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Self-dual singularity through lasing and antilasing in thin elastic plates

Physical Review B 2021年第13期103卷 134101-134101页

作者： M. Farhat P.-Y. Chen S. Guenneau Y. Wu Computer Electrical and Mathematical Science and Engineering (CEMSE) Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900 Saudi Arabia Department of Electrical and Computer Engineering University of Illinois at Chicago Chicago Illinois 60607 USA UMI 2004 Abraham de Moivre-CNRS Imperial College London London SW7 2AZ United Kingdom

We show here that a coherent perfect absorber and laser (CPAL) enabled by parity-time (PT)-symmetry breaking may be exploited to build monochromatic amplifying devices for flexural waves. The fourth-order partial differential equation governing the propagation of flexural waves in thin-elastic piezoelectric plates leads to 4×4 transfer matrices, and captures the interplay between propagating and evanescent waves that is translated into PT-symmetry properties specific to elastic plate systems. We thus demonstrate the possibility of using CPAL for such systems and we argue the possibility of using this concept to detect extremely small-scale vibration perturbation with important outcomes in surface science (imaging of nanometer vibration) and geophysics (improving seismic sensors like velocimeters). The device can also generate finite signals using very low exciting intensities and/or alternatively can be used as a perfect absorber for flexural energy, by tailoring the left and right incident wave amplitude and phase, with evident energy harvesting applications.

关键词： Bending Elastic modulus Mechanical & acoustical properties PT-symmetry

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Comparison of two newly suggested power, refrigeration, and hydrogen production, for moving towards sustainability schemes using improved solar-powered evolutionary algorithm optimization

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Chemosphere 2023年第1期336卷 139160页

作者： Hai, Tao Abd El-Salam, Nasser M. Kh, Teeba Ismail Chaturvedi, Rishabh El-Shafai, Walid Farhang, Babak School of Computer and Information Qiannan Normal University for Nationalities Guizhou Duyun558000 China Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou Province Guizhou Duyun558000 China Universiti Teknologi MARA Selangor Shah Alam40450 Malaysia Natural Science Department Community College King Saud University Riyadh12642 Saudi Arabia Department of Computer Engineering College of Engineering and Computer Science Lebanese French University Kurdistan Region Iraq Department of Mechanical Engineering Institute of Engineering & Technology GLA University UP Mathura281001 India Department Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Department of Energy Technology Aalborg University Denmark

In the third millennium, developing countries will confront significant environmental problems such as ozone depletion, global warming, the shortage of fossil resources, and greenhouse gas emissions. This research looked at a multigenerational system that can generate clean hydrogen, fresh water, electricity, heat, and cooling. The system's components include Rankine and Brayton cycles, an Organic Rankine Cycle (ORC), flash desalination, an Alkaline electrolyzer, and a solar heliostat. The proposed process has been compared for two different start-up modes with a combustion chamber and solar heliostat to compare renewable and fossil fuel sources. This research evaluated various characteristics, including turbine pressure, system efficiency, solar radiation, and isentropic efficiency. The energy and exergy efficiency of the proposed system were obtained at around 78.93% and 47.56%, respectively. Exergy study revealed that heat exchangers and alkaline electrolyzers had the greatest exergy destruction rates, at 78.93% and 47.56%, respectively. The suggested system produces 0.04663 kg/s of hydrogen. Results indicate that at the best operational conditions, the exergetic efficiency, power, and hydrogen generation of 56%, 6000 kW, and 1.28 kg/s is reached, respectively. Also, With a 15% improvement in the Brayton cycle's isentropic efficacy, the quantity of hydrogen produced increases from 0.040 kg/s to 0.0520 kg/s. © 2023 Elsevier Ltd

关键词： Solar energy

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Cover Feature: Compartmentalized Sesquiterpenoid Biosynthesis and Functionalization in theChlamydomonas reinhardtiiPlastid (ChemBioChem 5/2025)

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ChemBioChem 2025年第5期26卷

作者： Sergio Gutiérrez Sebastian Overmans Gordon B. Wellman Kyle J. Lauersen Bioengineering Program Biological Environmental Sciences and Engineering Division (BESE) King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia

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A Machine Learning-Based Microwave Device Model for Fully Printed VO2 RF Switches

A Machine Learning-Based Microwave Device Model for Fully Pr...

