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Novel Optical Materials and Applications, NOMA 2022

作者： Tockhorn, Philipp Sutter, Johannes Cruz, Alexandros Wagner, Philipp Jäger, Klaus Yoo, Danbi Lang, Felix Grischek, Max Li, Bor Al-Ashouri, Amran Köhnen, Eike Stolterfoht, Martin Neher, Dieter Schlatmann, Rutger Rech, Bernd Stannowski, Bernd Albrecht, Steve Becker, Christiane Division Solar Energy Helmholtz-Zentrum Berlin Für Materialien und Energie GmbH Kekuléstr. 5 Berlin12489 Germany Computational Nanooptics Group Zuse Institute Berlin Takustr. 7 Berlin14195 Germany Universität Potsdam Soft Matter Physics Karl-Liebknecht-Straße 24/25 Potsdam14476 Germany Faculty of Electrical Engineering and Computer Science Technische Universität Berlin Berlin10587 Germany Faculty 1: School of Engineering - Energy and Information Hochschule Für Technik und Wirtschaft Berlin Berlin10313 Germany

We present results on perovskite/silicon tandem solar cells with almost 30% power conversion efficiency. They comprise sinusoidal nanotextures between top and bottom cells and optically advanced rear reflectors with a... 详细信息

ISBN: (纸本)9781557528209

关键词： Perovskite

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Technology Roadmap for Flexible Sensors

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ACS NANO 2023年第6期17卷 5211-5295页

作者： Luo, Yifei Abidian, Mohammad Reza Ahn, Jong-Hyun Akinwande, Deji Andrews, Anne M. Antonietti, Markus Bao, Zhenan Berggren, Magnus Berkey, Christopher A. Bettinger, Christopher John Chen, Jun Chen, Peng Cheng, Wenlong Cheng, Xu Choi, Seon-Jin Chortos, Alex Dagdeviren, Canan Dauskardt, Reinhold H. Di, Chong-an Dickey, Michael D. Duan, Xiangfeng Facchetti, Antonio Fan, Zhiyong Fang, Yin Feng, Jianyou Feng, Xue Gao, Huajian Gao, Wei Gong, Xiwen Guo, Chuan Fei Guo, Xiaojun Hartel, Martin C. He, Zihan Ho, John S. Hu, Youfan Huang, Qiyao Huang, Yu Huo, Fengwei Hussain, Muhammad M. Javey, Ali Jeong, Unyong Jiang, Chen Jiang, Xingyu Kang, Jiheong Karnaushenko, Daniil Khademhosseini, Ali Kim, Dae-Hyeong Kim, Il-Doo Kireev, Dmitry Kong, Lingxuan Lee, Chengkuo Lee, Nae-Eung Lee, Pooi See Lee, Tae-Woo Li, Fengyu Li, Jinxing Liang, Cuiyuan Lim, Chwee Teck Lin, Yuanjing Lipomi, Darren J. Liu, Jia Liu, Kai Liu, Nan Liu, Ren Liu, Yuxin Liu, Yuxuan Liu, Zhiyuan Liu, Zhuangjian Loh, Xian Jun Lu, Nanshu Lv, Zhisheng Magdassi, Shlomo Malliaras, George G. Matsuhisa, Naoji Nathan, Arokia Niu, Simiao Pan, Jieming Pang, Changhyun Pei, Qibing Peng, Huisheng Qi, Dianpeng Ren, Huaying Rogers, John A. Rowe, Aaron Schmidt, Oliver G. Sekitani, Tsuyoshi Seo, Dae-Gyo Shen, Guozhen Sheng, Xing Shi, Qiongfeng Someya, Takao Song, Yanlin Stavrinidou, Eleni Su, Meng Sun, Xuemei Takei, Kuniharu Tao, Xiao-Ming Tee, Benjamin C. K. Thean, Aaron Voon-Yew Trung, Tran Quang Wan, Changjin Wang, Huiliang Wang, Joseph Wang, Ming Wang, Sihong Wang, Ting Wang, Zhong Lin Weiss, Paul S. Wen, Hanqi Xu, Sheng Xu, Tailin Yan, Hongping Yan, Xuzhou Yang, Hui Yang, Le Yang, Shuaijian Yin, Lan Yu, Cunjiang Yu, Guihua Yu, Jing Yu, Shu-Hong Yu, Xinge Zamburg, Evgeny Zhang, Haixia Zhang, Xiangyu Zhang, Xiaosheng Zhang, Xueji Zhang, Yihui Zhang, Yu Zhao, Siyuan Zhao, Xuanhe Zheng, Yuanjin Zheng, Yu-Qing Zheng, Zijian Zhou, Tao Zhu, Bowen Zhu, Ming Zhu, Rong Zhu, Yangzhi Zhu, Yong Zou, Guijin Chen, Xiaodong 08-03 Innovis Singapore 138634 Republic of Singapore Innovative Centre for Flexible Devices (iFLEX) School of Materials Science and Engineering Nanyang Technological University Singapore 639798 Singapore Department of Biomedical Engineering University of Houston Houston Texas 77024 United States School of Electrical and Electronic Engineering Yonsei University Seoul 03722 Republic of Korea Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 United States Microelectronics Research Center The University of Texas at Austin Austin Texas 78758 United States Department of Chemistry and Biochemistry California NanoSystems Institute and Department of Psychiatry and Biobehavioral Sciences Semel Institute for Neuroscience and Human Behavior and Hatos Center for Neuropharmacology University of California Los Angeles Los Angeles California 90095 United States Colloid Chemistry Department Max Planck Institute of Colloids and Interfaces 14476 Potsdam Germany Department of Chemical Engineering Stanford University Stanford California 94305 United States Laboratory of Organic Electronics Department of Science and Technology Campus Norrköping Linköping University 83 Linköping Sweden Wallenberg Initiative Materials Science for Sustainability (WISE) and Wallenberg Wood Science Center (WWSC) SE-100 44 Stockholm Sweden Department of Materials Science and Engineering Stanford University Stanford California 94301 United States Department of Biomedical Engineering and Department of Materials Science and Engineering Carnegie Mellon University Pittsburgh Pennsylvania 15213 United States Department of Bioengineering University of California Los Angeles Los Angeles California 90095 United States School of Chemistry Chemical Engineering and Biotechnology Nanyang Technological University Singapore 637457 Singapore Nanobionics Group Department of Chemical and Biological Engineering Monash University Clayton Australia 3800 Monash

