Silica and graphene mediate arsenic detection in mature rice grain by a newly patterned current–volt aptasensor

Abstract Arsenic is a major global threat to the ecosystem. Here we describe a highly accurate sensing platform using silica nanoparticles/graphene at the surface of aluminum interdigitated electrodes (Al IDE), able to detect trace amounts of arsenic(III) in rice grain samples. The morphology and electrical properties of fabricated Al IDEs were characterized and standardized using AFM, and SEM with EDX analyses. Micrometer scale Al IDEs were fabricated with silicon, aluminum, and oxygen as primary elements. Validation of the bare Al IDE with electrolyte fouling was performed at different pH levels. The sensing surface was stable with no electrolyte fouling at pH 7. Each chemical modification step was monitored with current–volt measurement. The surface chemical bonds were characterized by fourier transform infrared spectroscopy (FTIR) and revealed different peaks when interacting with arsenic (1600–1000 cm−1). Both silica nanoparticles and graphene presented a sensitive limit of detection as measured by slope calibration curves at 0.0000001 pg/ml, respectively. Further, linear regression was established using ΔI (A) = 3.86 E−09 log (Arsenic concentration) [g/ml] + 8.67 E−08 [A] for silica nanoparticles, whereas for graphene Y = 3.73 E−09 (Arsenic concentration) [g/ml] + 8.52 E−08 on the linear range of 0.0000001 pg/ml to 0.01 pg/ml. The R2 for silica (0.96) and that of graphene (0.94) was close to the maximum (1). Modification with silica nanoparticles was highly stable. The potential use of silica nanoparticles in the detection of arsenic in rice grain extract can be attributed to their size and stability