South African Journal of Chemical Engineering 39 (2022) 32–41
Available online 14 November 2021
1026-9185/© 2021 Published by Elsevier B.V. on behalf of Institution of Chemical Engineers. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/).
Full length article
The development of a novel FM nanoadsorbent for heavy metal remediation in polluted water
Khairiah Khairiah
a,b,*, Erna Frida
a,*, Kerista Sebayang
a, Perdinan Sinuhaji
a, Syahrul Humaidi
a, Ahmad Fudholi
caDepartment of Physics, FMIPA, Universitas Sumatera Utara, Jl. Bioteknologi I Kampus USU, Medan, 20155, Indonesia
bUniversitas Muslim Nusantara Al Washliyah, Jl. Garu II A No. 93, Medan Amplas, Kota Medan, Indonesia
cSolar Energy Research Institute, Universiti Kebangsaan Malaysia, 43600, Selangor, Malaysia
A R T I C L E I N F O Keywords:
Nanoadsorbent Fe3O4 magnetic Heavy metal Remediation Polluted water
A B S T R A C T
Heavy metal pollution in the environment is a severe issue. Heavy metals directly impact people’s lives since they accumulate in the food chain, even in low amounts. Some heavy metals were found to have polluted the water, exceeding the dangerous limits for life. A nanoadsorbent is needed to remediate heavy metals. Fe3O4 magnetic nanoadsorbent has been synthesized without and with additional materials using a combination method of coprecipitation and milling, namely Fe3O4 Magnetic (FM), Fe3O4 Magnetic/Activated Carbon (FMAC), Fe3O4 Magnetic/Chitosan (FMCH), and Fe3O4 Magnetic/Glutaraldehyde (FMG). According to the AAS characterization results, the adsorption percentage of FM nanoadsorbent without additives was higher than that of other materials with additives. Structural characterization showed the crystal size of Fe3O4 magnetic without additives with a range of 11 nm. The surface morphology characterization showed no aggregation, and the maximum percentage of Fe3O4 magnetic purity without additional material was 89.26%.% Adsorption is affected by contact time, stirring speed, and the pH of the solution. Optimum% adsorption occurred at a contact time of 120 min, a stirring speed of 200 rpm, and a solution pH of 7 (neutral) 99.27%. The novelty Fe3O4 magnetic nanoadsorbent without additional material is more effective in remediating polluted water.
1. Introduction
Heavy metal pollution in the environment is a severe issue. Heavy metals directly impact people’s lives since they accumulate in the food chain, even in low amounts (Joseph et al., 2019; Kyzas and Matis, 2015;
Nassar, 2010). Several heavy metals have been discovered in water, above the toxic level. Fe, Pb, Cd, Cr, Ni, Zn, Hg, Mn, and Cu are heavy metals that damage water. Mining is the most significant source of heavy metals, with 65% utilized to make batteries, plastic stabilizers, coal combustion, and anti-corrosion metal coatings (Gruber and Carsky, 2020; Manyangadze et al., 2020).
Furthermore, magnetic technology is frequently employed, with one application being a new technology for delivering rare earth elements.
(El-sayed, 2020; Okoli et al., 2018) These heavy metals contribute to various disorders, including prostate cancer, pancreatic cancer, and lung cancer (Khalil et al., 2017; Tamjidi and Esmaeili, 2019). Especially now, Indonesia and the world are facing COVID 19, a type of lung virus. As a result, humans must adopt a healthy lifestyle. The water used must also
be pure and wholesome to maintain the body’s immunity and avoid infection. Many strategies for removing heavy metal complexes from the aquatic environment have been developed in recent decades (Khan et al., 2013; Nazarzadeh et al., 2018). Ion exchange, reverse osmosis, membrane-based filtering for complicated precipitation, electro- coagulation, precipitation, and adsorption are only a few of the methods (Li et al., 2020). One of the reported separation membrane methods to date, with excellent polymer affinity and unusual physicochemical properties. Metal-organic frameworks (MOFs) exhibit ultra-high surface area, regular and highly regulated porosity (Yu et al., 2021). Adsorption, in general, is a more straightforward method with good efficacy, is ecologically benign, affordable, and simple to run when compared to other methods (Saikia et al., 2017; Tahoon et al., 2020).
