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Institution

King Abdullah University of Science and Technology

EducationJeddah, Saudi Arabia
About: King Abdullah University of Science and Technology is a education organization based out in Jeddah, Saudi Arabia. It is known for research contribution in the topics: Catalysis & Membrane. The organization has 6221 authors who have published 22019 publications receiving 625706 citations. The organization is also known as: KAUST.


Papers
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Journal ArticleDOI
TL;DR: It is shown that water incorporated in nanometre-sized voids within the polymer microstructure is the key factor in charge trapping and device degradation and by inserting molecular additives that displace water from these voids, it is possible to increase the stability as well as uniformity to a high level sufficient for demanding industrial applications.
Abstract: Due to their low-temperature processing properties and inherent mechanical flexibility, conjugated polymer field-effect transistors (FETs) are promising candidates for enabling flexible electronic circuits and displays. Much progress has been made on materials performance; however, there remain significant concerns about operational and environmental stability, particularly in the context of applications that require a very high level of threshold voltage stability, such as active-matrix addressing of organic light-emitting diode displays. Here, we investigate the physical mechanisms behind operational and environmental degradation of high-mobility, p-type polymer FETs and demonstrate an effective route to improve device stability. We show that water incorporated in nanometre-sized voids within the polymer microstructure is the key factor in charge trapping and device degradation. By inserting molecular additives that displace water from these voids, it is possible to increase the stability as well as uniformity to a high level sufficient for demanding industrial applications.

320 citations

Journal ArticleDOI
TL;DR: The synthesis and exceptional gas transport properties of two robust, solution-processable ultra-microporous (<7 Å) PIM-polyimides are described – integrating a three-dimensional 9,10-diisopropyltriptycene contortion center into a rigid fused-ring dianhydride.
Abstract: This Communication describes the synthesis and exceptional gas transport properties of two robust, solution-processable ultra-microporous (<7 Å) PIM-polyimides – KAUST-PI-1 and KAUST-PI-2 – integrating a three-dimensional 9,10-diisopropyltriptycene contortion center into a rigid fused-ring dianhydride. Rotation about the imide bonds is restricted by ortho-substituted methyl groups in the diamine. Bridgehead substitution at the 9,10-positions compounds the benefi ts of triptycene on three fronts: [ 13 ] First, it offers tunability of the porous texture; second, the triptycene imparts rigidity to short bridgehead substituents, effectively enhancing the overall three-dimensionality and rigidity of the moiety; third, it bolsters solution-processability by enhancing solubility. Functionalizing the bridgeheads with short branched isopropyl chains [ 18 ] primes the microstructure for highly permeable and highly selective diffusion-dominated performance surpassing all known polymers in industrial gas separations [ 5 ] including hydrogen (H 2 /N 2 , H 2 /CH 4 ) and oxygen (O 2 /N 2 ) separations, which constitute ∼75% of the gas separation market. [ 19 ]

320 citations

Journal ArticleDOI
19 Nov 2014
TL;DR: This work proposes an end-to-end system that is aware of the camera and image model, enforces natural-image priors, while jointly accounting for common image processing steps like demosaicking, denoising, deconvolution, and so forth, all directly in a given output representation.
Abstract: Conventional pipelines for capturing, displaying, and storing images are usually defined as a series of cascaded modules, each responsible for addressing a particular problem. While this divide-and-conquer approach offers many benefits, it also introduces a cumulative error, as each step in the pipeline only considers the output of the previous step, not the original sensor data. We propose an end-to-end system that is aware of the camera and image model, enforces natural-image priors, while jointly accounting for common image processing steps like demosaicking, denoising, deconvolution, and so forth, all directly in a given output representation (e.g., YUV, DCT). Our system is flexible and we demonstrate it on regular Bayer images as well as images from custom sensors. In all cases, we achieve large improvements in image quality and signal reconstruction compared to state-of-the-art techniques. Finally, we show that our approach is capable of very efficiently handling high-resolution images, making even mobile implementations feasible.

