King Abdullah University of Science and Technology

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.

Organic field-effect transistor-based flexible sensors

Abstract: Flexible electronic devices have attracted a great deal of attention in recent years due to their flexibility, reduced complexity and lightweight. Such devices can conformably attach themselves to any bendable surface and can possess diverse transduction mechanisms. Consequently, with continued emphasis on innovation and development, major technological breakthroughs have been achieved in this area. This review focuses on the advancements of using organic field-effect transistors (OFETs) in flexible electronic applications in the past 10 years. In addition, to the above mentioned features, OFETs have multiple advantages such as low-cost, readout integration, large-area coverage, and power efficiency, which yield synergy. To begin with, we have introduced organic semiconductors (OSCs), followed by their applications in various device configurations and their mechanisms. Later, the use of OFETs in flexible sensor applications is detailed with multiple examples. Special attention is paid to discussing the effects induced on physical parameters of OFETs with respect to variations in external stimuli. The final section provides an outlook on the mechanical aspects of OSCs, activation and revival processes of sensory layers, small area analysis, and pattern recognition techniques for electronic devices.

Drag Reduction by Leidenfrost Vapor Layers

Abstract: We demonstrate and quantify a highly effective drag reduction technique that exploits the Leidenfrost effect to create a continuous and robust lubricating vapor layer on the surface of a heated solid sphere moving in a liquid. Using high-speed video, we show that such vapor layers can reduce the hydrodynamic drag by over 85%. These results appear to approach the ultimate limit of drag reduction possible by different methods based on gas-layer lubrication and can stimulate the development of related energy saving technologies.

A dynamically reconfigurable Fano metamaterial through graphene tuning for switching and sensing applications

Abstract: We report on a novel electrically tunable hybrid graphene-gold Fano resonator. The proposed metamaterial consists of a square graphene patch and a square gold frame. The destructive interference between the narrow- and broadband dipolar surface plasmons, which are induced respectively on the surfaces of the graphene patch and the gold frame, leads to the plasmonic equivalent of electromagnetically induced transparency (EIT). The response of the metamaterial is polarization independent due to the symmetry of the structure and its spectral features are shown to be highly controllable by changing a gate voltage applied to the graphene patch. Additionally, effective group index of the device is retrieved and is found to be very high within the EIT window suggesting its potential use in slow light applications. Potential outcomes such as high sensing ability and switching at terahertz frequencies are demonstrated through numerical simulations with realistic parameters.

Finding Tiny Faces in the Wild with Generative Adversarial Network

Abstract: Face detection techniques have been developed for decades, and one of remaining open challenges is detecting small faces in unconstrained conditions. The reason is that tiny faces are often lacking detailed information and blurring. In this paper, we proposed an algorithm to directly generate a clear high-resolution face from a blurry small one by adopting a generative adversarial network (GAN). Toward this end, the basic GAN formulation achieves it by super-resolving and refining sequentially (e.g. SR-GAN and cycle-GAN). However, we design a novel network to address the problem of super-resolving and refining jointly. We also introduce new training losses to guide the generator network to recover fine details and to promote the discriminator network to distinguish real vs. fake and face vs. non-face simultaneously. Extensive experiments on the challenging dataset WIDER FACE demonstrate the effectiveness of our proposed method in restoring a clear high-resolution face from a blurry small one, and show that the detection performance outperforms other state-of-the-art methods.

Silicon-Compatible Photodetectors: Trends to Monolithically Integrate Photosensors with Chip Technology

Abstract: Encouraged by the increasing requirements of intelligent equipment, silicon integrated circuit–compatible photodetectors that support single-chip photonic–electronic systems have gained considerable progresses. Advanced materials have resulted in enhanced device performance based on traditional photovoltaic effect and photoconductive effect, and novel device designs have catalyzed new working mechanisms combing rapid photoresponse and high responsivity gain. Surprising applications are developed using monolithic photonic–electronic platforms, and the developing integration strategies keep pace with the developing complementary metal-oxide-semiconductor techniques as well as nonsilicon substrates. Here, the recent developments in silicon-compatible photodetectors, both in device advances and their integration routes, are reviewed. Meanwhile, the progresses, challenges, and possible future directions in this field are discussed and concluded.