jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Tianhao Wang | Linya Chen
Source: Energies (article, 2023-01-17)
Field: Materials Science — Materials Chemistry

Thermodynamic Behavior and Energy Transformation Mechanism of the Multi-Period Evolution of Cavitation Bubbles Collapsing near a Rigid Wall: A Numerical Study The dynamic behavior and energy transformation mechanism of the multi-period evolution of bubbles collapsing near a wall have been essential considerations in bubble dynamics research. In this study, a compressible two-phase solver considering thermodynamics and phase transitions is developed on OpenFOAM (version v2112). This model is validated via comparison with analytical solutions and experimental results. The dynamics of the multi-period evolution of bubbles collapse process at different dimensionless stand-off distances (γ) were accurately reproduced. The results indicate that the shock wave emitted by the collapse of cavitation bubbles impacts the wall, causing the fluid temperature along the wall to increase. Moreover, the liquid jet has a dual effect on the wall temperature increase, depending on the initial stand-off distance between the bubble and the wall. When γ is small, the jet carries the low-temperature fluid to occupy the high-temperature region, and when γ is large, the jet carries the high-temperature fluid to occupy the low-temperature region. Compared with the mechanisms above of wall temperature increase, the collapse process of cavitation, when directly attached to the wall, increases the fluid temperature along the wall more significantly. Additionally, an energy transformation mechanism is proposed considering the internal bubble energy based on the analysis of the internal bubble energy and acoustic radiation energy with different γ values. Both the internal and acoustic radiation energy initially decreased and subsequently increased with increasing γ values. These findings provide deeper insights into the near-wall collapsing cavitation process mechanism. Cavitation ; Bubble ; Mechanics ; Jet (fluid) ; Dimensionless quantity ; Compressibility ; Internal energy ; Shock wave ; Shock (circulatory) ; Materials science ; Thermodynamics ; Physics Ultrasound and Cavitation Phenomena ; Underwater Acoustics Research
Authors: Toufique Ahmed | Shihab Uddin
Source: Data in Brief (article, 2023-02-21)
Field: Materials Science — Polymers and Plastics

Textile weaving dataset for machine learning to predict rejection and production of a weaving factory Weaving is one of the most popular fabric manufacturing techniques. The weaving process consists of 3 major stages: warping, sizing, and weaving. The weaving factory henceforth involves a lot of data. But unfortunately, there is no attempt to utilize machine learning or data science in weaving production. Although a variety of scopes are there to implement statistical analysis, data science, and machine learning. The dataset was prepared by using the daily production report for 9 months. The final dataset contains 121,148 data with 18 parameters. Whereas the raw data contains the same number of entries with 22 columns. The raw data needs substantial work to combine the daily production report, treat the missing values, rename columns, and feature engineering to derive EPI, PPI, warp, weft count values, etc. The complete dataset is stored at https://data.mendeley.com/datasets/nxb4shgs9h/1. It is further processed to get the rejection dataset which is stored at https://data.mendeley.com/datasets/6mwgj7tms3/2. The future implementation of the dataset is to predict the weaving waste, investigate the statistical relations among various parameters, production prediction, etc. Weaving ; Computer science ; Factory (object-oriented programming) ; Textile ; Sizing ; Raw data ; Production (economics) ; Machine learning ; Artificial intelligence ; Process (computing) ; Manufacturing engineering ; Data mining ; Engineering ; Mechanical engineering Textile materials and evaluations ; Industrial Vision Systems and Defect Detection ; Dyeing and Modifying Textile Fibers
Authors: Phetploy Rungkamoltip | Sittiruk Roytrakul | Raphatphorn Navakanitworakul
Source: Biomedicines (article, 2023-08-21)
Field: Chemistry — Spectroscopy

MALDI-TOF MS Analysis of Serum Peptidome Patterns in Cervical Cancer Laboratory-based rapid mass spectrometry showed that serum peptidome patterns could serve as diagnostic tools for diagnosing cervical cancer; however, verification through larger cohorts and association with clinical data are required, and the use of externally validated samples, such as patients with other types of cancers, should be investigated to validate the specific peptide patterns. Cervical cancer ; Medicine ; Cancer ; Internal medicine ; Mass spectrometry ; Analysis of variance ; Wilcoxon signed-rank test ; Oncology ; Chemistry ; Chromatography ; Mann–Whitney U test Advanced Proteomics Techniques and Applications ; Genomics and Phylogenetic Studies ; Molecular Biology Techniques and Applications
Authors: Asfarina Abu Bakar | Chai Chang Yii | Chin Kui Fern | Yoong Hou Pin | Herwansyah Lago | Mohamad Nur Khairul Hafizi Rohani
Source: Energies (article, 2023-02-11)
Field: Materials Science — Materials Chemistry

