jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Özgür Yılmazel | Dilara ÖZTÜRK | Hercan YAVUZTÜRK | Halit Kaan CAN | Emre KAÇMAZ | Gamze Karanfil Kaçmaz
Source: Düzce Üniversitesi Bilim ve Teknoloji Dergisi (article, 2023-12-27)
Field: Materials Science — Biomaterials

Measuring the Thickness of Fiber Mats Using Light Transmittance via Image Processing Fiber materials possess unique properties, including a large active surface area, high surface-to-volume ratio, high porosity, high mechanical performance, and low density. Consequently, they serve as key components in various applications such as energy production and storage cells, batteries, wastewater treatment membranes, sensors, drug-releasing band-aids, and protective clothing. Electrospinning is a simple and versatile method for producing fiber materials. Despite its simplicity in terms of working principles, it faces challenges in achieving homogeneous thickness (evenly on the entire surface) throughout fiber mats due to inherent bending instability during the process. Non-uniform thickness not only diminishes the efficiency of these mats in applications but also adversely impacts their mechanical functionality. In this study, the aim is to develop a thickness measurement system based on image processing and the principle of light transmittance as a solution to the issues encountered in achieving uniform thickness and thickness control of fiber mats produced by electrospinning devices. To accomplish this, a closed mechanism with a light-impermeable encapsulation method was established. Various fiber mats, produced at different times were placed on the acetate floor built on LED lighting on the base of the mechanism. Using a camera with the adjusted settings positioned at the focal point on top of the mechanism, images of the fiber mats were captured, and image processing techniques were employed to determine threshold value ranges for the mat thicknesses. The actual thicknesses of the fiber mats were verified using an optical microscope, revealing that regions defined with the same color in different samples exhibited similar thicknesses. Materials science ; Electrospinning ; Transmittance ; Composite material ; Microfiber ; Optical fiber ; Fiber ; Porosity ; Optics ; Optoelectronics ; Polymer Electrospun Nanofibers in Biomedical Applications ; Textile materials and evaluations ; Aerosol Filtration and Electrostatic Precipitation
Authors: Tommaso Magrini | Chelsea Fox | Adeline Wihardja | Athena Kolli | Chiara Daraio
Source: arXiv (Cornell University) (preprint, 2023-09-05)
Field: Materials Science — Polymers and Plastics

Control of Mechanical and Fracture Properties in Two-phase Materials Reinforced by Continuous, Irregular Networks Composites with high strength and high fracture resistance are desirable for structural and protective applications. Most composites, however, suffer from poor damage tolerance and are prone to unpredictable fractures. Understanding the behavior of materials with an irregular reinforcement phase offers fundamental guidelines for tailoring their performance. Here, we study the fracture nucleation and propagation in two phase composites, as a function of the topology of their irregular microstructures. We use a stochastic algorithm to design the polymeric reinforcing network, achieving independent control of topology and geometry of the microstructure. By tuning the local connectivity of isodense tiles and their assembly into larger structures, we tailor the mechanical and fracture properties of the architected composites, at the local and global scale. Finally, combining different reinforcing networks into a spatially determined meso-scale assembly, we demonstrate how the spatial propagation of fractures in architected composite materials can be designed and controlled a priori. Materials science ; Fracture (geology) ; Composite material ; Microstructure ; Phase (matter) ; Nucleation ; Topology (electrical circuits) ; Composite number ; Fracture mechanics ; Computer science ; Structural engineering ; Mathematics ; Engineering Polymer composites and self-healing ; Advanced Polymer Synthesis and Characterization ; Polymer crystallization and properties
Authors: Fucheng Zhong | N. R. Napolitano | Caroline Heneka | Rui Li | F. E. Bauer | N. Bouché | Johan Comparat | Young-Lo Kim | Jens-Kristian Krogager | M. Longhetti | J. Loveday | Boudewijn F. Roukema | Benedict L. Rouse | M. Salvato | C. Tortora | Roberto J. Assef | L. P. Cassará | Luca Costantin | S. M. Croom | L. J. M. Davies | Alexander Fritz | G. Guiglion | A. Humphrey | E. Pompei | Cláudio Ricci | Cristobál Sifón | Elmo Tempel | Tayyaba Zafar
Source: arXiv (Cornell University) (preprint, 2023-11-07)
Field: Chemistry — Analytical Chemistry