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze continued...challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative

关键词： soft materials mechanics engineering flexible electronics conformable sensors bioelectronics human-machine interfaces body area sensor networks technology translation sustainable electronics

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Plasmonic and photonic enhancement of chiral near fields

arXiv

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arXiv 2022年

作者： Hu, Li Sun, Zhiguang Nie, Yingdong Huang, Yingzhou Fang, Yurui Chongqing Engineering Laboratory for Detection Control and Integrated System School of Computer Science and Information Engineering Chongqing Technology and Business University Chongqing400067 China School of Physics Dalian University of Technology Dalian116024 China State Key Laboratory of Coal Mine Disaster Dynamics and Control Chongqing Key Laboratory of Soft Condensed Matter Physics and Smart Materials College of Physics Chongqing University Chongqing400044 China

A chiral near field with a highly contorted electromagnetic field builds a bridge to match the chiral molecules and light wavelengths with large size differences. It significantly enhances the circular dichroism of chiral molecules and has great prospects in chirality sensing, detection, trapping, and other chirality-related applications. Surface plasmons feature outstanding light-trapping and electromagnetic-field-concentrating abilities. Plasmonic chiral nanostructures facilitate light manipulation to generate superchiral near fields. Meanwhile, the nanophotonic structures have attracted significant interest to obtain strong chiral fields due to their unique electromagnetic resonant properties. During the interaction of light and chiral materials, the chiral near field not only bridges the light and chiral molecules but is also responsible for the optical activities. This paper reviews state-of-the-art studies on chiral near field enhancement using plasmonic and photonic nanostructures. We review the principle of chiral electromagnetic fields and the development of plasmonic and photonic nanostructures for near field enhancement. The properties and applications of enhanced chiral near fields for chiral molecule detection, spin-orbit angular interaction, and the generation of the chiral optical force are examined. Finally, we discuss current challenges and provide a brief outlook of this field. Copyright © 2022, The Authors. All rights reserved.

