Ali and Ali BMC Chemistry(2024) 18:147
https://doi.org/10.1186/s13065-024-01257-5

BMC Chemistry

RESEARCH

Open AccessGreen synthesis of Carbonized ChitosanFe3O4-SiO2 nano-composite for adsorptionof heavy metals from aqueous solutions
Dalia Amer Ali1* and Rinad Galal Ali1
Abstract
Water pollution with heavy metals owing to industrial and agricultural activities have become a critical dilemma
to humans, plants as well as the marine environment. Therefore, it is of great importance that the carcinogenic
heavy metals present in wastewater to be eliminated through designing treatment technologies that canremove multiple pollutants. A novel green magnetic nano-composite called (Carbonized Chitosan-Fe3O4-SiO2)
was synthesized using Co-precipitation method to adsorb a mixture of heavy metal ions included; cobalt (Co2+),nickel (Ni2+) and copper (Cu2+) ions from aqueous solutions. The novelty of this study was the synthesis of a new
nano-composite which was green with magnetic properties to be more sustainable and environmentally friendly.
Its magnetic properties made it separated easily from solutions after accomplishment of the adsorption processusing a magnet. Extended Freundlich isotherm was the best fitted model with maximum adsorption capacity ofthe metal ions mixture 2908.92 mg/g. Different experimental parameters have been studied included the initialconcentration for a mixture of nickel, cobalt and copper metal ions (0.05–0.1 molar), dosage of adsorbent (0.5–
3.5 g/L) and contact time (6–90 min) to investigate their changing effect on the removal percents of the heavy
metal ions mixture from aqueous solutions. The experimental adsorption percent of cobalt ion ranged from 1.58
to 64.28%, nickel ion adsorption percent ranged from 10.68 to 94.12% and copper ion adsorption percent ranged
from 4.41 to 76.23% at pH = 9 were based on the combination of the adsorption process parameters.
Keywords Adsorption, Water pollution, Copper, Nickel, Cobalt, Chitosan, Silicon dioxide

Introduction
Over the last few years, removing heavy metal ions from
aqueous solutions has become increasingly important,whether as a means of pollution control or for the recovery of raw materials [1, 2]. Heavy metal contamination inhumans affects numerous organs, including the kidneys,
the liver, the stomach, the mental environment, and the*Correspondence:
Dalia Amer Ali
Dalia.Amer@bue.edu.eg
1
Department of Chemical Engineering, The British University in Egypt,
El-Sherouk City 11837, Egypt

reproductive system [3]. Humans are also susceptible tocarcinogenic effects caused by heavy metals [3]. Nickel(Ni), cobalt (Co) and copper (Cu) are most popular toxic
heavy metals [4]. These heavy metals can still be hazardous even when they are detected in traces [4]. Nickel
exists in the effluent wastewater from stainless steel andnickel alloy production [4]. While cobalt resources are
paint, pigment and electroplating industries [5]. The copper main resources are corroded plumbing systems, electronic and cables industry [2]. The maximum permissiblelevels of nickel, cobalt and copper in drinking water are
0.07 mg/l, 0.05 mg/L, 2 mg/L, respectively, according to
the world health organization (WHO) recommendations© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use,sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) andthe source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in thisarticle are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not includedin the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you willneed to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The
Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available
in this article, unless otherwise stated in a credit line to the data.

Ali and Ali BMC Chemistry(2024) 18:147[6, 7]. Nanotechnology is defined as the design and fabrication of materials, devices and systems with control at
nano-meters dimensions [8]. The essence of nanotechnology is therefore size and control [9]. Nanotechnology
is considered nowadays as a promising alternative technology for removal of various contaminants from wastewater [10]. Nano-adsorption and NF are considered to bepromising techniques introduced by nanotechnology for
wastewater treatment [10].
Chemical precipitation, biological methods, ion
exchange, and adsorption are some of the methods forremoving heavy metal ions from aqueous solutions [8,9]. Chemical precipitation, also defined as coagulation
precipitation, is a widely employed technique in industry and is regarded as influential and mature [2]. Biotechnological methods use the natural characteristics of
microorganisms to soak up and collect heavy metals [11].
Biological method is a more complex and costly methodof heavy metal elimination from wastewater due to production of large amounts of biomass [12]. Adsorption is
widely used in heavy metals removal from wastewater
due to the numerous advantages it offers [2]. It has various benefits over different forms of contaminant reduction for it is easy to develop and execute technologicallyeasy and is flexible to multiple treatment forms. It operates in favorable working circumstances and a broad pH
range [13]. Nano-adsorbents are better than the conventional adsorbents because, they have larger surface areas
and more active sites which give them higher degree ofpollutants selectivity [10]. The carbon-based adsorption
technique is widely applied in environmental protection, and biomass-derived carbon is recognized as oneof the most economical and promising adsorbents forheavy metal removal due to its high porosity and thus
high adsorption capacity [14]. In addition, nano-silica
is considered to be mineral adsorbent that has a highadsorption capacity for heavy metal ions at low operating
costs [13]. The presence of hydroxyl, carboxyl and aminogroups on the surface of adsorbent increases its affinity toadsorb heavy metals from wastewater [15, 16]. According to the previous studies, many adsorbents removed
low concentrations of heavy metals from aqueous solutions [2]. Therefore, it becomes necessary to create andimprove the properties of adsorbents to increase theirability in removal of high concentrations of heavy metals from aqueous solutions. Thus, the first objective of
this research study is to create a novel green magnetic
nano-composite consists of (Carbonized Chitosan) asa precursor material which will be functionalized withmagnetite (Fe3O4) and silica (SiO2) extracted from abio-waste (sugarcane bagasse) to increase its adsorption
capacity towards high concentrations of heavy metals.
The functionalization of the (Carbonized Chitosan) withmagnetite and silica will be performed in this study inPage 2 of 23

order to combine the benefits of high porosity and stability of the (Carbonized Chitosan) with high capacityof silica towards heavy metals and the magnetic properties of magnetite that will facilitate the separation of the
new nano-composite after adsorption process. A second
objective of this study is to evaluate the ability of this synthesized novel green nano-composite in simultaneous
removal of high concentration mixtures of heavy metal
ions (Co2+), (Ni2+) and (Cu2+) from aqueous solutions.

Materials and methods
Chemicals

Sugarcane bagasse was collected from a farm at Alsharkeya governorate, Egypt. All chemicals used in this study
were analytical grade reagents including; Ferric chloride hexahydrate (FeCl3.6H2O), Ferrous sulphate heptahydrate (FeSO4·7H2O), Copper sulphate pentahydrate(CuSO4.5H2O), Cobalt (II) chloride (COCL2), Nickel (II)chloride hexahydrate (NiCl2.6H2O) were provided by
Sigma Aldrich Company. Chitosan (C6H11NO4)n, Sodiumhydroxide (NaOH) and Hydrochloric acid (HCl 36% v/v)
were provided by Nano-Gate Company, Egypt. Deionizedwater was used for preparation of all solutions.
Equipment

The morphology of the extracted sodium silicate(Na2SiO3) and the (Carbonized Chitosan-Fe3O4-SiO2)
were conducted by scanning electron microscope (SEM,
Quattro s – Thermo Scientific, Netherland) and Transmission Electron Microscope (TEM) (JEM-1400Flash,
JEOL Solutions for Innovation Company, USA). The
specific surface area, pore-size and particle size were
determined by Brunauer-Emmett-Teller (BET) (NOVA
touch, Quantachrome Company, U.S.A). The purity ofthe prepared nano-composite was conducted by X-Ray
Diffraction (XRD) (Empyrean – Malvern Analytical
Company, Netherland). The identification of the groups
existed on the surface of the synthesized nano-composite
was investigated using Fourier Transformation Infrared(FTIR) spectra (Vertex 70 RAM II, Germany). The surface charge of the new prepared nano-composite wasdetermined using dynamic light scattering instrument(ZetaSizer Nano Series (HT), Nano ZS, Malvern Instruments, UK). Filtration of sodium silicate (Na2SiO3) was
performed using vacuum filtration apparatus (RS-1,
Shenzhen Educational Equipment, China). Vacuum dryer(Thermo-Fisher Scientific Company, USA) was used fordrying the final product.
Kinetics models

The rate of acceptance of the dissolve and the periodrequired for adsorption are both heavily influenced
by adsorption kinetics [17]. It is employed to evaluate
the effectiveness of the adsorbent and its mass transfer

Ali and Ali BMC Chemistry(2024) 18:147

Page 3 of 23

processes. Pseudo First Order (PFO) and Pseudo Second
Order (PSO) kinetic models were used to study the kinetics at various time points for adsorbing the mixture of
Co2+, Ni2+ and Cu2+ metal ions [17]. The kinetic models
of PFO and PSO were characterized by Eqs. (1) and (2)[18].

