall under the visible light
bismuth substitution. First, the emission intensity increased region. All samples illustrate a violet region emission peak
from 684 to 780 a.u. as bismuth doping increased from between 415 and 426 nm, Fig. 8 (a–d). The violet emission
0 to 0.05. Followed by a decrease to 581 a.u. for x = 0.1. peaks refer to the oxygen vacancies (Pandey et al. 2017).
 Environmental Science and Pollution Research

­ i0.33Zn0.33Co0.33-xBixFe2O4 nanoparticles for all samples (a, b) x = 0, (c, d) x = 0.05,

Fig. 6  TEM images and particle distribution histogram of N
(e, f) x = 0.1, (g, h) x = 0.15, and (i, j) x = 0.2

As reported previously, oxygen defects that may originate

from the photon holes may be attributed to the doping ratio
and the synthesis conditions of the prepared nanoparticles
(Senturk et al. 2023). The un-doped sample displayed higher
peak intensity in the violet region for all examined excita-
tion wavelengths. Hence, the un-doped sample interprets the
higher defects and oxygen vacancies over the prepared sam-
ples, as discussed in the XPS analysis section. This implies
that the doping of bismuth decreased the oxygen vacancies
in the prepared nanoparticles. Besides, a similar pattern was
detected for the visible region for all samples. As seen, no
other peaks were detected in the visible region other than
violet. This results in the lack of surface — defects, impuri-
ties, and aggregation of nanoparticles (Pandey et al. 2017).
Nevertheless, the emission peak intensity was clearly
affected by the variation of excitation energy. As illustrated
in Fig. 9, the increase of excitation energy decreases the
Fig. 7  Variation of DS, DM, and DTEM with x for intensity of the emission peak 7. Similar behavior is exhib-
­Ni0.33Zn0.33Co0.33-xBixFe2O4 nanoparticles (0 ≤ x ≤ 0.2) ited by all samples, except for the un-doped sample where
the intensity slightly increases at the highest excitation
wavelength λex = 370 nm. Farhat et al. (Farhat et al. 2024a)
reported a similar decreasing trend in the emission intensity
Environmental Science and Pollution Research

Fig. 8  PL spectra of ­Ni0.33Zn0.33Co0.33-xBixFe2O4 nanoparticles (0 ≤ x ≤ 0.2) under various excitation wavelength a λex = 310 nm, b λex = 330 nm,
c λex = 350 nm, and d λex = 370 nm

with the increase of excitation wavelength, resulting from

the reduction of photons emitted from the lower quantity
of excited electrons. It is worth mentioning that the varia-
tion of emission peaks is induced by the variation of excita-
tion wavelengths and the doping of bismuth. The change in
emission peak position and intensity may effectively impact
the optical properties of water treatment applications. The
PL spectra analysis provides valuable insights, such as the
recombination rate and defect rate of the prepared nanopar-
ticles, in addition to, the variation of emission peaks and
intensity that were controlled by the variation of excitation
wavelength and doping content.
Furthermore, the Commission Internation-
ale de L’Eclairage (CIE) coordinates of pure
­Ni0.33Zn0.33Co0.33Fe2O4 sample are given by the chroma-
ticity diagram, as shown in Fig. 10 for different excitation
wavelengths. It has been noted that the coordinates corre-
sponding to all wavelengths are situated in the deep blue
light emission region. As verified by the diagram, the gener-
ated ­Ni0.33Zn0.33Co0.33Fe2O4 ferrite nanocrystals can func-
Fig. 9  The effect of bismuth doping content and excitation energy on
the PL emission peak intensity of N­ i0.33Zn0.33Co0.33-xBixFe2O4 nano- tion as a deep blue LED and be used for appropriate display
particles applications. According to Nadumane et al. (Nadumane
 Environmental Science and Pollution Research

Table 3  Values of SBET, pore volume, and pore diameter of

­Ni0.33Zn0.33Co0.33-xBixFe2O4 nanoparticles where x = 0, 0.1 and 0.2
x SBET ­(m2·g−1) Pore volume Pore
­(cm3·g−1) diameter
(nm)

