jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Anna N. Morozovska | Eugene А. Eliseev | Yulian M. Vysochanskii | Viktoria V. Khist | Dean R. Evans
Source: arXiv (Cornell University) (preprint, 2022-09-21)
Field: Materials Science — Materials Chemistry

Screening-Induced Phase Transitions in Core-Shell Ferroic Nanoparticles Using the Landau-Ginzburg-Devonshire approach, we study screening-induced phase transitions in core-shell ferroic nanoparticles for three different shapes: an oblate disk, a sphere, and a prolate needle. The nanoparticle is made of a ferroic CuInP2S6 core and covered by a "tunable" screening shell made of a phase-change material with a conductivity that varies as the material changes between semiconductor and metallic phases. We reveal a critical influence of the shell screening length on the phase transitions and spontaneous polarization of the nanoparticle core. Since the tunable screening shell allows the control of the polar state and phase diagrams of core-shell ferroic nanoparticles, the obtained results can be of particular interest for applications in nonvolatile memory cells. Nanoparticle ; Materials science ; Shell (structure) ; Condensed matter physics ; Polar ; Polarization (electrochemistry) ; Phase (matter) ; Phase transition ; Core (optical fiber) ; Semiconductor ; Prolate spheroid ; Nanotechnology ; Chemical physics ; Optoelectronics ; Composite material ; Chemistry ; Physics Phase-change materials and chalcogenides ; Liquid Crystal Research Advancements ; Solid-state spectroscopy and crystallography
Authors: Marco Bertolini | Linlin Zhao | Djork-Arné Clevert | Floriane Montanari
Source: ChemRxiv (preprint, 2022-03-06)
Field: Materials Science — Materials Chemistry

Beyond Atoms and Bonds: Contextual Explainability via Molecular Graphical Depictions The field of explainable AI applied to molecular property prediction models has often been reduced to deriving atomic contributions. This has impaired the interpretability of such models, as chemists rather think in terms of larger, chemically meaningful structures, which often do not simply reduce to the sum of their atomic constituents. We develop an explanatory framework yielding both local as well as more complex structural attributions. We derive such contextual explanations in pixel space, exploiting the property that a molecule is not merely encoded through a collection of atoms and bonds, as is the case for string- or graph-based approaches. We provide evidence that the proposed explanation method satisfies desirable properties, namely sparsity and invariance with respect to the molecule’s symmetries. Interpretability ; Property (philosophy) ; Homogeneous space ; Computer science ; String (physics) ; Theoretical computer science ; Space (punctuation) ; Theoretical physics ; Graph ; Attribution ; Molecule ; Field (mathematics) ; Chemical physics ; Computational chemistry ; Chemistry ; Artificial intelligence ; Mathematics ; Physics ; Pure mathematics ; Epistemology ; Quantum mechanics ; Psychology ; Philosophy Machine Learning in Materials Science ; Computational Drug Discovery Methods
Authors: A. Luba | O. Pavlyuk | E. Goreshnik
Source: Visnyk of the Lviv University Series Chemistry (article, 2022-01-01)
Field: Chemistry — Inorganic Chemistry