PFO : Log (qe − q) = Log (qe) −t
1
P SO :=+
qt
k2 ∗ qe2



1
qe



k1*t
(1)
2.303
∗ t (2)Where qt and qe are, respectively, the quantity of heavy
metal ions that the adsorbent has absorbed at equilibrium and time (t). The rate constants for PFO and PSO
are k1 and k2, respectively
Single-component isotherm models

The ratio between the equilibrium solute concentrationon the exterior of the adsorbent (qe) and the contacting
solute quantity in the liquid (Ce) are related by a curve
known as the adsorption isotherm [19, 20]. It is typicallyused to analyze porous solids, design the adsorption procedure, and determine the adsorbent’s specific surface
area [19, 20].
Langmuir

The idea of monomolecular adsorption on a regular exterior is demonstrated by the Langmuir isotherm model.
This model can be described by Eq. (3) [15, 16]:

Ce
=
qe




1
1
*Ce +
(3)
qm
qm*KL

The Langmuir constant, KL, represents the adsorptionenergy (L/mg), and qm is the optimum monolayer adsorption capacity (mg/g). Ce and qe are the concentrations atequilibrium of the heavy metal ions mixture in (mg/L) inthe solution and solid phases, respectively.
Freundlich

The adsorption characteristics of the heterogeneous surface are revealed by this model [19]. The two-parameter
Freundlich isotherm model is described by the following
Eq. (4) [21, 22]:

Log qe = Log KH +1
∗ Log Ce (4)nWhere n and KH (L/mg) are the Freundlich constants,
which represent, respectively, adsorption intensity andcapacity.

Dubinin-Radushkevich

The process of adsorption onto heterogeneous surfaces
is represented in this model by a Gaussian energy distribution [21, 22]. This model, which is temperaturedependent, can be used for physical adsorption. Only
pollutants with intermediate concentration ranges canbe employed with this model [21, 22]. Following are theEqs. (5) and (6) that represent the Dubinin-Radushkevich
isotherm model [21, 22]:

Ln q = Ln qmax − β R2 T 2Ln2 (1 +E=√

1) (5)
C

1
(6)
2β

Where β (mol2/kJ2) denotes an adsorption energy constant, qmax (mg/g) denotes the optimum adsorption
capacity, and E denotes the free energy/adsorbate molecule (kJ). According to [22, 24] the quantity of E is utilized to tell the different kinds of adsorption approaches
apart:
a. A physical adsorption will occur whenever freeenergy/adsorbate molecule (E) is < 8 kJ/mol.
b. If 8 kJ/mol < E < than 16 kJ/mol, then ion exchange or
chemical adsorption will take place.
c. The reaction will be governed by particle diffusion if
E > 16 kJ/mol.
Multiple-component isotherm models

The multi-component adsorption idea is now crucial towastewater treatment procedures since wastewater today
contains significant quantities of multiple contaminants.
This is because single-component isotherm models areunable to capture the aggressive interchanges among thecontaminants current in the contaminated water. Additionally, the entire adsorption process is significantly
impacted by the competitive interactions between pollutant molecules. To demonstrate multiple-component
adsorption systems, Modified Langmuir isotherm models and Extended Freundlich isotherm can be employed[23].
Extended freundlich

In the event that interactions between the molecules ofdeposited contaminants occur, this model is utilized to
depict multilayer adsorption procedures on diverse exteriors [24, 25]. The following Eqs. (7) and (8) represent theextended Freundlich isotherm model [24, 25].

Ali and Ali BMC Chemistry(2024) 18:147

1
KF, 1. Ce, 1( n1 )+X1
(7)qe, 1 =
Ce, 1X1 + y1.Ce, 2Z1
1
KF, 2. Ce, 2( n2 )+X2
(8)qe, 2 =
Ce, 2X2 + y2.Ce, 2Z2

Where the equilibrium adsorption capacities for components 1 and 2 are respectively, qe,1 and qe,2 in (mg/g). The
Freundlich constants for components 1 and 2 are KF,1 andKF,2, respectively. The equilibrium concentrations of components 1 and 2 are Ce,1 and Ce,2, respectively, in (mg/L).
The adsorption strengths for elements 1 and 2 are givenby the numbers n1 and n2, which are derived from experimental data for distinct Freundlich isotherms.
Modified langmuirThis model clarifies how pollutant molecule interactions
take place in a solution. In order to highlight the competing impact of the pollutant molecules in the solution andto understand the nature of the adsorption process, thismodel also incorporates the interaction factor [23, 25].
Equation (9) is used to represent the modified Langmuir
isotherm model [23, 25].

qm, i . KL, i . ηCe,iL,i (9)
qe, i =
N
1 + j=1 (KL, j . ηCe,j)L,jThe Langmuir isotherm model illustrates the basic idea
behind monomolecular adsorption on uniform surfaces.
By applying the Langmuir constant for component i,
KL, i (L/mg), which is derived from experimental data of
individual Langmuir isotherms, one may determine theadsorption capacity of component i, qe, i (mg/g) at equilibrium. The calculation additionally takes into accountthe equilibrium concentration of component i, Ce, i(mg/L) and the monolayer adsorption capacity for component i, qm, i (mg/g). The interaction factor L,i is determined by the concentration of the other components,
and N represents the total number of components in thesolution. Using Microsoft Excel’s solver tool for non-linear regression, L,i and L,j were computed.
Statistical error function

In order to compare the application of different multicomponent isothermal models through nonlinear regression using the least squares method, Marquardt standard
deviation (MPSD) was used as a tool for determining thebest fitting isothermal equation [25]. This can be calculated using the following Eq. (10) [25];Page 4 of 23




2

1
qe,means − qe,calc
n
∗
i=1
n−p
qe,means
(10)MP SD = 100

Where; qe, calc (mg/g) is the calculated adsorption capacity at equilibrium, qe, mean (mg/g) is the average of qe, exp,(n) is the number of the experimental data and (p) is thenumber of factors in each isotherm model.
Extraction of sodium silicate (Na2SiO3) from sugarcane
bagasseAs shown in Fig. 1, small pieces of sugarcane bagasse
were washed with distilled water then dried for a day at
65 oC. Calcination process at 600 oC for 3 h was carriedout for the dried sugarcane bagasse. The extraction of
sodium silicate from the bagasse ash was performed ina two-neck round bottom flask with a condenser where
100 mL of 1 M HCl was mixed at 200 revolutions per
minute (rpm) with 10 g of the bagasse ash under heating at 100 °C for 2 h to increase the weight% of SiO2 andto decrease the other mineral oxides. Followed by washing the precipitate with distilled water until reaching aneutral pH and drying at 70 °C in a dryer for 2 h. Thena solution of 100 mL NaOH (1.5 M) was mixed withthe precipitate at 100 oC for 2 h. Finally, a filtration of
the resulted sodium silicate crystals was achieved using
a centrifuge at 3000 rpm for 10 min, cooling to room
temperature, drying at 70 oC in a dryer and storing in a
dessicator.
The following Eq. (11) represented the alkaline treatment of the bagasse ash using 1 M NaOH solution which
reacted with silica (SiO2) to produce sodium silicate(Na2SiO3) and water (H2O) [26].

