jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Anatolievich Vladimir | Ж. В. Смагина | A. F. Zinovieva | А. В. Двуреченский | Aleksandr Mudryi
Source: International Forum “Microelectronics – 2020”. Joung Scientists Scholarship “Microelectronics – 2020”. XIII International conference «Silicon – 2020». XII young scientists scholarship for silicon nanostructures and devices physics, material science, process and analysis (article, 2020-09-09)
Field: Materials Science — Materials Chemistry

LIGHT EMMITTING RECOMBINATION IN HETEROSTRUCTURES GE/SI WITH QUANTUM DOTS FORMED WITH USING ION BEAM RADIATION This work devotes to a comparative study of the photoluminescence of Ge/Si epitaxial structures with quantum dots created with using ion beam irradiation and structures with Ge nanoclusters formed as a result of the implantation of Ge ions into silicon and subsequent annealing. Nanoclusters ; Quantum dot ; Photoluminescence ; Optoelectronics ; Materials science ; Heterojunction ; Annealing (glass) ; Silicon ; Irradiation ; Ion ; Ion beam ; Ion implantation ; Germanium ; Radiation ; Nanotechnology ; Optics ; Chemistry ; Physics Silicon Nanostructures and Photoluminescence ; Ion-surface interactions and analysis ; Quantum Dots Synthesis And Properties
Authors: Natalia А. Poluektova | Daria Lizunkova
Source: International Forum “Microelectronics – 2020”. Joung Scientists Scholarship “Microelectronics – 2020”. XIII International conference «Silicon – 2020». XII young scientists scholarship for silicon nanostructures and devices physics, material science, process and analysis (article, 2020-09-09)
Field: Materials Science — Materials Chemistry

INFLUENCE OF TECHNOLOGICAL PARAMETERS ON THE PROPERTIES OF PHOTOSENSITIVE STRUCTURES WITH NANOCRYSTALLINE SILICON In this work, the influence of technological parameters on the current-voltage characteristics of solar cells with nanostructured silicon was studied. It is shown, that for structures with a developed surface, the selection of optimal diffusion regimes is required. Silicon ; Nanocrystalline material ; Materials science ; Diffusion ; Optoelectronics ; Nanocrystalline silicon ; Voltage ; Work (physics) ; Engineering physics ; Current (fluid) ; Nanotechnology ; Electronic engineering ; Crystalline silicon ; Electrical engineering ; Mechanical engineering ; Thermodynamics ; Engineering Silicon Nanostructures and Photoluminescence ; Laser-Ablation Synthesis of Nanoparticles ; Silicon and Solar Cell Technologies
Authors: FGBOU VO " | A. S. Lenshin | , Voronezh | Konstantin A. Barkov | Natalya G. Skopintseva | D. V. Minakov | П. В. Середин
Source: International Forum “Microelectronics – 2020”. Joung Scientists Scholarship “Microelectronics – 2020”. XIII International conference «Silicon – 2020». XII young scientists scholarship for silicon nanostructures and devices physics, material science, process and analysis (article, 2020-09-09)
Field: Materials Science — Materials Chemistry

FEATURES OF FORMATION AND FUNCTIONAL CHARACTERISTICS OF MULTILAYER SYSTEMS BASED ON POROUS SILICON In this work, the features of the phase composition and chemical bonds of the surface of multilayer porous silicon samples grown under different conditions were investigated by methods of optical and X-ray spectroscopy. Porous silicon ; Silicon ; Materials science ; Porosity ; Porous medium ; Chemical engineering ; Phase (matter) ; Chemical composition ; Work (physics) ; Spectroscopy ; Optoelectronics ; Composite material ; Chemistry ; Thermodynamics ; Organic chemistry Silicon Nanostructures and Photoluminescence ; Laser-Ablation Synthesis of Nanoparticles ; Nanowire Synthesis and Applications
Authors: А. В. Наумов | Natalya Smirnova | V. I. Startsev
Source: International Forum “Microelectronics – 2020”. Joung Scientists Scholarship “Microelectronics – 2020”. XIII International conference «Silicon – 2020». XII young scientists scholarship for silicon nanostructures and devices physics, material science, process and analysis (article, 2020-09-09)
Field: Materials Science — Materials Chemistry

