Optimization of Smithsonite Flotation Using ZnO and Al2O3 Nanocollectors: A Definitive Screening Design Approach

Optimization of Smithsonite Flotation Using ZnO and Al2O3 Nanocollectors: A Definitive Screening Design Approach | 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 Optimization of Smithsonite Flotation Using ZnO and Al 2 O 3 Nanocollectors: A Definitive Screening Design Approach Mohamad Meshkini, Mahdi Gharabaghi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5409694/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 30 Apr, 2025 Read the published version in Chemical Papers → Version 1 posted 5 You are reading this latest preprint version Abstract Conventional flotation techniques ores, often encounter challenges when applied to oxidized minerals. This limitation highlights the necessity for developing or improving flotation methods. In this study, the impact of ZnO and Al₂O₃ nanocollectors on smithsonite flotation was examined, and the process was optimized using a comprehensive Definitive Screening Design (DSD). Initially, ZnO and Al₂O₃ nanoparticles were synthesized and modified with sodium dodecyl sulfate (SDS). Characterization through TEM, XRD, and FTIR techniques confirmed the successful synthesis and modification of these nanocollectors. The flotation results indicated that ZnO and Al₂O₃ nanocollectors significantly enhanced recovery rates compared to conventional collectors, attributed to their increased surface area and improved interaction with smithsonite particles. The optimal flotation conditions were identified as a pH of 6.0, a pulp density of 7.0%, an air flow rate of 1.0 L/min, 360 g/t oleic acid, 180 g/t ZnO nanocollectors, 250 g/t Al₂O₃ nanocollectors, and 17 g/t A65 frother, achieving a peak recovery rate of 91.1%. Smithsonite Flotation Nanocollector Definitive Screening Design Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1. Introduction As global reserves of zinc sulfide ores continue to decline, the need for efficient methods to process nonsulfide zinc ores, such as smithsonite, is becoming increasingly critical [ 1 , 2 ]. Smithsonite presents a viable alternative to sulfide ores, though it poses distinct extraction challenges due to its complex composition. These ores frequently contain substantial amounts of carbonate gangue minerals, complicating the flotation process and leading to higher reagent consumption [ 3 ]. Additionally, smithsonite exhibits greater hydrophilicity, which necessitates more complex and energy-intensive processing techniques [ 4 – 6 ]. Case studies underscore the practical challenges and solutions in the flotation of smithsonite. The efficiency of the flotation process is influenced by several key parameters, including surfactant concentration, feed concentration, pH levels, bubble size, water flow rate, ionic strength, and temperature [ 7 ]. Comparative analyses of flotation behavior between smithsonite and other minerals, such as calcite, have yielded valuable insights for achieving selective flotation [ 8 – 10 ]. The effectiveness of various collectors and reagents has been extensively examined. Different collectors, such as dodecylamine (DDA) and potassium lauryl phosphate, have demonstrated varying levels of effectiveness. For instance, Hosseini and Forssberg found DDA to be effective when used in conjunction with sodium sulfide, while another study suggested that potassium lauryl phosphate offered better selectivity and recovery for smithsonite compared to calcite [ 11 ]. Traditional flotation methods, effective for sulfide ores, often fall short when applied to oxidized minerals, underscoring the need for novel or enhanced flotation techniques. Ongoing debates center around the optimal dosage of sodium sulfide, the effectiveness of various collectors, and the pH dependency of flotation processes. While some studies advocate for controlled sulfidization to maximize recovery rates, others emphasize the detrimental effects of oversulfidization [ 12 – 17 ]. Furthermore, the relative effectiveness of dodecylamine (DDA) and potassium lauryl phosphate as collectors remains a topic of contention [ 4 , 12 , 18 ]. Moreover, environmental concerns are crucial when assessing the use of flotation reagents, particularly in the context of sustainable mining practices [ 19 ]. The application of lead nitrate (Pb(NO₃)₂) and high concentrations of sulfide reagents in flotation processes has raised significant environmental challenges. The extensive use of sulfide reagents, such as sodium sulfide, can result in the generation of harmful by-products, including toxic gases like hydrogen sulfide (H₂S), which contribute to air and water pollution. The management and disposal of these reagents and their by-products require careful consideration to mitigate their environmental impact [ 12 , 20 , 21 ]. To address these concerns, the use of co-collectors is being explored as a strategy to minimize the reliance on toxic reagents. Co-collectors can enhance the efficiency of flotation processes, potentially allowing for lower dosages of harmful chemicals while still achieving desirable recovery rates. This approach not only reduces the environmental burden but also aligns with the principles of green chemistry. Researchers are actively investigating biodegradable or less toxic co-collectors as alternatives to traditional reagents, aiming to strike a balance between metallurgical performance and environmental sustainability. Innovative approaches, such as the use of nanocollectors and advanced flotation technologies, have shown significant promise in mineral flotation. Nanocollectors represent a groundbreaking advancement in this field, offering superior surface properties and reactivity due to their nanoscale dimensions. Unlike traditional bulk collectors, nanocollectors exhibit a higher surface area-to-volume ratio, resulting in more efficient adsorption on mineral surfaces and improved flotation performance [ 22 , 23 ]. The primary advantage of nanocollectors lies in their enhanced selectivity and adsorption efficiency compared to conventional bulk collectors. They interact more effectively with mineral surfaces, forming a uniform and densely packed adsorption layer. For example, nanocollectors can adsorb onto the negatively charged smithsonite surface at alkaline pH levels, particularly following sulfidization with Na₂S. This adsorption increases the hydrophobicity and flotation efficiency of smithsonite [ 24 ]. The flotation of smithsonite, a primary source of zinc, is crucial for zinc extraction across various industries, including batteries, coatings, and alloys. However, conventional flotation methods are often hampered by challenges such as suboptimal reagent efficiency, low selectivity, and environmental concerns. Recent studies emphasize the importance of refining reagent selection and optimizing flotation conditions to improve performance. Nanotechnology offers promising solutions, as nanoparticles exhibit unique surface properties and high reactivity, which can enhance interactions with mineral surfaces during flotation. Despite the growing interest in nanomaterials, there is a notable gap in research on the application of Al₂O₃ and ZnO nanoparticles as nanocollectors in smithsonite flotation. These nanocollectors could potentially enhance the process by increasing recovery rates, improving selectivity, and offering a more sustainable approach. This study aims to explore the effectiveness of Al₂O₃ and ZnO nanoparticles in enhancing smithsonite flotation performance. By systematically investigating their impact using a definitive screening design approach, this research seeks to address critical gaps in flotation chemistry and contribute to the development of more efficient and environmentally friendly mineral processing techniques. 2. Materials and methods 2.1. Sample The smithsonite samples used in this research were obtained from the Angouran mine, located in Zanjan province, Iran. These samples were first ground to achieve the d 80 below 10 µm, as illustrated in Fig. 1 a. The mineralogical composition of the smithsonite ore was analyzed using X-ray fluorescence (XRF), revealing a ZnO concentration of 63.61%. Additional constituents included 34.4% loss on ignition (LOI), 0.12% SO₃, 0.14% Na₂O, 0.2% MgO, 0.69% Fe₂O₃, 0.57% CaO, and 0.14% SiO₂. The total zinc content, measured at 48.92%, was determined through wet chemistry methods. The mineralogical phases were further investigated using X-ray diffraction (XRD), as shown in Fig. 1 b. 2.2. Reagents Armac C (cocoalkylamine acetate, 99%) and oleic acid (90%) were used as conventional collectors. Sodium sulfide (75%), sodium hydroxide (99%), and AeroFroth 65 (98%) were utilized as the sulfidizing reagent, modifier, and frother, respectively. Synthesized ZnO and Al₂O₃ were employed as nanocollectors. 2.3. ZnO nanoparticles synthesis Figure 2 a presents a schematic of the ZnO nanoparticle synthesis process. A bottom-up approach was employed for the synthesis of ZnO nanocollectors. Initially, 1.5 g of zinc acetate (99%) was dissolved in 65 mL of ethanol using a graduated cylinder and transferred to an Erlenmeyer flask. The solution was stirred on a magnetic stirrer at room temperature for 30 minutes to one hour until the zinc acetate was fully dissolved, resulting in a clear solution. Once dissolved, the temperature of the magnetic stirrer was gradually increased to evaporate the solvent and facilitate the formation of zinc oxide precipitates. The reaction proceeded until white precipitates appeared at the bottom of the flask, signaling the completion of the precipitation process. The precipitates were then dried at room temperature for two days and subsequently calcined in a furnace at 400°C for 14 hours to yield pure ZnO nanoparticles. 