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11th International Symposium on Turbulence and Shear Flow Phenomena, TSFP 2019

作者： Pullin, D.I. Cheng, Wan Samtaney, Ravi Graduate Aerospace Laboratories California Institute of Technology PasadenaCA91125 United States Mechanical Engineering Physical Science and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia

We discuss large-eddy simulations (LES) of the incompressible Navier-Stokes equations for Taylor-Couette flow. The ratio of the two co-axial cylinder diameters is η = ri/ro = 0.909 with ri the inner cylinder radius and ro the outer radius. The outer cylinder is stationary while the inner cylinder rotates with constant angular velocity ωi. Subgrid stresses are represented using the stretched-vortex model (SVM) where the subgrid motion is modeled by subgrid vortices undergoing stretching by the local resolved-scale velocity- gradient field. We report wall-resolved LES at Rei = driωi/ν up to Rei = 106 with ν the kinematic viscosity of the Newtonian fluid and d = ro − ri the cylinder gap. The present study focuses on the wall-turbulence behavior at relatively high Rei. Comparisons are made with direct numerical simulations (DNS) and with experimental results. © 2019 International Symposium on Turbulence and Shear Flow Phenomena, TSFP. All rights reserved.

关键词： Large eddy simulation

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mechanically robust bamboo node and its hierarchically fibrous structural design

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National science Review 2023年第2期10卷 199-211页

作者： Si-Ming Chen Si-Chao Zhang Huai-Ling Gao Quan Wang LiChuan Zhou Hao-Yu Zhao Xin-Yu Li Ming Gong Xiao-Feng Pan Chen Cui Ze-Yu Wang YongLiang Zhang HengAn Wu Shu-Hong Yu Department of Chemistry Institute of Biomimetic Materials & Chemistry Anhui Engineering Laboratory of Biomimetic MaterialsDivision of Nanomaterials & Chemistry Hefei National Research Center for Physical Sciences at the Microscale Institute of Energy Hefei Comprehensive National Science Center University of Science and Technology of China CAS Key Laboratory of Mechanical Behavior and Design of Materials Department of Modern MechanicsEngineering and Materials Science Experiment CenterUniversity of Science and Technology of China Institute of Innovative Materials (I2M) Department of Materials Science and EngineeringDepartment of Chemistry Southern University of Science and Technology

Although short bamboo nodes function in mechanical support and fluid exchange for bamboo survival,their structures are not fully understood compared to unidirectional fibrous ***,we identify the spatial heterostructure of the bamboo node via multiscale imaging strategies and investigate its me chanical properties by multimodal mechanical *** find three kinds of hierarchical fiber reinforcement schemes that originate from the bamboo node,including spatially tightened interlocking,triaxial interconnected scaffolding and isotropic *** reinforcement schemes,built on porous vascular bundles,microfibers and more-refined twist-aligned nanofibers,govern the structural stability of the bamboo via hierarchical *** addition,the spatial liquid transport associated with these multiscale fibers within the bamboo node is experimentally verified,which gives perceptible evidence for life-indispensable multidirectional fluid *** functional integration of mechanical reinforcement and liquid transport reflects the fact that the bamboo node has opted for elaborate structural optimization rather than ingredient *** study will advance our understanding of biological materials and provide insight into the design of fiber-reinforced structures and biomass utilization.

关键词： biological materials bamboo node hierarchical fiber structural reinforcement functional integration

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Conversion of twisted light to twisted excitons using carbon nanotubes

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npj Computational Materials 2022年第1期8卷 392-402页

作者： Xiaoning Zang Nirpendra Singh Mark T.Lusk Udo Schwingenschlögl Applied Physics Program Physical Sciences and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal23955-6900Saudi Arabia Department of Physics Khalifa University of Science and TechnologyAbu Dhabi127788United Arab Emirates Department of Physics Colorado School of MinesGoldenCO80401USA

Carbon nanotubes are explored as a means of coherently converting the orbital angular momentum of light to an excitonic form that is more amenable to quantum information *** analytical analysis,based on dynamical conductivity,is used to show that orbital angular momentum is conserved,modulo N,for a carbon nanotube illuminated by radially polarized,twisted *** result is numerically demonstrated using real-time time-dependent density functional theory which captures the absorption of twisted light and the subsequent transfer of twisted *** results suggest that carbon nanotubes are promising candidates for constructing optoelectronic circuits in which quantum information is more readily processed while manifested in excitonic form.

