jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Xiao-Jun Zhao | Yuezhi Cao | Zhiguang Cheng | B. Forghani | Lanrong Liu | Jiawen Wang
Source: IEEE Access (article, 2020-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Experimental and Numerical Study on Stray Loss in Laminated Magnetic Shielding Under 3-D AC-DC Hybrid Excitations for HVDC Transformers To investigate the stray loss in magnetic shielding components immersed in the 3-D AC-DC hybrid leakage magnetic field, a modified method is presented with the variation of the eddy current loss inside the coil due to the change of the leakage magnetic field taken into account. In addition, a new loss separation model is proposed to estimate the standard iron loss of the grain-oriented (GO) silicon steel sheet under AC-DC hybrid excitations. Furthermore, the material properties were appropriately treated based on the simplified model of laminated magnetic shielding for efficient numerical calculation. The comparison of field distribution and loss results obtained by experiment and calculation respectively was made, which shows good consistency and thus verifies the effectiveness of the proposed method in this paper. Meanwhile, the stray loss and additional loss in magnetic shielding are analyzed in detail to evaluate the potential threat of AC-DC hybrid excitations on the local overheating of the structural parts in HVDC transformers. Electromagnetic shielding ; Electromagnetic coil ; Eddy current ; Materials science ; Magnetic field ; Transformer ; Overheating (electricity) ; Electrical steel ; Electrical engineering ; Mechanics ; Nuclear magnetic resonance ; Physics ; Engineering ; Voltage ; Composite material Magnetic Properties and Applications ; Non-Destructive Testing Techniques ; Magnetic Field Sensors Techniques
Authors: Sheng-Chun Yang | Yong‐Lei Wang
Source: Computer Physics Communications (article, 2020-07-27)
Field: Chemistry — Spectroscopy

A hybrid MPI-CUDA approach for nonequispaced discrete Fourier transformation CUDA ; Computer science ; Parallel computing ; Computational science ; General-purpose computing on graphics processing units ; Fast Fourier transform ; Transformation (genetics) ; Speedup ; Algorithm ; Graphics Advanced NMR Techniques and Applications ; Magnetic properties of thin films ; Parallel Computing and Optimization Techniques
Authors: Markus Kühbach | Franz Roters
Source: Modelling and Simulation in Materials Science and Engineering (article, 2020-03-12)
Field: Materials Science — Materials Chemistry

Quantification of 3D spatial correlations between state variables and distances to the grain boundary network in full-field crystal plasticity spectral method simulations Abstract Deformation microstructure heterogeneities play a pivotal role during dislocation patterning and interface network restructuring. Thereby, they affect indirectly how the microstructure recrystallizes. Given this relevance, it has become common practice to study the evolution of deformation microstructure heterogeneities with 3D experiments and full-field crystal plasticity computer simulations including tools such as the spectral method. Quantifying material point to grain or phase boundary distances, though, is a practical challenge with spectral method crystal plasticity models because these discretize the material volume rather than mesh explicitly the grain and phase boundary interface network. This limitation calls for specific data post-processing methods to quantify the spatial correlations between state variable values at each material point and the points’ corresponding distance to the closest grain or phase boundary. This work contributes to the development of advanced such post-processing routines. Specifically, two grain reconstruction and three distancing methods are developed for solving above challenge. The individual strengths and limitations of these methods surplus the efficiency of their parallel implementation is assessed with an exemplary Düsseldorf Advanced Material Simulation Kit large scale crystal plasticity study. We apply the new tool to assess the evolution of subtle stress and disorientation gradients towards grain boundaries. Microstructure ; Discretization ; Plasticity ; Grain boundary ; Phase (matter) ; Crystal plasticity ; Deformation (meteorology) ; Dislocation ; Crystal (programming language) ; Work (physics) Microstructure and mechanical properties ; Nonlocal and gradient elasticity in micro/nano structures ; Microstructure and Mechanical Properties of Steels
Authors: Hyoung Tae Kim | Jin Ho Song | Rae-Joon Park
Source: Frontiers in Energy Research (article, 2020-12-21)
Field: Materials Science — Materials Chemistry

