Production of Precipitated Nano-Silica from Granite Waste

Production of Precipitated Nano-Silica from Granite Waste | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Production of Precipitated Nano-Silica from Granite Waste Atefeh Saeidi, Kianoush Barani This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6416965/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Precipitated nanosilica has diverse applications in advanced industries. One method for producing precipitated silica is through direct dissolution from mineral sources. This study investigates the production of nanostructured precipitated silica from granite waste powder. Initially, in the dissolution stage with sodium hydroxide, the effects of parameters such as solvent concentration, temperature, stirring speed, time, and sample mass were examined. The results showed that under optimal dissolution conditions (1.5M sodium hydroxide concentration, 80°C, 2.5h, and 900rpm stirring speed), only 0.76g of a 20g sample dissolved. In the precipitation stage, the effects of parameters like pH, temperature, time, and stirring speed were investigated. The results indicated that under optimal precipitation conditions (pH 7, 60°C, 1.5h, 1000rpm stirring speed), approximately 0.149g of nanostructured silica was obtained from the 0.76g of dissolved material. Both the dissolution and precipitation yields were very low, indicating the stability of silica in the granite sample. To enhance the efficiency, pressure dissolution, and calcination of the mineral material should be considered. Characterization of the produced precipitated silica using XRD, FTIR, BET, and SEM analyses revealed that it has the desirable quality for various industrial applications, including tire manufacturing. precipitated silica dissolution precipitation granite tire Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 1. Introduction Silica (SiO₂), accounting for about 60% of the Earth's crust, is a fundamental oxide compound found in quartz and silicate minerals. It serves as a crucial raw material in industries such as glass, cement, and ceramics. Technological advancements have expanded its applications, especially in nanoscale amorphous forms.[ 1 ]. Amorphous silica exists in three types: fumed silica, precipitated silica, and silica gel. While precipitated silica and silica gel share an amorphous structure, they differ in production methods and properties. Precipitated silica, characterized by its less porous structure and smaller internal surface area compared to silica gel, features a higher specific surface area, making it the most commercially significant type [ 2 ]. Precipitated nanosilica is widely utilized across industries due to its high surface area, reactivity, and versatility. It serves as a reinforcing agent in rubber and polymer composites, enhancing mechanical strength and durability. In electronics, it functions as an insulating material and filler in components, while in catalysis, coatings, and drug delivery systems, its biocompatibility and surface-modification capabilities are leveraged. Environmental applications include contaminant removal from air and water. One of the most significant uses of precipitated nanosilica is in tire manufacturing, especially for "green tires" introduced by Michelin in 1992. By integrating silica with carbon black, a silane coupling agent, and SSBR rubber in treads, critical tire properties such as modulus, tensile strength, abrasion resistance, and skid resistance are enhanced. Additionally, silica reduces fuel consumption by 3–15%, improves skid performance, and extends tire lifespan. The silica content in passenger car tires typically ranges from 10–30% by weight, depending on the model, size, and manufacturer [ 3 ]. The global precipitated silica market, valued at USD 2.15 billion in 2022, is projected to grow at a CAGR of 7.1% from 2023 to 2030. This growth is primarily driven by increasing demand from the rubber, agrochemical, and oral care industries. Among its applications, tire manufacturing represents the largest market share for precipitated silica [ 4 ]. For tire-grade silica, the preferred particle size ranges from 5 to 200nanometers (nm). Smaller particles provide a larger surface area, enhancing reinforcement and adhesion properties for improved traction and reduced rolling resistance, while larger particles offer better wear resistance and heat dissipation. The particle size distribution and surface area, typically between 150 and 300m²/g, can be optimized for specific tire applications. Silica used in tires generally has a bulk density of 650–750kg/m³ and requires high chemical purity (≥ 99%) to avoid performance-impacting contaminants. This ensures the silica's effectiveness in reinforcing tire compounds, contributing to better fuel efficiency, traction, and durability [ 5 ]. Precipitated silica is commonly produced via two industrial methods: the pyrometallurgical and hydrometallurgical processes. In the pyrometallurgical method, sodium carbonate and quartz are melted at high temperatures (1300–1500°C) to produce sodium silicate, a glassy, water-soluble material. This sodium silicate is leached with hot water under 4–5bar pressure in reactors, forming "water glass" or liquid sodium silicate. Precipitated silica is then obtained by neutralizing the sodium silicate solution with a mineral acid, such as sulfuric acid, through a controlled reaction. [ 6 ]: $$\:Na₂SiO₃\:\left(aq\right)\:+\:H₂SO₄\:\left(aq\right)\:\to\:\:SiO₂\:\left(s\right)\:+\:Na₂SO₄\:\left(aq\right)$$ 1 The hydrometallurgical method extracts silica from silica-rich sources using solvents such as acids, bases, or salts. Acids like sulfuric and hydrochloric acid effectively dissolve silica but often co-dissolve impurities like iron, contaminating the final product. Alkaline solvents, such as sodium hydroxide, are preferred due to their reduced dissolution of impurities, though they exhibit lower dissolution power overall. In this method, silica is obtained either as silicic acid or a metasilicate solution, depending on the process conditions. The reaction for silica dissolution using sodium hydroxide is as follows [ 7 ], [ 8 ]: $$\:SiO₂\:\left(s\right)\:+\:2NaOH\:\left(aq\right)\:\to\:\:Na₂SiO₃\:\left(aq\right)\:+\:H₂O\:\left(l\right)$$ 2 The hydrometallurgical method produces precipitated silica by neutralizing the leach solution, offering greater energy efficiency than the pyrometallurgical method as it operates without high temperatures. Efforts to optimize this process include identifying suitable feedstocks, such as agricultural residues (e.g., rice husk, rice straw, bagasse ash, and sugarcane bagasse residue), silica-rich minerals (e.g., olivine, feldspar, perlite, and bentonite), and industrial waste (e.g., fly ash). The choice of raw material is influenced by availability, cost, silica purity, and the level of associated impurities. [ 9 ]–[ 13 ]. The extraction of silica from rice husk for tire manufacturing was studied under specific conditions. The rice husk was first burned in an open environment and then converted into ash using an electric furnace. The ash was treated with caustic soda to produce a sodium silicate solution, from which silica was precipitated using sulfuric acid. The resulting silica matched the chemical purity of commercially available tire-grade silica but had a lower specific surface area (86.6–106.8m²/g) and smaller pore volume (0.63–1.29cm³/g) compared to commercial standards [ 14 ]. Amorphous precipitated silica (APS) was synthesized from olivine using a mixture of NaOH and KOH for alkaline dissolution. The combination of solvents achieved higher dissolution efficiency compared to single solvents. Key parameters, including alkali concentration, liquid/solid ratio, reaction time, and temperature, were optimized for maximum APS recovery. The resulting APS, with particle sizes below 10 nm, demonstrated properties ideal for applications in polymers and catalysis, such as a pore width of 5.59 nm, a cumulative pore volume of 0.96cm³/g, a BET surface area of 670.8m²/g, and a Langmuir surface area of 859.3m²/g. [ 15 ]. The dissolution of quartz sand in sodium hydroxide to form silica precipitate was investigated using the leaching method at atmospheric pressure. The effects of sodium hydroxide concentration, temperature, dissolution time, and stirring rate were examined, all of which positively influenced silica formation. Despite a high SiO₂ concentration in the feed material, the extraction rate remained low, with temperature being the most influential factor. The optimal conditions for silica precipitate formation were found to be at 90°C, with a stirring speed of 800 rpm and a 7.5M sodium hydroxide solution, yielding 13.6% silica precipitate [ 16 ]. A cost-effective process for utilizing Saudi Arabian desert sand to produce sodium silicate and precipitated silica was explored. Sodium silicate was synthesized via an alkali fusion method, followed by acid precipitation to obtain pure precipitated silica. The weight ratio of alkali to sand was optimized, resulting in a silica yield of about 80%. The silica produced was characterized using wet chemical methods, FTIR, TG-DTA, XRD, and SEM. XRD analysis revealed an amorphous silica peak at a diffraction angle of 21.8°, confirming the amorphous nature of the silica[ 17 ]. Amorphous silica nanoparticles were successfully extracted from grey pumice powder using an optimized alkaline treatment followed by acid precipitation. Pumice, a porous volcanic rock rich in silica and alumina with low iron content, offers potential for applications in adsorption, catalysis, and nanotechnology. The synthesized SiO₂ was characterized using XRD, FTIR, TEM-EDS, N₂ adsorption/desorption, and TG/DTA techniques. The results showed that the nanosilica had a mesoporous structure, a high surface area of 422m²/g, and particle sizes ranging from 5 to 15nm, confirmed by TEM and XRD. Thermal analysis indicated a 6.5% mass loss due to water and silanol group removal, demonstrating the feasibility of using pumice for large-scale production of amorphous silica nanopowder. [ 18 ]. A method for producing amorphous silica from perlite under microwave irradiation was developed, focusing on the effects of NaOH concentration, microwave irradiation time, and temperature on SiO₂ yield. The process consisted of alkali solubilization, gel formation, and acid dissolution. Characterization was performed using XRF, BET surface area, XRD, FTIR, and SEM-EDS techniques. The highest SiO₂ yield (94.48%) was achieved with 4N NaOH at 90°C for 15min, resulting in amorphous silica with a surface area of approximately 104m²/g. EDS analysis confirmed silicon as the predominant element, and XRD and FTIR data indicated increased amorphous characteristics, along with the presence of silanol and siloxane groups. This innovative process offers an efficient and sustainable method for producing high-purity amorphous silica from perlite, a solid waste material. [ 19 ]. A novel chemical process was developed to extract high-purity silica (99.99 wt%) from diatomite. The method involved acid dissolution of raw diatomite, alkali solubilization to form sodium silicate, and precipitation of silica gel using sulfuric acid. The silica gel was further purified by washing with 6M hydrochloric acid at elevated temperatures for three hours. Morphological and chemical analyses, including SEM, XRF, XRD, and ICP-OES, showed that the raw diatomite contained over 80 wt% amorphous microporous silica with particle sizes of 10–35µm. Stepwise acid dissolution increased the silica content to 90.2 wt%. Furthermore, boron was reduced by 70% using mannitol as a complexing agent during the final acid washing, resulting in ultra-high-purity silica suitable for advanced applications [ 20 ]. Precipitated silica is a strategic raw material for the industry. To mitigate the risks associated with its supply, achieving the technology for producing this vital material is of great importance. Given the abundance of silica-containing mineral resources in the world, producing precipitated silica from these sources is preferred over others. The aim of this research is to develop the knowledge for production of precipitated silica from mineral resources. In the extraction and processing of dimension stones, 50–70% of the stone is turned into waste, which is often unusable and poses environmental challenges. This study investigates the production of precipitated silica from granite waste. 