关键词： twisted carbon light

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AI-driven 3D Spatial Transcriptomics

arXiv

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arXiv 2025年

作者： Almagro-Pérez, Cristina Song, Andrew H. Weishaupt, Luca Kim, Ahrong Jaume, Guillaume Williamson, Drew F.K. Hemker, Konstantin Lu, Ming Y. Singh, Kritika Chen, Bowen Le, Long Phi Baras, Alexander S. Jiang, Sizun Bashashati, Ali Liu, Jonathan T.C. Mahmood, Faisal Department of Pathology Mass General Brigham Harvard Medical School BostonMA United States Cancer Program Broad Institute of Harvard and MIT CambridgeMA United States Data Science Program Dana-Farber Cancer Institute BostonMA United States Harvard-MIT Division of Health Sciences and Technology Massachusetts Institute of Technology CambridgeMA United States Department of Pathology Pusan National University Busan Korea Republic of Department of Pathology and Laboratory Medicine Emory University School of Medicine AtlantaGA United States Department of Computer Science & Technology University of Cambridge Cambridge United Kingdom Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA United States Rutgers Robert Wood Johnson Medical School New BrunswickNJ United States Department of Pathology Johns Hopkins Hospital BaltimoreMD United States Department of Biomedical Engineering Johns Hopkins Hospital BaltimoreMD United States Broad Institute of Harvard and MIT CambridgeMA United States Center for Virology and Vaccine Research Beth Israel Deaconess Medical Center Harvard Medical School BostonMA United States Department of Pathology Dana Farber Cancer Institute BostonMA United States Department of Pathology and Laboratory Medicine University of British Columbia VancouverBC Canada School of Biomedical Engineering University of British Columbia VancouverBC Canada Department of Mechanical Engineering Bioengineering Laboratory Medicine & Pathology University of Washington SeattleWA United States Harvard Data Science Initiative Harvard University CambridgeMA United States

A comprehensive three-dimensional (3D) map of tissue architecture and gene expression is crucial for illuminating the complexity and heterogeneity of tissues across diverse biomedical applications1. However, most spatial transcriptomics (ST) approaches remain limited to two-dimensional (2D) sections of tissue2–4. Although current 3D ST methods hold promise, they typically require extensive tissue sectioning, are complex, are not compatible with non-destructive 3D tissue imaging technologies, and often lack scalability5–8. Here, we present VOlumetrically Resolved Transcriptomics EXpression (VORTEX), an AI framework that leverages 3D tissue morphology and minimal 2D ST to predict volumetric 3D ST. By pretraining on diverse 3D morphology–transcriptomic pairs from heterogeneous tissue samples and then fine-tuning on minimal 2D ST data from a specific volume of interest, VORTEX learns both generic tissue-related and sample-specific morphological correlates of gene expression. This approach enables dense, high-throughput, and fast 3D ST, scaling seamlessly to large tissue volumes far beyond the reach of existing 3D ST techniques. By offering a cost-effective and minimally destructive route to obtaining volumetric molecular insights, we anticipate that VORTEX will accelerate biomarker discovery and our understanding of morphomolecular associations and cell states in complex tissues. Interactive 3D ST volumes can be viewed at https://***/. © 2025, CC BY-NC-ND.

关键词： Vortex flow

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A motion-level-aware denoising framework for x-ray fluoroscopic images

A motion-level-aware denoising framework for x-ray fluorosco...

