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SSRN 2024年

作者： Ojo, Solomon Onasanya, Juwon Benamara, Mourad Hamad, Bothina Manasreh, M.O. Material Science and Engineering program University of Arkansas FayettevilleAR72701 United States Institute of nanotechnology University of Arkansas FayettevilleAR72701 United States Physics Department University of Arkansas FayettevilleAR72701 United States Department of Electrical Engineering and Computer Science University of Arkansas FayettevilleAR72701 United States

Monolayers of ReS2 were grown by a chemical vapor deposition technique on SiO2/Si substrates and investigated at room temperature by using μ-Raman, μ-photoluminescence (PL) and absorbance spectroscopies. The Raman scattering spectrum exhibits several phonon modes that were confirmed by the computation analysis based on the density functional theory. The ReS2 structural integrity was confirmed by using the XRD and the energy dispersion spectroscopy that was obtained by the scanning electron microscopy. Photoluminescence spectra show excitons related to interband transition in thin monolayer flakes and bulk-like structures. Additionally, a sharp PL line located at 1.2620 eV with a second harmonic peak at 2.5420 eV was observed and explained in terms of interband excitonic transitions originating within the rhenium 5d orbit. An optical absorbance spectrum with an exciton peak around 1.4660 eV was obtained for an assembly of ReS2 flakes grown on silica substrate. © 2024, The Authors. All rights reserved.

关键词： Phonons

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Road-Width-Aware Network Optimisation for Bike Lane Planning

arXiv

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arXiv 2025年

作者： Basilone, Riccardo Bruno, Matteo Melo, Hygor Piaget Monteiro Avalle, Michele Loreto, Vittorio Sapienza Univ. of Rome Physics Dept Piazzale A. Moro 2 Rome00185 Italy Sony Computer Science Laboratories - Rome Joint Initiative CREF-SONY Centro Ricerche Enrico Fermi Via Panisperna 89/A Rome00184 Italy Via Panisperna 89/A Rome00184 Italy Postgraduate Program in Applied Informatics University of Fortaleza Ceará Fortaleza60811-905 Brazil Complexity Science Hub Josefstädter Strasse 39 ViennaA 1080 Austria

Active mobility is becoming an essential component of the green transition in modern cities. However, the challenge of designing an efficient network of protected bike lanes without disrupting existing road networks for motorised vehicles remains unsolved. This paper focuses on the specific case of Milan, using a network approach that considers street widths to optimise the placement of dedicated bike lanes at the edges of the network. Unlike other network approaches in this field, our method considers the actual shapes of the streets, which introduces a realistic aspect lacking in current studies. We used these data to simulate cycling networks that maximise connectivity while minimising the impact of bike lane placement on the drivable network. Our mixed simulation strategies optimise for edge betweenness and width. Furthermore, we quantify the impact of dedicated bike lane infrastructure on the existing road network, demonstrating that it is feasible to create highly effective cycling networks with minimal disruption caused by lane width reductions. This paper illustrates how realistic cycling lanes can be simulated using road width data and discusses the challenges and benefits of moving beyond one-dimensional road data in network studies. Copyright © 2025, The Authors. All rights reserved.

关键词： Bicycles

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Non-Hermitian metasurface for asymmetric thermal emission

Non-Hermitian metasurface for asymmetric thermal emission

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Conference on Lasers and Electro-Optics (CLEO)

作者： Ciril S. Prasad Henry O. Everitt Gururaj V. Naik Department of Electrical and Computer Engineering Rice University Houston TX USA Applied Physics Graduate Program Smalley-Curl Institute Rice University Houston TX USA U.S. Army DEVCOM Army Research Laboratory-South Houston TX USA

Non-Hermitian optics provides a unique platform to take advantage of absorption losses in materials and control radiative properties. We demonstrate a non-Hermitian metasurface that exhibit directional suppression of ... 详细信息

ISBN: (纸本)9781957171258

关键词： Fused silica Optical constants Photon counting Remote sensing Thermal emission Thermal imaging

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Velocity-gauge Real-time Time-dependent Density Functional Tight-binding for Large-scale Condensed Matter Systems

arXiv

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arXiv 2023年

作者： Xu, Qiang Del Ben, Mauro Okyay, Mahmut Sait Choi, Min Ibrahim, Khaled Z. Wong, Bryan M. Materials Science & Engineering Program Department of Chemistry Department of Physics & Astronomy University of California-Riverside RiversideCA92521 United States Applied Mathematics & Computational Research Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States