2. Materials and methods 2.1. Sample Preparation A 10kg sample of waste granite (broken slabs with dimensions ranging from 12 to 17cm) was collected from stone processing plants. The sample was then crushed using jaw, cone, and roller crushers to reduce the size to below 3 mm. The crushed material was homogenized and then divided into 1kg subsamples using riffle splitting. One of the 1kg subsamples was ground in a ball mill to achieve a particle size of 100% below 100µm. The ground product was spread and homogenized on a plate, and then 100 subsamples, each weighing 10g, were selected using a grid sampling method. 2.2. Sample characterization XRF analysis was performed on the sample to identify the oxides present. The results of the XRF analysis for the sample are presented in Table 1 . Based on these results, the most abundant oxides in the sample, in order of prevalence, are SiO₂, Al₂O₃, Na₂O, CaO, K₂O, Fe₂O₃, MgO, and TiO₂. To identify the phases present in the sample, XRD analysis was conducted on a 10g sample. The XRD spectrum of the sample is shown in the Fig. 1 . According to the analysis, the major phases identified in the sample are quartz and albite. Table 1 XRF analysis of the feed material (granite waste) Composition SiO 2 Al 2 O 3 Fe 2 O 3 CaO MgO TiO 2 K 2 O Amount 80.77% 7.29% 2.9% 1.92% 0.79% 0.33% 4.58% Composition P 2 O5 Cr 2 O 3 MnO ZnO SrO ZrO 2 Amount 0.82% 500ppm 450ppm 300ppm 450ppm 300ppm 2.3. Dissolution experiments The sample was initially dried in an oven at 105°C for one hour, then weighed accurately. A specific portion of the dried sample was separated for each experiment. The measured sample was transferred into a 500mL Erlenmeyer flask equipped with a magnetic stirrer, preferably with variable speed control. To conduct the experiments, hydrochloric acid dissolution was employed to remove impurities. For this purpose, a 1 M hydrochloric acid solution (150mL) was prepared in a 500mL Erlenmeyer flask. The sample was then added to the prepared solution. The acid dissolution process was carried out at 60°C for 3h with a stirring speed of 300rpm, using a magnetic stirrer equipped with a heater. After the dissolution process, the mixture was filtered, and the residue was washed at least three times with deionized water on filter paper to ensure the removal of residual acid. The obtained solid residue (filter cake) was dried in an oven and subsequently weighed for alkali dissolution experiment. Alkaline dissolution experiments were conducted on the filter cake obtained from the acid dissolution stage. Sodium hydroxide was used as the dissolution agent. For each experiment, 150mL of sodium hydroxide solution with the desired molarity was prepared in a 500mL laboratory Erlenmeyer flask. The filter cake from the acid dissolution stage was then added to the solution, and the alkaline dissolution process was carried out. In these experiments, the effects of various parameters, including sodium hydroxide concentration, sample mass, dissolution temperature, dissolution time, and stirring speed, were investigated. The range of these parameters is outlined below: Sodium hydroxide concentration (mol/L): 0.25, 0.5, 1, 1.5, 2, 2.5 Sample mass (g): 5, 10, 15, 20 Dissolution temperature (°C): 50, 60, 70, 80, 90, 100 Dissolution time (h): 2, 2.5, 3, 3.5, 4, 4.5 Stirring speed (rpm): 300, 500, 700, 900, 1100, 1300 A total of 48 dissolution experiments were conducted. After each experiment, the pulp was filtered, and the remaining filter cake was dried in an oven at 110°C for 2h. The dried sample was then weighed using a precision laboratory balance with an accuracy of 0.0001g. The dissolution percentage and dissolved mass were calculated using the following equations: $$\:\text{D}\text{i}\text{s}\text{s}\text{o}\text{l}\text{v}\text{e}\text{d}\:\text{M}\text{a}\text{s}\text{s}\:\left(\text{g}\right)\:=\text{W}\text{e}\text{i}\text{g}\text{h}\text{t}\:\text{a}\text{f}\text{t}\text{e}\text{r}\:\text{a}\text{c}\text{i}\text{d}\:\text{d}\text{i}\text{s}\text{s}\text{o}\text{l}\text{u}\text{t}\text{i}\text{o}\text{n}\:\left(\text{g}\right)\:-\:\text{W}\text{e}\text{i}\text{g}\text{h}\text{t}\:\text{a}\text{f}\text{t}\text{e}\text{r}\:\text{a}\text{l}\text{k}\text{a}\text{l}\text{i}\text{n}\text{e}\:\text{d}\text{i}\text{s}\text{s}\text{o}\text{l}\text{u}\text{t}\text{i}\text{o}\text{n}\:\left(\text{g}\right)$$ 1 $$\:Dissolution\:Percentage\:=\:\frac{Dissolved\:Mass\:\left(g\right)}{\:Total\:initial\:weight\:\left(g\right)}\:\:\times\:\:100$$ 2 2.3. Precipitation experiments Precipitation experiments were conducted on cooled alkaline leach solutions. Sulfuric acid was used as the precipitating agent. In each experiment, 500mL of the cooled alkaline leach solution was transferred into a laboratory Erlenmeyer flask. Separately, 100mL of 1 M sulfuric acid solution was prepared. The alkaline leach solution was placed on a magnetic stirrer equipped with a heater, and its temperature was raised to the desired level. Subsequently, the sulfuric acid solution was added dropwise over a period of 0.5 to 1h until the pH of the solution reached neutral pH. Upon the formation of a white gel-like precipitate, the heating was turned off, and the mixture was left undisturbed at room temperature for 24 h. The effects of various parameters on the precipitation process, including the final pH of the solution, precipitation temperature, precipitation time, and stirring speed, were investigated. The ranges of these parameters are as follows: Solution pH: 5, 6, 7, 8 Precipitation temperature (°C): 60, 70, 80, 90 Stirring speed (rpm): 400, 700, 1000, 1300 Precipitation time (h): 0.5, 1, 1.5, 2 A total of 16 precipitation experiments were conducted. After each experiment, the precipitate was filtered and separated. The filter cake was washed with deionized water and dried in an oven at 40°C for 24h, then weighed.To remove impurities, the dried filter cake was washed with 1 M hydrochloric acid at a stirring speed of 700rpm and a temperature of 80°C for 3h. The washed sample was then filtered, dried in an oven, and weighed again. Finally, the sample was calcined in a furnace at 800°C for 1h. The final calcined sample was weighed, and the optimization of the precipitation experiments was done based on the final weight after calcination. 2.4. Characterization of precipitated silica (product) Based on the optimized conditions for dissolution and precipitation, a quantity of precipitated silica was produced. To determine the characteristics of the product, X-ray diffraction (XRD) was performed to identify the phases present in the sample. Scanning electron microscopy (SEM) was used to measure particle size and examine surface morphology, BET analysis was conducted to determine the particle size, specific surface area, and porosity of the product. Additionally, Fourier-transform infrared spectroscopy (FTIR) was conducted to identify the chemical bonds and functional groups in the sample. 3. Results and discussion 3.1. Dissolution experiments 3.1.1. Effect of sodium hydroxide concentration In a chemical reaction, increasing the solvent concentration can enhance dissolution; however, excessively high concentrations may lead to increased solution viscosity and reduced mass transfer rates. Furthermore, higher concentrations might trigger undesirable side reactions. Therefore, optimizing the solvent concentration is critical to achieving maximum dissolution and process efficiency [ 21 ]. Figure 2 illustrates the effect of sodium hydroxide concentration on the dissolution percentage of the ore for different feed masses. In these experiments, the dissolution duration was 2h, the stirring speed was 300rpm, and the temperature was maintained at 60°C. The results indicate that, overall, the percentage of dissolved mass is quite low, with dissolution percentages remaining below 4% even under optimal conditions. Additionally, increasing the molarity of sodium hydroxide has a limited impact on the dissolution percentage. When the initial feed mass was 5g, increasing the solvent concentration from 0.25 M to 2.5 M resulted in a near-linear increase in dissolution, from 9–11%. However, the main goal is to achieve the highest amount of dissolved mass. Figure 3 shows the effect of sodium hydroxide concentration on the dissolved mass for different feed masses. The highest dissolved mass (2.56g) was obtained when the initial feed mass was 20g and the solvent concentration was 1.5M. In other cases, the dissolved mass was significantly lower, typically less than 1.5g. Overall, the dissolution efficiency is notably low. For subsequent experimental stages, a feed mass of 20g and a solvent concentration of 1.5M were selected as the optimum conditions. 3.1.2. Effect of temperature In a chemical reaction, increasing the reaction temperature leads to more frequent collisions between molecules in the solution, thereby accelerating the dissolution process. Figure 4 illustrates the effect of temperature variations on the ore dissolution percentage. In these experiments, the initial feed mass was 20g, the dissolution time was 2h, the stirring speed was 300rpm, and the solvent concentration was 1.5M. It is observed that as the temperature increases from 50°C to 100°C, the dissolution percentage follows an increasing trend, rising from 3–3.5%. The effect of increasing temperature on the dissolution is negligible. As the temperature increases from 50°C to 100°C, the dissolution percentage increases by only 0.5%. Due to difficulties in controlling the experiment at temperatures of 90°C and 100°C, 80°C was chosen as the optimal temperature and used in subsequent experiments. 3.1.3. Effect of stirring speed The stirring speed in a chemical reaction process can significantly enhance the reaction rate. Stirring not only accelerates the interaction between reactants but also aids in maintaining uniform temperature distribution throughout the process [ 22 ]. Figure 5 illustrates the effect of stirring speed on the dissolution of the ore. In these experiments, the initial sample mass was 20g, the solvent concentration was 1.5mol/L, the dissolution time was 2h, and the dissolution temperature was 80°C. It was observed that increasing the stirring speed from 300 to 1300rpm resulted in an increase in the dissolution percentage from 2.5–3.7%. This finding highlights the ore's high resistance to alkaline dissolution. A stirring speed of 900rpm was identified as the optimal condition and was adopted for subsequent experiments. 