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Medical Imaging 2023: Physics of Medical Imaging

作者： Jo, Geonhui Jang, Minhee Jeon, Sun-Young Kim, Wonjin Choi, Jang-Hwan Department of Computer Science and Engineering Ewha Womans University Seoul03760 Korea Republic of Division of Mechanical and Biomedical Engineering Graduate Program in System Health Science and Engineering Ewha Womans University Seoul03760 Korea Republic of

ISBN: (纸本)9781510660311

Fluoroscopy in a low-dose tube output is used to reduce the damage associated with radiation exposure. However, lowering the radiation dose inevitably increases random noise in x-ray images, resulting in poor diagnostic image quality, which requires noise reduction for accurate diagnosis. Also, in the case of non-static objects, the image is blurred due to motion. The most-used denoiser with a recursive filter (RF) preserves details well when applied to temporal data, but it is vulnerable to motion blur. Existing convolutional neural network (CNN)-based algorithms with single-frame input cannot use the temporary context, and others with multi-frame input are good for motion detection but poor for detail preservation. Therefore, we propose a motion-level-aware denoising framework to combine the results of RF- and CNN-based algorithms depending on the pixel-wise magnitude of motion to complement each other. The data we use are fluoroscopy images taken in continuous time, and we aim at many-to-one so that one frame is denoised by considering sequential frames. Also, since both RF- and CNN-based algorithms used in our architecture are many-to-one methods, they can consider spatiotemporal information. In the multi-frame input, the difference in intensity of each pixel between frames is calculated to obtain a moving map. Depending on the factor value from the moving map, the final image is obtained by reflecting the outputs of the RF- and CNN-based algorithms. If the factor value is high, the pixel intensity of the final image is like the CNN-based output, which is good for motion detection, and vice versa, it more reflects the intensity of RF output, which is excellent in perceptual quality. Therefore, it prevents motion blur and does not over-smooth microdetails, such as bones and muscles. The results show that combining the two outputs together records higher peak signal-to-noise ratio (PSNR) and has better perceptual quality for diagnosis than using only one method. F

关键词： Deep learning

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Challenges and deep learning-aided models for the development of natural hydrogen

Energy Science

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Energy science 2025年第01期01卷

作者： Shuyu Sun Jihong Shi Ping Hu Jie Liu Tao Zhang Physical Science and Engineering Division (PSE) King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900 Saudi Arabia Department of Physics King’s College London Strand London WC2R 2LS United Kingdom Department of Mechanical and Production Engineering — Mechanics and Materials Arhus University Denmark College of New Energy China University of Petroleum (East China) Qingdao Shandong China

Hydrogen is a promising energy carrier that plays a crucial role in the transition toward a low-carbon economy. While most hydrogen is currently produced from fossil fuels or through water electrolysis using renewable energy, natural hydrogen (also known as white, native, geological hydrogen) represents an underexplored and potentially abundant source. This paper aims to provide a comprehensive overview of the current state of knowledge on the development of natural hydrogen, highlighting the technical challenges in detection, exploration, production and transportation. To resolve these challenges, a number of deep learning-aided models have been developed, including geological feature detection models, phase equilibrium models and gas transportation models. Concluding remarks are discussed for insight into future research directions.

关键词： Natural hydrogen deep learning reservoir simulation TINN

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Integrated optical gas sensing and wireless communicationin the mid-infrared

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Applied Optics 2025年第16期64卷 D114-D121页

作者： Ali Elkhazraji Mohammed Sait Aamir Farooq Department of Mechanical Engineering King Fahd University of Petroleum & Minerals Dhahran 31261 Saudi Arabia Interdisciplinary Research Center for Hydrogen Technologies and Carbon Management King Fahd University of Petroleum & Minerals Dhahran 31261 Saudi Arabia Aramco Upstream Research Center EXPEC ARC King Abdullah University of Science and Technology (KAUST) Thuwal 23955 Saudi Arabia Physical Science and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955 Saudi Arabia