0 43.82 0.25 18.64

0.1 65.53 0.21 12.71
0.2 71.83 0.36 18.38

exhibit a type IV isotherm and an H2 hysteresis loop type

according to the IUPAC classification (Kassem et al. 2024).
The corresponding SBET, pore volume, and pore diameter
values are summarized in Table 3. As x increases from 0 to
0.2, the surface area increases from 43.82 to 71.83 m­ 2·g−1,
respectively. However, an inconsistent trend is observed for
the variation of the pore diameter and volume. Therefore,
Fig. 10  CIE diagram of the ­Ni0.33Zn0.33Co0.33Fe2O4 nanoparticles
doping ­Ni0.33Zn0.33Co0.33Fe2O4 with Bi influences the tex-
tural properties of the prepared nanoparticles. As shown in
et al. 2019), magnesium-doped nickel ferrite nanoparticles Fig. 11 (b) and Table 3, the pore diameter ranges between
exhibited white region emission and can be used in cool 12.71 and 18.64 nm, indicating the mesoporous structure of
white LED applications. Additionally, according to Naik the prepared nanoparticles.
et al. (Madhukara Naik et al. 2019), the CIE coordinates
for Zn–CoFe2O4 and C ­ oFe2O4 nanoparticles are situated in Adsorption performance
the bluish light and green light emission regions of the CIE of ­Ni0.33Zn0.33Co0.33‑xBixFe2O4 nanoparticles
diagram, respectively.
The textural properties of ­Ni0.33Zn0.33Co0.33-xBixFe2O4 Effect of contact time
nanoparticles where x = 0, 0.1, and 0.2 were evaluated using
­N2 adsorption-desorption measurements. Surface area (SBET) The adsorption performance of
was analyzed through Brunauer–Emmett–Teller analysis. In ­Ni 0.33Zn 0.33Co 0.33-xBi xFe 2O 4 nanoparticles, where x = 0,
addition, the pore volume and pore diameter were deter- 0.05, 0.1, 0.15, and 0.2, was evaluated in the removal of
mined using the Barrett–Joyner–Halenda model. The N ­ 2 methylene blue dye. To do so, 50 mg of the prepared nano-
adsorption-desorption isotherms, illustrated in Fig. 11 (a), particles was mixed with 100 mL of 25 ppm methylene

Fig. 11  a ­N2 adsorption–desorption isotherm and b pore size distribution of ­Ni0.33Zn0.33Co0.33-xBixFe2O4 nanoparticles where x = 0, 0.1 and 0.2
Environmental Science and Pollution Research

enhance the accessibility of adsorbate molecules to the

internal surface area, contributing to more efficient adsorp-
tion (Kassem et al. 2024).

Adsorption kinetics

To figure out the kinetic model that best fits the experi-
mental data, first- and second-order kinetic models
were applied. The linear forms of the kinetic models are
expressed as follows (Aridi et al. 2023):

(7)
( )
ln qe − qt = −k1 t + lnqe

t t 1
qt
= +
qe k2 q2e (8)