Various types of adsorbents for physical and chemical adsorption of heavy metal ion compounds have been developed, such as clay, inor- ganic polymers, zeolites, activated carbon, and magnetic. In recent years, zeolitic imidazolate frameworks (ZIFs) with a large specific sur- face area, excellent pore structure, and numerous surface functional
* Corresponding authors.
E-mail addresses: [email protected] (K. Khairiah), [email protected] (E. Frida).
Contents lists available at ScienceDirect
South African Journal of Chemical Engineering
journal homepage: www.elsevier.com/locate/sajce
https://doi.org/10.1016/j.sajce.2021.11.006
Received 25 July 2021; Received in revised form 17 October 2021; Accepted 9 November 2021
groups have shown tremendous promise in the removal of heavy metal ions/radionuclides (Katende et al., 2019; Y. Liu et al., 2021). Batch ex- periments, spectral analysis, and the Langmuir isotherms model were used to investigate the detailed interaction processes on ZIF, which demonstrated a decreasing tendency to remove metal ions and organic ligands on uranium (Y. Liu et al., 2021). BC (biochar) has shown high potential to remove water contaminants, wide availability of raw ma- terials, high surface area, expanded pore structure, and low cost. How- ever, the use of BC for water remediation has many limitations (Liang et al., 2021). The use of biochar and biochar-supported materials, particularly biochar-supported NZVI or iron oxides, for heavy metal ion/radionuclide sorption (Hu et al., 2020). This study discusses mag- netic materials. According to one of the magnetic materials, NZVI is quickly accumulated and oxidized, limiting its ability to remove con- taminants (Tang et al., 2021). Besides biochar, some COFs would be used to remove toxic heavy metals, radionuclides, and organic pollut- ants (X. Liu et al., 2021). Efforts to find new low-cost materials magnetic with nanotechnology have been developed to purify water contami- nated with hazardous metals.
Magnetic materials with nano sizes are distinctive due to their small size, unique features, large surface area, high adsorption capacity, increased catalytic activity, high dispersion rate, superparamagnetic ability, and ease of separation. This has attracted scientists to study the magnetic evolution of Fe3O4 and investigate its potential to be used as a nanoadsorbent to recover water polluted by heavy metals (Agnieszka, 2020; Das et al., 2020; X. Liu et al., 2021). Fe3O4 magnets have an essential role in the chemistry and physics of materials. Not many sci- entists have investigated Fe3O4 magnetic nanoadsorbents (Matome et al., 2020; Sarwar et al., 2021; Shen et al., 2009; Vahdat et al., 2020).
Most researchers investigating Fe3O4 magnetic nanoadsorbents include titanium oxide, activated carbon, silica, hydroxyapatite, and chitosan (Gutierrez et al., 2017; Koesnarpadi et al., 2015; Yuvaraja and Venkata, 2016). There is a weakness in the material formed, namely the frequent occurrence of aggregation, resulting in material instability in the adsorption of heavy metals in wastewater (Ahmad et al., 2019; Bayu et al., 2020; Dave and Chopda, 2014). This is reinforced by the adsorption study of four heavy metals, which showed that the adsorp- tion of Mn was not maximal, and only Pb was maximal. Another study found that it has an absorbing capacity of 65.52% (Ajinkya et al., 2020;
Feng et al., 2021; Tu et al., 2017). It is suspected that the Fe3O4 nano- adsorbent should not be added with additives because this nano- adsorbent has an excellent performance when standing alone. Its superparamagnetic properties allow it to bind to heavy metals opti- mally. It is thought that by adding more materials, the super- paramagnetic properties are lowered due to the formation of bonds with other compounds, which require a lot of energy, limiting the optimiza- tion and stability of heavy metal adsorption (Abbasi, 2017; Singh and Bahadur, 2019; Tu et al., 2017).