关键词： Dichroism

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Dear-DIA^(XMBD): Deep Autoencoder Enables Deconvolution of Data-Independent Acquisition Proteomics

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Research 2024年第1期6卷 707-720页

作者： Qingzu He Chuan-Qi Zhong Xiang Li Huan Guo Yiming Li Mingxuan Gao Rongshan Yu Xianming Liu Fangfei Zhang Donghui Guo Fangfu Ye Tiannan Guo Jianwei Shuai Jiahuai Han Department of Physics and Fujian Provincial Key Laboratory for Soft Functional Materials ResearchXiamen UniversityXiamen 361005China Oujiang Laboratory(Zhejiang Lab for Regenerative Medicine Vision and Brain Health)and Wenzhou InstituteUniversity of Chinese Academy of SciencesWenzhouZhejiang 325001China School of Life Sciences Xiamen UniversityXiamen 361102China State Key Laboratory of Cellular Stress Biology Innovation Center for Cell Signaling NetworkXiamen 361102China Department of Computer Science Xiamen UniversityXiamen 361005China National Institute for Data Science in Health and Medicine School of MedicineXiamen UniversityXiamen 361102China Bruker(Beijing)Scientific Technology Co.Ltd. BeijingChina Westlake Laboratory of Life Sciences and Biomedicine Key Laboratory of Structural Biology of Zhejiang ProvinceSchool of Life SciencesWestlake University18 Shilongshan RoadHangzhou 310024China Institute of Basic Medical Sciences Westlake Institute for Advanced Study18 Shilongshan RoadHangzhou 310024China Westlake Omics Ltd. Yunmeng Road 1HangzhouChina Department of Electronic Engineering Xiamen UniversityXiamen 361005China

Data-independent acquisition(DIA)technology for protein identification from mass spectrometry and related algorithms is developing *** spectrum-centric analysis of DIA data without the use of spectra library from data-dependent acquisition data represents a promising *** this paper,we proposed an untargeted analysis method,Dear-DIA^(XMBD),for direct analysis of DIA ***-DIA^(XMBD) first integrates the deep variational autoencoder and triplet loss to learn the representations of the extracted fragment ion chromatograms,then uses the k-means clustering algorithm to aggregate fragments with similar representations into the same classes,and finally establishes the inverted index tables to determine the precursors of fragment clusters between precursors and peptides and between fragments and *** show that Dear-DIA^(XMBD) performs superiorly with the highly complicated DIA data of different species obtained by different instrument platforms.

关键词： Deep Auto Independent

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Predicting Deterioration in Mild Cognitive Impairment with Survival Transformers, Extreme Gradient Boosting and Cox Proportional Hazard Modelling

arXiv

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arXiv 2024年

作者： Musto, Henry Stamate, Daniel Logofatu, Doina Stahl, Daniel Data Science and Soft Compuputing Lab Goldsmiths University of London London United Kingdom School of Health Sciences The University of Manchester Manchester United Kingdom Faculty of Computer Science and Engineering Frankfurt University of Applied Sciences Frankfurt Germany Department of Biostatistics Institute of Psychiatry Psychology and Neuroscience King's College London London United Kingdom

The paper proposes a novel approach of survival transformers and extreme gradient boosting models in predicting cognitive deterioration in individuals with mild cognitive impairment (MCI) using metabolomics data in the ADNI cohort. By leveraging advanced machine learning and transformer-based techniques applied in survival analysis, the proposed approach highlights the potential of these techniques for more accurate early detection and intervention in Alzheimer's dementia disease. This research also underscores the importance of non-invasive biomarkers and innovative modelling tools in enhancing the accuracy of dementia risk assessments, offering new avenues for clinical practice and patient care. A comprehensive Monte Carlo simulation procedure consisting of 100 repetitions of a nested cross-validation in which models were trained and evaluated, indicates that the survival machine learning models based on Transformer and XGBoost achieved the highest mean C-index performances, namely 0.85 and 0.8, respectively, and that they are superior to the conventional survival analysis Cox Proportional Hazards model which achieved a mean C-Index of 0.77. Moreover, based on the standard deviations of the C-Index performances obtained in the Monte Carlo simulation, we established that both survival machine learning models above are more stable than the conventional statistical model. © 2024, CC BY.