Fig. 12  Effect of contact time on the removal % achieved in the pres- where qe and qt (mg·g−1) represents the amount of methylene
ence of ­Ni0.33Zn0.33Co0.33-xBixFe2O4 nanoparticles (0 ≤ x ≤ 0.2) blue adsorbed at equilibrium and any time t, respectively.
In addition, k1 ­(min−1) and k2 (g·mg−1·min−1) represent the
blue solution at 25 °C. The influence of contact time on rate constant of the first-order and second-order models,
the removal % of methylene blue was studied in the pres- respectively. The obtained values of the rate constants (k1
ence of ­N i 0.33Zn 0.33Co 0.33-xBi xFe 2O 4 nanoparticles. The and k2) along with the coefficient of determination (R2) are
obtained results are displayed in Fig. 12. As the contact listed in Table 4. Higher R2 values are revealed for the sec-
time increases to 30 min, the removal % of methylene blue ond-order model compared to the first-order model. There-
greatly increases. However, the further increase in the con- fore, the examination of kinetic behavior showed that the
tact time above 30 min slightly improves the removal %. absorption of methylene blue adheres to the second-order
Thus, the adsorption equilibrium is achieved after 30 min. kinetics. This result is in good agreement with previously
Among the synthesized samples, improved adsorption published reports where the adsorption of methylene blue
performance is revealed by pure N ­ i0.33Zn0.33Co0.33Fe2O4 onto ­MgFe2O4 and Z ­ nFe2O4 adsorbents followed the sec-
nanoparticles (x = 0), where 94.4 and 97.1% of methylene ond-order kinetics (Zhang et al. 2017; Ivanets et al. 2022).
blue are adsorbed after a contact time of 30 and 120 min, Furthermore, the study identifies the highest rate constant
respectively. In addition, as x increases from 0 to 0.2, the (k 2 = 0.0050 g·mg−1·min −1) observed when using pure
removal %, analyzed after 30 min, decreases from 94.4 ­Ni0.33Zn0.33Co0.33Fe2O4 nanoparticles (x = 0), suggesting
to 73.6%, respectively. Therefore, introducing Bi dopant that this composition exhibits the most efficient adsorption
into ­Ni0.33Zn0.33Co0.33Fe2O4 nanoparticles reduces their kinetics for methylene blue among the tested nanoparticles.
adsorption activity. Among the prepared samples, the pure The applied first- and second-order kinetic models
nanoparticles with high oxygen vacancies and large pore do not adequately explain the diffusion mechanism of
diameters exhibited enhanced adsorption activity. Oxy- the adsorption process. Consequently, the intra-particle
gen vacancies create more active sites on the nanoparticle diffusion (IPD) model was used to gain insights into
surface, facilitating the interaction between the adsorbent the adsorption mechanism of methylene blue dye onto
and MB molecules (Ranjbari et al. 2024). This increases ­Ni0.33Zn0.33Co0.33-xBixFe2O4 nanoparticles. The equation
the overall adsorption capacity. In addition, larger pores of the IPD model is represented as follows (Li et al. 2021):

Table 4  Parameters x First-order model Second-order model

obtained from the first
−1 −1 2
and second-order kinetic k1 ­(min ) qe (mg·g ) R k2 (g·mg−1·min−1) qe (mg·g−1) R2
models for the adsorption
of methylene blue onto 0 0.0594 26.25 0.91 0.0050 50.48 0.99
­Ni0.33Zn0.33Co0.33-xBixFe2O4 0.05 0.0540 29.89 0.92 0.0035 50.20 0.99
nanoparticles (0 ≤ x ≤ 0.2) 0.1 0.0559 32.43 0.93 0.0029 50.68 0.99
0.15 0.0523 36.85 0.94 0.0015 53.02 0.97
0.2 0.0467 31.36 0.91 0.0025 44.74 0.99
 Environmental Science and Pollution Research

Table 5  Parameters x First region Second region

obtained from the IPD
−1 −1/2 −1
model for the adsorption kIPD1 (mg·g ·min ) C1 (mg·g ) kIPD2 (mg·g−1·min−1/2) C2 (mg·g−1)
of methylene blue onto
­Ni0.33Zn0.33Co0.33-xBixFe2O4 0 7.97 4.83 0.27 45.69
nanoparticles (0 ≤ x ≤ 0.2) 0.05 8.56 0.51 0.52 42.14
0.1 9.03 3.79 0.50 42.17
0.15 10.18 11.64 0.82 38.50
0.2 7.02 2.43 0.77 33.31

Fig. 14  Effect of pH on the removal % achieved in the presence of

Fig. 13  IPD applied on the adsorption of methylene blue onto ­Ni0.33Zn0.33Co0.33−xBixFe2O4 nanoparticles (0 ≤ x ≤ 0.2)
­Ni0.33Zn0.33Co0.33-xBixFe2O4 nanoparticles (0 ≤ x ≤ 0.2)

