The effluent containing phenol is one of the major health concerns for humans and the environment. Iron oxide nanoparticle (Fe NPs) has properties like size, large surface area, and magnetic nature that were more impressive for removing phenol from the aqueous solution.Batch adsorption tests for the removal of phenol from synthetic phenol water were done in the current work, and the modified iron oxide nanoparticle with rice husk ash (RH+Fe) was confirmed by characterization techniques like XRD, FTIR, SEM, and particle size analysis. Using 2.6 g/L, 50 °C, and 10 ppm of adsorbent dosage, starting concentration, and temperature of RH+Fe, 96 % of the Phenol was removed. The RH+Fe adsorbent data were best fitted for Langmuir isotherm and had an adsorption capacity of 90 mg g-1. In the kinetic investigation, the regression coefficient of pseudo-second order was determined to be 0.96. The results of the current investigation offer a promising phenol elimination adsorbent.
Introduction
Background:
Organic pollutants, particularly phenol, pose serious risks to human health and the environment. Phenol is highly toxic, easily penetrates skin, and causes damage to the nervous and cardiovascular systems. It is lethal at low doses and is a major pollutant in wastewater, producing bad taste and odor even at parts per billion (ppb) levels. Effective and eco-friendly phenol removal is crucial.
Existing Removal Methods:
Various methods such as chemical precipitation, ozonation, photochemical oxidation, and ion exchange are used, but adsorption is preferred due to its low cost, eco-friendliness, and effectiveness. Among adsorbents, iron oxides stand out due to high surface area and reactivity.
Innovation in This Study:
The study focused on synthesizing and characterizing a novel Rice Husk + Iron Oxide (RH+Fe) nanocomposite for phenol adsorption from water. RH is abundant, inexpensive, and waste-derived, while iron oxide enhances adsorption due to its nanoscale properties.
Materials and Methods:
Materials: Analytical-grade FeCl?, FeCl?, NaOH, phenol, and rice husk.
Preparation: RH was acid-washed, dried, and calcinated. RH+Fe nanoparticles were synthesized via co-precipitation, centrifuged, dried, and powdered.
Characterization Techniques:
FTIR, XRD, SEM, TEM, and EDX were used to analyze structural, morphological, and elemental properties.
Particle size was ~78 nm; SEM confirmed Fe loading and colloidal structure.
Key Findings:
1. Adsorption Performance:
Optimal Conditions:
Dosage: 2.6 g/L
Contact Time: 60 min
pH: 6
Initial Phenol Concentration: 10 mg/L
Temperature: 50 °C
Maximum Removal Efficiency: 96%
Adsorption Capacity: 84–90 mg/g
2. Mechanism and Modeling:
Kinetics: Best fitted to pseudo-second-order model (R² = 0.96), indicating chemisorption.
Isotherms:
Langmuir (R² = 0.96) showed monolayer adsorption on a homogenous surface.
Freundlich also supported multilayer adsorption but with slightly lower fit.
Thermodynamics:
Positive ?H° confirmed endothermic and spontaneous adsorption.
Positive ?S° indicated increased randomness at the solid-liquid interface.
3. Regeneration and Reuse:
RH+Fe maintained 82% efficiency after 5 cycles of reuse using NaOH regeneration.
Demonstrated cost-effectiveness, stability, and environmental viability.
Conclusion
The RH+Fe adsorbent was used in the current work to achieve phenol efficiency. The characterisation demonstrates that the RH+Fe adsorbent was expertly made. The ideal parameters were concentration10 mg L-1, dosage 2.6 g L-1, pH 6, and time 60 min, with a 96 % phenol elimination efficiency.
The adsorption of phenol and RH+Fe was largely dependent on optimised parameters. The RH+Fe adsorbent data was best suited to the Langmuir isotherm and had an adsorption capacity of 90 mg g-1, which is monolayer adsorption between adsorbate and adsorbent, according to calculations made from the equilibrium data. The regeneration of phenol elimination indicated 82 % in the fifth stage. As a result, this study significantly advances our knowledge of viable and useful methods for removing phenol from adsorbents.
Data availability: All data generated or analysed during this study are included in this article. Any other datasets used during the current study are available from the corresponding author on reasonable request.
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