jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Dominika Zákutná | Anne Fischer | Dominique Dresen | D. Nižňanský | Dirk Honecker | Sabrina Disch
Source: Journal of Applied Crystallography (article, 2022-11-03)
Field: Materials Science — Materials Chemistry

Multiscale magnetization in cobalt-doped ferrite nanocubes The magnetization of cobalt ferrite nanocubes of similar size, but with varying Co/Fe ratio, is extensively characterized on atomistic and nanoscopic length scales. Combination of X-ray diffraction, Mössbauer spectroscopy, magnetization measurements and polarized small-angle neutron scattering (SANS) reveals that a lower amount of cobalt leads to an enhanced magnetization. At the same time, magnetic SANS confirms no or negligible near-surface spin disorder in these highly crystalline, homogeneously magnetized nanoparticles, resulting in an exceptionally hard magnetic material with high coercivity. Magnetization ; Materials science ; Coercivity ; Cobalt ; Condensed matter physics ; Nanoscopic scale ; Neutron diffraction ; Neutron scattering ; Small-angle neutron scattering ; Scattering ; Ferrite (magnet) ; Nuclear magnetic resonance ; Diffraction ; Nanotechnology ; Optics ; Magnetic field ; Composite material ; Metallurgy ; Physics Magnetic Properties and Synthesis of Ferrites ; Magnetic properties of thin films ; Iron oxide chemistry and applications
Authors: Devendrá Pareek | Marco A. Gonzalez | Nedal Grewo | Marten L. Janßen | Kumarahgiri Arunakiri | Kayode Luqman Alimi | Martin Silies | Jürgen Parisi | Levent Gütay | Sascha Schäfer
Source: Advanced Materials Interfaces (article, 2022-09-20)
Field: Materials Science — Materials Chemistry

Large‐Area Growth of MoS<sub>2</sub>/WS<sub>2</sub> Heterostructures by a Sequential Atomic Layer Deposition and Spin‐Coating Approach Abstract Despite the plethora of intriguing phenomena observed in heterostructure stacks of 2D transition metal dichalcogenide (2D‐TMDC) flakes, their application in functional devices is still hampered due to the lack of reliable growth methodologies for large‐area heterostructures. Here, a scalable process for obtaining as‐grown transition metal di‐chalcogenide heterostructures by a combination of atomic layer deposition of monolayer MoS 2 and solution‐based processing of ultrathin WS 2 is presented. Spatially uniform optical and electrical characteristics of the individual TMDC layers and heterostructures are demonstrated down to micrometer length scales using Raman and photoluminescence spectroscopy, and light‐beam‐induced current measurements. An enhanced photogenerated current is observed for lateral MoS 2 –MoS 2 /WS 2 heterostructures demonstrating the suitability of this approach for the preparation of functional devices. Heterojunction ; Materials science ; Raman spectroscopy ; Chalcogenide ; Optoelectronics ; Photoluminescence ; Atomic layer deposition ; Nanotechnology ; Monolayer ; Layer (electronics) ; Chemical vapor deposition ; Spin coating ; Deposition (geology) ; Coating ; Optics 2D Materials and Applications ; Perovskite Materials and Applications ; Graphene research and applications
Authors: Marta Brioschi | Pietro Carrara | Vincent Polewczyk | Deepak Dagur | Giovanni Vinai | Pietro Parisse | Simone Dal Zilio | G. Panaccione | G. Rossi | Riccardo Cucini
Source: Optics Letters (article, 2022-11-09)
Field: Chemistry — Spectroscopy

Multidetection scheme for transient-grating-based spectroscopy Time-resolved optical spectroscopy represents an effective non-invasive approach to investigate the interplay of different degrees of freedom, which plays a key role in the development of novel functional materials. Here, we present magneto-acoustic data on Ni thin films on SiO<sub>2</sub> as obtained by a versatile pump-probe setup that combines transient grating spectroscopy with time-resolved magnetic polarimetry. The possibility to easily switch from a pulsed to continuous wave probe allows probing of acoustic and magnetization dynamics on a broad time scale, in both transmission and reflection geometry. Optics ; Grating ; Spectroscopy ; Diffraction grating ; Transient (computer programming) ; Materials science ; Physics ; Computer science Spectroscopy and Laser Applications ; Analytical Chemistry and Sensors ; Spectroscopy and Quantum Chemical Studies
Authors: Cristina Ileana Pascu | Claudiu Nicolicescu | Nicoleta Cioateră | Ștefan Gheorghe | Ionuț Geonea | Anca Didu
Source: Materials (article, 2022-03-10)
Field: Materials Science — Materials Chemistry