Effect of pH
qt = kIPD t 1∕2
+C (9)
To inspect the effect of pH on the adsorption process of
where k IPD (mg·g −1·min 1/2) and C (mg·g −1) denote the methylene blue, the adsorption reaction was performed in
IPD rate constant and the thickness of the boundary layer, different mediums where the pH ranges between 1 and 11.
respectively. The obtained values of kIPD and C are listed The obtained results are represented in Fig. 14. It is shown
in Table 5. As shown in Fig. 13, two linear regions exist that pure nanoparticles exhibit different behaviors com-
in the plot of the IPD model analyzed in the presence of pared to the doped nanoparticles. In the presence of pure
the prepared nanoparticles. This indicates that the adsorp- ­Ni0.33Zn0.33Co0.33-xBixFe2O4 nanoparticles with x = 0, the
tion process of methylene blue dye involves multiple stages. removal % of methylene blue increases as pH increases.
Additionally, greater values of the IPD rate constant are Thus, improved adsorption activity is exhibited in the basic
revealed in the first region, denoted as kIPD1, compared to medium and the highest removal % was achieved at pH 11.
that of the second region (kIPD2). The rapid diffusion phase Conversely, ­Ni0.33Zn0.33Co0.33-xBixFe2O4 nanoparticles (0.05
associated with the external surface adsorption of methyl- ≤ x ≤ 0.2) exhibit enhanced adsorption performance in an
ene blue is revealed from the first region of the IPD plot. acidic medium, and the maximum removal % is achieved
Conversely, a slow adsorption phase linked with the intra- at pH 1. To better understand this behavior, zeta potential
particle diffusion of methylene blue within the pores of the measurements were performed. As shown in Fig. 15, the
­Ni0.33Zn0.33Co0.33-xBixFe2O4 adsorbents is shown from the zeta potential of N
­ i0.33Zn0.33Co0.33-xBixFe2O4 nanoparticles
second region of the IPD plot. It is worth mentioning that with x = 0 and 0.2 are 12.5 and − 3.89 mV, respectively.
the non-zero values of C1 and C2 representing the thickness Consequently, the prepared nanoparticles became nega-
of the boundary layer suggest the contribution of surface tively charged after the incorporation of the Bi dopant. Since
adsorption. Hence, the intra-particle diffusion is not the sole methylene blue is a cationic dye, it carries a positive charge
rate-determining step. in the solution. Thus, it is attracted to negatively charged
Environmental Science and Pollution Research

Fig. 15  Zeta poten-

tial measurement of
­Ni0.33Zn0.33Co0.33-xBixFe2O4
nanoparticles where a x = 0 and
b x = 0.2

nanoparticles. In the case N

­ i0.33Zn0.33Co0.33-xBixFe2O4 nano- min. The maximum removal percentage, mainly 98.4%, is
particles with x = 0, the nanoparticles are positively charged achieved when pure N ­ i0.33Zn0.33Co0.33Fe2O4 (x = 0) adsor-
in acidic and neutral media and negatively charged in basic bents are mixed with 5 ppm methylene blue solution. As x
medium. Therefore, improved adsorption activity is revealed increases to reach 0.2, the removal % of 5 ppm methylene
in the basic medium. However, N ­ i0.33Zn0.33Co0.33-xBixFe2O4 blue solution is reduced to reach 76%. In addition, as the
nanoparticles with (0.05 ≤ x ≤ 0.2) are negatively charged. initial concentration increases to 100 ppm, the removal %
Therefore, in an acidic medium attractive forces occur recorded in the presence of pure ­Ni0.33Zn0.33Co0.33Fe2O4
between methylene blue and nanoparticles leading to (x = 0) adsorbent decreases to 79.8%. This can be attributed
enhanced adsorption activity. However, the incorporation to the higher availability of active sites on the adsorbent at
of negative charges in a basic medium leads to repulsion lower concentrations, allowing for the attachment of meth-
forces and reduces the adsorption activity. Among the pre- ylene blue molecules. As the initial concentration increases,
pared samples, superior adsorption performance is revealed the active sites become occupied, leading to a decrease in
by ­Ni0.33Zn0.33Co0.33-xBixFe2O4 nanoparticles with x = 0.05 the removal percentage.
where 98.2% of methylene blue is adsorbed after contact However, the adsorption capacity increases with
time of 30 min. the rise in initial concentration in the presence of the
­N i 0.33 Zn 0.33 Co 0.33-x Bi x Fe 2 O 4 (0 ≤ x ≤ 0.2) adsorbents,
Influence of initial dye concentration as depicted in Fig. 16 (b). Consequently, when the ini-
tial concentration rises from 5 to 100 ppm, the adsorp-
To study the influence of the initial concentration on the tion capacity (q e) determined in the presence of pure
removal % and adsorption capacity, the adsorption exper- ­N i 0.33 Zn 0.33 Co 0.33 Fe 2 O 4 adsorbent rises from 9.84 to
iment was carried out using 5, 10, 25, 50, and 100 ppm 159.6 mg·g −1. Notably, like the removal percentage,
methylene blue solution. The adsorption experiments were ­Ni0.33Zn0.33Co0.33Fe2O4 (x = 0) adsorbents exhibit the high-
performed at 25 °C, where 100 mL of the methylene blue est adsorption capacity among the prepared samples. It is
solution was mixed with 50 mg of the prepared adsorbents. important to highlight that at high dye concentrations, the
As shown in Fig. 16 (a), an increase in the initial concentra- driving force for mass transfer is substantial. This suggests
tion results in a decrease in the removal percentage for all a prominent tendency for dye molecules to move from the
the prepared samples, measured after a contact time of 30 liquid phase and adhere to the solid adsorbent nanoparticles
 Environmental Science and Pollution Research

