jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Volodymyr Kombarov | Volodymyr Sorokin | Yevgen Tsegelnyk | Sergiy Plankovskyy | Yevhen Aksonov | Olena Fojtů
Source: International Journal of Mechatronics and Applied Mechanics (article, 2021-07-21)
Field: Materials Science — General Materials Science

NUMERICAL CONTROL OF MACHINING PARTS FROM ALUMINUM ALLOYS WITH STICKING MINIMIZATION To implement a lot of technological processes in the manufacturing of aircraft parts from aluminum alloys, it is necessary to move the tool at a high speed. High requirements for accuracy and manufacturing quality aircraft parts are provided with application of CNC systems with adaptive control algorithms, in which due the mutual influence of the process parameters provided by the parameters of quality and accuracy. Among a number of factors adversely affecting the quality of high speed machining of aluminum alloys in the paper questions influence Lookahead system distortion predetermined (set up) cutting parameters on the formation conditions of the sticking material to the tool. The paper deals with high-speed machining without the use of a cooling lubricant (coolant). The paper provides a qualitative description of the heat generation variation in the cutting zone. It is concluded that it is necessary to cutting speed variation when feed variating. An experimental investigation of the cutting parameters for the appearance of the effect of the processed material sticking on the tool for alloy 1933 has been carried out. Areas of an unfavorable (negative) combination of parameters leading to the sticking of the material to the tool have been identified. The method of cutting modes adaptation to contour feed rate variation on curvilinear areas of a processing trajectory is proposed. The analysis of variation in cutting parameters with the partial deceleration of the spindle simultaneously with the deceleration of feed when moving along the path is carried out. The possibility of excluding the sticking of the processed material to the tool when variation the rotation speed by 2030% is shown. The proposed method is implemented in the CNC system and used for manufacturing of "Antonov" company airplane parts. Machining ; Aluminium ; Minification ; Materials science ; Metallurgy ; Control (management) ; Numerical control ; Mechanical engineering ; Computer science ; Engineering ; Artificial intelligence Material Properties and Applications ; Metallurgy and Material Forming ; Aluminum Alloy Microstructure Properties
Authors: Chaitanya Narendra | Trevor Brown | Puyan Mojabi
Source: IEEE Transactions on Antennas and Propagation (article, 2021-10-15)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Gradient-Based Electromagnetic Inversion for Metasurface Design Using Circuit Models A gradient-based optimization algorithm that is capable of directly designing a metasurface at the circuit parameter level for a desired field (amplitude and phase) pattern or a desired power (phaseless) pattern on some region of interest (ROI) external to the metasurface boundary is presented. Specifically, the inversion algorithm designs the microwave admittance profile of each subwavelength element of the metasurface when a three-layer admittance model is assumed. To this end, a forward model that maps the admittance profile of each layer of the metasurface to the desired field on the ROI is developed. Then, for the inverse design problem, a data misfit cost functional is defined and minimized over the unknown admittance profile using analytically derived gradients and step lengths. The developed inversion algorithm is then utilized to design metasurfaces capable of beam forming in the far-field zone. Admittance ; Inversion (geology) ; Inverse problem ; Computer science ; Inverse ; Microwave ; Amplitude ; Optics ; Algorithm ; Physics ; Electrical impedance ; Mathematics ; Mathematical analysis ; Geometry ; Telecommunications ; Geology Metamaterials and Metasurfaces Applications ; Antenna Design and Analysis ; Advanced Antenna and Metasurface Technologies
Authors: L L D Zhong | Lin Zhu | Zongwei Cai
Source: Journal of Analysis and Testing (review, 2021-09-08)
Field: Chemistry — Spectroscopy

Mass Spectrometry-based Proteomics and Glycoproteomics in COVID-19 Biomarkers Identification: A Mini-review Glycoproteomics ; Proteomics ; Biomarker discovery ; Coronavirus disease 2019 (COVID-19) ; Disease ; Computational biology ; Pandemic ; Identification (biology) ; Proteome ; Biology ; Medicine ; Bioinformatics ; Internal medicine ; Infectious disease (medical specialty) Advanced Proteomics Techniques and Applications ; Biosensors and Analytical Detection ; SARS-CoV-2 detection and testing
Authors: Reem H. Obaydo | Duaa J. Al Zakri | Amir Alhaj Sakur | Hayam M. Lotfy
Source: Future Journal of Pharmaceutical Sciences (article, 2021-02-12)
Field: Chemistry — Analytical Chemistry

