jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Muhammad Zubair | Fayyaz Ahmad | Zakariya Zubair | Abdul Jabbar | Jiya Baig
Source: Journal of the Textile Institute (article, 2023-12-12)
Field: Materials Science — Polymers and Plastics

Validation of fibre stress utilization model for modified ring spun yarns To model the fibre stress utilization in modified ring spun yarns, we developed an analytical formula from the experimental data. The development of empirical formulae is carried out by using two different techniques, i.e., Cubic Spline and Artificial Neural Network methods. The experimental data of stress-strain curves of fibre and yarn has a large variation. To cope this variability, we used the smoothing spline technique to find the best-fit curve with respect to a reasonable smoothness. The best nonlinear smooth fitting can be used to extrapolate the experimental data beyond the breaking point. The modified ring spun yarns (compact, SIRO and SIRO-compact) with 20/1, 30/1 and 40/1 English count, produced from viscose staple fibre, were used to predict fibre stress utilization up to the yarn break by extrapolating the mean stress-strain curves of fibre and yarn by using the artificial neural network. Moreover, a new distribution function of fibre distribution in yarn has been proposed and successfully implemented for the prediction of fibre stress utilization in yarn. The new formulation helps to compute the fibre stress utilization in the yarn analytically. The validation of the proposed methodology is presented by comparing the numerical results with the experimental data. The predicted fibre stress utilization was in good agreement with the experimental fibre stress utilization for all types of modified ring spun yarns. It has been observed that SIRO-compact yarn exhibits improved fibre stress utilization as compared to SIRO and compact yarns. Moreover, the new distribution functions Gamma and Gaussian distribution were introduced in parallel with the Dirac delta function. In previous similar studies on ring, rotor and air-jet spun yarns, the proposed model can only predict the fibre stress utilization before the breakage point whereas the modified model, in this study, can predict the fibre stress utilization up to the breaking point. Yarn ; Materials science ; Viscose ; Stress (linguistics) ; Composite material ; Curve fitting ; Smoothing ; Artificial neural network ; Structural engineering ; Mathematics ; Computer science ; Engineering ; Artificial intelligence ; Statistics Textile materials and evaluations ; Mechanical Behavior of Composites ; Vibration and Dynamic Analysis
Authors: Wu Xiaosong
Source: Frontiers in Science and Engineering (article, 2023-02-20)
Field: Chemistry — Physical and Theoretical Chemistry

The Legendary Scientific Figure: George parisi In 2021, the Nobel Prize in Physics was awarded to three physicists who made breakthroughs in understanding complex systems: Syukuro Manabe of Japan, Klaus Hasselmann of Germany and Giorgio Parisi of Italy. This paper mainly introduces the legendary experience of Italian scientist Giorgio parisi, including the promotion of Solvey Conference and his love affair with China. George (robot) ; Art history ; Art History and advancements in chemistry ; International Science and Diplomacy
Authors: Казеннов Московский Физико-Технический Институт | D Kozakov | P Kundrotas
Source:  (article, 2023-12-08)
Field: Materials Science — Materials Chemistry

Использование нейронной сети AlphaFold2 для улучшения результатов белок-белкового докинга () - ( Computer science Enzyme Structure and Function ; Biochemical and Molecular Research
Authors: Matthew Vuoncino | Dake Hao | Christopher D. Pivetti | Elan Sherazee | Nataliya Bahatyrevich | Brendon Bagley | Amory Koch | Emily Byrd | Zoe M. Saenz | Monalisa Hassan | Su Yeon Lee | Timothy M. Guenther | Aijun Wang | Mimmie Kwong
Source: Journal of Vascular Surgery (article, 2023-05-23)
Field: Materials Science — Biomaterials

Effects of Cyclic Peptide LXW7 Coating on Short-term Vascular Graft Patency Using a Porcine (Sus scrofa) Model Medicine ; Surgery ; Thrombus ; Progenitor cell ; Neointima ; In vivo ; Anastomosis ; Animal model ; Stem cell ; Stent ; Restenosis ; Internal medicine Electrospun Nanofibers in Biomedical Applications ; Polymer Surface Interaction Studies ; Protease and Inhibitor Mechanisms
Authors: Elizaveta Tiukalova | Yuzhou Zhao | Ji‐Hui Yang | Xiaodong Xu | Andrew R. Lupini | Juan Carlos Idrobo
Source: Microscopy and Microanalysis (article, 2023-07-22)
Field: Materials Science — Materials Chemistry