319 citations

Journal ArticleDOI
TL;DR: In just the past five years, the field of Earth observation has progressed beyond the offerings of conventional space agency based platforms to include a plethora of sensing opportunities afforded by CubeSats, Unmanned Aerial Vehicles, and smartphone technologies that are being embraced by both for-profit companies and individual researchers.
Abstract: In just the past five years, the field of Earth observation has progressed beyond the offerings of conventional space agency based platforms to include a plethora of sensing opportunities afforded by CubeSats, Unmanned Aerial Vehicles (UAVs), and smartphone technologies that are being embraced by both for-profit companies and individual researchers. Over the previous decades, space agency efforts have brought forth well-known and immensely useful satellites such as the Landsat series and the Gravity Research and Climate Experiment (GRACE) system, with costs typically on the order of one billion dollars per satellite and with concept-to-launch timelines on the order of two decades (for new missions). More recently, the proliferation of smartphones has helped to miniaturise sensors and energy requirements, facilitating advances in the use of CubeSats that can be launched by the dozens, while providing ultra-high (3-5 m) resolution sensing of the Earth on a daily basis. Start-up companies that did not exist five years ago now operate more satellites in orbit than any space agency, and at costs that are a mere fraction of the cost of traditional satellite missions. With these advances come new space-borne measurements, such as real-time high-definition video for tracking air pollution, storm-cell development, flood propagation, precipitation monitoring, or even for constructing digital surfaces using structure-from-motion techniques. Closer to the surface, measurements from small unmanned drones and tethered balloons have mapped snow depths, floods, and estimated evaporation at sub-meter resolutions, pushing back on spatio-temporal constraints and delivering new process insights. At ground level, precipitation has been measured using signal attenuation between antennae mounted on cell phone towers, while the proliferation of mobile devices has enabled citizen-scientists to catalogue photos of environmental conditions, estimate daily average temperatures from battery state, and sense other hydrologically important variables such as channel depths using commercially available wireless devices. Global internet access is being pursued via high altitude balloons, solar planes, and hundreds of planned satellite launches, providing a means to exploit the Internet of Things as an entirely new measurement domain. Such global access will enable real-time collection of data from billions of smartphones or from remote research platforms. This future will produce petabytes of data that can only be accessed via cloud storage and will require new analytical approaches to interpret. The extent to which today's hydrologic models can usefully ingest such massive data volumes is unclear. Nor is it clear whether this deluge of data will be usefully exploited, either because the measurements are superfluous, inconsistent, not accurate enough, or simply because we lack the capacity to process and analyse them. What is apparent is that the tools and techniques afforded by this array of novel and game-changing sensing platforms present our community with a unique opportunity to develop new insights that advance fundamental aspects of the hydrological sciences. To accomplish this will require more than just an application of the technology: in some cases, it will demand a radical rethink on how we utilise and exploit these new observing systems to enhance our understanding of the Earth and its linked processes.

319 citations

Journal ArticleDOI
TL;DR: The proposed electrode structure capitalizes on the high specific capacitance of MnO2 and the ability of MXenes to improve conductivity and cycling stability and exhibited excellent cycling stability.
Abstract: Transition-metal carbides (MXenes) are an emerging class of two-dimensional materials with promising electrochemical energy storage performance. Herein, for the first time, by direct chemical synthesis, nanocrystalline e-MnO2 whiskers were formed on MXene nanosheet surfaces (e-MnO2/Ti2CTx and e-MnO2/Ti3C2Tx) to make nanocomposite electrodes for aqueous pseudocapacitors. The e-MnO2 nanowhiskers increase the surface area of the composite electrode and enhance the specific capacitance by nearly 3 orders of magnitude compared to that of pure MXene-based symmetric supercapacitors. Combined with enhanced pseudocapacitance, the fabricated e-MnO2/MXene supercapacitors exhibited excellent cycling stability with ∼88% of the initial specific capacitance retained after 10000 cycles which is much higher than pure e-MnO2-based supercapacitors (∼74%). The proposed electrode structure capitalizes on the high specific capacitance of MnO2 and the ability of MXenes to improve conductivity and cycling stability.

319 citations


Authors

Showing all 6430 results

NameH-indexPapersCitations
Jian-Kang Zhu161550105551
Jean M. J. Fréchet15472690295
Kevin Murphy146728120475
Jean-Luc Brédas134102685803
Carlos M. Duarte132117386672
Kazunari Domen13090877964
Jian Zhou128300791402
Tai-Shung Chung11987954067
Donal D. C. Bradley11565265837
Lain-Jong Li11362758035
Hong Wang110163351811
Peng Wang108167254529
Juan Bisquert10745046267
Jian Zhang107306469715
Karl Leo10483242575
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023141
2022371
20212,836
20202,809
20192,544
20182,251