3.1.4. Effect of dissolution time Figure 6 illustrates the effect of time on the dissolution of the ore. These experiments were conducted with an initial sample weight of 20g, a dissolution temperature of 80°C, a stirring speed of 900rpm, and a solvent concentration of 1.5mol/L. The results show that the highest dissolution percentage (3.8%) was achieved at a time of 2.5h, with dissolution decreasing at longer dissolution durations. The limited effect of extended time on dissolution percentages can be attributed to several factors. As the dissolution process progresses, the solution may approach saturation, reducing the driving force for mass transfer. Additionally, the formation of product layers or precipitates on the ore surface can inhibit further reaction. If the process is reaction-controlled, the dissolution may plateau over time. Furthermore, easily soluble phases may dissolve early, leaving more refractory phases behind. Lastly, the thermodynamic driving force diminishes as the system approaches equilibrium. These factors collectively limit the impact of prolonged dissolution on efficiency[ 23 ]. 3.1.5. Optimal dissolution conditions Based on the results of the dissolution experiments, the optimal conditions were determined as follows: an initial mass of 20g, a sodium hydroxide concentration of 1.5mol/L, a dissolution temperature of 80°C, a dissolution time of 2.5h, and a stirring speed of 900rpm. These conditions were selected for the dissolution stage and applied in the subsequent precipitation stage experiments. It is predicted that under optimal conditions, approximately 3.8% of the initial sample mass, equivalent to 0.76g, will dissolved. 3.2. Precipitation experiments 3.2.1. Effect of pH The pH plays a crucial role in the precipitation of silica from sodium metasilicate solutions when sulfuric acid is added. At lower pH levels, the silica (SiO₂) begins to hydrolyze and form hydroxyl groups, which leads to the formation of a silica network. However, as the pH increases, more hydroxyl groups are formed, resulting in the polymerization of silica molecules into a gel-like structure. When the pH is decreased further by the addition of sulfuric acid, the silica network breaks down, promoting its precipitation. The optimal pH range for efficient silica precipitation is generally between 6 and 7, as higher pH values may lead to unwanted side reactions and lower precipitation efficiency. Therefore, precise control of pH is essential to enhance the purity and yield of the precipitated silica [ 24 ], [ 25 ]. Figure 7 shows the effect of pH variations on the yield of precipitated silica. In these precipitation experiments, the temperature was set at 90°C, the duration was 0.5h, and the stirring speed was 1000rpm. It can be observed that as the pH increases from 5 to 7, the yield of precipitated silica increases from 0.012g to 0.020g. However, with a further increase in pH from 7 to 8, the yield of silica decreases to 0.010g. At lower pH (around 5), the silicate ions remain predominantly in a dissolved state, and the environment is not favorable for silica polymerization and precipitation. As the pH approaches 7, the reaction between sulfuric acid and sodium silicate facilitates the formation of solid silica, leading to an increase in the amount of precipitated silica. When the pH increases further to 8, the conditions shift towards the re-dissolution of silica. At this higher pH, silicate ions tend to remain in the solution as dissolved species rather than forming solid silica. At this stage, a pH of 7 was selected as the optimal pH and used in subsequent experiments. 3.2.2. Effect of temperature At higher temperatures, the rate of hydrolysis and polymerization of silica increases, promoting faster precipitation. This is because elevated temperatures enhance the collision frequency between molecules, accelerating the dissolution and subsequent precipitation of silica. However, excessively high temperatures may lead to the formation of larger, less stable silica aggregates, which can reduce the purity and yield of the final product. Therefore, controlling temperature is essential to optimize the precipitation process, with moderate temperatures typically providing the best results. For silica precipitation from sodium metasilicate, temperatures around 80–90°C are commonly used to achieve efficient and controlled precipitation[ 26 ]. Figure 8 shows the effect of temperature variations on the yield of silica precipitated. In these experiments, the pH was maintained at neutral (7), the precipitation time was 0.5h, and the stirring speed was set to 1000rpm. It can be observed that as the temperature increased from 60 to 90°C, the amount of silica precipitated decreased from 0.112g to 0.02g, following a decreasing trend. The amount of silica produced decreased significantly with the temperature increase, with a 0.092% reduction observed for a 30°C rise. At higher temperatures, the stability of amorphous silica decreases. As a result, some of the silica that was previously formed as a precipitate may re-dissolve into the solution. In this stage, a temperature of 60°C was selected as the optimal temperature and used in subsequent experiments. 3.2.3. Effect of stirring speed Increasing the stirring speed typically enhances the rate of silica precipitation by improving the mixing of the reactants (silicate solution and sulfuric acid), which promotes more effective interactions between them. This improved contact leads to a more uniform distribution of the precipitate, enhancing the overall yield of silica. Very high stirring speeds may also hinder the formation of larger silica particles, or cause the formed silica to re-dissolve. Additionally, in some systems, intense stirring may lead to the formation of gas bubbles or foam, which can affect the precipitation dynamics and reduce the overall yield. Therefore, an optimal stirring speed is necessary to balance effective mixing with controlled particle size formation [ 27 ]. Figure 9 shows the effect of stirring speed variations on the yield of silica precipitated. In these experiments, the pH was neutral (7), the precipitation temperature was 60°C, and the precipitation time was 0.5h. It can be observed that as the stirring speed increased from 400 to 1000rpm, the yield of silica increased from 0.074g to 0.108g. However, with further increase in stirring speed to 1300rpm, the amount of silica decreased to 0.041g. At this stage, a stirring speed of 1000rpm was chosen as the optimal condition and was used in subsequent experiments. 3.2.4. Effect of precipitation time In general, longer precipitation times allow for more complete formation and accumulation of the silica. However, excessive precipitation time may lead to the re-dissolution of some of the precipitated silica. Over time, some particles may grow too large and, due to their weight, may not settle completely or may even remain suspended in the system. Additionally, over extended periods, the structure of the precipitated silica may change from amorphous to a gel-like or colloidal form. This structural change can reduce the efficiency of precipitation and lower the final yield. Hence, an optimal precipitation time must be identified to achieve the highest yield without unnecessary energy consumption or side reaction. Figure 10 illustrates the effect of precipitation time on the yield of silica precipitated. The experiments in this stage were conducted with a neutral pH (7), a temperature of 60°C, and a stirring speed of 1000rpm. It is observed that as the precipitation time increases from 0.5h to 1.5h, the yield of precipitated silica increases from 0.099g to 0.149g. However, further increasing the precipitation time to 2h results in a decrease in silica amount to 0.075g. Based on these results, a precipitation time of 1.5h was selected as the optimal condition for subsequent experiments. 3.2.5. Optimal precipitation conditions Based on the results of the precipitation experiments, the optimal conditions for the precipitation stage are as follows: pH = 7, precipitation temperature of 60°C, precipitation time of 1.5h, and stirring speed of 1000rpm. It is predicted that under these optimal conditions, approximately 0.149g of the initial sample will be converted to nano silica. 3.3. Characterization of precipitated silica 3.3.1. XRD and XRF analysis The XRD spectrum of of the precipitate silica is shown in Fig. 11 . The broadening of the peak in the 20° ≤ 2θ ≤ 30° range indicates that the produced material is amorphous, with no crystalline phases identified. The low intensity of the peak further suggests that the silica particles are fine in size. The results of the XRF analysis for the precipitated silica are presented in Table 2 . Based on these results, the silica content in the precipitated silica exceeds 95%, while other impurities are present in the following order of abundance: Fe₂O₃, CaO, K₂O, and Cr₂O₃. The precipitated silica produced is suitable for various industrial applications, including its use in tire manufacturing. Table 2 XRF analysis of the precipitated silica Composition SiO 2 Cl K 2 O CaO TiO 2 Fe 2 O 3 Cr 2 O3 L.O.I Amount (%) 95.91 0.14 0.66 0.77 0.33 0.88 0.52 0.75 3.3.2. FTIR analysis Figure 12 presents the FTIR spectrum of the precipitated nanosilica produced in this study. The FTIR spectrum displays a broad and strong band at a wavenumber of approximately 1091 cm⁻¹, corresponding to the asymmetric stretching vibrations of the Si-O-Si group. Additionally, a less intense band is observed between 1173 and 1190 cm⁻¹, attributed to the symmetric stretching vibrations of the Si-O-Si group. These strong bands are characteristic of silica (SiO₂). Absorption peaks observed at 3450, 2925, and 1635 cm⁻¹ are likely related to Si-OH bonds, indicating the presence of water that remains within the silica network even after calcination in the furnace. Overall, the FTIR spectrum confirms the formation of precipitated nanosilica. 3.3.3. SEM analysis The produced precipitated silica powder was scanned using a field-emission scanning electron microscope (FESEM), and the results are presented in Fig. 13 . The particle sizes are highlighted in the images, revealing that the particle size ranges from 20 to 30 nanometers. This observation aligns well with the characteristics of precipitated nanosilica. 3.3.4. BET analysis The BET analysis was performed for the precipitated silica sample. Based on the results of this analysis, the specific surface area of the precipitated silica is 91.25m²/g, the pore volume is 0.9525cm³/g, the average pore diameter is 41.809nm, and the Langmuir surface area is 117.78m²/g. The nitrogen adsorption/desorption isotherm for the precipitated nanoslica (Fig. 14 ) reveals critical insights into the textural properties of the precipitated silica. The isotherm typically exhibits a type IV pattern, characteristic of mesoporous materials, with a clear hysteresis loop indicating capillary condensation within the pores. The presence of a hysteresis loop suggests the material contains uniform mesopores. 