Characterization of Titanium Alloy Obtained by Powder Metallurgy Ti-based alloys are an important class of materials suitable especially for medical applications, but they are also used in the industrial sector. Due to their low tribological properties it is necessary to find optimal technologies and alloying elements in order to develop new alloys with improved properties. In this paper, a study on the influence of sintering treatments on the final properties of a titanium alloy is presented. The alloy of interest was obtained using the powders in following weight ratio: 80% wt Ti, 8% wt Mn, 3% wt Sn, 6% wt Aluminix123, 2% wt Zr and 1% wt graphite. Two sintering methods were used, namely two-step sintering (TSS) and multiple-step sintering (MSS), as alternatives to conventional sintering which uses a single sintering dwell time. Evolution of sample morphology, composition and crystalline structure with sintering method was evidenced. The lower values for the friction coefficient and for the wear rate was attained in the case of the sample obtained by TSS. Sintering ; Materials science ; Alloy ; Powder metallurgy ; Metallurgy ; Graphite ; Tribology ; Titanium ; Dwell time ; Titanium alloy Titanium Alloys Microstructure and Properties ; Advanced materials and composites ; Metal and Thin Film Mechanics
Authors: Mateus Botani de Souza Dias | Fernando José Gomes Landgraf | Krzysztof Chwastek
Source: Energies (article, 2022-02-03)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Modeling the Effect of Compressive Stress on Hysteresis Loop of Grain-Oriented Electrical Steel Modeling of hysteresis loops may be useful for the designers of magnetic circuits in electric machines. The present paper focuses on the possibility to apply the Harrison model to describe hysteresis loops of grain-oriented electrical steel subject to compressive stress. The model extension is achieved by introduction of an additional term into the equation that describes irreversible magnetization process. The extension term does not include a product of stress and magnetization, as could be anticipated from Sablik’s theory, applicable, e.g., to the Jiles–Atherton model. The present contribution points out the fundamental differences between the two aforementioned modeling approaches, which are based on different philosophies despite some apparent similarities. The modeling results are in a qualitative agreement with the experimental results obtained from a single sheet tester for a representative commercially available grain-oriented electrical steel grade 0.27 mm thick. Electrical steel ; Hysteresis ; Magnetization ; Extension (predicate logic) ; Magnetic hysteresis ; Stress (linguistics) ; Materials science ; Compressive strength ; Mechanical engineering ; Mechanics ; Metallurgy ; Computer science ; Engineering ; Magnetic field ; Physics ; Condensed matter physics ; Composite material Magnetic Properties and Applications ; Microstructure and Mechanical Properties of Steels ; Electric Motor Design and Analysis
Authors: Maomao Zhang | Zhidong Zhou
Source: Micromachines (article, 2022-06-09)
Field: Materials Science — Materials Chemistry

Bending and Vibration Analysis of Flexoelectric Beam Structure on Linear Elastic Substrates With the development of micro-nanotechnology, smart electronic devices are being updated and developed, and more and more flexoelectric sensors, actuators, and energy harvesters attached to elastic substrates have attracted a surge of interest due to unique features at the nano-scale. In this paper, the static bending behavior and vibration characteristics of a flexoelectric beam structure based on a linear elastic substrate under a magnetic field environment are investigated. Based on the electrical Gibbs free energy density, the governing equations and boundary conditions of structures are derived by using the Euler-Bernoulli beam theory and the Hamilton's variational principle. The expressions of the deflection and the induced electric potential of the beam structure are expressed analytically. The natural frequency of the beam under the open-circuit electrical conditions with surface electrodes (OCI) are obtained after further extending the solution. The results show that the flexoelectric effect, the linear elastic substrate, and the magnetic field have significant effects on the static bending and vibration behaviors of the flexoelectric beam which are beneficial for designing and developing flexoelectric devices with elastic substrates. Materials science ; Bending ; Vibration ; Beam (structure) ; Structural engineering ; Bending stiffness ; Flexoelectricity ; Composite material ; Piezoelectricity ; Acoustics ; Engineering ; Physics Nonlocal and gradient elasticity in micro/nano structures ; Innovative Energy Harvesting Technologies ; Vibration and Dynamic Analysis
Authors: Jonathan Hey | D. V. Maheswar Repaka | Tao Li | Jun Tan
Source: Energies (article, 2022-08-30)
Field: Materials Science — Materials Chemistry