This study demonstrates the feasibility of a hybrid open-path opticalcommunication and gas sensing system utilizing an 8 µmquantum-cascade laser (QCL). The system integrates hydrogen sulfide ( ${\rm H}_{2}{\rmS}$ ) detection with wireless opticalcommunication, enabling real-time monitoring over large distances withminimal infrastructure. Spectral simulations based on HITRAN2020 wereused to select an optimal wavelength ( $1234.6\,\,\rmcm^{-1}$ ) that ensures minimal interferencefrom atmospheric ${\rm H}_{2}{\rmO}$ and ${\rm CO}_2$ while maintaining high sensitivityfor ${\rm H}_2{\rmS}$ . Experimental validation confirmedthe system’s independent capabilities for sensing and *** simultaneous operation, the system demonstrated robustperformance with an inverse relationship between bit error rate (BER)and gas sensing accuracy as ${\rm H}_2{\rmS}$ concentration varied. Theintersection point of these performance metrics ( ${\sim}{8}\% \;{\rmH_{2}S}$ ) highlights the system’s operationalfeasibility at relevant leak concentrations in oil and gasenvironments. This work lays the groundwork for advanced hybridsystems applicable to industrial safety and environmentalmonitoring.

关键词： Diode lasers Distributed feedback lasers Fiber Bragg grating sensors Free space optics Optical detection Optical wireless communication

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Application of infrared thermal imaging to map stress distributions in a solid oxide fuel cell

Application of infrared thermal imaging to map stress distri...

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30th Fuel Cell Seminar

作者： Clague, R. Aguiar, P. Brett, D.J.L. Marquis, A.J. Schottl, S. Simpson, R. Brandon, N.P. Department of Mechanical Engineering Imperial College London United Kingdom Department of Earth Science and Engineering Imperial College London United Kingdom Engineering and Process Control Division National Physical Laboratory Teddington United Kingdom

ISBN: (纸本)9781566775496

The application of infrared thermal imaging to the study of solid oxide fuel cell components with applied thermal gradients is demonstrated. Thermal imaging of a technologically relevant SOFC sample was carried out while a temperature gradient was induced by heating the sample in a furnace and blowing cold nitrogen at its centre. Subsequently the stress field in the sample was determined by a novel method of converting the thermal image into nodal temperatures for a finite element analysis. Asymmetry in the temperature distribution across the samples was marked, whereas previous versions of the thermal gradient experiment had assumed axisymmetry. © The Electrochemical Society.

关键词： Thermal gradients

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Selective Interface engineering with Large π-Conjugated Molecules Enables Durable Zn Anodes

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Angewandte Chemie 2025年

作者： Dr. Feng Zhang Dr. Qiangqiang Meng Jia-Wei Qian Dr. Jingwei Chen Wei-Xu Dong Dr. Kai Chen Dr. Yang-Feng Cui Prof. Dr. Shi Xue Dou Prof. Dr. Li-Feng Chen Division of Nanomaterials & Chemistry Hefei National Research Center for Physical Sciences at the Microscale School of Chemistry and Materials Science CAS Key Laboratory of Mechanical Behavior and Design of Materials (LMBD) School of Engineering Science University of Science and Technology of China Hefei Anhui 230026 PR China. School of Materials Science and Engineering Ocean University of China Qingdao 266100 PR China Pillar of Engineering Product Development Singapore University of Technology and Design Singapore 487372 Singapore Institute for Superconducting and Electronic Materials University of Wollongong NSW 2522 Australia Institute of Energy Materials Science (IEMS) University of Shanghai for Science and Technology Shanghai PR China.

Undesirable dendrite growth and side reactions at the electrical double layer (EDL) of Zn/electrolyte interface are critical challenges limiting the performance of aqueous zinc ion batteries. Through density functional theory calculations, we demonstrate that grafting large π-conjugated molecules (e.g. bilirubin, biliverdin, lumirubin, and hemoglobin) onto Zn surface induces preferential adsorption on non-(002) facets, leading to interfacial charge redistribution, upshifted Zn d-band center, and enhanced H + fixation capability. Among these, bilirubin (BR) is identified as the most effective, preferentially adsorbing onto non-Zn(002) facets to inhibit hydrogen evolution reaction and promote Zn(002) planar growth during plating. This approach results in average Coulombic efficiency of 99.86 % over 4000 cycles in Zn||BR-1@Cu cells and prolonged lifespan exceeding 1600 h in BR-1@Zn||BR-1@Zn cells at 10 mA cm −2 and 1 mAh cm −2 . Even under harsh conditions of 25 mA cm −2 and 10 mAh cm −2 , BR-1@Zn||BR-1@Zn cell maintains a lifespan of over 400 h. Furthermore, BR-1@Zn||MnO 2 and BR-1@Zn||NVO full cells achieve 76.4 % and 86.1 % capacity retention after 800 and 1400 cycles at 1.0 A g −1 , respectively. This study underscores the importance of grafting large π-conjugated molecules to allow selective Zn(002) exposure, Zn d-band center upshift, and EDL structure regulation, paving the way towards durable Zn anodes.