Compared to other ferrite nanoparticles tested under similar

conditions, the nanoparticles prepared in this study demon-
strated superior adsorption activity for the removal of MB.
For instance, the adsorption capacities of ­ZnFe2O4 and
­CoFe2O4 nanoparticles were reported in a previous study
to be 17.9 and 16.4 mg·g−1, respectively (Ramadan and
Shehata 2021). In addition, Gayathri Manju et al. (2019)
reported the adsorption capacity of 62 mg·g−1 for ­NiFe2O4
nanoparticles. The maximum adsorption capacity for MB
dye onto C­ o0.9Zn0.1Fe2O4 nanoparticles was determined to
be 3.4 mg·g−1 (Tatarchuk et al. 2019). Therefore, combin-
ing equal proportions of Ni, Zn, and Co to prepare tri-metal
ferrite nanoparticles enhance adsorption performance com-
pared to ­NiFe2O4, ­ZnFe2O4 and ­CoFe2O4.
The adsorption capacity of N­ i0.33Zn0.33Co0.33Fe2O4 nano-
particles through methylene blue has been compared with
previous studies of several ferrite adsorbents and listed in
Table 6. Note that the reported values were obtained recently
through likely conditions and adsorbents that are also com-
parable with the present work. Despite the decrease in
adsorption capacity with the increase of bismuth doping,
the prepared samples have gained the highest adsorption
capacity.

Adsorption isotherm

To understand the adsorption mechanism and clarify the

adsorption relation between the methylene blue dye and
­Ni0.33Zn0.33Co0.33-xBixFe2O4 (0 ≤ x ≤ 0.2) adsorbents, it is
Fig. 16  Effect of initial methylene blue concentration on the essential to analyze the adsorption isotherms. Therefore,
a removal % and b adsorption capacity in the presence of non-linear Langmuir, Freundlich, and Temkin isotherms
­Ni0.33Zn0.33Co0.33-xBixFe2O4 nanoparticles (0 ≤ x ≤ 0.2) were applied. The plots representing the fitting of these
isotherms are shown in Fig. 17, and the extracted param-
eters are listed in Table 7. The Langmuir isotherm model
(Adewuyi et al. 2021). This phenomenon is the key factor suggested that no intermolecular interaction exists between
contributing to the increased adsorption capacity in the pres- the adsorbate molecules. Thus, the adsorption of methyl-
ence of a high initial dye concentration. ene blue dye molecules is limited to monolayer. Whereas
It is worth mentioning that the adsorption capacity (qe) the Freundlich isotherm model suggests the formation
of pure ­Ni0.33Zn0.33Co0.33Fe2O4 adsorbent, when mixed with of a multilayer and applies to heterogeneous adsorption
a 50 ppm MB solution, is determined to be 87.36 mg·g−1. surfaces, it is important to note that adsorbate-adsorbent