A Comparison of Double-End Partial Discharge Localization Algorithms in Power Cables The double-end partial discharge (PD) measurement method is the most common method for measuring and localizing PD sources in power cables. The sensitivity of the PD sensor, the processing speed of the data acquisition unit, and the method of the PD localization algorithm are the three main keys to ensuring the accuracy of the PD source localization on power cables. A new multi-end PD localization algorithm known as segmented correlation trimmed mean (SCTM) has recently demonstrated excellent accuracy in the localization of PD sources on power cables. The algorithm, however, is only applicable to multi-end PD measurement methods. In this paper, the mathematical equation of the SCTM algorithm is customized to match the double-end PD measurement method. A MATLAB simulation was conducted to assess the performance of the SCTM algorithm in the double-end PD measurement method. The maximum peak detection (MPD) algorithm, segmented correlation (SC), and SCTM algorithm were compared as PD localization algorithms. The SC algorithms have shown that identifying the correlation bond between two cues instead of the peak of the PD signal in the MPD algorithm significantly increases the PD localization accuracy. The results show that the SCTM algorithm outperforms the MPD and SC algorithms in terms of accuracy. Algorithm ; Partial discharge ; MATLAB ; Power (physics) ; Computer science ; SIGNAL (programming language) ; Engineering ; Voltage ; Electrical engineering ; Physics High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation ; Lightning and Electromagnetic Phenomena
Authors: Naif Hadadi | Adel Belayadi | Ahmed AlRabiah | Ousmane Ly | Collins Ashu Akosa | Michael Vogl | H. Bahlouli | Aurélien Manchon | Adel Abbout
Source: Physical review. B./Physical review. B (article, 2023-11-13)
Field: Materials Science — Materials Chemistry

Pseudo electric field and pumping valley current in graphene nanobubbles The extremely high pseudo magnetic field emerging in strained graphene suggests that an oscillating nanodeformation will induce a very high current even without electric bias. In this paper, we demonstrate the subterahertz (THz) dynamics of a valley current and the corresponding charge pumping with a periodically excited nanobubble. We discuss the amplitude of the pseudo electric field and investigate the dependence of the pumped valley current on the different parameters of the system. Finally, we report the signature of extra-harmonics generation in the valley current that might lead to potential modern device development operating in the nonlinear regime. Graphene ; Current (fluid) ; Electric field ; Harmonics ; Terahertz radiation ; Excited state ; Amplitude ; Magnetic field ; Electric current ; Field (mathematics) ; Physics ; Condensed matter physics ; Voltage ; Materials science ; Optoelectronics ; Nanotechnology ; Atomic physics ; Optics Graphene research and applications ; Quantum and electron transport phenomena ; Topological Materials and Phenomena
Authors: Kosuke Nogaki | Jiani Fei | Emanuel Gull | Hiroshi Shinaoka
Source: SciPost Physics Codebases (article, 2023-11-13)
Field: Materials Science — Materials Chemistry

Nevanlinna.jl: A Julia implementation of Nevanlinna analytic continuation We introduce a Julia implementation of the recently proposed Nevanlinna analytic continuation method. The method is based on Nevanlinna interpolants and inherently preserves the causality of a response function due to its construction. For theoretical calculations without statistical noise, this continuation method is a powerful tool to extract real-frequency information from numerical input data on the Matsubara axis. This method has been applied to first-principles calculations of correlated materials. This paper presents its efficient and full-featured open-source implementation of the method including the Hamburger moment problem and smoothing. Continuation ; Smoothing ; Analytic continuation ; Moment (physics) ; Nevanlinna theory ; Mathematics ; Applied mathematics ; Analytic function ; Function (biology) ; Noise (video) ; Calculus (dental) ; Mathematical optimization ; Computer science ; Meromorphic function ; Mathematical analysis ; Artificial intelligence Solid-state spectroscopy and crystallography ; Acoustic Wave Resonator Technologies ; Thermal Expansion and Ionic Conductivity
Authors: B.C. Shin | Changsang Yun
Source: Fashion and Textiles (article, 2023-09-04)
Field: Materials Science — Polymers and Plastics

