Title Science and Technology Indonesia e-ISSN:2580-4391 p-ISSN:2580-4405 Vol. 6, No. 4, October 2021 Research Paper Biogenic Silica Extracted from Salacca Leaf Ash for Salicylic Acid Adsorption Is Fatimah1*, Faiha Ulfiyani Zaenuri1, Lolita Narulita Doewandono1, Amri Yahya1, Putwi Widya Citradewi1, Suresh Sagadevan2, Won-Chun Oh3 1Chemistry Department, Universitas Islam Indonesia, Yogyakarta 55584, Indonesia2Nanotechnology & Catalysis Research Center, University of Malaya, Kuala Lumpur 50603, Malaysia3Department of Advanced Materials Science and Engineering, Hanseo University, Seosan-si, Chungnam 356–706, South Korea *Corresponding author: isfatimah@uii.ac.id AbstractThe extraction of biogenic silica from Salacca leaf ash and its utilization as an adsorbent for salicylic acid has been successfullyconducted. The caustic extraction by refluxing the ash in NaOH followed by slow titration using acid produced the silica gel. Thesintering of the dried gel was varied at 300, 400, and 500°C to evaluate its physicochemical character for adsorption purposes.Instrumental analysis of X-ray diffraction, scanning electron microscopy, gas sorption analysis, and Fourier transform infraredspectroscopy (FTIR) were employed. The kinetics of salicylic acid adsorption was investigated in a batch adsorption system andshowed the fitness of the adsorption with a pseudo-second-order kinetics. The isotherm studies revealed that salicylic acid adsorptionobeyed the Langmuir model. At varied sintering temperatures, the highest adsorption capacity and affinity were achieved at atemperature of 500°C, due to the increasing specific surface area. The maximum adsorption capacity of 36.7 mg/g is comparablewith other work, but at less cost and synthesis process. The varied pH for adsorption is a suggestion that the neutral pH is the mostfeasible compared to the acidic and basic conditions. KeywordsAdsorption, Biogenic Silica, Salicylic Acid Received: 29 June 2021, Accepted: 18 September 2021 https://doi.org/10.26554/sti.2021.6.4.296-302 1. INTRODUCTION The use of pharmaceuticals has signicantly increased in recent decades and later due to the current COVID-19 pandemic. Many drugs and pharmaceutically active compounds (PACs) areproduced inanextraordinarilysignicantamount. Asacon- sequence, pharmaceuticalwaste frompharmacyindustrial eu- ent is also increased. Besides, as a wastewaterconstituent, PACs are released during manufacturing and by disposal of unused or expired drugs. Due to their bioactivities, the removal and handlingof manyPACs must be appropriatelydesigned to min- imize environmental contamination. In the form of wastewater, standard technologies used for chemicals-containing water re- mediation are used forPACs treatment. Technologies based on advanced oxidation processes (AOP), adsorption, and electro- chemical oxidation are popular treatment methods (Choi and Shin, 2020; Rakishev et al., 2021). The utilized low-cost mate- rials, such as activated carbon, silica, and silica-alumina-based materials, have been explored to enhance the eectiveness of the PAC adsorption process. High adsorptive capability, high ecacy, and good selec- tivity for removing a particular pharmaceutical compound are signicant features for selecting substances to remove PACs from the environment. Salicylic acid (SA, C7H6O3) is a critical compound in pharmaceutical industries that is widely used for some other pharmaceutical compounds, such as acetylsalicylic acid (ASA, C9H8O4) and atenolol (ATL, C14H22N2O3). It is estimated that 40,000 tons of SA are consumed annually, and a high percentage of SA waste is released annually. The lack of specic SA treatment in wastewater management must cause adverse eects on the aquatic environment and biodiversity. Moderate to high toxic eects are caused by environmental SA exposure to aquatic organisms, including oxidative stress and toxicity (Freitas et al., 2020; Gómez-Oliván et al., 2014; Nunes, 2019). SA is a common and widely used analgesic, antipyretic, and anti-inammatory