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European Conference on Microwave

作者： Shuai Yang Ahmad Khusro Weiwei Li Mohammad Vaseem Mohammad Hashmi Atif Shamim CEMSE Division King Abdullah University of Science and Technology Electrical Engineering Program Thuwal Saudi Arabia Jamia Millia Islamia New Delhi India Nazarbayev University Astana Kazakhstan

ISBN: (数字)9782874870590

ISBN: (纸本)9781728170398

Fully printed vanadium dioxide (VO 2 ) based Radio Frequency (RF) switches have been recently developed for advanced frequency-reconfigurable RF electronics. A reliable and versatile model for the VO 2 switches is required for design and simulations in the modern computer-Aided Design (CAD) tools. This paper proposes a machine learning (ML) based model for VO 2 RF switches, which is much more time and resource efficient as compared to the traditional device models. The computational efficiency, accuracy and robustness of the proposed model over a frequency range of 30 GHz is demonstrated through an excellent agreement between the modelled and measured results. The comparison between the measured and modelled results demonstrate a mean-square error (MSE) of lower than 5 × 10 -4 and 5 × 10 -3 for the magnitude and phase values over the complete frequency range.

关键词： Radio frequency Microwave measurement Solid modeling Analytical models Computational modeling Tools Frequency measurement

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Spacetime modulation in floating thin elastic plates

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Physical Review B 2021年第1期104卷 014308-014308页

作者： Mohamed Farhat Sebastien Guenneau Pai-Yen Chen Ying Wu Computer Electrical and Mathematical Science and Engineering (CEMSE) Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900 Saudi Arabia UMI 2004 Abraham de Moivre-CNRS Imperial College London London SW7 2AZ United Kingdom Department of Electrical and Computer Engineering University of Illinois at Chicago Chicago Illinois 60607 USA

We consider the propagation of flexural-gravity waves in thin elastic plates floating atop nonviscous fluids, e.g., seawater, which are governed by a partial differential equation with Laplacian and tri-Laplacian terms. We investigate the effect of time modulation as well as spacetime modulation on thin floating elastic plates and show the peculiarity of the phenomena of the k-band gap and the rotated k-band gap in the context of flexural-gravity waves. This makes possible floating plates with nonreciprocal features and behaving as elastodynamic analogs of luminal electromagnetic metamaterials, with exotic applications in enhanced control of ocean waves, such as filtering devices, unidirectional acoustic propagation, and isolation effects and energy harvesting in maritime engineering.

关键词： Band gap Elastic deformation Phonons Metamaterials

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Conditional Generative Modeling for Amorphous Multi-Element Materials

arXiv

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arXiv 2025年

作者： Li, Honglin Liu, Chuhao Guo, Yongfeng Luo, Xiaoshan Chen, Yijie Liu, Guangsheng Li, Yu Wang, Ruoyu Wang, Zhenyu Wu, Jianzhuo Ma, Cheng Xie, Zhuohang Lv, Jian Ding, Yufei Zhang, Huabin Luo, Jian Zhong, Zhicheng Li, Mufan Wang, Yanchao Li, Wan-Lu Key Laboratory of Material Simulation Methods and Software Ministry of Education College of Physics Jilin University Changchun China Aiiso Yufeng Li Family Department of Chemical and Nano Engineering University of California La Jolla San DiegoCA United States Institute of Molecular Engineering Plus College of Chemistry Fuzhou University Fuzhou China College of Chemistry and Molecular Engineering Peking University Beijing China School of Physics Nankai University Tianjin China Institute of Modern Physics Fudan University Shanghai China Program in Materials Science and Engineering University of California La Jolla San DiegoCA United States School of Artificial Intelligence and Data Science University of Science and Technology of China Hefei230026 China Suzhou Institute for Advanced Research University of Science and Technology of China Suzhou215123 China International Center of Future Science Jilin University Changchun China Department of Computer Science and Engineering University of California La Jolla San DiegoCA United States Center for Renewable Energy and Storage Technologies Physical Science and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia Suzhou Lab Suzhou215123 China