关键词： Risk assessment

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Nanoparticle localization within chiral liquid crystal defect lines and nanoparticle interactions

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Physical Review E 2023年第3期107卷 034701-034701页

作者： Mykola Tasinkevych Sungoh Park Haridas Mundoor Ivan I. Smalyukh SOFT Group School of Science and Technology Nottingham Trent University Clifton Lane Nottingham NG11 8NS United Kingdom Departamento de Física and Centro de Física Teórica e Computacional Faculdade de Ciências Universidade de Lisboa 1749-016 Lisboa Portugal International Institute for Sustainability with Knotted Chiral Meta Matter Hiroshima University Higashihiroshima 739-8511 Japan Department of Physics University of Colorado Boulder Colorado 80309 USA Soft Materials Research Center Department of Electrical Computer and Energy Engineering and Materials Science and Engineering Program and Renewable and Sustainable Energy Institute National Renewable Energy Laboratory University of Colorado Boulder Colorado 80309 USA

Self-assembly of colloidal particles into predefined structures is a promising way to design inexpensive manmade materials with advanced macroscopic properties. Doping of nematic liquid crystals (LCs) with nanoparticles has a series of advantages in addressing these grand scientific and engineering challenges. It also provides a very rich soft matter platform for the discovery of unique condensed matter phases. The LC host naturally allows the realization of diverse anisotropic interparticle interactions, enriched by the spontaneous alignment of anisotropic particles due to the boundary conditions of the LC director. Here we demonstrate theoretically and experimentally that the ability of LC media to host topological defect lines can be used as a tool to probe the behavior of individual nanoparticles as well as effective interactions between them. LC defect lines irreversibly trap nanoparticles enabling controlled particle movement along the defect line with the use of a laser tweezer. Minimization of Landau–de Gennes free energy reveals a sensitivity of the ensuing effective nanoparticle interaction to the shape of the particle, surface anchoring strength, and temperature, which determine not only the strength of the interaction but also its repulsive or attractive character. Theoretical results are supported qualitatively by experimental observations. This work may pave the way toward designing controlled linear assemblies as well as one-dimensional crystals of nanoparticles such as gold nanorods or quantum dots with tunable interparticle spacing.

关键词： Charged colloids Complex fluids Liquid crystals

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In Situ Graft‑on Fibrous Composites and Nanostructure Interlocking Facilitate Highly Stable Wearable Sensors for SIDS Prevention

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Advanced Fiber Materials 2024年第3期6卷 825-840页

作者： Kaifeng Chen Weitao Wang Zhihao Ye Yabo Dong Linpu Wan Zijian Zhang Cheng Lin Liwu Liu Jinsong Leng Xinyu Wang Wei Yang Shaoxing Qu Zongrong Wang State Key Laboratory of Silicon and Advanced Semiconductor Materials and School of Materials Science and Engineering Zhejiang UniversityHangzhou 310027People’s Republic of China Institute of Thermal Science and Technology Shandong UniversityJinan 250061People’s Republic of China School of Computer Science and Technology Zhejiang UniversityHangzhou 310027People’s Republic of China Key Laboratory of Soft Machines and Smart Devices of Zhejiang Province and School of Aeronautics and Astronautics Zhejiang UniversityHangzhou 310027People’s Republic of China Department of Astronautical Science and Mechanics Harbin Institute of Technology(HIT)Harbin 150001People’s Republic of China Center for Composite Materials and Structures Harbin Institute of Technology(HIT)Harbin 150080People’s Republic of China

High-performance and reliable wearable devices for healthcare are in high demand for the health monitoring of infants,ensuring that life-threatening events can be addressed ***,the continuous monitoring of infant respiration for preventing sudden infant death syndrome(SIDS)is proposed using high-performance flexible piezoresistive sensors(FPS).The thorny challenges associated with FPS,including the signal drift and poor repeatability,are progressively improved via the employment of high-Tg matrix,the strengthening of in situ graft-on conducting polyaniline layer byβ-cyclodextrin(β-CD),and the nanostructure interlocking between the piezoresistive layer and *** sensor presents high linear sensitivity(30.7 kPa^(−1)),outstanding recoverability(low hysteresis up to 1.98%FS),static stability(4.00%signal drift after 24 h at 2.4 kPa)and dynamic stability(1.92%decay of signal intensity after 50,000 cycles).A wireless infant respiration monitoring system is *** patterns and the real-time respiration rate are displayed on the *** are implemented when abnormal status such as bradypnea and tachypnea is detected.

关键词： Wearable devices Flexible pressure sensor Respiration monitoring Inclusion complex In situ graft-on composite

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HCVMultiscaleFit: A Simulator For Parameter Estimation in Multiscale Models Of Hepatitis C Virus Dynamics

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AIP conference proceedings 2020年第1期2293卷 420028页

作者： Alexander Churkin Vladimir Reinharz Stephanie Lewkiewicz Harel Dahari Danny Barash Department of Software Engineering Sami Shamoon College of Engineering Beer-Sheva Israel. Center for Soft and Living Matter Institute for Basic Science Ulsan South Korea. Department of Mathematics University of California at Los Angeles Los Angeles California USA. The Program for Experimental and Theoretical Modeling Division of Hepatology Department of Medicine Stritch School of Medicine Loyola University Chicago Maywood Illinois USA. Department of Computer Science Ben-Gurion Universty Beer-Sheva Israel.

