KAUST Professor Derya Baran and her team at startup iyris have developed transparent solar panels that can turn windows into a source of renewable energy. The technology allows buildings to generate their own electricity, aligning with Saudi Vision 2030's goals for sustainable energy. iyris' first customer is the Red Sea Farm, another KAUST-based business, which aims to use the windows to improve plant growth and crop yield. Why it matters: This innovation could significantly reduce reliance on fossil fuels and promote sustainable urban development in the region, where cooling demands drive high electricity consumption.
KAUST Ph.D. student Sara Abbas and SABIC researcher won a poster award at the Royal Society of Chemistry’s 13th International Conference on Materials Chemistry. The research focuses on smart window technology using electrochromism. The technology can change its appearance and transmittance in response to electrical voltage. Why it matters: This award highlights the importance of materials chemistry research at KAUST and SABIC, particularly for applications suited to warm climates.
KAUST participated in the International Exhibition & Conference on Higher Education in Riyadh, showcasing interdisciplinary research and startups. KAUST researchers presented smart solar windows that convert sunlight into electricity using organic photovoltaic materials. Another KAUST team developed SandX, a sand and paraffin wax composite, which significantly reduced water evaporation and increased crop yields in field trials. Why it matters: These innovations demonstrate KAUST's commitment to advancing sustainable energy and desert agriculture in Saudi Arabia through cutting-edge research and technology commercialization.
KAUST researchers have developed a dual-use wireless sensor system that monitors both traffic congestion and flood incidents in cities. The system combines ultrasonic range finders and infrared thermal sensors to provide real-time, accurate data on traffic flow and roadway flooding. Data is sent to central servers and assimilated with satellite data to form real-time maps and forecasts. Why it matters: This technology can provide up-to-the-minute warnings for flash floods and traffic, enabling rapid emergency response and potentially saving lives in urban environments.
The KAUST Smart Home has received LEED Platinum certification, ranking second globally with a score of 94. The project retrofitted an existing home with features like 120 solar panels and hydropanels producing drinking water from atmospheric humidity. It also includes a leak detection system and smart fill windows controllable via touch panel. Why it matters: This demonstrates how existing infrastructures in the region can be improved to meet sustainability goals using smart technology.
KAUST researchers have developed solar panels with 4D-printed legs that readjust their position to track the sun's movement without consuming electrical energy. The design uses smart materials that contract when exposed to sunlight, tilting the panel towards the sun. A multidisciplinary team of interns collaborated on the project, integrating physics, electrical engineering, and mechanical engineering expertise. Why it matters: This low-cost, energy-efficient solar-tracking technology could significantly increase the energy output of solar cells, offering a viable renewable energy solution for the region and beyond.
KAUST led a session at the World Economic Forum's Meeting of the New Champions in Dalian, China, focusing on sustainability science. President Tony Chan and faculty members Peiying Hong, Mohamed Eddaoudi, and Derya Baran presented KAUST's research in water reuse, carbon capture, and transparent solar cells. Derya Baran highlighted KAUST spinoff iyris, which aims to turn windows into solar power plants. Why it matters: This showcases KAUST's role as an innovative hub for global research and education, particularly in green technologies, and highlights the university's commitment to addressing environmental challenges.
This paper proposes a smart dome system for mosques that uses machine learning to automatically control dome ventilation based on weather conditions and outside temperatures. The system was tested on the Prophet Mosque in Saudi Arabia using K-Nearest Neighbors and Decision Tree algorithms. The Decision Tree algorithm achieved a higher accuracy of 98% compared to 95% for the k-NN algorithm.