In this study, four magnetic materials will be synthesized and char- acterized: magnetic Fe3O4 without addition (FM), magnetic Fe3O4 with activated carbon additive (FMAC), magnetic Fe3O4 with chitosan addi- tive (FMCH), and magnetic Fe3O4 with glutaraldehyde additive (FMG).
The novelty of Fe3O4 nanoadsorbent without additions is produced in a variety of heterogeneous nano sizes, allowing it to be used for the adsorption of numerous heavy metals that are hazardous to the envi- ronment (Agnieszka, 2020; Chen et al., 2017; Li et al., 2016). The method used to produce Fe3O4 Fe3O4 magnetic nanoadsorbent is a combination method between coprecipitation and milling processes formed by concentrations of FAS (ammonium iron sulfate) III and FAS (ammonium iron sulfate) II compounds. It varies to produce suitable surface modifications and heterogeneous particle sizes to recover water polluted by various heavy metals such as Mn, Fe, Pb, and Zn (Jiang et al., 2018).
2. Experimental procedure 2.1. Materials and synthesis
The materials used in this research are FAS II (ammonium iron sul- fate II), FAS III (ammonium iron sulfate III), NH4OH solution, activated carbon, chitosan, and glutaraldehyde with Merck manufacturer from CV. Amor Chemical Indonesia. In addition, another material is equated.
The method in this study is the coprecipitation method and the milling process with HEM (High Energy Milling). A comparison of FAS (III) and FAS (II) was made at a ratio of 3:1. First, 8.97 g of FAS (III) was weighed, and 3.18 g of FAS (II) was mixed and dissolved in 150 mL of distilled water until dissolved (Ku et al., 2020; Moussa, 2013; Tamjidi and Esmaeili, 2019). Then they stirred and added excess 2 M NH4OH solu- tion (pH >7) little by little, and the reaction continued until it reached pH 9. At the same time, heated and stirred using a water bath shaker (Ahmad et al., 2019; Alizadeh et al., 2020; Thabede et al., 2021). The temperature used is 70 ◦C for 30 min.
The solution was allowed to stand, and a magnetic precipitate (Fe3O4) was formed, then rinsed using distilled water until the pH was neutral according to the pH of the distilled water used. Dried in a desiccator for 24 h and filtered using filter paper (Amin et al., 2014;
Chibowski, 2018). After that, the dry Fe3O4 magnetic powder was put into the HEM for 12 h to get a fine powder. Four different adsorbent samples were made for the study, namely FM, FMAC, FMCH, and FMG.
All can get a comparison and the same treatment. Fig. 1.1 2.2. Adsorption study
The adsorption study was carried out by first checking the polluted water using AAS. Mn, Fe, Pb, and Zn initial concentrations were 1.248, 1.421, 0.17, and 18.513 mg/L. These results indicate that the water contains several harmful heavy metals exceeding the standard limits for clean water quality. The effectiveness of heavy metals was studied by varying the experimental conditions, namely temperature, stirring speed, and contact time. For the pH conditions, the solution was made neutral (pH 7), and the mass of the adsorbent sample was 2 g each.
(Basuki et al., 2021) The following equation calculates the percentage of heavy metal removal:
%Adsorption=Co− Ce
Co
×100%
With
Fig. 1.1.Fe3O4 magnetic nanoadsorbent formation.
Fig. 2.1. Adsorption process.
co : Initial Concentration (mg/l) ce : Final Concentration (mg/l) Fig. 2.1
2.3. Effect of variations in contact time, stirring speed, and pH
Contact time is a significant variable in removing pollutants from polluted water. The development of contact time was studied by varying from 30, 60, 90, 120, and 150 min. The result of stirring speed was analyzed by running it from 50, 100, 150, 200, and 250 rpm. The effect of pH was studied by varying from 4, 5, 6, 7, and 8 with constant experimental conditions.