Ultraviolet spectrophotometric methods for the determination of the minor component presented in fixed-dose pharmaceutical combinations through the last two decades (2000–2020) Abstract Background The pharmaceutical industry and the National Regulatory Authorities are now focusing on the quantification of multi-component drugs for quality control testing. Main body Recently, the utilization of the ultraviolet spectrophotometric methods has become vital for the analytical studies for the routine analysis of different fixed-dose combination products either in the presence of a minor component in their combination or not. This article reviewed several published methods to those that have been applied to quantify some pharmaceutical combinations containing minor components through the last two decades. Conclusion The applied spectrophotometric methods are labor, time-saving, and also considered a cheap substitute for the overpriced high-performance liquid chromatographic technique. Minor (academic) ; Component (thermodynamics) ; Ultraviolet ; Chromatography ; Quality (philosophy) ; Computer science ; Chemistry ; Materials science ; Law ; Physics Analytical Methods in Pharmaceuticals ; Analytical Chemistry and Chromatography ; Pesticide Residue Analysis and Safety
Authors: Yongjia Zhang | Jianxin Zhou | Yajun Yin | Xu Shen | Xiaoyuan Ji
Source: Journal of Materials Research and Technology (article, 2021-07-24)
Field: Materials Science — Materials Chemistry

Multi-GPU implementation of a cellular automaton model for dendritic growth of binary alloy A parallel three-dimensional (3D) cellular automaton (CA) model is developed for dendritic growth simulation during solidification of binary alloy. The CA model is implemented using the graphic processing unit (GPU). Compute Unified Device Architecture (CUDA) is combined with Message Passing Interface (MPI) to perform large-scale simulation on the multi-GPU architecture. A CUDA-Aware OpenMPI is used to reduce the communication cost between different GPU cards. The accuracy and the speedup ratio of the CA model are investigated. First, the simulated steady-state tip velocity under different undercooling is compared with the LGK analytical solution. Then, dendritic growth during directional solidification and equiaxed multi-dendrite growth are simulated. Dendritic growth simulation with a domain size up to 453 million grids is performed. Finally, the speedup ratio of the CA model using four GPUs is compared with that using four CPU processes via MPI, which leads to a maximal speedup ratio of 152.19. The developed CA model achieves high parallel performance compared with the MPI-based parallel model. The developed CA model is capable of predicting the columnar to equiaxed transition (CET) event during directional solidification. The results indicate that increasing cooling rate promotes the occurrence of the equiaxed dendrites in the melt ahead of the solidification front, and equiaxed dendrites are prone to nucleate in the columnar dendrite groove zone when a middle cooling rate is applied. Equiaxed crystals ; Speedup ; Parallel computing ; Directional solidification ; Dendrite (mathematics) ; CUDA ; Computer science ; Supercooling ; Cellular automaton ; Nucleation ; GPU cluster ; Computational science ; Materials science ; Geometry ; Algorithm ; Alloy ; Thermodynamics ; Composite material ; Physics ; Mathematics Solidification and crystal growth phenomena ; Aluminum Alloy Microstructure Properties ; Metallurgy and Material Forming
Authors: Kan Hatakeyama‐Sato | Kenichi Oyaizu
Source: ACS Omega (article, 2021-05-25)
Field: Materials Science — Materials Chemistry