DISTRIBUTION OF VACANCY CLUSTERS IN CZ-GE MONOCRYSTALS DIAM 200 MM GROWN WITH ADDITIONAL HEATER The distribution of vacancy clusters in large-diameter Ge CZ single crystals under various growing conditions has been investigated. Materials science ; Vacancy defect ; Distribution (mathematics) ; Condensed matter physics ; Physics ; Mathematics Silicon Nanostructures and Photoluminescence ; Chalcogenide Semiconductor Thin Films ; Semiconductor Quantum Structures and Devices
Authors: Ksenia Milanina | А. Н. Агафонов
Source: International Forum “Microelectronics – 2020”. Joung Scientists Scholarship “Microelectronics – 2020”. XIII International conference «Silicon – 2020». XII young scientists scholarship for silicon nanostructures and devices physics, material science, process and analysis (article, 2020-09-09)
Field: Chemistry — Spectroscopy

PLANAR GAS CHROMATOGRAPHIC COLUMNS MANUFACTURED ON SILICONE SUBSTRATES This paper presents the main stages in the development of technology for the manufacture of planar gas chromatographic columns. Planar ; Silicone ; Chromatography ; Materials science ; Gas chromatography ; Computer science ; Chemistry ; Composite material Analytical Chemistry and Chromatography ; Microfluidic and Capillary Electrophoresis Applications ; Innovative Microfluidic and Catalytic Techniques Innovation
Authors: O. V. Kononenko | А. В. Зотов | V. N. Matveev
Source: International Forum “Microelectronics – 2020”. Joung Scientists Scholarship “Microelectronics – 2020”. XIII International conference «Silicon – 2020». XII young scientists scholarship for silicon nanostructures and devices physics, material science, process and analysis (article, 2020-09-09)
Field: Materials Science — Materials Chemistry

TURBOSTRATIC MULTILAYER GRAPHENE – PROSPECTS FOR USE AS MAGNETIC FIELD SENSORS AND PHOTODETECTORS The transport properties, magnetoresistance, and photoresponse are investigated in turbostratic multilayer graphene films grown by chemical vapor deposition. Photodetector ; Graphene ; Materials science ; Optoelectronics ; Magnetic field ; Field (mathematics) ; Engineering physics ; Nanotechnology ; Physics Graphene research and applications ; Supercapacitor Materials and Fabrication ; Molecular Junctions and Nanostructures
Authors: V. M. Dolgopolov | Pavel Irakin | В. O. Varakin
Source: International Forum “Microelectronics – 2020”. Joung Scientists Scholarship “Microelectronics – 2020”. XIII International conference «Silicon – 2020». XII young scientists scholarship for silicon nanostructures and devices physics, material science, process and analysis (article, 2020-09-09)
Field: Materials Science — Materials Chemistry

ADVANCED PROCESS OF DEEP ANISOTROPIC ETCHING OF SILICON WITH A HIGH ASPECT RATIO FOR THE FORMATION OF TSV STRUCTURES The aim of this work was to improve the existing technology of deep anisotropic etching of silicon for its application in the manufacture of three-dimensional TSV structures, namely, to increase the selectivity to the mask and reduce the surface roughness. Materials science ; Etching (microfabrication) ; Silicon ; Through-silicon via ; Aspect ratio (aeronautics) ; Surface roughness ; Anisotropy ; Surface finish ; Deep reactive-ion etching ; Optoelectronics ; Process (computing) ; Nanotechnology ; Reactive-ion etching ; Composite material ; Optics ; Computer science ; Layer (electronics) Silicon Nanostructures and Photoluminescence ; Nanowire Synthesis and Applications ; Advanced Surface Polishing Techniques
Authors: Samuel Tovey | Anand Narayanan Krishnamoorthy | Ganesh Sivaraman | Jicheng Guo | Chris J. Benmore | Andreas Heuer | Christian Holm
Source: ChemRxiv (preprint, 2020-05-22)
Field: Materials Science — Materials Chemistry

DFT Accurate Interatomic Potential for Molten NaCl from Machine Learning Molten alkali chloride salts are a critical component in concentrated solar power and nuclear applications. Despite their ubiquity, the extreme chemical reactivity of molten alkali chlorides at high temperatures has presented a significant challenge in characterizing atomic structures and dynamic properties experimentally. Here we investigate molten NaCl by performing high temperature molecular dynamics simulations using a Gaussian Approximation Potential (GAP) trained on Density Functional Theory (DFT) datasets. Our GAP model, trained with a meager 1000 atomic configurations, arrives at near DFT accuracy with a mean absolute error of 1.5 meV/atom, thus enabling fast analysis of high temperature salt properties on large length (5000 ion pairs) and time (> 1ns) scales, currently inaccessible to ab initio simulations. Calculated structure factors and diffusion constants from our GAP model simulations show excellent agreement with experiments. Our results indicate that GAP models are able to capture the many-body interactions required to accurately model ionic-systems. Molecular dynamics ; Density functional theory ; Alkali metal ; Molten salt ; Atom (system on chip) ; Diffusion ; Ion ; Chemistry ; Interatomic potential ; Chemical physics ; Ab initio ; Ionic bonding ; Thermodynamics ; Atomic physics ; Materials science ; Computational chemistry ; Physics ; Computer science ; Inorganic chemistry Machine Learning in Materials Science
Authors: Xinping Zhang | Fawei Tang | Meng Wang | Wangbin Zhan | Huaxin Hu | Yurong Li | Richard H. Friend | Xiaoyan Song
Source: Apollo (University of Cambridge) (article, 2020-03-01)
Field: Materials Science — Polymers and Plastics

