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Fluorinated Graphene-Coated N95 Respirators for Enhanced Protection against Viral Accumulation and Transmission

Advanced engineering Materials 2025年

作者： He, Fengjie Zhang, Jiongyu Zhai, Shengjie Liu, Changchun Zhao, Hui Department of Mechanical Engineering University of Nevada Las Vegas 4505 S Maryland Parkway Las Vegas89154 United States Department of Biomedical Engineering University of Connecticut Health Center 263 Farmington Avenue FarmingtonCT06030 United States Department of Electrical and Computer Engineering University of Nevada Las Vegas 4505 S Maryland Parkway Las Vegas89154 United States

Highly contagious respiratory infection diseases such as COVID-19 can be transmitted by inhaling virus laden liquid droplets and short-range aerosols, released by an infected person. Particularly, in hospitals, spraying of the respiratory droplets containing pathogens from the conjunctiva or mucus of a susceptible person plays a key role in transferring the infectious diseases. N95 filtering respirators are a critical personal protective equipment. However, due to concerns over the virus accumulation on the N95 respirators, there is an urgent need to make the N95 respirators less contaminated. To address this critical issue, a one-step spray coating approach is developed to coat the fluorinated graphene (FG) nanosheet onto the N95 respirators. The synergistic effect of the FG nanosheet with a low surface energy and the increased surface roughness by FG on the respirator's surface makes it superhydrophobic. For respiratory droplets like saliva and mucus, the FG-coated respirators also show excellent superhydrophobicity. Furthermore, the ability against virus accumulation on the FG-coated respirators is tested by using the mucus droplets laden with SARS-CoV-2. The results show that FG-coated respirators largely increase the virus repel efficiency even under multiple contacts and effectively reduce the virus accumulation. © 2025 The Author(s). Advanced engineering Materials published by Wiley-VCH GmbH.

关键词： Sprayed coatings

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A flexible head fixation system for optical imaging and electrophysiology in awake mice

A flexible head fixation system for optical imaging and elec...

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Clinical and Translational Biophotonics, Translational 2020

作者： Thunemann, Martin Mächler, Phillip Fomin-Thunemann, Natalie Lu, Yichen Liu, Xin Kuzum, Duygu Devor, Anna Department of Neurosciences University of California San Diego San DiegoCA92093 United States Department of Electrical and Computer Engineering University of California San Diego San DiegoCA92093 United States Department of Biomedical Engineering Boston University BostonMA02215 United States Department of Radiology University of California San Diego San DiegoCA92093 United States Athinoula A. Martinos Center for Biomedical Imaging CharlestownMA02129 United States

ISBN: (纸本)9781943580743

关键词： Electrophysiology

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Torsional periodic lattice distortions and diffraction of twisted 2D materials

arXiv

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arXiv 2022年

作者： Sung, Suk Hyun Goh, Yin Min Yoo, Hyobin Engelke, Rebecca Xie, Hongchao Zhang, Kuan Li, Zidong Ye, Andrew Deotare, Parag B. Tadmor, Ellad B. Mannix, Andrew J. Park, Jiwoong Zhao, Liuyan Kim, Philip Hovden, Robert Department of Materials Science and Engineering University of Michigan Ann ArborMI48109 United States Department of Physics University of Michigan Ann ArborMI48109 United States Department of Physics Sogang University Seoul04107 Korea Republic of Department of Physics Harvard University CambridgeMA02138 United States Aerospace Engineering and Mechanics University of Minnesota MinneapolisMN55455 United States Electrical and Computer Engineering Department University of Michigan Ann ArborMI48109 United States Pritzker School of Molecular Engineering University of Chicago ChicagoIL60637 United States Applied Physics Program University of Michigan Ann ArborMI48109 United States Department of Materials Science and Engineering Stanford University StanfordCA94305 United States Department of Chemistry University of Chicago ChicagoIL60637 United States

Twisted 2D materials form complex moiré structures that spontaneously reduce symmetry through picoscale deformation within a mesoscale lattice. We show twisted 2D materials contain a torsional displacement field comprised of three transverse periodic lattice distortions (PLD). The torsional PLD amplitude provides a single order parameter that concisely describes the structural complexity of twisted bilayer moirés. Moreover, the structure and amplitude of a torsional periodic lattice distortion is quantifiable using rudimentary electron diffraction methods sensitive to reciprocal space. In twisted bilayer graphene, the torsional PLD begins to form at angles below 3.89° and the amplitude reaches 8 pm around the magic angle of 1. 1°. At extremely low twist angles (e.g. below 0.25°) the amplitude increases and additional PLD harmonics arise to expand Bernal stacked domains separated by well defined solitonic boundaries. The torsional distortion field in twisted bilayer graphene is analytically described and has an upper bound of 22.6 pm. Similar torsional distortions are observed in twisted WS2, CrI3, and WSe2/MoSe2 © 2022, CC BY.

