jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Feier Hou
Source: Communications Chemistry (article, 2021-09-16)
Field: Materials Science — Materials Chemistry

Open questions on physical chemistry of crystal growth from congruent melts Crystallization is observed in both nature and in the lab, and is critical to diverse areas of science and technology. Here, the author summarizes the theories that have been proposed to explain crystal growth from melts, and raises some open questions that remain. Crystallization is observed in both nature and in the lab, and is critical to diverse areas of science and technology. Here, the author summarizes the theories that have been proposed to explain crystal growth from melts, and raises some open questions that remain. Crystallization ; Crystal growth ; Crystal (programming language) ; Physical science ; Epistemology ; Theoretical physics ; Chemistry ; Physics ; Computer science ; Thermodynamics ; Psychology ; Philosophy ; Crystallography ; Mathematics education Material Dynamics and Properties ; nanoparticles nucleation surface interactions ; Crystallization and Solubility Studies
Authors: Weihang Dong | Xiaolei Guo | Yong Hu | Jinxin Wang | Guangjun Tian
Source: BioResources (article, 2021-02-05)
Field: Materials Science — Polymers and Plastics

Discrete wavelet transformation and genetic algorithm – back propagation neural network applied in monitoring woodworking tool wear conditions in the milling operation spindle power signals Tool wear conditions monitoring is an important mechanical processing system that can improve the processing quality of wood plastic composite furniture and reduce industrial energy consumption. An appropriate signal, feature extraction method, and model establishment method can effectively improve the accuracy of tool wear monitoring. In this work, an effective method based on discrete wavelet transformation (DWT) and genetic algorithm (GA) – back propagation (BP) neural network was proposed to monitor the tool wear conditions. The spindle power signals under different spindle speeds, depths of milling, and tool wear conditions were collected by power sensors connected to the machine tool control box. Based on the feature extraction method, the approximate coefficients of spindle power signal were extracted by DWT. Then, the extracted approximate coefficients, spindle speeds, depths of milling, and tool wear conditions were taken as samples to train the monitoring model. Threshold and weight of BP neural network were optimized by GA, and the accuracy of monitoring model established by the GA – BP neural network can reach 100%. Thus, the proposed monitoring method can accurately monitor tool wear conditions with different milling parameters, which can achieve the purpose of improving the processing quality of wood plastic composite furniture and reducing energy consumption. Artificial neural network ; Tool wear ; Genetic algorithm ; Energy (signal processing) ; Machine tool ; Power (physics) ; Milling cutter ; SIGNAL (programming language) ; Feature (linguistics) ; Feature extraction ; Energy consumption ; Transformation (genetics) ; Discrete wavelet transform ; Signal processing ; Engineering ; Wavelet transform ; Wavelet ; Computer science ; Machining ; Mechanical engineering ; Artificial intelligence ; Electronic engineering ; Digital signal processing ; Machine learning ; Mathematics Textile materials and evaluations ; Advanced machining processes and optimization ; Industrial Vision Systems and Defect Detection
Authors: Majeda Khraisheh | Fares Almomani | Gavin Walker
Source: Energies (article, 2021-01-25)
Field: Chemistry — Inorganic Chemistry

