jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Hossein Rostamian | Mohammad Nader Lotfollahi
Source: Physica A Statistical Mechanics and its Applications (article, 2019-10-21)
Field: Chemistry — Spectroscopy

Statistical modeling of aspirin solubility in organic solvents by Response Surface Methodology and Artificial Neural Networks Solubility ; Ethyl acetate ; Response surface methodology ; Acetone ; Mean squared error ; Chemistry ; Correlation coefficient ; Coefficient of determination ; Artificial neural network ; Biological system ; Materials science ; Chromatography ; Mathematics ; Artificial intelligence ; Computer science ; Statistics ; Organic chemistry Analytical Chemistry and Chromatography ; Crystallization and Solubility Studies ; Analytical Methods in Pharmaceuticals
Authors: Yiming Zhang | Julian Evans | Shoufeng Yang
Source: Metallurgical and Materials Transactions A (article, 2019-10-30)
Field: Materials Science — Materials Chemistry

Exploring Correlations Between Properties Using Artificial Neural Networks Abstract The traditional aim of materials science is to establish the causal relationships between composition, processing, structure, and properties with the intention that, eventually, these relationships will make it possible to design materials to meet specifications. This paper explores another approach. If properties are related to structure at different scales, there may be relationships between properties that can be discerned and used to make predictions so that knowledge of some properties in a compositional field can be used to predict others. We use the physical properties of the elements as a dataset because it is expected to be both extensive and reliable and we explore this method by showing how it can be applied to predict the polarizability of the elements from other properties. Computer science ; Field (mathematics) ; Artificial neural network ; Polarizability ; Artificial intelligence ; Machine learning ; Mathematics ; Physics Machine Learning in Materials Science ; Mineral Processing and Grinding ; X-ray Diffraction in Crystallography
Authors: Alexander Hudson | Ricard Solà | Jorge T. Ueta | William Battell | Oliver Jamieson | Thomas Dunbar | Beatriz Maciá | Marloes Peeters
Source: Biomimetics (article, 2019-02-20)
Field: Chemistry — Analytical Chemistry

Synthesis of Optimized Molecularly Imprinted Polymers for the Isolation and Detection of Antidepressants via HPLC Antidepressants such as amitryptiline and fluoxetine are on the list of modern essential medicines of the World Health Organization. However, there are growing concerns regarding the ecological impact of these pharmaceuticals, leading to a great need to improve current wastewater treatment procedures. In this contribution, we will report on the use of molecularly imprinted polymers (MIPs) for the extraction of antidepressants in water samples. MIPs were developed for fluoxetine and duloxetine, antidepressants belonging to the class of selective serotonin reuptake inhibitors (SSRIs). The binding capacity of these microparticles was evaluated using ultraviolet-visible (UV-Vis) spectroscopy. A new high-performance liquid chromatography (HPLC) procedure coupled to UV detection was developed, which enabled the study of mixtures of fluoxetine and duloxetine with other nitrogen-containing compounds. These results indicate that it is possible to selectively extract SSRIs from complex samples. Therefore, these versatile polymers are a promising analytical tool for the clean-up of water samples, which will benefit aquatic life and reduce the ecological impact of pharmaceuticals. Molecularly imprinted polymer ; Fluoxetine ; Duloxetine ; High-performance liquid chromatography ; Chemistry ; Chromatography ; Serotonin ; Medicine ; Organic chemistry ; Selectivity Analytical chemistry methods development ; Analytical Chemistry and Chromatography ; Innovative Microfluidic and Catalytic Techniques Innovation
Authors: David Jou | Liliana Restuccia
Source: Entropy (article, 2019-12-06)
Field: Materials Science — Materials Chemistry

Nonlinear Heat Transport in Superlattices with Mobile Defects We consider heat conduction in a superlattice with mobile defects, which reduce the thermal conductivity of the material. If the defects may be dragged by the heat flux, and if they are stopped at the interfaces of the superlattice, it is seen that the effective thermal resistance of the layers will depend on the heat flux. Thus, the concentration dependence of the transport coefficients plus the mobility of the defects lead to a strongly nonlinear behavior of heat transport, which may be used in some cases as a basis for thermal transistors. Superlattice ; Thermal conduction ; Thermal conductivity ; Heat flux ; Materials science ; Thermal resistance ; Nonlinear system ; Thermal ; Condensed matter physics ; Thermodynamics ; Heat transfer ; Optoelectronics ; Composite material ; Physics Thermal properties of materials ; Thermal Radiation and Cooling Technologies ; Heat Transfer and Optimization
Authors: Xianze Hong | A. H. Harker | Mohan Edirisinghe
Source: Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences (article, 2019-05-01)
Field: Materials Science — Biomaterials

