Development of clay supported SiO2 nanocomposite: Synthesis and multifunctional studies for antioxidant, photocatalysis and sensors

In this study, a clay/SiO 2 nanocomposite was made from used rice husk integrating eco-friendly materials employing a reflux process. Structural and spectroscopic analysis revealed a crystalline clay/SiO 2 composite with an average size of approximately 26 nm. The developed material was subsequently tested for radical scavenging activity, photocatalysis, and sensor detection investigation. Clay/SiO 2 antioxidant activity increased by 88 % with a smaller IC 50 of 565 μg/mL when treated with 2-diphenylpicrylhydrazyl (DPPH) free radical. In comparison to the extracted silica from rice husk, orange G dye (OG) had the highest photocatalytic degradation activity at 99 % in 150 min. This is attributed to increased surface area (273.6 m 2 /g), pore diameter (5.431 nm), and oxygen vacancies, respectively. Kinetic analysis demonstrates that both clay/SiO 2 and SiO 2 are suitable for first-order models. The clay/SiO 2 degradation rate constant ( K f . o = 20.71 × 10 − 3 ) is higher than SiO 2 ( K f . o = 6.33 × 10 − 3 ) . This study used tomato juice (TJ) and oxalic acid (OA) sensors to evaluate their performance and sensitivity using interfacial kinetics. Electrochemical analysis, such as cyclic voltammetry (CV) and differential pulse voltammetry (DPV), exhibited outstanding sensing capability with 0–240 mM concentration ranges, a high sensitivity of 8 × 10⁻⁵ A·cm⁻²·mM⁻¹ and a low detection limit of 15.67 mM for OA and 13.46 mM for TJ. DPV experiments revealed that OA and TJ sensors have remarkable selectivity against common interferers. These findings emphasize its promise in food matrices, water purification, and healthcare applications. • Conversion of waste rice husk into Clay/SiO 2 nanocomposite by acid leaching method. • Maximum (88 %) Antioxidant activity was evaluated using DPPH radical. • Developed material was applied to measure the photocatalysis of orange G dye. • Electrochemical sensors activity was successfully checked by using CV and DPV method.