4. Conclusion The findings of this study indicate that dissolving granite powder in sodium hydroxide solution is extremely challenging. Under the optimized dissolution conditions (1.5M NaOH concentration, 80°C dissolution temperature, 2.5h dissolution time, and stirring speed of 900rpm, only 0.76g of material dissolves from a 20g sample. Neither increasing molarity nor temperature significantly enhances dissolution. Similar studies involving other mineral materials also report low dissolution percentages. Fine grinding, roasting the material at temperatures above 1000°C to disrupt the silica mineral lattice, or conducting pressure dissolution could potentially improve efficiency. In the precipitation phase, under optimized conditions (pH 7, 60°C precipitation temperature, 1.5h precipitation time, and stirring speed of 1000rpm), only 0.149g of precipitated nanosilica is obtained from the 0.76g of dissolved material, equating to a yield of approximately 20%, which is notably low. This might be attributed to the diluted nature of the resulting sodium silicate solution from dissolution. Despite this, the quality of the precipitated silica, including particle size and purity, the specific surface area, the pore volume meets the expected quality standards for industrial applications, particularly in the tire manufacturing industry. Considering the strategic importance of producing precipitated silica, further research is necessary in this field. Alternative raw materials with higher silica content could be explored, but significant improvement in dissolution percentages is unlikely. Instead, efforts should focus on optimizing dissolution and precipitation conditions to improve process efficiency and yield. Declarations Acknowledgments : The authors would like to express their sincere gratitude to Lorestan University for its support. Special thanks are extended to the Mineral Processing Laboratory and the Central Laboratory for providing the necessary facilities and equipment for conducting the experiments. Funding: The authors did not receive any financial support for the research, authorship, and/or publication of this paper. References P. Degryse and J. Elsen, Industrial minerals: resources, characteristics, and applications , vol. 13. Leuven University Press, 2003. E. D. E. R. Hyde, A. Seyfaee, F. Neville, and R. Moreno-Atanasio, “Colloidal silica particle synthesis and future industrial manufacturing pathways: a review,” Ind. Eng. Chem. Res. , vol. 55, no. 33, pp. 8891–8913, 2016. J. Neethirajan, A. Parathodika, G. Hu, and K. Naskar, “Functional rubber composites based on silica-silane reinforcement for green tire application: the state of the art. Funct Compos Mater 3: 7.” 2022. “Precipitated Silica Market Size & Growth Analysis Report,” 2022. [Online]. Available: https://www.grandviewresearch.com/industry-analysis/precipitated-silica-market B. Shoul, Y. Marfavi, B. Sadeghi, E. Kowsari, P. Sadeghi, and S. Ramakrishna, “Investigating the potential of sustainable use of green silica in the green tire industry: A review,” Environ. Sci. Pollut. Res. , vol. 29, no. 34, pp. 51298–51317, 2022. M. Lolage, P. Parida, M. Chaskar, A. Gupta, and D. Rautaray, “Green Silica: Industrially scalable & sustainable approach towards achieving improved ‘nano filler--Elastomer’ interaction and reinforcement in tire tread compounds,” Sustain. Mater. Technol. , vol. 26, p. e00232, 2020. F. S. Mahmood, H. Q. Hussein, and Z. T. Abdulwahhab, “Preparation and characterization of high surface area nanosilica from Iraqi sand via sol-gel technique,” J. Pet. Res. Stud. , vol. 12, no. 4, pp. 104–117, 2022. E. A. Negash, B. B. Tesfamariam, G. A. Asrat Mengesha, Y. Shasho, Y. S. Mekuriya, and S. T. Beyene, “High-Purity Amorphous Silica from Industrial Filter Cake Waste: Synthesis and Process Optimization,” Mater. Res. Express , 2024. G. Prameswara et al. , “Silica precipitation from rice husk ash leachate: optimization and kinetic analysis,” Chem. Pap. , pp. 1–7, 2024. V. Mamidi, R. Katakojwala, and S. V. Mohan, “Amorphous nano-silica from sugarcane bagasse ash--process optimization, characterization, and sustainability analysis,” Biomass Convers. Biorefinery , pp. 1–13, 2024. M. Sulaiman, N. I. D. Iya, and M. Aliyu, “Synthesis of silica nanoparticles from sugarcane waste: Precipitation-based size control and characterization,” FUDMA J. Sci. , vol. 8, no. 03, pp. 222–227, 2024. K. . . Ayinla, A. A. Baba, S. K. Padhy, O. Adio, K. A. Odeleye, and B. C. Tripathy, “Synthesis and characterization of pure silica powder from a k-feldspar silicate ore for industrial value addition,” Commun. Fac. Sci. Univ. Ankara Ser. B Chem. Chem. Eng. , vol. 61, no. 1, pp. 69–87, 2019. K. Srivastava, N. Shringi, V. Devra, and A. Rani, “Pure silica extraction from perlite: Its characterization and affecting factors,” Int. J. Innov. Res. Sci. Eng. Technol. , vol. 2, no. 7, pp. 2936–2942, 2013. M. Shiva and others, “Study of operating conditions of silica extraction from rice husk for Special use in rubber,” J. Appl. Res. Chem. Eng. , vol. 5, no. 2, pp. 65–77, 2021. N. Raza, W. Raza, S. Madeddu, H. Agbe, R. V Kumar, and K.-H. Kim, “Synthesis and characterization of amorphous precipitated silica from alkaline dissolution of olivine,” RSC Adv. , vol. 8, no. 57, pp. 32651–32658, 2018. E. Febriana et al. , “Dissolution of quartz sand in sodium hydroxide solution for producing amorphous precipitated silica,” in IOP Conference Series: Materials Science and Engineering , 2020, p. 12047. R. Sharafudeen et al. , “Preparation and characterization of precipitated silica using sodium silicate prepared from Saudi Arabian desert sand,” Silicon , vol. 9, pp. 917–922, 2017, doi: 10.1007/s12633-016-9531-8. A. Mourhly, M. Khachani, A. El Hamidi, M. Kacimi, M. Halim, and S. Arsalane, “The synthesis and characterization of low-cost mesoporous silica SiO2 from local pumice rock,” Nanomater. Nanotechnol. , vol. 5, p. 35, 2015. K. Srivastava, N. Shringi, V. Devra, and A. Rani, “A facile method for production of amorphous silica from perlite under microwave irradiation,” Int. J. IT, Eng. Appl. Sci. Res. , vol. 4, no. 1, pp. 18–24, 2015. I. Abdellaoui, M. M. Islam, T. Sakurai, S. Hamzaoui, and K. Akimoto, “Impurities removal process for high-purity silica production from diatomite,” Hydrometallurgy , vol. 179, no. April, pp. 207–214, 2018, doi: 10.1016/j.hydromet.2018.06.009. A. Martell, Critical stability constants: inorganic complexes . Springer Science & Business Media, 2013. F. K. Crundwell, “The dissolution and leaching of minerals: Mechanisms, myths and misunderstandings,” Hydrometallurgy , vol. 139, pp. 132–148, 2013. A. Vignes, Extractive metallurgy 2: metallurgical reaction processes . John Wiley & Sons, 2013. A. A. S. Navarro and B. V. Salas, “Synthesis of silica nanoparticles from sodium metasilicate,” Int. J. Nanoparticles , vol. 14, no. 1, pp. 1–12, 2022. E. A. Gorrepati, P. Wongthahan, S. Raha, and H. S. Fogler, “Silica precipitation in acidic solutions: mechanism, pH effect, and salt effect,” Langmuir , vol. 26, no. 13, pp. 10467–10474, 2010. M. Sholeh, R. Rochmadi, H. Sulistyo, and B. Budhijanto, “Nanostructured silica from bagasse ash: the effect of synthesis temperature and pH on its properties,” J. Sol-Gel Sci. Technol. , vol. 97, pp. 126–137, 2021. K. Quarch, E. Durand, C. Schilde, A. Kwade, and M. Kind, “Mechanical fragmentation of precipitated silica aggregates,” Chem. Eng. Res. Des. , vol. 88, no. 12, pp. 1639–1647, 2010. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6416965","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":457267529,"identity":"b09f5646-6239-45d5-92fb-206c79ad5d42","order_by":0,"name":"Atefeh Saeidi","email":"","orcid":"","institution":"Lorestan University","correspondingAuthor":false,"prefix":"","firstName":"Atefeh","middleName":"","lastName":"Saeidi","suffix":""},{"id":457267530,"identity":"dc5f40ec-a0dd-4083-9264-6ebf22b6bb28","order_by":1,"name":"Kianoush Barani","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuUlEQVRIiWNgGAWjYBACAyhpwM8OEeAhXotkM2lagLTBYWIdZs5+9uHnggIGY+PDPAYMP2oYZMwbCGix7Ek3lp5hwGBmBtTC2HOMgUfmACGHHUhjkAaabwPSwsDbwMAjQchhBuefMf8GaTFuBtrylygtN9LYQLaYGTDzGDATZYvljGds1jwGEsYSh9kKDssckyCsxZw/jfk2zx8bw/725o0P39TY2BPUAgUQdQdgjFEwCkbBKBgFFAIAg6MsOYOgoAgAAAAASUVORK5CYII=","orcid":"","institution":"Lorestan University","correspondingAuthor":true,"prefix":"","firstName":"Kianoush","middleName":"","lastName":"Barani","suffix":""}],"badges":[],"createdAt":"2025-04-10 06:23:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6416965/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6416965/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82884187,"identity":"5776fb6c-a771-4685-a32d-7f9fcc480c32","added_by":"auto","created_at":"2025-05-16 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11:32:51","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":52775,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of stirring speed on the dissolution percentage\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6416965/v1/c2cb101dfbf15f2912bf5af1.png"},{"id":82884191,"identity":"15b31f72-52a1-429e-ba93-bf4e1bd5affc","added_by":"auto","created_at":"2025-05-16 11:32:51","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":49683,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of dissolution time on the dissolution percentage\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-6416965/v1/ed801dc259d768e2e45951b1.png"},{"id":82884930,"identity":"3629de7f-4ecc-4e45-8a76-5408e77e7d55","added_by":"auto","created_at":"2025-05-16 11:40:51","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":55431,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of pH on the yield of precipitated silica\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-6416965/v1/7c9d7c1ee42752683761491e.png"},{"id":82884193,"identity":"04095b3e-680f-40cf-9e1c-372b0f2600fe","added_by":"auto","created_at":"2025-05-16 11:32:51","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":64441,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of temperature on the yield of precipitated silica\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-6416965/v1/b9fa2b11497c11617e79d486.png"},{"id":82884932,"identity":"c0e3044d-001b-43cb-a1f7-f4029cd64073","added_by":"auto","created_at":"2025-05-16 11:40:51","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":68236,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of stirring speed on the yield of precipitated silica\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-6416965/v1/a7d79cdab836904d98201110.png"},{"id":82884933,"identity":"e1197232-568c-4677-9a49-ac77cc03c591","added_by":"auto","created_at":"2025-05-16 11:40:51","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":65617,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of precipitation time on the yield of precipitated silica\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-6416965/v1/11d344f586048d242ff4c4d0.png"},{"id":82884197,"identity":"78e2c176-7886-4bce-9862-b03a5e645171","added_by":"auto","created_at":"2025-05-16 11:32:51","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":110385,"visible":true,"origin":"","legend":"\u003cp\u003eXRD spectrum of the precipitated silica\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-6416965/v1/34a505f1ac4f6de268965b2f.png"},{"id":82884206,"identity":"a6afe2ec-13b3-4a90-9309-634518c40b2b","added_by":"auto","created_at":"2025-05-16 11:32:51","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":410065,"visible":true,"origin":"","legend":"\u003cp\u003eFTIR spectrum of the precipitated silica\u003c/p\u003e","description":"","filename":"12.png","url":"https://assets-eu.researchsquare.com/files/rs-6416965/v1/569e4f446ba45bfc36ac90d8.png"},{"id":82884942,"identity":"b4cc7c04-85c8-4d2d-b914-61543d57ac89","added_by":"auto","created_at":"2025-05-16 11:40:51","extension":"png","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":922608,"visible":true,"origin":"","legend":"\u003cp\u003eSEM backscatter image\u003c/p\u003e","description":"","filename":"13.png","url":"https://assets-eu.researchsquare.com/files/rs-6416965/v1/3e963dad0ddfaa30de7af54d.png"},{"id":82884232,"identity":"6c5dca54-7cc4-4191-a979-e116acbce895","added_by":"auto","created_at":"2025-05-16 11:32:52","extension":"png","order_by":14,"title":"Figure 14","display":"","copyAsset":false,"role":"figure","size":90682,"visible":true,"origin":"","legend":"\u003cp\u003eThe nitrogen adsorption/desorption isotherm\u003c/p\u003e","description":"","filename":"14.png","url":"https://assets-eu.researchsquare.com/files/rs-6416965/v1/8c1dbe9d57d6fe8da6cff748.png"},{"id":93650996,"identity":"07a84ccf-943a-41b5-9b0d-f988fc9aee9d","added_by":"auto","created_at":"2025-10-16 05:47:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3651190,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6416965/v1/d14f7d3c-037b-4481-8519-6d3508aa154c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Production of Precipitated Nano-Silica from Granite Waste","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSilica (SiO₂), accounting for about 60% of the Earth's crust, is a fundamental oxide compound found in quartz and silicate minerals. It serves as a crucial raw material in industries such as glass, cement, and ceramics. Technological advancements have expanded its applications, especially in nanoscale amorphous forms.