SiO2+2NaOH → Na2SiO3+H2 O (11)Synthesis of (Carbonized Chitosan-Fe3O4-SiO2) green
magnetic nano-composite

Since Carbonized Chitosan has a large specific surface
area, it is used as the precursor for the composite. As
represented in Fig. 2, Chitosan was carbonized in a furnace at 300 ◦ C and 5 ◦ C /min for 2 h followed by cooling
until room temperature was reached. For co-precipitation of Magnetite (Fe3O4) on the produced Carbonized
Chitosan; 2.95 g of the Carbonized Chitosan was mixed
with 100 ml solution of Fe3+: Fe2+ which was preparedin a molar ratio 2:1 using FeCl3.6H2O and FeSO4.7H2O
as the precursor salts, respectively. 50 ml of 3 M NaOH
was added to the previous mixture in a drop by drop
wise with mechanical stirring at 300 rpm and heating
at 85 ◦ C for 2 h. Filtration of the produced composite(Carbonized Chitosan-Fe3O4) took place through centrifugation at 3000 rpm for 10 min, rinsing with distilled

Ali and Ali BMC Chemistry(2024) 18:147

Page 5 of 23

Fig. 1 Extraction scheme of sodium silicate from sugarcane bagasse

Fig. 2 Preparation scheme of the (Carbonized Chitosan-Fe3O4-SiO2) green magnetic nano-composite

water until neutral pH then drying in a dryer at 40 ◦ C .
For co-precipitation of SiO2 on the produced composite(Carbonized Chitosan-Fe3O4); 400 ml of sodium silicate
solution 20% (v/v) was mixed with 4.3 g of (Carbonized Chitosan-Fe3O4). 250 ml of 0.1 M HCl was incorporated to the previous mixture in a drop-by-drop wise
till reaching neutral pH with mechanical stirring at
300 rpm and heating at 80 ◦ C for 2 h. Filtration of the

produced composite (Carbonized Chitosan-Fe3O4-SiO2)
has been accomplished using a centrifuge at 3000 rpm
for 10 min followed by washing with distilled water until
reaching neutral pH then drying in a dryer at 40 ◦ C andfinally storage of the composite in a desiccator. The following reaction Eqs. (12) and (13) took place during
the synthesis of the new nano-composite (Carbonized
Chitosan-Fe3O4-SiO2):

Ali and Ali BMC Chemistry(2024) 18:147•Co-precipitation reaction for production of magnetite

2F eCl3 · 6H2 O+
F eSo4 · 7H2O + 8NaOH → F e3O4 (s) + (12)Na2 SO4 + 6NaCl + 23H2 O•Sodium silicate reaction with hydrochloric acid to produce
silicaNa2 SiO3 + 2HCl → SiO2 + 2NaCl + H2 O (13)Adsorption batch experiments

At pH = 9, adjusted with 0.1 M NaOH solution, heavy
metals (Cu2+, Co2+, and Ni2+) were adsorbed from
aqueous solutions. Using CuSO4.5H2O, COCl2 andNiCl2.6H2O, initial concentrations of heavy metals ion
were prepared. The experiments were carried out in conical glass flasks that were shaken vigorously at 200 rpm
using a laboratory shaker. After adsorption, each heavy
metal ion concentration in aqueous solution was measured using a UV/VIS spectrophotometer (UV-5100,
Shanghai Metash Instruments Company), and the following Eq. (14) was used to evaluate the removal efficiency[15, 22]:

RE% = [( Co − C) / Co] *100 (14)Where Co and C are starting and finishing concentrations
in Molar for each heavy metal ion, respectively.
Limitations of this study

One of the experimental limitations occurs during preparation of the (Carbonized Chitosan-Fe3O4-SiO2) nanocomposite using co-precipitation method is the difficultyin particle size control and the nano-particles distribution on the surface of the composite. Moreover, using theco-precipitation method may also produce non-uniform
particle sizes and distributions, which affects the properties of the nanocomposite. In addition, to achieve thedesired distribution and structure, precise conditions will
be required which can be challenging to replicate consistently. Using the synthesized nano-composite for adsorption may not be very selective towards particular metal
ions, resulting in competitive adsorption behaviors andlower efficiency in the removal and recovery of individual
metal ions from a mixture. It can be challenging to completely desorption all the metal ions and regenerate theactive sites of the synthesized nano-composite for reuse
without losing its adsorptive capacity and performance.
The removal of metal ions is sensitive to pH thus; it isnecessary to determine the suitable pH before starting
the adsorption experiments.

Page 6 of 23

Experimental design

A wide range of parameters are involved in the processof surface adsorption. As a result, maximizing theseparameters is essential to obtaining a high analyte surface
adsorption rate. Response Surface Methodology (RSM) –Central Composite Design (CCD) has become more andmore well-known as the most effective statistical methodology for examining and maximizing the parameters ofdiverse processes within the range of protocols and procedures that are available [27]. RSM-CCD uses a variety
of statistical and mathematical methods to construct anexperimental model with the aim of optimizing response
through thoughtful experiment design that concurrently
elucidates the interdependent relationships between variables [27]. The first step in this analysis is to plan a number of tests in order to get enough response predictions[28]. The influence of various factors on the accuracy of
the result can then be ascertained by fitting a hypothetical (empirical) model to the data acquired in the chosen
design and ultimately figuring out the ideal conditions
on the model’s input variables, leading to maximizingor minimizing the study’s response [27]. Furthermore,it may determine the mix of parameters and values
required to optimum effectiveness (pollutant removal)
by looking at parametric effects and interactions. RSM
modelling and the Design Expert v.13 program were usedin the design and optimization of the reaction parameters. The number of CCD-designed experiments wasdetermined by Eq. (15) [28]:N = k 2 + 2k + n (15)Where k is the number of factors examined, n is thenumber of replicates, and N is the total number ofexperiments.
The position of the axial points within the experimental domain can be inferred from the value of alphain CCD, which is an important consideration [28]. The
alpha value, which can be either orthogonal or spherical, dictates the design of a CCD. In addition, the design
is usually in the middle of being either face centered or
rotatable. Consequently, the design is computed using
Eq. (16) [28]:α = (2k )

0.25

(16)

Because it ensures that the axial point in the factorial
portion of the design is in the proper location, alpha = 1
is the desirable value to be used. Three levels of factors
need to be included in the design matrix for this kind ofdesign, which is referred to as face centered design [28].
A system’s behavior can be mathematically explained by
specifying the relationship between its inputs and outputs [28]. The behavior of the system can be explained byAli and Ali BMC Chemistry(2024) 18:147

Page 7 of 23

a second-order polynomial model, sometimes known asa quadratic model. This model is represented by Eq. (17)[21, 22]:

Y=



2
k
k
βo +
i=1 β i xi +i=1 β ii xii + (17)


k
k
i=1
j=1 β ij xixj + ∈Here, Y represents the responses, k is the total number
independent factors, β o is an intercept, i, ii, and ij with
β represent the coefficient values for linear, quadratic,
and interaction effects, respectively, and xi and xj in theabove equation show the coded levels for independent
variables. For this research, Eq. (17) is written as Eq. (18)[21, 22]:Yi =β o + β 1 x1 + β 2 x2 + β 3 x3 + β 11 x21 +(18)β 22 x22 + β 33 x23 + β 12 x1x2 + β 13 x1x3 + β 23 x2 x3

Table 1 illustrated the experimental design matrix generated by (CCD) including three responses of the removal
percents of nickel, cobalt and copper metal ions from
aqueous solutions. Based on the information shown in
Table 1, the Analysis of Variance (ANOVA) and multiple

regression analyses in the (CCD) with quadratic model
Eq. (18) were carried out.

