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  • Presentation

    Over 19% Efficiency in Ternary Organic Solar Cells Enabled by n-Type Dopants

    (FUNDACIO DE LA COMUNITAT VALENCIANA SCITO, 2023-10-18) Ling, Zhaoheng; Material Science and Engineering Program; Physical Science and Engineering (PSE) Division; KAUST Solar Center (KSC)

    The use of molecular dopants is an intriguing strategy for achieving a high power conversion efficiency (PCE) in organic solar cells (OSCs). However, despite its promise, the number of molecular dopants that enhance the PCE of OPVs remains limited. In this study, we introduce two novel n-type dopants, Ethyl Viologen (EV) and Methyl Viologen (MV), into ternary PM6:BTP-eC9-PC71BM bulk heterojunction (BHJ) OPVs and compare their performance with other known n-type dopants. Our findings reveal that the addition of EV and MV results in remarkable enhancements in PCE, reaching maximum values of 19.03% and 18.61%, respectively, along with fill factor (FF) values of 80% and 79.2%, respectively. We demonstrate that EV and MV function as both n-type dopants and microstructure modifiers, inducing enhancements in the absorption coefficient, balancing the charge carrier mobility, increasing the carrier lifetime, and reducing charge carrier recombination. Our results suggest that low concentrations of EV and MV can enhance the performance of highly efficient organic solar cells to levels beyond those achievable by the pristine BHJ.

  • Presentation

    Global Sensitivity Analysis of an Oil Spill Model: a Regularized Regression Approach

    (2021-12) Mittal, Hari Vansh RAI; Hammoud, Mohamad Abed ElRahman; Maitre, Olivier; Hoteit, Ibrahim; Knio, Omar; Mechanical Engineering Program; Physical Science and Engineering (PSE) Division; Earth Science and Engineering Program; Extreme Computing Research Center; Applied Mathematics and Computational Science Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division; Ecole Polytechnique, Palaiseau Cedex, France

    Polynomial chaos expansions (PCEs) are employed to propagate parametric uncertainties in an oil spill model. The computations focus on high-resolution simulations in the Red Sea, using the Modelo Hidrodinâmico (MOHID) oil spill model driven by state-of-the-art met-ocean data. In this study, six input parameters, related to numerical modeling and oil properties, are considered. A surrogate model is generated, which predicts the sensitivities of MOHID's outputs termed as Quantities of Interest (QoIs), which encompasses physical properties of oil and its transport in the Red Sea. Different release locations are selected depending upon the climate and topography of the basin. At least 600 Latin Hypercube samples are used for parameterization and the coefficients of PC expansions are computed using regularized regression based on the LASSO algorithm. The performance of the surrogate model is assessed in terms of the L1 and L2 norms of errors associated with different orders of polynomials. Simulations report low L1 and L2 norms of errors (less than 7% ) for the considered QoIs. Furthermore, the global sensitivity analysis of the QoIs reports the significance of tertiary sensitivity terms (sensitivity greater than 0.2%).

  • Presentation

    GROWTH PERFORMANCE, PROXIMATE COMPOSITION, AND FEED CONVERSION RATIO OF JUVENILES AND PRE-ADULT GILT HEAD SEABREAM Sparus aurata FED COST-EFFECTIVE, IMPROVED DIETS

    (European Aquaculture Society, 2022) Zehra, Seemab; Mohamed, A.; Pantanella, Edoardo; De Mello, Paulo; Laranja, Joseph Leopoldo Quimno; Saleh, R.; Abul Kasim, Aboobucker; Al Shaikhi, A.; Al-Suwailem, Abdulaziz M.; King Abdullah University of Science and Technology, Beacon Development. 4700 King Abdullah University of Science and Technology, 23955-6900 Thuwal. Kingdom of Saudi Arabia.; Beacon Development Company; Beacon Development Department; Office of the VP, KAUST Innovation; Ministry of Environment, Water and Agriculture, King AbdulAziz Rd., 11195 Riyadh, Saudi Arabia
  • Presentation

    Load-Altering Attacks Against Power Grids Under COVID-19 Low-Inertia Conditions

    (IEEE, 2023-07-16) Lakshminarayana, Subhash; Ospina, Juan; Konstantinou, Charalambos; Resilient Computing and Cybersecurity Center; Electrical and Computer Engineering Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division; Warwick; LANL

    The COVID-19 pandemic has impacted our society by forcing shutdowns and shifting the way people interacted worldwide. In relation to the impacts on the electric grid, it created a significant decrease in energy demands across the globe. Recent studies have shown that the low demand conditions caused by COVID-19 lockdowns combined with large renewable generation have resulted in extremely low-inertia grid conditions. In this work, we examine how an attacker could exploit these scenarios to cause unsafe grid operating conditions by executing load-altering attacks (LAAs) targeted at compromising hundreds of thousands of IoT-connected high-wattage loads in low-inertia power systems. Our study focuses on analyzing the impact of the COVID-19 mitigation measures on U.S. regional transmission operators (RTOs), formulating a plausible and realistic least-effort LAA targeted at transmission systems with low-inertia conditions, and evaluating the probability of these large-scale LAAs. Theoretical and simulation results are presented based on the WSCC 9-bus and IEEE 118-bus test systems. Results demonstrate how adversaries could provoke major frequency disturbances by targeting vulnerable load buses in low-inertia systems and offer insights into how the temporal fluctuations of renewable energy sources, considering generation scheduling, impact the grid’s vulnerability to LAAs.

  • Presentation

    Classification Of Environmental Micro-Fibres Using Stimulated Raman Microspectroscopy

    (IEEE, 2023-06-26) Laptenok, Siarhei; Genchi, Luca; Martin, C.; Balkhair, Fadia; Duarte, Carlos M.; Liberale, Carlo; Computer, Electrical and Mathematical Sciences and Engineering, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia; Biological and Environmental Science and Engineering (BESE) Division; Bioscience Program; Beacon Development Department; Office of the VP, KAUST Innovation; Marine Science Program; Red Sea Research Center (RSRC); Computational Bioscience Research Center (CBRC); Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division; Red Sea Global, SEZ Department of Environmental Sustainability, AlRaidah Digital City, Riyadh 12382 – 6726, Saudi Arabia

    The mass usage of plastic materials in daily life has exponentially increased the amount of plastic waste in the environment. Various environmental factors degrade bigger plastic debris into smaller microplastic particles (less than 5 mm in size). Those particles have been detected in every possible environment, from oceans to fresh bottled water, from deserts to agricultural soils, food and air, and human blood. Due to its long degradation time and high surface-to-value ratio, microplastic can become an efficient vehicle for various pollutants that can accumulate in time. Therefore, accumulation in the human tissue will likely have a negative long-term effect. Microfibers are considered the most abundant microparticle type in the environment - their size (small, often < 15 μm in diameter, and relatively long length) and light weight allow easy and fast distribution even using aerial pathways.