KAUST and NADEC have signed an MoU to collaborate on agricultural research, technology development, and professional training to enhance Saudi Arabia's food systems. The partnership aims to translate scientific insights into practical solutions for a resilient and stable food and agriculture sector. KAUST researchers will gain access to NADEC's fields to test and scale solutions. Why it matters: This collaboration between a leading research university and a major agricultural company can accelerate innovation in sustainable food production, addressing critical challenges like water scarcity and rising temperatures in the region.
MEDAD, a KAUST spin-off, won the 2020 MEED Sustainability Medal for its "Innovative Hybrid Solar Desalination Cycle." The MEDAD hybrid cycle desalinates seawater using solar energy at 60-80 degrees Celsius, combining adsorption with multi-effect desalination. The cycle achieved performance levels of 20% of thermodynamic limits and a water production cost of $0.48/m3. Why it matters: This award recognizes the potential of KAUST-developed technology to address critical water scarcity challenges in the GCC region through sustainable and cost-effective desalination.
Deanna Lacoste is an assistant professor of mechanical engineering in KAUST's Physical Science and Engineering Division. She is featured in a "Faculty Focus" section. Why it matters: This is a routine faculty highlight from KAUST.
The Directed Energy Research Center (DERC) is partnering with Montena Technology to study high-altitude electromagnetic pulses and design infrastructure safeguards. DERC is also collaborating with Radaz to evaluate ground penetrating and synthetic aperture radars in Abu Dhabi, aiming to identify natural resources. Additionally, DERC and Université de Picardie Jules Verne are working on laser sources and sensors, with a DERC researcher spending four years in France. Why it matters: These partnerships enhance DERC's research capabilities in critical areas like infrastructure protection, resource exploration, and advanced sensing technologies.
Nestlé Saudi Arabia and KAUST have signed a memorandum of understanding to collaborate on research in packaging, agriculture, and food technology. The partnership aims to develop sustainable solutions that enhance public health, strengthen food safety standards, and support knowledge localization, aligning with Saudi Vision 2030. KAUST will contribute its research expertise, while Nestlé will provide its global food technology expertise. Why it matters: This partnership signifies a commitment to advancing food and agriculture innovation in Saudi Arabia, fostering a sustainable food ecosystem and promoting healthier lifestyles in alignment with national goals.
KAUST and the Saudi Food and Drug Authority (SFDA) have partnered to develop a new method using nuclear magnetic resonance (NMR) to detect adulterants in olive oil. The method aims to identify and quantify vegetable oils mixed with olive oil, addressing concerns about the mislabeling of olive oil in the Saudi market. KAUST's comprehensive suite of NMR machines was critical for the project. Why it matters: This collaboration enhances food safety and quality control in Saudi Arabia, a major olive oil importer, and helps to ensure consumers receive authentic, high-quality products.
KAUST spin-out company NOMADD, which specializes in robotic PV cleaning systems, has secured a Series B investment from Saudi construction company CEPCO. The investment will support NOMADD's project pipeline and growth ambitions, enabling them to scale operations and serve more customers. CEPCO will also advise on technology development and local manufacturing in Saudi Arabia. Why it matters: This investment validates KAUST's innovation fund strategy and supports the deployment of sustainable energy solutions in the region, leveraging local expertise and manufacturing.
Marcus Engsig from DERC will present a paper at the MATLAB User Group Meeting in Abu Dhabi on October 6. The paper, titled ‘Generalization of Higher Order Methods For Fast Iterative Matrix Inversion Compatible With GPU Acceleration’, discusses a novel approach to matrix inversion using GPUs. The method, named Nested Neumann, achieves 4-100x acceleration compared to standard MATLAB methods for large matrices. Why it matters: This research contributes to faster computation in numerical and physical modeling, crucial for processing large datasets in various scientific and engineering applications in the region.