Results and discussion
Scanning electron microscopy (SEM)

Figure 3 represented the SEM of the extracted Na2SiO3from sugarcane bagasse. This figure illustrated a heterogeneous and porous surface with almost equally sized
spherical particles.
Figure 4 depicted the surface morphology of Carbonized Chitosan, Carbonized Chitosan-Fe3O4 and Carbonized Chitosan-Fe3O4-SiO2 synthesized nano-composite.
The honeycomb carbon structure appeared in Fig. 4awhich ensured the successful carbonization of chitosan.
The Fe3O4 particles have been adopted on the surfaceof Carbonized Chitosan as shown in Fig. 4b where they
appeared as irregular spherical particles. The particles’
size of Carbonized Chitosan–Fe3O4 ranged from 45 nm
to 85 nm. The SiO2 spherical particles have been distributed on the surface of the Carbonized Chtiosan-Fe3O4
composite as shown in Fig. 4c. In addition, the Carbonized Chitosan-Fe3O4-SiO2 particles were agglomerated
due to the magnetic characteristics of Fe3O4 with particle
sizes ranged from 130 nm to 200 nm.
Transmission electron microscope (TEM)

Figure 5a showed the core/shell structure at 1 nm where
the translucent edges were separated from the dark

Table 1 Experimental design matrix
Run

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20

A: Initial concentration ofheavy metals ions

B: Contact time

C: Adsorbent
dose

Percent removal ofnickel ion

Percent removal of
cobalt ion(Molar)
0.1
0.1
0.075
0.1
0.05
0.075
0.075
0.075
0.05
0.1
0.075
0.05
0.05
0.1
0.075
0.075
0.075
0.05
0.075
0.075

(Min)
48
90
48
90
48
48
6
90
90
6
48
6
6
6
48
48
48
90
48
48

(g/L)
2
3.5
2
0.5
2
2
2
2
0.5
3.5
2
0.5
3.5
0.5
2
0.5
2
3.5
3.5
2

%
38.6
66.53
70.82
30.57
87.73
70.82
48.67
75.28
71.77
20.8
70.82
54.93
61.11
10.63
70.82
60.28
70.82
94.12
82.01
70.82

%
15.39
23.73
38.45
10.09
57.86
38.45
21.64
45.95
48.75
5
38.45
30.5
38.17
1.58
38.45
28.28
38.45
64.28
52.08
38.45

Percent
removalof copper ion%
24.38
34.725
55.36
18.06
68.49
55.36
35.08
60.17
52.706
10.89
55.36
42.78
50.56
4.411
55.36
43.27
55.36
76.23
67.85
55.36

Ali and Ali BMC Chemistry(2024) 18:147

Fig. 3 SEM of sodium silicate (Na2SiO3)

Fig. 4 SEM of the Carbonized Chitosan (a), Carbonized Chitosan-Fe3O4 (b) and (Carbonized Chitosan-Fe3O4-SiO2) nano-composite (c)Page 8 of 23

Ali and Ali BMC Chemistry(2024) 18:147

Page 9 of 23

Fig. 5 TEM of the synthesized (Carbonized Chitosan-Fe3O4-SiO2) nano-composite (a) at 1 nm, (b) at 200 nm and 100 nm (c)center. This showed that Fe3O4 first grew on the outermost layer of the Carbonized Chitosan (core), then SiO2
grew on the surface of Fe3O4. Agglomerations appearedin non-spherical structure due to the presence of Fe3O4
particles as shown in Fig. 5b. Figure 5c detected core/shell structure with nearly spherical shape composed ofdarker point (Carbonized Chitosan), lighter contrast of
Fe3O4 as the first shell and the lightest contrast of SiO2 as
the outer shell.
Brunauer-emmett-teller (BET)BET surface areas, and pore volume of Carbonized Chitosan, Carbonized Chitosan-Fe3O4 and the synthesizedcomposite Carbonized Chitosan-Fe3O4-SiO2 were studied using N2 adsorption (desorption) analysis as represented in Fig. 6. Carbonized Chitosan, Carbonized
Chitosan-Fe3O4 and Carbonized Chitosan-Fe3O4-SiO2
composite had BET surface areas of 30.213 m2/g, 38.734
m2/g, and 45.024 m2/g. In addition, the cumulative BJH
pore volumes were 0.235 cm3/g, 0.258 cm3/g, and 0.267
cm3/g, respectively. Based on the BET analysis, Fe3O4 and

SiO2 particles provided good contribution in increasing
the active surface area of the Carbonized Chitosan.
X-ray diffraction (XRD)

The XRD patterns of Carbonized Chitosan, Magnetite(Fe3O4), Silica (SiO2) and (Carbonized Chitosan-Fe3O4SiO2) nano-composite were presented in Fig. 7. Figure 7ashowed a broad peak at a range of 2Ɵ = 20-22.53o [29]which indicated the amorphous structure of the Carbonized Chitosan. Figure 7b represented the free magnetite
nano-particles with sharp peaks observed at 2Ɵ = 30.23°,
36.36°, 43.23°, 54.25°, 58.35° and 63.10° [30]. After coatingof Carbonized Chitosan with Fe3O4, it was observed an
extensive decrease in the peak intensity of the Carbonized Chitosan due to the high crystallinity of magnetite.
In addition, SiO2 peaks appeared in Fig. 7c at 2Ɵ = 21.8°,
35.97°, 47.67° and 48.55° [31] which ensured the deposition of SiO2 particles on the surface of Carbonized Chitosan-Fe3O4 composite.

Ali and Ali BMC Chemistry(2024) 18:147

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Fig. 6 N2 adsorption-desorption isotherm for Carbonized Chitosan (a), Carbonized Chitosan-Fe3O4 (b) and Carbonized Chitosan-Fe3O4-SiO2 composite(c)Fourier transformation infrared (FTIR)

Figure 8 represented the FTIR band of free magnetite and(Carbonized Chitosan) versus the (Carbonized Chitosan-Fe3O4-SiO2) synthesized nano-composite. The FTIR
analysis was performed under a range of wavelengths
between 400 and 4000 cm− 1. The observed peaks from458.2 cm to 1 to 640.3 cm-1 at the FTIR analysis of freemagnetite revealed to Fe-O bonds in the crystalline latticeof Fe3O4 [32]. These peaks appeared in the IR of the synthesized nano-composite (Carbonized Chitosan-Fe3O4SiO2) ensuring the precipitation of Fe3O4 particles on thesurface of the precursor (Carbonized Chitosan). In addition, the peaks at 1629.7 cm-1 and 3324.9 cm-1 revealed
to (-OH) group [32]. Regarding the IR band of the (Carbonized Chitosan), peaks at 873.32 cm-1, 711 cm-1,
608.3 cm-1, 562.8 cm-1, 1040.39 cm-1 and 1407.3 cm-1
revealed to the (C = O) and (C-H) groups. respectively,
ensuring the successful carbonization of Chitosan [33].

Peaks in the (Carbonized Chitosan-Fe3O4-SiO2) nanocomposite at 1634.69 cm-1 and 3368.42 cm-1 attributed to(-OH) group [34], these peaks appeared due to washingusing distilled water during the preparation of the nanocomposite. In addition, two new sharp peaks appearedat 449.12 cm-1 and 420.3 cm-1 revealed to the (Si-O-Fe)[35]. Moreover, new peaks appeared at 1057.01 cm-1
and 787.69 cm-1 revealed to (Si-O-Si) and (Si-O) groups,
respectively [35]. The disappearance of the IR bands at
711 cm-1, 873.32 cm-1 and 1040.39 cm-1 were due to theco-precipitation of SiO2 and Fe3O4 particles on the surface of the precursor (Carbonized Chitosan).
Figure 9 represented the FTIR band of the FTIR bandof the (Carbonized Chitosan-Fe3O4-SiO2) synthesizednano-composite (before) and (after) adsorption of a mixture of heavy metals (Co2+, Ni2+ and Cu2+) from an aqueous solution. A new peak appeared after adsorption at