Simulation of a Station Blackout Accident for the SMART Using the CINEMA Code SMART is a small-sized integral type PWR containing major components within a single reactor pressure vessel. Advanced design features implemented into SMART have been proven or qualified through experience, testing, or analysis according to the applicable approved standards. After Fukushima accident, a rising attention is posed on the strategy to cope with a Station Blackout (SBO) accident, which is one of the representative severe accidents related to the nuclear power plants. The SBO is initiated by a loss of all offsite power with a concurrent failure of both emergency diesel generators. With no alternate current power source, most of the active safety systems that perform safety functions are not available. The purpose of SBO analysis in this paper is to show that the integrity of the containment can be maintained during a SBO accident in the SMART (System-integrated Modular Advanced ReacTor). Therefore, the accident sequence during a SBO accident was simulated using the CINEMA-SMART (Code for INtegrated severe accidEnt Management and Analysis-SMART) code to evaluate the transient scenario inside the reactor vessel after an initiating event, core heating and melting by core uncovery, relocation of debris, reactor vessel failure, discharge of molten core, and pressurization of the containment. It is shown that the integrity of the containment can be maintained during a SBO accident in the SMART reactor. It has to be mentioned that the assumptions used in this analysis are extremely conservative that the passive safety systems of PSIS and PRHRS were not credited. In addition, as ANS73 decay heat with 1.2 multiplier was used in this analysis, actual progression of the accident would be much slow and amount of hydrogen generation will be much less. Blackout ; Accident management ; Containment (computer programming) ; Cabin pressurization ; Reactor pressure vessel ; Nuclear engineering ; Nuclear power plant ; Corium ; Engineering ; Reliability engineering ; Loss-of-coolant accident ; Computer science ; Environmental science ; Power (physics) ; Electric power system ; Coolant ; Mechanical engineering ; Heat transfer Nuclear Materials and Properties ; Nuclear Engineering Thermal-Hydraulics ; Risk and Safety Analysis
Authors: Kevin Yang | Wengong Jin | Kyle Swanson | Regina Barzilay | Tommi Jaakkola
Source: arXiv (Cornell University) (preprint, 2020-02-11)
Field: Materials Science — Materials Chemistry

Improving Molecular Design by Stochastic Iterative Target Augmentation Generative models in molecular design tend to be richly parameterized, data-hungry neural models, as they must create complex structured objects as outputs. Estimating such models from data may be challenging due to the lack of sufficient training data. In this paper, we propose a surprisingly effective self-training approach for iteratively creating additional molecular targets. We first pre-train the generative model together with a simple property predictor. The property predictor is then used as a likelihood model for filtering candidate structures from the generative model. Additional targets are iteratively produced and used in the course of stochastic EM iterations to maximize the log-likelihood that the candidate structures are accepted. A simple rejection (re-weighting) sampler suffices to draw posterior samples since the generative model is already reasonable after pre-training. We demonstrate significant gains over strong baselines for both unconditional and conditional molecular design. In particular, our approach outperforms the previous state-of-the-art in conditional molecular design by over 10% in absolute gain. Finally, we show that our approach is useful in other domains as well, such as program synthesis. Computer science ; Generative model ; Generative grammar ; Parameterized complexity ; Simple (philosophy) ; Weighting ; Machine learning ; Property (philosophy) ; Sequential analysis ; Artificial intelligence ; Generative Design ; Data mining ; Algorithm ; Mathematics ; Statistics ; Engineering Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Chemical Synthesis and Analysis
Authors: Katsuhiko Ishiguro | Kazuya Ujihara | Ryohto Sawada | Hirotaka Akita | Masaaki Kotera
Source: arXiv (Cornell University) (preprint, 2020-10-02)
Field: Materials Science — Materials Chemistry

Data Transfer Approaches to Improve Seq-to-Seq Retrosynthesis Retrosynthesis is a problem to infer reactant compounds to synthesize a given product compound through chemical reactions. Recent studies on retrosynthesis focus on proposing more sophisticated prediction models, but the dataset to feed the models also plays an essential role in achieving the best generalizing models. Generally, a dataset that is best suited for a specific task tends to be small. In such a case, it is the standard solution to transfer knowledge from a large or clean dataset in the same domain. In this paper, we conduct a systematic and intensive examination of data transfer approaches on end-to-end generative models, in application to retrosynthesis. Experimental results show that typical data transfer methods can improve test prediction scores of an off-the-shelf Transformer baseline model. Especially, the pre-training plus fine-tuning approach boosts the accuracy scores of the baseline, achieving the new state-of-the-art. In addition, we conduct a manual inspection for the erroneous prediction results. The inspection shows that the pre-training plus fine-tuning models can generate chemically appropriate or sensible proposals in almost all cases. Retrosynthetic analysis ; Computer science ; Transformer ; Baseline (sea) ; Task (project management) ; Machine learning ; Artificial intelligence ; Transfer (computing) ; Transfer of learning ; Domain (mathematical analysis) ; Generative grammar ; Data mining ; Engineering ; Mathematics Machine Learning in Materials Science ; Genomics and Phylogenetic Studies ; Innovative Microfluidic and Catalytic Techniques Innovation
Authors: Rei Tatsumi | Osamu Koike | Yukio Yamaguchi | Yoshiko Tsuji
Source: The Journal of Chemical Physics (article, 2020-10-22)
Field: Materials Science — Polymers and Plastics