2.4. Adsorption kinetics modeling
One of the isothermic adsorption models is Langmuir. Langmuir described a certain number of active sites proportional to the surface area on the surface of the adsorbent. The bond between the adsorbed substance and the adsorbent can occur physically or chemically. The linearization equation of the Langmuir isothermic adsorption model in a solution system is expressed by the following equation (Rukayat and Usman, 2021).
ce
qe
= 1 KLqmax
+ 1 qmax
ce
With:
qmax : The maximum monolayer adsorption capacity of the adsorbent (mg/g)
K : Langmuir constant (L/mg) ce : Final Concentration (mg/l)
The kinetic model of heavy metal ion adsorption by the adsorbent in the solution system can also be investigated using pseudo-first-order and pseudo-second-order kinetic models. These models are recommended for the same adsorption of oleate, oxalate, and malonate on the adsor- bent surface. The equation is stated as follows (Wibowo et al., 2017):
dqt
dt
=k1(qe− qt)
Where t is the adsorption contact time, qe and qt are the mass of
adsorbate that is adsorbed on the surface of the adsorbent. Then the initial first-order adsorption rate can be formulated by
h1=k1qe
The equation for pseudo-second-order is as follow dqt
dt
=k2(qe− qt)2
The pseudo-second-order initial adsorption rate is formulated as follows h1=k1qe2
2.5. Characterization
Adsorption tests on heavy metal-polluted water were performed on the Fe3O4 nanoadsorbent. It is tested using an AAS (Atomic Absorption Spectroscopy) to detect the metal compounds in the water before and after treatment with Fe3O4 nanoadsorbent. The best findings were ob- tained by determining the functional groups generated on the Fe3O4
nanoadsorbent using FTIR (Fourier Transform Infra-Red). PSA (Particle Size Analyzer) was used to determine the particle size of Fe3O4 nano- adsorbent powder. The morphology and more precise composition of the Fe3O4 nanoadsorbent are determined by SEM/EDS (Scanning Electron Microscope/Energy Dispersive X-Ray Spectroscopy). The phase formed from Fe3O4 nanoadsorbent powder was determined using XRD (X-Ray Diffraction). (Blue et al., 2021; Lin et al., 2020). Calculation of crystal size with the Scherer
S= 0,9λ Bcosθ With
S =Crystal Size (nm) λ =Wavelength (A).
B =FWHM (full width half maximum)(rad) θ =Angle with High Intensity(o)
2.6. % adsorption
The effect of contact time variation aims to optimize% adsorption. In
0 20 40 60 80 100 120
0 50 100 150 200
% Ads o rpon Me an Various Heavy metals
Contact Time (minute)
FM FMAC FMCH FMG
Fig. 3.1. Effect of contact time variations.
this case, the material used compares FM, FMAC, FMCH, and FMG. In graph 3.1, it can be seen that the percentage adsorption of the four heavy metals (Mn, Fe, Pb, and Zn) reached 99.07% at a contact time of 120 min and a stirring speed of 200 rpm, then decreased again. This unique thing also happens to other materials. Compared to other studies reported, it is a striking finding, where the% adsorption was only 65.52% (Dave and Chopda, 2014; Gutierrez and Hilt, 2017; Lin and Jiang, 2017).
The pH of the solution is a significant parameter in% adsorption because it is related to the surface ionization of nanoparticles and heavy metal ions in polluted water. % adsorption was observed at pH 4, 5, 6, 7, and 8. It can be seen that the material with very high% adsorption is Fe3O4. Fig. 3.2 shows that the highest% adsorption occurs at pH 5. The same thing happens with other materials.
The effect of variations in speed is essential in seeing the quality of%
adsorption. Variations start at 50, 100, 150, 200, and 250 rpm.%
Optimal adsorption was seen at 200 rpm and decreased at 250 rpm. It occurs in each material, whether it is FM, FMAC, FMCH, and FMG.