Empirical modelling and optimization of pressure-coupled infusion gyration parameters for the nanofibre fabrication Pressure-coupled infusion gyration (PCIG) is a novel promising technique for economical and effective mass production of nanofibres with desirable geometrical characteristics. The average diameter of spun fibres significantly influences the structural, mechanical and physical properties of the produced fibre mats. Having a comprehensive understanding of the significant effects of PCIG experimental variables on the spun fibres is beneficial. In this work, response surface methodology was used to explore the interaction effects and the optimal PCIG experimental variables for achieving the desired morphological characteristics of fibres. The effect of experimental variables, namely solution concentration, infusion (flow) rate, applied pressure and rotational speed, was studied on the average fibre diameter and standard deviations. A numerical model for the interactional influences of experimental variables was developed and optimized with a nonlinear interior point method that can be used as a framework for selecting the optimal conditions to obtain poly-ethylene oxide fibres with desired morphology (targeted average diameter and narrow standard deviation). The adequacy of the models was verified by a set of validation experiments. The results proved that the predicted optimal conditions were able to achieve the average diameter that matched the pre-set desired value with less than 10% of difference. Materials science ; Gyration ; Work (physics) ; Standard deviation ; Volumetric flow rate ; Mechanics ; Response surface methodology ; Fabrication ; Design of experiments ; Flow (mathematics) ; Rotational speed ; Biological system ; Composite material ; Mathematics ; Mechanical engineering ; Statistics ; Geometry ; Engineering ; Physics Electrospun Nanofibers in Biomedical Applications ; Additive Manufacturing and 3D Printing Technologies ; Electrohydrodynamics and Fluid Dynamics
Authors: V. A. Levashov | R. E. Ryltsev | N. M. Chtchelkatchev
Source: Soft Matter (article, 2019-01-01)
Field: Materials Science — Materials Chemistry

Anomalous behavior and structure of a liquid of particles interacting through the harmonic-repulsive pair potential near the crystallization transition A characteristic property of many soft matter systems is an ultrasoft effective interaction between their structural units. This softness often leads to complex behavior. In particular, ultrasoft systems under pressure demonstrate polymorphism of complex crystal and quasicrystal structures. Therefore, it is of interest to investigate how different can be the structure of the fluid state in such systems at different pressures. Here we address this issue for a model liquid composed of particles interacting through the harmonic-repulsive pair potential. This system can form different crystal structures as the liquid is cooled. We find that, at certain pressures, the liquid exhibits unusual properties, such as a negative thermal expansion coefficient. Besides, the volume and the potential energy of the system can increase during crystallization. At certain pressures, the system demonstrates high stability against crystallization and it is hardly possible to crystallize it on the timescales of the simulations. To address the liquid's structure at high pressures, we consider the scaled pair distribution function (PDF) and the bond-orientational order (BOO) parameters. The marked change happening with the PDF, as pressure increases, is the splitting of the first peak which is caused by the appearance of non-negligible interactions with the second neighbors and the following rearrangement of the structure. Our findings suggest that non-trivial effects, usually explained by different interactions at different spatial scales, can also be observed in one-component systems with simple one-length-scale ultrasoft repulsive interactions. Harmonic ; Crystallization ; Component (thermodynamics) ; Condensed matter physics ; Materials science ; Chemical physics ; Thermodynamics ; Physics ; Quantum mechanics Material Dynamics and Properties ; nanoparticles nucleation surface interactions ; Advanced Thermodynamics and Statistical Mechanics
Authors: R. Ramesh | Sasikanth Manipatruni | Ian A. Young
Source: MRS Bulletin (article, 2019-04-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Electric-field control of magnetism Magnetism ; Field (mathematics) ; Engineering physics ; Materials science ; Condensed matter physics ; Physics ; Mathematics Multiferroics and related materials ; Magnetic and transport properties of perovskites and related materials ; Advanced Condensed Matter Physics
Authors: Pinku Nath | Demet Usanmaz | David Hicks | Corey Oses | Marco Fornari | Marco Buongiorno Nardelli | Cormac Toher | Stefano Curtarolo
Source: Physical Review Materials (article, 2019-07-08)
Field: Materials Science — Materials Chemistry