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Fig. 7 XRD analysis of the Carbonized Chitosan (a), Magnetite (b), and (Carbonized Chitosan-Fe3O4-SiO2) synthesized nano-composite (c)Fig. 8 FTIR analysis of free Magnetite (a), (Carbonized-Chitosan) (b), and (Carbonized Chitosan-Fe3O4-SiO2) synthesized nano-composite (c)Ali and Ali BMC Chemistry(2024) 18:147

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Fig. 9 FTIR analysis of the (Carbonized Chitosan-Fe3O4-SiO2) synthesized nano-composite (before) (a) and (after) (b) simultaneous adsorption process

558.5 cm-1 revealed the Co2+ ion [36]. Additionally, newpeaks appeared after adsorption at 619.5 cm-1 and 463.06
attributed to the Cu2+ metal ion bounded with C-Ogroup and Ni-O stretching, respectively [33, 36]. The
decrease in the intensity of peaks at 3368.42 cm-1 and3393.01 cm-1 took place after adsorption indicating different binding between the central metal Co2+ ion andligand [37].
Zeta potential (ZP)

The difference in potential between the layer of fluid
around the surfaces and the bulk fluid containing theparticles is measured by the zeta potential in nanoparticle surfaces with oppositely charged ions. The (Carbonized Chitosan-Fe3O4-SiO2) synthetic green magnetic
nanocomposite’s isoelectric point must be determinedbecause electrostatic interactions between pollutant
loads and particle surfaces influence the adsorption ofheavy metal ions (Cu2+, Co2+, and Ni2+) [38]. According to Fig. 10, the synthesized nano-composite (Carbonized Chitosan-Fe3O4-SiO2) exhibited double isoelectric
points at pH 3 and pH 8. Double isoelectric points might
be resulted from the complex chemistry of Carbonized
Chitosan in combination with the other composite components; SiO2 and Fe3O4. Since Carbonized Chitosan and
SiO2 have theoretical isoelectric points of pH = 3.5 and3, the lower isoelectric point at pH = 3 was due to theirpresence [39]. While the higher pH = 8 was due to thepresence of Fe3O4 which had theoretical isoelectric pointof 7.9 [37].
Kinetics study

Pseudo First Order (PFO) and Pseudo Second Order(PSO) kinetics models were used during the kinetics
study of this adsorption system. This Kinetics study was
performed at different contact times and under the following experimental conditions; pH = 9, initial concentrations of heavy metal ions mixture = 0.1 M, 0.075 M
and 0.05 M, temperature = 25 oC and dosage of adsorbent = 2 g/L. As shown in Table 2, the highest R2 values
were for the PFO model which indicated that the PFO
was the best fitted model with the experimental results.
Additionally, it was observed that the values of k1 in the
PFO model with respect to cobalt, nickel and copper ionsconcentrations of 0.1 M, 0.075 M and 0.05 M were extensively higher than the values of k2 for the same metal ion
concentrations in the PSO model. Therefore, it could beconcluded that the adsorption rate of the heavy metal
ions mixture of cobalt, nickel and copper ions from aqueous solutions in the PFO model was higher than the rate
in PSO model.

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Fig. 10 Zeta Potential analysis for the synthesized nano-composite (Carbonized Chitosan-Fe3O4-SiO2)

Table 2 Results of the PFO and PSO kinetic models
Kinetic model

Initial heavy metals ion
concentration (M)Parameters

PFO

0.1

R2
k1 (min-1)
R2
k1 (min-1)
R2
k1 (min-1)
R2
k2 (mg/g.min)
R2
k2 (mg/g.min)
R2
k2 (mg/g.min)

0.075
0.05
PSO

0.1
0.075
0.05

Single-component isotherm study

Langmuir, Freundlich and Dubinin-Radushkevich isotherm models were investigated under fixed experimental conditions of dosage of adsorbent = 3.5 g/L, contact
time = 90 min, pH = 9 and at different single nickel, cobalt
and copper ions concentrations ranged from 0.05 M to
0.1 M. The adsorption mechanism of this adsorption system could be conducted through determination of thebest fitted model with the experimental results. As represented in Table 3, Freundlich isotherm model had higher
R2 values (0.9876), (0.805) and (0.9694) for nickel, cobalt
and copper ions, respectively comparing with the R2 values of Langmuir isotherm model. Based on this observation, it was concluded that each single metal ion has beenadsorbed from aqueous solutions using the synthesizedwith respect to cobalt ion with respect to nickel ion withrespect
to copper ion
0.99930.99550.9998
0.034
0.059
0.041
0.9981
0.9976
0.9982
0.032
0.036
0.039
0.99920.99970.9957
0.041
0.065
0.046
0.11780.9896
0.9974
8.67E-06
1.72E-05
2.93E-05
0.9944
0.9986
0.99850.00008
0.000120.00011
0.99780.99980.99970.00010.000140.00015

nano-composite (Carbonized Chitosan-Fe3O4-SiO2)
based on a multilayer adsorption mechanism. Additionally, Table 3 illustrated that the synthesized new nanocomposite had a high adsorption capacity (qmax) for the
mixture of heavy metal ions of 2000 mg/g, 1666.67 mg/g
and 2000 mg/g for nickel, cobalt and copper ions,
respectively.
Multiple-component isotherm study

Table 4 demonstrated that, in the Modified Langmuir
isotherm model, the bonding strength between the ionsand the synthesized nano-composite was in the following
order: Co2+ > Ni2+ > Cu2+ as the values of KL for cobalt
ion = 304.2 (L/mg) > KL value of nickel ion = 117.3 (L/mg) > KL value of copper ion = 78.4 (L/mg). In addition,

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Table 3 Isotherm parameters of single nickel, cobalt and copper
ions
Isotherm
modelsLangmuirParameters

NickelCobaltCopperR2
qmax (mg/g)
KL (L/mg)
RL (Separation
factor)Freundlich R2
1/nn
KF (L/mg)
Dubinin-Ra- B (mol2/kJ2)
dushkevich E (kJ/mol)

0.98762000
0.0001
0.571

0.805
1666.67
0.00960.017

0.96942000
0.00620.025

0.98831.302
0.768
28.347361,9840.001 < 8 kJ/
mol1289.50.89240.371
2.67
139.15795.020.025 < 8 kJ/
mol1299.20.98680.376
2.657
140.671543.20.018 < 8 kJ/
mol1484.6qmax (mg/g)

it was worthy to observe that the maximum adsorption
capacity (qmax) = 2908.92 mg/g in case of multiple-component system was less than the summation of qmax foreach metal ion = 4761.91 mg/g. The reason may be dueto the occurrence of various binding sites on the surface of the prepared nano-composite, each with varying
degrees of specificity toward the individual cobalt, nickel,
and copper ions, or to the partial overlying of adsorption active sites for cobalt, nickel, and copper ions in
the tertiary system. Additionally, it was evident that the
Extended Freundlich isotherm model’s values for the
Marquardt’s Standard Deviation (MPSD) of the cobalt,
nickel, and copper ions were lower than those of the
Modified Langmuir isotherm model. Thus, The Extended
Freundlich isotherm model was the best matched modelwith the experimental data indicating that the adsorption
mechanism was a multi-layer adsorption for this system.
Regression model equations development

Quadratic model was the best-fitted model with theexperimental results. It has been conducted using the
Design Expert software program, USA (Version 13). The
effects of three experimental factors were investigatedincluding, the initial nickel, cobalt and copper ions concentrations (molar) (M), contact time (min) and dosage of adsorbent (g/L). Three responses were detected

experimentally including; the nickel, cobalt and copper
ions adsorption percents.
The quadratic model of the elimination percent
of nickel ions after removal of insignificant terms toincrease the model’s accuracy could be described in thefollowing Eq. (19):Y1 =+ 71.31 − 20.25 A + 14.21 B + 9.64 C
(19)
2
2
+ 2.2 AC + 5.25 BC − 8.87 A − 10.06 C
The quadratic model for the removal percent of cobalt
ions after removal of insignificant terms could be
described in the following Eq. (20):
Y2 = +39.31 − 18.38 A + 9.59 B + 6.41 C − 6.81 B 2
(20)The quadratic model for copper ion removal percent
after removal of insignificant terms could be described in
the following Eq. (21):Y3 =+ 55.74 − 19.83 A + 9.82 B+
(21)
2
2
7.90 C + 3.24 BC − 9.87 A − 8.68 B
Where Y1, Y2 and Y3 represented the nickel ion, cobalt
ion and copper ion adsorption percentages, respectively.
A, B and C are the initial nickel, cobalt and copper ionsconcentrations (molar), contact time (min) and dosage ofadsorbent (g/L), respectively.
Nickel ion adsorption model – effect of process variables