Multidimensional analysis for fabric drapability Abstract This study analyzed fabric drapability in one, two, and three dimensions to provide an assessment method reflecting real conditions. One-dimensional analysis of drapability involved observing the fabric movement by reciprocating motion. The movement appeared differently depending on the fabric characteristics, and the shape and location of the node showed differently, which were considered to be influenced by the weight of the sample along with the drape coefficient. Two-dimensional analysis identified the significant factors for the drape information. This examination confirmed that, even if drape factors were similar, differences in draped shape were observed based on the factors related to node shapes. Three-dimensional analysis, using a 3D scanner, involved the use of the mean distances between draped samples and the standard truncated cone, their standard deviation, and the coefficient of variation. The coefficient of variation was high in the groups wherein the shape of the drape was irregular. In the 3D analysis, the distances between samples and the standard truncated cone were expressed in colors to intuitively deliver the drape information. To determine a factor that could indicate drapability among the factors derived from each dimension, the existing drape coefficient was employed for correlation analysis. Three pairs of samples with similar drape coefficients but different drape shapes were selected to verify the above results. In conclusion, one-dimensional node location, two-dimensional standard deviation of node severity, and three-dimensional coefficient of variation were shown to effectively demonstrate the drape characteristic that the drape coefficient could not indicate. Standard deviation ; Node (physics) ; Correlation coefficient ; Coefficient of variation ; Reciprocating motion ; Variation (astronomy) ; Mathematics ; Dimension (graph theory) ; Statistics ; Computer science ; Artificial intelligence ; Physics ; Combinatorics ; Acoustics Textile materials and evaluations ; Structural Analysis of Composite Materials ; Optical measurement and interference techniques
Authors: Kim Corinna Dümbgen | Roberta Pascazio | Bas van Beek | Zeger Hens | Ivan Infante
Source: The Journal of Physical Chemistry A (article, 2023-04-11)
Field: Materials Science — Materials Chemistry

Classical Force Field Parameters for InP and InAs Quantum Dots with Various Surface Passivations Classical molecular dynamics (MD) simulations on realistic colloidal quantum dot (QD) systems are often hampered by missing force field (FF) parameters for an accurate description of the QD-ligand interface. However, such calculations are of major interest, specifically for studying the surface chemistry of colloidal nanocrystals. In this work, we have utilized a previously published stochastic optimization algorithm to obtain FF parameters for InP and InAs QDs capped by Cl, amine, carboxylate, and thiolate ligands. Our FF parameters are interfaced with well-established FFs for organic molecules, allowing for the simulation of InP and InAs QDs with a broad range of organic ligands in explicit apolar solvents. The quality of our FF parameters was assessed by comparing properties of the classical MD simulations with <i>ab initio</i> MD simulations and experimental and theoretical values from the literature. Quantum dot ; Nanocrystal ; Ab initio ; Molecular dynamics ; Colloid ; Molecule ; Materials science ; Force field (fiction) ; Field (mathematics) ; Ligand (biochemistry) ; Amine gas treating ; Carboxylate ; Work (physics) ; Range (aeronautics) ; Quantum ; Chemical physics ; Nanotechnology ; Chemistry ; Computational chemistry ; Physical chemistry ; Physics ; Quantum mechanics ; Stereochemistry ; Mathematics ; Organic chemistry Quantum Dots Synthesis And Properties ; Molecular Junctions and Nanostructures ; Semiconductor Quantum Structures and Devices
Authors: Corey D. Pilgrim | Travis S. Grimes | C. Mark Smith | Colt R. Heathman | Jopaul Mathew | Santa Jansone‐Popova | Santanu Roy | Debmalya Ray | Vyacheslav S. Bryantsev | Peter R. Zalupski
Source: Scientific Reports (article, 2023-10-19)
Field: Chemistry — Inorganic Chemistry