2.4. Al 2 O 3 nanoparticles synthesis Figure 2 b provides a schematic representation of the Al 2 O 3 nanoparticle synthesis process. To synthesize Al₂O₃ nanocollectors, 3 grams of aluminum nitrate (99%) and 0.5 grams of sucrose (99.5%) were dissolved in 50 milliliters of deionized water (DI) using a magnetic stirrer set at 35°C for one hour to prepare the precursor mixture. Ammonium nitrate solution was then added dropwise to the precursor mixture to control the pH, which is crucial for determining the morphology of the γ-Al₂O₃ nanoparticles. The addition of ammonium nitrate caused the solution to transition from clear to milky, indicating the formation of aluminum hydroxide particles. The mixture was transferred to a 75-milliliter autoclave and heated in a furnace at 300°C for 20 hours. Following the hydrothermal reaction, the resulting product was washed with ethanol and centrifuged to remove impurities. The washed product was then dried at 100°C and calcined at 900°C for five hours to convert the aluminum hydroxide to γ-Al₂O₃ nanoparticles. 2.5. Surface modification To enhance flotation performance, surface modification of the Al₂O₃ and ZnO nanoparticles was carried out using sodium dodecyl sulfate (SDS). In this process, 1 gram of the synthesized nanoparticles was dissolved in 15–20 milliliters of deionized water. A 5% SDS solution was then added to the mixture. The solution was stirred thoroughly at room temperature to ensure a uniform coating of the nanoparticles with SDS, thereby improving their interaction with minerals during the flotation process. Figure 3 a depicts a schematic of the modified ZnO and Al₂O₃ particles. 2.6. Flotation experiments This research employs an experimental design to assess the efficacy of various nanocollectors in improving smithsonite flotation recovery. The choice of this approach is based on the need to systematically control and manipulate variables such as pH, pulp density, and reagent dosages to accurately determine their effects on flotation performance. By utilizing a statistically rigorous design of experiments (DOE), specifically the Definitive Screening Design (DSD), we aim to thoroughly investigate both the main effects and interaction effects of these parameters. This methodological approach ensures the generation of reliable and reproducible data, providing a solid foundation for evaluating the effectiveness of nanocollectors in mineral processing applications. The flotation tests were organized according to a Definitive Screening Design (DSD) to evaluate the impact of multiple factors. The experimental design included several key variables: pH Levels : Three distinct pH levels—6.0, 9.0, and 12.0—were selected to assess their effect on the flotation process. Pulp Densities : Pulp densities of 3.0%, 5.0%, and 7.0% were tested to study their impact on particle interaction and slurry viscosity. Air Flow Rates : Air flow rates of 1.0 L/min, 3.0 L/min, and 5.0 L/min were varied to determine the optimal bubble size and froth stability. Oleic Acid Dosage : Dosages of oleic acid, a collector, were set at 0, 500, and 1000 g/Ton to investigate its effect on enhancing the hydrophobicity of smithsonite particles. Armac C Dosage : Armac C, another collector, was used at the same dosages as oleic acid for comparative effectiveness. ZnO Nanocollector Dosage : ZnO nanocollectors were tested at 0, 125, and 250 g/Ton to leverage their unique properties for improved recovery rates. γ-Al₂O₃ Nanocollector Dosage : γ-Al₂O₃ nanocollectors were similarly tested at 0, 125, and 250 g/Ton to evaluate their selective adsorption capabilities. Frother A65 Dosage : Frother A65 was added at concentrations of 0, 25, and 50 g/Ton to study its impact on froth formation and stability. For the flotation experiments, a custom-designed flotation cell with a height of 30 cm and a diameter of 4 cm was employed. The cell, as depicted in Fig. 3 b, featured a circular air sparger at the bottom to generate bubbles, with air supplied via a compressor. Each flotation test was conducted for a total duration of 4 minutes. Following the flotation process, both concentrate and tailings samples were filtered, dried in an oven, and weighed to calculate the recovery percentage using the formula: R = \(\:\frac{C}{F}\) Where C is the weight of the concentrate and F is the weight of the feed. Each test began with the preparation of a 5 g sample of smithsonite ore, which was mixed with deionized water and the specified chemical reagents. The pulp was conditioned on a magnetic stirrer, with conditioning times of 1 minute for frothers and 4 minutes for collectors. The reagent dosages were determined according to the experimental design table. The pH of the solution was adjusted to the desired level using sulfuric acid or sodium hydroxide. After conditioning, the pulp was transferred to the flotation cell. A controlled flow rate of wash water was applied at the top of the cell to maintain consistent conditions for froth removal. The flotation process was initiated by opening the air valve and continued for 4 minutes, during which froth was continuously collected. 3. Results and discussions 3.1. Characterizations of ZnO and Al₂O₃ nano particles Transmission Electron Microscopy (TEM) was employed to determine the particle size and morphology of the synthesized ZnO and Al₂O₃ nanocollectors. TEM analysis, as shown in Fig. 4a and 4b, revealed spherical ZnO and Al₂O₃ nanoparticles with average particle sizes of approximately 30 nm and 55 nm, respectively. This confirmed the successful synthesis of nanocollectors suitable for flotation applications. X-Ray Diffraction (XRD) analysis was conducted to evaluate the crystalline structure of both ZnO and Al₂O₃ nanoparticles. As shown in Fig. 4c, the XRD pattern for ZnO nanocollectors displayed peaks corresponding to the hexagonal wurtzite phase of ZnO, with no additional impurity phases detected. Similarly, Fig. 4d presents the XRD analysis for Al₂O₃ nanocollectors, confirming the presence of γ-Al₂O₃ with no secondary crystalline phases, indicating high purity. Fourier Transform Infrared Spectroscopy (FTIR) was used to analyze the surface modification of ZnO and Al₂O₃ nanoparticles. As shown in Fig. 4e, FTIR analysis of ZnO nanoparticles modified with SDS revealed characteristic absorption peaks in the 800 − 400 cm⁻¹ range corresponding to metal-oxygen (M-O) bonds, with specific Zn-O absorptions typically appearing between 600 − 400 cm⁻¹. The surface modification caused a shift in these Zn-O absorption peaks to the 825 − 621 cm⁻¹ range, indicating successful interaction between SDS and ZnO. Additionally, peaks around 1000 cm⁻¹ (S = O bond of SO₄ in SDS) and absorption bands at 1476, 2851, and 2919 cm⁻¹ (C-H bond bending and stretching) confirmed the presence of SDS on the ZnO surface. For Al₂O₃ nanoparticles modified with SDS, similar FTIR analysis, as shown in Fig. 4f, confirmed successful coating with SDS through characteristic absorption peaks. 3.2. Definitive Screening Design Eight different factors were defined in the Definitive Screening Design, and nineteen flotation experiments were performed based on this design. The experimental data, summarized in Table 1 , indicate varying recovery rates under different operational conditions. The results demonstrate the effectiveness of the employed collectors and nanocollectors in enhancing smithsonite ore recovery. The highest recovery rate, achieved with the use of ZnO nanocollectors, was 90.3%, highlighting their superior efficiency in the flotation process. Table 1. Experimental layout Based on Definitive Screening Design results Factor Run pH Pulp Density (%) Air Flow (L/min) Oleic acid (g/ton) Armac C (g/ton) ZnO (g/ton) Al 2 O 3 (g/ton) Frother-A65 (g/ton) Recovery (%) 1 9 7 3 0 0 250 0 25 57.5 2 6 3 1 0 0 0 0 0 12.6 3 12 7 3 500 500 0 250 0 59.8 4 12 3 1 1000 0 125 125 50 55.9 5 6 3 5 500 1000 250 125 25 75.1 6 9 7 5 1000 1000 125 250 0 46.1 7 9 3 1 500 500 125 125 50 87.8 8 12 5 5 0 500 250 0 0 46 9 9 5 1 0 0 250 125 0 42 10 6 5 3 0 500 125 250 50 80.1 11 6 7 1 1000 0 125 0 25 48 12 12 7 3 1000 1000 250 250 50 70.1 13 9 3 3 1000 500 0 250 50 69.9 14 6 5 3 1000 1000 0 125 0 29.7 15 12 3 1 0 0 0 125 0 44.3 16 9 5 5 0 1000 125 125 25 78 17 12 5 5 500 500 125 250 25 78.7 18 6 7 1 500 0 250 250 50 90.3 19 6 3 5 0 500 0 125 0 22.5 Based on the experimental data, the general trend in the recovery rates as a function of operational factors was determined by fitting the data. The fitted model is expressed as a nonlinear combination of the operational factors, where each factor is multiplied by a specific coefficient that quantifies its impact on the recovery rate. The model can be represented as: \(\:{\left(Recover\:rate\right)}^{2}={a}_{1}\times\:pH+{a}_{2}\times\:Pulp\:Density+{a}_{3}\times\:Air\:Flow\:Rate+\dots\:\) (Eq. 1) Here, a 1 , a 2 , a 3 , etc., are the coefficients that were determined through data fitting, and they represent the contribution of each respective factor to the overall recovery rate. The table 2 summarizes the coefficients for each operational factor: 3.3. The effect of pH, Pulp density, air flow rate and Frother Figure 5 presents the recovery rates as a function of varying pH levels, pulp densities, and air flow rates, calculated based on Eq. 1. The pH had a significant impact on flotation recovery. Figure 5 a shows that recovery rates decreased at both acidic and basic pH levels, while the highest recovery occurred under slightly alkaline conditions. This suggests that alkaline environments enhance the stability and effectiveness of collectors, improving their interaction with the mineral surface. The optimal recovery rate was achieved with an air flow rate of 3.0 L/min. As shown in Fig. 5 b, variations in air flow rates directly influenced bubble formation and froth stability, both of which are essential for effective mineral separation. Excessive air flow resulted in turbulence, while insufficient air flow caused inadequate bubble generation. The recovery efficiency was significantly influenced by pulp density. The study identified 7.0% as the optimal pulp density, yielding the highest recovery rates. Figure 5 c illustrates that inadequate particle interaction at low pulp density and increased slurry viscosity at high pulp density respectively hindered recovery, resulting in reduced efficiency. The optimal frother dosage was determined to be 30 g/t (Fig. 5 d). 