AFLOW-QHA3P: Robust and automated method to compute thermodynamic properties of solids Accelerating the calculations of finite-temperature thermodynamic properties is a major challenge for rational materials design. Reliable methods can be quite expensive, limiting their applicability in autonomous high-throughput workflows. Here, the three-phonon quasiharmonic approximation (QHA) method is introduced, requiring only three phonon calculations to obtain a thorough characterization of the material. Leveraging a Taylor expansion of the phonon frequencies around the equilibrium volume, the method efficiently resolves the volumetric thermal expansion coefficient, specific heat at constant pressure, the enthalpy, and bulk modulus. Results from the standard QHA and experiments corroborate the procedure, and additional comparisons are made with the recently developed self-consistent QHA. The three approaches---three-phonon, standard, and self-consistent QHAs---are all included within the open-source ab initio framework aflow, allowing the automated determination of properties with various implementations within the same framework. Thermal expansion ; Limiting ; Phonon ; Characterization (materials science) ; Constant (computer programming) ; Material properties ; Ab initio ; Thermal Thermal Expansion and Ionic Conductivity ; Machine Learning in Materials Science ; Boron and Carbon Nanomaterials Research
Authors: Guilherme Duarte Ramos Matos | David L. Mobley
Source: F1000Research (preprint, 2019-01-04)
Field: Materials Science — Materials Chemistry

Challenges in the use of atomistic simulations to predict solubilities of drug-like molecules <b>Background: </b>Solubility is a physical property of high importance to the pharmaceutical industry, the prediction of which for potential drugs has so far been a hard task. We attempted to predict the solubility of acetylsalicylic acid (ASA) by estimating the absolute chemical potentials of its most stable polymorph and of solutions with different concentrations of the drug molecule. <b>Methods:</b> Chemical potentials were estimated from all-atom molecular dynamics simulations. We used the Einstein molecule method (EMM) to predict the absolute chemical potential of the solid and solvation free energy calculations to predict the excess chemical potentials of the liquid-phase systems. <b>Results:</b> Reliable estimations of the chemical potentials for the solid and for a single ASA molecule using the EMM required an extremely large number of intermediate states for the free energy calculations, meaning that the calculations were extremely demanding computationally. Despite the computational cost, however, the computed value did not agree well with the experimental value, potentially due to limitations with the underlying energy model. Perhaps better values could be obtained with a better energy model; however, it seems likely computational cost may remain a limiting factor for use of this particular approach to solubility estimation. <b>Conclusions:</b> Solubility prediction of drug-like solids remains computationally challenging, and it appears that both the underlying energy model and the computational approach applied may need improvement before the approach is suitable for routine use. Solubility ; Solvation ; Molecule ; Chemistry ; Molecular dynamics ; Thermodynamics ; Computational chemistry ; Statistical physics ; Chemical physics ; Physics ; Physical chemistry ; Organic chemistry Crystallization and Solubility Studies ; Crystallography and molecular interactions ; Surfactants and Colloidal Systems
Authors: Xuefei Tan | Deli Zang | Haiqun Qi | Feng Liu | Guoliang Cao | Shih‐Hsin Ho
Source: Processes (article, 2019-07-02)
Field: Materials Science — Surfaces, Coatings and Films