A) Effect of initial (Co2+, Ni2+ and Cu2+) ions concentration The initial (Co2+, Ni2+, and Cu2+) ion concentration’s coefficient in the regression Eq. (19) denoted aninverse relationship with the nickel ion adsorption percent. This was brought on by the fact that as the concentration of (Co2+, Ni2+, and Cu2+) ions raised, there werefewer active sites on the adsorbent. Figure 11 depictedthat the adsorption percent of nickel ions decreased from80 to 20% as the initial concentration of the heavy metal
ions increased from 0.05 M to 0.098 M at various contact

Table 4 Tertiary isotherm parameters of the multiple component models
Isotherm models
Extended Freundlich

Modified Langmuir

Parameters
Nickel ion adsorption
Cobalt ion adsorption
Copper ion adsorption
Parameters
Nickel ion adsorption
Cobalt ion adsorption
Copper ion adsorption

x1
3.07
2.67
2.83
Η
0.00074
0.007280.00139

y1
-0.78
-0.91
-0.87
KL (L/mg)
117.3
304.2
78.4

z1
3.03
2.65
2.81
qmax (mg/g)
800.04
1548.73
560.15

n
3.066
2.67
2.86
MPSD
0.17940.84990.9889KF (L/mg)
159.11111.92164.58MPSD
0.19490.17150.1956

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Fig. 11 Contour plot of initial metal ions concentration and contact time versus the removal percent of the nickel iontime levels and under the specified experimental conditions of pH = 9, dosage of adsorbent = 2 g/L.
B) Effect of the dosage of adsorbent Dosage of adsorbent and nickel ion adsorption percents were directly
proportional, according to the regression Eq. (19). Adsorbent specific surface area increased along with an increasein adsorbent dosage, increasing the amount of available
active sites for nickel ion adsorption. Figure 12 depictedthat an increase in the dosage of adsorbent from 0.5 to
3.5 g/L had a favourable impact on the nickel ion removal
percent as it climbed from 50 to 80% at various contact
times and under these specified experimental conditions;
pH = 9, initial (Co2+, Ni2+ and Cu2+) ions concentration = 0.075 M.
Cobalt ion adsorption model – effect of process variables
A) Effect of initial (Co2+, Ni2+ and Cu2+) ions concentration

The coefficient of the initial (Co2+, Ni2+ and Cu2+) ionsconcentration in the regression Eq. (20) indicated that
there was an inverse proportionality between it and thecobalt ion adsorption percent. This was due to the reduction in active locations on the adsorbent as the (Co2+,
Ni2+ and Cu2+) ions concentration increased. According

to Fig. 13, cobalt ion adsorption percent decreased from50 to 10% with a rise in the initial concentration of (Co2+,
Ni2+ and Cu2+) ions from 0.05 M to 0.092 M at various
levels of contact times and under specified experimental
conditions; pH = 9 and dosage of adsorbent = 2 g/L.
B) effect of the dosage of adsorbent

Referring to the regression Eq. (20), the dosage of adsorbent and the cobalt ion adsorption percent were directly
proportional. The exact surface area of the adsorbent
increased as the dosage of the adsorbent increased simultaneously, which caused a peak in the availability ofactive locations for cobalt ion adsorption. The high significant effect of the dosage of adsorbent on the cobalt
ion removal percent illustrated in Fig. 14. As an increasein the dosage of adsorbent from 0.5 g/L to 3.5 g/L had
a positive effect on the Co2+ ion removal percent as itincreased from 20 to 50% at various stages of contact
times and under specified experimental conditions;
pH = 9, initial metal ions concentration = 0.075 M.
Copper ion adsorption model – effect of process variables
A) Effect of initial (Co2+, Ni2+ and Cu2+) ions concentration

In the regression Eq. (21), the initial heavy metal ionsconcentration had a negative sign. This coefficient of

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Fig. 12 Contour plot of dosage of adsorbent and contact time versus the removal percent of the nickel ion

the initial metal ions concentration in the regression
Eq. (21) indicated that there was an inverse proportionality between it and the copper ion adsorption percent.
This was due to the decrease in active sites on the adsorbent as the (Co2+, Ni2+ and Cu2+) ions concentration
increased. According to Fig. 15, copper ion adsorption
percent decreased from 60 to 10% with a rise in the initialconcentration of (Co2+, Ni2+ and Cu2+) ions from 0.05 M
to 0.098 M at different levels of contact time and under
specified experimental conditions: pH = 9 and dosage ofadsorbent = 2 g/L.
B) Effect of the dosage of adsorbent

Based on the regression Eq. (21), the dosage of adsorbent
and the copper ion adsorption percent were directly proportional. When the dosage of adsorbent increased, thespecific surface area of the adsorbent increased simultaneously which led to an increase in the availability ofactive sites for copper ion adsorption. The highly significant effect of the dosage of adsorbent on the copper
ion removal percent illustrated in Fig. 16. As an increasein the dosage of adsorbent from 0.5 g/L to 3.5 g/L had
a positive effect on the Cu2+ ion removal percent as itincreased from 40 to 60% at different levels of contact
time and under these fixed experimental conditions;
pH = 9, initial heavy metal ions concentration = 0.075 M.

Optimization
Numerical optimization was performed to reach the optimum conditions at which the maximum removal percents of Ni2+, Co2+, and Cu2+ metal ions were achieved
using Design Expert software. The optimization goals
were chosen to reach the maximum removal percents of
Ni2+, Co2+, and Cu2+ ions as represented in Table 5.
Figure 17 a, b and c represented the maximum removal
percents of Ni2+, Co2+, and Cu2+ metal ions were 88.99%,
61.72% and 70.56%, respectively. These values wereachieved at specified experimental conditions of pH = 9,
initial (Co2+, Ni2+ and Cu2+) ions concentration = 0.05 M,
dosage of adsorbent = 2.5 g/L, contact time = 90 min andtemperature = 25 oC.

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Fig. 13 Contour plot for initial (Co2+, Ni2+ and Cu2+) ions concentration and contact time versus the cobalt ion removal percent

Desorption and regeneration of the spent(Carbonized Chitosan-Fe3O4-SiO2) nano-composite
For desorption of heavy metal ions from wastewater or
aqueous solutions, Ethylene Diamine Tetra Acetic Acid
(EDTA) solutions or acids such as Nitric acid (HNO3) orHydrochloric acid (HCl) could be used [40]. Five samplesof (Carbonized Chitosan-Fe3O4-SiO2) each with 0.1 g
were added in conical flasks with 80 mL of 0.05 M ofheavy metal ion mixture (Ni2+, Co2+, and Cu2+) at pH = 9.
These conical flasks were shaken vigorously at 200 rpm
for 90 min at 25 oC followed by filtration of the composite, washing with double distilled water then drying at
40 oC for 7 h. 1 M of the desorption solution HNO3 wasadded to each dried composite after adsorption in conical flasks which were shaken at 200 rpm for 10 min at 25o
C followed by composite filtration, washing with deionized water and drying. the following Eq. (22) was used toevaluate the desorption efficiency [40]:Cdesorption
Desorption efficiency (ηdes) =× 100
Cadsorption
(22)Cadsorption represents the equilibrium concentrationof heavy metal ions on the surface of adsorbent andCdesorption represents the concentration of heavy metal
ions in the desorption solution.
The five samples of (Carbonized Chitosan-Fe3O4-SiO2)
composite from adsorption were firstly washed with deionized water then dried in an oven for 40 oC for 4 h. The
dried composite samples with dosage of (2.5 g/L) wereadded to heavy metal ions solution with concentration of
0.05 M, pH = 9, temp = 25 oC, and contact time = 90 min.
Five cycles of (Carbonized Chitosan-Fe3O4-SiO2) reusability were conducted using the same experimental conditions mentioned above. The reusability efficiency foreach cycle was determined using the following Eq. (23)[40]:

Reusability efficiency =CadsorptionCo× 100 (23)Cadsorption represents the equilibrium concentration ofheavy metal ions on the surface of adsorbent and Co represents the initial concentration of heavy metal ions inthe synthetic aqueous solution.