We present a new velocity-gauge real-time, time-dependent density functional tight-binding (VG-rtTDDFTB) implementation in the open-source DFTB+ software package (https://***) for probing electronic excitations in large, condensed matter systems. Our VG-rtTDDFTB approach enables real-time electron dynamics simulations of large, periodic, condensed matter systems containing thousands of atoms with a favorable computational scaling as a function of system size. We provide computational details and benchmark calculations to demonstrate its accuracy and computational parallelizability on a variety of large material systems. As a representative example, we calculate laser-induced electron dynamics in a 512-atom amorphous silicon supercell to highlight the large periodic systems that can be examined with our implementation. Taken together, our VG-rtTDDFTB approach enables new electron dynamics simulations of complex systems that require large periodic supercells, such as crystal defects, complex surfaces, nanowires, and amorphous materials. Copyright © 2023, The Authors. All rights reserved.

关键词： Gages

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The total phenolic and flavonoid contents of Aloe vera and Morinda citrifolia extracts as antibacterial material against Pseudomonas aeruginosa

The total phenolic and flavonoid contents of Aloe vera and M...

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作者： Royani, Ahmad Hanafi, Muhammad Julistiono, Heddy Manaf, Azwar Postgraduate Program of Materials Science Study Department of Physics Faculty of Mathematics and Natural Sciences Universitas Indonesia Depok16424 Indonesia Research Center for Metallurgy National Research and Innovation Agency Puspiptek Area Tangerang Selatan15314 Indonesia Research Center for Raw Material of Medicine and Traditional Medicine National Research and Innovation Agency Puspiptek Area Tangerang Selatan15314 Indonesia Research Center for Applied Microbiology National Research and Innovation Agency Jl. Raya Bogor Km. 46 Cibinong Science Center Cibinong16911 Indonesia

Pseudomonas aeruginosa is a pioneer bacterium initiating the biofilm formation process so that it is corrosive to some metals in the marine environment. One of the efforts to prevent and control corrosion due to environmentally friendly biofilms is using green biocides. The extraction of Aloe vera and Morinda citrifolia with methanol were carried out to obtain antibacterial material. The extract of those plants with multilevel maceration method. The study aimed to identify the total phenolic and flavonoid contents in A. vera and M. citrifolia crude extracts and compare the two antibacterial extract activities. The total phenolic and flavonoid contents were analyzed using the Folin-Ciocalteu and the aluminum chloride colorimetric methods. The antibacterial activity against P. aeruginosa was conducted using the microdilution method to determine the minimum inhibitory concentration (MIC). The structure of the bioactive components of both A. vera and M. citrifolia extracts were identified using a liquid chromatography-mass spectrometer (LC/MS-MS). The MIC of A. vera and M. citrifolia for P. aeruginosa bacteria is about 6144 µg/mL, while the MIC of antibiotic Enrofloxacin is 16 µg/mL. The mean of total phenolic and flavonoid contents for the methanolic extracts of A. vera and M. citrifolia were 1.39% and 4.03% (phenolic), and 0.26% and 0.28% (flavonoids), respectively. The chemical structure of A. vera consists of 2″-O-Feruloylaloesin, Kaempferol-3-O-rutinoside, and Natsudaidain. At the same time, the chemical structure of M. citrifolia consists of 7-Hydroxy-Methoxycoumarin and Cirsiumaldehyde. A. vera and M. citrifolia crude extracts had lower inhibition than antibacterial control (Enrofloxacin) for P. aeruginosa. The lower bacteria inhibition was due to the low active materials (phenolic and flavonoid contents). So, the purification methods of crude extracts to obtain active materials with high antibacterial activity were needed. © 2022

关键词： Bacteria

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Structural properties of hyperuniform Voronoi networks

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Physical Review E 2025年第3期111卷 034123-034123页