关键词： Graphene

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Speckle statistics of biological tissues in optical coherence tomography

arXiv

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arXiv 2021年

作者： Ge, Gary R. Rolland, Jannick P. Parker, Kevin J. The Institute of Optics University of Rochester RochesterNY14627 United States Department of Electrical and Computer Engineering University of Rochester RochesterNY14627 United States Department of Biomedical Engineering University of Rochester NY14627 United States Center for Visual Science University of Rochester NY14627 United States

The speckle statistics of optical coherence tomography images of biological tissue have been studied using several historical probability density functions. A recent hypothesis implies that underlying power-law distributions in the medium structure, such as the fractal branching vasculature, will contribute to power-law probability distributions of speckle statistics. Specifically, these are the Burr type XII distribution for speckle amplitude, the Lomax distribution for intensity, and the generalized logistic distribution for log amplitude. In this study, these three distributions are fitted to histogram data from nine optical coherence tomography scans of various biological tissues and samples. The distributions are also compared with conventional distributions such as the Rayleigh, K, and gamma distributions. The results indicate that these newer distributions based on power laws are, in general, more appropriate models and support the plausibility of their use for characterizing biological tissue. Potentially, the governing power-law parameter of these distributions could be used as a biomarker for tissue disease or pathology. Copyright © 2021, The Authors. All rights reserved.

关键词： Optical tomography

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Exploring the Non - Hermitian Topology of Exceptional Points in Lasers and Fiber Loops

Exploring the Non - Hermitian Topology of Exceptional Points...

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Conference on Lasers and Electro-Optics Europe (CLEO EUROPE)

作者： Alexander Schumer Hadiseh Nasari Yuzhou G. N. Liu Gisela Lopez-Galmiche Jason Leshin Helena E. Lopez-Aviles Lei Ding Yousef Alahmadi Absar U. Hassan Qi Zhong Stefan Rotter Patrick LiKamWa Demetrios N. Christodoulides Mercedeh Khajavlkhan Institutefor Theoretical Physics Vienna University of Technology (TU Wien) Vienna Austria Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los Angeles USA CREOL The College of Optics & Photonics University of Central Florida Orlando FL USA Center of Excellence for Telecomm Applications Joint Centers of Excellence Program King Abdul Aziz City for Science and Technology Riyadh Saudi Arabia Department of Physics & Astronomy University of Southern California Los Angeles CA USA

ISBN: (纸本)9798350345995

When non-Hermitian eigenvalue surfaces form intertwined Riemann surfaces, the corresponding non-Hermitian singularities, also know as exceptional points (EPs), are located at the center of this specific topology. Various experimental platforms have recently been presented in which interesting new physics associated with these branch point singularities can be explored. In particular, it has been shown that dynamically encircling EPs may lead to a so-called chiral state transfer. The chirality in this context refers to the fact that in such an encircling protocol, the final state at the end of an EP -enclosing loop solely depends on the encircling direction (clockwise or counterclockwise), but not on the initial state. Such a chiral behavior is intrinsically linked to the state vector deviating from adiabatically following the system's eigenstates associated with the eigenvalue surfaces; instead, due to the non-Hermitian violation of the adiabatic theorem, non-adiabatic jumps let the system undergo transitions from lossy eigenstates to eigenstates with gain. Here, we present two experiments that implement concepts that go beyond this established paradigm.

关键词： Attenuation Chirality Fiber lasers Lasers Surfaces Waveguides

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Clinical characteristics of hospitalized children with community-acquired pneumonia and respiratory infections: Using machine learning approaches to support pathogen prediction at admission

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Journal of microbiology, immunology, and infection = Wei mian yu gan ran za zhi 2023年第4期56卷 772-781页

作者： Tu-Hsuan Chang Yun-Chung Liu Siang-Rong Lin Pei-Hsin Chiu Chia-Ching Chou Luan-Yin Chang Fei-Pei Lai Department of Pediatrics Chi Mei Medical Center Tainan City Taiwan. Department of Pediatrics National Taiwan University Hospital College of Medicine National Taiwan University Taipei City Taiwan. Institute of Applied Mechanics National Taiwan University Taipei City Taiwan. Institute of Applied Mechanics National Taiwan University Taipei City Taiwan. Electronic address: ccchou@iam.ntu.edu.tw. Department of Pediatrics National Taiwan University Hospital College of Medicine National Taiwan University Taipei City Taiwan. Electronic address: lychang@ntu.edu.tw. Graduate Institute of Biomedical Electronics and Bioinformatics Taipei City National Taiwan University Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei City Taiwan Department of Electrical Engineering National Taiwan University Taipei City Taiwan.