Galaxy Spectra neural Network (GaSNet). II. Using Deep Learning for Spectral Classification and Redshift Predictions Large sky spectroscopic surveys have reached the scale of photometric surveys in terms of sample sizes and data complexity. These huge datasets require efficient, accurate, and flexible automated tools for data analysis and science exploitation. We present the Galaxy Spectra Network/GaSNet-II, a supervised multi-network deep learning tool for spectra classification and redshift prediction. GaSNet-II can be trained to identify a customized number of classes and optimize the redshift predictions for classified objects in each of them. It also provides redshift errors, using a network-of-networks that reproduces a Monte Carlo test on each spectrum, by randomizing their weight initialization. As a demonstration of the capability of the deep learning pipeline, we use 260k Sloan Digital Sky Survey spectra from Data Release 16, separated into 13 classes including 140k galactic, and 120k extragalactic objects. GaSNet-II achieves 92.4% average classification accuracy over the 13 classes (larger than 90% for the majority of them), and an average redshift error of approximately 0.23% for galaxies and 2.1% for quasars. We further train/test the same pipeline to classify spectra and predict redshifts for a sample of 200k 4MOST mock spectra and 21k publicly released DESI spectra. On 4MOST mock data, we reach 93.4% accuracy in 10-class classification and an average redshift error of 0.55% for galaxies and 0.3% for active galactic nuclei. On DESI data, we reach 96% accuracy in (star/galaxy/quasar only) classification and an average redshift error of 2.8% for galaxies and 4.8% for quasars, despite the small sample size available. GaSNet-II can process ~40k spectra in less than one minute, on a normal Desktop GPU. This makes the pipeline particularly suitable for real-time analyses of Stage-IV survey observations and an ideal tool for feedback loops aimed at night-by-night survey strategy optimization. Redshift ; Galaxy ; Astrophysics ; Physics ; Sky ; Active galactic nucleus ; Quasar ; Spectral line ; Pipeline (software) ; Artificial neural network ; Artificial intelligence ; Computer science ; Astronomy Spectroscopy and Chemometric Analyses ; CCD and CMOS Imaging Sensors ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Shanshan Wang | Jiaqi Liu | Fan Li | Hua Zhang
Source: Applied Mathematics and Nonlinear Sciences (article, 2023-10-24)
Field: Materials Science — Polymers and Plastics

Learning curve improvement model for sportswear comfort and sports functionality analysis Abstract In this paper, a performance optimization model for sportswear based on the learning curve effect is proposed on the learning curve base model, which is a systematic method for improving and optimizing sportswear’s comfort performance and sports functionality compared with the traditional model. Laplace’s law measurement method is used to predict the garment comfort pressure in terms of comfort measurement. The finite element method was used to analyze the sports apparel’s functionality. The results show that the most obvious deformation under the pressure of sportswear occurs in the middle section of the inner thigh, with a maximum value of 1.786E-002mm and a mean square error of 3.0875×10 −14 .The research findings of this paper can serve as a reference for sportswear designers and manufacturers and encourage the development and innovation of the sportswear industry. Clothing ; Finite element method ; Clothing industry ; Engineering ; Computer science ; Simulation ; Engineering drawing ; Industrial engineering ; Structural engineering Textile materials and evaluations ; Thermoregulation and physiological responses ; Ergonomics and Musculoskeletal Disorders
Authors: Chenglong Jia | Penghao Chu | Wenbin Zhao | Zhong Tang
Source: IET Generation Transmission & Distribution (article, 2023-11-28)
Field: Materials Science — Materials Chemistry