Classification of drying segregation states by a generalized diffusion model During drying of binary colloidal mixtures, one colloidal particle component can segregate to the top surface. We investigate conditions where the segregation occurs through the analysis of a linearized diffusion model with Fick's law generalized for binary colloidal mixtures. The present model is the simplest representation that includes cross-diffusion between different particle components to describe the segregation. Using the analytical solutions of this model, we classify states in terms of which the particle component segregates for the following variables: the mixture ratio of particle components, diffusion coefficients, and drying rates. The obtained state diagrams suggest how to control the segregation by designing material and operation conditions. Diffusion ; Statistical physics ; Mathematics ; Materials science ; Thermodynamics ; Physics Textile materials and evaluations
Authors: Vibhu Srivastava | Prateek Mishra | Sunny
Source: Photonics and Nanostructures - Fundamentals and Applications (article, 2020-05-12)
Field: Materials Science — Materials Chemistry

Investigations on transient regime of Ge2Sb2Te5-based vertical photodetector integrated with silicon-on-insulator waveguide Materials science ; Photodetector ; Wavelength ; Optoelectronics ; Amorphous solid ; Waveguide ; Amorphous silicon ; Photodiode ; Optics ; Insulator (electricity) ; Silicon ; Crystalline silicon ; Physics ; Chemistry Phase-change materials and chalcogenides ; Photonic and Optical Devices ; Thin-Film Transistor Technologies
Authors: Ю.В. Заика | Е.К. Костикова | Ю. С. Нечаев
Source: Журнал технической физики (article, 2020-10-11)
Field: Chemistry — Organic Chemistry

Пики термодесорбции водорода: моделирование и интерпретация Various models of hydrogen thermal desorption peaks are analyzed. The dynamics model of the volume-averaged concentration with a continuum parameter allows integrally taking into account the degree of dominance of the limiting factors (diffusion and recombination of atoms into molecules during desorption). An analytical criterion for peaks symmetry is proposed in the context of comparison with the method of decomposing the component spectrum into the sum of Gaussian. Modifications of the Kissinger method for estimating the activation energy of desorption in experiments with several heating rates and procedures for solving the inverse problem of parametric identification of a unimodal peak using only one heating rate are presented. A comparative with a diffusion model with dynamic boundary conditions is performed. It is shown that the cause of local peaks can be not only capture with different binding energies but also the dynamics of interaction of bulk and surface processes, change in the surface structure during heating. Desorption ; Thermodynamics ; Thermal desorption ; Thermal ; Parametric statistics ; Context (archaeology) ; Gaussian ; Diffusion ; Chemistry ; Statistical physics ; Chemical physics ; Physics ; Physical chemistry ; Mathematics ; Computational chemistry ; Adsorption ; Statistics Chemical Thermodynamics and Molecular Structure
Authors: Xin Wei | Yumei Wang | Xianmou Guo | Kaijun Gou | Jing Li | Sanming Li | Lin Zhao | Heran Li
Source: International Journal of Nanomedicine (article, 2020-10-01)
Field: Materials Science — Materials Chemistry

&lt;p&gt;Biomimetic Synthesis and Evaluation of Interconnected Bimodal Mesostructured MSF@Poly(Ethyleneimine)s for Improved Drug Loading and Oral Adsorption of the Poorly Water-Soluble Drug, Ibuprofen&lt;/p&gt; B-BMSF@PEI with bimodal mesoporous system and interconnected nanopores was obtained owing to the dynamic self-assembly functions of PEIs. It had superiority in drug loading and could improve the oral adsorption of ibuprofen to a satisfactory level. Materials science ; Wetting ; Adsorption ; Bioavailability ; Simulated body fluid ; Chemical engineering ; Dissolution ; Ibuprofen ; Drug carrier ; Desorption ; Drug delivery ; Nuclear chemistry ; Chemistry ; Nanotechnology ; Scanning electron microscope ; Organic chemistry ; Pharmacology ; Composite material Mesoporous Materials and Catalysis ; Advanced Drug Delivery Systems ; Polymer Surface Interaction Studies
Authors: Andrey Tarasov | Alexander Klyushin | Matthias Friedrich | Frank Girgsdies | Robert Schlögl | Elias Frei
Source: Applied Catalysis A General (article, 2020-02-10)
Field: Materials Science — Materials Chemistry