BACKGROUND:Acute respiratory infections (ARIs) are common in children. We developed machine learning models to predict pediatric ARI pathogens at admission. METHODS:We included hospitalized children with respiratory infections between 2010 and 2018. Clinical features were collected within 24 h of admission to construct models. The outcome of interest was the prediction of 6 common respiratory pathogens, including adenovirus, influenza virus types A and B, parainfluenza virus (PIV), respiratory syncytial virus (RSV), and Mycoplasma pneumoniae (MP). Model performance was estimated using area under the receiver operating characteristic curve (AUROC). Feature importance was measured using Shapley Additive exPlanation (SHAP) values. RESULTS:A total of 12,694 admissions were included. Models trained with 9 features (age, event pattern, fever, C-reactive protein, white blood cell count, platelet count, lymphocyte ratio, peak temperature, peak heart rate) achieved the best performance (AUROC: MP 0.87, 95% CI 0.83-0.90; RSV 0.84, 95% CI 0.82-0.86; adenovirus 0.81, 95% CI 0.77-0.84; influenza A 0.77, 95% CI 0.73-0.80; influenza B 0.70, 95% CI 0.65-0.75; PIV 0.73, 95% CI 0.69-0.77). Age was the most important feature to predict MP, RSV and PIV infections. Event patterns were useful for influenza virus prediction, and C-reactive protein had the highest SHAP value for adenovirus infections. CONCLUSION:We demonstrate how artificial intelligence can assist clinicians identify potential pathogens associated with pediatric ARIs upon admission. Our models provide explainable results that could help optimize the use of diagnostic testing. Integrating our models into clinical workflows may lead to improved patient outcomes and reduce unnecessary medical costs.

关键词： Children Community-acquired pneumonia Machine learning Pathogens prediction Respiratory infections

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programmable threshold sensing in wireless devices using Ising dynamics

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Nature Electronics 2025年 1-8页

作者： Nicolas Casilli Hussein M. E. Hussein Ryan Tetro Luca Colombo Matteo Rinaldi Cristian Cassella Seunghwi Kim Andrea Alù Philip X.-L. Feng Institute for Nano Systems Innovation (NanoSI) Department of Electrical and Computer Engineering Northeastern University Boston MA USA Photonics Initiative Advanced Science Research Center City University of New York New York City NY USA Physics Program Graduate Center City University of New York New York City NY USA Department of Electrical and Computer Engineering University of Florida Gainesville FL USA

Ising machines—comprising dissipatively coupled nodes capable of emulating the behaviour of ferromagnetic spins—can form analogue computing engines that surpass the sequential processing constraints of von Neumann architectures. However, the incorporation of Ising dynamics into radio-frequency wireless technologies remains limited, especially in terms of their potential to enhance wireless sensing capabilities. Here we report a passive wireless sensor that uses Ising dynamics to accurately implement threshold sensing. The device correlates the occurrence of violations in a sensed parameter with transitions in the coupling state of two parametric oscillators acting as Ising spins. As a result, the accuracy of the device is unaffected by distortions in its input and output signals due to multipath and is less prone to clutter caused by co-site interference. We illustrate the potential of the approach in temperature threshold sensing using a microfabricated lithium niobate microelectromechanical temperature sensor to couple two radio-frequency parametric oscillators, and show that such a system allows the sensor threshold to be wirelessly reprogrammed.

关键词： Ising model

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A micromirror array with annular partitioning for high-speed random-access axial focusing

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Light(Science & Applications) 2020年第1期9卷 241-255页

作者： Nathan Tessema Ersumo Cem Yalcin Nick Antipa Nicolas Pegard Laura Waller Daniel Lopez Rikky Muller The University of California Berkeley and University of CaliforniaSan Francisco Graduate Program in BioengineeringBerkeleyCA 94720USA Department of Electrical Engineering&Computer Sciences University of CaliforniaBerkeleyCA 94720USA Department of Applied Physical Sciences University of North Carolina at Chapel HillChapel HillNC 27514USA Chan Zuckerberg Biohub San FranciscoCA 94158USA Physical Measurement Laboratory National Institute of Standards and TechnologyGaithersburgMD 20899USA