Characterization of internal discharge shock waves of gas‐insulated switchgears using shadowgraphy Abstract The gas‐insulated switchgear (GIS) is a vital component of a power system, and understanding the shock wave characteristics of its internal discharge is crucial to ensure the safe and stable operation of the entire system. In this study, a high‐speed shadowing technique is employed to obtain the shadowgraphs of a typical flow‐field evolution of sulfur hexafluoride (SF 6 ) gas following the breakdown of a pin–plate gap inside a GIS. Experimental data were used to derive parameters, including the Mach number, propagation speed, distance of the discharge shock wave, and the temperature, pressure, density, and velocity of the SF 6 gas after wave generation. With a 0.2‐mm discharge gap and 0.4‐MPa pressure, the discharge generates a spherical shock wave, centred at the contact between the discharge channel and electrodes, that propagates in all directions. The shock wave gradually weakens after 20 μs, propagating at near‐sonic speed, and its Mach number decreases from 2.92 to 1.15; similarly, its post‐wave parameters sharply decrease during the first 20 μs. Additionally, a significant reflection occurs when the shock wave propagates to the metal wall. The authors’ findings provide a valuable reference for detecting and diagnosing the internal discharge in GISs. Switchgear ; Shock wave ; Sulfur hexafluoride ; Mach number ; Mechanics ; Shock (circulatory) ; Acoustics ; Shock diamond ; Mach wave ; Moving shock ; Materials science ; Oblique shock ; Shadowgraphy ; Optics ; Electrical engineering ; Physics ; Engineering High voltage insulation and dielectric phenomena ; Lightning and Electromagnetic Phenomena ; Power Transformer Diagnostics and Insulation
Authors: Raşit Fikret Yılmaz | Sultan Erkan | Salih Ökten | Ahmet Tutar | Ertan Şahi̇n
Source: TURKISH JOURNAL OF CHEMISTRY (article, 2023-12-29)
Field: Chemistry — Organic Chemistry

Bromination and conversion of tetrahydro-1H-indene to bisoxirane with a new approach: synthesis, structural characterization by spectroscopic and theoretical methods, and biological analysis supported by DFT and docking In this study, a new method for synthesizing diepoxides is proposed. Tetrahydroindene <b>1</b> was brominated with NBS in the presence of LiClO<sub>4</sub> and acetic acid, resulting in the formation of dibromodiacetate derivatives <b>2</b> and <b>3</b>. Treatment of compounds <b>2</b> and <b>3</b> with NaOH in methanol produced a mixture of diepoxides <b>4</b> and <b>5</b>. Additionally, direct bromination of tetrahydro-1H-indene yielded tetrabromo octahydroindene isomers <b>6</b> and <b>7</b>. The structures of the compounds were characterized using spectroscopic techniques such as <sup>1</sup>H NMR, <sup>13</sup>C NMR, APT, COSY, and XRD. The new method provides an easy and selective route to access epoxides for the synthesis of various chemicals. This study also highlights the selective formation of endo-exo and exo-exo orientations of the obtained diepoxides, distinguishing it from previous studies. The stability and properties of the stereoisomers were investigated using computational methods, revealing the most stable configurations. Reactive sites in the molecules were identified using contour diagrams and molecular electrostatic potential maps. The anticancer properties of the compounds were evaluated in silico, comparing them to 5-fluorouracil (5-FU) against several cancer cell lines. The compounds exhibited the most effective anticancer activity against MCF-7 cells, with the order of anticancer activities generally determined as <b>2</b> > <b>7</b> > <b>3</b> > <b>6</b> > <b>5</b> > <b>4</b> > 5-FU. Chemistry ; Halogenation ; Indene ; Docking (animal) ; Computational chemistry ; Combinatorial chemistry ; Characterization (materials science) ; Organic chemistry ; Nanotechnology Chemical Reaction Mechanisms ; Organic Chemistry Cycloaddition Reactions ; Free Radicals and Antioxidants
Authors: Chentian | Huruizhi | Liuyuting | Zouyang
Source: Applied Mathematics and Nonlinear Sciences (article, 2023-11-29)
Field: Materials Science — Materials Chemistry