Copper(I) halide complexes with n,n’-diallylthiomorpholinium chloride: synthesis and crystal structure By means of alternating current electrochemical technique, basing on ethanolic solutions of CuCl 2 ·2H 2 O or CuBr 2 and N,N’-diallylthiomorpholinium chloride, the two isostructural s-complexes of [C 4 H 8 NS(C 3 H 5 ) 2 Cu Hal 2 ] composition were obtained in a single crystal form and characterized by X-ray single crystal method: sp. gr. P 2 1 / c , Z = 4, Hal = Cl ( І ) – a = 7.7763(4), b = 13.1892(5), c = 13.1761(6) Å, β = 103.470(5)°, V = 1314.2(1) Å 3 , r calc. = 1.611 g/сm 3 , m (MoK a ) = 2.20 mm −1 , q max. = 28.8°, 10141 measured, 2659 used reflections, R ( F 2 ) = 0.032, S = 1.07; Hal = 1,04Br/0,96Cl ( ІІ ) – a = 7.9771(3), b = 13.2391(5), c = 13.1422(5) Å, β = 103.942(4), V = 1347.1(1) Å 3 , r calc. = 1.80 g/см 3 , m (MoK a ) = 5.02 mm −1 , q max. = 29.0°, 21269 measured, 2772 used reflections, R ( F 2 ) = 0.027, S = 1.08. In the crystal structure of the studied compounds, the trigonal-pyramidal coordination environment of Cu(I) includes sulfur atoms of the organic cation and three chloride anions (compound I ) or chloride/bromide mixture (compound II ). Atoms occupying position Hal (2) perform a bridging function and connect individual coordination polyhedrons into dimeric topological units {L 2 Cu 2 Hal 4 }. These dimers through hydrogen bonding are linked into a three-dimensional framework. None of the available allylic groups of the N,N’-diallylthiomorpholinium cation are coordinated to the copper(I) ion. In our opinion, this feature of the discussed crystal structure of [(C 4 H 8 NS(C 3 H 5 ) 2 )Cu Hal 2 ] compounds is explained by the influence of competition between the sulfur atom and the C=C bond of the allyl group of the cation during complexation in solution and the redistribution of electron density in the crystal structure of solid compounds due to hydrogen contacts C–H… Hal . Keywords : N,N’-diallylthiomorpholinium; copper(І); s-complexes; crystal structure. Isostructural ; Chemistry ; Crystal structure ; Crystallography ; Halide ; Bromide ; Copper ; Chloride ; Electrochemistry ; Hydrogen bond ; Stereochemistry ; Molecule ; Inorganic chemistry ; Electrode ; Organic chemistry ; Physical chemistry Crystal structures of chemical compounds ; Organometallic Compounds Synthesis and Characterization ; Metal complexes synthesis and properties
Authors: Paweł Twardowski | Maciej Tabaszewski | Agata Felusiak | Piotr Kieruj | Martyna Wiciak-Pikuła | Jakub Czyżycki
Source: Advances in Science and Technology – Research Journal (article, 2022-11-29)
Field: Materials Science — Materials Chemistry

Identification of Tool Wear During Cast Iron Drilling Using Machine Learning Methods The paper concerns the monitoring of the tool condition on the basis of vibration acceleration signals. The cutting edge condition is determined by wear on the flank surface of the drill. As tools, a twist drills made of cemented carbide were used. A gray cast iron plate EN-GJL-250 was used as the workpiece. Based on the signals, appropriate measures correlated with the wear of the drill were developed. By using binary decision trees CART (Classification and Regression Tree) with two data partitioning methods (Gini index and Cross-entropy), the original number of measures was limited to the most common and those that provide the smallest error in the tool condition classification. Comparing the results for the best trees built with different measures of partition quality in nodes for all available data indicated a better performance of the Gini index. The applied solution allows for high accuracy of the tool classification. The solution is to be used in industry. Cast iron ; Identification (biology) ; Drilling ; Computer science ; Metallurgy ; Engineering ; Manufacturing engineering ; Materials science ; Biology Metal Alloys Wear and Properties ; Advanced machining processes and optimization ; Metallurgy and Material Forming
Authors: Meryem Pir | Fatma Budak
Source: Düzce Üniversitesi Bilim ve Teknoloji Dergisi (article, 2022-04-29)
Field: Chemistry — Organic Chemistry

(3-(4-chlorophenyl)-4,5-dihydroisoxazole-4,5-diyl)dimethanol Compound: Antibacterial Activity, Antifungal Activity and Calculated Structural Parameters We intended to quantify the antibacterial and antifungal activity results of 4,5-dihydroisoxazole dimethanol compound (1a) against several bacteria and fungi and also calculate some structural parameters (theoretical descriptors) of compound (1a) with this work. Microdilution broth procedures were studied using microdilution wells for the minimal inhibitory concentrations (MICs) test. Compound (1a) exhibited fair activities against all the bacteria and fungi. Compound (1a) has been a good result (MIC = 50 µg/ml) against particularly P. aeruginosa. The structure of compound (1a) was drawn, and geometrical optimization was done using the Ab initio (RHF/3-21G) level. Broth microdilution ; Antifungal ; Minimum inhibitory concentration ; Bacteria ; Microbiology ; Chemistry ; Antibacterial activity ; Stereochemistry ; In vitro ; Biology ; Biochemistry Synthesis and biological activity ; Phenothiazines and Benzothiazines Synthesis and Activities ; Fungal Plant Pathogen Control
Authors: K. M. Faridul Hasan | Péter György Horváth | Miklós Bak | László Bejó | Tibor Alpár
Source: Research Square (preprint, 2022-05-23)
Field: Materials Science — Polymers and Plastics