作者： Eli Newby Wenlong Shi Yang Jiao Reka Albert Salvatore Torquato Department of Physics Pennsylvania State University University Park Pennsylvania 16802 USA Materials Science and Engineering Arizona State University Tempe Arizona 85287 USA Department of Physics Arizona State University Tempe Arizona 85287 USA Department of Chemistry Princeton University Princeton New Jersey 08544 USA Department of Physics Princeton University Princeton New Jersey 08544 USA Princeton Institute of Materials Princeton University Princeton New Jersey 08544 USA Program in Applied and Computational Mathematics Princeton University Princeton New Jersey 08544 USA

Disordered hyperuniform many-particle systems are recently discovered exotic states of matter, characterized by the complete suppression of normalized infinite-wavelength density fluctuations, as in perfect crystals, while lacking conventional long-range order, as in liquids and glasses. In this work, we begin a program to quantify the structural properties of nonhyperuniform and hyperuniform networks. In particular, large two-dimensional (2D) Voronoi networks (graphs) containing approximately 10,000 nodes are created from a variety of different point configurations, including the antihyperuniform hyperplane intersection process (HIP), nonhyperuniform Poisson process, nonhyperuniform random sequential addition (RSA) saturated packing, and both non-stealthy and stealthy hyperuniform point processes. We carry out an extensive study of the Voronoi-cell area distribution of each of the networks by determining multiple metrics that characterize the distribution, including their average areas and corresponding variances as well as higher-order cumulants (i.e., skewness γ1 and excess kurtosis γ2). We show that the HIP distribution is far from Gaussian, as evidenced by a high skewness (γ1=3.16) and large positive excess kurtosis (γ2=16.2). The Poisson (with γ1=1.07 and γ2=1.79) and non-stealthy hyperuniform (with γ1=0.257 and γ2=0.0217) distributions are Gaussian-like distributions, since they exhibit a small but positive skewness and excess kurtosis. The RSA (with γ1=0.450 and γ2=−0.0384) and the highest stealthy hyperuniform distributions (with γ1=0.0272 and γ2=−0.0626) are also non-Gaussian because of their low skewness and negative excess kurtosis, which is diametrically opposite of the non-Gaussian behavior of the HIP. The fact that the cell-area distributions of large, finite-sized RSA and stealthy hyperuniform networks (e.g., with N≈10,000 nodes) are narrower, have larger peaks, and smaller tails than a Gaussian distribution implies that in the thermodynamic limit th

关键词： Gaussian distribution

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Detection and Recognition of Vehicle Components Using Image Processing and Deep Learning Techniques

Detection and Recognition of Vehicle Components Using Image ...

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Research, Invention, and Innovation Congress (RI2C)

作者： Mahasak Ketcham Thittaporn Ganokratanaa Patiyuth Pramkeaw Phumraphi Boonthai Narumol Chumuang Department of Information Technology Management King Mongkut's University of Technology North Bangkok Bangkok Thailand Applied Computer Science Program King Mongkut's University of Technology Thonburi Bangkok Thailand Media Technology Program King Mongkut's University of Technology Thonburi Bangkok Thailand Department Media Technology Muban Chombueng Rajabhat University Ratchaburi Thailand

This research study presents an algorithmic approach for the detection and identification of key components on license plates, including numerical digits, province codes, vehicle colors, and vehicle makes and types. The methodology integrates image processing techniques and deep learning methodologies to achieve comprehensive image analysis. The algorithm incorporates image preprocessing techniques to optimize the input images, followed by a deep neural network trained on a large annotated dataset. The algorithm utilizes image segmentation and character recognition techniques to detect and classify numerical digits on license plates. Similarly, it employs segmentation and classification processes for identifying province codes, vehicle colors, makes, and types. Extensive training ensures the algorithm's accuracy and robustness under varying conditions. The proposed algorithm demonstrates the potential for accurate license plate component detection and identification, with applications in law enforcement and traffic monitoring systems.

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Dermatological Diagnostics: A Unified Deep Learning Framework for Skin Lesion and Cancer Classification

Dermatological Diagnostics: A Unified Deep Learning Framewor...