Partial Discharge Detection Technology for GIS Insulation Defects under Complex Electromagnetic Environment Abstract This paper first introduces the main types of GIS insulation defects and explores the discharge mechanism of GIS insulation. Then, the space of discharge features of GIS insulation defects in a complex electromagnetic environment is constructed, and the feature dimensionality reduction is carried out by using principal component analysis. Then, the support vector machine algorithm is explored and optimized with the immune algorithm to identify and detect the local features of insulation defects. Finally, the local discharge characteristics of GIS insulation defects are investigated through simulation experiments, and the discharge results are analyzed. The results show that the average peak-to-peak value is around 31mV and the power distribution band is 133~168MHZ for the spiky insulation defects, the average peak-to-peak value is around 19.8mV and the power distribution band is around 202MHZ for the metallic particles insulation, and the peak value of the air gap is less than 8mV and more than 48mV for some, and the power distribution band is 98MHZ~146MHZ. The localized discharge characteristics of the defects of the GIS insulation parts are identified and detected by the immune optimization of the support vector machine algorithm. The overall recognition rate of immunodeficient partial discharges of insulating parts is around 0.90. This study is able to detect the type of partial discharges in GIS insulating parts well. Partial discharge ; Power (physics) ; Materials science ; Dimensionality reduction ; Principal component analysis ; Computer science ; Curse of dimensionality ; Acoustics ; Electrical engineering ; Artificial intelligence ; Engineering ; Physics ; Voltage High voltage insulation and dielectric phenomena
Authors: Shimeng Guo | Jinwei Gan
Source: Highlights in Science Engineering and Technology (article, 2023-03-29)
Field: Chemistry — Analytical Chemistry

Research on Glass Classification and Recognition based on Support Vector Machines Glass artefacts undergo weathering and a significant exchange of internal elements due to burial in the ground. In order to classify the glass types, Principal Component Analysis was used to transform the existing chemical indicators into a small number of principal components. Subsequently, Support Vector Machine approach was used to classify the glass types to be predicted based on the selected principal components. K-means clustering algorithm was then used to classify the two glass types into subclasses on the basis of the selected chemical components and to perform sensitivity analysis. Using this model, the glass types of the samples to be tested can be identified. Principal component analysis ; Pattern recognition (psychology) ; Support vector machine ; Cluster analysis ; Artificial intelligence ; Basis (linear algebra) ; Principal (computer security) ; Computer science ; Biological system ; Mathematics ; Biology Spectroscopy and Chemometric Analyses ; Remote-Sensing Image Classification ; Industrial Vision Systems and Defect Detection
Authors: Y. Yang | Ning Li | Xiaolong Huang | Yang Kang | Can Li | Xudong Fan | Chunsheng Weng
Source: AIP Advances (article, 2023-11-01)
Field: Chemistry — Spectroscopy

