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Deep learning inter-atomic potential for thermal and phonon behaviour of silicon carbide with quantum accuracy

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arXiv 2021年

作者： Fu, Baoqin Sun, Yandong Zhang, Linfeng Wang, Han Xu, Ben Key Laboratory of Radiation Physics and Technology of the Ministry of Education Institute of Nuclear Science and Technology Sichuan University Chengdu610064 China Graduate School China Academy of Engineering Physics Beijing100193 China Program in Applied and Computational Mathematics Princeton University PrincetonNJ United States Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics Beijing100088 China

Silicon carbide (SiC) is an essential material for next generation semiconductors and components for nuclear plants. It’s applications are strongly dependent on its thermal conductivity, which is highly sensitive to microstructures. Molecular dynamics (MD) simulation is the most used methods to address thermal transportation mechanisms in devices or microstructures of nano-meters. However, the implementation of MD is limited in SiC because of lacking accurate inter-atomic potentials. In this work, using the Deep Potential (DP) methodology, we developed two inter-atomic potentials (DP-*Corresponding author. IAPs) for SiC based on two adaptively generated datasets within the density functional approximations at the local density and the generalized gradient levels. These two DP-IAPs manifest their speed with quantum accuracy in lattice dynamics simulations as well as scattering rate analysis of phonon transportation. Combining with molecular dynamics simulations, the thermal transport and mechanical properties were systematically investigated. The presented methodology and the inter-atomic potentials pave the way for a systematic approach to model heat transport in SiC related devices using multiscale modelling. Copyright © 2021, The Authors. All rights reserved.

关键词： Silicon carbide

Meta-control of social learning strategies

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arXiv 2021年

作者： Yaman, Anil Bredeche, Nicolas Çaylak, Onur Leibo, Joel Z. Lee, Sang Wan Computer Science Department Vrije Universiteit Amsterdam Amsterdam Netherlands Institut des Systèmes Intelligents et de Robotique Sorbonne Université CNRS Paris France Department of Mathematics and Computer Science Eindhoven University of Technology Eindhoven Netherlands DeepMind London United Kingdom Department of Bio and Brain Engineering Korea Advanced Institute of Science and Technology Daejeon Korea Republic of Center for Neuroscience-Inspired AI Korea Advanced Institute of Science and Technology Daejeon Korea Republic of Program of Brain and Cognitive Engineering Korea Advanced Institute of Science and Technology Daejeon Korea Republic of KI for Health Science and Technology Korea Advanced Institute of Science and Technology Daejeon Korea Republic of KI for Artificial Intelligence Korea Advanced Institute of Science and Technology Daejeon Korea Republic of Computer Science Department Vrije Universiteit Amsterdam Amsterdam Netherlands

Social learning, copying other's behavior without actual experience, offers a cost-effective means of knowledge acquisition. However, it raises the fundamental question of which individuals have reliable information: successful individuals versus the majority. The former and the latter are known respectively as success-based and conformist social learning strategies. We show here that while the success-based strategy fully exploits the benign environment of low uncertainly, it fails in uncertain environments. On the other hand, the conformist strategy can effectively mitigate this adverse effect. Based on these findings, we hypothesized that meta-control of individual and social learning strategies provides effective and sample-efficient learning in volatile and uncertain environments. Simulations on a set of environments with various levels of volatility and uncertainty confirmed our hypothesis. The results imply that meta-control of social learning affords agents the leverage to resolve environmental uncertainty with minimal exploration cost, by exploiting others' learning as an external knowledge base. Copyright © 2021, The Authors. All rights reserved.

关键词： Learning systems

Trends in bimetallic nanomaterials and methods for fourth-generation glucose sensors

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TrAC - Trends in Analytical Chemistry 2023年 162卷

作者： Naikoo, Gowhar A. Arshad, Fareeha Hassan, Israr U. Omar, Fatima Ba Tambuwala, Murtaza M. Mustaqeem, Mujahid Saleh, Tawfik A. Department of Mathematics and Sciences College of Arts and Applied Sciences Dhofar University SalalahPC 211 Oman College of Engineering Dhofar University SalalahPC 211 Oman Lincoln Medical School University of Lincoln Brayford Pool Campus LincolnLN6 7TS United Kingdom Department of Chemistry National Taiwan University No. 1 Section 4 Roosevelt Road Taipei10617 Taiwan Nano-Science and Technology Program Taiwan International Graduate Program Institute of Physic Academia Sinica Taipei106 Taiwan Department of Chemistry King Fahd University of Petroleum & Minerals Dhahran31261 Saudi Arabia