However, the best performance is in Fe3O4 material for each heavy metal, as shown in Fig. 3.3
The adsorption of various heavy metal ions (Mn, Fe, Pb, and Zn) was
tested at the concentrations contained in polluted water, which had been successfully removed by% adsorption using Fe3O4 material. It can be seen from the three graphs in Figs. 3.1, 3.2, and 3.3. These images show variations strongly influencing the% adsorption in pH, contact time, and stirring speed.% adsorption increased with increasing pH, contact time, and stirring speed but decreased again when pH 4 was reached, the contact time was 150 min, and the stirring speed was 250 rpm. It occurs in all materials. It is because the active sites on the adsorbent become saturated under these conditions. From the observations, the charac- terization test of SEM/EDS, XRD, FTIR, and PSA was the best material, namely Fe3O4 magnetic without additional material with pH seven treatment, contact time of 120 min, and stirring speed of 250 rpm.
2.7. Adsorption kinetics modeling of various heavy metals
The Langmuir model analyzed the four heavy metal ions (Mn, Fe, Pb, and Zn). The graph can be seen in Fig. 3.4, which shows a curved dia- gram. So this curvature proves the surface heterogeneity of the binding sites on Fe3O4 nanoadsorbents. This model indicates that the Fe3O4
nanoadsorbent is excellent and suitable for adsorbing the four heavy 0
20 40 60 80 100 120
0 2 4 6 8 10
% Adsorpon Mean Various Heavy metals
pH
FM FMAC FMCH FMG
Fig. 3.2. Effect of Variation of Solution pH.
0 20 40 60 80 100 120
0 100 200 300
% Ad sorpon Mean Various Heavy Metals
Srring Speed
FM FMAC FMCH FMG
Fig. 3.3.Effect of variation of stirring speed.
-10 0 10 20 30 40 50 60
0 0.05 0.1 0.15
Ce/qe (g/L)
Ce (mg/L)
Zn
0 0.5 1 1.5 2
0 0.005 0.01 0.015 0.02
Ce/qe (g/L)
Ce (mg/L)
Pb 0
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
0 0.5 1 1.5
Ce/qe (g/L)
Ce (mg/L)
Mn
-1 0 1 2 3 4 5 6 7 8
0 0.1 0.2 0.3
Ce/qe (g/L)
Ce (mg/L)
Fe
Fig. 3.4. The Langmuir model.
Table. 1.1
Parameter of Langmuir isotermic.
Mn Pb Fe Zn
Ce (mg/L) Ce/qe (g/L) Ce (mg/L) Ce/qe (g/L) Ce (mg/L) Ce/qe (g/L) Ce (mg/L) Ce/qe (g/L)
0,915 0,031,017 0,0074 0,172,568 0,185 0,074 0,0473 0,357,928
0,713 0,02,391 0,0102 0,115,784 0,169 0,068,699 0,11,058 0,140,713
0,577 0,019,533 0,011,107 0,10,021 0,086 0,014,862 0,076,673 0,205,547
0,491 0,017,072 0,01,564 0,061,381 0,052 0,008,228 0,10,052 0,14,813
0,609 0,028,148 0,006,516 0,179,558 0,146 0,063,368 0,022,788 0,735,914
0,897 0,085,974 0,003,067 0,410,543 0,174 0,145 0,016,067 1,053,174
1068 0,239,309 0,001,257 1,042,841 0,195 0,413,636 0,009,177 1,864,524
Fig. 3.5. (a). Adsorption kinetics graph (b). Water visualization before and after treatment.
metals at different concentrations (Alamrani, 2021; Sarwar et al., 2021).