Dynamic axial focusing functionality has recently experienced widespread incorporation in microscopy,augmented/virtual reality(AR/VR),adaptive optics and material ***,the limitations of existing varifocal tools continue to beset the performance capabilities and operating overhead of the optical systems that mobilize such *** varifocal tools that are the least burdensome to operate(*** crystal,elastomeric or optofluidic lenses)suffer from low(≈100 Hz)refresh ***,the fastest devices sacrifice either critical capabilities such as their dwelling capacity(*** gradient lenses or monolithic micromechanical mirrors)or low operating overhead(*** mirrors).Here,we present a general-purpose random-access axial focusing device that bridges these previously conflicting features of high speed,dwelling capacity and lightweight drive by employing lowrigidity micromirrors that exploit the robustness of defocusing phase ***,the device consists of an 8.2mm diameter array of piston-motion and 48-μm-pitch micromirror pixels that provide 2πphase shifting for wavelengths shorter than 1100 nm with 10-90% settling in 64.8μs(i.e.,15.44 kHz refresh rate).The pixels are electrically partitioned into 32 rings for a driving scheme that enables phase-wrapped operation with circular symmetry and requires<30 V per *** experiments demonstrated the array’s wide focusing range with a measured ability to target 29 distinct resolvable depth ***,the features of the proposed array offer the potential for compact,straightforward methods of tackling bottlenecked applications,including high-throughput single-cell targeting in neurobiology and the delivery of dense 3D visual information in AR/VR.

关键词： mirror axial random

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A robust CNN framework with dual feedback feature accumulation for detecting pneumonia opacity from chest x-ray images

arXiv

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arXiv 2020年

作者： Alam, Md. Jahin Ali, Shams Nafisa Hasan, Md. Zubair Department of Electrical and Electronic Engineering Bangladesh University of Engineering and Technology Dhaka Bangladesh Department of Biomedical Engineering Bangladesh University of Engineering and Technology Dhaka Bangladesh Department of Computer Science and Engineering Military Institute of Science and Technology Dhaka Bangladesh

Pneumonia is one of the most acute respiratory diseases having remarkably high prevalence and mortality rate. Chest X-ray (CXR) has been widely utilized for the diagnosis of this disease owing to its availability, diagnostic speed and accuracy. However, even for an expert radiologist, it is quite challenging to readily determine pneumonia opacity by examining CXRs. Therefore, this study has been structured to automate the pneumonia detection process by introducing a robust deep learning framework. The proposed network comprises of Process Convolution (Pro_Conv) blocks for feature accumulation inside Dual Feedback (DF) blocks to propagate the feature maps towards a viable detection. Experimental analysis showcase: (1) the proposed network proficiently distinguishes between normal and pneumonia opacity containing CXRs with the mean accuracy, sensitivity and specificity of 97.78%, 98.84% and 95.04%, respectively;(2) the network is constructed with significantly low parameters than the traditional ImageNets to reduce memory consumption for deployment in memory constrained mobile platforms;(3) the trade-off between accuracy and number of parameters of the model outperforms the considered classical networks by a remarkable margin;and (4) the false-negatives are lower than the false-positives (both of which are low in count) which prove the model's low-fatality prediction. Hence, the proposed network can be deployed for a rapid screening of pneumonia and can act as a great assistive tool for the radiologists in the diagnosis process. Copyright © 2020, The Authors. All rights reserved.

关键词： computer aided diagnosis

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Graphene calorimetric single-photon detector

arXiv

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arXiv 2024年

作者： Huang, Bevin Arnault, Ethan G. Jung, Woochan Fried, Caleb Russell, B. Jordan Watanabe, Kenji Taniguchi, Takashi Henriksen, Erik A. Englund, Dirk Lee, Gil-Ho Fong, Kin Chung Intelligence Community Postdoctoral Research Fellowship Program Massachusetts Institute of Technology CambridgeMA02139 United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Department of Physics Pohang University of Science and Technology Pohang790-784 Korea Republic of Department of Physics Washington University in St. Louis St. LouisMO United States Research Center for Electronic and Optical Materials National Institute for Materials Science 1-1 Namiki Tsukuba305-0044 Japan Research Center for Materials Nanoarchitectonics National Institute for Materials Science 1-1 Namiki Tsukuba305-0044 Japan RTX BBN Technologies Quantum Engineering and Computing Group CambridgeMA02138 United States

Single photon detectors (SPDs) [1, 2] are essential technology in quantum science, quantum network, biology, and advanced imaging [3-5]. To detect the small quantum of energy carried in a photon, conventional SPDs rely on energy excitation across either a semiconductor bandgap or superconducting gap. While the energy gap suppresses the false-positive error, it also sets an energy scale that can limit the detection efficiency of lower energy photons and spectral bandwidth of the SPD [6-8]. Here, we demonstrate an orthogonal approach to detect single near-infrared photons using graphene calorimeters [9-13]. By exploiting the extremely low heat capacity of the pseudo-relativistic electrons in graphene near its charge neutrality point [14], we observe an electron temperature rise up to ∼2 K using a hybrid Josephson junction. In this proof-of-principle experiment, we achieve an intrinsic quantum efficiency of 87% (75%) with dark count © 2024, CC BY.

关键词： Particle beams

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