drug, with an estimated annual consumption of 50–120 billion pills. Exploring adsorp- tion preparation for SAadsorption will be critical in sustainable pharmaceutical industries (Choi and Shin, 2020). In many studies, the use of some SA adsorbents, such as natural zeolite (clinoptilolite), clays (bentonite and kaolin), acti- vated carbon, and other polymeric resins (Rakić et al., 2013; Otero et al., 2004), is reported. Silica and its building blocks, https://crossmark.crossref.org/dialog/?doi=10.26554/sti.2021.6.4.296-302&domain=pdf https://doi.org/10.26554/sti.2021.6.4.296-302 Fatimah et. al. Science and Technology Indonesia, 6 (2021) 296-302 such as MCM-41, have also been reported to have high SA adsorption ecacy. The SA adsorption using silica-based ma- terials is not only proposed for water remediation, but it is also used as preconcentration and drug loading in slow-release drug preparation. As part of the exploration of new and re- newable materials from the perspective of green chemistry, the use of biogenic silica for this purpose was proposed to improve economic benets. The high potency of Salacca leaf ash as a silica source was reported in previous works. The leavesare anagriculturalwaste produced in high amounts (Silviana and Bayu, 2018). The industrial utilization of Salacca leaves as a source of biogenic silicaprovideseconomicvalueforthe industrialandagricultural sectors. Based on this background, this research was aimed to use biogenic silica extraction from the ash of Salacca leaves for SA adsorption. The potential content of silica in Salacca leaf ash (SLA) was revealed in previous investigations, but a more detailed study reporting its use as an SA adsorbent was not registered yet. Therefore, biogenic silica extraction for SA adsorption, considering the extraction method for creating specic physicochemical characteristics as an adsorbent, was performed in this study. As an adopted extraction method from the standard method of biogenic silica extraction from other sources, this study was focused on the eect of the silica sintering process on its physicochemical characteristics and SA adsorption capability. 2. EXPERIMENTAL SECTION 2.1 Materials Salacca leaves were obtained from an agricultural area in the Sleman District, Yogyakarta, Indonesia. Chemicals used to extract silica from the Salacca leaves consisted of NaOH (97%), HCl (30%), SA (99%), and ammonium phosphate (99%). Such substances were purchased from Merck-Millipore (Germany) for pro analyst quality. 2.2 Method The SLA was obtained by pre-treatment, which consisted of cleaning them with water and then drying them in an oven at 60°C. Later, the cleaned and dried leaves were incinerated in a mue furnace at 500°C under atmospheric conditions for 2 h. Silica extraction was performed by reuxing 10 g of SLA with 100 ml of 1 M NaOH solution for 1 h. The result was ltered, and the ltrate was adjusted to pH 7.4 by dropping HCl 1 M until a white gel was produced. The precipitate was then kept in a hot air oven at 80°C overnight before sintering at varying temperatures: 300, 400, and 500°C. The samples were encoded as SiO2-300, SiO2-400, and SiO2-500, respec- tively. The physicochemical characterization of the materials was performed using X-ray diraction (XRD), a gas sorption analyzer, a Fourier transform infrared (FTIR) spectropho- tometry, and scanning electron microscope-energy dispersive X-ray spectrophotometry (SEM-EDS). A Bruker D2 Phase 2nd Gen X-ray diractometer was employed in the analysis. A Ni-ltered Cu K𝛼 ray (_ = 1.54056 Å) was used as a radiation source, and the measurements were carried out from 2\ = 10° to 80° at a rate of 0.4°/min. For the gas sorption analysis, a NOVA 1200 instrument was employed. For each analysis, the samples were degassed at 90ºC for 4 h before analysis. /A Perkin-Elmer FTIR spectrophotometer was used in the anal- ysis, and a Phenom X instrument was used in the SEM-EDS analysis. The schematic representation of the silica extraction method is shown in Figure 1. Figure 1. Schemtic Representation of The Method for Biogenic Silica Extraction 2.3 Adsorption Experiment The SA adsorption experiments were conducted in a batch system using a bench horizontal shaker at 600 rpm. The SA analysis was performed on a UV-Visible spectrophotometric analysis based on a standard curve. 