Femtosecond visualization of oxygen vacancies in metal oxides. Oxygen vacancies often determine the electronic structure of metal oxides, but existing techniques cannot distinguish the oxygen-vacancy sites in the crystal structure. We report here that time-resolved optical spectroscopy can solve this challenge and determine the spatial locations of oxygen vacancies. Using tungsten oxides as examples, we identified the true oxygen-vacancy sites in WO2.9 and WO2.72, typical derivatives of WO3 and determined their fingerprint optoelectronic features. We find that a metastable band with a three-stage evolution dynamics of the excited states is present in WO2.9 but is absent in WO2.72. By comparison with model bandstructure calculations, this enables determination of the most closely neighbored oxygen-vacancy pairs in the crystal structure of WO2.72, for which two oxygen vacancies are ortho-positioned to a single W atom as a sole configuration among all O─W bonds. These findings verify the existence of preference rules of oxygen vacancies in metal oxides. Oxygen ; Metastability ; Vacancy defect ; Materials science ; Metal ; Chemical physics ; Spectroscopy ; Crystal structure ; Crystal (programming language) ; Single crystal ; Femtosecond ; Crystallography ; Oxygen atom ; Tungsten ; Chemistry ; Physics ; Molecule ; Optics ; Laser ; Metallurgy ; Computer science Transition Metal Oxide Nanomaterials
Authors: Reza Maleki | Mohammad Dahri | Ebrahim Ghasemy | Hossein Akbarialiabad
Source: Research Square (Research Square) (preprint, 2020-10-22)
Field: Materials Science — Biomaterials

A Mechanistic Insight into Doxorubicin Adsorption on N-isopropyl Acrylamide Grafted Nanotube: Optimization Study of Loading Temperature Abstract Background : The drug development process is costly and time-consuming; hence, nowadays, enormous efforts have been established through computational studies for finding appropriate strategies, methods and solutions for enhancing the drug production and administration procedures. Hydrogels that undertake deformation upon pertinent changes in temperature have significant aptitude as drug delivery systems. These biomaterials have made a substantial impact on the development of drugs for critical diseases, especially cancer therapy. Drug loading and uptake are primary and fundamental steps of the drug development and discovery process. N-isopropyl acrylamide is a common and well-known thermo-sensitive and injectable hydrogel for the drug uptake under the lower critical solution temperature (LCST). In the current study, carbon nanotube (CNT) as a nanocarrier was modified via N-isopropyl acrylamide. On the other hand, Doxorubicin as an anti-cancer drug applied on mentionted systems to develop drug packing at three different temperatures. Results: After computational parametrization of the system via bioinformatics software and databases, Molecular dynamics (MD) simulation was run. To this end, the detailed simulations were carried out to reveal the interaction energy, numbers of hydrogen bonds, the gyration radius, mean square displacement, and radial distribution function as well as Gibss free energy. Besides, the optimal loading temperature for doxorubicin was determined. The results achieved from simulating the polymer demonstrated a decrease in the gyration radius at a higher temperature. A decrease of gyration radius resulted in more concentrated aggregation with stronger bonds. Conclusions: Therefore, at the higher temperature, the more stable polymer interaction and better doxorubicin loading were acquired. The smart absorption of doxorubicin onto the CNT modified via N-iso-propyl acrylamide (NIPA) give a significant and valuable view on the future studies regarding the drug development and novel, biocompatible, and biodegradable stimuli-sensitive drug delivery system. Lower critical solution temperature ; Radius of gyration ; Materials science ; Nanocarriers ; Polymer ; Molecular dynamics ; Carbon nanotube ; Drug delivery ; Nanotechnology ; Chemical engineering ; Computational chemistry ; Thermodynamics ; Chemistry ; Chemical physics ; Composite material Electrospun Nanofibers in Biomedical Applications ; Graphene and Nanomaterials Applications ; Hydrogels: synthesis, properties, applications
Authors: Yan Guo
Source: Research Repository (Delft University of Technology) (article, 2020-05-15)
Field: Materials Science — Surfaces, Coatings and Films