[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAmorphous silica exists in three types: fumed silica, precipitated silica, and silica gel. While precipitated silica and silica gel share an amorphous structure, they differ in production methods and properties. Precipitated silica, characterized by its less porous structure and smaller internal surface area compared to silica gel, features a higher specific surface area, making it the most commercially significant type [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePrecipitated nanosilica is widely utilized across industries due to its high surface area, reactivity, and versatility. It serves as a reinforcing agent in rubber and polymer composites, enhancing mechanical strength and durability. In electronics, it functions as an insulating material and filler in components, while in catalysis, coatings, and drug delivery systems, its biocompatibility and surface-modification capabilities are leveraged. Environmental applications include contaminant removal from air and water. One of the most significant uses of precipitated nanosilica is in tire manufacturing, especially for \"green tires\" introduced by Michelin in 1992. By integrating silica with carbon black, a silane coupling agent, and SSBR rubber in treads, critical tire properties such as modulus, tensile strength, abrasion resistance, and skid resistance are enhanced. Additionally, silica reduces fuel consumption by 3\u0026ndash;15%, improves skid performance, and extends tire lifespan. The silica content in passenger car tires typically ranges from 10\u0026ndash;30% by weight, depending on the model, size, and manufacturer [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe global precipitated silica market, valued at USD 2.15\u0026nbsp;billion in 2022, is projected to grow at a CAGR of 7.1% from 2023 to 2030. This growth is primarily driven by increasing demand from the rubber, agrochemical, and oral care industries. Among its applications, tire manufacturing represents the largest market share for precipitated silica [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFor tire-grade silica, the preferred particle size ranges from 5 to 200nanometers (nm). Smaller particles provide a larger surface area, enhancing reinforcement and adhesion properties for improved traction and reduced rolling resistance, while larger particles offer better wear resistance and heat dissipation. The particle size distribution and surface area, typically between 150 and 300m\u0026sup2;/g, can be optimized for specific tire applications. Silica used in tires generally has a bulk density of 650\u0026ndash;750kg/m\u0026sup3; and requires high chemical purity (\u0026ge;\u0026thinsp;99%) to avoid performance-impacting contaminants. This ensures the silica's effectiveness in reinforcing tire compounds, contributing to better fuel efficiency, traction, and durability [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePrecipitated silica is commonly produced via two industrial methods: the pyrometallurgical and hydrometallurgical processes. In the pyrometallurgical method, sodium carbonate and quartz are melted at high temperatures (1300\u0026ndash;1500\u0026deg;C) to produce sodium silicate, a glassy, water-soluble material. This sodium silicate is leached with hot water under 4\u0026ndash;5bar pressure in reactors, forming \"water glass\" or liquid sodium silicate. Precipitated silica is then obtained by neutralizing the sodium silicate solution with a mineral acid, such as sulfuric acid, through a controlled reaction. [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]:\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:Na₂SiO₃\\:\\left(aq\\right)\\:+\\:H₂SO₄\\:\\left(aq\\right)\\:\\to\\:\\:SiO₂\\:\\left(s\\right)\\:+\\:Na₂SO₄\\:\\left(aq\\right)$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe hydrometallurgical method extracts silica from silica-rich sources using solvents such as acids, bases, or salts. Acids like sulfuric and hydrochloric acid effectively dissolve silica but often co-dissolve impurities like iron, contaminating the final product. Alkaline solvents, such as sodium hydroxide, are preferred due to their reduced dissolution of impurities, though they exhibit lower dissolution power overall. In this method, silica is obtained either as silicic acid or a metasilicate solution, depending on the process conditions. The reaction for silica dissolution using sodium hydroxide is as follows [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]:\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:SiO₂\\:\\left(s\\right)\\:+\\:2NaOH\\:\\left(aq\\right)\\:\\to\\:\\:Na₂SiO₃\\:\\left(aq\\right)\\:+\\:H₂O\\:\\left(l\\right)$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe hydrometallurgical method produces precipitated silica by neutralizing the leach solution, offering greater energy efficiency than the pyrometallurgical method as it operates without high temperatures. Efforts to optimize this process include identifying suitable feedstocks, such as agricultural residues (e.g., rice husk, rice straw, bagasse ash, and sugarcane bagasse residue), silica-rich minerals (e.g., olivine, feldspar, perlite, and bentonite), and industrial waste (e.g., fly ash). The choice of raw material is influenced by availability, cost, silica purity, and the level of associated impurities. [\u003cspan additionalcitationids=\"CR10 CR11 CR12\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u0026ndash;[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe extraction of silica from rice husk for tire manufacturing was studied under specific conditions. The rice husk was first burned in an open environment and then converted into ash using an electric furnace. The ash was treated with caustic soda to produce a sodium silicate solution, from which silica was precipitated using sulfuric acid. The resulting silica matched the chemical purity of commercially available tire-grade silica but had a lower specific surface area (86.6\u0026ndash;106.8m\u0026sup2;/g) and smaller pore volume (0.63\u0026ndash;1.29cm\u0026sup3;/g) compared to commercial standards [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAmorphous precipitated silica (APS) was synthesized from olivine using a mixture of NaOH and KOH for alkaline dissolution. The combination of solvents achieved higher dissolution efficiency compared to single solvents. Key parameters, including alkali concentration, liquid/solid ratio, reaction time, and temperature, were optimized for maximum APS recovery. The resulting APS, with particle sizes below 10 nm, demonstrated properties ideal for applications in polymers and catalysis, such as a pore width of 5.59 nm, a cumulative pore volume of 0.96cm\u0026sup3;/g, a BET surface area of 670.8m\u0026sup2;/g, and a Langmuir surface area of 859.3m\u0026sup2;/g. [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe dissolution of quartz sand in sodium hydroxide to form silica precipitate was investigated using the leaching method at atmospheric pressure. The effects of sodium hydroxide concentration, temperature, dissolution time, and stirring rate were examined, all of which positively influenced silica formation. Despite a high SiO₂ concentration in the feed material, the extraction rate remained low, with temperature being the most influential factor. The optimal conditions for silica precipitate formation were found to be at 90\u0026deg;C, with a stirring speed of 800 rpm and a 7.5M sodium hydroxide solution, yielding 13.6% silica precipitate [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA cost-effective process for utilizing Saudi Arabian desert sand to produce sodium silicate and precipitated silica was explored. Sodium silicate was synthesized via an alkali fusion method, followed by acid precipitation to obtain pure precipitated silica. The weight ratio of alkali to sand was optimized, resulting in a silica yield of about 80%. The silica produced was characterized using wet chemical methods, FTIR, TG-DTA, XRD, and SEM. XRD analysis revealed an amorphous silica peak at a diffraction angle of 21.8\u0026deg;, confirming the amorphous nature of the silica[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAmorphous silica nanoparticles were successfully extracted from grey pumice powder using an optimized alkaline treatment followed by acid precipitation. Pumice, a porous volcanic rock rich in silica and alumina with low iron content, offers potential for applications in adsorption, catalysis, and nanotechnology. The synthesized SiO₂ was characterized using XRD, FTIR, TEM-EDS, N₂ adsorption/desorption, and TG/DTA techniques. The results showed that the nanosilica had a mesoporous structure, a high surface area of 422m\u0026sup2;/g, and particle sizes ranging from 5 to 15nm, confirmed by TEM and XRD. Thermal analysis indicated a 6.5% mass loss due to water and silanol group removal, demonstrating the feasibility of using pumice for large-scale production of amorphous silica nanopowder. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA method for producing amorphous silica from perlite under microwave irradiation was developed, focusing on the effects of NaOH concentration, microwave irradiation time, and temperature on SiO₂ yield. The process consisted of alkali solubilization, gel formation, and acid dissolution. Characterization was performed using XRF, BET surface area, XRD, FTIR, and SEM-EDS techniques. The highest SiO₂ yield (94.48%) was achieved with 4N NaOH at 90\u0026deg;C for 15min, resulting in amorphous silica with a surface area of approximately 104m\u0026sup2;/g. EDS analysis confirmed silicon as the predominant element, and XRD and FTIR data indicated increased amorphous characteristics, along with the presence of silanol and siloxane groups. This innovative process offers an efficient and sustainable method for producing high-purity amorphous silica from perlite, a solid waste material. [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA novel chemical process was developed to extract high-purity silica (99.99 wt%) from diatomite. The method involved acid dissolution of raw diatomite, alkali solubilization to form sodium silicate, and precipitation of silica gel using sulfuric acid. The silica gel was further purified by washing with 6M hydrochloric acid at elevated temperatures for three hours. Morphological and chemical analyses, including SEM, XRF, XRD, and ICP-OES, showed that the raw diatomite contained over 80 wt% amorphous microporous silica with particle sizes of 10\u0026ndash;35\u0026micro;m. Stepwise acid dissolution increased the silica content to 90.2 wt%. Furthermore, boron was reduced by 70% using mannitol as a complexing agent during the final acid washing, resulting in ultra-high-purity silica suitable for advanced applications [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePrecipitated silica is a strategic raw material for the industry. To mitigate the risks associated with its supply, achieving the technology for producing this vital material is of great importance. Given the abundance of silica-containing mineral resources in the world, producing precipitated silica from these sources is preferred over others. The aim of this research is to develop the knowledge for production of precipitated silica from mineral resources. In the extraction and processing of dimension stones, 50\u0026ndash;70% of the stone is turned into waste, which is often unusable and poses environmental challenges. This study investigates the production of precipitated silica from granite waste.