Former Saudi Research Science Institute (SRSI) student Abdullatif, now a junior at Berkeley, published a paper in the Journal of the American Chemical Society (JACS). The paper, "Isomerically Pure Tetramethylrhodamine Voltage Reporters," details the design, synthesis, and application of Rhodamine Voltage Reporters (RhoVRs). Abdullatif, who worked at KAUST during her SRSI program on carbon dioxide capture, plans to return for advanced studies. Why it matters: This highlights KAUST's role in nurturing young Saudi talent in STEM and contributing to high-impact scientific research.
KAUST researchers have developed an artificial electronic retina mimicking the behavior of rod retina cells, utilizing a hybrid perovskite material (MAPbBr3) embedded in PVDF-TrFE-CEF. The photoreceptor array, made of metal-insulator-metal capacitors, detects light intensity through changes in electrical capacitance. Connected to a CMOS-sensing circuit and a spiking neural network, the 4x4 array achieved around 70 percent accuracy in recognizing handwritten numbers. Why it matters: This research paves the way for energy-efficient neuromorphic vision sensors and advanced computer vision applications, potentially revolutionizing camera technology.
KAUST researchers in the Sensors Lab are developing neuromorphic circuits for vision sensors, drawing inspiration from the human eye. They created flexible photoreceptors using hybrid perovskite materials, with capacitance tunable by light stimulation, mimicking the human retina. The team collaborates with experts in image characterization and brain pattern recognition to connect the 'eye' to the 'brain' for object identification. Why it matters: This biomimetic approach promises advancements in AI, machine learning, and smart city development within the region.
Researchers at KAUST have developed a new method called Deep State Identifier for extracting information from videos for reinforcement learning. The method learns to predict returns from video-encoded episodes and identifies critical states using mask-based sensitivity analysis. Experiments demonstrate the method's potential for understanding and improving agent behavior in DRL.
KAUST researchers led by Prof. Omar Mohammed developed safer scintillation materials to improve X-ray imaging. A team led by Assoc. Prof. Yoji Kobayashi discovered a calcium-based catalyst that unexpectedly synthesizes ammonia. Why it matters: These research advancements from KAUST contribute to scientific innovation in materials science and sustainable chemical processes within the region.
KAUST researchers from the Red Sea Research Center are studying mesophotic reefs (40-150m deep) as potential climate refuges for corals threatened by marine heatwaves. These deeper reefs experience less heat and light stress compared to shallow-water corals. Advanced tools like submarines and robots are now enabling the study of these previously neglected ecosystems. Why it matters: Understanding the resilience of Red Sea corals could provide crucial insights for global coral reef conservation strategies amid climate change.
KAUST professor Pierre Magistretti has been elected to the Norwegian Academy of Science and Letters. His election recognizes his contributions to neuroscience, specifically his work on lactate's role in brain function. Magistretti's research focuses on the lactate shuttle system and how neurons and glial cells cooperate to meet energy demands. Why it matters: This honor highlights KAUST's contribution to international neuroscience and can foster further collaboration in the field.
KAUST researchers developed a laser-based sensor that exploits the "chirp" phenomenon in semiconductor lasers to accurately measure gas temperature in combustion systems. The sensor uses spectroscopic measurements at very fast rates (1.0 MHz) and can measure temperature at the nanosecond timescale at repetition rates of thousands of kHz. The new sensor reduces uncertainty compared to previous methods and works rapidly in transient shock tube experiments. Why it matters: This in-house development provides a non-invasive, accurate, and easily implementable system for combustion research, with implications for understanding and improving energy efficiency.