Flame retardant hybrid composite manufacturing through reinforcing lignocellulosic and carbon fibers reinforced with epoxy resin (F@LC) Abstract Novel flame retardant hybrid composites were developed from lignocellulosic and carbon fibers reinforced with epoxy resin using hot pressing technology. The size of the lignocellulosic fibers was within 0.045 to 0.8 mm and carbon fibers ranged from 5 mm to 8 mm. The nominal thickness of the composites was 10 mm, whereas the nominal density was 730 kg/m 3 . Composite dimensions were 400 mm × 400 mm. The developed panels were tested for internal bonding strength and flexural properties to investigate their mechanical performance. Furthermore, SEM (Scanning electron microscopy) test was conducted to examine the morphologies of the products before and after fracture and found substantial quantities of both types of fiber in the composite system. The EDX (Energy disruptive X-ray) analysis also displayed the chemical elements present in the developed products. Moreover, an FTIR (Fourier transform infrared spectroscopy) study showed strong chemical interactions among the lignocellulosic and carbon fibers with the thermosetting epoxy polymers. The flame retardancy tests of the composite materials also showed significant thermal stability, especially after loading carbon fibers in the composite system. Moreover, dimensional stability showed an improving trend with the increase of carbon fibers as the reinforcement. Overall, the composite materials developed using lignocellulosic and carbon fibers with epoxy resin is showing a novel route to develop composites with high mechanical performance and considerable flame retardancy. Epoxy ; Fire retardant ; Composite number ; Materials science ; Composite material ; Composite epoxy material ; Carbon fibers ; Gelcoat ; Pulp and paper industry ; Engineering Natural Fiber Reinforced Composites ; Additive Manufacturing and 3D Printing Technologies ; Flame retardant materials and properties
Authors: Mr Patil | I Z Mukti | D Biswas | D P Hughes | M Salathe
Source: International Research Journal of Modernization in Engineering Technology and Science (article, 2022-09-20)
Field: Chemistry — Analytical Chemistry

PLANT LEAF DISEASE CLASSIFICATION USING CONVOLUTIONAL NEURAL NETWORKS (CNN) Different diseases can significantly reduce crop yields, putting our food supply at risk. Therefore, it is vital and necessary to correctly identify plant illnesses. Traditional categorization techniques like laboratory testing and naked-eye assessment have a number of limitations, including the fact that they take a lot of time and are subjective. Convolutional neural networks (CNN)-based deep learning (DL) techniques are now often employed in the categorization of plant diseases. They have partially eliminated the issues with conventional categorization techniques. In this study, we examined the most current CNN networks that are significant for classifying plant leaf diseases. We provided a summary of the DL concepts used to categorise plant diseases. In addition, we reviewed CNN's difficulties and their corresponding solutions for classifying plant diseases. Convolutional neural network ; Computer science ; Artificial intelligence ; Pattern recognition (psychology) Spectroscopy and Chemometric Analyses
Authors: Benjamin P. Robertson | Lena Hoover | Gerald Rott | Michelle Quan | Michelle A. Calabrese
Source: Research Square (preprint, 2022-12-22)
Field: Materials Science — Biomaterials

Development of microbeads from unmodified biomass with tunable size and competitive mechanical properties Abstract Despite national and international regulations, plastic microbeads are still widely used in personal care and consumer products (PCCPs) as exfoliants and rheological modifiers, causing significant microplastic pollution following use. As a sustainable alternative, microbeads were produced by extrusion of biomass solutions and precipitation into anti-solvent. Despite using novel blends of biodegradable, non-derivatized biomass including cellulose and Kraft lignin, resulting microbeads are within the shape, size, and stiffness range of commercial plastic microbeads, even without crosslinking. Solution processability and resulting bead shape and Young’s modulus can be tuned via biomass source, concentration, and degree of polymerization; biomass concentration, extrusion geometry, and precipitation and extraction conditions control the bead size. Lignin incorporation reduces the solution viscosity, which improves processability but also produces flatter beads with higher moduli than cellulose-only microbeads. While some lignin leaches from the beads when stored in water, adding surfactants like sodium dodecyl sulfate suppresses this effect, resulting in good mechanical stability over two months with no noticeable structural degradation. The stability of these mixed-source biomass microbeads - despite the absence of chemical crosslinking or derivatization - makes this route a promising, robust approach for obtaining environmentally-benign microbeads of tunable size and stiffness for use in PCCPs. Biomass (ecology) ; Extrusion ; Materials science ; Cellulose ; Lignin ; Chemical engineering ; Bead ; Rheology ; Sodium dodecyl sulfate ; Pulp and paper industry ; Composite material ; Chemistry ; Chromatography ; Organic chemistry biodegradable polymer synthesis and properties ; Microplastics and Plastic Pollution ; Natural Fiber Reinforced Composites
Authors: Mohsen Ostad Shabani | Amir Baghani | Mohammad Reza Rahimipour | Mansour Razavi | Mohammad Zakeri | Fatemeh Heydari
Source: Kovove Materialy-Metallic Materials (article, 2022-11-02)
Field: Materials Science — General Materials Science