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Sample Preparation\u003c/h2\u003e \u003cp\u003eA 10kg sample of waste granite (broken slabs with dimensions ranging from 12 to 17cm) was collected from stone processing plants. The sample was then crushed using jaw, cone, and roller crushers to reduce the size to below 3 mm. The crushed material was homogenized and then divided into 1kg subsamples using riffle splitting. One of the 1kg subsamples was ground in a ball mill to achieve a particle size of 100% below 100\u0026micro;m. The ground product was spread and homogenized on a plate, and then 100 subsamples, each weighing 10g, were selected using a grid sampling method.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Sample characterization\u003c/h2\u003e \u003cp\u003eXRF analysis was performed on the sample to identify the oxides present. The results of the XRF analysis for the sample are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Based on these results, the most abundant oxides in the sample, in order of prevalence, are SiO₂, Al₂O₃, Na₂O, CaO, K₂O, Fe₂O₃, MgO, and TiO₂. To identify the phases present in the sample, XRD analysis was conducted on a 10g sample. The XRD spectrum of the sample is shown in the Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. According to the analysis, the major phases identified in the sample are quartz and albite.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eXRF analysis of the feed material (granite waste)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComposition\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSiO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAl\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFe\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCaO\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMgO\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTiO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eK\u003csub\u003e2\u003c/sub\u003eO\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmount\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80.77%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.29%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.92%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.79%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.33%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.58%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComposition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP\u003csub\u003e2\u003c/sub\u003eO5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCr\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMnO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eZnO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSrO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eZrO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmount\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.82%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e500ppm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e450ppm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e300ppm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e450ppm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e300ppm\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Dissolution experiments\u003c/h2\u003e \u003cp\u003eThe sample was initially dried in an oven at 105\u0026deg;C for one hour, then weighed accurately. A specific portion of the dried sample was separated for each experiment. The measured sample was transferred into a 500mL Erlenmeyer flask equipped with a magnetic stirrer, preferably with variable speed control. To conduct the experiments, hydrochloric acid dissolution was employed to remove impurities. For this purpose, a 1 M hydrochloric acid solution (150mL) was prepared in a 500mL Erlenmeyer flask. The sample was then added to the prepared solution. The acid dissolution process was carried out at 60\u0026deg;C for 3h with a stirring speed of 300rpm, using a magnetic stirrer equipped with a heater. After the dissolution process, the mixture was filtered, and the residue was washed at least three times with deionized water on filter paper to ensure the removal of residual acid. The obtained solid residue (filter cake) was dried in an oven and subsequently weighed for alkali dissolution experiment.\u003c/p\u003e \u003cp\u003eAlkaline dissolution experiments were conducted on the filter cake obtained from the acid dissolution stage. Sodium hydroxide was used as the dissolution agent. For each experiment, 150mL of sodium hydroxide solution with the desired molarity was prepared in a 500mL laboratory Erlenmeyer flask. The filter cake from the acid dissolution stage was then added to the solution, and the alkaline dissolution process was carried out. In these experiments, the effects of various parameters, including sodium hydroxide concentration, sample mass, dissolution temperature, dissolution time, and stirring speed, were investigated. The range of these parameters is outlined below:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eSodium hydroxide concentration (mol/L): 0.25, 0.5, 1, 1.5, 2, 2.5\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSample mass (g): 5, 10, 15, 20\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eDissolution temperature (\u0026deg;C): 50, 60, 70, 80, 90, 100\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eDissolution time (h): 2, 2.5, 3, 3.5, 4, 4.5\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eStirring speed (rpm): 300, 500, 700, 900, 1100, 1300\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eA total of 48 dissolution experiments were conducted. After each experiment, the pulp was filtered, and the remaining filter cake was dried in an oven at 110\u0026deg;C for 2h. The dried sample was then weighed using a precision laboratory balance with an accuracy of 0.0001g. The dissolution percentage and dissolved mass were calculated using the following equations:\u003cdiv id=\"Equ3\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ3\" name=\"EquationSource\"\u003e\n$$\\:\\text{D}\\text{i}\\text{s}\\text{s}\\text{o}\\text{l}\\text{v}\\text{e}\\text{d}\\:\\text{M}\\text{a}\\text{s}\\text{s}\\:\\left(\\text{g}\\right)\\:=\\text{W}\\text{e}\\text{i}\\text{g}\\text{h}\\text{t}\\:\\text{a}\\text{f}\\text{t}\\text{e}\\text{r}\\:\\text{a}\\text{c}\\text{i}\\text{d}\\:\\text{d}\\text{i}\\text{s}\\text{s}\\text{o}\\text{l}\\text{u}\\text{t}\\text{i}\\text{o}\\text{n}\\:\\left(\\text{g}\\right)\\:-\\:\\text{W}\\text{e}\\text{i}\\text{g}\\text{h}\\text{t}\\:\\text{a}\\text{f}\\text{t}\\text{e}\\text{r}\\:\\text{a}\\text{l}\\text{k}\\text{a}\\text{l}\\text{i}\\text{n}\\text{e}\\:\\text{d}\\text{i}\\text{s}\\text{s}\\text{o}\\text{l}\\text{u}\\text{t}\\text{i}\\text{o}\\text{n}\\:\\left(\\text{g}\\right)$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ4\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ4\" name=\"EquationSource\"\u003e\n$$\\:Dissolution\\:Percentage\\:=\\:\\frac{Dissolved\\:Mass\\:\\left(g\\right)}{\\:Total\\:initial\\:weight\\:\\left(g\\right)}\\:\\:\\times\\:\\:100$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Precipitation experiments\u003c/h2\u003e \u003cp\u003ePrecipitation experiments were conducted on cooled alkaline leach solutions. Sulfuric acid was used as the precipitating agent. In each experiment, 500mL of the cooled alkaline leach solution was transferred into a laboratory Erlenmeyer flask. Separately, 100mL of 1 M sulfuric acid solution was prepared. The alkaline leach solution was placed on a magnetic stirrer equipped with a heater, and its temperature was raised to the desired level. Subsequently, the sulfuric acid solution was added dropwise over a period of 0.5 to 1h until the pH of the solution reached neutral pH. Upon the formation of a white gel-like precipitate, the heating was turned off, and the mixture was left undisturbed at room temperature for 24 h. The effects of various parameters on the precipitation process, including the final pH of the solution, precipitation temperature, precipitation time, and stirring speed, were investigated. The ranges of these parameters are as follows:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eSolution pH: 5, 6, 7, 8\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePrecipitation temperature (\u0026deg;C): 60, 70, 80, 90\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eStirring speed (rpm): 400, 700, 1000, 1300\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePrecipitation time (h): 0.5, 1, 1.5, 2\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eA total of 16 precipitation experiments were conducted. After each experiment, the precipitate was filtered and separated. The filter cake was washed with deionized water and dried in an oven at 40\u0026deg;C for 24h, then weighed.To remove impurities, the dried filter cake was washed with 1 M hydrochloric acid at a stirring speed of 700rpm and a temperature of 80\u0026deg;C for 3h. The washed sample was then filtered, dried in an oven, and weighed again. Finally, the sample was calcined in a furnace at 800\u0026deg;C for 1h. The final calcined sample was weighed, and the optimization of the precipitation experiments was done based on the final weight after calcination.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Characterization of precipitated silica (product)\u003c/h2\u003e \u003cp\u003eBased on the optimized conditions for dissolution and precipitation, a quantity of precipitated silica was produced. To determine the characteristics of the product, X-ray diffraction (XRD) was performed to identify the phases present in the sample. Scanning electron microscopy (SEM) was used to measure particle size and examine surface morphology, BET analysis was conducted to determine the particle size, specific surface area, and porosity of the product. Additionally, Fourier-transform infrared spectroscopy (FTIR) was conducted to identify the chemical bonds and functional groups in the sample.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results and discussion","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Dissolution experiments\u003c/h2\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e3.1.1. Effect of sodium hydroxide concentration\u003c/h2\u003e \u003cp\u003eIn a chemical reaction, increasing the solvent concentration can enhance dissolution; however, excessively high concentrations may lead to increased solution viscosity and reduced mass transfer rates. Furthermore, higher concentrations might trigger undesirable side reactions. Therefore, optimizing the solvent concentration is critical to achieving maximum dissolution and process efficiency [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e illustrates the effect of sodium hydroxide concentration on the dissolution percentage of the ore for different feed masses. In these experiments, the dissolution duration was 2h, the stirring speed was 300rpm, and the temperature was maintained at 60\u0026deg;C. The results indicate that, overall, the percentage of dissolved mass is quite low, with dissolution percentages remaining below 4% even under optimal conditions. Additionally, increasing the molarity of sodium hydroxide has a limited impact on the dissolution percentage.