Oxygen diffusion in Cu-based catalysts: A probe for metal support interactions Catalysis ; Diffusion ; Metal ; Oxygen ; Oxide ; Copper ; Chemistry ; Inorganic chemistry ; Redox ; Materials science ; Physical chemistry ; Analytical Chemistry (journal) ; Thermodynamics ; Metallurgy Catalytic Processes in Materials Science ; Catalysts for Methane Reforming ; Catalysis and Hydrodesulfurization Studies
Authors: Boon Siong Wee | Valach Andrian Velintine | Eric Kwabena Droepenu | Suk Fun Chin | Ying Kuan
Source: Biointerface Research in Applied Chemistry (article, 2020-12-10)
Field: Materials Science — Materials Chemistry

Effects of Humic Acid and Natural Sunlight Irradiation on the Behaviour of Zinc Oxide Nanoparticles in the Aqueous Environment The unique properties of ZnO nanoparticles have attracted scientists’ interest to produce on a large-scale. Household items, cosmetics, consumer products, and electric sensors are some products that utilize these ZnO nanomaterials. Eventually, ZnO nanoparticles will be released into the environment in various ways. Once released, ZnO nanoparticles would dissociate into Zn2+ ions, which are toxic to aquatic organisms. The presence of humic acid and exposure to sunlight could affect the dissolution of ZnO nanoparticles. Two sizes of commercial ZnO nanoparticles (&lt; 50 nm and &lt; 100 nm) were chosen to study the influence of humic acid and sunlight on the dissolution. In the presence of humic acid, the dissolution of both sizes is higher, with 67 % and 39 % Zn2+ dissolved for &lt; 50 nm and &lt; 100 nm, respectively. The concentration of Zn2+ ions seems to be consistent or stable when exposed to sunlight. However, the humic acid enhanced the release of Zn2+ ions. Langmuir isotherm model best fitted for the humic acid's sorption onto the ZnO nanoparticles with the process been favorable. Humic acid ; Dissolution ; Nanoparticle ; Aqueous solution ; Zinc ; Chemistry ; Sorption ; Nanomaterials ; Nuclear chemistry ; Environmental chemistry ; Adsorption ; Chemical engineering ; Inorganic chemistry ; Materials science ; Nanotechnology ; Organic chemistry Nanoparticles: synthesis and applications ; Mercury impact and mitigation studies ; Microplastics and Plastic Pollution
Authors: Armel Boutchuen | Dell Zimmerman | Abdollah Arabshahi | John M. Melnyczuk | Soubantika Palchoudhury
Source: Beilstein Journal of Nanotechnology (article, 2020-02-06)
Field: Materials Science — Biomaterials

Understanding nanoparticle flow with a new in vitro experimental and computational approach using hydrogel channels Nanoparticles (NPs) are considered as one of the most promising drug delivery vehicles and a next-generation solution for current medical challenges. In this context, variables related to flow of NPs such as the quantity of NPs lost during transport and flow trajectory greatly affect the clinical efficiency of NP drug delivery systems. Currently, there is little knowledge of the physical mechanisms dominating NP flow inside the human body due to the limitations of available experimental tools for mimicking complex physiological environments at the preclinical stage. Here, we report a coupled experimental and computational fluid dynamics (CFD)-based novel in vitro approach to predict the flow velocity and binding of NP drug delivery systems during transport through vasculature. Poly(hydroxyethyl)methacrylate hydrogels were used to form soft cylindrical constructs mimicking vascular sections as flow channels for synthesized iron oxide NPs in these first-of-its-kind transport experiments. Brownian dynamics and material of the flow channels played key roles in NP flow, based on the measurements of NP flow velocity over seven different mass concentrations. A fully developed laminar flow of the NPs under these conditions was simultaneously predicted using CFD. Results from the mass loss of NPs during flow indicated a diffusion-dominated flow at higher particle concentrations but a flow controlled by the surrounding fluid and Brownian dynamics at the lowest NP concentrations. The CFD model predicted a mass loss of 1.341% and 6.253% for the 4.12 g·mL<sup>-1</sup> and 2.008 g·mL<sup>-1</sup> inlet mass concentrations of the NPs, in close confirmation with the experimental results. This further highlights the reliability of our new in vitro technique in providing mechanistic insights of NP flow for potential preclinical stage applications. Laminar flow ; Computational fluid dynamics ; Context (archaeology) ; Flow (mathematics) ; Materials science ; Drug delivery ; Flow conditions ; Mechanics ; Nanoparticle ; Brownian dynamics ; Fluid dynamics ; Flow velocity ; Nanotechnology ; Brownian motion ; Biomedical engineering ; Chemistry ; Physics ; Engineering Nanoparticle-Based Drug Delivery ; Electrohydrodynamics and Fluid Dynamics ; Microfluidic and Bio-sensing Technologies
Authors: Shahanaz Parvin | Al Mamun | Md. Fazle Rubbi | Md. Abdur Ruman | Md. Moshiur Rahman | Biplob Kumar Biswas
Source: Aceh International Journal of Science and Technology (article, 2020-09-07)
Field: Chemistry — Analytical Chemistry