3.4. The effect of collectors A comparative analysis of various collectors highlighted notable differences in their performance. Oleic acid, a commonly used collector, achieved a maximum recovery rate of 70.1%, as illustrated in Fig. 6 a. Despite its widespread application, oleic acid's efficiency was surpassed by Armac C. In contrast, Armac C demonstrated superior performance with a peak recovery rate of 75.1%, particularly at a dosage of 500 g/Ton, attributable to its enhanced surface activity and effective interaction with the mineral surfaces (Fig. 6 b). The improved recovery rates suggest that Armac C's amphiphilic properties enhance particle attachment and separation, making it a viable alternative in flotation processes. The data emphasize Armac C’s effectiveness as a collector, particularly in optimizing flotation performance under various conditions. 3.5. The effect of nanocollectors The use of ZnO nanocollectors had a significant impact on the flotation recovery rates of smithsonite, as illustrated in Fig. 7 a. The experimental results demonstrated a clear correlation between the dosage of ZnO nanocollectors and the recovery rate. Specifically, the recovery rate increased steadily with higher dosages of ZnO nanocollectors, highlighting their effectiveness in enhancing the hydrophobicity of smithsonite particles and improving separation efficiency. The analysis identified an optimal dosage of 125 g/Ton, where the recovery rate reached its peak at 90.3%. This optimal concentration provided the best balance between effectiveness and cost, as further increases in dosage yielded only marginal improvements in recovery. Beyond this optimal point, additional ZnO nanocollectors did not substantially enhance recovery, indicating that an excess dosage may lead to diminishing returns and increased operational costs. The incorporation of Al₂O₃ nanocollectors demonstrated a significant enhancement in smithsonite recovery rates, as depicted in Fig. 7 b. The experimental data revealed a consistent increase in recovery rates with higher dosages of Al₂O₃ nanocollectors, underscoring their effectiveness in improving flotation performance. Specifically, the optimal dosage for Al₂O₃ nanocollectors was found to be 125 g/Ton, which achieved a peak recovery rate of 87.8%. Beyond this dosage, the recovery rates plateaued, with no substantial gains observed at higher concentrations. This plateau effect indicates that additional doses of Al₂O₃ nanocollectors do not proportionately increase recovery efficiency, potentially due to factors such as particle saturation or aggregation. The results highlight the utility of Al₂O₃ nanocollectors in refining flotation processes, particularly in enhancing the selective separation of smithsonite from unwanted gangue minerals. By optimizing the dosage of Al₂O₃ nanocollectors, it is possible to improve the overall efficacy of the flotation method while controlling costs and avoiding unnecessary excess. These findings suggest that Al₂O₃ nanocollectors are a valuable tool for maximizing recovery rates in mineral processing, contributing to more effective and efficient flotation operations. 3.6. Zeta Potential Measurements Figure 8 displays the zeta potential measurements across different pH levels for smithsonite, ZnO nanocollectors, and Al₂O₃ nanocollectors. The measurements for smithsonite revealed significant variations in surface charge with changes in pH. At pH 6, smithsonite exhibited a positive zeta potential of 17 mV, indicating a positively charged surface. This zeta potential decreased to 8 mV at pH 8 and became increasingly negative with higher pH levels, reaching − 5 mV at pH 10 and − 20 mV at pH 12. These results suggest that smithsonite’s surface charge shifts from positive to negative in more alkaline conditions. In contrast, ZnO nanocollectors displayed a consistently negative zeta potential across the pH range. At pH 6, the zeta potential was − 2 mV, becoming more negative as pH increased to -11 mV at pH 8, -18 mV at pH 10, and − 29 mV at pH 12. This trend indicates that ZnO nanocollectors exhibit enhanced negative surface charge in alkaline environments, which may improve their dispersion in the flotation slurry. Al 2 O 3 nanocollectors showed a positive zeta potential at all tested pH levels, with values of 36 mV at pH 6, decreasing slightly to 33 mV at pH 8, and further to 26 mV at pH 10 and 21 mV at pH 12. Despite the decrease, the positive zeta potential remained significant, suggesting that Al 2 O 3 nanocollectors maintain effective electrostatic interactions with the negatively charged surfaces of smithsonite, which could enhance their performance in flotation processes. 4. Conclusion This study successfully synthesized ZnO and Al₂O₃ nanocollectors and investigated their impact on the flotation recovery of smithsonite ore. The research systematically varied key operational factors, including pH, pulp density, and air flow rate, to identify the optimal conditions for maximizing zinc recovery, utilizing a rigorous experimental approach through the Definitive Screening Design (DSD). The results demonstrated that the introduction of ZnO and Al₂O₃ nanocollectors significantly enhanced recovery rates compared to conventional collectors. This improvement is likely due to the increased surface area and enhanced interaction between the nanocollectors and smithsonite particles, which facilitated more effective attachment and separation during the flotation process. Furthermore, factors such as pH, pulp density, and air flow rate were also pivotal in determining recovery rates. The optimal conditions for maximum recovery—achieved with a pH of 6.0, a pulp density of 7.0%, an air flow rate of 1.0 L/min, 360 g/t of oleic acid, 180 g/t of ZnO nanocollectors, 250 g/t of Al₂O₃ nanocollectors, and 17 g/t of A65 frother—resulted in a peak recovery rate of 91.1%. These findings underscore the importance of optimizing all flotation parameters to achieve maximum efficiency. Declarations Conflicts of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐ The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: References Hales MC, Frost RL (2008) Thermal analysis of smithsonite and hydrozincite. J Therm Anal Calorim 91:855–860 Jia K, Feng Q, Zhang G, Ji W, Zhang W, Yang B (2018) The role of S (II) and Pb (II) in xanthate flotation of smithsonite: Surface properties and mechanism. Appl Surf Sci 442:92–100 Hosseini SH, Forssberg E (2006) Adsorption studies of smithsonite flotation using dodecylamine and oleic acid. Min Metall Explor 23(2):87–96 Wang Z, Xu L, Wang J, Wang L, Xiao J (2017) A comparison study of adsorption of benzohydroxamic acid and amyl xanthate on smithsonite with dodecylamine as co-collector. Appl Surf Sci 426:1141–1147 Zeng Y, Liu J, Dong W, Hao J, Wang Y (2020) Study on sulfide layer attenuation behavior of smithsonite during sulfidization flotation. Front Mater 6:347 Feng Q, Wen S, Bai X, Chang W, Cui C, Zhao W (2019) Surface modification of smithsonite with ammonia to enhance the formation of sulfidization products and its response to flotation. Miner Eng 137:1–9 Krishnan S et al (2021) Current technologies for recovery of metals from industrial wastes: An overview, Environmental Technology & Innovation, vol. 22, p. 101525 Miller D (2005) Sulphidization flotation for recovery of lead and zinc from oxide-sulfide ores, 中国有色金属学会会刊: 英文版, vol. 15, no. 5, pp. 1138–1144 Chen Y, Tang X (2020) Selective flotation separation of smithsonite from calcite by application of amino trimethylene phosphonic acid as depressant. Appl Surf Sci 512:145663 Liu C, Zhang W, Song S, Li H, Liu Y (2019) Flotation separation of smithsonite from calcite using 2-phosphonobutane-1, 2, 4-tricarboxylic acid as a depressant, Powder technology. 352:11–15 Hosseini SH, Forssberg E (2007) Physicochemical studies of smithsonite flotation using mixed anionic/cationic collector. Miner Eng 20(6):621–624 Feng Q, Wang M, Zhang G, Zhao W, Han G (2023) Enhanced adsorption of sulfide and xanthate on smithsonite surfaces by lead activation and implications for flotation intensification. Sep Purif Technol 307:122772 Luo B et al (2019) Characterization of sulfide film on smithsonite surface during sulfidation processing and its response to flotation performance. Powder Technol 351:144–152 Zheng H, Zhang G, Li C, Li B, Ye G (2023) The surface dissolution process of smithsonite and its effect on flotation behaviour. Colloids Surf A 676:132118 Wang M, Zhao W, Han G, Feng Q (2023) Utilization of lead ions to improve surface hydrophobicity and flotation recovery of sulfidized smithsonite. Colloids Surf A 663:131126 Shi Q, Feng Q, Zhang G, Deng H (2012) Electrokinetic properties of smithsonite and its floatability with anionic collector. Colloids Surf A 410:178–183 Mehdilo A, Irannajad M, Zarei H (2014) Smithsonite flotation from zinc oxide ore using alkyl amine acetate collectors. Sep Sci Technol 49(3):445–457 Liu M, Chen J, Chen Y, Zhu Y (2020) Interaction between smithsonite and carboxyl collectors with different molecular structure in the presence of water: A theoretical and experimental study. Appl Surf Sci 510:145410 Taseidifar M, Makavipour F, Pashley RM, Rahman AM (2017) Removal of heavy metal ions from water using ion flotation. Environ Technol Innov 8:182–190 Song Z, Wen S, Han G, Feng Q (2023) Recent Progress on Chelating Reagents in Flotation of Zinc Oxide Ores: A Review, Minerals, vol. 13, no. 10, p. 1278 Zhang S, Wen S, Xian Y, Liang G, Li M (2021) Pb ion pre-modification enhances the sulfidization and floatability of smithsonite. Miner Eng 170:107003 Hoseinian FS, Ramshini S, Rezai B, Kowsari E, Safari M (2023) Toxic heavy metal ions removal from wastewater by ion flotation using a nano collector. Miner Eng 204:108380 Chang L et al (2021) Enhancing the ion flotation removal of Cu (Ⅱ) via regulating the oxidation degree of nano collector-graphene oxide. J Clean Prod 295:126397 Yang S, Pelton R, Raegen A, Montgomery M, Dalnoki-Veress K (2011) Nanoparticle flotation collectors: mechanisms behind a new technology, Langmuir, vol. 27, no. 17, pp. 10438–10446 Supplementary Files GraphicalAbstract.png Cite Share Download PDF Status: Published Journal Publication published 30 Apr, 2025 Read the published version in Chemical Papers → Version 1 posted Reviewers agreed at journal 18 Nov, 2024 Reviewers invited by journal 18 Nov, 2024 Editor invited by journal 11 Nov, 2024 Editor assigned by journal 11 Nov, 2024 First submitted to journal 08 Nov, 2024 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. 