Callibration in mathematical models that are based on differential equations is known to be of fundamental importance. For sophisticated models such as age-structured models that simulate biological agents, parameter estimation or fitting (callibration) that solves all cases of data points available presents a formidable challenge, as efficiency considerations need to be employed in order for the method to become practical. In the case of multiscale models of hepatitis C virus dynamics that deal with partial differential equations (PDEs), a fully numerical parameter estimation method was developed that does not require an analytical approximation of the solution to the multiscale model equations, avoiding the necessity to derive the long-term approximation for each model. However, the method is considerably slow because of precision problems in estimating derivatives with respect to the parameters near their boundary values, making it almost impractical for general use. In order to overcome this limitation, two steps have been taken that significantly reduce the running time by orders of magnitude and thereby lead to a practical method. First, constrained optimization is used, letting the user add constraints relating to the boundary values of each parameter before the method is executed. Second, optimization is performed by derivative-free methods, eliminating the need to evaluate expensive numerical derviative approximations. These steps that were successful in significantly speeding up a highly non-efficient approach, rendering it practical, can also be adapted to multiscale models of other viruses and other sophisticated differential equation models. The newly efficient methods that were developed as a result of the above approach are described. Illustrations are provided using a user-friendly simulator that incorporates the efficient methods for multiscale models. We provide a simulator called HCVMultiscaleFit with a Graphical User Interface that applies these

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Recent Advances in Triboelectric Nanogenerators: From Technological Progress to Commercial Applications

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ACS Nano 2023年第12期17卷 11087-11219页

作者： Choi, Dongwhi Lee, Younghoon Lin, Zong-Hong Cho, Sumin Kim, Miso Ao, Chi Kit Soh, Siowling Sohn, Changwan Jeong, Chang Kyu Lee, Jeongwan Lee, Minbaek Lee, Seungah Ryu, Jungho Parashar, Parag Cho, Yujang Ahn, Jaewan Kim, Il-Doo Jiang, Feng Lee, Pooi See Khandelwal, Gaurav Kim, Sang-Jae Kim, Hyun Soo Song, Hyun-Cheol Kim, Minje Nah, Junghyo Kim, Wook Menge, Habtamu Gebeyehu Park, Yong Tae Xu, Wei Hao, Jianhua Park, Hyosik Lee, Ju-Hyuck Lee, Dong-Min Kim, Sang-Woo Park, Ji Young Zhang, Haixia Zi, Yunlong Guo, Ru Cheng, Jia Yang, Ze Xie, Yannan Lee, Sangmin Chung, Jihoon Oh, Il-Kwon Kim, Ji-Seok Cheng, Tinghai Gao, Qi Cheng, Gang Gu, Guangqin Shim, Minseob Jung, Jeehoon Yun, Changwoo Zhang, Chi Liu, Guoxu Chen, Yufeng Kim, Suhan Chen, Xiangyu Hu, Jun Pu, Xiong Guo, Zi Hao Wang, Xudong Chen, Jun Xiao, Xiao Xie, Xing Jarin, Mourin Zhang, Hulin Lai, Ying-Chih He, Tianyiyi Kim, Hakjeong Park, Inkyu Ahn, Junseong Huynh, Nghia Dinh Yang, Ya Wang, Zhong Lin Baik, Jeong Min Choi, Dukhyun Kyung Hee University Gyeonggi Yongin17104 Korea Republic of Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology 77 Massachusetts Avenue CambridgeMA02139 United States Department of Mechanical Engineering Soft Robotics Research Center Seoul National University Seoul08826 Korea Republic of Department of Mechanical Engineering Gachon University Seongnam13120 Korea Republic of Department of Biomedical Engineering National Taiwan University Taipei10617 Taiwan Frontier Research Center on Fundamental and Applied Sciences of Matters National Tsing Hua University Hsinchu30013 Taiwan School of Advanced Materials Science & Engineering Sungkyunkwan University Suwon16419 Korea Republic of Sungkyunkwan University 2066 Seobu-ro Gyeonggi Suwon16419 Korea Republic of Department of Chemical and Biomolecular Engineering National University of Singapore 4 Engineering Drive 4 117585 Singapore Division of Advanced Materials Engineering Jeonbuk National University 567 Baekje-daero Jeonbuk Jeonju54896 Korea Republic of Jeonbuk National University 567 Baekje-daero Jeonbuk Jeonju54896 Korea Republic of Department of Physics Inha University 100 Inha-ro Incheon22212 Korea Republic of School of Materials Science & Engineering Yeungnam University Gyeongbuk Gyeongsan38541 Korea Republic of 291 Daehak-ro Daejeon34141 Korea Republic of School of Materials Science and Engineering Nanyang Technological University 50 Nanyang Avenue 639798 Singapore Institute of Flexible Electronics Technology of Tsinghua Zhejiang Jiaxing314000 China Nanomaterials and System Lab Major of Mechatronics Engineering Faculty of Applied Energy System Jeju National University Jeju632-43 Korea Republic of School of Engineering University of Glasgow GlasgowG128QQ United Kingdom Seoul02792 Korea Republic of Department of Physics Inha University Incheon22212 Korea Republic of Suwon16419 Korea Republic of Department of