关键词： large π-conjugated molecules preferential absorption interface engineering d-band center aqueous zinc-ion battery

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Eco-friendly moxifloxacin removal using date seed waste and Ni-Fe LDH: Adsorption efficiency and antimicrobial potential

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Ecotoxicology and Environmental Safety 2025年 297卷 118256页

作者： Mahmoud, Ahmed Abo El-Ela, Fatma I. Mahmoud, Rehab Shehata, Ayman Z. El-Raheem, Hany Abd Salama, Esraa Allam, Ahmed A. Alfassam, Haifa E. Zaher, Amal Environmental Science and Industrial Development Department Faculty of Postgraduate Studies for Advanced Sciences Beni-Suef University Beni-Suef 62511 Egypt Department of Pharmacology Faculty of Veterinary Medicine Beni-Suef University Beni-Suef 62511 Egypt Chemistry Department Faculty of Science Beni-Suef University Beni-Suef 62511 Egypt Department of Food Safety and Technology Faculty of Veterinary Medicine Beni-Suef University Beni-Suef Egypt Centre of Excellence for Trace Analysis and Biosensor Division of Physical Science Faculty of Science Prince of Songkla University Songkhla Hat Yai 90110 Thailand Environmental Engineering Program Zewail City of Science and Technology October Gardens 6th of October Giza 12578 Egypt Department of Biology College of Science Imam Mohammad Ibn Saud Islamic University Riyadh 11623 Saudi Arabia Department of Biology college of Science Princess Nourah bint Abdulrahman University P.O. BOX 84428 Riyadh 11671 Saudi Arabia

Background: New pharmacological remediation techniques were needed due to their detrimental impacts on human health and aquatic ecosystems. Layer double hydroxide (LDH) can be made inexpensively and readily available using easy preparation techniques. Three nanomaterials date seed powder (DSP), Ni-Fe LDH, and Ni-Fe LDH/(DSP) composite are used to eliminate Moxifloxacin (MOX). Objective: Providing the date seed powder (DSP), Ni-Fe LDH, and Ni-Fe LDH/(DSP) composite multifunction as an ecofriendly adsorbents for antibiotic residues also its assessing antibacterial effectiveness in addition to other fungal organisms. Methods: The catalysts were synthesized via co-precipitation and characterized using HRTEM, FESEM, FT-IR, X-ray, PZC and BET analyses. Adsorption experiments were conducted to evaluate the effects of pH, adsorbent dose, and contact time, while kinetic and isotherm models were employed to elucidate the adsorption mechanisms. Minimum Inhibitory Concentration (MIC), Minimum Fungicidal Concentration (MFC), Minimum Bactericidal Concentration (MBC), and Disc Diffusion assays for bacterial activity were applied for antifungal study. Results: The removal percent of the MOX was 35.37 % at pH 3, 44.91 % at pH 7, and 83.50 % at pH 5 for (DSP), Ni-Fe LDH and Ni-Fe LDH /(DSP) composite, respectively. The Langmuir- Freundlich model is the best suitable model for three nanomaterials (DSP), Ni-Fe LDH and Ni-Fe LDH /(DSP), R² were (0.97,0.99 and 0.99, respectively) and q_max were (212.77, 206.7 and 251,6 respectively). Conclusion: current research indicates that the Ni-Fe LDH/(DSP) composite is a promising nanomaterial for treating wastewater and has a greater antimicrobial efficacy than each alone against both bacterial and fungal pathogens. © 2025 The Authors

关键词： Adsorption Antibiotic-resistant pathogens Biomaterial Date seeds LDH Mechanism MOX

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