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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-5409694","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":379623700,"identity":"cf548779-dc86-4483-9941-25cdf589aa26","order_by":0,"name":"Mohamad Meshkini","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6ElEQVRIiWNgGAWjYPACGx77880HgAwJGWK1pMkx3DiWANLCQ6yWQ8YMB3IMQCzCWszZzz7+8KPmQGJjw5nPr27UWPAwsB8+ugGfFsuedDPJnmN3EpuZe7dZ5xwDOownLe0GPi0GB9LYGHjYniW2MZzdZpzDBtQiwWOGX8v5Z8wf//w7nNjDkPPMOOcfMVpupDFI87YdNpZgyGF+nNtGhBbLGc/YpGX70uQMJI6ZMef2SfCwEfKLOX8a88c332x4DPibH3/O+VYnx89++Bh+hyGx2STAJD7l6FqYPxBSPQpGwSgYBSMTAABV4kmQ7UwPbAAAAABJRU5ErkJggg==","orcid":"","institution":"Tehran University: University of Tehran","correspondingAuthor":true,"prefix":"","firstName":"Mohamad","middleName":"","lastName":"Meshkini","suffix":""},{"id":379623701,"identity":"a6a4a046-44c1-4523-9d38-77c0f5cdaef3","order_by":1,"name":"Mahdi Gharabaghi","email":"","orcid":"","institution":"Tehran University: University of Tehran","correspondingAuthor":false,"prefix":"","firstName":"Mahdi","middleName":"","lastName":"Gharabaghi","suffix":""}],"badges":[],"createdAt":"2024-11-07 12:00:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5409694/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5409694/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11696-025-04060-1","type":"published","date":"2025-04-30T15:57:16+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":70488027,"identity":"fec9d236-2b35-47ba-a067-189b7205bde2","added_by":"auto","created_at":"2024-12-03 16:13:32","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":100956,"visible":true,"origin":"","legend":"\u003cp\u003ea) Cumulative particle size distribution of the smithsonite sample and b) XRD pattern of smithsonite sample.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5409694/v1/d29663eeafba58c7b2220bce.png"},{"id":70488026,"identity":"07b61976-b5dc-4242-928a-b4d6027b65c9","added_by":"auto","created_at":"2024-12-03 16:13:32","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":214460,"visible":true,"origin":"","legend":"\u003cp\u003ea) Schematic representation of the ZnO nanoparticle synthesis process and b) Schematic representation of the Al\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e nanoparticle synthesis process.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5409694/v1/0c4fccf7ea941d9b79a185af.png"},{"id":70488030,"identity":"4d92c410-70b1-4986-9576-c869faa0ddf8","added_by":"auto","created_at":"2024-12-03 16:13:32","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":145831,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic representation of the modified a) ZnO, b) Al₂O₃ nanoparticles, and c) Schematic representation of the flotation cell.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5409694/v1/d31edd376f2b0d01ad568f74.png"},{"id":70488313,"identity":"302db082-b478-4c08-b857-909264926039","added_by":"auto","created_at":"2024-12-03 16:21:32","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":132861,"visible":true,"origin":"","legend":"\u003cp\u003eTEM images of (a) Al₂O₃ and (b) ZnO nanoparticles; XRD patterns of (c) Al₂O₃ and (d) ZnO nanoparticles; FTIR spectra of (e) Al₂O₃ and (f) ZnO nanoparticles.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5409694/v1/430b88378b115a5580d95f4e.png"},{"id":70488312,"identity":"485d4692-fe0c-42f7-ab4d-52a21c07f3c4","added_by":"auto","created_at":"2024-12-03 16:21:32","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":109615,"visible":true,"origin":"","legend":"\u003cp\u003eDetermined recovery rates as a function of a) pH, b) air flow rate, c) pulp density and d) Frother, based on model fitting results (Equation 1).\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-5409694/v1/ab98a00cab5eb5088abf9415.png"},{"id":70488311,"identity":"07a51105-51d6-4c61-805f-efda07fda70d","added_by":"auto","created_at":"2024-12-03 16:21:32","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":87807,"visible":true,"origin":"","legend":"\u003cp\u003eDetermined recovery rates as a function of a) oletic acid and b) Armac C dosage, based on model fitting results (Equation 1).\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-5409694/v1/6cd34ed531c77086fa0ff60f.png"},{"id":70488033,"identity":"d3f3cca2-762b-4fb1-8a71-f93bc38e2284","added_by":"auto","created_at":"2024-12-03 16:13:32","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":76698,"visible":true,"origin":"","legend":"\u003cp\u003eDetermined recovery rates as a function of a) ZnO and b) Al\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e nanocollector dosage, based on model fitting results (Equation 1).\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-5409694/v1/3d2876b31ed10d1741ac977b.png"},{"id":70488032,"identity":"25c040c0-99eb-49d2-a57b-58341dbbb750","added_by":"auto","created_at":"2024-12-03 16:13:32","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":81537,"visible":true,"origin":"","legend":"\u003cp\u003eZeta potential measurements of smithsonite, ZnO nanocollectors, and Al₂O₃ nanocollectors across different pH levels.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-5409694/v1/0949e4d784ce9ad9354a5c4e.png"},{"id":81987831,"identity":"bfcf76ea-4c93-4810-b801-5ba86e1db954","added_by":"auto","created_at":"2025-05-05 16:06:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1621110,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5409694/v1/52c3cda8-83d1-4528-bfc0-95b30c0c2298.pdf"},{"id":70488034,"identity":"30e7f1bd-8325-4376-afac-e59def1af201","added_by":"auto","created_at":"2024-12-03 16:13:32","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":8399964,"visible":true,"origin":"","legend":"","description":"","filename":"GraphicalAbstract.png","url":"https://assets-eu.researchsquare.com/files/rs-5409694/v1/f7b78de1de9d1519c5f8a05b.png"}],"financialInterests":"","formattedTitle":"\u003cp\u003eOptimization of Smithsonite Flotation Using ZnO and Al\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e Nanocollectors: A Definitive Screening Design Approach\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eAs global reserves of zinc sulfide ores continue to decline, the need for efficient methods to process nonsulfide zinc ores, such as smithsonite, is becoming increasingly critical [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Smithsonite presents a viable alternative to sulfide ores, though it poses distinct extraction challenges due to its complex composition. These ores frequently contain substantial amounts of carbonate gangue minerals, complicating the flotation process and leading to higher reagent consumption [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Additionally, smithsonite exhibits greater hydrophilicity, which necessitates more complex and energy-intensive processing techniques [\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCase studies underscore the practical challenges and solutions in the flotation of smithsonite. The efficiency of the flotation process is influenced by several key parameters, including surfactant concentration, feed concentration, pH levels, bubble size, water flow rate, ionic strength, and temperature [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Comparative analyses of flotation behavior between smithsonite and other minerals, such as calcite, have yielded valuable insights for achieving selective flotation [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The effectiveness of various collectors and reagents has been extensively examined. Different collectors, such as dodecylamine (DDA) and potassium lauryl phosphate, have demonstrated varying levels of effectiveness. For instance, Hosseini and Forssberg found DDA to be effective when used in conjunction with sodium sulfide, while another study suggested that potassium lauryl phosphate offered better selectivity and recovery for smithsonite compared to calcite [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTraditional flotation methods, effective for sulfide ores, often fall short when applied to oxidized minerals, underscoring the need for novel or enhanced flotation techniques. Ongoing debates center around the optimal dosage of sodium sulfide, the effectiveness of various collectors, and the pH dependency of flotation processes. While some studies advocate for controlled sulfidization to maximize recovery rates, others emphasize the detrimental effects of oversulfidization [\u003cspan additionalcitationids=\"CR13 CR14 CR15 CR16\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Furthermore, the relative effectiveness of dodecylamine (DDA) and potassium lauryl phosphate as collectors remains a topic of contention [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMoreover, environmental concerns are crucial when assessing the use of flotation reagents, particularly in the context of sustainable mining practices [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The application of lead nitrate (Pb(NO₃)₂) and high concentrations of sulfide reagents in flotation processes has raised significant environmental challenges. The extensive use of sulfide reagents, such as sodium sulfide, can result in the generation of harmful by-products, including toxic gases like hydrogen sulfide (H₂S), which contribute to air and water pollution. The management and disposal of these reagents and their by-products require careful consideration to mitigate their environmental impact [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo address these concerns, the use of co-collectors is being explored as a strategy to minimize the reliance on toxic reagents. Co-collectors can enhance the efficiency of flotation processes, potentially allowing for lower dosages of harmful chemicals while still achieving desirable recovery rates. This approach not only reduces the environmental burden but also aligns with the principles of green chemistry. Researchers are actively investigating biodegradable or less toxic co-collectors as alternatives to traditional reagents, aiming to strike a balance between metallurgical performance and environmental sustainability.