Design Optimization of a Rotary Thermomagnetic Motor for More Efficient Heat Energy Harvesting A rotary thermomagnetic motor that is designed for heat energy harvesting is presented in this paper. The power output, power density, and efficiency of the device is estimated using a mathematical model coupling the heat transfer, magnetic interactions, and rotor dynamics. The design analysis shows that the efficiency of the device is maximized, when there is a balance between the volume of thermomagnetic material used against the rate of heating and cooling of the material. On the other hand, the power output is determined largely by the size of the rotor, while the power density tends to peak at a particular aspect (length to diameter) ratio of the rotor. It is also observed that a higher rate of cooling leads to more output, especially when this is matched to a similar rate of heat supplied to the thermomagnetic motor. The result from the design optimization points to an ‘optimal’ design configuration and corresponding operating conditions that results in the largest power output, highest power density and best efficiency. After the optimization, it is estimated that the rotary thermomagnetic motor is able to produce up to 88 W of power with a power density of approximately 27 kW/m3 of thermomagnetic material used, while a maximum thermal-to-mechanical energy conversion efficiency of 2.1% is achievable. The results obtained from this design analysis and optimization shows the potential for such a rotary thermomagnetic motor to be implemented at a larger scale for heat energy harvesting application. Thermomagnetic convection ; Power density ; Rotor (electric) ; Maximum power principle ; Power (physics) ; Materials science ; Heat transfer ; Mechanical engineering ; Automotive engineering ; Engineering ; Mechanics ; Thermodynamics ; Magnetic field ; Physics Advanced Thermoelectric Materials and Devices ; Advanced Thermodynamic Systems and Engines ; Advanced Thermodynamics and Statistical Mechanics
Authors: Andre K. Y. Low | Yee‐Fun Lim | Kedar Hippalgaonkar | Eléonore Vissol-Gaudin
Source:  (preprint, 2022-12-12)
Field: Materials Science — Materials Chemistry

Mapping Pareto Fronts for Efficient Multi-Objective Materials Discovery With advancements in automation and high-throughput techniques, complex materials discovery with multiple conflicting objectives can now be tackled in experimental labs. Given that physical experimentation is greatly limited by evaluation budget, maximizing efficiency of optimization becomes crucial. We discuss the limitations of using hypervolume as a performance indicator for desired optimality across the entire multi-objective optimization run and propose new metrics specific to experimentation: ability to perform well for complex high-dimensional problems, minimizing wastage of evaluations, consistency/robustness of optimization, and ability to scale well to high throughputs. With these metrics, we perform a comparison of two conceptually different and state-of-the-art algorithms (Bayesian and Evolutionary) on synthetic and real-world datasets. We discuss the merits of both approaches with respect to exploration and exploitation, where fully resolving the Pareto Front could be the main aim for greater scientific value in understanding materials space, and thus provide a perspective for materials scientists to implement optimization in their platforms. Bayesian optimization ; Computer science ; Robustness (evolution) ; Multi-objective optimization ; Pareto principle ; Consistency (knowledge bases) ; Mathematical optimization ; Machine learning ; Artificial intelligence ; Mathematics Machine Learning in Materials Science ; Advanced Multi-Objective Optimization Algorithms ; Manufacturing Process and Optimization
Authors: Aura S. Merlano | Elim Albiter | Miguel A. Valenzuela | Lina M. Hoyos | Ángel Salazar
Source: Nanocomposites (article, 2022-12-31)
Field: Chemistry — Organic Chemistry