Diabetes mellitus is one of the most rapidly rising chronic diseases around the globe. To combat these rising numbers, active research has been done in recent years to enhance the sensitivity, selectivity, and specificity of glucose biosensors. Despite the easy availability of these enzymatic glucose sensors, these have demonstrated limitations like low stability, short shelf-life, and being easily altered by physical and chemical environmental factors. To overcome these limitations, non-enzymatic sensors, also called fourth-generation glucose sensors, have been developed. These sensors use nanomaterials and do not employ any enzymes therefore exhibit better shelf life, improved sensitivity, and allow for quick detection of glucose without needing additional steps. In recent years, bimetallic nanocomposite-based fourth-generation glucose sensors have gained widespread attention from the scientific community. Owing to the synergistic effect of two distinct metal nanomaterials, these sensors show enhanced reproducibility and excellent stability as compared to monometallic nanomaterials. In this review, we aim to represent a comprehensive overview of the recent developments in the development of bimetallic nanocomposite-based glucose sensors for rapid and accurate glucose detection. After a brief introduction, we discussed the various bimetallic nanomaterials developed in recent years, followed by a discussion on the mechanism of action of such sensors. We then briefly discussed the industrial challenges of developing such sensors and discussed the advantages and disadvantages of bimetallic nanomaterial-based sensors. We finally concluded the review by highlighting the future perspectives of this new and upcoming field. © 2023 Elsevier B.V.

关键词： Glucose sensors

Coconut waste to green nanomaterial: Large scale synthesis of N-doped graphene nano sheets

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Nano-Structures and Nano-Objects 2023年 36卷

作者： Siburian, Rikson Tang, Liang Wei Alias, Yatimah Tok, Alfred Iing Yoong Goei, Ronn Simanjuntak, Crystina Tarigan, Kerista Paiman, Suriati Goh, Boon Tong Anshori, Isa Kurniawan, Cepi Postgraduate Program Department of Chemistry Faculty of Mathematics and Natural Sciences Universitas Sumatera Utara Medan 20155 Indonesia Department of Chemistry Faculty of Mathematics and Natural Sciences Universitas Sumatera Utara Medan 20155 Indonesia Carbon and Frankincense Research Center Universitas Sumatera Utara Medan 20155 Indonesia Department of Chemistry Faculty of Science Universiti Malaya Kuala Lumpur 50603 Malaysia University Malaya Centre for Ionic Liquids (UMCiL) Universiti Malaya Kuala Lumpur 50603 Malaysia School of Materials Science and Engineering Nanyang Technological University 50 Nanyang Avenue Singapore 639798 Singapore Department of Physics Faculty of Mathematics and Natural Sciences Universitas Sumatera Utara Medan 20155 Indonesia Physics Department Faculty of Science Universiti Putra Malaysia Selangor (Serdang) Seri Kembangan 43400 Malaysia Low Dimensional Materials Research Centre Department of Physics Faculty of Science University of Malaya Kuala Lumpur 50603 Malaysia Biomedical Engineering Department School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung 40132 Indonesia Research Center of Nanoscience and Nanotechnology Bandung Institute of Technology Bandung 40132 Indonesia Chemistry Department Faculty of Mathematics and Natural Sciences Universitas Negeri Semarang Semarang 50229 Indonesia Functional Material Research Center Universitas Negeri Semarang Semarang 50229 Indonesia

