Graphene has been regarded as a promising candidate channel material for flexible devices operating at radio-frequency (RF). In this work we fabricated and fully characterized double bottom-gate graphene field effect transistors on flexible polymer substrates for high frequency applications. We report a record high as-measured current gain cut-off frequency (ft) of 39 GHz. The corresponding maximum oscillation frequency (fmax) is 13.5 GHz. These state of the art high frequency performances are stable against bending, with a typical variation of around 10%, for a bending radius of up to 12 mm. To demonstrate the reliability of our devices, we performed a fatigue stress test for RF-GFETs which were dynamically bend tested 1000 times at 1 Hz. The devices are mechanically robust, and performances are stable with typical variations of 15%. Finally we investigate thermal dissipation, which is a critical parameter for flexible electronics. We show that at the optimum polarization the normalized power dissipated by the GFETs is about 0.35 mW μm(-2) and that the substrate temperature is around 200 degree centigrade. At a higher power, irreversible degradations of the performances are observed. Our study on state of the art flexible GFETs demonstrates mechanical robustness and stability upon heating, two important elements to assess the potential of GFETs for flexible electronics.
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http://dx.doi.org/10.1039/c6nr01521b | DOI Listing |
ACS Nano
January 2025
Battery and Electrochemistry Laboratory (BELLA), Institute of Nanotechnology, Karlsruhe Institute of Technology (KIT), Kaiserstr. 12, Karlsruhe 76131, Germany.
Improving interfacial stability between cathode active material (CAM) and solid electrolyte (SE) is vital for developing high-performance all-solid-state batteries (ASSBs), with compatibility issues among the cell components representing a major challenge. CAM surface coating with a chemically inert ion conductor is a promising approach to suppress side reactions occurring at the cathode interfaces. Another strategy to mitigate mechanical degradation involves utilizing single-crystalline particle morphologies.
View Article and Find Full Text PDFACS Appl Mater Interfaces
January 2025
CAS Key Laboratory of Green Process and Engineering, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China.
Maintaining human body temperature in both high and low-temperature environments is fundamental to human survival, necessitating high-performance thermal insulation materials to prevent heat exchange with the external environment. Currently, most fibrous thermal insulation materials are characterized by large weight, suboptimal thermal insulation, and inferior mechanical and waterproof performance, thereby limiting their effectiveness in providing thermal protection for the human body. In this study, lightweight, waterproof, mechanically robust, and thermal insulating polyamide-imide (PAI) grooved micro/nanofibrous aerogels were efficiently and directly assembled by electrospinning.
View Article and Find Full Text PDFACS Nano
January 2025
John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, United States.
Silicon carbide (SiC) is a semiconductor used in quantum information processing, microelectromechanical systems, photonics, power electronics, and harsh environment sensors. However, its high-temperature stability, high breakdown voltage, wide bandgap, and high mechanical strength are accompanied by a chemical inertness, which makes complex micromachining difficult. Photoelectrochemical (PEC) etching is a simple, rapid means of wet processing SiC, including the use of dopant-selective etch stops that take advantage of the mature SiC homoepitaxy.
View Article and Find Full Text PDFFront Nutr
January 2025
Department of Epidemiology and Health Statistics, Tianjin Medical University, Tianjin, China.
Background: Although more risk prediction models are available for feeding intolerance in enteral-nourishment patients, it is still unclear how well these models will work in clinical settings. Future research faces challenges in validating model accuracy across populations, enhancing interpretability for clinical use, and overcoming dataset limitations.
Objective: To thoroughly examine studies that have been published on feeding intolerance risk prediction models for enteral nutrition patients.
Front Neurorobot
January 2025
College of Artificial Intelligence, Taiyuan University of Technology, Jinzhong, Shanxi, China.
Accurate building segmentation has become critical in various fields such as urban management, urban planning, mapping, and navigation. With the increasing diversity in the number, size, and shape of buildings, convolutional neural networks have been used to segment and extract buildings from such images, resulting in increased efficiency and utilization of image features. We propose a building semantic segmentation method to improve the traditional Unet convolutional neural network by integrating attention mechanism and boundary detection.
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