Simultaneous multi-parameter analysis of detonation field based on line fitting of wavelength modulated second harmonic signals In the wavelength modulation method of laser absorption spectroscopy, the second harmonic signal contains numerous information about the flow field parameters. The fitting of the second harmonic line allows us to accurately obtain some of the important parameters in the flow field. In this paper, the second harmonic signal of the absorbed laser signal is obtained by simulation for the temperature, pressure, and gas concentration in the detonation field. A particle swarm optimization algorithm is then applied to obtain the optimal parameter solution for fitting the line, thus implementing an algorithm for the simultaneous analysis of multiple parameters using the second harmonic signal. When the appropriate modulation depth and parameters of the particle swarm optimization algorithm were selected, the relative error of fitting results for temperature and pressure were within 4.94% and 9.34%. This algorithm can be used to synchronize the measurement of temperature and pressure in the presence of large variations in the modulation index. Harmonic ; SIGNAL (programming language) ; Modulation (music) ; Particle swarm optimization ; Harmonic analysis ; Detonation ; Modulation index ; Optics ; Laser ; Frequency modulation ; Approximation error ; Line (geometry) ; Wavelength ; Field (mathematics) ; Physics ; Computational physics ; Algorithm ; Materials science ; Acoustics ; Mathematics ; Chemistry ; Computer science ; Mathematical analysis ; Radio frequency ; Voltage ; Pulse-width modulation Spectroscopy and Laser Applications ; Laser Design and Applications ; Atmospheric and Environmental Gas Dynamics
Authors: Daniele Carosi | Fabiana Zama | Alessandro Morri | Lorella Ceschini
Source: arXiv (Cornell University) (preprint, 2023-08-28)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Linearizing Anhysteretic Magnetization Curves: A Novel Algorithm for Finding Simulation Parameters and Magnetic Moments This paper proposes a new method for determining the simulation parameters of the Jiles-Atherton Model used to simulate the first magnetization curve and hysteresis loop in ferromagnetic materials. The Jiles-Atherton Model is an important tool in engineering applications due to its relatively simple differential formulation. However, determining the simulation parameters for the anhysteretic curve is challenging. Several methods have been proposed, primarily based on mathematical aspects of the anhysteretic and first magnetization curves and hysteresis loops. This paper focuses on finding the magnetic moments of the material, which are used to define the simulation parameters for its anhysteretic curve. The proposed method involves using the susceptibility of the material and a linear approximation of a paramagnet to find the magnetic moments. The simulation parameters can then be found based on the magnetic moments. The method is validated theoretically and experimentally and offers a more physical approach to finding simulation parameters for the anhysteretic curve and a simplified way of determining the magnetic moments of the material. Magnetization ; Hysteresis ; Magnetic hysteresis ; Magnetic moment ; Ferromagnetism ; Paramagnetism ; Algorithm ; Computer science ; Physics ; Mathematical analysis ; Mathematics ; Condensed matter physics ; Magnetic field Magnetic Properties and Applications ; Electric Motor Design and Analysis ; Magnetic properties of thin films
Authors: Arief Syarifuddin | Erdina Arianti | Kusnindar Priohutomo | Rosi Dwi Yulfani | Berlian Arswendo Adietya | Aurista Miftahatul Ilmah | Taufan Prasetyo
Source: Kapal Jurnal Ilmu Pengetahuan dan Teknologi Kelautan (article, 2023-02-24)
Field: Materials Science — Materials Chemistry

Comparative Study of Welding Material Elasticity with the SMAW Process for 2G Positions Between Before and After Using Welding Machines with Augmented Reality Technology The high cost of certification and the low pass percentage in welding certification are common issues for beginner welders. The use of Augmented Reality (AR) technology is expected to solve these issues. The results of the penetrant, bending, and tensile tests showed that the welder who had used the AR welding machine produced better welding specimens than before they practiced using the AR welding machine. The penetrant test after beginner welder practiced using the AR welding machine produces rounded defects with a defect size of 1,44 mm (accepted by ASME Section V), whereas before they practiced using the AR welding machine it produces defects that cannot be accepted by the criteria. The maximum open discontinuity length in the bending test on the welded specimen after welder practiced using the AR welding machine is 2,90 mm (accepted by ASME Section IX), whereas the bending test before welder practiced using the AR welding machine is not accepted by the citeria. The tensile test results after welder practiced using the AR welding machine were 410,00 and 455,66 N/mm2 for the maximum tensile stress. This value exceeds the minimum tensile strength of SA-36 carbon steel, which is 400 N/mm2. When compared to the specimen before the welder practiced using the AR welding machine, the modulus of elasticity produced after the welder practiced using the AR welding machine is also smaller, indicating that the material has better elasticity. Based on the results of the tests, it can be seen that the AR welding machine can be used for the implementation of competency certification because the quality of the weld results is better, there are fewer risks (sparks, eye irritation, and burns), and the use of welding consumables is reduced Welding ; Materials science ; Ultimate tensile strength ; Tensile testing ; Mechanical engineering ; Electric resistance welding ; Robot welding ; Electrogas welding ; Shielded metal arc welding ; Metallurgy ; Heat-affected zone ; Composite material ; Gas metal arc welding ; Engineering Material Selection and Properties ; Impulse Buying and Technology Impacts ; Welding Techniques and Residual Stresses