High Purity/Recovery Separation of Propylene from Propyne Using Anion Pillared Metal-Organic Framework: Application of Vacuum Swing Adsorption (VSA) Propylene is one of the world’s most important basic olefin raw material used in the production of a vast array of polymers and other chemicals. The need for high purity grade of propylene is essential and traditionally achieved by the very energy-intensive cryogenic separation. In this study, a pillared inorganic anion SIF62− was used as a highly selective C3H4 due to the square grid pyrazine-based structure. Single gas adsorption revealed a very high C3H4 uptake value (3.32, 3.12, 2.97 and 2.43 mmol·g−1 at 300, 320, 340 and 360 K, respectively). The values for propylene for the same temperatures were 2.73, 2.64, 2.31 and 1.84 mmol·g−1, respectively. Experimental results were obtained for the two gases fitted using Langmuir and Toth models. The former had a varied degree of representation of the system with a better presentation of the adsorption of the propylene compared to the propyne system. The Toth model regression offered a better fit of the experimental data over the entire range of pressures. The representation and fitting of the models are important to estimate the energy in the form of the isosteric heats of adsorption (Qst), which were found to be 45 and 30 kJ·Kmol−1 for propyne and propylene, respectively. A Higher Qst value reveals strong interactions between the solid and the gas. The dynamic breakthrough for binary mixtures of C3H4/C3H6 (30:70 v/v)) were established. Heavier propylene molecules were eluted first from the column compared to the lighter propyne. Vacuum swing adsorption was best suited for the application of strongly bound materials in adsorbents. A six-step cycle was used for the recovery of high purity C3H4 and C3H6. The VSA system was tested with respect to changing blowdown time and purge time as well as energy requirements. It was found that the increase in purge time had an appositive effect on C3H6 recovery but reduced productivity and recovery. Accordingly, under the experimental conditions used in this study for VSA, the purge time of 600 s was considered a suitable trade-off time for purging. Recovery up to 99%, purity of 98.5% were achieved at a purge time of 600 s. Maximum achieved purity and recovery were 97.4% and 98.5% at 100 s blowdown time. Energy and power consumption varied between 63–70 kWh/ton at the range of purge and blowdown time used. The VSA offers a trade-off and cost-effective technology for the recovery and separation of olefins and paraffin at low pressure and high purity. Propyne ; Adsorption ; Air separation ; Sorption ; Chemistry ; Materials science ; Analytical Chemistry (journal) ; Physical chemistry ; Organic chemistry Metal-Organic Frameworks: Synthesis and Applications ; Covalent Organic Framework Applications ; Membrane Separation and Gas Transport
Authors: Katarzyna Wojdalska | Yujiao Dong | Jaana Vapaavuori
Source: Materials & Design (article, 2021-10-13)
Field: Chemistry — Organic Chemistry

Textile integrable mechanochromic strain sensor based on the interplay of supramolecular interactions Mechanochromic materials, when exposed to mechanical deformation, undergo a modification of optical properties. This behaviour can stem from either conformational rearrangements, disruptions of intermolecular interactions, or molecular structure changes affecting absorption, emission, or reflection abilities. Here reversible colour change of Disperse Red 1/polyvinylpyrrolidone films resulting from humidity annealing and subsequent stretching is reported. Due to the humidity-induced blue shift of the absorbance peak related to exciton coupling of the chromophores, the tone of films abruptly changes from red to orange. Upon stretching, the gradual disaggregation of the chromophores takes place and therefore the colour switches back to red in a stepless manner. Using either red–green–blue analysis of time lapse photography or UV–Visible measurements, this transformation, which is also well visible by the naked eye, can be followed with high accuracy. This work offers the opportunity to apply the strain sensor in humid environments to prevent the mechanical failures by showing a colour change in areas subjected to undesired stress. Moreover, dip-coating yarns with mechanochromic coating allows fabrication of functional yarns that change their colour based on their stretching state – thus enabling preparation of colour-changing stretchable textiles was demonstrated. Materials science ; Chromophore ; Absorbance ; Exciton ; Naked eye ; Coating ; Polyvinylpyrrolidone ; Supramolecular chemistry ; Intermolecular force ; Composite material ; Textile ; Optoelectronics ; Photochemistry ; Chemical engineering ; Optics ; Polymer chemistry ; Molecule ; Fluorescence ; Organic chemistry Polydiacetylene-based materials and applications ; Luminescence and Fluorescent Materials ; Photochromic and Fluorescence Chemistry
Authors: Nicolas Lebert | Nicolas Gay | Emmanuel Richaud
Source: Polymer Degradation and Stability (article, 2021-12-28)
Field: Materials Science — Polymers and Plastics