3. RESULTS AND DISCUSSION 3.1 Material Characterization Figure 2. XRD Pattern of Derived SiO2 The extracted silica at varying sintering temperatures was detectedthroughXRDmeasurementwiththereectionsshown in Figure 2. A broad peak at a 2\ value of about 22° was ex- hibited by the XRD patterns in all samples. The broadness of these exhibited peaks are a conrmation that the synthe- sized biogenic nano silica samples were naturally amorphous © 2021 The Authors. Page 297 of 302 Fatimah et. al. Science and Technology Indonesia, 6 (2021) 296-302 and were tted with the JCPDS data le No: JCPDS 46-1045 (Chun et al., 2020; Fatimah et al., 2019; Jaafari et al., 2020). Figure 3. SEM Prole of Derived SiO2 Samples Ahigherpeakintensityandtheremovalofsomeotherpeaks reecting the impurities in the SiO2-300 sample were caused bythe sintering. However, the SiO2 content was not inuenced by the sintering temperature in the EDX analysis, suggesting that the impurities corresponded to silicious materials. The increasing intensity and the broad peak shift at the lower angle were attributed to the increasing pore size homogeneity caused by H2O removal and dehydration at increasing temperatures. A similar eect was observed in silica extraction from rice husk ash and the characteristics of silica forms (Alyosef et al., 2013; Prasad and Pandey, 2012). The determined SiO2 content was around 98.7–98.8% wt. The removal of the exhibited minor peaksanddehydrationat thehighertemperaturewasconrmed by the surface morphology change, as shown in Figure 3. More homogeneous particle sizes and a more opening surface were found for SiO2-500. The surface morphology proles of the samples are in agreement with the surface prole data obtained by gas sorption analysis. Table 1. Surface Parameters and SiO2 Content of Materials Parameter SiO2-300 SiO2-400 SiO2-500 Specic surface area 58.9 89.7 92.9(m2/g) Pore radius (Å) 10.9 12.2 11.8 Pore volume (cc/g) 5.26 x10−3 23.1 x10−3 25.6 x10−3 SiO2 content (% wt) 98.7 98.7 98.8 The sintering temperature eect on the surface was also identied from the change of specic surface area, and pore distribution, shown in Figure 4. The calculated parameters are shown in Table 1. The specic surface area of 58.9 m2/g was demonstrated by the prepared SiO2. After the sintering process, it was increased to 89.7 m2/g and 92.9 m2/g at 300°C and 500°C, respectively. The increased specic surface area is consistent with the adsorption-desorption prole Figure 4 and the pore size distribution Figure 4, reecting the improvement inadsorptioncapabilityatall theP/P° ranges. Themicroporous domination, which is characteristic of silica and nano silica extracted from biogenic sources, was implied by the isotherm pattern and pore distribution plots. Figure 4. Adsorption-Desorption Isotherm of SiO2 samples (a), Pore Distribution Curve of SiO2 Samples (b) The comparison of silica content and the specic surface area from various silica sources are shown in Table 2. In other sources in which a high specic surface area (more than 100 m2/g) was exhibited, such as oat and rice husks, the specic surface area of SiO2 obtained in this research was relatively lower (more than 99% wt) with high specic surface area (more than 100 m2/g), but the silica content is relatively high (98.7% wt). The FTIR spectra comparison is shown in Figure 5 shows. There was no signicant dierence among the materials. The -OH absorptions were identied at a wavenumber of around 3388.9–3394.1 cm−1, and the lower wavenumber (3388.9 cm−1) corresponded to SiO2-300. The band was unidenti- ed at a higher calcination temperature, indicating the reduced amount of -OH functional group on the surface caused by the heating and dehydration