Amorphous multi-element materials offer unprecedented tunability in composition and properties, yet their rational design remains challenging due to the lack of predictive structure-property relationships and the vast configurational space. Traditional modeling struggles to capture the intricate short-range order that dictates their stability and functionality. We here introduce ApolloX, a pioneering predictive framework for amorphous multi-element materials, establishing a new paradigm by integrating physics-informed generative modeling with particle swarm optimization, using chemical short-range order as an explicit constraint. By systematically navigating the disordered energy landscape, ApolloX enables the targeted design of thermodynamically stable amorphous configurations. It accurately predicts atomic-scale arrangements, including composition-driven metal clustering and amorphization trends, which are well-validated by experiments, while also guiding synthesis by leveraging sluggish diffusion to control elemental distribution and disorder. The resulting structural evolution, governed by composition, directly impacts catalytic performance, leading to improved activity and stability with increasing amorphization. This predictive-experimental synergy transforms the discovery of amorphous materials, unlocking new frontiers in catalysis, energy storage, and functional disordered systems. Copyright © 2025, The Authors. All rights reserved.

关键词： Amorphization

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High-speed colour-converting photodetector with all-inorganic CsPbBr_(3) perovskite nanocrystals for ultraviolet light communication

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Light(science & Applications) 2019年第1期8卷 306-317页

作者： Chun Hong Kang Ibrahim Dursun Guangyu Liu Lutfan Sinatra Xiaobin Sun Meiwei Kong Jun Pan Partha Maity Ee-Ning Ooi Tien Khee Ng Omar F.Mohammed Osman M.Bakr Boon S.Ooi Photonics Laboratory Division of ComputerElectricaland Mathematical Sciences and EngineeringKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia Division of Physical Science and Engineering King Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia Quantum Solutions LLC Thuwal 23955-6900Kingdom of Saudi Arabia

Optical wireless communication(OWC)using the ultra-broad spectrum of the visible-to-ultraviolet(UV)wavelength region remains a vital field of research for mitigating the saturated bandwidth of radio-frequency(RF)***,the lack of an efficient UV photodetection methodology hinders the development of UV-based *** key technological impediment is related to the low UV-photon absorption in existing silicon photodetectors,which offer low-cost and mature *** address this technology gap,we report a hybrid Sibased photodetection scheme by incorporating CsPbBr_(3) perovskite nanocrystals(NCs)with a high photoluminescence quantum yield(PLQY)and a fast photoluminescence(PL)decay time as a UV-to-visible colourconverting layer for high-speed solar-blind UV *** facile formation of drop-cast CsPbBr_(3) perovskite NCs leads to a high PLQY of up to ~73% and strong absorption in the UV *** the addition of the NC layer,a nearly threefold improvement in the responsivity and an increase of ~25% in the external quantum efficiency(EQE)of the solar-blind region compared to a commercial silicon-based photodetector were ***,timeresolved photoluminescence measurements demonstrated a decay time of 4.5 ns under a 372-nm UV excitation source,thus elucidating the potential of this layer as a fast colour-converting layer.A high data rate of up to 34 Mbps in solar-blind communication was achieved using the hybrid CsPbBr_(3)-silicon photodetection scheme in conjunction with a 278-nm UVC light-emitting diode(LED).These findings demonstrate the feasibility of an integrated high-speed photoreceiver design of a composition-tuneable perovskite-based phosphor and a low-cost silicon-based photodetector for UV communication.

关键词： perovskite ultraviolet inorganic

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FDA-MIMO radar detecting target embedded in mainlobe deceptive jamming plus Gaussian noise

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Signal Processing 2026年 238卷

作者： Bang Huang Wen-Qin Wang Ping Li Jiangwei Jian Libing Huang Wenkai Jia Mingcheng Fu School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu 611731 China Computer Electrical and Mathematical Science and Engineering (CEMSE) division in King Abdullah University of Science and Technology (KAUST) Thuwal Makkah Province Saudi Arabia

In this paper, we address the challenge of detecting targets embedded in a mainlobe deceptive jamming environment, compounded by Gaussian noise, for the frequency diverse array multiple input multiple output (FDA-MIMO) radar. Unlike conventional MIMO and/or phased-array (PA) radar systems, FDA-MIMO radar leverages additional range information, presenting a promising avenue for mitigating mainlobe deception interference. Our work begins by establishing a waveform-orthogonal FDA-MIMO radar received signal model under Gaussian noise, which encompasses thermal noise, suppression interference, and clutter after secondary range dependence compensation. Subsequently, we formulate the problem of binary hypothesis signal detection in the presence of mainlobe deception interference and training data within a detection scenario. To address this detection problem, we propose two adaptive detectors based on the one-step and two-step general likelihood ratio test (GLRT) criteria, denoted as OGLRT and TGLRT, respectively. Numerical simulation results demonstrate that our proposed detectors exhibit the constant false alarm rate (CFAR) property against the noise covariance matrix. Moreover, the performance of our proposed methods surpasses that of existing subspace detectors, with OGLRT exhibiting the best detection performance. As the frequency offsets for FDA-MIMO radar decrease, the performance of all detectors gradually deteriorates until they no longer retain target detection capabilities. This observation implies that, in the mainlobe deception interference environment considered in this paper, MIMO radar loses its ability to detect targets.