Revealing Atomic Structure, Strain and Moiré-Exciton Coupling of hBN/WSe2/WS2 Superlattice at LN2 Temperature by Monochromated EELS and ADF-STEM Imaging Journal Article Revealing Atomic Structure, Strain and Moiré-Exciton Coupling of hBN/WSe2/WS2 Superlattice at LN2 Temperature by Monochromated EELS and ADF-STEM Imaging Get access Elizaveta Tiukalova, Elizaveta Tiukalova Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, United States Corresponding author: tiukalovae@ornl.gov Search for other works by this author on: Oxford Academic Google Scholar Yuzhou Zhao, Yuzhou Zhao Department of Physics, University of Washington, Seattle, WA, United States Search for other works by this author on: Oxford Academic Google Scholar Jihui Yang, Jihui Yang Materials Science & Engineering Department, University of Washington, Seattle, WA, United States Search for other works by this author on: Oxford Academic Google Scholar Xiaodong Xu, Xiaodong Xu Department of Physics, University of Washington, Seattle, WA, United StatesMaterials Science & Engineering Department, University of Washington, Seattle, WA, United States Search for other works by this author on: Oxford Academic Google Scholar Andrew R Lupini, Andrew R Lupini Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, United States Search for other works by this author on: Oxford Academic Google Scholar Juan Carlos Idrobo Juan Carlos Idrobo Materials Science & Engineering Department, University of Washington, Seattle, WA, United StatesPhysical Sciences Division, Pacific Northwest National Laboratory, Richland, WA, United States Search for other works by this author on: Oxford Academic Google Scholar Microscopy and Microanalysis, Volume 29, Issue Supplement_1, 1 August 2023, Pages 1707–1708, https://doi.org/10.1093/micmic/ozad067.881 Published: 22 July 2023 Superlattice ; Materials science ; Exciton ; Strain (injury) ; Coupling (piping) ; Moiré pattern ; Condensed matter physics ; Optoelectronics ; Composite material ; Optics ; Physics ; Biology 2D Materials and Applications ; Perovskite Materials and Applications ; MXene and MAX Phase Materials
Authors: Donovan Birky | Nolan Strauss | Jacob Hochhalter | John M Emery | Coleman Alleman | Michael Buche
Source:  (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

Interpretable machine learning for uncertain, microstructure-dependent constitutive models Constitutive equation ; Computer science ; Microstructure ; Artificial intelligence ; Machine learning ; Materials science ; Engineering ; Composite material ; Structural engineering ; Finite element method Machine Learning in Materials Science
Authors: Junjie Wang | Yang Li | Jingzhu Wu | Cuiling Liu | Xiaorong Sun | Shanzhe Zhang
Source: Terahertz Science and Technology (article, 2023-03-01)
Field: Chemistry — Analytical Chemistry