Generative Models for Extrapolation Prediction in Materials Informatics We report a deep generative model for regression tasks in materials informatics. The model is introduced as a component of a data imputer and predicts more than 20 diverse experimental properties of organic molecules. The imputer is designed to predict material properties by "imagining" the missing data in the database, enabling the use of incomplete material data. Even removing 60% of the data does not diminish the prediction accuracy in a model task. Moreover, the model excels at extrapolation prediction, where target values of the test data are out of the range of the training data. Such an extrapolation has been regarded as an essential technique for exploring novel materials but has hardly been studied to date due to its difficulty. We demonstrate that the prediction performance can be improved by >30% by using the imputer compared with traditional linear regression and boosting models. The benefit becomes especially pronounced with few records for an experimental property (<100 cases) when prediction would be difficult by conventional methods. The presented approach can be used to more efficiently explore functional materials and break through previous performance limits. Extrapolation ; Computer science ; Boosting (machine learning) ; Materials informatics ; Predictive modelling ; Machine learning ; Generative grammar ; Regression ; Data mining ; Range (aeronautics) ; Property (philosophy) ; Artificial intelligence ; Linear regression ; Generative model ; Health informatics ; Mathematics ; Statistics ; Engineering Machine Learning in Materials Science ; Computational Drug Discovery Methods ; X-ray Diffraction in Crystallography
Authors: Junyao Wu | Shan Yi | Yixuan Wang | Jun Yao | Wei Gao
Source: International Journal of Smart and Nano Materials (article, 2021-04-03)
Field: Materials Science — Materials Chemistry

Polymer-based TiO<sub>2</sub> nanocomposite membrane: synthesis and organic pollutant removal Titanium dioxide (TiO2) nanoparticles are efficient photocatalysis for treating organic pollutants in water. Immobilizing TiO2 nanoparticles not only enables the reuse of nanoparticles but also prevents the harmful impact of releasing nanoparticles into the aquatic environment. In this study, a porous composite microfiber membrane based on polyacrylonitrile (PAN) with TiO2 nanoparticles has been synthesized by electrospinning technique. The new membrane system has exhibited excellent adsorptive-photocatalytic property to degrade Methylene blue (MB). Using the nonlinear form of the pseudo-first-order, pseudo-second-order, Elovich, and Intra-particle diffusion models, the adsorption mechanism was analyzed. Coupling with adsorption and photocatalysis, the efficiency of this membrane system was illustrated via the multistage linear form of the pseudo-first-order kinetic; and the electrical energy per order (EEO) confirmed the lowest energy requirements to transfer selected pollutants. Combining the results of SEM, BET, FTIR, XRD and TGA, it revealed the relationship of microstructure, composition, and MB decomposition performance. The finding presents new knowledge for material design and evaluation of polymers/oxides membrane systems for remediating organic pollutants in water. Photocatalysis ; Polyacrylonitrile ; Chemical engineering ; Materials science ; Nanocomposite ; Titanium dioxide ; Membrane ; Adsorption ; Nanoparticle ; Electrospinning ; Polymer ; Nanomaterials ; Nanotechnology ; Chemistry ; Composite material ; Organic chemistry ; Catalysis Nanoparticles: synthesis and applications ; Electrospun Nanofibers in Biomedical Applications ; Membrane Separation Technologies
Authors: Alyson Shoji | Christopher H. Kang | Kazuumi Fujioka | John P. Rose | Rui Sun
Source: Journal of Chemical Theory and Computation (article, 2021-12-01)
Field: Chemistry — Spectroscopy

Assessing the Intestinal Permeability of Small Molecule Drugs via Diffusion Motion on a Multidimensional Free Energy Surface A protocol that accurately assesses the intestinal permeability of small molecule compounds plays an essential role in decreasing the cost and time in inventing a new drug. This manuscript presents a novel computational method to study the passive permeation of small molecule drugs based on the inhomogeneous solubility-diffusion model. The multidimensional free energy surface of the drug transiting through a lipid bilayer is computed with transition-tempered metadynamics that accurately captures the mechanisms of passive permeation. The permeability is computed by following the diffusion motion of the drug molecules along the minimal free energy path found on the multidimensional free energy surface. This computational method is assessed by studying the permeability of five small molecule drugs (ketoprofen, naproxen, metoprolol, propranolol, and salicylic acid). The results demonstrate a remarkable agreement between the computed permeabilities and those measured with the intestinal assay. The <i>in silico</i> method reported in this manuscript also reproduces the permeability measured from the intestinal assay (<i>in vivo</i>) better than the cell-based assays (e.g., PAMPA and Caco-2) do. In addition, the multidimensional free energy surface reveals the interplay between the structure of the small molecule and its permeability, shedding light on strategies of drug optimization. Permeation ; Chemistry ; Permeability (electromagnetism) ; Polar surface area ; Metadynamics ; Molecule ; Lipid bilayer ; Chemical physics ; Passive transport ; Molecular dynamics ; Small molecule ; Biophysics ; Membrane ; Materials science ; Computational chemistry ; Organic chemistry ; Biochemistry Analytical Chemistry and Chromatography ; Surfactants and Colloidal Systems ; Drug Transport and Resistance Mechanisms
Authors: Hewen Zheng | Qiannan Li | Yeqing Ling | Mamdouh Omran | Lei Gao | Guo Chen
Source: Journal of Materials Research and Technology (article, 2021-05-26)
Field: Chemistry — Organic Chemistry