Fabrication of Green Superhydrophobic/Superoleophilic Wood Flour for Efficient Oil Separation from Water The removal of oil from waste water is gaining increasing attention. In this study, a novel synthesis method of green superhydrophobic/superoleophilic wood flour is proposed using the deposition of nano–zinc oxide (nZnO) aggregated on the fiber surface and the subsequent hydrophobic modification of octadecanoic acid. The as-prepared wood flour displayed great superhydrophobicity and synchronous superoleophilicity properties with the water contact angle (WCA) of 156° and oil contact angle (OCA) of 0° for diesel oil. Furthermore, the as-prepared wood flour possessed an excellent stability, probably due to the strong adhesion of nZnO, which aggregates to the fiber surface of wood flour with the action of glutinous polystyrene. The maximum adsorption capacity of as-prepared wood flour was 20.81 g/g for engine oil, which showed that the as-prepared wood flour is a potential candidate as an efficient oil adsorbent in the field of water-oil separation. Moreover, it has good chemical steadiness and environmental durability. Taken together, all the information acquired from this research could be valuable in evaluating the potential of as-prepared wood flour as a competitive and sustainable oil-water separation material. Contact angle ; Materials science ; Adsorption ; Fiber ; Chemical engineering ; Polyethylene terephthalate ; Composite material ; Organic chemistry ; Chemistry Surface Modification and Superhydrophobicity ; Electrohydrodynamics and Fluid Dynamics ; Advanced Sensor and Energy Harvesting Materials
Authors: Zhicheng Wu | Ming Zhou | Erfan Khoram | Boyuan Liu | Zongfu Yu
Source: arXiv (Cornell University) (preprint, 2019-08-13)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Neuromorphic Metasurface Metasurfaces have been used to realize optical functions such as focusing and beam steering. They use sub-wavelength nanostructures to control the local amplitude and phase of light. Here we show that such control could also enable a new function of artificial neural inference. We demonstrate that metasurfaces can directly recognize objects by focusing light from an object to different spatial locations that correspond to the class of the object. Neuromorphic engineering ; Object (grammar) ; Computer science ; Phase (matter) ; Inference ; Optics ; Class (philosophy) ; Amplitude ; Wavelength ; Artificial neural network ; Artificial intelligence ; Physics ; Computer vision Metamaterials and Metasurfaces Applications ; Photoreceptor and optogenetics research ; Molecular Communication and Nanonetworks
Authors: Daniel Medyński | A. Janus
Source: Archives of Foundry Engineering (article, 2019-06-28)
Field: Materials Science — Materials Chemistry

Effect of Cr, Mo and Al on Structure and Selected Mechanical Properties of Austenitic Cast Iron Results of a research on influence of chromium, molybdenum and aluminium on structure and selected mechanical properties of Ni-Mn-Cu cast iron in the as-cast and heat-treated conditions are presented.All raw castings showed austenitic matrix with relatively low hardness, making the material machinable.Additions of chromium and molybdenum resulted in higher inclination to hard spots.However, a small addition of aluminium slightly limited this tendency.Heat treatment consisting in soaking the castings at 500 °C for 4 h resulted in partial transformation of austenite to acicular, carbon-supersaturated ferrite, similar to the bainitic ferrite.A degree of this transformation depended not only on the nickel equivalent value (its lower value resulted in higher transformation degree), but also on concentrations of Cr and Mo (transformation degree increased with increasing total concentration of both elements).The castings with the highest hard spots degree showed the highest hardness, while hardness increase, caused by heat treatment, was the largest in the castings with the highest austenite transformation degree.Addition of Cr and Mo resulted in lower thermodynamic stability of austenite, so it appeared a favourable solution.For this reason, the castings containing the highest total amount of Cr and Mo with an addition of 0.4% Al (to reduce hard spots tendency) showed the highest tensile strength. Materials science ; Austenite ; Cast iron ; Metallurgy ; Microstructure Metal Alloys Wear and Properties ; Metallurgy and Material Forming ; Microstructure and Mechanical Properties of Steels
Authors: Utkarsh Bhardwaj | H. Hemani | M. Warrier | Nancy Semwal | Kawsar Ali | A. Arya
Source: The Journal of Open Source Software (article, 2019-09-19)
Field: Materials Science — Materials Chemistry

CSaransh : Software Suite to Study Molecular Dynamics Simulations of Collision Cascades The micro-structural properties of materials change due to irradiation. The defects formed during the displacement cascades caused by irradiation are the primary source of radiation damage The number of primary defects produced, defect cluster size distribution, and defect cluster structures after a collision cascade can be studied using Molecular Dynamics simulations. These results determine the long term evolution of the micro-structural changes in the material (Becquart et al. Suite ; Collision ; Computer science ; Software ; Molecular dynamics ; Dynamics (music) ; Physics ; Chemistry ; Computational chemistry ; Programming language ; Geography Fusion materials and technologies ; Nuclear Materials and Properties ; Ion-surface interactions and analysis
Authors: Naveen K. Karri | Changki Mo
Source: SN Applied Sciences (article, 2019-08-26)
Field: Materials Science — Materials Chemistry