Table 6  Comparison of Absorbent Maximum adsorption capacity Reference

maximum adsorption capacity (mg ­g−1)
on various absorbents
ZnFe2O4 17.9 Ramadan and Shehata (2021)
NiFe2O4 62 Gayathri Manju et al. (2019)
CoFe2O4 16.4 Ramadan and Shehata (2021)
Ferrite bismuth nanoparticles 23.83 Soltani and Entezari (2013)
Ni0.5Zn0.5Fe2O4 9.4 Tahar et al. (2024)
Co0.9Zn0.1Fe2O4 3.4 Tatarchuk et al. (2019)
CoFe1.9Zn0.1O4 27.79 Amar et al. (2020)
Ni0.33Zn0.33Co0.33Fe2O4 87.36 Present study
Environmental Science and Pollution Research

Fig. 17  The fitting plots of non-linear adsorption isotherms for adsorption of methylene blue onto ­Ni0.33Zn0.33Co0.33-xBixFe2O4 nanoparticles
where a x = 0, b x = 0.05, c x = 0.1, d x = 0.15, and e x = 0.2
 Environmental Science and Pollution Research

Table 7  Parameters obtained x 0 0.05 0.1 0.15 0.2

from the fitting of non-linear
adsorption isotherms Langmuir −1
QL (mg·g ) 208.95 60.66 57.95 55.88 48.87
bL (L·mg−1) 0.14 3.71 1.09 −3.79 −2.40
R2 0.97 0.18 0.19 0.19 0.21
Freundlich KF ((mg·g−1) 35.63 20.39 19.16 13.34 9.23
(mg·L−1)1/n)
n 2.01 1.60 1.69 1.47 1.62
R2 0.99 0.99 0.98 0.99 0.99
Temkin KT (L·mg−1) 8.21 3.07 2.14 1.12 0.82
bT (J·mol−1) 94.45 86.21 84.12 72.78 101.26
R2 0.88 0.85 0.90 0.91 0.93

molecule interaction is taken into consideration in the

Temkin model. Equations (10), (11), and (12) represent the
Langmuir, Freundlich, and Temkin isotherm, respectively
(Kassem et al. 2024):
QL bL Ce
qe = (10)
1 + bL Ce

( 1)
qe = KF × Cen (11)

RT
qe =
bT
ln(KT Ce ) (12)

where QL and bL denote the maximum monolayer adsorption

capacity of the prepared adsorbents and Langmuir constant,
respectively. The parameters n and KF represent the adsorp-
Fig. 18  Effect of temperature on the removal percentage of methyl-
tion intensity and Freundlich constant, respectively. The
ene blue in the presence of ­Ni0.33Zn0.33Co0.33-xBixFe2O4 nanoparticles
coefficient related to the sorption heat is denoted as bT, and (0 ≤ x ≤ 0.2)
KT signifies the equilibrium binding constant. The Langmuir
model yielded extremely low R2 values accompanied by the
negative Langmuir constant specifically for the adsorption
process in the presence of ­Ni0.33Zn0.33Co0.33-xBixFe2O4
nanoparticles ( x = 0.15 and 0.2). Hence, this indicates the Effect of temperature and thermodynamic parameters
inadequacy of the Langmuir model to describe the adsorp-
tion phenomenon of methylene blue. The highest values To examine the inf luence of temperature, adsorp-
of R2 were revealed from the fitting of the Freundlich iso- tion exper iments of met hylene blue dye onto
therm model. Thus, the Freundlich model more effectively ­Ni0.33Zn0.33Co0.33-xBixFe2O4 nanoparticles were conducted
describes the adsorption process of methylene blue onto at 298, 318, 333, 348, and 363 K. Figure 18 shows that the
the ­N i 0.33Zn 0.33Co 0.33-xBi xFe 2O 4 nanoparticles. Among removal percentage increases with temperature, indicating
the prepared nanoparticles, the highest values of adsorp- enhanced adsorption. Additionally, improved adsorption
tion intensity and Freundlich constant are revealed by pure activity was observed in the pure nanoparticles (x = 0),
­Ni0.33Zn0.33Co0.33Fe2O4 nanoparticles. It has been docu- which is consistent with previous findings. To understand
mented that improved adsorption is associated with values the nature of the adsorption process of methylene blue
of n falling within the range of 1–10 (Zhang et al. 2017). onto the prepared nanoparticles, thermodynamic param-
In this study, the obtained n values fall within this range, eters including free energy change (ΔG0), enthalpy (ΔH0),
indicating favorable adsorption of methylene blue dye onto and entropy (ΔS 0) were determined. These parameters
the prepared samples. were calculated using the following equations (Kassem
et al. 2024; Sharrouf et al. 2024):
Environmental Science and Pollution Research