Detection method of cottonseed fullness on the basis of terahertz spectroscopy and imaging technology Cottonseed fullness is an important indicator in characterizing the quality of cottonseed. This paper explores the application of terahertz time-domain spectral transmission imaging technology with image refactoring image processing and other methods in cottonseed fullness detection research. In this study, the Terapulse 4000 terahertz(THz) time-domain spectroscopy system and a transmission imaging accessory are used to collect THz spectral images of cottonseed samples. Certain differences can be observed in the composition and spatial distribution of the seed kernel and the seed cavity for which terahertz images at different depths is useful in clearly distinguishing the seed kernel and the seed cavity. To explore the imaging results of the samples under different refactoring methods and use the maximum inter-class variance method (Otsu method) to remove the background to obtain complete sample images,the mathematical morphology algorithm is used to select the circular structural element with a side length of 3 as the check image for dilation corrosion and non-destructively extract the images of different tissues of cottonseed. The THz time-domain spectral images are organized, and then a fullness model of cottonseed based on the THz time-domain spectral images is established according to the enrichment quantification calculation formula. Experimental results show that the non-destructive testing of cottonseed samples can be achieved by using terahertz time-domain spectral imaging technology and is expected to provide a theoretical basis and a method reference for shelled seeds’ non-destructive testing. Terahertz radiation ; Spectroscopy ; Cottonseed ; Terahertz spectroscopy and technology ; Basis (linear algebra) ; Materials science ; Optics ; Remote sensing ; Physics ; Chemistry ; Mathematics ; Optoelectronics ; Geography ; Astronomy ; Food science Spectroscopy and Chemometric Analyses ; Terahertz technology and applications ; Remote Sensing and Land Use
Authors: Kevin M. Roccapriore | Maxim Ziatdinov | Riccardo Torsi | Joshua A. Robinson | Sergei V. Kalinin
Source: Microscopy and Microanalysis (article, 2023-07-22)
Field: Materials Science — Materials Chemistry

Measuring Single Atomic Defects in 2D Materials with Off-axis EELS Using Real-time AI-driven Detection Journal Article Measuring Single Atomic Defects in 2D Materials with Off-axis EELS Using Real-time AI-driven Detection Get access Kevin M Roccapriore, Kevin M Roccapriore Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, United States Corresponding author: roccapriorkm@ornl.gov Search for other works by this author on: Oxford Academic Google Scholar Maxim Ziatdinov, Maxim Ziatdinov Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, United StatesComputational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN, United States Search for other works by this author on: Oxford Academic Google Scholar Riccardo Torsi, Riccardo Torsi Materials Science and Engineering, Penn State University, University Park, PA, United States Search for other works by this author on: Oxford Academic Google Scholar Joshua Robinson, Joshua Robinson Materials Science and Engineering, Penn State University, University Park, PA, United States Search for other works by this author on: Oxford Academic Google Scholar Sergei V Kalinin Sergei V Kalinin Department of Materials Science and Engineering, University of Tennessee, Knoxville TN, United States Search for other works by this author on: Oxford Academic Google Scholar Microscopy and Microanalysis, Volume 29, Issue Supplement_1, 1 August 2023, Pages 392–393, https://doi.org/10.1093/micmic/ozad067.184 Published: 22 July 2023 Oak Ridge National Laboratory ; Ridge ; Library science ; National laboratory ; National park ; Graduate students ; Engineering physics ; Art history ; Engineering ; History ; Archaeology ; Physics ; Geography ; Sociology ; Computer science ; Cartography ; Nuclear physics Electronic and Structural Properties of Oxides ; Electron and X-Ray Spectroscopy Techniques ; Semiconductor materials and devices
Authors: Harley D. Scammell | Mathias S. Scheurer
Source: arXiv (Cornell University) (preprint, 2023-08-21)
Field: Materials Science — Materials Chemistry