Tuning aminopolycarboxylate chelators for efficient complexation of trivalent actinides The complexation of trivalent lanthanides and minor actinides (Am<sup>3+</sup>, Cm<sup>3+</sup>, and Cf<sup>3+</sup>) by the acyclic aminopolycarboxylate chelators 6,6'-((ethane-1,2-diylbis-((carboxymethyl)azanediyl))bis-(methylene))dipicolinic acid (H<sub>4</sub>octapa) and 6,6'-((((4-(1-(2-(2-(2-hydroxyethoxy)ethoxy)ethyl)-1H-1,2,3-triazol-4-yl)pyridine-2,6-diyl)bis-(methylene))bis-((carboxymethyl)azanediyl))bis-(methylene)) dipicolinic acid (H<sub>4</sub>pypa-peg) were studied using potentiometry, spectroscopy, competitive complexation liquid-liquid extraction, and ab initio molecular dynamics simulations. Two studied reagents are strong multidentate chelators, well-suited for applications seeking radiometal coordination for in-vivo delivery and f-element isolation. The previously reported H<sub>4</sub>octapa forms a compact coordination packet, while H<sub>4</sub>pypa-peg is less sterically constrained due to the presence of central pyridine ring. The solubility of H<sub>4</sub>octapa is limited in a non-complexing high ionic strength perchlorate media. However, the introduction of a polyethylene glycol group in H<sub>4</sub>pypa-peg increased the solubility without influencing its ability to complex the lanthanides and minor actinides in solution. Chemistry ; Denticity ; Methylene ; Lanthanide ; Pyridine ; Dipicolinic acid ; Solubility ; Chelation ; Deprotonation ; Inorganic chemistry ; Coordination complex ; Titration ; Nuclear chemistry ; Medicinal chemistry ; Organic chemistry ; Metal Radioactive element chemistry and processing ; Lanthanide and Transition Metal Complexes ; Radiopharmaceutical Chemistry and Applications
Authors: Ryan M. Richard | Kristopher Keipert | Jonathan M. Waldrop | Murat Keçeli | David B. Williams‐Young | Raymond A. Bair | Jeffery S. Boschen | Zachery Crandall | Kevin Gasperich | Quazi Ishtiaque Mahmud | Ajay Panyala | Edward F. Valeev | Hubertus J. J. van Dam | Wibe A. de Jong | Theresa L. Windus
Source: The Journal of Chemical Physics (article, 2023-05-12)
Field: Materials Science — Materials Chemistry

PluginPlay: Enabling exascale scientific software one module at a time For many computational chemistry packages, being able to efficiently and effectively scale across an exascale cluster is a heroic feat. Collective experience from the Department of Energy's Exascale Computing Project suggests that achieving exascale performance requires far more planning, design, and optimization than scaling to petascale. In many cases, entire rewrites of software are necessary to address fundamental algorithmic bottlenecks. This in turn requires a tremendous amount of resources and development time, resources that cannot reasonably be afforded by every computational science project. It thus becomes imperative that computational science transition to a more sustainable paradigm. Key to such a paradigm is modular software. While the importance of modular software is widely recognized, what is perhaps not so widely appreciated is the effort still required to leverage modular software in a sustainable manner. The present manuscript introduces PluginPlay, https://github.com/NWChemEx-Project/PluginPlay, an inversion-of-control framework designed to facilitate developing, maintaining, and sustaining modular scientific software packages. This manuscript focuses on the design aspects of PluginPlay and how they specifically influence the performance of the resulting package. Although, PluginPlay serves as the framework for the NWChemEx package, PluginPlay is not tied to NWChemEx or even computational chemistry. We thus anticipate PluginPlay to prove to be a generally useful tool for a number of computational science packages looking to transition to the exascale. Exascale computing ; Computer science ; Petascale computing ; Modular design ; Software ; Software engineering ; Leverage (statistics) ; Computational science ; Distributed computing ; Supercomputer ; Parallel computing ; Operating system Machine Learning in Materials Science ; Scientific Computing and Data Management ; Cloud Computing and Resource Management
Authors: Gábor Cśanyi | John W. R. Morgan | David J. Wales
Source: The Journal of Chemical Physics (article, 2023-09-12)
Field: Materials Science — Materials Chemistry