\u003c/p\u003e \u003cp\u003eInnovative approaches, such as the use of nanocollectors and advanced flotation technologies, have shown significant promise in mineral flotation. Nanocollectors represent a groundbreaking advancement in this field, offering superior surface properties and reactivity due to their nanoscale dimensions. Unlike traditional bulk collectors, nanocollectors exhibit a higher surface area-to-volume ratio, resulting in more efficient adsorption on mineral surfaces and improved flotation performance [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe primary advantage of nanocollectors lies in their enhanced selectivity and adsorption efficiency compared to conventional bulk collectors. They interact more effectively with mineral surfaces, forming a uniform and densely packed adsorption layer. For example, nanocollectors can adsorb onto the negatively charged smithsonite surface at alkaline pH levels, particularly following sulfidization with Na₂S. This adsorption increases the hydrophobicity and flotation efficiency of smithsonite [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe flotation of smithsonite, a primary source of zinc, is crucial for zinc extraction across various industries, including batteries, coatings, and alloys. However, conventional flotation methods are often hampered by challenges such as suboptimal reagent efficiency, low selectivity, and environmental concerns. Recent studies emphasize the importance of refining reagent selection and optimizing flotation conditions to improve performance. Nanotechnology offers promising solutions, as nanoparticles exhibit unique surface properties and high reactivity, which can enhance interactions with mineral surfaces during flotation. Despite the growing interest in nanomaterials, there is a notable gap in research on the application of Al₂O₃ and ZnO nanoparticles as nanocollectors in smithsonite flotation. These nanocollectors could potentially enhance the process by increasing recovery rates, improving selectivity, and offering a more sustainable approach. This study aims to explore the effectiveness of Al₂O₃ and ZnO nanoparticles in enhancing smithsonite flotation performance. By systematically investigating their impact using a definitive screening design approach, this research seeks to address critical gaps in flotation chemistry and contribute to the development of more efficient and environmentally friendly mineral processing techniques.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Sample\u003c/h2\u003e \u003cp\u003eThe smithsonite samples used in this research were obtained from the Angouran mine, located in Zanjan province, Iran. These samples were first ground to achieve the d\u003csub\u003e80\u003c/sub\u003e below 10 \u0026micro;m, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe mineralogical composition of the smithsonite ore was analyzed using X-ray fluorescence (XRF), revealing a ZnO concentration of 63.61%. Additional constituents included 34.4% loss on ignition (LOI), 0.12% SO₃, 0.14% Na₂O, 0.2% MgO, 0.69% Fe₂O₃, 0.57% CaO, and 0.14% SiO₂. The total zinc content, measured at 48.92%, was determined through wet chemistry methods. The mineralogical phases were further investigated using X-ray diffraction (XRD), as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Reagents\u003c/h2\u003e \u003cp\u003eArmac C (cocoalkylamine acetate, 99%) and oleic acid (90%) were used as conventional collectors. Sodium sulfide (75%), sodium hydroxide (99%), and AeroFroth 65 (98%) were utilized as the sulfidizing reagent, modifier, and frother, respectively. Synthesized ZnO and Al₂O₃ were employed as nanocollectors.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. ZnO nanoparticles synthesis\u003c/h2\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea presents a schematic of the ZnO nanoparticle synthesis process. A bottom-up approach was employed for the synthesis of ZnO nanocollectors. Initially, 1.5 g of zinc acetate (99%) was dissolved in 65 mL of ethanol using a graduated cylinder and transferred to an Erlenmeyer flask. The solution was stirred on a magnetic stirrer at room temperature for 30 minutes to one hour until the zinc acetate was fully dissolved, resulting in a clear solution. Once dissolved, the temperature of the magnetic stirrer was gradually increased to evaporate the solvent and facilitate the formation of zinc oxide precipitates. The reaction proceeded until white precipitates appeared at the bottom of the flask, signaling the completion of the precipitation process. The precipitates were then dried at room temperature for two days and subsequently calcined in a furnace at 400\u0026deg;C for 14 hours to yield pure ZnO nanoparticles.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Al\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e nanoparticles synthesis\u003c/h2\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb provides a schematic representation of the Al\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e nanoparticle synthesis process. To synthesize Al₂O₃ nanocollectors, 3 grams of aluminum nitrate (99%) and 0.5 grams of sucrose (99.5%) were dissolved in 50 milliliters of deionized water (DI) using a magnetic stirrer set at 35\u0026deg;C for one hour to prepare the precursor mixture. Ammonium nitrate solution was then added dropwise to the precursor mixture to control the pH, which is crucial for determining the morphology of the γ-Al₂O₃ nanoparticles. The addition of ammonium nitrate caused the solution to transition from clear to milky, indicating the formation of aluminum hydroxide particles. The mixture was transferred to a 75-milliliter autoclave and heated in a furnace at 300\u0026deg;C for 20 hours. Following the hydrothermal reaction, the resulting product was washed with ethanol and centrifuged to remove impurities. The washed product was then dried at 100\u0026deg;C and calcined at 900\u0026deg;C for five hours to convert the aluminum hydroxide to γ-Al₂O₃ nanoparticles.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Surface modification\u003c/h2\u003e \u003cp\u003eTo enhance flotation performance, surface modification of the Al₂O₃ and ZnO nanoparticles was carried out using sodium dodecyl sulfate (SDS). In this process, 1 gram of the synthesized nanoparticles was dissolved in 15\u0026ndash;20 milliliters of deionized water. A 5% SDS solution was then added to the mixture. The solution was stirred thoroughly at room temperature to ensure a uniform coating of the nanoparticles with SDS, thereby improving their interaction with minerals during the flotation process. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea depicts a schematic of the modified ZnO and Al₂O₃ particles.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Flotation experiments\u003c/h2\u003e \u003cp\u003eThis research employs an experimental design to assess the efficacy of various nanocollectors in improving smithsonite flotation recovery. The choice of this approach is based on the need to systematically control and manipulate variables such as pH, pulp density, and reagent dosages to accurately determine their effects on flotation performance. By utilizing a statistically rigorous design of experiments (DOE), specifically the Definitive Screening Design (DSD), we aim to thoroughly investigate both the main effects and interaction effects of these parameters. This methodological approach ensures the generation of reliable and reproducible data, providing a solid foundation for evaluating the effectiveness of nanocollectors in mineral processing applications.\u003c/p\u003e \u003cp\u003eThe flotation tests were organized according to a Definitive Screening Design (DSD) to evaluate the impact of multiple factors. The experimental design included several key variables:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003epH Levels\u003c/b\u003e: Three distinct pH levels\u0026mdash;6.0, 9.0, and 12.0\u0026mdash;were selected to assess their effect on the flotation process.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003ePulp Densities\u003c/b\u003e: Pulp densities of 3.0%, 5.0%, and 7.0% were tested to study their impact on particle interaction and slurry viscosity.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eAir Flow Rates\u003c/b\u003e: Air flow rates of 1.0 L/min, 3.0 L/min, and 5.0 L/min were varied to determine the optimal bubble size and froth stability.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eOleic Acid Dosage\u003c/b\u003e: Dosages of oleic acid, a collector, were set at 0, 500, and 1000 g/Ton to investigate its effect on enhancing the hydrophobicity of smithsonite particles.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eArmac C Dosage\u003c/b\u003e: Armac C, another collector, was used at the same dosages as oleic acid for comparative effectiveness.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eZnO Nanocollector Dosage\u003c/b\u003e: ZnO nanocollectors were tested at 0, 125, and 250 g/Ton to leverage their unique properties for improved recovery rates.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eγ-Al₂O₃ Nanocollector Dosage\u003c/b\u003e: γ-Al₂O₃ nanocollectors were similarly tested at 0, 125, and 250 g/Ton to evaluate their selective adsorption capabilities.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eFrother A65 Dosage\u003c/b\u003e: Frother A65 was added at concentrations of 0, 25, and 50 g/Ton to study its impact on froth formation and stability.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eFor the flotation experiments, a custom-designed flotation cell with a height of 30 cm and a diameter of 4 cm was employed. The cell, as depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb, featured a circular air sparger at the bottom to generate bubbles, with air supplied via a compressor. Each flotation test was conducted for a total duration of 4 minutes. Following the flotation process, both concentrate and tailings samples were filtered, dried in an oven, and weighed to calculate the recovery percentage using the formula:\u003c/p\u003e \u003cp\u003e \u003cem\u003eR =\u003c/em\u003e \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{C}{F}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003eWhere C is the weight of the concentrate and F is the weight of the feed.