Rice Husk Wastes as a Precursor for Synthesis and Adsorption Modeling of Silicon Oxide Nanoparticles for Methylene Blue and Textile Wastewater Treatment
Keywords:
Environmental remediation, textile industrial contamination, silicon-based nanoparticles, plant precursorAbstract
Silicon oxide nanoparticles (SiONPs) were successfully synthesized from rice husk waste using a low-temperature, bio-derived route, and their structural, optical, surface, and environmental remediation properties were comprehensively investigated. UV–visible spectroscopy revealed a strong absorption maximum at ~452–453 nm, corresponding to a reduced optical band gap of 2.73 eV, calculated using the Planck relation . This band gap is significantly lower than that of stoichiometric SiO₂ (≈5.0–9.0 eV), indicating a pronounced red shift attributed to non-stoichiometry (SiO), oxygen vacancies, surface defects, and heteroatom incorporation. FTIR analysis confirmed the presence of Si–O–Si and Si–O bonds, abundant surface hydroxyl (Si–OH) groups, and minor residual organic functionalities, supporting a defect-rich and surface-functionalized structure. XRF and SEM–EDX analyses showed that the nanoparticles are silicon-rich, with Si contents of ~90.9 wt%, alongside minor K (2.52 wt%), Ca (1.63 wt%), Mg (0.47 wt%), Al (0.20 wt%), P (0.15 wt%), and S (0.15 wt%), and no detectable transition-metal impurities, confirming that the visible-light activity is intrinsic to the SiONPs. Zeta potential measurements indicated a well-defined point of zero charge (PZC) at pH ≈ 5.8, with positive surface charge under acidic conditions and increasingly negative charge at neutral to alkaline pH, favoring adsorption of cationic pollutants. X-ray diffraction showed a silica-dominated, semi-crystalline system composed mainly of nanocrystalline quartz with minor magnesium and aluminium silicates and a significant amorphous fraction (≈17–25 wt%). Rietveld refinement yielded acceptable agreement factors (Rp = 6.21%, Rwp = 8.94%, χ² = 2.20) and crystallite sizes of 25–45 nm, lattice strain of (3.2–6.8) × 10⁻³, and dislocation densities of (0.5–1.6) × 10¹⁵ m⁻², indicating a defect-rich nanostructure. Dynamic light scattering confirmed a relatively narrow particle size distribution consistent with the nanocrystalline dimensions. The functional performance of the SiONPs was demonstrated through adsorption studies using methylene blue and real textile wastewater. Adsorption kinetics followed a pseudo-second-order model (R² = 0.987), while equilibrium data fitted the Langmuir isotherm best (qmax = 92.5 mg g⁻¹, R² = 0.994), indicating monolayer adsorption on a homogeneous surface. When applied to textile effluent, the SiONPs achieved removal efficiencies of 91.2% for color, 77.2% for COD, 74.4% for BOD₅, and 74.4% for TSS. Overall, the combination of visible-light activity, tunable surface charge, high adsorption capacity, and strong agreement across multiple characterization techniques highlights rice-husk-derived SiONPs as low-cost, sustainable, and highly effective materials for wastewater treatment, photocatalysis, and related environmental applications
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Nyeneime William Akpanudo (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors retain copyright and grant the journal the right of first publication. Articles published in this journal are licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), permitting unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
How to Cite
Similar Articles
- Samuel Awolumate, Bernadette Tosan Fregene, Efficiency Status in Artisanal Fishing Amidst Overfishing, Pollution, and Infrastructure Development on Inland Water Fisheries in Nigeria , Applied Science, Computing, and Energy: Vol. 2 No. 1 (2025): VOLUME 2 ISSUE 1
- Faith D. Olasunkanmi, Chidinma M. Dike, Ja’afaru Umma Hani, Taiwo Suliyat Mofoyeke, Esther Oshaji, Ijeoma Joy Nwajiaku, Oluwakemi Adesola, Adebayo Adegbenro, AI and ML Assessment of Performance-Based Financing Models in Health Care: A Review , Applied Science, Computing, and Energy: Vol. 3 No. 2 (2025): VOLUME 3 ISSUE 2
- Oyedeji Olugbenga James, Mojeed Olawale, INNOVATIONS IN CHRONIC DISEASE MANAGEMENT USING DIGITAL HEALTH TECHNOLOGIES , Applied Science, Computing, and Energy: Vol. 2 No. 2 (2025): VOLUME 2 ISSUE 2
- Prisca Ijeoma Okochi, Comfort C. Olebara, Generative Adversarial Network (Gans) For Realistic Digital Human Creation in Academia , Applied Science, Computing, and Energy: Vol. 3 No. 2 (2025): VOLUME 3 ISSUE 2
- Boniface Egbu Odor, Emmanuel Nzegbule, Precious Chieze Chikezie, Tochukwu Nnamdi Onyemuche, N. Jerius Ejeje, Doris Olachi Alilonu, Obinna Charles Ekoh, Peter Chibuzor Onuoha, Marycynthia Amarachi Ojiakor, Assessing the effect of herbicide use (Glyphosate) on fruiting and phytochemical characteristics of edible soil mushroom (Pleurotus ostreatus) , Applied Science, Computing, and Energy: Vol. 3 No. 2 (2025): VOLUME 3 ISSUE 2
- Ukeme Nsikak Essien, Bright Aiyehirue Agwogie, Quantitative Assessment of Carbon Sequestration Potential and Biomass Accumulation in Selected Forest Ecosystems of Southern Nigeria , Applied Science, Computing, and Energy: Vol. 4 No. 3 (2026): Volume 4, Issue 3
- Anthony I. G. Ekedegwa, Integrated Optimization of Nuclear Energy Transmission Systems to Minimize Grid and Data Center Power Losses , Applied Science, Computing, and Energy: Vol. 4 No. 3 (2026): Volume 4, Issue 3
- Ibrahim Bashir Usman, Auwalu Musa, Abdullahi Lawal, Aliyu Muhammad, First-Principles G0W0+BSE Calculations: Electronic and Optical Properties of Zns Monolayer , Applied Science, Computing, and Energy: Vol. 3 No. 2 (2025): VOLUME 3 ISSUE 2
- Babatunde Ogunyemi, COMPUTATIONAL DESIGN OF PYRIDYL-BENZALDEHYDE DERIVATIVES AS ECO-FRIENDLY CORROSION INHIBITORS: A DFT-BASED STUDY , Applied Science, Computing, and Energy: Vol. 2 No. 2 (2025): VOLUME 2 ISSUE 2
- Abubakar Tahiru, Oluwasanmi M. Odeniran, The Application of Artificial Intelligence to Develop Predictive models that Improve Harvesting Efficiency while Protecting biodiversity in Sustainable Forest Ecosystems. , Applied Science, Computing, and Energy: Vol. 1 No. 1 (2024): VOLUME 1 ISSUE 1
You may also start an advanced similarity search for this article.