\u003c/p\u003e \u003cp\u003eWhen the initial feed mass was 5g, increasing the solvent concentration from 0.25 M to 2.5 M resulted in a near-linear increase in dissolution, from 9\u0026ndash;11%. However, the main goal is to achieve the highest amount of dissolved mass. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the effect of sodium hydroxide concentration on the dissolved mass for different feed masses. The highest dissolved mass (2.56g) was obtained when the initial feed mass was 20g and the solvent concentration was 1.5M. In other cases, the dissolved mass was significantly lower, typically less than 1.5g. Overall, the dissolution efficiency is notably low. For subsequent experimental stages, a feed mass of 20g and a solvent concentration of 1.5M were selected as the optimum conditions.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e3.1.2. Effect of temperature\u003c/h2\u003e \u003cp\u003eIn a chemical reaction, increasing the reaction temperature leads to more frequent collisions between molecules in the solution, thereby accelerating the dissolution process. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e illustrates the effect of temperature variations on the ore dissolution percentage. In these experiments, the initial feed mass was 20g, the dissolution time was 2h, the stirring speed was 300rpm, and the solvent concentration was 1.5M. It is observed that as the temperature increases from 50\u0026deg;C to 100\u0026deg;C, the dissolution percentage follows an increasing trend, rising from 3\u0026ndash;3.5%. The effect of increasing temperature on the dissolution is negligible. As the temperature increases from 50\u0026deg;C to 100\u0026deg;C, the dissolution percentage increases by only 0.5%. Due to difficulties in controlling the experiment at temperatures of 90\u0026deg;C and 100\u0026deg;C, 80\u0026deg;C was chosen as the optimal temperature and used in subsequent experiments.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e\u003cb\u003e3.1.3. Effect of stirring speed\u003c/b\u003e\u003c/h2\u003e \u003cp\u003eThe stirring speed in a chemical reaction process can significantly enhance the reaction rate. Stirring not only accelerates the interaction between reactants but also aids in maintaining uniform temperature distribution throughout the process [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Figure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e illustrates the effect of stirring speed on the dissolution of the ore. In these experiments, the initial sample mass was 20g, the solvent concentration was 1.5mol/L, the dissolution time was 2h, and the dissolution temperature was 80\u0026deg;C. It was observed that increasing the stirring speed from 300 to 1300rpm resulted in an increase in the dissolution percentage from 2.5\u0026ndash;3.7%. This finding highlights the ore's high resistance to alkaline dissolution. A stirring speed of 900rpm was identified as the optimal condition and was adopted for subsequent experiments.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e\u003cb\u003e3.1.4. Effect of dissolution time\u003c/b\u003e\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e illustrates the effect of time on the dissolution of the ore. These experiments were conducted with an initial sample weight of 20g, a dissolution temperature of 80\u0026deg;C, a stirring speed of 900rpm, and a solvent concentration of 1.5mol/L. The results show that the highest dissolution percentage (3.8%) was achieved at a time of 2.5h, with dissolution decreasing at longer dissolution durations. The limited effect of extended time on dissolution percentages can be attributed to several factors. As the dissolution process progresses, the solution may approach saturation, reducing the driving force for mass transfer. Additionally, the formation of product layers or precipitates on the ore surface can inhibit further reaction. If the process is reaction-controlled, the dissolution may plateau over time. Furthermore, easily soluble phases may dissolve early, leaving more refractory phases behind. Lastly, the thermodynamic driving force diminishes as the system approaches equilibrium. These factors collectively limit the impact of prolonged dissolution on efficiency[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003e3.1.5. Optimal dissolution conditions\u003c/h2\u003e \u003cp\u003eBased on the results of the dissolution experiments, the optimal conditions were determined as follows: an initial mass of 20g, a sodium hydroxide concentration of 1.5mol/L, a dissolution temperature of 80\u0026deg;C, a dissolution time of 2.5h, and a stirring speed of 900rpm. These conditions were selected for the dissolution stage and applied in the subsequent precipitation stage experiments. It is predicted that under optimal conditions, approximately 3.8% of the initial sample mass, equivalent to 0.76g, will dissolved.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Precipitation experiments\u003c/h2\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003e3.2.1. Effect of pH\u003c/h2\u003e \u003cp\u003eThe pH plays a crucial role in the precipitation of silica from sodium metasilicate solutions when sulfuric acid is added. At lower pH levels, the silica (SiO₂) begins to hydrolyze and form hydroxyl groups, which leads to the formation of a silica network. However, as the pH increases, more hydroxyl groups are formed, resulting in the polymerization of silica molecules into a gel-like structure. When the pH is decreased further by the addition of sulfuric acid, the silica network breaks down, promoting its precipitation. The optimal pH range for efficient silica precipitation is generally between 6 and 7, as higher pH values may lead to unwanted side reactions and lower precipitation efficiency. Therefore, precise control of pH is essential to enhance the purity and yield of the precipitated silica [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e shows the effect of pH variations on the yield of precipitated silica. In these precipitation experiments, the temperature was set at 90\u0026deg;C, the duration was 0.5h, and the stirring speed was 1000rpm. It can be observed that as the pH increases from 5 to 7, the yield of precipitated silica increases from 0.012g to 0.020g. However, with a further increase in pH from 7 to 8, the yield of silica decreases to 0.010g. At lower pH (around 5), the silicate ions remain predominantly in a dissolved state, and the environment is not favorable for silica polymerization and precipitation. As the pH approaches 7, the reaction between sulfuric acid and sodium silicate facilitates the formation of solid silica, leading to an increase in the amount of precipitated silica. When the pH increases further to 8, the conditions shift towards the re-dissolution of silica. At this higher pH, silicate ions tend to remain in the solution as dissolved species rather than forming solid silica. At this stage, a pH of 7 was selected as the optimal pH and used in subsequent experiments.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e \u003ch2\u003e3.2.2. Effect of temperature\u003c/h2\u003e \u003cp\u003eAt higher temperatures, the rate of hydrolysis and polymerization of silica increases, promoting faster precipitation. This is because elevated temperatures enhance the collision frequency between molecules, accelerating the dissolution and subsequent precipitation of silica. However, excessively high temperatures may lead to the formation of larger, less stable silica aggregates, which can reduce the purity and yield of the final product. Therefore, controlling temperature is essential to optimize the precipitation process, with moderate temperatures typically providing the best results. For silica precipitation from sodium metasilicate, temperatures around 80\u0026ndash;90\u0026deg;C are commonly used to achieve efficient and controlled precipitation[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Figure\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e shows the effect of temperature variations on the yield of silica precipitated. In these experiments, the pH was maintained at neutral (7), the precipitation time was 0.5h, and the stirring speed was set to 1000rpm. It can be observed that as the temperature increased from 60 to 90\u0026deg;C, the amount of silica precipitated decreased from 0.112g to 0.02g, following a decreasing trend. The amount of silica produced decreased significantly with the temperature increase, with a 0.092% reduction observed for a 30\u0026deg;C rise. At higher temperatures, the stability of amorphous silica decreases. As a result, some of the silica that was previously formed as a precipitate may re-dissolve into the solution. In this stage, a temperature of 60\u0026deg;C was selected as the optimal temperature and used in subsequent experiments.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003e3.2.3. Effect of stirring speed\u003c/h2\u003e \u003cp\u003eIncreasing the stirring speed typically enhances the rate of silica precipitation by improving the mixing of the reactants (silicate solution and sulfuric acid), which promotes more effective interactions between them. This improved contact leads to a more uniform distribution of the precipitate, enhancing the overall yield of silica. Very high stirring speeds may also hinder the formation of larger silica particles, or cause the formed silica to re-dissolve. Additionally, in some systems, intense stirring may lead to the formation of gas bubbles or foam, which can affect the precipitation dynamics and reduce the overall yield. Therefore, an optimal stirring speed is necessary to balance effective mixing with controlled particle size formation [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Figure\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e shows the effect of stirring speed variations on the yield of silica precipitated. In these experiments, the pH was neutral (7), the precipitation temperature was 60\u0026deg;C, and the precipitation time was 0.5h. It can be observed that as the stirring speed increased from 400 to 1000rpm, the yield of silica increased from 0.074g to 0.108g. However, with further increase in stirring speed to 1300rpm, the amount of silica decreased to 0.041g. At this stage, a stirring speed of 1000rpm was chosen as the optimal condition and was used in subsequent experiments.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e \u003ch2\u003e3.2.4. Effect of precipitation time\u003c/h2\u003e \u003cp\u003eIn general, longer precipitation times allow for more complete formation and accumulation of the silica. However, excessive precipitation time may lead to the re-dissolution of some of the precipitated silica. Over time, some particles may grow too large and, due to their weight, may not settle completely or may even remain suspended in the system. Additionally, over extended periods, the structure of the precipitated silica may change from amorphous to a gel-like or colloidal form. This structural change can reduce the efficiency of precipitation and lower the final yield. Hence, an optimal precipitation time must be identified to achieve the highest yield without unnecessary energy consumption or side reaction. Figure\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e illustrates the effect of precipitation time on the yield of silica precipitated. The experiments in this stage were conducted with a neutral pH (7), a temperature of 60\u0026deg;C, and a stirring speed of 1000rpm. It is observed that as the precipitation time increases from 0.5h to 1.5h, the yield of precipitated silica increases from 0.099g to 0.149g. However, further increasing the precipitation time to 2h results in a decrease in silica amount to 0.075g. Based on these results, a precipitation time of 1.5h was selected as the optimal condition for subsequent experiments.