Flower-like and nanorods ZnO deposited on rGO as efficient photocatalysts for removal of polychlorinated biphenyls (PCBs) PCBs were used for several decades as coolants, lubricants in transformers, plasticizers, and dielectric fluids, being highly carcinogenic and representing a severe environmental problem in soil and water. Pure and modified TiO2 has been the most studied photocatalyst looking to degrade PCBs into less toxic products. Lately, ZnO-graphene composites have played an essential role in the photocatalytic degradation of various toxic organic compounds. In this work, ZnO nanostructures were coupled with reduced graphene oxide (ZnO-rGO) via a one-pot microwave-assisted hydrothermal route. As a result, the composites exhibited improved photocatalytic performance for PCBs degradation compared to ZnO nanoparticles. Thus, this research provides an in-situ method to grow different morphologies of ZnO on rGO. Graphene ; Nanorod ; Photocatalysis ; Materials science ; Oxide ; Plasticizer ; Chemical engineering ; Hydrothermal circulation ; Degradation (telecommunications) ; Nanotechnology ; Photodegradation ; Zinc ; Composite material ; Chemistry ; Catalysis ; Metallurgy ; Organic chemistry Nanomaterials for catalytic reactions ; Advanced Photocatalysis Techniques ; Graphene research and applications
Authors: Manon Rolland | Eric R. Dufresne | Nghia P. Truong | Athina Anastasaki
Source: Polymer Chemistry (article, 2022-01-01)
Field: Chemistry — Organic Chemistry

The effect of surface-active statistical copolymers in low-energy miniemulsion and RAFT polymerization Study of the composition, lenght and chemical structure of surface-active statistical copolymers in low-energy miniemulsions. Miniemulsion ; Copolymer ; Raft ; Polymerization ; Polymer chemistry ; Surface energy ; Materials science ; Reversible addition−fragmentation chain-transfer polymerization ; Chemical engineering ; Radical polymerization ; Polymer ; Composite material ; Engineering Advanced Polymer Synthesis and Characterization ; Surfactants and Colloidal Systems ; biodegradable polymer synthesis and properties
Authors: Ying Liu | Lin Wu | Ao Chen | Chang Xu | Xiaoyu Yang | Yilai Zhou | Zhiyuan Liao | Baoguo Zhang | HU Ya | Hailiang Fang
Source: Coatings (article, 2022-07-07)
Field: Materials Science — Materials Chemistry

Component Design of Environmentally Friendly High-Temperature Resistance Coating for Oriented Silicon Steel and Effects on Anti-Corrosion Property Oriented silicon steel is vital for power transformer cores, while the high-temperature annealing process limits the industrialization of environmentally friendly coatings on the surface. In this paper, the high-temperature binders Al(H2PO4)3 solution and silica sol were introduced innovatively. They condensed into macromolecular polymer chains, network structures and SiO2 particles at high temperatures, providing high-temperature stability and adhesion. The influence of types of silica sol, additives and functional fillers on the corrosion resistance of the coating was studied. The prepared environmentally friendly inorganic insulating coating for oriented silicon steel has excellent corrosion resistance after curing at 475 °C and annealing at 800 °C, which was matched with the currently rolling process of oriented silicon steel. The salt-spray resistance can last for more than 24 h and up to 72 h. Environmentally friendly ; Materials science ; Corrosion ; Coating ; Annealing (glass) ; Silicon ; Curing (chemistry) ; Composite material ; Polymer ; Metallurgy Silicone and Siloxane Chemistry ; Corrosion Behavior and Inhibition ; Polymer Nanocomposites and Properties
Authors: Refat Atef Ghunem | Ayman El‐Hag | M. Marzinotto | M. Tariq Nazir | K. L. Wong | Shesha Jayaram
Source: IEEE Electrical Insulation Magazine (article, 2022-06-15)
Field: Materials Science — Materials Chemistry

Overhead Lines and Wildfires: Role of Outdoor Insulators: Prepared by a Task Force of the IEEE DEIS Outdoor Insulation Technical Committee Insulator leakage current is the primary root cause of pole fires; therefore, it is critical to recognize outdoor insulators as potential cause of wildfires. Task force ; Insulator (electricity) ; Electrical engineering ; Forensic engineering ; Root cause ; Engineering ; Environmental science ; Materials science ; Reliability engineering High voltage insulation and dielectric phenomena ; Lightning and Electromagnetic Phenomena ; Fire dynamics and safety research
Authors: Mohammad Kharezy | Hassan Mirzaei | Torbjörn Thiringer | Yuriy Serdyuk
Source: Energies (article, 2022-03-09)
Field: Materials Science — Materials Chemistry