Utilization of Egg-shell, a Locally Available Biowaste Material, for Adsorptive Removal of Congo Red from Aqueous Solution Egg-shell, a locally obtainable biowaste material, was successfully used for common textile dye (congo red) removal from synthetic wastewater solution. All adsorptive experiments were carried out in a batch method. Experiments were conducted to understand the consequence of different functioning parameters, for example, the pH of the solution, adsorbent dosage, reaction time, and initial adsorbate concentration. The surface morphology of the egg-shell was analyzed by scanning electron microscopy (SEM) images of the adsorbent (before as well as after adsorption) showed that there was a change in surface morphology, which ensured the congo red adsorption on the adsorbent surface. The adsorbent dose was determined to be 1g as optimum value, while the solution pH 5 was seemingly the best operating pH at the tested conditions. Complete adsorption was achieved in 120 min while the pseudo-second-order kinetic model portrayed the sorption kinetics quite nicely. Langmuir adsorption model (monolayer adsorption) was the best-suited model for describing the sorption process in the concern of the correlation coefficient. The values of dimensionless separation parameters (RL) signified that the adsorption process was promising for all studied concentrations. A considerably great extent of sorption capacity (153.85 mg/g) of egg-shell adsorbent indicated that it could be employed for wastewater treatment in textile and related industries Adsorption ; Congo red ; Sorption ; Aqueous solution ; Langmuir adsorption model ; Wastewater ; Chemical engineering ; Monolayer ; Chemistry ; Materials science ; Langmuir ; Chromatography ; Nuclear chemistry ; Environmental engineering ; Organic chemistry ; Nanotechnology ; Environmental science Dye analysis and toxicity
Authors: Olivier Vitrac | Murielle Hayert
Source: SN Applied Sciences (article, 2020-08-13)
Field: Chemistry — Organic Chemistry

Modeling in food across the scales: towards a universal mass transfer simulator of small molecules in food Abstract Multiscale modeling in food is the cutting-edge strategy to revisit food structure and food composition to meet specific targets such as bioavailability, oral perception, or to evaluate the contamination of food by chemicals. A special implementation of Langevin dynamics is proposed to describe mass transfer in structured food. The concepts of random walks over discrete times and physicochemical interactions are connected via an exact solution of the Fokker–Planck equation across interfaces. The methodology is illustrated on the calculation of effective diffusivities of small solutes in emulsions in relationship with their polydispersity, the volume fraction of dispersed phase d = [0.1, 0.4], the ratio of diffusion coefficients between the two phases, r D = [10 −2 , 10 2 ], and the partition coefficients between the continuous and disperse phases, K = [10 −2 , + ∞[. Simulated diffusion paths are detailed in 2D emulsions and the effective diffusivities compared with the core–shell model of Kalnin and Kotomin (J Phys A Math Gen 31(35):7227–7234, 1998). The same effects are finally tabulated for 3D emulsions covering the full range of food applications. The methodology is comprehensive enough to enable various extensions such as chemisorption, adsorption in the surfactant layer, local flows, flocculation/creaming. Mass transfer ; Statistical physics ; Diffusion ; Chemistry ; Chemical physics ; Biological system ; Thermodynamics ; Materials science ; Physics Surfactants and Colloidal Systems ; Material Dynamics and Properties ; Coagulation and Flocculation Studies