Image quality assessment and image fusion for electron tomography Electron tomography is a powerful tool in materials science to characterize nanostructures in three dimensions (3D). In scanning transmission electron microscopy (STEM), the sample under study is exposed to a focused electron beam and tilted to obtain twodimensional (2D) projections at different angles; many imaging modes are available such as high-angle annular dark-field (HAADF). In tomography, the collection of projections is called a tilt-series, from which we can reconstruct a 3D image that represents the sample. While HAADF tomography can clearly reveal the inner structure of the sample, it cannot directly provide compositional information. To better understand nanomaterials with more types of elements, spectral imaging techniques like energy dispersive X-ray spectroscopy (EDS) must be pursued. EDS tomography, however, is currently hampered by slow data acquisition, resulting in a small number of elemental maps with low signalto- noise ratio (SNR). Electron tomography, especially EDS tomography, is an ill-posed inverse problem whose solution is not stable and unique. Although advanced reconstruction techniques may yield a more accurate result by incorporating prior knowledge, they also involve fine-tuning parameters that highly influence the reconstruction quality. Furthermore, while great efforts have been dedicated to developing tomography techniques for image enhancement, directly combining reconstruction volumes at hand has still not been widely considered to the best of our knowledge. Electron tomography ; Tomography ; Iterative reconstruction ; Sample (material) ; Optics ; Image quality ; Scanning transmission electron microscopy ; Image fusion ; Tilt (camera) ; Computer vision ; Computer science ; Artificial intelligence ; Materials science ; Physics ; Image (mathematics) ; Transmission electron microscopy ; Mathematics ; Geometry Electron and X-Ray Spectroscopy Techniques ; Advanced Electron Microscopy Techniques and Applications ; Advancements in Photolithography Techniques
Authors: Alexey V. Gulyuk
Source: NCSU Libraries Repository (North Carolina State University Libraries) (article, 2020-10-28)
Field: Chemistry — Organic Chemistry

Properties of Gallium Nitride-Microorganism Interfaces. GYLYUK, ALEXEY.Properties of Gallium Nitride-Microorganism Interfaces.(Under the direction of Dr. Albena Ivanisevic).A wide portfolio of advanced programmable materials and structures has been developed for biological applications in the last two decades.In particular, due to their unique properties, semiconducting materials have been utilized in areas of biocomputing, implantable electronics, and healthcare.As a new concept of such programmable material design, biointerfaces based on inorganic semiconducting materials as substrates introduce unconventional paths for bioinformatics and biosensing.In particular, understanding how the properties of a substrate can alter microbial biofilm behavior enables researchers to better characterize and thus create programmable biointerfaces with necessary characteristics on-demand.During the preliminary research stage, the most promising semiconductor material types along with target microorganisms were identified and subsequently utilized for further studies.Gallium-based surfaces (particularly, GaN with different doping levels) were chosen as the most promising semiconducting materials to be used in inorganic substrate-microorganism biointerfaces.The work was based on the hypothesis that they can be tailored to induce controllable microorganism behavior under specific user defined external conditions.At this stage of the work Pseudomonas aeruginosa was the test organism in the first two experimental parts of the dissertation work.As a the typical in-hospital infection, P.aeruginosa possesses high survivability and enhanced abilities to form resilient biofilms on various surfaces.These factors allowed us to perform a set of studies that enable to create GaN-P.aeruginosabiointerfaces, characterize them and identify factors triggering the morphological and physiological reactions of formulated structures. Gallium nitride ; Microorganism ; Materials science ; Nanotechnology ; Bacteria ; Biology ; Genetics ; Layer (electronics) Fullerene Chemistry and Applications
Authors: Yu Ding | Yu Kumagai | Fumiyasu Oba | Lee A. Burton
Source: arXiv (Cornell University) (preprint, 2020-07-04)
Field: Materials Science — Materials Chemistry

Data-Mining Element Charges in Inorganic Materials Oxidation states are well-established in chemical science teaching and research. We data-mine more than 168,000 crystallographic reports to find an optimal allocation of oxidation states to each element. In doing so we uncover discrepancies between text-book chemistry and reported charge states observed in materials. We go on to show how the oxidation states we recommend can significantly facilitate materials discovery and heuristic design of novel inorganic compounds. Element (criminal law) ; Heuristic ; Heavy element ; Charge (physics) ; Computer science ; Chemistry ; Nanotechnology ; Materials science ; Physics ; Political science ; Artificial intelligence ; Quantum mechanics Machine Learning in Materials Science ; Electronic and Structural Properties of Oxides ; Advanced Photocatalysis Techniques
Authors: Stephen Lam | Qingjie Li | Jonathan P. Mailoa | Charles Forsberg | R. G. Ballinger | Ju Li
Source: ChemRxiv (preprint, 2020-11-02)
Field: Chemistry — Inorganic Chemistry

