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Polarization‑entangled photon‑pair source with van der Waals 3R‑WS_(2) crystal

eLight 2024年第1期4卷 99-106页

作者： Jiangang Feng Yun‑Kun Wu Ruihuan Duan Jun Wang Weijin Chen Jiazhang Qin Zheng Liu Guang‑Can Guo Xi‑Feng Ren Cheng‑Wei Qiu Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore CAS Key Laboratory of Quantum Information University of Science and Technology of ChinaHefei 230026China CAS Center for Excellence in Quantum Information and Quantum Physics University of Science and Technology of ChinaHefei 230026China Hefei National Laboratory University of Science and Technology of ChinaHefei 230088China School of Materials Science and Engineering Nanyang Technological UniversitySingapore 639798Singapore Department of Optical Science and Engineering and Shanghai Frontiers Science Research Base of Intelligent Optoelectronics and PerceptionFudan UniversityShanghai 200433China

Ultracompact entangled photon sources are pivotal to miniaturized quantum photonic *** der Waals(vdW)nonlinear crystals promise efficient photon-pair generation and on-chip monolithic integration with nanophotonic ***,it remains challenging to generate maximally entangled Bell states of photon pairs with high purity,generation rate,and fidelity required for practical ***,we realize a polarization-entangled photon-pair source based on spontaneous parametric down conversion in an ultrathin rhombohedral tungsten disulfide(3R-WS2)*** vdW entangled photonic source exhibits a high photon-pair purity with a coincidenceto-accidental ratio of above 800,a generation rate of 31 Hz,and two maximally polarization-entangled Bell states with fidelities exceeding 0.93 and entanglement degree over *** results stem from scalable optical nonlinearity,enhanced second-order susceptibility by electronic transitions,and a well-defined symmetry-enabled selection rule inherent in *** polarization entangled photon source can be integrated with photonic structures for generating more complex entangled states,thus paving an avenue for advanced quantum photonic systems toward computation and metrology.

关键词： purity maximal Polarization

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High-fidelity model to predict heat transfer enhancement for liquid film boiling on uniform micro-structured wicking surfaces

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National science Review 2024年第6期11卷 93-95页

作者： Vishwanath Ganesan Mohammad Jalal Inanlu Nenad Miljkovic Department of Mechanical Science and Engineering University of Illinois Urbana-Champaign Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign Materials Research Laboratory University of Illinois Urbana-Champaign International Institute for Carbon Neutral Energy Research (WPI-I2CNER) Kyushu University Institute for Sustainability Energy and Environment (iSEE)University of Illinois Urbana-Champaign

The field of thermal management in highpower electronic devices is a critical area of study, focusing on the efficient dissipation of heat to prevent device overheating and failure [1]. A key aspect of this field is understanding the dynamics of thin liquid film boiling, both on uniform and non-uniform micro-structured wicking surfaces, which can significantly enhance the heat transfer effectiveness[2].

关键词： structured predict micro liquid model boiling enhancement film heat high-fidelity

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A Comprehensive Technique Based on Machine Learning for Device and Circuit Modeling of Gate-All-Around Nanosheet Transistors

IEEE Open Journal of Nanotechnology

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IEEE Open Journal of Nanotechnology 2023年 4卷 181-194页

作者： Butola, Rajat Li, Yiming Kola, Sekhar Reddy National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Institute of Communications Engineering the Institute of Biomedical Engineering the Department of Electronics and Electrical Engineering the Institute of Pioneer Semiconductor Innovation and the Institute of Artificial Intelligence Innovation Hsinchu300093 Taiwan

Machine learning (ML) is poised to play an important part in advancing the predicting capability in semiconductor device compact modeling domain. One major advantage of ML-based compact modeling is its ability to capture complex relationships and patterns in large datasets. Therefore, in this paper a novel design scheme based on dynamically adaptive neural network (DANN) is proposed to develop fast and accurate compact model (CM). This framework constitutes a powerful yet computationally efficient methodology and exhibits emergent dynamic behaviors. This paper demonstrates that the compact model based on ML can be designed to replicate the performance of conventional compact model for nanodevices. For this work, gate-all-around (GAA) nanosheet (NS) device characteristics are comprehensively analyzed for process variability sources using the proposed model. The device geometry parameters such as channel length, nanosheet width and nanosheet thickness are fed as input features to the DANN model. The adaptive neural network learns dynamically by updating weights of the model in accordance with the input features and achieves accurate neural weight convergence. The proposed model predicted the electrical characteristics of NS devices with less than 1% error rate. The model is also implemented and validated for the simulations of digital circuit designs such as inverter, and logic gates. ©;2023 The Authors.

关键词： Circuit simulation

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Femtosecond Laser–Inscribed Fiber Bragg Grating Sensors: Enabling Distributed High-Temperature Measurements and Strain Monitoring in Steelmaking and Foundry Applications

Femtosecond Laser–Inscribed Fiber Bragg Grating Sensors: En...