Geometry optimization for structural reliability and performance of a thermoelectric generator Reliability (semiconductor) ; Bismuth telluride ; Thermoelectric generator ; Finite element method ; Thermoelectric effect ; Generator (circuit theory) ; Computer science ; Reliability engineering ; Mechanical engineering ; Process (computing) ; Materials science ; Thermoelectric materials ; Power (physics) ; Structural engineering ; Engineering ; Thermodynamics Advanced Thermoelectric Materials and Devices ; Thermal Radiation and Cooling Technologies ; Thermal properties of materials
Authors: Gürcan Samtaş | Salih Korucu
Source: Bulletin of the Polish Academy of Sciences Technical Sciences (article, 2019-08-31)
Field: Materials Science — Materials Chemistry

Optimization of cutting parameters in pocket milling of tempered and cryogenically treated 5754 aluminum alloy Aluminum alloys are widely used today in plastic injection molds in the automotive and aerospace industries due to their high strength and weight ratio, good corrosion and fatigue resistance as well as high feed rates. The 5754 aluminum alloy has high corrosion resistance and a structure suitable for cold forming. In this study, an AA 5754-H111 tempered aluminum alloy with the dimensions of 80×80×30&amp;nbsp;mm was used, and some of the materials were cryogenically heat treated. For the milling operations, ϕ12&amp;nbsp;mm diameter 76&amp;nbsp;mm height uncoated as well as TiCN and TiAlN coated end mills were used. Different levels of cutting depth (1.25, 2.0, 2.5&amp;nbsp;mm), cutting speed (50, 80, 100&amp;nbsp;m/ min), feed rate (265, 425, 530&amp;nbsp;m/ min) and machining pattern (concentric, back and forth and inward helical) were used. The number of experiments was reduced from 486 to 54 using the Taguchi L54 orthogonal array. The values obtained at the end of the experiments were evaluated using the signal-to-noise ratio, ANOVA, three-dimensional graphs and the regression method. Based on the result of the verification experiments, the processing accuracy for surface roughness was improved from 3.20&amp;nbsp;μm to 0.90&amp;nbsp;μm, with performance increase of 71.88%. Materials science ; Aluminium ; Metallurgy ; Alloy Metal Alloys Wear and Properties ; Advanced machining processes and optimization ; Metallurgy and Material Forming
Authors: Yakov Abetbool | Shailendra Rajput | Asher Yahalom | Moshe Averbukh
Source: Electronics (article, 2019-08-13)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Comprehensive Study on Dynamic Parameters of Symmetric and Asymmetric Ultracapacitors Electrical storage components such as ultracapacitors (UC) have received significant attention from various industrial sectors, from electric vehicles to renewable power plants. This article presents the investigations on dynamic properties of asymmetric Li-ion hybrid (CPQ2300S: 2300 F, 2.2–3.8 V, JSR Co., Tokyo, Japan) and symmetric double-layer (BCAP3400: 3400 F, 2.85 V, Maxwell Technologies Co., San Diego, CA, USA) ultracapacitors. The internal resistance and capacitance of both UCs were slightly changed with respect to current and voltage alterations, but these changes were more prominent for the Li-ion UC. The internal resistance of the Li-ion UC became five times larger and its capacitance decreased significantly when the temperature decreased from +25 °C to −20 °C. More importantly, the double-layer UC exhibited nearly constant capacitance for a wide range of temperature changes (0 °C to −40 °C), although internal resistance increased somewhat. Electrochemical impedance spectroscopy analysis of both UCs was performed for the frequency range of 1 Hz–1 kHz and in the temperature range from −15 °C to +30 °C. It was observed that the temperature effects were much more pronounced for the asymmetric Li-ion UC than that of the symmetric double-layer UC. This work also proposes an improved equivalent circuit model based on an infinite number of resistance-capacitance (r–C) chains. The characteristic behavior of symmetric UCs can be explained precisely by the proposed model. This model is also applicable to asymmetric UCs, but with less precision. Capacitance ; Supercapacitor ; Internal resistance ; Materials science ; Dielectric spectroscopy ; Ion ; Electrochemistry ; Double-layer capacitance ; Electrical impedance ; Voltage ; Range (aeronautics) ; Analytical Chemistry (journal) ; Electrical engineering ; Condensed matter physics ; Electrode ; Chemistry ; Composite material ; Physics ; Power (physics) ; Thermodynamics ; Engineering Supercapacitor Materials and Fabrication ; Advanced Battery Technologies Research ; Advancements in Battery Materials