Optimisation on the microwave drying of ammonium polyvanadate (APV)- based on a kinetic study Vanadium pentoxide (V2O5) is one of the fundamental materials applied in the productions of batteries, vanadium-aluminium alloys, biomedicine, catalysis, etc. High purity V2O5 can be prepared from an intermediate product, namely ammonium polyvanadate (APV), using roasting after a drying process. In this paper, microwave heating was used as an alternative drying option for APV, which has advantages including selective heating, high heating efficiency, energy-saving, and environmental protection. The authors investigated the microwave heating characteristics of APV and discussed the effects of microwave power, the mass of APV, and initial water content on the efficiency of microwave drying. The dynamic analysis of the APV microwave drying process was also carried out. Four groups of thin-layer drying dynamic models, namely Modified-Page model, Verma model, Sickmplified-Fick's-diffusion model, and Two-term-exponential model, were fitted with the experimental data. Through comparison, the Modified Page model could better describe the microwave drying process of APV. Microwave ; Materials science ; Pentoxide ; Vanadium ; Roasting ; Aluminium ; Microwave heating ; Diffusion ; Process engineering ; Analytical Chemistry (journal) ; Chemical engineering ; Thermodynamics ; Composite material ; Metallurgy ; Chromatography ; Chemistry Microwave-Assisted Synthesis and Applications ; Metallurgical Processes and Thermodynamics ; Food Drying and Modeling
Authors: Jie Xiao | Jiaxiang Zhang | Lun Pan | Chengxiang Shi | Xiangwen Zhang | Ji‐Jun Zou
Source: Transactions of Tianjin University (article, 2021-06-02)
Field: Materials Science — Materials Chemistry

Photocatalytic Synthesis of High-Energy-Density Fuel: Catalysts, Mechanisms, and Challenges Abstract High-energy-density liquid hydrocarbon fuels are generally synthesized using various chemical reactions to improve the performance (e.g., range, load, speed) of aerospace vehicles. Compared with conventional fuels, such as aviation kerosene and rocket kerosene, these liquid hydrocarbon fuels possess the advantages of high-energy-density and high volumetric calorific value; therefore, the fuels have important application value. The photocatalytic process has shown great potential for the synthesis of a diverse range of fuels on account of its unique properties, which include good efficiency, clean atomic economy, and low energy consumption. These characteristics have led to the emergence of the photocatalytic process as a promising complement and alternative to traditional thermocatalytic reactions for fuel synthesis. Extensive effort has been made toward the construction of catalysts for the multiple photocatalytic syntheses of high-energy-density fuels. In this review, we aim to summarize the research progress on the photocatalytic synthesis of high-energy-density fuel by using homogeneous and heterogeneous catalytic reactions. Specifically, the synthesis routes, catalysts, mechanistic features, and future challenges for the photocatalytic synthesis of high-energy-density fuel are described in detail. The highlights of this review not only promote the development of the photocatalytic synthesis of high-energy-density fuel but also expand the applications of photocatalysis to other fields. Graphic abstract Photocatalysis ; Kerosene ; Catalysis ; Liquid fuel ; Materials science ; Aerospace ; Process engineering ; Waste management ; Chemical engineering ; Nanotechnology ; Environmental science ; Combustion ; Chemistry ; Organic chemistry ; Engineering ; Aerospace engineering Catalytic Processes in Materials Science ; Advanced Photocatalysis Techniques ; Electrocatalysts for Energy Conversion
Authors: Thiago S. Silva | Fernando Coelho
Source: Beilstein Journal of Organic Chemistry (review, 2021-07-07)
Field: Chemistry — Organic Chemistry