Global analysis of energy landscapes for materials modeling: A test case for C60 In this contribution, we employ computational tools from the energy landscape approach to test Gaussian Approximation Potentials (GAPs) for C60. In particular, we apply basin-hopping global optimization and explore the landscape starting from the low-lying minima using discrete path sampling. We exploit existing databases of minima and transition states harvested from previous work using tight-binding potentials. We explore the energy landscape for the full range of structures and pathways spanning from the buckminsterfullerene global minimum up to buckybowls. In the initial GAP model, the fullerene part of the landscape is reproduced quite well. However, there are extensive families of C1@C59 and C2@C58 structures that lie lower in energy. We succeeded in refining the potential to remove these artifacts by simply including two minima from the C2@C58 families found by global landscape exploration. We suggest that the energy landscape approach could be used systematically to test and improve machine learning interatomic potentials. Maxima and minima ; Energy landscape ; Energy (signal processing) ; Potential energy ; Gaussian ; Range (aeronautics) ; Computer science ; Work (physics) ; Exploit ; Statistical physics ; Physics ; Mathematics ; Materials science ; Quantum mechanics Machine Learning in Materials Science ; Fullerene Chemistry and Applications ; Advanced Chemical Physics Studies
Authors: Gowtham Nimmal Haribabu | Jeyapriya Thimukonda Jegadeesan | Chiranjib Bhattacharya | Bikramjit Basu
Source: Computational Materials Science (article, 2023-09-21)
Field: Materials Science — Materials Chemistry

A deep adversarial approach for the generation of synthetic titanium alloy microstructures with limited training data Discriminator ; Computer science ; Microstructure ; Titanium alloy ; Convolutional neural network ; Artificial intelligence ; Pattern recognition (psychology) ; Deep learning ; Kernel (algebra) ; Materials science ; Algorithm ; Mathematics ; Alloy Machine Learning in Materials Science ; Hydrogen embrittlement and corrosion behaviors in metals ; Welding Techniques and Residual Stresses
Authors: Yanyan Liu | Mingjun Xu | Luís M. Portela | Valeria Garbin
Source: Soft Matter (article, 2023-12-04)
Field: Materials Science — Materials Chemistry

Diffusion across particle-laden interfaces in Pickering droplets Emulsions stabilized by nanoparticles, known as Pickering emulsions, exhibit remarkable stability, which enables applications ranging from encapsulation, to advanced materials, to chemical conversion. The layer of nanoparticles at the interface of Pickering droplets is a semi-permeable barrier between the two liquid phases, which can affect the rate of release of encapsulates, and the interfacial transfer of reactants and products in biphasic chemical conversion. A gap in our fundamental understanding of diffusion in multiphase systems with particle-laden interfaces currently limits the optimal development of these applications. To address this gap, we developed an experimental approach for <i>in situ</i>, real-time quantification of concentration fields in Pickering droplets in a Hele-Shaw geometry and investigated the effect of the layer of nanoparticles on diffusion of solute across a liquid-liquid interface. The experiments did not reveal a significant hindrance on the diffusion of solute across an interface densely covered by nanoparticles. We interpret this result using an unsteady diffusion model to predict the spatio-temporal evolution of the concentration of solute with a particle-laden interface. We find that the concentration field is only affected in the immediate vicinity of the layer of particles, where the area available for diffusion is affected by the particles. This defines a characteristic time scale for the problem, which is the time for diffusion across the layer of particles. The far-field concentration profile evolves towards that of a bare interface. This localized effect of the particle hindrance is not measurable in our experiments, which take place over a much longer time scale. Our model also predicts that the hindrance by particles can be more pronounced depending on the particle size and physicochemical properties of the liquids and can ultimately affect performance in applications. Pickering emulsion ; Diffusion ; Nanoparticle ; Particle (ecology) ; Chemical physics ; Materials science ; Nanotechnology ; Particle size ; Chemical engineering ; Chemistry ; Thermodynamics ; Physics ; Physical chemistry Pickering emulsions and particle stabilization ; Proteins in Food Systems ; Surfactants and Colloidal Systems
Authors: Mahshid Akbari-Meinagh | Seyedeh‐Arefeh Safavi‐Mirmahalleh | Hossein Roghani‐Mamaqani | Mehdi Salami‐Kalajahi
Source: Journal of environmental chemical engineering (article, 2023-03-27)
Field: Materials Science — Polymers and Plastics

Preparation of stimuli-responsive hydrogel vitrimers as recyclable dye adsorbent for water purification Self-healing hydrogels ; Adsorption ; Aqueous solution ; Differential scanning calorimetry ; Thermogravimetric analysis ; Glycidyl methacrylate ; Nuclear chemistry ; Swelling ; Fourier transform infrared spectroscopy ; Methacrylic acid ; Materials science ; Chemical engineering ; Chemistry ; Copolymer ; Polymer chemistry ; Organic chemistry ; Composite material ; Polymer Polymer composites and self-healing ; Advanced Polymer Synthesis and Characterization ; Pickering emulsions and particle stabilization