Diazinon is a very toxic pesticide for animals and humans that is widely used in the agricultural sector, so this pollutant needs to be reduced or eliminated in the environment through photodegradation using photocatalysts derived from metal oxides. The catalytic activity of metal oxides is enhanced by adding a support material and increasing the surface area by reducing the particle size to nano size. In this study, kaolin as a source of Al2O3 and golden snail shells as a source of CaO which used to synthesize Al2O3-CaO nanoparticles (NPs) with a simple and environmentally friendly method using plant infusions. Synthesis of Al2O3-CaO NPs using infused red guava leaves (Psidium guajava L.) had been done by utilized the secondary metabolites as reducing agents and stabilizers in the nanoparticle synthesis. FTIR analysis confirmed the presence of alumina (Al-O) groups at wave numbers 850 – 650 cm-1 and CaO at 3642 cm-1. XRD analysis showed NPs Al2O3-CaO had cubic with the crystal size of 14.59 nm. The morphology of Al2O3-CaO NPs showed in the SEM pictures were agglomerated. Al2O3-CaO NPs degraded diazinon by 75% within 180 minutes under UV radiation. Thus, this research not only reduce waste material, but also reduces water pollutant.

The purpose of this research  was to examine the value of the Wien’s constant using PhET Simulation virtual laboratory and simple numerical approach. The independent and dependent variable is blackbody temperature (T) and maximum wavelength (λ_max). In the use of a virtual laboratory, research is carried out by shifting the black body temperature feature so  the graph will display a spectral power density that varies to the wavelenght. Numerical approach was used in this research is Newton Raphson methods by Python program. Both of simulation and numerical approach yield the value of the maximum wavelength (λ_max) for a black body temperature variation. The black body temperatures and their appropriate maximum wavelength data then analyzed using linear regression. Final result show that value Wien’s constant using PhET is 2,93 × 10-3 mK with relative error obtained is 1,07 % while using Newton Raphson the Wien’s constant value obtained is 3,07 × 10-3 mK with relative error is 5,90 %. The two approachs carried out produce data that slightly different, but still in a very good accucracy range when compared with theory. So, PhET Simulation and Newton Raphson methods effective to examine the value of the Wien’s constant.