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Advances in Computing, Communication and Networking (ICAC2N), International Conference on

作者： Vinod Kumar Isha Jain Durga Sritha Dongla Shivangi Rai Vani Rastogi Eva Kaushik Rohit Kaushik School of Engineering & Applied Science The George Washington University Washington D.C USA Computer Science & Engineering Department Dr. Akhilesh Das Gupta Institute of Technology and Management New Delhi India Computer Science & Engineering Department Gandhi Institute of Technology and Management Visakhapatnam Andhra Pradesh Data Scientist DXC Technology Noida India CS and Mathematics Department Data Analytics Program University of Illinois Springfield USA

ISBN: (数字)9798350356816

ISBN: (纸本)9798350356823

Skin pathologies encompass a spectrum of conditions, with malignancies such as melanoma representing a critical diagnostic urgency. This investigation delineates the deployment of Convolutional Neural Networks (CNNs) for the classification of dermatological anomalies, benchmarking CNN diagnostic fidelity against dermatological expert evaluations. The study underscores the efficacy of CNN classifiers in expediting the diagnostic workflow for various cutaneous disorders. Advocating for an automated diagnostic framework, the research introduces a CNN-based system aimed at reducing human diagnostic load, accelerating diagnostic timelines, and enhancing survival outcomes. Utilizing advanced image processing algorithms and deep learning architectures, the research presents an automated classification system for skin pathologies, addressing both benign and malignant presentations. The classification matrix includes nine dermatological conditions: actinic keratosis, basal cell carcinoma, benign keratosis, dermatofibroma, melanoma, nevus, seborrheic keratosis, squamous cell carcinoma, and vascular lesions. The objective is to engineer a CNN model with robust diagnostic performance across a diverse lesion dataset, ensuring accurate identification and categorization of dermatological conditions.

关键词： Deep learning Pathology Accuracy Melanoma computer architecture Benchmark testing Skin Convolutional neural networks Lesions Medical diagnosis

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Understanding degeneracy of two-point correlation functions via Debye random media

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Physical Review E 2021年第4期104卷 045306-045306页

作者： Murray Skolnick Salvatore Torquato Department of Chemistry Department of Physics Princeton Institute for the Science and Technology of Materials and Program in Applied and Computational Mathematics Princeton University Princeton New Jersey 08544 USA

It is well known that the degeneracy of two-phase microstructures with the same volume fraction and two-point correlation function S2(r) is generally infinite. To elucidate the degeneracy problem explicitly, we examine Debye random media, which are entirely defined by a purely exponentially decaying two-point correlation function S2(r). In this work, we consider three different classes of Debye random media. First, we generate the “most probable” class using the Yeong-Torquato construction algorithm [Yeong and Torquato, Phys. Rev. E 57, 495 (1998)]. A second class of Debye random media is obtained by demonstrating that the corresponding two-point correlation functions are effectively realized in the first three space dimensions by certain models of overlapping, polydisperse spheres. A third class is obtained by using the Yeong-Torquato algorithm to construct Debye random media that are constrained to have an unusual prescribed pore-size probability density function. We structurally discriminate these three classes of Debye random media from one another by ascertaining their other statistical descriptors, including the pore-size, surface correlation, chord-length probability density, and lineal-path functions. We also compare and contrast the percolation thresholds as well as the diffusion and fluid transport properties of these degenerate Debye random media. We find that these three classes of Debye random media are generally distinguished by the aforementioned descriptors, and their microstructures are also visually distinct from one another. Our work further confirms the well-known fact that scattering information is insufficient to determine the effective physical properties of two-phase media. Additionally, our findings demonstrate the importance of the other two-point descriptors considered here in the design of materials with a spectrum of physical properties.

关键词： Complex systems

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Effect of Periodic Poling on Self-phase Modulation in Thin-film Lithium Niobate Waveguides

Effect of Periodic Poling on Self-phase Modulation in Thin-f...

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Frontiers in Optics, FiO 2022

作者： Gül, Gamze Abdelsalam, Kamal Fathpour, Sasan Lee, Kim F. Kanter, Gregory S. Kumar, Prem Graduate Program in Applied Physics Northwestern University 2145 Sheridan Road EvanstonIL60208 United States CREOL The College of Optics and Photonics University of Central Florida OrlandoFL32816 United States Department of Electrical and Computer Engineering University of Central Florida OrlandoFL32816 United States Center for Photonic Communication and Computing Dept. of Electrical and Computer Eng. Northwestern University EvanstonIL60208 United States

We study self-phase modulation of sub-picosecond telecom wavelength pulses in partially periodically poled thin-film lithium niobate waveguides. We experimentally and computationally investigate the effect of phase mi... 详细信息

ISBN: (纸本)9781557528209

关键词： Thin films

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