\u003c/p\u003e \u003cp\u003eEach test began with the preparation of a 5 g sample of smithsonite ore, which was mixed with deionized water and the specified chemical reagents. The pulp was conditioned on a magnetic stirrer, with conditioning times of 1 minute for frothers and 4 minutes for collectors. The reagent dosages were determined according to the experimental design table. The pH of the solution was adjusted to the desired level using sulfuric acid or sodium hydroxide. After conditioning, the pulp was transferred to the flotation cell. A controlled flow rate of wash water was applied at the top of the cell to maintain consistent conditions for froth removal. The flotation process was initiated by opening the air valve and continued for 4 minutes, during which froth was continuously collected.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results and discussions","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1. Characterizations of ZnO and Al₂O₃ nano particles\u003c/h2\u003e\n \u003cp\u003eTransmission Electron Microscopy (TEM) was employed to determine the particle size and morphology of the synthesized ZnO and Al₂O₃ nanocollectors. TEM analysis, as shown in Fig.\u0026nbsp;4a and 4b, revealed spherical ZnO and Al₂O₃ nanoparticles with average particle sizes of approximately 30 nm and 55 nm, respectively. This confirmed the successful synthesis of nanocollectors suitable for flotation applications.\u003c/p\u003e\n \u003cp\u003eX-Ray Diffraction (XRD) analysis was conducted to evaluate the crystalline structure of both ZnO and Al₂O₃ nanoparticles. As shown in Fig.\u0026nbsp;4c, the XRD pattern for ZnO nanocollectors displayed peaks corresponding to the hexagonal wurtzite phase of ZnO, with no additional impurity phases detected. Similarly, Fig.\u0026nbsp;4d presents the XRD analysis for Al₂O₃ nanocollectors, confirming the presence of \u0026gamma;-Al₂O₃ with no secondary crystalline phases, indicating high purity.\u003c/p\u003e\n \u003cp\u003eFourier Transform Infrared Spectroscopy (FTIR) was used to analyze the surface modification of ZnO and Al₂O₃ nanoparticles. As shown in Fig.\u0026nbsp;4e, FTIR analysis of ZnO nanoparticles modified with SDS revealed characteristic absorption peaks in the 800\u0026thinsp;\u0026minus;\u0026thinsp;400 cm⁻\u0026sup1; range corresponding to metal-oxygen (M-O) bonds, with specific Zn-O absorptions typically appearing between 600\u0026thinsp;\u0026minus;\u0026thinsp;400 cm⁻\u0026sup1;. The surface modification caused a shift in these Zn-O absorption peaks to the 825\u0026thinsp;\u0026minus;\u0026thinsp;621 cm⁻\u0026sup1; range, indicating successful interaction between SDS and ZnO. Additionally, peaks around 1000 cm⁻\u0026sup1; (S\u0026thinsp;=\u0026thinsp;O bond of SO₄ in SDS) and absorption bands at 1476, 2851, and 2919 cm⁻\u0026sup1; (C-H bond bending and stretching) confirmed the presence of SDS on the ZnO surface. For Al₂O₃ nanoparticles modified with SDS, similar FTIR analysis, as shown in Fig.\u0026nbsp;4f, confirmed successful coating with SDS through characteristic absorption peaks.\u003c/p\u003e\n \u003ch2\u003e3.2. Definitive Screening Design\u003c/h2\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003cp\u003eEight different factors were defined in the Definitive Screening Design, and nineteen flotation experiments were performed based on this design. The experimental data, summarized in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, indicate varying recovery rates under different operational conditions. The results demonstrate the effectiveness of the employed collectors and nanocollectors in enhancing smithsonite ore recovery. The highest recovery rate, achieved with the use of ZnO nanocollectors, was 90.3%, highlighting their superior efficiency in the flotation process.\u003c/p\u003e\n \u003cp\u003eTable 1. Experimental layout Based on Definitive Screening Design results\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.16667%;\"\u003e\n \u003cp\u003eFactor\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eRun\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.83333%;\"\u003e\n \u003cp\u003epH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.1667%;\"\u003e\n \u003cp\u003ePulp Density (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003eAir Flow (L/min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003eOleic acid (g/ton)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003eArmac C (g/ton)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003eZnO (g/ton)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003eAl\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e (g/ton)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6667%;\"\u003e\n \u003cp\u003eFrother-A65 \u0026nbsp;(g/ton)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5%;\"\u003e\n \u003cp\u003eRecovery (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.16667%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.83333%;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.1667%;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6667%;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5%;\"\u003e\n \u003cp\u003e57.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.16667%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.83333%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.1667%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6667%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5%;\"\u003e\n \u003cp\u003e12.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.16667%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.83333%;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.1667%;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6667%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5%;\"\u003e\n \u003cp\u003e59.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.16667%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.83333%;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.1667%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e1000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6667%;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5%;\"\u003e\n \u003cp\u003e55.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.16667%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.83333%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.1667%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e1000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6667%;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5%;\"\u003e\n \u003cp\u003e75.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.16667%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.83333%;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.1667%;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e1000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e1000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6667%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5%;\"\u003e\n \u003cp\u003e46.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.16667%;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.83333%;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.1667%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6667%;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5%;\"\u003e\n \u003cp\u003e87.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.16667%;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.83333%;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.1667%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6667%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5%;\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.16667%;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.83333%;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.1667%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6667%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5%;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.16667%;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.83333%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.1667%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6667%;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5%;\"\u003e\n \u003cp\u003e80.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.16667%;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.83333%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.1667%;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e1000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6667%;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5%;\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.16667%;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.83333%;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.1667%;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e1000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e1000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6667%;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5%;\"\u003e\n \u003cp\u003e70.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.16667%;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.83333%;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.1667%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e1000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6667%;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5%;\"\u003e\n \u003cp\u003e69.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.16667%;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.83333%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.1667%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e1000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e1000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6667%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5%;\"\u003e\n \u003cp\u003e29.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.16667%;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.83333%;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.1667%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6667%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5%;\"\u003e\n \u003cp\u003e44.