The Impact of Hydrogen Valence on Its Bonding and Transport in Molten Fluoride Salts Interest in molten salts has increased significantly over the last decade due to their potential application in various clean-energy technologies including hydrogen generation, solar heat storage, and advanced nuclear power plants. In the development of new molten salt-based fission and fusion systems, controlling hydrogen poses a critical challenge due to its ability to corrode structural materials as 3H+, and its potential to cause significant radioactive release as diffusive 3H0. Yet, the chemistry and transport behavior of the hydrogen species remain poorly understood despite several decades of research. Using ab initio molecular dynamics, we present a coupled examination of hydrogen valence, speciation and transport in the prototypical salts 66.6%LiF-33.3¾F2 (Flibe) and 46.5%LiF-11.5%NaF-42%KF (Flinak). We discovered significant differences between 3H0 and 3H+transport behaviors. 3H+ diffuses 2-4 times slower than 3H0, which can be ascribed to hydrogen bonding and complexation in solution. This work helps explain varying experimental results and provides useful species transport data for designing hydrogen control systems for molten salts. Hydrogen ; Molten salt ; Chemistry ; Valence (chemistry) ; Chemical physics ; Hydrogen storage ; Inorganic chemistry ; Organic chemistry Inorganic Fluorides and Related Compounds ; Molten salt chemistry and electrochemical processes ; Ammonia Synthesis and Nitrogen Reduction
Authors: zheng cheng | Dongbo Zhao | Jing Ma | Wei Li | Shuhua Li
Source: ChemRxiv (preprint, 2020-05-18)
Field: Materials Science — Materials Chemistry

An On-the-fly Approach to Construct Generalized Energy-Based Fragmentation Machine Learning Force Fields of Complex Systems The paper describes a modification to the generalized energy-based fragmentation (GEBF) method that uses a machine fitted potential energy surface for the subsytems instead of ab initio calculation, in order to speed up the calculations. An on-the-fly active learning is used to construct vaious kind of subsystems force field automatically. Our method can bpyss over 99% of the QM calculations during the ab inito molecular dynamics. Fragmentation (computing) ; Force field (fiction) ; Construct (python library) ; On the fly ; Computer science ; Ab initio ; Field (mathematics) ; Energy (signal processing) ; Statistical physics ; Classical mechanics ; Physics ; Artificial intelligence ; Mathematics ; Quantum mechanics ; Pure mathematics Machine Learning in Materials Science ; Quantum Computing Algorithms and Architecture ; Electronic and Structural Properties of Oxides
Authors: Zachary D. McClure | Alejandro Strachan
Source: arXiv (Cornell University) (preprint, 2020-07-20)
Field: Materials Science — Materials Chemistry

Expanding materials selection via transfer learning for high-temperature\n oxide selection Materials with higher operating temperatures than today's state of the art\ncan improve system performance in several applications and enable new\ntechnologies. Under most scenarios, a protective oxide scale with high melting\ntemperatures and thermodynamic stability as well as low ionic diffusivity is\nrequired. Thus, the design of high-temperature systems would benefit from\nknowledge of these properties and related ones for all known oxides. While some\nproperties of interest are known for many oxides (e.g. elastic constants exist\nfor over 1,000 oxides), melting temperature is known for a relatively small\nsubset. The determination of melting temperatures is time consuming and costly,\nboth experimentally and computationally, thus we use data science tools to\ndevelop predictive models from the existing data. The relatively small number\nof available melting temperature values precludes the use of standard tools;\ntherefore, we use a multi-step approach based on sequential learning where\nsurrogate data from first-principles calculations is leveraged to develop\nmodels using small datasets. We use these models to predict the desired\nproperties for nearly 11,000 oxides and quantify uncertainties in the space.\n Oxide ; Computer science ; Stability (learning theory) ; Scale (ratio) ; Melting temperature ; Thermal diffusivity ; Materials science ; Selection (genetic algorithm) ; Melting point ; Thermodynamics ; Machine learning ; Physics Machine Learning in Materials Science ; Metallurgical Processes and Thermodynamics ; Crystallization and Solubility Studies