Green Solution for Insulation System of a Medium Frequency High Voltage Transformer for an Offshore Wind Farm High Voltage Direct Current (HVDC) transmission represents the most efficient way for transporting produced electrical energy from remotely located offshore wind farms to the shore. Such systems are implemented today using very expensive and large power transformers and converter stations placed on dedicated platforms. The present study aims at elaborating a compact solution for an energy collections system. The solution allows for a minimum of total transformer weight in the wind turbine nacelle reducing or even eliminating the need for a sea-based platform(s). The heart of the project is a Medium Frequency Transformer (MFT) that has a high DC voltage insulation towards ground. The transformer is employed in a DC/DC converter that delivers the energy into a serial array without additional conversion units. The insulation design methodology of an environmentally friendly HV insulation system for an MFT, based on pressboard and biodegradable oil, is introduced. The measurement method and results of the measurements of electrical conductivities of the transformer oil and Oil Impregnated Pressboard (OIP) are reported. The measurements show that the biodegradable ester oil/OIP conductivities are generally higher than the mineral oil/OIP conductivities. Numerical simulations reveal that the performance of the insulation system is slightly better when ester oil is used. Additionally, a lower temperature dependency for ester oil/OIP conductivities is observed, with the result that the transformer filled with ester oil is less sensitive to temperature variations. Transformer ; Pressboard ; Offshore wind power ; Turbine ; Renewable energy ; Electrical engineering ; Mineral oil ; Insulation system ; Automotive engineering ; Voltage ; Marine engineering ; Transformer oil ; Materials science ; Wind power ; Engineering ; Environmental science ; Mechanical engineering High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation ; Thermal Analysis in Power Transmission
Authors: Xuanjie Lin | Hantong Jiang | Liquan Wang | Yongsheng Ren | Wenhui Ma | Shu Zhan
Source: Molecular Physics (article, 2022-05-17)
Field: Materials Science — Materials Chemistry

3D-structure-attention graph neural network for crystals and materials Machine learning has been widely used in physics and chemistry. As a deep learning method based on graph domain analysis, graph neural networks (GNNs) have natural advantages in predicting material properties. We find that most existing models focus on the topological relationship between atoms without considering the specific positions. However, 3D-spatial distribution is the key to affecting the atomic state and interaction relationship, which has a decisive impact on the material properties. Here, we present a 3D-structure-attention graph neural network (3SAGNN) model, introducing the attention mechanism. The model focuses on the critical areas in the material 3D structure that significantly impact the prediction properties to effectively improve the accuracy of material properties prediction. We prove that the performance of 3SAGNN on a variety of datasets outperforms prior ML models, such as CGCNN. Our proposed model was tested on 36,000 inorganic materials dataset, 20,000 Pt nanocluster dataset, 18,000 porous materials, and 37,000 alloy surface reactions. The experimental results show that 3SAGNN can predict formation energies, total energies, band gaps, and surface catalytic properties more accurately and quickly than density functional theory. Finally, we improve the interpretability of the model through visualisation and show the working mechanism of the network. Interpretability ; Computer science ; Artificial neural network ; Graph ; Focus (optics) ; Artificial intelligence ; Machine learning ; Theoretical computer science ; Biological system ; Physics Machine Learning in Materials Science ; Computational Drug Discovery Methods ; X-ray Diffraction in Crystallography
Authors: Meriem Mouzai | Saliha Oukid | Aouache Mustapha
Source: Neural Computing and Applications (article, 2022-06-08)
Field: Materials Science — Materials Chemistry

Machine learning modeling for the prediction of materials energy Artificial intelligence ; Machine learning ; Computer science ; Artificial neural network ; Random forest ; Field (mathematics) ; Support vector machine ; Energy (signal processing) ; Algorithm ; Mathematics Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Computational Drug Discovery Methods