关键词： Adaptive detection Frequency diverse array multiple input multiple output (FDA-MIMO) Mainlobe interference General likelihood ratio test (GLRT) One-step Two-step

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Resistive neural hardware accelerators

arXiv

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arXiv 2021年

作者： Smagulova, Kamilya Fouda, Mohammed E. Kurdahi, Fadi Salama, Khaled Eltawil, Ahmed Division of CEMSE King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia Electrical Engineering and Computer Science Dept. University of California–Irvine IrvineCA92697 United States

Deep Neural Networks (DNNs), as a subset of Machine Learning (ML) techniques, entail that real-world data can be learned and that decisions can be made in real time. However, their wide adoption is hindered by a number of software and hardware limitations. The existing general-purpose hardware platforms used to accelerate DNNs are facing new challenges associated with the growing amount of data and are exponentially increasing the complexity of computations. An emerging non-volatile memory (NVM) devices and processing-in-memory (PIM) paradigm is creating a new hardware architecture generation with increased computing and storage capabilities. In particular, the shift towards ReRAM-based in-memory computing has great potential in the implementation of area and power efficient inference and in training large-scale neural network architectures. These can accelerate the process of the IoT-enabled AI technologies entering our daily life. In this survey, we review the state-of-the-art ReRAM-based DNN many-core accelerators, and their superiority compared to CMOS counterparts was shown. The review covers different aspects of hardware and software realization of DNN accelerators, their present limitations, and future prospectives. In particular, comparison of the accelerators shows the need for the introduction of new performance metrics and benchmarking standards. In addition, the major concerns regarding the efficient design of accelerators include a lack of accuracy in simulation tools for software and hardware co-design. Copyright © 2021, The Authors. All rights reserved.

关键词： Deep neural networks

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Negative photo conductivity triggered with visible light in wide bandgap oxide-based optoelectronic crossbar memristive array for photograph sensing and neuromorphic computing applications

npj Unconventional Computing

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npj Unconventional Computing 2024年第1期1卷 1-9页

作者： Dayanand Kumar Hanrui Li Manoj Kumar Rajbhar Abdul Momin Syed Nazek El-Atab Amit Singh Hoonkyung Lee Smart Advanced Memory Devices and Applications (SAMA) Laboratory Electrical and Computer Engineering Program Computer Electrical Mathematical Science and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia Department of Physics and Astronomy University of Manchester Manchester UK Department of Physics Konkuk University Seoul Republic of Korea

Photoresponsivity studies of wide-bandgap oxide-based devices have emerged as a vibrant and popular research area. Researchers have explored various material systems in their quest to develop devices capable of responding to illumination. In this study, we engineered a mature wide-bandgap oxide-based bilayer heterostructure synaptic memristor to emulate the human brain for applications in neuromorphic computing and photograph sensing. The device exhibits advanced electric and electrophotonic synaptic functions, such as long-term potentiation (LTP), long-term depression (LTD), and paired-pulse facilitation (PPF), by applying successive electric and photonic pulses. Moreover, the device exhibits exceptional electrical SET and photonic RESET endurance, maintaining its stability for a minimum of 1200 cycles without any degradation. Density functional theory calculations of the band structures provide insights into the conduction mechanism of the device. Based on this memristor array, we developed an autoencoder and convolutional neural network for noise reduction and image recognition tasks, which achieves a peak signal-to-noise ratio of 562 and high accuracy of 84.23%, while consuming lower energy by four orders of magnitude compared with the Tesla P40 GPU. This groundbreaking research not only opens doors for the integration of our device into image processing but also represents a significant advancement in the realm of in-memory computing and photograph-sensing features in a single cell.

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