KAUST and Bruker Corporation have launched the KAUST–Bruker Center of Excellence (CoE) in Magnetic Resonance, formalizing a long-standing collaboration. The CoE will provide KAUST users access to cutting-edge magnetic resonance technologies and serve as a training site. Bruker showcased advanced technologies including the world's first 900 MHz wide-bore NMR spectrometer and a 500 MHz super wide-bore MRI spectrometer. Why it matters: This CoE enhances KAUST's position as a leading research institution in the region and fosters innovation in magnetic resonance research and applications.
KAUST and Bruker have renewed their Memorandum of Understanding and expanded it into a Strategic Partnership and Collaboration Agreement. The initial MoU launched the KAUST-Bruker Center of Excellence (CoE) for Magnetic Resonance (MR) located in the University's Core Laboratories in 2018. The expanded agreement extends the CoE to include X-ray technologies, enhancing technological interaction between the two organizations. Why it matters: This partnership strengthens KAUST's research capabilities and positions it as a leader in scientific innovation in Saudi Arabia and the wider region.
Professor Arnab Pain's group at KAUST discovered new insights on how a malaria protein enables parasites to spread malaria in human cells. Professor Haavard Rue's group upgraded the Integrated and Nested Laplace Approximation (INLA) for faster real-time modeling of large datasets. A KAUST-led study examined the stability of Y-series nonfullerene acceptors for organic solar cells. Why it matters: KAUST continues producing impactful research across diverse fields from medicine to climate change, advancing scientific knowledge and potential applications.
AMRC researchers Jide Oyebanji and Tarcisio Silvia will present papers at the MATLAB User Group Meeting in Abu Dhabi. Oyebanji's paper focuses on the 'Design of an Interactive TPMS Designing Desktop App' using MATLAB's numerical capabilities. Silvia's presentation discusses the optimization of MIMO active vibration controllers for electromechanical systems using MATLAB Simulink and Particle Swarm Optimization. Why it matters: The presentations showcase the application of computational tools like MATLAB in advanced materials research and digital engineering within the UAE.
KAUST Discovery will host a webinar on solvent-based recycling of lithium-ion batteries. The presentation will be given by Dr. Yaocai Bai, an R&D Staff Scientist at Oak Ridge National Laboratory (ORNL). The talk will explore solvent-based separation processes to efficiently separate electrode materials from metal foils in end-of-life batteries and manufacturing scraps. Why it matters: Battery recycling is a key area for sustainability efforts in the region, as it has implications for energy independence and environmental protection.
Baker Hughes has donated JewelSuite™ reservoir modeling software to KAUST to enhance teaching, learning, and research. The software simplifies modeling and streamlines the building of accurate 3-D reservoir models. It will enable students and faculty to gain a clearer picture of the subsurface and predict oil or gas deposits. Why it matters: This donation will help KAUST train future leaders in the petroleum engineering industry and advance research in reservoir modeling.
KAUST's Imaging and Characterization Core Lab (IAC) co-hosted a materials science optical microscopy workshop with Leica Microsystems. The workshop included hands-on training led by IAC staff scientist Ebtihaj Bukhari and Leica specialist Philippe Vignal. Researchers from KAUST, King Abdulaziz University (KAU), and Obeikan participated in the event. Why it matters: Such workshops contribute to developing local expertise in advanced materials science techniques, crucial for Saudi Arabia's industrial and research sectors.
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.