In this paper, a breakthrough was achieved in large-scale production of N-doped Graphene Nano Sheets (N-GNS) using coconut fruits. The main objectives were to produce N-GNS on a large scale and assess its electrical conductivity. The process involved two key steps: first, producing GNS from coconut fruits through pyrolysis, and then generating N-GNS by doping with nitrogen using ammonia solution at room temperature. Various analytical techniques were used to characterize the produced N-GNS, including X-ray Diffraction (XRD), Scanning Electron Microscopy with Energy Dispersive Spectroscopy (SEM-EDS), Transmission Electron Microscopy (TEM), X-ray Photoelectron Spectroscopy (XPS), Raman spectroscopy, and electrochemical cyclic voltammetry and electrochemical impedance spectroscopy. The XRD data indicated that the C (002) peak of N-GNS shifted to a higher 2θ value (2θ = 24.72°) compared to GNS (2θ = 23.86°), suggesting an incorporation of nitrogen into carbon structure in N-GNS. This was further supported by XPS data, which identified N-pyridine (BE = 402.0 eV) and C-N (BE = 286.8 eV) in N-GNS. TEM images showed that N-GNS had a flat surface, and the distance between graphene layers slightly expanded (0.36 nm) compared to graphene layers (0.34 nm). SEM images and EDX data validated the morphology, resembling honeycomb lattices, with a significant content of N atoms. Raman data successfully identified the D-band and G-band in N-GNS, further validating its production. Most importantly, N-GNS exhibited electrical conductivity, making it a promising candidate for conductive and supporting materials in various applications. The significance of this research extends beyond N-GNS production, opening up new avenues for the sustainable synthesis of valuable nanomaterials from coconut fruit waste, contributing to both graphene technology and environmental conservation. © 2023 Elsevier B.V.

关键词： C-sp2 Electrical conductivity Graphene nano sheets N-graphene nano sheets N-pyridine XPS

Integrability of Goldilocks quantum cellular automata

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arXiv 2024年

作者： Hillberry, Logan E. Piroli, Lorenzo Vernier, Eric Halpern, Nicole Yunger Prosen, Tomaž Carr, Lincoln D. Department of Physics The University of Texas at Austin AustinTX78712 United States Dipartimento di Fisica e Astronomia Università di Bologna INFN Sezione di Bologna via Irnerio 46 BolognaI-40126 Italy Laboratoire de Probabilités Statistique et Modélisation CNRS Université Paris Cité Sorbonne Université Paris France Joint Center for Quantum Information and Computer Science NIST University of Maryland College ParkMD20742 United States Institute for Physical Science and Technology University of Maryland College ParkMD20742 United States Faculty of Mathematics and Physics University of Ljubljana Jadranska 19 LjubljanaSI-1000 Slovenia Institute of Mathematics Physics and Mechanics Jadranska 19 LjubljanaSI-1000 Slovenia Quantum Engineering Program Colorado School of Mines GoldenCO80401 United States Department of Physics Colorado School of Mines GoldenCO80401 United States Department of Applied Mathematics and Statistics Colorado School of Mines GoldenCO80401 United States

Goldilocks quantum cellular automata (QCA) have been simulated on quantum hardware and produce emergent small-world correlation networks. In Goldilocks QCA, a single-qubit unitary is applied to each qubit in a one-dimensional chain subject to a balance constraint: a qubit is updated if its neighbors are in opposite basis states. Here, we prove that a subclass of Goldilocks QCA—including the one implemented experimentally—map onto free fermions and therefore can be classically simulated efficiently. We support this claim with two independent proofs, one involving a Jordan–Wigner transformation and one mapping the integrable six-vertex model to QCA. We compute local conserved quantities of these QCA and predict experimentally measurable expectation values. These calculations can be applied to test large digital quantum computers against known solutions. In contrast, typical Goldilocks QCA have equilibration properties and quasienergy-level statistics that suggest nonintegrability. Still, the latter QCA conserve one quantity useful for error mitigation. Our work provides a parametric quantum circuit with tunable integrability properties with which to test quantum hardware. © 2024, CC BY.