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e \u003ch2\u003e3.2.5. Optimal precipitation conditions\u003c/h2\u003e \u003cp\u003eBased on the results of the precipitation experiments, the optimal conditions for the precipitation stage are as follows: pH\u0026thinsp;=\u0026thinsp;7, precipitation temperature of 60\u0026deg;C, precipitation time of 1.5h, and stirring speed of 1000rpm. It is predicted that under these optimal conditions, approximately 0.149g of the initial sample will be converted to nano silica.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Characterization of precipitated silica\u003c/h2\u003e \u003cdiv id=\"Sec22\" class=\"Section3\"\u003e \u003ch2\u003e3.3.1. XRD and XRF analysis\u003c/h2\u003e \u003cp\u003eThe XRD spectrum of of the precipitate silica is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e. The broadening of the peak in the 20\u0026deg; \u0026le; 2θ\u0026thinsp;\u0026le;\u0026thinsp;30\u0026deg; range indicates that the produced material is amorphous, with no crystalline phases identified. The low intensity of the peak further suggests that the silica particles are fine in size.\u003c/p\u003e \u003cp\u003eThe results of the XRF analysis for the precipitated silica are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Based on these results, the silica content in the precipitated silica exceeds 95%, while other impurities are present in the following order of abundance: Fe₂O₃, CaO, K₂O, and Cr₂O₃. The precipitated silica produced is suitable for various industrial applications, including its use in tire manufacturing.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eXRF analysis of the precipitated silica\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComposition\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSiO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCl\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eK\u003csub\u003e2\u003c/sub\u003eO\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCaO\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTiO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eFe\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eCr\u003csub\u003e2\u003c/sub\u003eO3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eL.O.I\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmount (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003e3.3.2. FTIR analysis\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003e presents the FTIR spectrum of the precipitated nanosilica produced in this study. The FTIR spectrum displays a broad and strong band at a wavenumber of approximately 1091 cm⁻\u0026sup1;, corresponding to the asymmetric stretching vibrations of the Si-O-Si group. Additionally, a less intense band is observed between 1173 and 1190 cm⁻\u0026sup1;, attributed to the symmetric stretching vibrations of the Si-O-Si group. These strong bands are characteristic of silica (SiO₂). Absorption peaks observed at 3450, 2925, and 1635 cm⁻\u0026sup1; are likely related to Si-OH bonds, indicating the presence of water that remains within the silica network even after calcination in the furnace. Overall, the FTIR spectrum confirms the formation of precipitated nanosilica.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section3\"\u003e \u003ch2\u003e3.3.3. SEM analysis\u003c/h2\u003e \u003cp\u003eThe produced precipitated silica powder was scanned using a field-emission scanning electron microscope (FESEM), and the results are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003e. The particle sizes are highlighted in the images, revealing that the particle size ranges from 20 to 30 nanometers. This observation aligns well with the characteristics of precipitated nanosilica.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003e3.3.4. BET analysis\u003c/h2\u003e \u003cp\u003eThe BET analysis was performed for the precipitated silica sample. Based on the results of this analysis, the specific surface area of the precipitated silica is 91.25m\u0026sup2;/g, the pore volume is 0.9525cm\u0026sup3;/g, the average pore diameter is 41.809nm, and the Langmuir surface area is 117.78m\u0026sup2;/g.\u003c/p\u003e \u003cp\u003eThe nitrogen adsorption/desorption isotherm for the precipitated nanoslica (Fig.\u0026nbsp;\u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e14\u003c/span\u003e) reveals critical insights into the textural properties of the precipitated silica. The isotherm typically exhibits a type IV pattern, characteristic of mesoporous materials, with a clear hysteresis loop indicating capillary condensation within the pores. The presence of a hysteresis loop suggests the material contains uniform mesopores.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eThe findings of this study indicate that dissolving granite powder in sodium hydroxide solution is extremely challenging. Under the optimized dissolution conditions (1.5M NaOH concentration, 80\u0026deg;C dissolution temperature, 2.5h dissolution time, and stirring speed of 900rpm, only 0.76g of material dissolves from a 20g sample. Neither increasing molarity nor temperature significantly enhances dissolution. Similar studies involving other mineral materials also report low dissolution percentages. Fine grinding, roasting the material at temperatures above 1000\u0026deg;C to disrupt the silica mineral lattice, or conducting pressure dissolution could potentially improve efficiency.\u003c/p\u003e \u003cp\u003eIn the precipitation phase, under optimized conditions (pH 7, 60\u0026deg;C precipitation temperature, 1.5h precipitation time, and stirring speed of 1000rpm), only 0.149g of precipitated nanosilica is obtained from the 0.76g of dissolved material, equating to a yield of approximately 20%, which is notably low. This might be attributed to the diluted nature of the resulting sodium silicate solution from dissolution.\u003c/p\u003e \u003cp\u003eDespite this, the quality of the precipitated silica, including particle size and purity, the specific surface area, the pore volume meets the expected quality standards for industrial applications, particularly in the tire manufacturing industry. Considering the strategic importance of producing precipitated silica, further research is necessary in this field. Alternative raw materials with higher silica content could be explored, but significant improvement in dissolution percentages is unlikely. Instead, efforts should focus on optimizing dissolution and precipitation conditions to improve process efficiency and yield.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e:\u003c/p\u003e\n\u003cp\u003eThe authors would like to express their sincere gratitude to Lorestan University for its support. Special thanks are extended to the Mineral Processing Laboratory and the Central Laboratory for providing the necessary facilities and equipment for conducting the experiments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors did not receive any financial support for the research, authorship, and/or publication of this paper.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eP. Degryse and J. Elsen, \u003cem\u003eIndustrial minerals: resources, characteristics, and applications\u003c/em\u003e, vol. 13. Leuven University Press, 2003.\u003c/li\u003e\n\u003cli\u003eE. D. E. R. Hyde, A. Seyfaee, F. Neville, and R. Moreno-Atanasio, \u0026ldquo;Colloidal silica particle synthesis and future industrial manufacturing pathways: a review,\u0026rdquo; \u003cem\u003eInd. Eng. Chem. Res.\u003c/em\u003e, vol. 55, no. 33, pp. 8891\u0026ndash;8913, 2016.\u003c/li\u003e\n\u003cli\u003eJ. Neethirajan, A. 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Rautaray, \u0026ldquo;Green Silica: Industrially scalable \u0026amp; sustainable approach towards achieving improved \u0026lsquo;nano filler--Elastomer\u0026rsquo; interaction and reinforcement in tire tread compounds,\u0026rdquo; \u003cem\u003eSustain. Mater. Technol.\u003c/em\u003e, vol. 26, p. e00232, 2020.\u003c/li\u003e\n\u003cli\u003eF. S. Mahmood, H. Q. Hussein, and Z. T. Abdulwahhab, \u0026ldquo;Preparation and characterization of high surface area nanosilica from Iraqi sand via sol-gel technique,\u0026rdquo; \u003cem\u003eJ. Pet. Res. Stud.\u003c/em\u003e, vol. 12, no. 4, pp. 104\u0026ndash;117, 2022.\u003c/li\u003e\n\u003cli\u003eE. A. Negash, B. B. Tesfamariam, G. A. Asrat Mengesha, Y. Shasho, Y. S. Mekuriya, and S. T. Beyene, \u0026ldquo;High-Purity Amorphous Silica from Industrial Filter Cake Waste: Synthesis and Process Optimization,\u0026rdquo; \u003cem\u003eMater. Res. Express\u003c/em\u003e, 2024.\u003c/li\u003e\n\u003cli\u003eG. 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Des.\u003c/em\u003e, vol. 88, no. 12, pp. 1639\u0026ndash;1647, 2010.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"precipitated silica, dissolution, precipitation, granite, tire","lastPublishedDoi":"10.21203/rs.3.rs-6416965/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6416965/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePrecipitated nanosilica has diverse applications in advanced industries. One method for producing precipitated silica is through direct dissolution from mineral sources. This study investigates the production of nanostructured precipitated silica from granite waste powder. Initially, in the dissolution stage with sodium hydroxide, the effects of parameters such as solvent concentration, temperature, stirring speed, time, and sample mass were examined. The results showed that under optimal dissolution conditions (1.5M sodium hydroxide concentration, 80\u0026deg;C, 2.5h, and 900rpm stirring speed), only 0.76g of a 20g sample dissolved. In the precipitation stage, the effects of parameters like pH, temperature, time, and stirring speed were investigated. The results indicated that under optimal precipitation conditions (pH 7, 60\u0026deg;C, 1.5h, 1000rpm stirring speed), approximately 0.149g of nanostructured silica was obtained from the 0.76g of dissolved material. Both the dissolution and precipitation yields were very low, indicating the stability of silica in the granite sample. To enhance the efficiency, pressure dissolution, and calcination of the mineral material should be considered. Characterization of the produced precipitated silica using XRD, FTIR, BET, and SEM analyses revealed that it has the desirable quality for various industrial applications, including tire manufacturing.\u003c/p\u003e","manuscriptTitle":"Production of Precipitated Nano-Silica from Granite Waste","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-16 11:32:46","doi":"10.21203/rs.3.rs-6416965/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3ebf97ce-1450-4a79-9125-83afd8cca7f1","owner":[],"postedDate":"May 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-16T05:38:55+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-16 11:32:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6416965","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6416965","identity":"rs-6416965","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}