Ali and Ali BMC Chemistry(2024) 18:147

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Fig. 14 Contour plot for dosage of adsorbent and contact time versus the removal percent of cobalt ion

All metal ions studied were successfully desorbed at100% efficiency. According to these results, it was possible to recover and reuse the (Carbonized ChitosanFe3O4-SiO2) synthesized nano-adsorbent without losing
its adsorption capacity, as well as the metal ions. Using
the (Carbonized Chitosan-Fe3O4-SiO2) adsorbent, thepotential of recovering metal ions (Co2+, Cu2+, and Ni2+)
as well as the adsorbent, would certainly improve theeconomic feasibility of the adsorption process.

Adsorption of Co2+, Cu2+, and Ni2+ using thesynthesized nano-composite versus different
adsorbents
The results of the present study were compared with theresults of similar studies in terms of absorption capacity,
operating conditions and adsorbent regeneration. Table 6
displayed a variety of adsorbent materials that were previously documented for their ability to eliminate Co2+,
Cu2+, and Ni2+ from aqueous solutions in batch mode. As

represented in Table 6, the prepared (Carbonized Chitosan-Fe3O4-SiO2) nano-composite could be considered as
one of the most efficient adsorbents recently synthesized
for the purpose of adsorbing Co2+, Cu2+, and Ni2+, whencompared to other previously reported adsorbents.

Future work
Scale-up and commercialization: Once the process has
been optimized, there is potential for scale-up and commercialization of the technology. This will involve working with industry partners to develop large-scale systems
for removal of a mixture of heavy metal ions from wastewater using green magnetic nano-composite (Carbonized Chitosan-Fe3O4-SiO2).
Environmental impact assessment: the environmental impact of this process will be explored including theenergy required for it and the potential for waste disposal
issues. This will help to ensure that the process is sustainable and environmentally friendly.

Ali and Ali BMC Chemistry(2024) 18:147

Fig. 15 Contour plot of initial metal ions concentration and contact time versus the copper ion removal percent

Page 19 of 23

Ali and Ali BMC Chemistry(2024) 18:147

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Fig. 16 Contour plot of dosage of adsorbent and contact time versus the copper ion removal percent

Table 5 Optimization constraints
FactorInitial concentration of
the heavy metal ions mixture (M)Contact time (min)Dosage of adsorbent (g/L)% Nickel ion removal% Cobalt ion removal% Copper ion removal

Goal
Minimize

Lower limit
0.05

Upper limit
0.1

Value
---

Maximize
TargetMaximize
Maximize
Maximize

6
0.5
10.63
1.58
4.41

90
3.5
94.12
64.28
76.23

--2.5
-------

Ali and Ali BMC Chemistry(2024) 18:147

Fig. 17 Maximum removal percents of nickel (a), cobalt (b) and copper (c) metal ions from aqueous solutions

Page 21 of 23

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Table 6 Comparison of adsorption capacity for the removal of Co2+, Cu2+, and Ni2+ metal ions by different adsorbents
Adsorbent

pH

Contact
time

Initial Conc.
(Molar)Chitosan/clinoptilolite

5

24 h

Chitosan/methacrylic acid nanoparticles
Carboxylate-functionalized sugarcane bagasse (SPA)
Poly[N-(4-[4-(amino phenyl) methyl phenyl methacrylamide])](PAMMAm)
Hazelnut husks carbon activated with phosphoric acid (HHPAAC)
Carbonized Chitosan-Fe3O4-SiO2

6
5.5–5.75
5.5-6

5h
3h
30 min0.07 for eachmetal ion
0.01 each
0.05 each
0.017 each

6
9

24 h
90 min0.06 each
0.1 each

Conclusions
A new green magnetic nano-composite (Carbonized Chitosan-Fe3O4-SiO2) was synthesized using co-precipitation method. Surface characterization of the synthesizednano-composite was performed including SEM, TEM,
BET, XRD, FTIR, and ZP and, to ensure that the preparation of the new green nano-composite was achieved
successfully. The kinetics models of this adsorption system were studied where the best fitted model with theexperimental results was Pseudo First Order (PFO)model. Dubinin-Radushkevich was studied for singlecomponent adsorption system indicated that the type ofadsorption was physical adsorption. Extended Freundlich
multiple-component isotherm was the best-fitted model
indicating that the adsorption mechanism was a multilayer adsorption for this system. Regarding the multiplecomponent system, the maximum adsorption capacityof Ni2+, Co2+ and Cu2+ were 800.04 mg/g, 1548.73 mg/g
and 560.15 mg/g, respectively. In this study, a wide rangeof experimental parameters were investigated, including
the initial concentrations of the heavy metals mixture ofnickel, cobalt and copper ions (0.05, 0.075, and 0.1 M),
the contact time (6, 48, and 90 min), as well as the dosageof adsorbent (0.5, 2, and 3.5 g/L) to assess their impact
on the adsorption percents of the heavy metals mixtureof nickel, cobalt and copper ions. The optimum adsorption percents of nickel, cobalt and copper ions of 88.99%,
61.72%, and 70.56%, respectively were achieved at specified experimental conditions of pH = 9, initial (Co2+, Ni2+
and Cu2+) ions concentration = 0.05 M, dosage of adsorbent = 2.5 g/L, and contact time = 90 min.
Author contributions
All authors contributed to the study conception. Material preparation, datacollection, software, characterization, analysis and supervision were performed
by Dr. Dalia Amer Ali. Material preparation, data collection and analysis were
performed by Eng. Rinad Galal Ali. The first draft of the manuscript was written
by Dr. Dalia Amer Ali and all authors commented on previous versions of themanuscript. All authors read and approved the final manuscript.
Funding
The authors have not disclosed any funding.

Maximum adsorption
capacity (qmax) (mg/g)
Ni2+
Co2+
Cu2+
247.03467.90 719.3

Temp
(oC)

Ref.

25

[41]

340
54.7
110.92220
33.04
108.96

195
59.42
66.09

20
25
25

[2]
[1]
[42]

16.3
800.0417.3
1548.7

24.3
78.4

25
25

[43]
This
study

Open access funding provided by The Science, Technology & Innovation
Funding Authority (STDF) in cooperation with The Egyptian Knowledge Bank
(EKB).
Data availability
The data used to support this study’s findings are available from thecorresponding author upon request.