Displacement-field-tunable superconductivity in an inversion-symmetric twisted van der Waals heterostructure We investigate the superconducting properties of inversion-symmetric twisted trilayer graphene by considering different parent states, including spin-singlet, triplet, and SO(4) degenerate states, with or without nodal points. By placing transition metal dichalcogenide layers above and below twisted trilayer graphene, spin-orbit coupling is induced in TTLG and, due to inversion symmetry, the spin-orbit coupling does not spin-split the bands. The application of a displacement field ($D_0$) breaks the inversion symmetry and creates spin-splitting. We analyze the evolution of the superconducting order parameters in response to the combined spin-orbit coupling and $D_0$-induced spin-splitting. Utilizing symmetry analysis combined with both a direct numerical evaluation and a complementary analytical study of the gap equation, we provide a comprehensive understanding of the influence of spin-orbit coupling and $D_0$ on superconductivity. These results contribute to a better understanding of the superconducting order in twisted trilayer graphene. Point reflection ; Superconductivity ; Condensed matter physics ; Degenerate energy levels ; Spin–orbit interaction ; Graphene ; Heterojunction ; Physics ; Spin (aerodynamics) ; Displacement field ; Quantum mechanics Graphene research and applications ; Quantum and electron transport phenomena ; Superconductivity in MgB2 and Alloys
Authors: Jianwei Wang | Ze Zhang | Zhiyan Lin | Hanting Li | Zhenjun Fan | Hua Gao
Source: Research Square (preprint, 2023-05-19)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Tunable narrowband and broadband coexisting absorber enabled by a simple all-metal grating for sensing applications Abstract We realize a tunable narrowband and broadband coexisting absorber based on a simple step-shaped all-metal grating structure. The absorber presents an ultra-narrow absorption band of 1.5 nm and a relatively broad absorption band of 29.8 nm, both with nearly 100% absorption in the infrared region. The mechanism underlying the dual-band perfect absorption is the interaction between two diffraction coupled surface plasmon polariton (SPP) modes with one of them modulated by a cavity resonance. Influences of structure parameters on the absorption performance are numerically investigated. It is found that the positions of the two perfect absorption peaks can be easily tuned both independently and together by changing the structural parameters. In addition, the designed grating structure presents excellent sensing performance with sensitivity and figure of merit as high as 2514 nm/RIU and 1600RIU -1 , respectively. Such high sensing metrics arise from the poor field localization and the ultra-narrow absorption band enabled by the diffraction coupled SPP modes as well as the specially designed all-metal structure. The excellent sensing performance, flexible tenability and simple structure design endow this grating absorber with great potential in high-precision biochemical sensing applications. Grating ; Absorption (acoustics) ; Materials science ; Narrowband ; Broadband ; Optoelectronics ; Absorption band ; Optics ; Diffraction ; Diffraction grating ; Plasmon ; Physics Metamaterials and Metasurfaces Applications ; Plasmonic and Surface Plasmon Research ; Advanced Antenna and Metasurface Technologies
Authors: Et al. Md Najumunnisa
Source: International Journal on Recent and Innovation Trends in Computing and Communication (article, 2023-11-05)
Field: Chemistry — Analytical Chemistry

Advanced Dielectric Anomaly Detection for Non-Destructive Fruit Inspection Using Electromagnetic Microwave Technique This paper presents a comprehensive investigation into the application of an electromagnetic microwave technique combined with the dielectric anomaly approach algorithm for the non-destructive inspection of fruits. The proposed antenna configuration comprises eight elements arranged in a circular array, enabling the collection of signals scattered by objects, specifically fruits, placed in their path. The collected data undergoes a series of processing steps, including Fast Fourier Transform, covariance matrix estimation, eigenvalue and eigenvector computation, and spatial spectrum construction. The dielectric anomaly algorithm is then applied to detect defects in the fruits. The study covers five different types of fruits, both healthy and defective, and gathers essential dielectric properties. Furthermore, a novel hybrid IQR method is introduced for outlier detection in the dielectric data. The results demonstrate the effectiveness of the proposed methodology in providing valuable insights into the internal structures of fruits and detecting anomalies, contributing to the enhancement of quality assessment in fruit inspection processes. Anomaly detection ; Microwave ; Dielectric ; Outlier ; Anomaly (physics) ; Covariance matrix ; Computer science ; Computation ; Eigenvalues and eigenvectors ; Antenna (radio) ; Algorithm ; Biological system ; Pattern recognition (psychology) ; Materials science ; Data mining ; Artificial intelligence ; Physics ; Telecommunications ; Optoelectronics ; Biology Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Industrial Vision Systems and Defect Detection
Authors: Shubhang Goswami | Kipton Barros | Matthew R. Carbone
Source: arXiv (Cornell University) (preprint, 2023-06-19)
Field: Materials Science — Materials Chemistry