process. The absorption bands at 1633–1638 cm−1 were representations of the asymmetric stretchingvibrationsSi-O-Si stretchingvibration, followingthe Si-O symmetric stretching vibration identied at a wavenum- ber of around 1387 cm−1. Other absorption bands around 430–460 cm−1 are indications of Si-O bending vibrations. © 2021 The Authors. Page 298 of 302 Fatimah et. al. Science and Technology Indonesia, 6 (2021) 296-302 Table 2. Comparison of SiO2 Specic Surface Area and Content Obtained from Various Sources Source Silica content Specic surface Reference(%wt) area (m2/g) Rice husk 97.7 313 (Alyosef et al., 2013) Sugarcane baggase 87.6 15 (Alyosef et al., 2013) Oat husk 99.1 248 (Maseko et al., 2021) 91.6 301 (Maseko et al., 2021) Ground nut shell nd 0.89 (Peerzada and Chidambaram, 2020) Oat husk 94.1–94.3 124–129 (Mattos et al., 2016) Horsetail 98.2 393 (Mattos et al., 2016) Bamboo leaves ash 99.1 428 (Rangaraj and Venkatachalam, 2017) Salacca leaves ash 98.7 58.9 This work Figure 5. FTIR Spectra of Materials 3.2 Adsorption of SA The SA adsorption kinetics were evaluated by referring to the pseudo-rst-order and pseudo-second-order by the following equations 1– 2 : ln(qe − qt) = lnqe − kt (1) t qt = 1 k2q2e + t qe (2) where, qt (mg/g) is the amount of adsorbed metal ions at the time of t, qe (mg/g) is adsorption capacity, k (min−1) is the rst-orderrate constant, and k2 (g/mgmin) is the second-order rate constant of adsorption (min−1) (Lee et al., 2018; Zou et al., 2018). SA adsorption kinetics are shown by the curve in Figure 6. Insignicant adsorption capabilities were exhibited by the SiO2-400 and SiO2-500 with the varied sintering temperature. Nonetheless, such numbers were still higher than those for SiO2-300. The higher R2 values for the pseudo-second-order kinetics model for all adsorbents are suggestions for the second-order Figure 6. Kinetics of SA Adsorption on SiO2 Samples [Initial SA Concentration = 20 mg/L, Temperature = 25°C, pH = 7] tness. The kinetics order represented the dependency of the adsorption mechanism concerning both the SA concentration and the available adsorption sites. SA adsorption was also obtained using polymeric and activated carbon in a similar ki- netics study (Câmara and Neto, 2008). Given the chemical SA structure, which contains the hydroxyl functional groups and the aromatic ring, hydrogen bonding and electrostatic interac- tion are the main mechanisms besides the possible molecular sieving mechanism. Given the silica surface interaction with some other aromatic compounds, the net negative charge of the aromatic ring is electrostatically bound with the oxygen on the silica surface. Meanwhile, the hydrogen atom interacts with the surface via hydrogen bonding (Sadhu et al., 2014; Yuan et al., 2019). The schematic representation of the adsorption mechanism is shown in Figure 6. The adsorption isotherm was performed by modeling the adsorption data using the Langmuir and Freundlich models to studythe interactionbetweentheadsorbateandadsorbent. The Freundlich and Langmuir model equations are represented in the following equations 3–4: © 2021 The Authors. Page 299 of 302 Fatimah et. al. Science and Technology Indonesia, 6 (2021) 296-302 Table 3. The Calculated Langmuir and Fruendlich Isotherm Parameters Adsorbent Langmuir Freundlich qm (mg/g) KL (L/mg) RL R 2 KF (L/g) 1/n R 2 SiO2-300 26.58 2.11 0.93 0.997 1.32 0.28 0.931 SiO2-400 26.51 1.86 0.93 0.997 1.33 0.29 0.916 SiO2-500 34.91 8.21 0.8 0.981 1.49 0.39 0.945 qe = KFC 1/n e (3) qe = qmKLCe 1 + KLCe (4) where qe (mg/g) is the equilibrium adsorption capacity of the adsorbent, Ce (mg/L) is the concentration of adsorbate in equilibrium, qm (mg/g) is the maximum adsorptive capacity of the adsorbent, KF is the Freundlich constant related to the adsorption-desorption equilibrium of adsorption capacity, n is the Freundlich constant related to the adsorption intensity, and KL (L/mg) is the Langmuir constant related to the adsorption energy (Dada et al., 2012). The equilibrium parameter from