Methodologies for the synthesis of quaternary carbon centers via hydroalkylation of unactivated olefins: twenty years of advances Olefin double-bond functionalization has been established as an excellent strategy for the construction of elaborate molecules. In particular, the hydroalkylation of olefins represents a straightforward strategy for the synthesis of new C(sp<sup>3</sup>)-C(sp<sup>3</sup>) bonds, with concomitant formation of challenging quaternary carbon centers. In the last 20 years, numerous hydroalkylation methodologies have emerged that have explored the diverse reactivity patterns of the olefin double bond. This review presents examples of olefins acting as electrophilic partners when coordinated with electrophilic transition-metal complexes or, in more recent approaches, when used as precursors of nucleophilic radical species in metal hydride hydrogen atom transfer reactions. This unique reactivity, combined with the wide availability of olefins as starting materials and the success reported in the construction of all-carbon C(sp<sup>3</sup>) quaternary centers, makes hydroalkylation reactions an ideal platform for the synthesis of molecules with increased molecular complexity. Electrophile ; Chemistry ; Olefin fiber ; Combinatorial chemistry ; Reactivity (psychology) ; Hydride ; Organic synthesis ; Nucleophile ; Organic chemistry ; Metal ; Catalysis Catalytic C–H Functionalization Methods ; Radical Photochemical Reactions ; Catalytic Alkyne Reactions
Authors: Sivakumar Sekharan | Xuetao Liu | Zhuocen Yang | Xiang Liu | Li Deng | Shigang Ruan | Yuriy A. Abramov | Guangxu Sun | Sizhu Li | Tian Zhou | Baime Shi | Qun Zeng | Qiao Zeng | Chao Chang | Yingdi Jin | Xuekun Shi
Source: RSC Advances (article, 2021-01-01)
Field: Materials Science — Materials Chemistry

Selecting a stable solid form of remdesivir using microcrystal electron diffraction and crystal structure prediction Therapeutic options in response to the coronavirus disease 2019 (COVID-19) outbreak are urgently needed. In this communication, we demonstrate how to support selection of a stable solid form of an antiviral drug remdesivir in quick time using the microcrystal electron diffraction (MicroED) technique and a cloud-based and artificial intelligence implemented crystal structure prediction platform. We present the MicroED structures of remdesivir forms II and IV and conclude that form II is more stable than form IV at ambient temperature in agreement with experimental observations. The combined experimental and theoretical study can serve as a template for formulation scientists in the pharmaceutical industry. Coronavirus disease 2019 (COVID-19) ; Diffraction ; Crystal structure ; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ; Crystal (programming language) ; Electron diffraction ; Materials science ; Nanotechnology ; Coronavirus ; Electron ; Crystallography ; Chemistry ; Computer science ; Physics ; Disease ; Medicine ; Optics ; Infectious disease (medical specialty) Enzyme Structure and Function ; Crystallography and molecular interactions ; X-ray Diffraction in Crystallography
Authors: Takashi Miyake | Yosuke Harashima | Taro Fukazawa | H. Akai
Source: Science and Technology of Advanced Materials (article, 2021-06-04)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Understanding and optimization of hard magnetic compounds from first principles First-principles calculation based on density functional theory is a powerful tool for understanding and designing magnetic materials. It enables us to quantitatively describe magnetic properties and structural stability, although further methodological developments for the treatment of strongly correlated 4f electrons and finite-temperature magnetism are needed. Here, we review recent developments of computational schemes for rare-earth magnet compounds, and summarize our theoretical studies on Nd<sub>2</sub>Fe<sub>14</sub>B and <i>R</i>Fe<sub>12</sub>-type compounds. Effects of chemical substitution and interstitial dopants are clarified. We also discuss how data-driven approaches are used for studying multinary systems. Chemical composition can be optimized with fewer trials by the Bayesian optimization. We also present a data-assimilation method for predicting finite-temperature magnetization in wide composition space by integrating computational and experimental data. JavaScript ; Zoom ; Computer science ; Feature (linguistics) ; Computer graphics (images) ; Programming language ; Theoretical computer science ; Algorithm ; Physics ; Optics ; Linguistics ; Philosophy Magnetic Properties of Alloys ; Magnetic and transport properties of perovskites and related materials ; Machine Learning in Materials Science