Conclusion

Ni0.33Zn0.33Co0.33-xBixFe2O4 nanoparticles were formed

using a chemical co-precipitation technique, along a 21%
of α-Fe2O3 phase for the highest doping content (x = 0.2).
The structural and morphological analysis confirmed the
decreasing value of the crystallite and particle size as bis-
muth doping increased from x = 0 to 0.2. Moreover, XPS
spectra revealed the presence of the main core levels, with-
out the presence of any impurity ions. The un-doped sam-
ple acquired the highest number of oxygen defects obtained
from the maximum area of O 1s core level in the XPS analy-
sis and through the peak in the DLE region in the PL analy-
sis. Optically, the NBE peak illustrated in the PL spectra
reported the highest recombination rate for x = 0.15. Addi-
tionally, the emission peak position and intensity may be
Fig. 19  Plot of ln(Kd) versus 1/T controlled by the excitation wavelength and the bismuth con-
tent. Such insights may enhance the adsorption performance.
Hence, the adsorption activity was studied for methylene
Table 8  Thermodynamic parameters for the methylene blue adsorp- blue pollutant removal under several conditions (contact
tion reaction onto ­ Ni0.33Zn0.33Co0.33-xBixFe2O4 nanoparticles time, pH, and dye concentration). Accordingly, the adsorp-
(0 ≤ x ≤ 0.2)
tion activity revealed an enhancement from 94.4 to 97.1% of
x ΔH (kJ·mol−1) ΔS (J·mol−1·K−1) ΔG (kJ·mol−1) methylene blue adsorbed after a contact time of 30 and 120
0.00 49.75 179.72 − 9.92 min, respectively. Moreover, the removal % decreased from
0.05 35.10 127.89 − 7.36 94.4 to 73.6%, as bismuth content increased from 0 to 0.2
0.10 34.15 123.21 − 6.75 and analyzed after 30 min. The pure sample (x = 0) achieved
0.15 30.15 109.25 − 6.11 the highest % (98.4%) when mixed with 5 ppm methylene
0.20 32.52 112.38 − 4.79 blue solution. Additionally, pH influence showed a signifi-
cant result, where the un-doped sample (x = 0) showed an
enhancement in MB adsorption for pH = 11. Conversely,
the doping of bismuth improved the adsorption of MB dye,
Cac especially at pH = 1, where the removal percentage reached
Kd = , (13) 98.2%. As confirmed by zeta potential analysis, the surface
Ce
of the pure nanoparticles was positively charged (+ 12.5
mV), but it became negatively charged (− 3.89 mV) when
ΔH 0 ΔS0
◦