Physically interpretable approximations of many-body spectral functions The rational function approximation provides a natural and interpretable representation of response functions such as the many-body spectral functions. We apply the Vector Fitting (VFIT) algorithm to fit a variety of spectral functions calculated from the Holstein model of electron-phonon interactions. We show that the resulting rational functions are highly efficient in their fitting of sharp features in the spectral functions, and could provide a means to infer physically relevant information from a spectral dataset. The position of the peaks in the approximated spectral function are determined by the location of poles in the complex plane. In addition, we developed an enhanced version of VFIT by introducing a regularization parameter that is slowly annealed to zero. With this new procedure, we demonstrate it is possible to achieve accurate spectral function fits that vary smoothly as a function of physical conditions. Regularization (linguistics) ; Rational function ; Spectral representation ; Representation (politics) ; Function (biology) ; Complex plane ; Spectral function ; Position (finance) ; Mathematics ; Spectral shape analysis ; Algorithm ; Spectral line ; Applied mathematics ; Statistical physics ; Computer science ; Mathematical analysis ; Physics ; Artificial intelligence ; Quantum mechanics Machine Learning in Materials Science ; Spectroscopy and Quantum Chemical Studies ; Electrochemical Analysis and Applications
Authors: Congcong Huang | Zenghua Fan | Ming Fan | Zhi Ping Xu | Jun Gao
Source: Micromachines (article, 2023-03-29)
Field: Materials Science — Surfaces, Coatings and Films

A Predictive Model of Capillary Forces and Contact Diameters between Two Plates Based on Artificial Neural Network Many efforts have been devoted to the forecasting of the capillary force generated by capillary adsorption between solids, which is fundamental and essential in the fields of micro-object manipulation and particle wetting. In this paper, an artificial neural network (ANN) model optimized by a genetic algorithm (GA-ANN) was proposed to predict the capillary force and contact diameter of the liquid bridge between two plates. The mean square error (<i>MSE</i>) and correlation coefficient (<i>R</i><sup>2</sup>) were employed to evaluate the prediction accuracy of the GA-ANN model, theoretical solution method of the Young-Laplace equation and simulation approach based on the minimum energy method. The results showed that the values of <i>MSE</i> of capillary force and contact diameter using GA-ANN were 10.3 and 0.0001, respectively. The values of <i>R</i><sup>2</sup> were 0.9989 and 0.9977 for capillary force and contact diameter in regression analysis, respectively, demonstrating the accuracy of the proposed predictive model. The sensitivity analysis was conducted to investigate the influence of input parameters, including liquid volume and separation distance, on the capillary force and contact diameter. The liquid volume and separation distance played dominant roles in affecting the capillary force and contact diameter. Capillary action ; Artificial neural network ; Mean squared error ; Contact force ; Wetting ; Contact angle ; Materials science ; Correlation coefficient ; Mechanics ; Biological system ; Mathematics ; Artificial intelligence ; Computer science ; Physics ; Composite material ; Statistics ; Classical mechanics Surface Modification and Superhydrophobicity ; Adhesion, Friction, and Surface Interactions ; Advanced Sensor and Energy Harvesting Materials
Authors: Rainie Bozzai | Thomas Rothvoß
Source: arXiv (Cornell University) (preprint, 2023-10-12)
Field: Chemistry — Inorganic Chemistry

Stronger Coreset Bounds for Kernel Density Estimators via Chaining We apply the discrepancy method and a chaining approach to give improved bounds on the coreset complexity of a wide class of kernel functions. Our results give randomized polynomial time algorithms to produce coresets of size $O\big(\frac{\sqrt{d}}{\varepsilon}\sqrt{\log\log \frac{1}{\varepsilon}}\big)$ for the Gaussian and Laplacian kernels in the case that the data set is uniformly bounded, an improvement that was not possible with previous techniques. We also obtain coresets of size $O\big(\frac{1}{\varepsilon}\sqrt{\log\log \frac{1}{\varepsilon}}\big)$ for the Laplacian kernel for $d$ constant. Finally, we give the best known bounds of $O\big(\frac{\sqrt{d}}{\varepsilon}\sqrt{\log(2\max\{1,α\})}\big)$ on the coreset complexity of the exponential, Hellinger, and JS Kernels, where $1/α$ is the bandwidth parameter of the kernel. Combinatorics ; Chaining ; Mathematics ; Bounded function ; Binary logarithm ; Exponent ; Kernel (algebra) ; Discrete mathematics ; Mathematical analysis Metal-Organic Frameworks: Synthesis and Applications ; Mathematical Approximation and Integration ; MicroRNA in disease regulation