Mechanical and macromolecular changes during thermal degradation of polyphenylsulfone Rheometry ; Glass transition ; Materials science ; Molar mass ; Degradation (telecommunications) ; Composite material ; Modulus ; Strain (injury) ; Macromolecule ; Dynamic mechanical analysis ; Thermal ; Stress–strain curve ; Yield (engineering) ; Rheology ; Polymer ; Thermodynamics ; Chemistry ; Deformation (meteorology) Flame retardant materials and properties ; Polymer crystallization and properties ; Polymer Nanocomposites and Properties
Authors: Mutasem Sh. Alkhasawneh
Source: International Journal of Advanced Computer Science and Applications (article, 2021-01-01)
Field: Chemistry — Analytical Chemistry

Olive Oil Ripping Time Prediction Model based on Image Processing and Neural Network The agriculture sector in Jordan depends very much on planting the olive trees. More than ten million of olive trees are planted in the Jordanian soil. Olive fruit are harvested for two purposes; either to produce oil or to produce olive table (pickled olive). Olive fruit harvesting time for extracting the oil from the olive fruit is crucial. Hence, harvesting the olive fruit on ripping time gives the best amount and quality of oil. It also, could lose 15% to 20% of multiple values because of harvesting time. Olive fruit ripping time is varied since it depends on the rainfall, temperature and cultivation. A system to predict the optimal time for harvesting olive fruit for producing oil only is introduced. It based one Digital Image Processing (DIP) and artificial intelligent neural network. Moreover, four features were extracted from the olive fruit image based on the red, green and blue colors. The proposed system tested olive fruits in three stages of ripping time; under ripping, on ripping and over ripping. The classification accuracy achieved in the three stages was 97.51% in under ripping stage 95.10% in ripping stage, and 96.12% in over ripping stage. The proposed system performance was 96.14%. Olive oil ; Olive trees ; Image processing ; Artificial neural network ; Horticulture ; Computer science ; Artificial intelligence ; Biology ; Food science ; Image (mathematics) Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Advanced Chemical Sensor Technologies
Authors: Sho Hayakawa | Jake Isaacs | Hugh Medal | Haixuan Xu
Source: Computational Materials Science (article, 2021-04-09)
Field: Materials Science — Materials Chemistry

Atomistic modeling of meso-timescale processes with SEAKMC: A perspective and recent developments Kinetic Monte Carlo ; Saddle point ; Statistical physics ; On the fly ; Monte Carlo method ; Molecular dynamics ; Diffusion ; Computer science ; Nanotechnology ; Materials science ; Physics ; Chemistry ; Computational chemistry ; Thermodynamics ; Mathematics Machine Learning in Materials Science ; Nuclear Materials and Properties ; Advanced Chemical Physics Studies
Authors: Ahmed A. Bakhsh
Source: Energies (article, 2021-05-10)
Field: Materials Science — Polymers and Plastics