Serious climate changes and energy-related environmental problems are currently critical issues in the world. In order to reduce carbon emissions and save our environment, renewable energy harvesting technologies will serve as a key solution in the near future. Among them, triboelectric nanogenerators (TENGs), which is one of the most promising mechanical energy harvesters by means of contact electrification phenomenon, are explosively developing due to abundant wasting mechanical energy sources and a number of superior advantages in a wide availability and selection of materials, relatively simple device configurations, and low-cost processing. Significant experimental and theoretical efforts have been achieved toward understanding fundamental behaviors and a wide range of demonstrations since its report in 2012. As a result, considerable technological advancement has been exhibited and it advances the timeline of achievement in the proposed roadmap. Now, the technology has reached the stage of prototype development with verification of performance beyond the lab scale environment toward its commercialization. In this review, distinguished authors in the world worked together to summarize the state of the art in theory, materials, devices, systems, circuits, and applications in TENG fields. The great research achievements of researchers in this field around the world over the past decade are expected to play a major role in coming to fruition of unexpectedly accelerated technological advances over the next decade. © 2023 The Authors. Published by American Chemical Society

关键词： Nanogenerators

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A Generalized Density Dissipation for Weakly-Compressible Sph

SSRN

引用

SSRN 2023年

作者： Zheng, Bo Xue Cai, Zhi Wen Zhao, Pei Dong Xu, Xiao Yang Chan, Tak Shing Yu, Peng Department of Mathematics University of Oslo Oslo0851 Norway Guangdong Provincial Key Laboratory of Turbulence Research and Applications Department of Mechanics and Aerospace Engineering Southern University of Science and Technology Shenzhen518055 China China Ship Scientific Research Center Wuxi214082 China School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China School of Naval Architecture and Ocean Engineering Dalian University of Technology Dalian116024 China School of Computer Science and Technology Xi’an University of Science and Technology Xian710054 China Center for Complex Flows and Soft Matter Research Southern University of Science and Technology Shenzhen518055 China

Weakly compressible Smoothed Particle Hydrodynamics (SPH) is known to suffer from numerical pressure noise, which can significantly undermine simulation stability and accuracy. In response, this study introduces a novel density dissipation scheme aimed at suppressing such unphysical noise. The proposed scheme overcomes the limitations of conventional density dissipation schemes, which are ineffective at fluid interfaces in multiphase flow simulations. As a result, the novel scheme is generally applicable to the entire computational domain, encompassing both single-phase flow and multiphase flow. This advancement is achieved through two key components. Firstly, the traditional density dissipation is replaced with a density increment dissipation approach that enables dissipation to cross interfaces separating different fluids. Secondly, based on dissipation volume conservation, we employ a dissipation volume correction factor (VCF) to stabilize simulations characterized by large density ratios. We demonstrate the accuracy, stability, and robustness of our method through four three-dimensional benchmarks: sloshing under external excitations, the rising of single and double bubbles, Rayleigh-Taylor instability, and Kelvin-Helmholtz instability. Additionally, this study reveals the relationship between SPH utilizing density dissipation and the approximate Riemann solver. © 2023, The Authors. All rights reserved.

关键词： Multiphase flow

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