lnKd = − + , (14) the Bi content reached 0.2. In addition, the well-fitting of the
RT R
non-linear Freundlich isotherm model suggested the forma-
tion of a multilayer and heterogeneous adsorption surface.
ΔG0 = ΔH 0 − TΔS0 (15) Among the prepared nanoparticles, the highest values of
where Kd is the equilibrium constant; Cac is the concentra- adsorption intensity and Freundlich constant are revealed
tion of methylene blue adsorbed at equilibrium; and Ce is the by pure ­Ni0.33Zn0.33Co0.33Fe2O4 nanoparticles revealing
equilibrium concentration of methylene blue in the solution. the favorable adsorption of MB onto the prepared samples.
R denotes the universal gas constant, and T is the tempera- Through the last decade, ferrite nanoparticles have gained
ture in Kelvin. By plotting ln(Kd) against 1/T, as shown in the attention of researchers for the pollutant. To wrap up,
Fig. 19, ΔH0 and ΔS0 can be derived from the slope and the the nanoferrites synthesized in this study have gained a very
intercept, respectively. The estimated values of ΔH0, ΔS0, high adsorption capacity for methylene blue removal from
and ΔG0 are listed in Table 8. The positive value of ΔH0 water, compared to various recent studies. Further research
confirms that the adsorption of methylene blue dye onto the will aim to study the removal of MB under sunlight for real
prepared nanoparticles is an endothermic process. The posi- water samples, not only through laboratory experiments.
tive value of ΔS0 indicates an increase in disorder during the Acknowledgements The Advanced Nanomaterial Research Lab – Bei-
adsorption process. Additionally, the negative values of ΔG0 rut Arab University – Lebanon, Alexandria University, and Egypt Japan
confirm that the process is spontaneous.
 Environmental Science and Pollution Research

University of Science & Technology — Egypt is highly acknowledged characterization on pure and Sm-doped ZnO nanoparticles. J
for its experimental support. Nanomater 2018:7096195. https://d​ oi.o​ rg/1​ 0.1​ 155/2​ 018/7​ 09619​ 5
Bahnasawy N, Elbanna AM, Ramadan M, Allam NK (2022) Fabrica-
Author contribution All the authors contributed to the study’s concep- tion of polyhedral Cu–Zn oxide nanoparticles by dealloying and
tion and design. The conceptualization was led by Ramadan Awad. anodic oxidation of German silver alloy for photoelectrochemical
Material preparation, data collection, and analysis were performed by water splitting. Sci Rep 12:16785
Dema Dasuki, Amani Aridi, Marwa Elkady, Khulud Habanjar, Gehan Banerjee M, Mukherjee A, Chakrabarty S et al (2019) Bismuth-doped
M. El-Subruiti, and Ramadan Awad. The first draft of the manuscript nickel ferrite nanoparticles for room temperature memory devices.
was written by Dema Dasuki, Amani Aridi, and Khulud Habanjar, ACS Appl Nano Mater 2:7795–7802. https://​doi.​org/​10.​1021/​
with all the authors providing comments on the previous versions of acsanm.​9b018​28
the manuscript. All the authors read and approved the final version. Birniwa AH, Mahmud HNME, Abdullahi SS et al (2022) Adsorption
behavior of methylene blue cationic dye in aqueous solution using
Data availability The data used in this study will be made available polypyrrole-polyethylenimine nano-adsorbent. Polymers 14:3362
upon request. Channa N, Khalid M, Chandio AD et al (2020) Nickel-substituted
manganese spinel ferrite nanoparticles for high-frequency appli-
Declarations cations. J Mater Sci: Mater Electron 31:1661–1671. https://​doi.​
org/​10.​1007/​s10854-​019-​02684-0
Ethics approval Not applicable. Di Quarto F, Zaffora A, Di Franco F, Santamaria M (2024) Modeling
of optical band-gap values of mixed oxides having spinel struc-
Consent to participate Not applicable. ture AB 2 O 4 (A = Mg, Zn and B = Al, Ga) by a semiempirical
approach. ACS Org Inorg Au 4:120–134. https://​doi.​org/​10.​1021/​
Consent for publication Not applicable. acsor​ginor​gau.​3c000​30
Dos Santos ME, Aparecido Ferreira R, Noronha Lisboa-Filho P, Peña
Competing interests The authors declare no competing interests. O (2013) Cation distribution and magnetic characterization of the
multiferroic cobalt manganese Co2MnO4 spinel doped with bis-
muth. J Magn Magn Mater 329:53–58. https://​doi.​org/​10.​1016/j.​
jmmm.​2012.​09.​070
Elkady M, Shokry H, El-Sharkawy A et al (2019) New insights into
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