The influence of the casting method on mechanical properties of A356-Al2O3 nanocompositeEffect of boron addition on microstructure and toughness of Ti-containing weld metals This study investigates the effect of casting methods, content and size of reinforcing particles and heat treatment on the mechanical properties of A356-Al2O3 composite. First, composite samples were made by three methods: gravity sand casting, squeeze casting, and semi-solid compo casting, and then some of them were subjected to the T6 heat treatment. Test specimens were extracted from the samples, and their tensile and yield strength, elongation, and porosity were measured, analyzed, and compared. In addition, the microstructures of composites made by nano and micro scale reinforcing particles were studied and compared. It was concluded that the superior mechanical properties were obtained in samples made by semi-solid compo casting using nanoscale reinforcing secondary phase and subjected to the T6 heat treatment. Microstructure ; Materials science ; Metallurgy ; Boron ; Casting ; Toughness ; Welding ; Chemistry Material Properties and Applications ; Intermetallics and Advanced Alloy Properties ; Advanced materials and composites
Authors: Hiroshi Nakajima | Hirofumi Tsukasaki | Takuya Kimura | Atsushi Sakuda | Akitoshi Hayashi | Shigeo Mori
Source: Microscopy and Microanalysis (article, 2022-07-22)
Field: Materials Science — Materials Chemistry

Local Structure and Crystallization Process in Mechanochemically Prepared Na3PS4 All-solid-state batteries have attracted much attention due to their safety and high density. To reduce the cost of batteries, utilizing abundant resources is advantageous. The ranking of Clarke numbers, which is a measure of the crustal abundance ratio of each element, suggests that sodium (Na) is about 1,000 times larger than lithium (Li). Thus, Sodium batteries are expected to be next-generation storage batteries that have safety, economy, and high energy density. To realize this battery, it is essential to develop a solid electrolyte that exhibits high sodium ionic conductivity at room temperature. Crystallization ; Materials science ; Process (computing) ; Chemical engineering ; Crystallography ; Chemistry ; Computer science ; Engineering Solid-state spectroscopy and crystallography ; Advanced Battery Materials and Technologies ; Crystal Structures and Properties
Authors: V. Vignesh | S. Vijayan | G. Selvakumar | D. Prince Sahaya Sudherson
Source: Bulletin of the Chemical Society of Ethiopia (article, 2022-07-15)
Field: Chemistry — Analytical Chemistry