the Langmuir isotherm, RL, is represented as follows equation 5 : RL = 1 1 + KLqm (5) Figure 7. Linear Langmuir Model Plot of SA Adsorption by SiO2 Samples The calculated parameters are shown in Table 3. From the values, it was observed that both models applied well for SA adsorption in all SiO2 samples. However, the Langmuir model was better based on the nearness to the unity of the R2 values. This nding is also shown in Figure 7, where the tness of ad- sorption data with the Langmuir model was implied. A typical surface diusion control of the adsorption by a homogeneous surface was demonstrated by the tness of the Langmuir model (Câmara and Neto, 2008). The role of chemisorption on the silica surface was validated by the 1/n values from the Fre- undlich isotherm that was laid at 1/n < 1, and by the Langmuir model, the RL values ranged from 0 < RL < 1 (0.80–0.94) for all adsorbents. In previous similar works, it was stated that the RL values = 0, 0 < RL < 1, RL = 1, and RL > 1 are indicative of irreversible, favorable, linear, and unfavorable adsorption, respectively. The SA adsorption from all the samples in this work was favorable (Yagub et al., 2014). Table 4. Comparison of SA Adsorption Capacity Using Various Adsorbents Adsorbent Adsorption ReferenceCapacity (mg/g) Zeolite 8.97 (Rakić et al., 2013) Zeolite 2.3 (Cabrera-Lafaurie et al., 2014) Bentonite 34.5 (Rakishev et al., 2021) Activated Carbon 4.2 (Rakishev et al., 2021) Non-Imprinted 63.5 (Xu et al., 2021) Polymer (NIP) Hexadecyltrimethy 42 (Choi and Shin, 2020)lammonium-Modied Montmorillonite Molecularly Imprinted 30.42 (Rahangdale et al., 2016) Chitosan Graphene 63.66 (Lee et al., 2018) Molecularly Imprinted 30.3 (Rahangdale et al., 2016) Polymer Si-500 36.7 This work From the varied sintering temperature, the SiO2-500 was suggested by all parameters from both isotherms to have the highest anity for SA adsorption. The adsorption anity was in linewiththespecicsurfaceareadata, indicatingthatahigher sintering temperature produced a higher specic surface area. Based on the adsorption capability data and the comparison with other adsorbents presented in Table 4, the SA adsorption © 2021 The Authors. Page 300 of 302 Fatimah et. al. Science and Technology Indonesia, 6 (2021) 296-302 by the biogenic silica extracted in this research was comparable to that obtained from bentonite and was even higher than that obtained from zeolite. With a capacity of 36.7 mg/g, the SiO2-500 sample give higher value compared to molecularly imprinted polymer and molecularly imprinted chitosan, even though it is still lower compared to other adsorbents. It is important to be noted that the synthesis method in this work is by the lower cost. 3.3 Eect of pH Figure 8. Eect of pH on SA Adsorption Capacity by The Materials The study of the eect of pH on adsorption capability is of critical importance for the application purpose. The varying pH of 4, 7, and 9 on the SA adsorbed percentage is shown in Figure 8. There was optimum adsorption at the neutral (pH = 7) from these values, which was identied by the highest SA adsorption percentage for all SiO2 samples. The lower adsorption capacity at a low pH (pH = 4) is attributed to the protonic condition of the silica surface. Therefore, there was a repulsive force on the SA surface. Contrarily, the negative charge of the surface was led by the basic condition (pH = 10), according to equation 6, as follows: SiOH + OH– > SiO– + H2O (6) Repulsive force may occur due to the hydroxyl group in SA (Mustafa et al., 2003). The adsorption mechanism is sug- gested to be intensely dependent on the surface charge by the results. This nding is characteristic of adsorption, with no other mechanism, such as covalent, ligan-metal ion, or 𝜋-𝜋 interaction. 4. CONCLUSIONS In this study, biogenic silica was successfully extracted from Salacca leaf ash, and the silica samples were shown to be eec- tive adsorbents for salicylic acid from an aqueous solution. 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