Table 1.1
The following adsorption kinetics analysis determines the adsorption reaction rate, adsorption constant, and adsorption rate based on calcu- lations and plotted graphs as shown in Fig. 3.5. The chart shows pseudo- first-order and pseudo-second-order. Pseudo-first-order shows sharp curvature in contrast to and pseudo-second-order. It happens because pseudo-second-order has high mobility compared to pseudo-first-order for all types of heavy metals. So it has a pseudo-second-order ability to interact with higher affinity sites. (Alamrani, 2021) Table 1.2;
Rukayat and Usman, 2021; Wibowo et al., 2017
2.8. Characterization
SEM/EDS analysis is shown in Fig. 3.6 and Fig. 3.7, which shows that the particles of Fe3O4 nanoadsorbent look heterogeneous, and no ag- gregation occurs. The crystal size is in the range of 9–100 nm. It supports
the results of the calculation of the adsorption kinetics in Fig. 3.5. The material contained also shows that Fe3O4 is dominant at 89.26%. It shows that the synthesis carried out succeeded in obtaining optimal purity. The FTIR spectrum in Fig. 3.8 also confirms that the bending of the H–O–H vibrations at about 1000–1600/cm, typical of H O mole- cules, has a very low intensity. In addition, the second absorption band, between 900 and 1000/cm, corresponds to flexural vibrations associ- ated with O–H bonds (Basuki et al., 2021; Gutierrez and Hilt, 2017).
O–H in-plane and out-of-plane bonds appear at 1583.45–1481.23 and 935.41–838.98/cm. For strong hydrogen bridges, the maximum is around 900–1000/cm. Two bands corresponding to the hydroxyl groups attached to the hydrogen bonds on the iron oxide surface and the water molecules chemically adsorbed to the particle surface magnets (Matome et al., 2020). The sample shows two intense peaks, at 582 and 640/cm bands, respectively, caused by stretching the vibrational modes associ- ated with the metal-oxygen absorption of the band (Fe–O bonds in the Fe3O4 crystal lattice). A feature formed is a spinel and ferrite structure (Blue et al., 2021; Lesaoana et al., 2019). It is supported by the XRD test results in Fig. 3.9, which show a crystalline pattern with all of the peaks being magnetic and suitable for the coprecipitation synthesis method (Chibowski, 2018; El-sayed, 2020).
Furthermore, the Fe3O4 magnetic shows the characteristics of bulk magnetite crystals, where the peak area offers nano-crystalline proper- ties. As calculated from the Scherrer equation, the resulting average crystal diameter of the magnetite nanoparticles is in the range of 11 nm.
The PSA test results in Fig. 3.10 show that the particles formed are excellent. The crystals coalesce to form particle sizes in the 130 nm range with heterogeneous particle distribution.
Table 1.2
Parameters of adsorption kinetics.
No Initial concentration (mg/l) Co
Mean Qe Reaction
Order Reaction rate constant (k)
Absorption rate 1 Mn =1.210 0,019,468 Order 1 3,938,983 0,076,684
Order 2 7,877,966 1,20,823 2 Fe =1.351 0,006,988 Order 1 4,963,561 0,034,685
Order 2 9,927,122 0,688,652 3 Pb =0.210 0,002,634 Order 1 5,939,252 0,015,644 Order 2 118,785 0,371,654 4 Zn =0.06 0,047,929 Order 1 3,038,035 0,14,561
Order 2 6,076,069 1,769,472
Fig. 3.6.SEM of image magnetic Fe3O4 nanoparticles.
2.9. Interaction mechanism
Fig. 3.1 shows the highest% adsorption at a contact time of 120 min because the adsorbate concentration cannot interact with the nano adsorbent at the contact time, where the adsorbate molecules are not bound to the active site of the adsorbent due to saturation of the nano adsorbent and part of the nano adsorbent releases the adsorbate so that decreased after optimal conditions. Fig. 3.2 shows that at the optimum pH conditions of pH 5 and down to pH 4. At pH 6–5, the adsorption on metals is more significant. This is because the competition between H+ ions and metal ions decreases so that more metal can be adsorbed under these conditions. After pH 5, the adsorption of metal ions by the adsorbent tends to decrease. The metal ion binding interaction by the
hydroxyl group (CH2OH) present in the nano adsorbent undergoes saturation. The adsorption capacity increased from pH 7 to pH 5.