Experimental investigation and mechanism analysis: Effect of concentration and temperature on the heat transfer characteristics of novel MWCNT-mustard oil nanofluid ABSTRACT. The bio-oils as alternative lubricating fluid are potential solution for the automotive and industrial mechanical systems. The development of novel renewable and non-toxic bio-oils with better heat transfer distinctiveness will strengthen the economy of farmers in the agricultural based countries. The most innovative approach to improve the heat transfer characteristics of bio-oils is converting it into nanofluids by dispersing nanomaterials which has extremely high heat transfer characteristics. In this study, MWCNT-Mustard oil nanofluids were formulated through ultrasonication and their dispersion stability was estimated through Zeta-potential technique. The thermal stability of the MWCNT-Mustard oil nanofluids are estimated through thermogravimetric analysis and concentration and temperature dependent density, thermal conductivity and specific heat capacity of MWCNT-Mustard oil nanofluids are also determined and their characteristics are discussed. The heat transfer characteristics of MWCNT-Mustard oil nanofluids observed through the heat pipe test rig at different inlet temperatures, mass flow rate of nanofluids and Reynolds number. The results exhibits that the dispersion of MWCNT enhances the heat transfer characteristics of MWCNT-Mustard oil nanofluids.&#x0D; &#x0D; KEY WORDS: Non-toxic bio-oils, Nanomaterials, Nanofluids, Thermogravimetric analysis, MWCNT, Mustard oil&#x0D; Bull. Chem. Soc. Ethiop. 2022, 36(3), 675-686. &#x0D; DOI: https://dx.doi.org/10.4314/bcse.v36i3.16 Nanofluid ; Thermogravimetric analysis ; Chemistry ; Zeta potential ; Heat transfer ; Dispersion stability ; Chemical engineering ; Dispersion (optics) ; Nanomaterials ; Composite material ; Nanoparticle ; Materials science ; Thermodynamics ; Organic chemistry ; Polymer Petroleum Processing and Analysis ; Lubricants and Their Additives ; Nanofluid Flow and Heat Transfer
Authors: Hun Lee | Sehyuk Lee | Soonsung So | Sang-Hyuk Park | Austin J. Minnich | Joo‐Hyoung Lee | Young-Dahl Jho
Source: Journal of Applied Physics (article, 2022-02-18)
Field: Materials Science — Materials Chemistry

Enhancing anisotropy of thermal conductivity based on tandem acoustic Bragg reflectors Thermal metamaterials have emerged as one of the latest research topics in applied science due to breakthrough advantages in modifying conductive heat flux. An acoustic Bragg reflector (ABR), composed of alternating arrays of two materials with contrasting acoustic impedances, is anticipated to coherently manipulate the transport properties of thermally important phonon branches by attaining interface roughness close to the monoatomic scale. However, there is a lack of research on how a narrow portion of the phononic band of a particular ABR can be extended to cover the entire thermal spectrum. Here, we report a modeling study of thermal transport using ABR, representatively based on GaAs/AlAs, GaN/AlN, or HfO2/SiO2 superlattices. Our calculations show that the anisotropy of thermal conductivity in HfO2/SiO2 can be significantly improved by tandemizing four different ABR layers, thus approaching the theoretically anticipated values based on monolayered materials. This work demonstrates how the tandem ABR can expand forbidden phononic bands beyond that occupied by a single ABR and proposes a practical strategy for realizing spectrally functionalized thermal properties from compound semiconductor materials that can be directly integrated into the existing device fabrication processes. Materials science ; Thermal conductivity ; Anisotropy ; Phonon ; Fabrication ; Metamaterial ; Electrical conductor ; Optoelectronics ; Semiconductor ; Thermal ; Acoustic impedance ; Optics ; Condensed matter physics ; Acoustics ; Composite material ; Physics ; Ultrasonic sensor Thermal properties of materials ; Thermal Radiation and Cooling Technologies ; Acoustic Wave Phenomena Research
Authors: Handong Ling | Linda Hung | Joseph P. Montoya | Muratahan Aykol
Source: ChemRxiv (preprint, 2022-03-22)
Field: Materials Science — Materials Chemistry

Solving Inorganic Crystal Structures from X-ray Powder Diffraction Using a Generative First-Principles Framework X-ray powder diffraction (XRD) is a powerful structure characterization technique, but solving unknown inorganic crystal structures from powder diffraction patterns can often be labor-intensive or speculative. We introduce an Automated XRD to Structure (AXS) solution method based on the crystal symmetry obtained from XRD patterns, an efficient search of candidate structures spanning the available degrees of freedom, and density functional theory (DFT). This methodology is completely agnostic to structural prototypes and robust in solving inorganic structures of various chemistries, crystal systems, and unit cell sizes; 92% of all crystal structures were accurately determined from the simulated XRD patterns in our benchmark set. In addition, we demonstrate the efficacy of this methodology on experimental XRD patterns by solving the crystal structures of Li8HfO6, Li3CrO4, and LiFeO2. Diffraction ; Benchmark (surveying) ; Crystal structure ; Crystal (programming language) ; Materials science ; Powder diffraction ; Crystallography ; Density functional theory ; X-ray crystallography ; Set (abstract data type) ; Computer science ; Physics ; Chemistry ; Computational chemistry ; Optics X-ray Diffraction in Crystallography ; Machine Learning in Materials Science ; Zeolite Catalysis and Synthesis