关键词： Qubits

Thermo-economic and environmental evaluation of thin film evaporation using novel metal-organic frameworks to enhance solar desalination performance

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Process Safety and Environmental Protection 2025年 199卷

作者： Sharshir, Swellam W. Abdo, Mohamed R. Yusuf, Kareem El-Naggar, Ahmed A. Joseph, Abanob Ismail, M. Elsaid, Ashraf Mimi El-Samadony, M.O.A. Abdelfatah, Mahmoud El-Shaer, Abdelhamid Yuan, Zhanhui College of Materials Engineering Fujian Agriculture and Forestry University Fuzhou350002 China Mechanical Engineering Department Faculty of Engineering Kafrelsheikh University Kafrelsheikh33516 Egypt Department of Physics and Engineering Mathematics Faculty of Engineering University of Kafrelsheikh Kafrelsheikh Egypt Department of Chemistry College of Science King Saud University Riyadh11451 Saudi Arabia Physics Department Faculty of Science Kafrelsheikh University Kafrelsheikh33516 Egypt Nano Science and Technology Program Faculty of Science Kafrelsheikh University Kafrelsheikh33516 Egypt Department of Mechanical Engineering Faculty of Engineering Suez University SuezP.O. Box 43221 Egypt Refrigeration and Air Conditioning Technology Department Faculty of Technology and Education Helwan University CairoP.O. Box 11282 Egypt Mechanical Power Engineering Department Faculty of Engineering Tanta University Tanta City Egypt

The growing shortage of freshwater resources has spurred the development of innovative and sustainable desalination technologies. This study presents a thermo-economic analysis of an innovative hemispherical solar still (HSS) enhanced with a novel Metal-Organic Framework (MOF), specifically Iron-Aluminum Benzene Tricarboxylate. The MOF was characterized through structural, morphological, and optical investigations and integrated into the HSS using two enhancement methods: (I) as a nanofluid (MOF-NF) at a 1 wt% concentration in the feedwater, and (II) as a heat localization material (MOF-HL) by dispersing it on a black cotton wick that spans the basin surface. An external condenser (EC) was added to further enhance condensation in a subsequent configuration. Three identical HSS systems were used for comparative performance evaluation: a baseline unit (CHSS) and two modified systems, one with a condenser and one without. The results indicated that both MOF-based approaches significantly improved the thermal performance and freshwater yield of the HSS. Notably, the MOF-HL configuration outperformed the MOF-NF configuration across all performance metrics. The configuration designated as MOF-HL-EC achieved the highest rate of freshwater production, with a 96.16 % increase in distillate productivity compared to the CHSS. Additionally, this configuration exhibited exergy and energy efficiencies of 3.18 % and 61.1 %, respectively—improvements of 80.85 % and 95.72 % over the traditional system. Economically, the MOF-HL-EC configuration reduced the production cost of distilled water to 0.0115$ per liter, marking a reduction of 25.29 %. © 2025 The Institution of Chemical Engineers

关键词： Iron analysis

Automating the Practice of science – Opportunities, Challenges, and Implications

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arXiv 2024年

作者： Musslick, Sebastian Bartlett, Laura K. Chandramouli, Suyog H. Dubova, Marina Gobet, Fernand Griffiths, Thomas L. Hullman, Jessica King, Ross D. Nathan Kutz, J. Lucas, Christopher G. Mahesh, Suhas Pestilli, Franco Sloman, Sabina J. Holmes, William R. Institute of Cognitive Science Osnabrück University Osnabrück49090 Germany Department of Cognitive Linguistic & Psychological Sciences Brown University ProvidenceRI02912 United States Centre for Philosophy of Natural and Social Science London School of Economics Lakatos Building Houghton Street LondonWC2A 2AE United Kingdom AaltoFI-00076 Finland Department of Computing Science University of Alberta 8900 114 St NW EdmontonABT6G 2S4 Canada Cognitive Science Program Indiana University 1101 E 10th St BloomingtonIN47405 United States School of Psychology University of Roehampton LondonSW15 4JD United Kingdom Departments of Psychology and Computer Science Princeton University PrincetonNJ United States Department of Computer Science Northwestern University IL United States Department of Chemical Engineering and Biotechnology University of Cambridge CambridgeCB3 0AS United Kingdom Department of Computer Science and Engineering Chalmers University of Technology Gothenburg412 96 Sweden Department of Applied Mathematics and Electrical and Computer Engineering University of Washington Seattle98195 United States School of Informatics University of Edinburgh 10 Crichton St. EH8 9AB United Kingdom Department of Materials Science and Engineering University of Toronto Canada Department of Psychology Department of Neuroscience The University of Texas AustinTX United States Department of Computer Science University of Manchester M13 9PL United Kingdom