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.16667%;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.83333%;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.1667%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e1000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6667%;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5%;\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.16667%;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.83333%;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.1667%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6667%;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5%;\"\u003e\n \u003cp\u003e78.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.16667%;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.83333%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.1667%;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6667%;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5%;\"\u003e\n \u003cp\u003e90.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.16667%;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.83333%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14.1667%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11%;\"\u003e\n \u003cp\u003e500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.83333%;\"\u003e\n \u003cp\u003e125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.6667%;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.5%;\"\u003e\n \u003cp\u003e22.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003cp\u003eBased on the experimental data, the general trend in the recovery rates as a function of operational factors was determined by fitting the data. The fitted model is expressed as a nonlinear combination of the operational factors, where each factor is multiplied by a specific coefficient that quantifies its impact on the recovery rate. The model can be represented as:\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Taba\" border=\"1\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\left(Recover\\:rate\\right)}^{2}={a}_{1}\\times\\:pH+{a}_{2}\\times\\:Pulp\\:Density+{a}_{3}\\times\\:Air\\:Flow\\:Rate+\\dots\\:\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(Eq.\u0026nbsp;1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eHere, a\u003csub\u003e1\u003c/sub\u003e, a\u003csub\u003e2\u003c/sub\u003e, a\u003csub\u003e3\u003c/sub\u003e, etc., are the coefficients that were determined through data fitting, and they represent the contribution of each respective factor to the overall recovery rate. The table 2 summarizes the coefficients for each operational factor:\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/58894_9946feeafa4c1df7/58894_custom_files/img1733241829.png\" width=\"828\" height=\"452\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3. The effect of pH, Pulp density, air flow rate and Frother\u003c/h2\u003e\n \u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e presents the recovery rates as a function of varying pH levels, pulp densities, and air flow rates, calculated based on Eq. 1. The pH had a significant impact on flotation recovery. Figure \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003ea shows that recovery rates decreased at both acidic and basic pH levels, while the highest recovery occurred under slightly alkaline conditions. This suggests that alkaline environments enhance the stability and effectiveness of collectors, improving their interaction with the mineral surface. The optimal recovery rate was achieved with an air flow rate of 3.0 L/min. As shown in Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eb, variations in air flow rates directly influenced bubble formation and froth stability, both of which are essential for effective mineral separation. Excessive air flow resulted in turbulence, while insufficient air flow caused inadequate bubble generation. The recovery efficiency was significantly influenced by pulp density. The study identified 7.0% as the optimal pulp density, yielding the highest recovery rates. Figure \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003ec illustrates that inadequate particle interaction at low pulp density and increased slurry viscosity at high pulp density respectively hindered recovery, resulting in reduced efficiency. The optimal frother dosage was determined to be 30 g/t (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003ed).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003e3.4. The effect of collectors\u003c/h2\u003e\n \u003cp\u003eA comparative analysis of various collectors highlighted notable differences in their performance. Oleic acid, a commonly used collector, achieved a maximum recovery rate of 70.1%, as illustrated in Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003ea. Despite its widespread application, oleic acid\u0026apos;s efficiency was surpassed by Armac C. In contrast, Armac C demonstrated superior performance with a peak recovery rate of 75.1%, particularly at a dosage of 500 g/Ton, attributable to its enhanced surface activity and effective interaction with the mineral surfaces (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eb). The improved recovery rates suggest that Armac C\u0026apos;s amphiphilic properties enhance particle attachment and separation, making it a viable alternative in flotation processes. The data emphasize Armac C\u0026rsquo;s effectiveness as a collector, particularly in optimizing flotation performance under various conditions.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003e3.5. The effect of nanocollectors\u003c/h2\u003e\n \u003cp\u003eThe use of ZnO nanocollectors had a significant impact on the flotation recovery rates of smithsonite, as illustrated in Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003ea. The experimental results demonstrated a clear correlation between the dosage of ZnO nanocollectors and the recovery rate. Specifically, the recovery rate increased steadily with higher dosages of ZnO nanocollectors, highlighting their effectiveness in enhancing the hydrophobicity of smithsonite particles and improving separation efficiency.\u003c/p\u003e\n \u003cp\u003eThe analysis identified an optimal dosage of 125 g/Ton, where the recovery rate reached its peak at 90.3%. This optimal concentration provided the best balance between effectiveness and cost, as further increases in dosage yielded only marginal improvements in recovery. Beyond this optimal point, additional ZnO nanocollectors did not substantially enhance recovery, indicating that an excess dosage may lead to diminishing returns and increased operational costs.\u003c/p\u003e\n \u003cp\u003eThe incorporation of Al₂O₃ nanocollectors demonstrated a significant enhancement in smithsonite recovery rates, as depicted in Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003eb. The experimental data revealed a consistent increase in recovery rates with higher dosages of Al₂O₃ nanocollectors, underscoring their effectiveness in improving flotation performance. Specifically, the optimal dosage for Al₂O₃ nanocollectors was found to be 125 g/Ton, which achieved a peak recovery rate of 87.8%. Beyond this dosage, the recovery rates plateaued, with no substantial gains observed at higher concentrations. This plateau effect indicates that additional doses of Al₂O₃ nanocollectors do not proportionately increase recovery efficiency, potentially due to factors such as particle saturation or aggregation.\u003c/p\u003e\n \u003cp\u003eThe results highlight the utility of Al₂O₃ nanocollectors in refining flotation processes, particularly in enhancing the selective separation of smithsonite from unwanted gangue minerals. By optimizing the dosage of Al₂O₃ nanocollectors, it is possible to improve the overall efficacy of the flotation method while controlling costs and avoiding unnecessary excess. These findings suggest that Al₂O₃ nanocollectors are a valuable tool for maximizing recovery rates in mineral processing, contributing to more effective and efficient flotation operations.\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003e3.6. Zeta Potential Measurements\u003c/h2\u003e\n \u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e displays the zeta potential measurements across different pH levels for smithsonite, ZnO nanocollectors, and Al₂O₃ nanocollectors. The measurements for smithsonite revealed significant variations in surface charge with changes in pH. At pH 6, smithsonite exhibited a positive zeta potential of 17 mV, indicating a positively charged surface. This zeta potential decreased to 8 mV at pH 8 and became increasingly negative with higher pH levels, reaching \u0026minus;\u0026thinsp;5 mV at pH 10 and \u0026minus;\u0026thinsp;20 mV at pH 12. These results suggest that smithsonite\u0026rsquo;s surface charge shifts from positive to negative in more alkaline conditions.\u003c/p\u003e\n \u003cp\u003eIn contrast, ZnO nanocollectors displayed a consistently negative zeta potential across the pH range. At pH 6, the zeta potential was \u0026minus;\u0026thinsp;2 mV, becoming more negative as pH increased to -11 mV at pH 8, -18 mV at pH 10, and \u0026minus;\u0026thinsp;29 mV at pH 12. This trend indicates that ZnO nanocollectors exhibit enhanced negative surface charge in alkaline environments, which may improve their dispersion in the flotation slurry.\u003c/p\u003e\n \u003cp\u003eAl\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e nanocollectors showed a positive zeta potential at all tested pH levels, with values of 36 mV at pH 6, decreasing slightly to 33 mV at pH 8, and further to 26 mV at pH 10 and 21 mV at pH 12. Despite the decrease, the positive zeta potential remained significant, suggesting that Al\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e nanocollectors maintain effective electrostatic interactions with the negatively charged surfaces of smithsonite, which could enhance their performance in flotation processes.