Meet Banu Ibrahimova, the student who designed an AI-controlled floating robot that removed up to 90.2% of a tested pollutant from model wastewater using UV light

Banu Ibrahimova, a student at School-Lyceum 6 in Baku, Azerbaijan, is working on a project to develop an AI-controlled floating robot that treats polluted water. The design focuses on industrial wastewater that may contain toxic cyanide-based compounds from gold mining and other industries. The project also tested the treatment method on model wastewater containing thiocyanate, phenol, and naphthalene.According to the International Science and Engineering Fair (ISEF), the robot uses ultraviolet light to break down pollutants and sensors to monitor water conditions throughout the treatment process. After 42 hours of irradiation, the reported conversion efficiencies were approximately 90.2% for thiocyanate, 86.1% for phenol, and 61% for naphthalene.How UV light breaks down cyanide in industrial wastewaterThe project addresses industrial wastewater that may contain highly toxic cyanide-based compounds, including waste from gold mining and other industries. These substances can threaten ecosystems and human health. The research investigates how ultraviolet photochemical processes can transform cyanide-related species into less toxic products. Under UV light at a wavelength of 185 nanometres, water molecules split and produce highly reactive hydroxyl radicals.These radicals oxidise cyanide ions, converting them into products including ammonia and carbon dioxide. In the final step described in the pathway, nitrogen atoms can be released as nitrogen gas.UV lamps and sensors support real-time wastewater treatmentThe proposed robot is designed to float on polluted water and operate in situ. It is equipped with xenon ultraviolet lamps enclosed in quartz tubes. Modified sensors continuously monitor several conditions during treatment, including pH, temperature, conductivity, cyanide concentration, turbidity, distance, and radiation background.The project presents this arrangement as a way to monitor water during remediation. The robot is AI-controlled, and the sensor data let it assess process efficiency and optimise the photochemical cleanup in real time.How did pollutant levels change during UV treatmentThe project evaluated treatment using model wastewater containing thiocyanate, phenol, and naphthalene. Researchers monitored contaminant concentrations using ion chromatography and high-performance liquid chromatography, also known as HPLC.The reported results showed that pollutant concentrations continued to decrease as irradiation time increased. After a treatment period of 42 hours, conversion efficiencies were approximately 90.2% for thiocyanate, 86.1% for phenol, and 61% for naphthalene. The figures differ across the three substances, with thiocyanate showing the highest reported conversion efficiency and naphthalene the lowest.These results describe the performance recorded for the model wastewater under the conditions used in the project. The results show decreasing concentrations over time, with a separate conversion percentage reported for each tested contaminant during the 42-hour treatment period.A proposed approach to sustainable industrial wastewater treatmentThe project also reported intermediate products formed during treatment. Their formation was presented as confirmation that an oxidative degradation pathway had occurred. Based on the findings, the project proposes a reagent-free approach that combines photochemical treatment with real-time water monitoring.The stated aim is to provide an efficient and sustainable technology for industrial wastewater remediation. The project description does not present the method as a treatment already deployed at industrial scale; it describes the robot design and reports tests using model wastewater.