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AISTech 2024 Iron and Steel Technology Conference

作者： Inalegwu, Ogbole C. Mekala, Yeshwanth Reddy Saha, Rony Kumer Mumtaz, Farhan Alla, Dinesh Reddy Neelakandan, Deva Prasad Smith, Jeffrey D. O’Malley, Ronald J. Gerald, Rex E. Huang, Jie Department of Electrical and Computer Engineering Missouri University of Science and Technology RollaMO65409 United States Department of Materials Science and Engineering Missouri University of Science and Technology RollaMO65409 United States Missouri University of Science and Technology RollaMO65409 United States

ISBN: (纸本)9780930767259

This study demonstrates the use of fiber Bragg grating (FBG) sensors for distributed temperature and strain monitoring in steelmaking and foundry applications. Integrated into inexpensive optical fibers, FBGs offer accurate and real-time remote sensing, detecting shifts in wavelength due to temperature (up to 1,800 °C), strain, or structural wear and tear. Furthermore, the intrinsic features of FBG sensors: compact size, immunity to electromagnetic interference and corrosion, robustness to vibration, ease of integration into existing composite structures, and non-intrusive measurement capacity in harsh environments make them ideal for steelmaking. FBGs optimize production, ensure quality, and enhance safety within the steel industry. © 2024 by the Association for Iron & Steel Technology.

关键词： Fiber Bragg gratings

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A Graph Neural Network Multi-Task Learning-Based Approach for Detection and Localization of Cyberattacks in Smart Grids 48

A Graph Neural Network Multi-Task Learning-Based Approach fo...

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Takiddin, Abdulrahman Atat, Rachad Ismail, Muhammad Davis, Katherine Serpedin, Erchin Texas A and M University Department of Electrical and Computer Engineering College StationTX United States Texas A and M University at Qatar Electrical and Computer Engineering Program Doha Qatar Tennessee Technological University Department of Computer Science CookevilleTN United States

ISBN: (纸本)9781728163277

False data injection attacks (FDIAs) on smart power grids' measurement data present a threat to system stability. When malicious entities launch cyberattacks to manipulate the measurement data, different grid components will be affected, which leads to failures. For effective attack mitigation, two tasks are required: determining the status of the system (normal operation/under attack) and localizing the attacked bus/power substation. Existing mitigation techniques carry out these tasks separately and offer limited detection performance. In this paper, we propose a multi-Task learning-based approach that performs both tasks simultaneously using a graph neural network (GNN) with stacked convolutional Chebyshev graph layers. Our results show that the proposed model presents superior system status identification and attack localization abilities with detection rates of 98.5-100% and 99-100%, respectively, presenting improvements of 5-30% compared to benchmarks. © 2023 IEEE.

关键词： Smart power grids

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Revolutionizing Neurological Diagnostics: Integrating 6G Technology with Deep Learning for Enhanced Detection of Multiple Sclerosis and Myelitis

Revolutionizing Neurological Diagnostics: Integrating 6G Tec...

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2024 International Telecommunications Conference, ITC-Egypt 2024

作者： Noureldeen, Rana M. Elshshtawy, Rahma A. Elgohary, Omnia A. Wahba, Fatma Alzahraa A. Attia, Marco K. Abo Elazm, Zeinab B. Khattap, Mohamed G. Galal Eldeen Mohamed Ali Hassan, Hend Mostafa, Mariam Ibrahim, Nayra Ramadan, Reem Refaat, Yomna Khaled, Mennatallah Maher, Ali Abd Elaziz, Mohamed Gamal Abdellatif Ibrahim, Ahmed Faculty of Applied Health Sciences Galala University Suez435611 Egypt Faculty of Computer Science and Engineering Galala University Suez435611 Egypt Artificial Intelligence Science Program Faculty of Computer Science and Engineering Galala University Suez435611 Egypt Air Defense College Department of Electronics and Electrical Communications Engineering Alexandria Egypt

ISBN: (纸本)9798350351408

This paper proposes an alternative detection frame-work for multiple sclerosis (MS) and idiopathic acute transverse myelitis (ATM) within the 6G-enabled Internet of Medical Things (IoMT) environment. The developed framework relies on the implementation of a deep learning technique known as Dense Convolutional Networks (DenseNets) in the 6G-enabled IoMT to enhance prediction performance. To validate the performance of DenseNets, we compared it with other deep learning techniques, including Convolutional Neural Networks (CNN) and MobileNet, using real-world datasets. The experimental results show the high performance of DenseNets in predicting MS and ATM compared to other methods, achieving an accuracy of nearly 90 %. © 2024 IEEE.

关键词： Convolutional neural networks

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Automated classification of big X-ray diffraction data using deep learning models

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npj Computational materials 2023年第1期9卷 169-180页

作者： Jerardo E.Salgado Samuel Lerman Zhaotong Du Chenliang Xu Niaz Abdolrahim Materials Science program University of RochesterRochesterNew York 14627USA Department of Computer Science University of RochesterRochesterNew York 14627USA Department of Mechanical Engineering University of RochesterRochesterNew York 14627USA Laboratory for Laser Energetics University of RochesterRochesterNew York 14627USA

In current in situ X-ray diffraction(XRD)techniques,data generation surpasses human analytical capabilities,potentially leading to the loss of *** techniques require human intervention,and lack the performance and adaptability required for material *** the critical need for high-throughput automated XRD pattern analysis,we present a generalized deep learning model to classify a diverse set of materials’crystal systems and space *** our approach,we generate training data with a holistic representation of patterns that emerge from varying experimental conditions and crystal *** also employ an expedited learning technique to refine our model’s expertise to experimental *** addition,we optimize model architecture to elicit classification based on Bragg’s Law and use evaluation data to interpret our model’s *** evaluate our models using experimental data,materials unseen in training,and altered cubic crystals,where we observe state-of-the-art performance and even greater advances in space group classification.