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eThis study successfully synthesized ZnO and Al₂O₃ nanocollectors and investigated their impact on the flotation recovery of smithsonite ore. The research systematically varied key operational factors, including pH, pulp density, and air flow rate, to identify the optimal conditions for maximizing zinc recovery, utilizing a rigorous experimental approach through the Definitive Screening Design (DSD). The results demonstrated that the introduction of ZnO and Al₂O₃ nanocollectors significantly enhanced recovery rates compared to conventional collectors. This improvement is likely due to the increased surface area and enhanced interaction between the nanocollectors and smithsonite particles, which facilitated more effective attachment and separation during the flotation process. Furthermore, factors such as pH, pulp density, and air flow rate were also pivotal in determining recovery rates. The optimal conditions for maximum recovery\u0026mdash;achieved with a pH of 6.0, a pulp density of 7.0%, an air flow rate of 1.0 L/min, 360 g/t of oleic acid, 180 g/t of ZnO nanocollectors, 250 g/t of Al₂O₃ nanocollectors, and 17 g/t of A65 frother\u0026mdash;resulted in a peak recovery rate of 91.1%. These findings underscore the importance of optimizing all flotation parameters to achieve maximum efficiency.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflicts of interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e☒\u0026nbsp;The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e☐ The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHales MC, Frost RL (2008) Thermal analysis of smithsonite and hydrozincite. J Therm Anal Calorim 91:855\u0026ndash;860\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJia K, Feng Q, Zhang G, Ji W, Zhang W, Yang B (2018) The role of S (II) and Pb (II) in xanthate flotation of smithsonite: Surface properties and mechanism. Appl Surf Sci 442:92\u0026ndash;100\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHosseini SH, Forssberg E (2006) Adsorption studies of smithsonite flotation using dodecylamine and oleic acid. Min Metall Explor 23(2):87\u0026ndash;96\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang Z, Xu L, Wang J, Wang L, Xiao J (2017) A comparison study of adsorption of benzohydroxamic acid and amyl xanthate on smithsonite with dodecylamine as co-collector. Appl Surf Sci 426:1141\u0026ndash;1147\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZeng Y, Liu J, Dong W, Hao J, Wang Y (2020) Study on sulfide layer attenuation behavior of smithsonite during sulfidization flotation. Front Mater 6:347\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFeng Q, Wen S, Bai X, Chang W, Cui C, Zhao W (2019) Surface modification of smithsonite with ammonia to enhance the formation of sulfidization products and its response to flotation. Miner Eng 137:1\u0026ndash;9\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKrishnan S et al (2021) Current technologies for recovery of metals from industrial wastes: An overview, Environmental Technology \u0026amp; Innovation, vol. 22, p. 101525\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiller D (2005) Sulphidization flotation for recovery of lead and zinc from oxide-sulfide ores, 中国有色金属学会会刊: 英文版, vol. 15, no. 5, pp. 1138\u0026ndash;1144\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen Y, Tang X (2020) Selective flotation separation of smithsonite from calcite by application of amino trimethylene phosphonic acid as depressant. Appl Surf Sci 512:145663\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu C, Zhang W, Song S, Li H, Liu Y (2019) Flotation separation of smithsonite from calcite using 2-phosphonobutane-1, 2, 4-tricarboxylic acid as a depressant, Powder technology. 352:11\u0026ndash;15\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHosseini SH, Forssberg E (2007) Physicochemical studies of smithsonite flotation using mixed anionic/cationic collector. Miner Eng 20(6):621\u0026ndash;624\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFeng Q, Wang M, Zhang G, Zhao W, Han G (2023) Enhanced adsorption of sulfide and xanthate on smithsonite surfaces by lead activation and implications for flotation intensification. Sep Purif Technol 307:122772\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLuo B et al (2019) Characterization of sulfide film on smithsonite surface during sulfidation processing and its response to flotation performance. Powder Technol 351:144\u0026ndash;152\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZheng H, Zhang G, Li C, Li B, Ye G (2023) The surface dissolution process of smithsonite and its effect on flotation behaviour. Colloids Surf A 676:132118\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang M, Zhao W, Han G, Feng Q (2023) Utilization of lead ions to improve surface hydrophobicity and flotation recovery of sulfidized smithsonite. Colloids Surf A 663:131126\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShi Q, Feng Q, Zhang G, Deng H (2012) Electrokinetic properties of smithsonite and its floatability with anionic collector. Colloids Surf A 410:178\u0026ndash;183\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMehdilo A, Irannajad M, Zarei H (2014) Smithsonite flotation from zinc oxide ore using alkyl amine acetate collectors. Sep Sci Technol 49(3):445\u0026ndash;457\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu M, Chen J, Chen Y, Zhu Y (2020) Interaction between smithsonite and carboxyl collectors with different molecular structure in the presence of water: A theoretical and experimental study. Appl Surf Sci 510:145410\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTaseidifar M, Makavipour F, Pashley RM, Rahman AM (2017) Removal of heavy metal ions from water using ion flotation. Environ Technol Innov 8:182\u0026ndash;190\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSong Z, Wen S, Han G, Feng Q (2023) Recent Progress on Chelating Reagents in Flotation of Zinc Oxide Ores: A Review, Minerals, vol. 13, no. 10, p. 1278\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang S, Wen S, Xian Y, Liang G, Li M (2021) Pb ion pre-modification enhances the sulfidization and floatability of smithsonite. Miner Eng 170:107003\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHoseinian FS, Ramshini S, Rezai B, Kowsari E, Safari M (2023) Toxic heavy metal ions removal from wastewater by ion flotation using a nano collector. Miner Eng 204:108380\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChang L et al (2021) Enhancing the ion flotation removal of Cu (Ⅱ) via regulating the oxidation degree of nano collector-graphene oxide. J Clean Prod 295:126397\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang S, Pelton R, Raegen A, Montgomery M, Dalnoki-Veress K (2011) Nanoparticle flotation collectors: mechanisms behind a new technology, Langmuir, vol. 27, no. 17, pp. 10438\u0026ndash;10446\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"chemical-papers","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"chpa","sideBox":"Learn more about [Chemical Papers](http://link.springer.com/journal/11696)","snPcode":"11696","submissionUrl":"https://www.editorialmanager.com/CHPA/default.aspx","title":"Chemical Papers","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Smithsonite, Flotation, Nanocollector, Definitive Screening Design","lastPublishedDoi":"10.21203/rs.3.rs-5409694/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5409694/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eConventional flotation techniques ores, often encounter challenges when applied to oxidized minerals. This limitation highlights the necessity for developing or improving flotation methods. In this study, the impact of ZnO and Al₂O₃ nanocollectors on smithsonite flotation was examined, and the process was optimized using a comprehensive Definitive Screening Design (DSD). Initially, ZnO and Al₂O₃ nanoparticles were synthesized and modified with sodium dodecyl sulfate (SDS). Characterization through TEM, XRD, and FTIR techniques confirmed the successful synthesis and modification of these nanocollectors. The flotation results indicated that ZnO and Al₂O₃ nanocollectors significantly enhanced recovery rates compared to conventional collectors, attributed to their increased surface area and improved interaction with smithsonite particles. The optimal flotation conditions were identified as a pH of 6.0, a pulp density of 7.0%, an air flow rate of 1.0 L/min, 360 g/t oleic acid, 180 g/t ZnO nanocollectors, 250 g/t Al₂O₃ nanocollectors, and 17 g/t A65 frother, achieving a peak recovery rate of 91.1%.\u003c/p\u003e","manuscriptTitle":"Optimization of Smithsonite Flotation Using ZnO and Al2O3 Nanocollectors: A Definitive Screening Design Approach","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-03 16:13:27","doi":"10.21203/rs.3.rs-5409694/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2024-11-18T22:46:43+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-11-18T17:53:54+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Chemical Papers","date":"2024-11-11T10:03:11+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-11-11T09:03:14+00:00","index":"","fulltext":""},{"type":"submitted","content":"Chemical Papers","date":"2024-11-08T07:38:36+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"chemical-papers","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"chpa","sideBox":"Learn more about [Chemical Papers](http://link.springer.com/journal/11696)","snPcode":"11696","submissionUrl":"https://www.editorialmanager.com/CHPA/default.aspx","title":"Chemical Papers","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"43dc6acc-592c-40df-ba93-e341ebb2f283","owner":[],"postedDate":"December 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-05-05T16:02:25+00:00","versionOfRecord":{"articleIdentity":"rs-5409694","link":"https://doi.org/10.1007/s11696-025-04060-1","journal":{"identity":"chemical-papers","isVorOnly":false,"title":"Chemical Papers"},"publishedOn":"2025-04-30 15:57:16","publishedOnDateReadable":"April 30th, 2025"},"versionCreatedAt":"2024-12-03 16:13:27","video":"","vorDoi":"10.1007/s11696-025-04060-1","vorDoiUrl":"https://doi.org/10.1007/s11696-025-04060-1","workflowStages":[]},"version":"v1","identity":"rs-5409694","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5409694","identity":"rs-5409694","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}