Declarations
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Received: 18 January 2024 / Accepted: 25 July 2024

References
1. Ramos SN, do C, Xavier ALP, Teodoro FS, Gil LF, Gurgel LVA. Removal of
cobalt(II), copper(II), and nickel(II) ions from aqueous solutions usingphthalate-functionalized sugarcane bagasse: Mono- and multicomponent
adsorption in batch mode. Ind Crops Prod. 2016;79:116–30.
2. Qasem NAA, Mohammed RH, Lawal DU. Removal of heavy metal ions fromwastewater: a comprehensive and critical review. npj Clean Water 4, (2021).
3. Zhang P et al. Water Quality Degradation Due to Heavy Metal Contamination:
Health Impacts and Eco-Friendly Approaches for Heavy Metal Remediation.
Toxics 11, (2023).
4. Stevens M, Batlokwa B. Removal of Nickel (II) and cobalt (II) from Wastewater using vinegar-treated Eggshell Waste Biomass. J Water Resour Prot.
2017;09:931–44.
5. Prochaska C, Gallios G. NANO-adsorbents for cobalt removal fromwastewater:
A Bibliometric analysis of research articles indexed in the Scopus database.
Processes 9, (2021).
6. Goodman TM. International standards for colour. Colour Des Theor Appl Second Ed. 2012;417–52. https://doi.org/10.1016/B978-0-08-101270-3.00018-7.
7. CUMINGS JN. Biochemical Aspects. Proceedings of the Royal Society of Medicine
vol. 55 (1962).
8. Ramsden JJ. What is nanotechnology? Nanotechnol Perceptions.
2005;1:3–17.
9. Dehkharghani FM et al. Nano Micro Biosystems advances and challenges.
(2023).
10. Suzaimi ND, Goh PS, Malek NA. N. N. Modified-Nano-Adsorbents for Nitrateefficient removal: a review. J Appl Membr Sci Technol. 2019;23:65–81.
11. Nnaji ND, Onyeaka H, Miri T, Ugwa C. Bioaccumulation for heavy metal
removal: a review. SN Appl Sci 5, (2023).

Ali and Ali BMC Chemistry(2024) 18:147

12. Zabochnicka-Światek M, Krzywonos M. Potentials of biosorption andbioaccumulation processes for heavy metal removal. Pol J Environ Stud.
2014;23:551–61.
13. Raji Z, Karim A, Karam A, Khalloufi S. Adsorption of Heavy metals: mechanisms, kinetics, and applications of various adsorbents in Wastewater
Remediation—A Review. Waste. 2023;1:775–805.
14. Soffian MS, et al. Carbon-based material derived from biomass waste forwastewater treatment. Environ Adv. 2022;9:100259.
15. El-sayed ME. A. Nanoadsorbents for water and wastewater remediation. Sci
Total Environ. 2020;739:139903.
16. Costa HP, de Silva S, M. G. C., Vieira MG. A. Biosorption of aluminum ions from
aqueous solutions using non-conventional low-cost materials: a review. J
Water Process Eng. 2021;40:101925.
17. Batool F, Akbar J, Iqbal S, Noreen S, Bukhari SNA. Study of Isothermal, Kinetic,
and Thermodynamic Parameters for Adsorption of Cadmium: An Overview ofLinear and Nonlinear Approach and Error Analysis. Bioinorg. Chem. Appl 2018,(2018).
18. Worku Z, et al. Adsorption of chromium from electroplating wastewater using activated carbon developed from water hyacinth. BMC Chem.
2023;17:1–17.
19. Salama E, et al. The superior performance of silica gel supported nano zerovalent iron for simultaneous removal of cr (VI). Sci Rep. 2022;12:1–19.
20. Yakout SM, Elsherif E. Batch kinetics, isotherm and thermodynamic studiesof adsorption of strontium from aqueous solutions onto low cost rice-straw
based carbons. Carbon - Sci Technol. 2010;3:144–53.
21. William Kajjumba G, Emik S, Öngen A, Kurtulus Özcan H, Aydın S. Modellingof Adsorption kinetic Processes—Errors, theory and application. Adv Sorption
Process Appl. 2019. https://doi.org/10.5772/intechopen.80495.
22. Saadi R, Saadi Z, Fazaeli R, Fard NE. Monolayer and multilayer adsorption
isotherm models for sorption from aqueous media. Korean J Chem Eng.
2015;32:787–99.
23. Girish CR. Various isotherm models for multicomponent adsorption: a review.
Int J Civ Eng Technol. 2017;8:80–6.
24. Sahu O, Singh N. Significance of Bioadsorption Process on Textile Industry
Wastewater. The impact and prospects of Green Chemistry for Textile Technology.
Elsevier Ltd.; 2018. https://doi.org/10.1016/B978-0-08-102491-1.00013-7.
25. Hami HK, Abbas RF, Mahdi AS, Maryoosh AA. An overview of using error function in Adsorption Isotherm modeling. Muthanna J Pure Sci. 2020;8:22–30.
26. Chindaprasirt P, Rattanasak U. Eco-production of silica from sugarcane
bagasse ash for use as a photochromic pigment filler. Sci Rep. 2020;10:1–9.
27. Hsu CY, et al. A chemometric approach based on response surface methodology for optimization of antibiotic and organic dyes removal from water
samples. BMC Chem. 2024;18:1–15.
28. Asghar A, Raman AAA, Daud WM. A. W. A Comparison of Central Composite
Design and Taguchi Method for Optimizing Fenton Process. Sci. World J 2014,(2014).
29. Park KH et al. Hierarchically Porous Carbon Networks Derived from Chitosan
for High-Performance Electrochemical Double-Layer Capacitors. Nanomaterials 13, (2023).

Page 23 of 23

30. Bordbar AK et al. Characterization of Modified Magnetite Nanoparticles forAlbumin Immobilization. Biotechnol. Res. Int 2014, 1–6 (2014).
31. Joni IM, Nulhakim L, Vanitha M, Panatarani C. Characteristics of crystalline
silica (SiO2) particles prepared by simple solution method using sodium
silicate (Na2SiO3) precursor. J Phys Conf Ser 1080, (2018).
32. Nalbandian L, et al. Magnetic nanoparticles in medical diagnostic applications: synthesis, characterization and proteins conjugation. Curr Nanosci.
2015;12:455–68.
33. Stuart BH. Infrared spectroscopy: fundamentals and Applications. Infrared
Spectroscopy: Fundamentals Appl 8 (2005).
34. Nurul Ulya H, Taufiq A. Sunaryono. Comparative Structural properties ofNanosized ZnO/Fe3O4 composites prepared by Sonochemical and Sol-Gel
methods. IOP Conf Ser Earth Environ Sci. 2019;276:2–11.
35. Tran TN, Pham TVA, Le MLP, Nguyen TPT, Tran VM. Synthesis of amorphoussilica and sulfonic acid functionalized silica used as reinforced phase for polymer electrolyte membrane. Adv Nat Sci Nanosci Nanotechnol. 2013;4:3–9.
36. Eslam AA, Aboelazm, Gomaa AM, Ali KFC. Cobalt oxide Supercapacitor
Electrode recovered from spent Lithium-ion battery. Chem Adv Mater.
2018;3:67–74.
37. Mitić Ž, Cakić M, Nikolić G. Fourier-transform IR spectroscopic investigationsof cobalt(II)-dextran complexes by using D2O isotopic exchange. Spectroscopy. 2010;24:269–75.
38. Khoshnevisan K, Barkhi M. Zeta potential Electrochemical sensing of the biomarker serotonin view project Nanomedicine Research Journal View project.
(2015) https://doi.org/10.13140/RG.2.1.4554.3844
39. Antonio Alves Júnior J, Baptista Baldo J. The behavior of Zeta Potential of
Silica Suspensions. New J Glas Ceram. 2014;04:29–37.
40. Martínez ME, et al. Removal of Heavy Metal ions from Wastewater with Polyε-Caprolactone-Reinforced Chitosan Composite. Polym (Basel). 2022;14:1–23.
41. Dinu MV, Dragan ES. Evaluation of Cu2+, Co2 + and Ni2 + ions removal from
aqueous solution using a novel chitosan/clinoptilolite composite: kinetics
and isotherms. Chem Eng J. 2010;160:157–63.
42. Kushwaha AK, Gupta N, Chattopadhyaya MC. Dynamics of adsorptionof Ni(II), Co(II) and Cu(II) from aqueous solution onto newly synthesizedpoly[N-(4-[4-(aminophenyl)methylphenylmethacrylamide])]. Arab J Chem.
2017;10:S1645–53.
43. Usanmaz S, Özer Ç, İmamoğlu M. Removal of Cu(II), ni(II) and Co(II) ions from
aqueous solutions by hazelnut husks carbon activated with phosphoric acid.
Desalin Water Treat. 2021;227:300–8.

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