关键词： Automate classify cubic

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Voltage-Controlled Synthesis of Higher Harmonics in Hybrid Josephson Junction Circuits

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Physical Review Letters 2024年第18期133卷 186303页

作者： L. Banszerus W. Marshall C. W. Andersson T. Lindemann M. J. Manfra C. M. Marcus S. Vaitiekėnas Center for Quantum Devices Niels Bohr Institute Department of Physics Department of Physics and Astronomy Birck Nanotechnology Center School of Electrical and Computer Engineering School of Materials Engineering Materials Science and Engineering

We report measurements of the current-phase relation of two voltage-controlled semiconductor-superconductor hybrid Josephson junctions (JJs) in series. The two hybrid junctions behave similar to a single-mode JJ with effective transparency determined by the ratio of Josephson coupling strengths of the two junctions. Gate-voltage control of Josephson coupling (measured from switching currents) allows tuning of the harmonic content from sinusoidal, for asymmetric tuning, to highly nonsinusoidal, for symmetric tuning. The experimentally observed tunable harmonic content agrees with a model based on two conventional (sinusoidal) JJs in series.

关键词： Critical current Josephson effect Josephson junctions Semiconductors Superconducting devices Superconductors Resistivity measurements

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Multiregion Light Control in Diffusive Media via Wavefront Shaping

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Physical Review Letters 2024年第14期133卷 146901页

作者： Liam Shaughnessy Rohin E. McIntosh Arthur Goetschy Chia Wei Hsu Nicholas Bender Hasan Yılmaz Alexey Yamilov Hui Cao Department of Applied Physics Ming Hsieh Department of Electrical and Computer Engineering School of Applied and Engineering Physics Institute of Materials Science and Nanotechnology Physics Department

Wavefront shaping allows focusing light through or inside strongly scattering media, but the background intensity also increases which reduces the target’s contrast. By combining transmission or deposition matrices for different regions, we construct joint operators to achieve spatially resolved control of light in diffusive systems. The eigenmode of a contrast operator can maximize the power contrast between a target and its surrounding. A difference operator enhances the power delivery to a target while avoiding the background increase. This work opens the door to coherent control of nonlocal effects in wave transport for practical applications.

关键词： Optics & lasers Random & disordered media Coherent control

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Harnessing the power of functionalized biochar:progress,challenges,and future perspectives in energy,water treatment,and environmental sustainability

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Biochar 2024年第1期6卷 407-486页

作者： Muhammad Zubair Yameen Salman Raza Naqvi Dagmar Juchelková Muhammad Nouman Aslam Khan Laboratory of Alternative Fuels and Sustainability School of Chemical and Materials Engineering(SCME)National University of Sciences and Technology(NUST)Sector H-12Islamabad 44000Pakistan. Department of Electronics Faculty of Electrical Engineering and Computer ScienceVŠB-Technical University of Ostrava17.Listopadu 2172/1570800 OstravaPorubaCzech Republic. Department of Engineering and Chemical Sciences Karlstad UniversityKarlstadSweden.

The swift advancement of sustainable energy technologies,coupled with the urgent need to address environmental challenges,has generated considerable interest in the multifaceted applications of biochar materials to promote energy,water,and environmental *** comprehensive review examines recent advancements in the production and applications of functionalized biochar materials,emphasizing their pivotal roles in energy conversion and storage,wastewater treatment,CO_(2)reduction,soil amelioration,and the promotion of carbon neutrality within a circular economy *** functionalization of biochar materials involves surface chemistry and porosity modifications,achieved through techniques like templating,chemical activation,metal impregnation,or heteroatom *** modifications substantially enhance the catalytic activity,energy storage capacity,and cycling stability of biochar materials,making them particularly effective in diverse energy applications such as water splitting,fuel cells,and ***,functionalized biochar materials demonstrate remarkable efficacy as catalysts and adsorbents in wastewater treatment,proficiently removing pollutants like heavy metals,organic contaminants,and nutrients,thereby facilitating resource recovery from *** review also underscores the potential of functionalized biochar materials in CO_(2)capture and conversion,exploring innovative strategies to augment their CO_(2)adsorption capacity and state-of-the-art catalytic processes for transforming captured CO_(2)into valuable fuels and *** summary,this review offers valuable insights into the recent advancements in biochar research,underscoring its substantial commercial potential as a versatile material contributing to a cleaner and more sustainable future.

关键词： Engineered biochar Sustainable energy technologies Wastewater treatment Carbon reduction Circular economy

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