Gamma-Ray Modified Polymer/Clay Composites: Synthesis, Characterization, and Formulation Optimization Using Multivariate Calculus and Graph Theory To enhance the oxidation strength and crosslinking yield of ultrahigh molecular weight polyethylene (UHMWPE), its composites were prepared by mixing 1%, 2%, and 3% (by wt.) of magnesium silicate hydrous (sepiolite) during this study. These composites were irradiated with 25 kGy and 50 kGy of irradiation doses in the open air. Subsequent to irradiation, the composites were characterized for updates in structure, oxidation strength, and degree of crosslinking while estimating the values of oxidation index (OI), crosslink density (Gx), and percent crystallinity (Xc), respectively. The reaction of modified sepiolite (SP) on irradiating UHMWPE/SP composites was evident from the origination of peaks at Si-O, O-Si-O, Si-O-Si, and Mg-OH and stretching vibration at 974 cm−1, 1014 cm−1, and 1080 cm−1, respectively. In addition, the moderate negative correlation of OI (−0.46) and strong positive correlation of Gx (0.87) with the absorbed dose, made obvious from correlation analysis, confirmed the effectiveness of SP in enhancing the oxidation strength and crosslink density of UHMWPE. Furthermore, cluster analysis (CA) grouped the composites as low, moderate, and best based on dissimilarities, i.e., oxidation strength and crosslink density, which was further confirmed by principal component analysis (PCA). PCA also revealed that the OI, Gx, and absorbed dose were the active variables for this best group. After confirming the effectiveness of SP (as an active filler for enhancing the oxidation strength and crosslink density of UHMWPE) and recognizing the OI, Gx, and absorbed dose as active variables, the next step was to determine the necessary minimum amount of SP concentration and radiation dose required for the composite that outperforms all others. For this, a parametric graph theory and matrix approach was employed to rank the composites of the best group, revealing that the UHMWPE/SP composite with 1% (by wt.) of Si12O30Mg8(OH)4(H2O)4·8H2O and irradiated with 50 kGy of irradiation dose was the most suitable choice of all existing alternatives tested in this study. Although this is the first attempt, to the best of our knowledge, where a smart approach using multivariate calculus and decision-making tools was utilized for figuring the best UHMWPE composite formulation along with appropriate treatment dose, the results and methodology could be extended for any polymer of industrial scale, such as those used in medical implants, defense armor, bulletproof jackets, etc. Crystallinity ; Materials science ; Composite material ; Sepiolite ; Irradiation ; Polyethylene ; Izod impact strength test ; Nuclear chemistry ; Ultimate tensile strength ; Chemistry ; Organic chemistry Polymer Nanocomposites and Properties ; Polymer Nanocomposite Synthesis and Irradiation ; Conducting polymers and applications
Authors: Shirin Nasr Esfahani | enkatesan Muthukumar | Emma Regentova | Kazem Taghva | Mohamed B. Trabia
Source: International Journal of Advanced Computer Research (article, 2021-03-31)
Field: Chemistry — Analytical Chemistry

Food recognition improvement by using hyper-spectral imagery The primary objective of this paper, which is an extended version of the work presented in [1] is to determine the feasibility of exploiting spectral features in classification for automatic food recognition and quality/nutrition evaluation systems. Food intake is one of the necessary factors of human health, which means a human body should get enough nutrient and vitamins through one's daily diet in order to stay healthy. Nowadays people are more concerned about what they eat and how that affects their lifestyle. Furthermore, current eating behaviors and range of nutrition consumption has changed. Artificial intelligence ; Pattern recognition (psychology) ; Computer science Spectroscopy and Chemometric Analyses ; Remote-Sensing Image Classification ; Advanced Chemical Sensor Technologies
Authors: Szabolcs Horvát | Adeeba Fathima | Stefan Görlich | Michael Schlierf | Carl D. Modes | Nils Kröger
Source: Discover Materials (article, 2021-03-01)
Field: Materials Science — Biomaterials

Computational analysis of the effects of nitrogen source and sin1 knockout on biosilica morphology in the model diatom Thalassiosira pseudonana Abstract Morphogenesis of the silica based cell walls of diatoms, a large group of microalgae, is a paradigm for the self-assembly of complex 3D nano- and microscale patterned inorganic materials. In recent years, loss-of-function studies using genetic manipulation were successfully applied for the identification of genes that guide silica morphogenesis in diatoms. These studies revealed that the loss of one gene can affect multiple morphological parameters, and the morphological changes can be rather subtle being blurred by natural variations in morphology even within the same clone. Both factors severely hamper the identification of morphological mutants using subjective by-eye inspection of electron micrographs. Here we have developed automated image analysis for objectively quantifying the morphology of ridge networks and pore densities from numerous electron micrographs of diatom biosilica. This study demonstrated differences in ridge network morphology and pore density in diatoms growing on ammonium rather than nitrate as the sole nitrogen source. Furthermore, it revealed shortcomings in previous by-eye evaluation of the biosilica phenotype of the silicanin-1 knockout mutant. We anticipate that the computational methods established in the present work will be invaluable for unraveling genotype–phenotype correlations in diatom biosilica morphogenesis. Diatom ; Morphogenesis ; Morphology (biology) ; Phenotype ; Thalassiosira pseudonana ; Biology ; Mutant ; Gene ; Biophysics ; Botany ; Genetics ; Ecology ; Nutrient Diatoms and Algae Research ; Protist diversity and phylogeny ; Marine and coastal ecosystems
Authors: Eike Caldeweyher
Source: The Journal of Open Source Software (article, 2021-04-15)
Field: Materials Science — Materials Chemistry