This phenomenon could be explained qualitatively based on the presence of metal species and nanoadsorbents in the solution. The adsorption capacity is relatively small at low pH, namely pH 8–7 (Zhu et al., 2021). This is due to the low pH (acidic). H+ions in the solution will increase metal ions’ binding to functional groups on the surface of the nanoadsorbent. However, at pH 7, the adsorption capacity was relatively high. This is because there are more OH-ions in the solution, and the functional group of the nano adsorbent is negatively charged so that the competition for H+ions with metal ions is reduced in binding to the nanoadsorbent groups. This causes more metal to be adsorbed.
Fig. 3.3 shows that% adsorption increases at a stirring speed of 100–200 Fig. 3.7. EDS graph of magnetic Fe3O4 nanoparticles.
Fig. 3.8.FTIR spectrum of magnetic Fe3O4 nanoparticles.
rpm and decreases at 250 rpm.
The decrease due to the too-short interaction makes the interaction between the nano adsorbent and adsorbate particles released. In addi- tion, the fast stirring at 250 rpm makes the nano adsorbent not have strong bonds with ions, resulting in only a small amount being absorbed.
The speed of 200 rpm is the optimum and effective condition for adsorbing heavy metal ions. The interaction mechanism of the FM nano adsorbent was demonstrated by analysis of the FTIR, XRD, and PSA spectra. Fig. 3.8 shows the FTIR spectrum of the FM nano adsorbent after the heavy metal adsorption (Hu et al., 2021; Thabede et al., 2021).
The bonding mechanisms in the O–H plane and outside the O–H plane appeared to be 1583.45–1.481.23 and 935.41–838.98/cm. For strong hydrogen bridges, the maximum is around 900–1000/cm. The two bands correspond to the hydroxyl groups bonded to hydrogen bonds on the surface of the FM nanoadsorbent and water molecules that are chemically adsorbed to the FM nano adsorbent’s surface. The tetrahe- dral and octahedral sites of these oxide structures bind heavy metals. In addition, the FTIR spectrum shows an absorption band at 1.706/cm,
which corresponds to the vibration of the carboxylate group (C =O).
The oleic acid molecules are adsorbed onto the crystal surface. The crystallization interaction was supported by XRD, which showed a crystal pattern with all the peaks being magnetic and suitable for the coprecipitation synthesis method (Blue et al., 2021; T. Zhang et al., 2021; Zhu et al., 2021). The highest adsorption percentage showed crystallization properties, such as the diffraction pattern in Fig. 3.9 with a crystal size of 11 nm. The interaction of particles with a particle size distribution model produced by PSA is around 130 nm, and heteroge- neous shows high adsorption (T. Zhang et al., 2021) percentage of 99.27%. The percentage shows the maximum results.
3. Conclusion
In this study, the coprecipitation method synthesized FM nano- adsorbent and remediated water contaminated with various heavy metals, namely Mn, Fe, Pb, and Zn. The experimental results suggest that
% adsorption is affected by contact time, stirring speed, and pH solution.
Fig. 3.9.XRD pattern and crystal size for magnetite particles.
Fig. 3.10. PSA of magnetic Fe3O4 nanoparticles.
The optimum% adsorption occurred at a contact time of 120 min, a stirring speed of 200 rpm, and a solution pH of 5, which reached 99.27%. So that from the four materials made, it is shown that FM nanoadsorbents without additives are more effective in remediating polluted water. It is supported by the SEM/EDS, XRD, FTIR, and PSA characterization results.
CRediT authorship contribution statement
Khairiah Khairiah: Data curation, Writing – review & editing. Erna Frida: Data curation, Writing – original draft. Kerista Sebayang:
Methodology, Investigation. Perdinan Sinuhaji: Visualization, Inves- tigation. Syahrul Humaidi: Visualization, Investigation. Ahmad Fud- holi: Data curation, Writing – original draft.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgement
Thank you to the Directorate General of Resources for Science, Technology and Higher Education for trusting the author to get a scholarship for the BPPDN doctoral program. Thanks to the Deputy for Strengthening Research and Development under contract number 233/
UN5.2.3.1/PPM/KP-DRPM/2021 and the Muslim Nusantara Alwasliyah University for providing PDD grants for this research to be completed optimally.
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