Automation transformed various aspects of our human civilization, revolutionizing industries and streamlining processes. In the domain of scientific inquiry, automated approaches emerged as powerful tools, holding promise for accelerating discovery, enhancing reproducibility, and overcoming the traditional impediments to scientific progress. This article evaluates the scope of automation within scientific practice and assesses recent approaches. Furthermore, it discusses different perspectives to the following questions: Where do the greatest opportunities lie for automation in scientific practice?;What are the current bottlenecks of automating scientific practice?;and What are significant ethical and practical consequences of automating scientific practice? By discussing the motivations behind automated science, analyzing the hurdles encountered, and examining its implications, this article invites researchers, policymakers, and stakeholders to navigate the rapidly evolving frontier of automated scientific practice. © 2024, CC BY.

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Enhancing healthcare AI stability with edge computing and machine learning for extubation prediction

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Scientific Reports 2025年第1期15卷 1-11页

作者： Huang, Kuo-Yang Hsu, Ying-Lin Chung, Che-Liang Chen, Huang-Chi Horng, Ming-Hwarng Lin, Ching-Hsiung Liu, Ching-Sen Xu, Jia-Lang Division of Chest Medicine Department of Internal Medicine Changhua Christian Hospital Changhua Taiwan Institute of Genomics and Bioinformatics National Chung Hsing University Taichung Taiwan Ph.D. Program in Medical Biotechnology National Chung Hsing University Taichung Taiwan Institute of Statistics National Chung Hsing University Taichung Taiwan Division of Chest Medicine Department of Internal Medicine Yuanlin Christian Hospital Changhua Taiwan Department of Applied Mathematics National Chung Hsing University Taichung Taiwan Department of Computer Science and Information Engineering Chaoyang University of Technology Taichung Taiwan

The advancement of the Internet of Medical Things (IoMT) has revolutionized data acquisition and processing in critical care settings. Given the pivotal role of ventilators, accurately predicting extubation outcomes is essential to optimize patient care. This study presents an edge computing-based framework that incorporates machine learning algorithms to predict ventilator extubation success using real-time data collected directly from ventilators. The system was deployed on edge devices to enable on-site inference with minimal latency. Among the evaluated models, Random Forest and XGBoost, the latter demonstrated superior predictive performance under both holdout and tenfold cross-validation schemes. Notably, the edge-based architecture reduced server data transmissions by 83.33%, while improving system stability, resilience, and sustainability. This paper details the model evaluation and demonstrates the feasibility and efficiency of edge intelligence in ventilator weaning decision support. © The Author(s) 2025.

关键词： Clinical decision support system Edge-computing Extubation Internet of medical things Machine learning

A growth model for water distribution networks with loops

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arXiv 2021年

作者： Sugishita, Kashin Abdel-Mottaleb, Noha Zhang, Qiong Masuda, Naoki Department of Mathematics State University of New York at Buffalo BuffaloNY14260-2900 United States Department of Transdisciplinary Science and Engineering Tokyo Institute of Technology Tokyo152-8550 Japan Department of Civil and Environmental Engineering University of South Florida TampaFL33620 United States Computational and Data-Enabled Science and Engineering Program State University of New York at Buffalo BuffaloNY14260-5030 United States Faculty of Science and Engineering Waseda University Tokyo169-8555 Japan

Water distribution networks (WDNs) expand their service areas over time. These growth dynamics are poorly understood. One facet of WDNs is that they have loops in general, and closing loops may be a functionally important process for enhancing their robustness and efficiency. We propose a growth model for WDNs which generates networks with loops and is applicable to networks with multiple water sources. We apply the proposed model to four empirical WDNs to show that it produces networks whose structure is similar to that of the empirical WDNs. The comparison between the empirical and modeled WDNs suggests that the empirical WDNs may realize a reasonable balance between cost, efficiency, and robustness in terms of the network structure. We also study the design of pipe diameters based on a biological positive feedback mechanism. Specifically, we apply a model inspired by Physarum polycephalum to find moderate positive correlations between the empirical and modeled pipe diameters. The difference between the empirical and modeled pipe diameters suggests that we may be able to improve the performance of WDNs by following organizing principles of biological flow networks. Copyright © 2021, The Authors. All rights reserved.

关键词： Water distribution systems