kallisto: A command-line interface to simplify computational modelling and the generation of atomic features Caldeweyher, E., (2021). kallisto: A command-line interface to simplify computational modelling and the generation of atomic features. Journal of Open Source Software, 6(60), 3050, https://doi.org/10.21105/joss.03050 Interface (matter) ; Computer science ; Line (geometry) ; Open source ; Software ; Computational science ; Programming language ; Operating system ; Geometry ; Mathematics Machine Learning in Materials Science ; Catalysis and Oxidation Reactions ; Advanced Physical and Chemical Molecular Interactions
Authors: Nanjun Chen | Shenyang Hu | Wahyu Setyawan | Bharat Gwalani | Peter V. Sushko | Suveen N. Mathaudhu
Source: Modelling and Simulation in Materials Science and Engineering (article, 2021-12-20)
Field: Materials Science — Materials Chemistry

Formation and dissociation of shear-induced high-energy dislocations: insight from molecular dynamics simulations Abstract Solid-phase processing (SPP) allows one to create complex microstructures, not achievable via thermal processing alone. The resulting structures exhibit a rich palette of defects, both thermal and non-thermal, including defect substructures, such as dislocation networks. It is essential to understand the mechanisms of deformation and defect structure formation to guide SPP towards achieving desired microstructures and material properties. In this study, large-scale molecular dynamics simulations are used to investigate the effects of inhomogeneous strain distribution, that mimics deformation conditions of tribological tests, on the evolution of defects under severe shear deformation in polycrystalline Al. Analysis of defect nucleation and reaction pathways reveals that strong geometric constraints suppress the nucleation and slide of low energy dislocation 1/2⟨110⟩{111} but promote the nucleation and slide of high energy dislocations, such as <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:mfenced close="]" open="["> <mml:mrow> <mml:mn>1</mml:mn> <mml:mrow> <mml:mover accent="true"> <mml:mrow> <mml:mn>1</mml:mn> </mml:mrow> <mml:mo>¯</mml:mo> </mml:mover> </mml:mrow> <mml:mn>0</mml:mn> </mml:mrow> </mml:mfenced> </mml:math> (001) and 1/2 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:mfenced close="]" open="["> <mml:mrow> <mml:mn>1</mml:mn> <mml:mrow> <mml:mover accent="true"> <mml:mrow> <mml:mn>1</mml:mn> </mml:mrow> <mml:mo>¯</mml:mo> </mml:mover> </mml:mrow> <mml:mrow> <mml:mover accent="true"> <mml:mrow> <mml:mn>2</mml:mn> </mml:mrow> <mml:mo>¯</mml:mo> </mml:mover> </mml:mrow> </mml:mrow> </mml:mfenced> </mml:math> (1 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:mrow> <mml:mover accent="true"> <mml:mrow> <mml:mn>1</mml:mn> </mml:mrow> <mml:mo>¯</mml:mo> </mml:mover> </mml:mrow> </mml:math> 1). A rough contact surface, characteristic to tribological tests, imposes an inhomogeneous stress field leading to inhomogeneous defect substructures due to location-dependent activation of slip systems. The results suggest that high-energy dislocations can dominate the evolution of grain structures in highly constrained environments, which should be considered in modeling plastic deformation and grain refinement during SPP. Materials science ; Nucleation ; Dislocation ; Microstructure ; Dissociation (chemistry) ; Crystallography ; Thermodynamics ; Physical chemistry ; Physics ; Composite material ; Chemistry Microstructure and mechanical properties ; Metal and Thin Film Mechanics ; Aluminum Alloys Composites Properties
Authors: Liguo WANG | Lifeng Wang
Source: National Remote Sensing Bulletin (article, 2021-01-01)
Field: Chemistry — Analytical Chemistry

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